Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov 
Author-X-Name-First: Dmitry 
Author-X-Name-Last: Ivanov 
Author-Name: Richard Hartl 
Author-X-Name-First: Richard 
Author-X-Name-Last: Hartl 
Author-Name: Alexandre Dolgui 
Author-X-Name-First: Alexandre 
Author-X-Name-Last: Dolgui 
Author-Name: Alexander Pavlov 
Author-X-Name-First: Alexander 
Author-X-Name-Last: Pavlov 
Author-Name: Boris Sokolov 
Author-X-Name-First: Boris 
Author-X-Name-Last: Sokolov 
Title: Integration of aggregate distribution and dynamic transportation planning in a supply chain with capacity disruptions and the ripple effect consideration 
Abstract:
 We study the dynamic planning decisions of a logistics service provider
 that is in charge of the integrated supply chain (SC) planning. We examine
 an SC with multiple products, suppliers, transit nodes and customers in a
 multi-period mode. The logistics service provider is responsible for
 aggregate distribution planning and operative dynamic transportation
 planning. It is to decide on aggregate distribution flows as well as on
 the time-dependent intensities (i.e. transportation batches). These
 decisions are tightly incorporated but previous research considered them
 mostly isolated. This is quite natural since these problems contain data
 of different detail degree, which can be hardly incorporated in only one
 model. To resolve this problem, we present a hybrid multi-period,
 multi-commodity distribution--transportation model as an optimal control
 problem blended with mathematical programming. This contribution has some
 particular features. First, it extends previous research by elaborating on
 the dynamic optimal control model. Second, it considers multi-period
 problem statement with multiple products and alternative transportation
 channels. Third, we represent the integrated dynamic SC planning in order
 to take into account the ripple effect. With the results of this study,
 the dynamic issues in integrated logistics planning in the SC can be
 addressed, and an intelligent solution to an important problem of SC
 management has been proposed.
Journal: International Journal of Production Research 
Pages: 6963-6979 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2014.986303 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986303 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianhui Mou 
Author-X-Name-First: Jianhui 
Author-X-Name-Last: Mou 
Author-Name: Liang Gao 
Author-X-Name-First: Liang 
Author-X-Name-Last: Gao 
Author-Name: Xinyu Li 
Author-X-Name-First: Xinyu 
Author-X-Name-Last: Li 
Author-Name: Chao Lu 
Author-X-Name-First: Chao 
Author-X-Name-Last: Lu 
Author-Name: Hongjie Hu 
Author-X-Name-First: Hongjie 
Author-X-Name-Last: Hu 
Title: Optimisation of the reverse scheduling problem by a modified genetic algorithm 
Abstract:
 Traditional scheduling methods can only arrange the operations on
 corresponding machines with appropriate sequences under pre-defined
 environments. This means that traditional scheduling methods require that
 all parameters to be determined before scheduling. However, real
 manufacturing systems often encounter many uncertain events. These will
 change the status of manufacturing systems. These may cause the original
 schedule to no longer be optimal or even to be infeasible. Traditional
 scheduling methods, however, cannot cope with these cases. New scheduling
 methods are needed. Among these new methods, one method &#x2018;reverse
 scheduling&#x2019; has attracted more and more attentions. This paper
 focuses on the single-machine reverse scheduling problem and designs a
 modified genetic algorithm with a local search (MLGA) to solve it. To
 improve the performance of MLGA, efficient encoding, offspring update
 mechanism and a local search have been employed and developed. To verify
 the feasibility and effectiveness of the proposed MLGA, 27 instances have
 been conducted and results have been compared with existing methods. The
 results show that the MLGA has achieved satisfactory improvement. This
 approach also has been applied to solve a real-world scheduling problem
 from one shipbuilding industry. The results show that the MLGA can bring
 some benefits.
Journal: International Journal of Production Research 
Pages: 6980-6993 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2014.988890 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988890 
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Template-Type: ReDIF-Article 1.0
Author-Name: Vittaldas V. Prabhu 
Author-X-Name-First: Vittaldas V. 
Author-X-Name-Last: Prabhu 
Author-Name: Damien Trentesaux 
Author-X-Name-First: Damien 
Author-X-Name-Last: Trentesaux 
Author-Name: Marco Taisch 
Author-X-Name-First: Marco 
Author-X-Name-Last: Taisch 
Title: Energy-aware manufacturing operations 
Abstract:
 This editorial introduces the special issue on energy-aware manufacturing
 operations in the International Journal of Production Research. The 12
 papers in this special issue were selected because of their high quality
 and also because they deal with topics related to energy-aware
 manufacturing operations. Three broad challenges are collectively
 addressed by the papers in this special issue: energy-efficiency vs.
 manufacturing-system effectiveness in optimisation; the volatility in
 energy availability, supply and cost; modelling energy consumption in
 varying scales and across different sub-systems. Previous global
 discussions about the state of the art in energy-aware manufacturing
 operations are provided, as well as exploratory guidelines for future
 research in this area.
Journal: International Journal of Production Research 
Pages: 6994-7004 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1100766 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1100766 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xin Xu 
Author-X-Name-First: Xin 
Author-X-Name-Last: Xu 
Author-Name: Simon Meteyer 
Author-X-Name-First: Simon 
Author-X-Name-Last: Meteyer 
Author-Name: Nicolas Perry 
Author-X-Name-First: Nicolas 
Author-X-Name-Last: Perry 
Author-Name: Yaoyao Fiona Zhao 
Author-X-Name-First: Yaoyao Fiona 
Author-X-Name-Last: Zhao 
Title: Energy consumption model of Binder-jetting additive manufacturing processes 
Abstract:
 Considering the potential for new product design possibilities and the
 reduction of environmental impacts, Additive Manufacturing (AM) processes
 are considered to possess significant advantages for automotive, aerospace
 and medical equipment industries. One of the commercial AM techniques is
 Binder-jetting (BJ). This technique can be used to process a variety of
 materials including stainless steel, ceramic, polymer and glass. However,
 there is very limited research about this AM technology on energy
 consumption aspect. This paper presents a method to build an energy
 consumption model for printing stage of BJ process. Mathematical analyses
 are performed to find out the correlation between the energy consumption
 and geometry of the manufactured part. Based on the analyses, total energy
 consumption is calculated as a function of part geometry and printing
 parameters. Finally, test printing is performed to check the accuracy of
 the model. This process model provides a tool to optimise part geometry
 design with respect to energy consumption.
Journal: International Journal of Production Research 
Pages: 7005-7015 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2014.937013 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.937013 
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Template-Type: ReDIF-Article 1.0
Author-Name: Luoke Hu 
Author-X-Name-First: Luoke 
Author-X-Name-Last: Hu 
Author-Name: Renzhong Tang 
Author-X-Name-First: Renzhong 
Author-X-Name-Last: Tang 
Author-Name: Keyan He 
Author-X-Name-First: Keyan 
Author-X-Name-Last: He 
Author-Name: Shun Jia 
Author-X-Name-First: Shun 
Author-X-Name-Last: Jia 
Title: Estimating machining-related energy consumption of parts at the design phase based on feature technology 
Abstract:
 To overcome the difficulties in previous researches about energy-efficient
 design of parts, a method to estimate machining-related energy consumption
 of parts at the design phase is proposed. The binary tree is constructed
 to describe the structure of a part, and each node in the binary tree
 represents one feature in the part. The material embodied energy,
 theoretical cutting energy consumption and air-cutting energy consumption
 of a feature can be calculated based on its design and manufacturing
 parameters. At the design phase, manufacturing parameters of a feature can
 be obtained by the method of feature mapping from design parameters. By
 adding up above three types of energy consumption, total energy
 consumption of a feature can be calculated. Further, by adding up total
 energy consumption of all features in a part, the energy consumption of
 this part can be estimated. The proposed method was demonstrated by
 estimating the energy consumption of a shaft part designed by an auto
 parts manufacturer, and meanwhile the measured energy consumption of the
 shaft part was acquired by experimental measurement. The estimation
 accuracy is analysed and verified by comparing the estimated value and
 measured value.
Journal: International Journal of Production Research 
Pages: 7016-7033 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12  
X-DOI: 10.1080/00207543.2014.944281 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.944281 
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Template-Type: ReDIF-Article 1.0
Author-Name: Victor Santana-Viera 
Author-X-Name-First: Victor 
Author-X-Name-Last: Santana-Viera 
Author-Name: Jesus Jimenez 
Author-X-Name-First: Jesus 
Author-X-Name-Last: Jimenez 
Author-Name: Tongdan Jin 
Author-X-Name-First: Tongdan 
Author-X-Name-Last: Jin 
Author-Name: Jose Espiritu 
Author-X-Name-First: Jose 
Author-X-Name-Last: Espiritu 
Title: Implementing factory demand response via onsite renewable energy: a design-of-experiment approach 
Abstract:
 This paper proposes the implementation of demand response (DR) programmes
 in large manufacturing facilities featuring distributed wind and solar
 energy. Manufacturing facilities are high consumers of electric power. For
 this reason, these facilities usually pay exorbitant utility bills, which
 could be as much as $10--20 million per year. A high consumption of
 electricity also means that upstream fossil-fuelled power plants must
 release thousands of metric tonnes of carbon annually during the
 generation of electricity. DR contracts offer a lower utility rate in
 return for a load reduction during contingent events (i.e. peak hours).
 This paper covers the modelling and implementation of an
 interruptible/curtailable DR programme participated by a manufacturer that
 possesses onsite renewable generation units. These complementary energy
 resources allow the manufacturer to meet the curtailment requirements
 without causing any major electricity shortage that adversely affects the
 normal production schedule. We developed a stochastic programming model to
 determine the capacity of the wind turbine and solar panels that maximise
 the DR programme savings. The optimal solutions are derived based on
 central composite design methodology.
Journal: International Journal of Production Research 
Pages: 7034-7048 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2014.957877 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.957877 
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Template-Type: ReDIF-Article 1.0
Author-Name: Hyun Woo Jeon 
Author-X-Name-First: Hyun Woo 
Author-X-Name-Last: Jeon 
Author-Name: Marco Taisch 
Author-X-Name-First: Marco 
Author-X-Name-Last: Taisch 
Author-Name: Vittaldas V. Prabhu 
Author-X-Name-First: Vittaldas V. 
Author-X-Name-Last: Prabhu 
Title: Modelling and analysis of energy footprint of manufacturing systems 
Abstract:
 Increasing the energy efficiency of manufacturing plants will reduce the
 production costs and environmental impact. In order to analyse and improve
 the energy efficiency of manufacturing plants, however, we need models to
 evaluate the energy footprints of the plants. A key challenge of
 estimating plant-level footprints is that systemic methods of connecting
 information on the product, machine and plant levels are not available.
 Thus, we propose methods to parameterise product-level elements and to
 model machine-level factors based on those elements. From the
 machine-level models, the proposed approach performs simulation
 experiments and provides the energy footprints in closed-form equations
 for the plant level. We also suggest that the resulting model can be
 combined with probabilistic techniques to benchmark the energy efficiency
 of plants at the industry level. In a case study, we demonstrate how to
 apply the proposed methods to estimate the energy footprint of a
 hypothetical plant. The procedures introduced here enable manufacturers to
 evaluate the energy consumption of their facilities at early stages of
 manufacturing, and provide tools to assess the energy efficiency of their
 plant by comparison with peers.
Journal: International Journal of Production Research 
Pages: 7049-7059 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2014.961208 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961208 
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Template-Type: ReDIF-Article 1.0
Author-Name: Bj&#xf6;rn Johansson 
Author-X-Name-First: Bj&#xf6;rn 
Author-X-Name-Last: Johansson 
Author-Name: Anders Skoogh 
Author-X-Name-First: Anders 
Author-X-Name-Last: Skoogh 
Author-Name: Jon Andersson 
Author-X-Name-First: Jon 
Author-X-Name-Last: Andersson 
Author-Name: Karin Ahlberg 
Author-X-Name-First: Karin 
Author-X-Name-Last: Ahlberg 
Author-Name: Lars Hanson 
Author-X-Name-First: Lars 
Author-X-Name-Last: Hanson 
Title: Power-level sampling of metal cutting machines for data representation in discrete event simulation 
Abstract:
 An extension to the application area for discrete event simulation (DES)
 has been ongoing since the last decade and focused only on economic
 aspects to include ecologic sustainability. With this new focus,
 additional input parameters, such as electrical power consumption of
 machines, are needed. This paper aim at investigating how NC machine power
 consumption should be represented in simulation models of factories. The
 study includes data-sets from three different factories. One factory
 producing truck engine blocks, one producing brake disc parts for cars and
 one producing forklift components. The total number of data points
 analysed are more than 2,45,000, where of over 1,11,000 on busy state for
 11 NC machines. The low variability between busy cycles indicates that
 statistical representations are not adding significant variability.
 Furthermore, results show that non-value-added activities cause a
 substantial amount of the total energy consumption, which can be reduced
 by optimising the production flow using dynamic simulations such as DES.
Journal: International Journal of Production Research 
Pages: 7060-7070 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2014.980456 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980456 
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Template-Type: ReDIF-Article 1.0
Author-Name: G&#xf6;kan May 
Author-X-Name-First: G&#xf6;kan 
Author-X-Name-Last: May 
Author-Name: Bojan Stahl 
Author-X-Name-First: Bojan 
Author-X-Name-Last: Stahl 
Author-Name: Marco Taisch 
Author-X-Name-First: Marco 
Author-X-Name-Last: Taisch 
Author-Name: Vittal Prabhu 
Author-X-Name-First: Vittal 
Author-X-Name-Last: Prabhu 
Title: Multi-objective genetic algorithm for energy-efficient job shop scheduling 
Abstract:
 The paper investigates the effects of production scheduling policies aimed
 towards improving productive and environmental performances in a job shop
 system. A green genetic algorithm allows the assessment of multi-objective
 problems related to sustainability. Two main considerations have emerged
 from the application of the algorithm. First, the algorithm is able to
 achieve a semi-optimal makespan similar to that obtained by the best of
 other methods but with a significantly lower total energy consumption.
 Second, the study demonstrated that the worthless energy consumption can
 be reduced significantly by employing complex energy-efficient machine
 behaviour policies.
Journal: International Journal of Production Research 
Pages: 7071-7089 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1005248 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005248 
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Template-Type: ReDIF-Article 1.0
Author-Name: Antonella Meneghetti 
Author-X-Name-First: Antonella 
Author-X-Name-Last: Meneghetti 
Author-Name: Eleonora Dal Borgo 
Author-X-Name-First: Eleonora 
Author-X-Name-Last: Dal Borgo 
Author-Name: Luca Monti 
Author-X-Name-First: Luca 
Author-X-Name-Last: Monti 
Title: Rack shape and energy efficient operations in automated storage and retrieval systems 
Abstract:
 Energy efficiency has become a primary goal to be pursued for sustainable
 logistics. In automated storage and retrieval systems this leads to revise
 the traditional control policies aimed at picking time minimisation and to
 pay more attention to rack configuration, which has been not a research
 concern from the time-based perspective. Proper models for energy
 calculation should be developed by introducing new factors neglected in
 time analysis, such as the weight of unit loads and the differentiation of
 shifts along the horizontal and vertical axis as regard energy
 requirements, due to different contribution of gravity, inertia and
 friction. In this study, a classification of racks based on system height
 is proposed in order to select the proper crane specifications needed to
 compute the torque to be overcome by motors to serve a given location
 within a rack. An overall optimisation model based on Constraint
 Programming hybridised with Large Neighborhood Search is developed,
 allowing the joint application of the best control policies for storage
 assignment and sequencing both for time and energy-based optimisation, as
 well as the introduction of multiple weight unit loads and energy
 recovery. Simulations analysis is performed in order to assess the impact
 of the rack shape on energy saving. Results show how, regardless the
 demand curve and the optimisation objective, the best performances in
 terms of energy efficiency are reached by the intermediate height rack
 shapes, while the lower ones outperform when considering travel time
 performance.
Journal: International Journal of Production Research 
Pages: 7090-7103 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1008107 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1008107 
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Template-Type: ReDIF-Article 1.0
Author-Name: Dileep Dhavale 
Author-X-Name-First: Dileep 
Author-X-Name-Last: Dhavale 
Author-Name: Joseph Sarkis 
Author-X-Name-First: Joseph 
Author-X-Name-Last: Sarkis 
Title: Integrating carbon market uncertainties into a sustainable manufacturing investment decision: a Bayesian NPV approach 
Abstract:
 Net present value (NPV) is a widely used technique in capital budgeting.
 In this paper, we develop a Bayesian NPV framework using a Gibbs sampler.
 This approach allows decision-makers to integrate their knowledge, past
 experience, and uncertain and volatile cash flows from carbon emissions
 credits into decisions dealing with energy efficient, sustainable
 manufacturing equipment. The results indicate NPV is highly dependent on
 the nature of volatility and uncertainty of the cash flows. Without
 inclusion of this information through the Bayesian framework results, NPV
 becomes overstated, and thus it may provide biased guidance for the
 investment. The results developed in this paper further show that the
 frequency of very high and low cash flows and to a lesser degree their
 variability adversely impacts NPV. The results may also explain reasons
 for the economic phenomenon known as the energy efficiency gap.
Journal: International Journal of Production Research 
Pages: 7104-7117 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1018450 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1018450 
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Template-Type: ReDIF-Article 1.0
Author-Name: Bar&#x131;&#x15f; Tan 
Author-X-Name-First: Bar&#x131;&#x15f; 
Author-X-Name-Last: Tan 
Author-Name: Yahya Yavuz 
Author-X-Name-First: Yahya 
Author-X-Name-Last: Yavuz 
Title: Modelling and analysis of a business model to offer energy-saving technologies as a service 
Abstract:
 In this study, we present a stochastic model to analyse a business plan
 that is based on offering energy-saving technologies as a service. In this
 arrangement, the total differential cost of replacing an existing
 technology with a more efficient one is financed from the future energy
 savings that are shared between a service provider that installs the more
 efficient technology and its customer. The model we present captures
 improvements in energy efficiencies and costs of technologies with time,
 variation in energy consumption, uncertainty in energy prices and useful
 life of a technology, and revenue from carbon offsets. By using an
 analytical model, we analyse the feasibility of this business model using
 expected cost and also value-at-risk criteria. We show that when the
 service provider selects the contract parameters in a right way, the
 business plan brings financial benefits. The customer also benefits
 financially from reduction in energy usage and replacement costs, and also
 from additional revenue obtained through selling carbon offsets.
 Furthermore, since this business plan is based on increasing energy
 efficiency, the proposed approach decreases energy consumption, and
 therefore carbon dioxide emissions. As a result, using an analytical
 model, we show that offering energy-saving technologies as a service is a
 win--win--win situation for the service provider, its customer and for the
 environment.
Journal: International Journal of Production Research 
Pages: 7118-7135 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1055343 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055343 
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Template-Type: ReDIF-Article 1.0
Author-Name: Yevgenia Mikhaylidi 
Author-X-Name-First: Yevgenia 
Author-X-Name-Last: Mikhaylidi 
Author-Name: Hussein Naseraldin 
Author-X-Name-First: Hussein 
Author-X-Name-Last: Naseraldin 
Author-Name: Liron Yedidsion 
Author-X-Name-First: Liron 
Author-X-Name-Last: Yedidsion 
Title: Operations scheduling under electricity time-varying prices 
Abstract:
 Global climate change requires stakeholders to consider energy elements in
 their decision-making. Electricity costs, in particular, constitute a
 significant portion of operational costs in most manufacturing systems.
 The electricity bills can be lowered if electricity-consuming operations
 are correctly scheduled. We consider a manufacturing operations control
 problem with known time-varying electricity prices in a finite planning
 horizon. Each operation is unique and has its own concave electricity
 consumption function. Pre-emptions of operations are allowed, yet
 postponing an operation incurs a cumulative penalty for each time period.
 In addition, each pre-emption is considered a new operation. The
 electricity cost in each time period is exogenous and there exists a
 capacity constraint on the total electricity amount consumed in each
 period due to infrastructure and provider&#x2019;s limitations. There is a
 fixed start-up cost incurred for switching on the machine and a fixed
 reservation cost incurred for keeping the machine &#x2018;On&#x2019;. The
 system also includes a rechargeable battery. The customer has to determine
 when to process each operation within the time horizon so as to minimise
 total electricity consumption and operations postponement penalty costs. A
 dynamic programming solution is proposed and the complexity of the models
 is analysed. After examining several special cases of the model, the
 optimum times to charge and discharge the rechargeable battery are
 determined. A polynomial time algorithm for a special case of a single
 operation with uniform capacity is proposed.
Journal: International Journal of Production Research 
Pages: 7136-7157 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1058981 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1058981 
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Template-Type: ReDIF-Article 1.0
Author-Name: Seokgi Lee 
Author-X-Name-First: Seokgi 
Author-X-Name-Last: Lee 
Author-Name: Vittaldas V. Prabhu 
Author-X-Name-First: Vittaldas V. 
Author-X-Name-Last: Prabhu 
Title: Energy-aware feedback control for production scheduling and capacity control 
Abstract:
 In this paper, we propose an energy-aware feedback control model for
 production scheduling and capacity control. Specifically, we integrate
 functions of production scheduling and capacity control, taking into
 account the costs of energy consumption and machine maintenance varied by
 production capacity, and the penalty cost imposed by just-in-time
 production requirements. Continuous control variables are used to adjust
 the system and the resulting dynamics are modelled. Computational
 experiments show that interrelated dynamics among these three performance
 factors are well explained by the proposed controllers, and considerably
 better energy performance, about 20.0--40.0% improvement, in an
 energy-aware production compared to a conventional strategy.
Journal: International Journal of Production Research 
Pages: 7158-7170 
Issue: 23 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1082666 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1082666 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaolan Xie 
Author-X-Name-First: Xiaolan 
Author-X-Name-Last: Xie 
Author-Name: Mark A. Lawley 
Author-X-Name-First: Mark A. 
Author-X-Name-Last: Lawley 
Title: Operations research in healthcare 
Journal: International Journal of Production Research 
Pages: 7173-7176 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1102356 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1102356 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Bohui Liang 
Author-X-Name-First: Bohui 
Author-X-Name-Last: Liang 
Author-Name: Ayten Turkcan 
Author-X-Name-First: Ayten 
Author-X-Name-Last: Turkcan 
Author-Name: Mehmet Erkan Ceyhan 
Author-X-Name-First: Mehmet Erkan 
Author-X-Name-Last: Ceyhan 
Author-Name: Keith Stuart 
Author-X-Name-First: Keith 
Author-X-Name-Last: Stuart 
Title: Improvement of chemotherapy patient flow and scheduling in an outpatient oncology clinic 
Abstract:
 Due to increasing demand, the oncology clinics have been experiencing
 higher workloads and increasing delays in laboratory, pharmacy and
 chemotherapy administration areas. In this study, we worked with an
 oncology clinic where patients receive chemotherapy treatment. A discrete
 event simulation model is developed to evaluate the operational
 performance in the clinic and to identify initiatives for improvement in
 process flow, scheduling and staffing. A mathematical programming model is
 developed to generate balanced appointment schedules for oncologist visit
 and chemotherapy treatment. Our results show that patient waiting times
 and clinic total working times can be reduced, and a more balanced
 resource utilisation can be achieved using better scheduling methods.
Journal: International Journal of Production Research 
Pages: 7177-7190 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2014.988891 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988891 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7177-7190




Template-Type: ReDIF-Article 1.0
Author-Name: Andres F. Osorio 
Author-X-Name-First: Andres F. 
Author-X-Name-Last: Osorio 
Author-Name: Sally C. Brailsford 
Author-X-Name-First: Sally C. 
Author-X-Name-Last: Brailsford 
Author-Name: Honora K. Smith 
Author-X-Name-First: Honora K. 
Author-X-Name-Last: Smith 
Title: A structured review of quantitative models in the blood supply chain: a taxonomic framework for decision-making 
Abstract:
 This paper presents a structured review of the literature on quantitative
 modelling for the blood product supply chain. This is a widely researched
 topic, dating back to the 1960s, and several other reviews have been
 published over the years. However, this paper presents new relevant
 information for researchers, not only by including more recent models but
 chiefly because of the structured way in which the models are presented.
 The models are broken down into five categories. The first four categories
 represent the four stages (echelons) in the supply chain: collection,
 production, inventory and delivery. The final category contains
 &#x2018;integrated&#x2019; models which cover more than one stage. Each
 section (other than integrated models, which are treated slightly
 differently) contains two distinct elements. The first element is a
 diagrammatic representation of decisions and relationships, broken down by
 hierarchy level (strategic -- tactical -- operational). The second element
 is a text description of the main features, contributions and gaps found
 in the analysed models. An additional element for each section is
 available online, namely a searchable table describing specific features
 of each echelon, together with a taxonomic key to assist the reader.
Journal: International Journal of Production Research 
Pages: 7191-7212 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1005766 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005766 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7191-7212




Template-Type: ReDIF-Article 1.0
Author-Name: Xiaofang Wang 
Author-X-Name-First: Xiaofang 
Author-X-Name-Last: Wang 
Author-Name: Laurens G. Debo 
Author-X-Name-First: Laurens G. 
Author-X-Name-Last: Debo 
Author-Name: Alan Scheller-Wolf 
Author-X-Name-First: Alan 
Author-X-Name-Last: Scheller-Wolf 
Title: Managing nurse lines -- practical challenges and the developing theory 
Abstract:
 As a fast growing specialty, medical telephone triage lines (nurse lines)
 play an important role in providing advice and recommendations to help
 ensure that medical care is delivered at the appropriate level. In this
 paper, we discuss the operations of these nurse lines, based on studies in
 the literature and interviews with nurse line researchers and
 practitioners. This leads us to identify issues relevant for the design
 and management of such lines, challenges that operations research
 (OR)/operations management (OM) can help address. We demonstrate that a
 classical call center modelling approach, focusing exclusively on
 congestion, will be insufficient in addressing these challenges. Thus, we
 motivate research on an integrated framework in which both congestion and
 decision-making accuracy are coupled. We summarise the limited extant
 research in OR/OM that is applicable to the unique challenges posed by
 nurse lines, highlighting these models&#x2019; contributions, as well as
 the questions they leave unanswered. These questions provide significant
 opportunities for future research.
Journal: International Journal of Production Research 
Pages: 7213-7225 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1005875 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005875 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7213-7225




Template-Type: ReDIF-Article 1.0
Author-Name: Serpil Mutlu 
Author-X-Name-First: Serpil 
Author-X-Name-Last: Mutlu 
Author-Name: James Benneyan 
Author-X-Name-First: James 
Author-X-Name-Last: Benneyan 
Author-Name: John Terrell 
Author-X-Name-First: John 
Author-X-Name-Last: Terrell 
Author-Name: Victoria Jordan 
Author-X-Name-First: Victoria 
Author-X-Name-Last: Jordan 
Author-Name: Ayten Turkcan 
Author-X-Name-First: Ayten 
Author-X-Name-Last: Turkcan 
Title: A co-availability scheduling model for coordinating multi-disciplinary care teams 
Abstract:
 We introduce a co-availability scheduling problem that arises in various
 healthcare settings in which personnel from different disciplines work
 together as care teams and for which synchronisation of their availability
 impacts scheduling flexibility and procedure timeliness. Examples include
 breast cancer surgery involving oncologic and plastic surgeons, primary
 and specialty care integrated visits, and vascular interventions involving
 cardiac surgeons, radiologists and radiology technicians. We develop an
 integer programming model to help create optimal schedules that maximise
 the amount of co-available time across the scheduling templates of the
 desired team members, while still satisfying each of their clinic
 coverage, preference and extraneous responsibilities constraints.
 Application to breast surgery at a major cancer centre increased team
 co-availability by 94%, with sensitivity analysis in other scenarios
 producing 64--152%, increases in favourable team assignments, and without
 negatively affecting operating room neither utilisation nor surgery
 delays.
Journal: International Journal of Production Research 
Pages: 7226-7237 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1018452 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1018452 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7226-7237




Template-Type: ReDIF-Article 1.0
Author-Name: Eren Demir 
Author-X-Name-First: Eren 
Author-X-Name-Last: Demir 
Author-Name: Christos Vasilakis 
Author-X-Name-First: Christos 
Author-X-Name-Last: Vasilakis 
Author-Name: Reda Lebcir 
Author-X-Name-First: Reda 
Author-X-Name-Last: Lebcir 
Author-Name: David Southern 
Author-X-Name-First: David 
Author-X-Name-Last: Southern 
Title: A simulation-based decision support tool for informing the management of patients with Parkinson&#x2019;s disease 
Abstract:
 We describe a decision support toolkit that was developed with the aim of
 assisting those responsible with the management and treatment of
 Parkinson&#x2019;s disease (PD) in the UK. Having created a baseline model
 and established its face validity, the toolkit captures the complexity of
 PD services at a sufficient level and operates within a user-friendly
 environment; that is, an interface was built to allow users to specify
 their own local PD service and input their own estimates or data of
 service demands and capacities. The main strength of this decision support
 tool is the adoption of a team approach to studying the system, involving
 six PD specialist nurses across the country, ensuring that variety of
 views and suggestions are taken as well as systems modelling and
 simulations. The tool enables key decision-makers to estimate the likely
 impact of changes, such as increased use of community services on
 activity, cost, staffing levels, skill-mix and utilisation of resources.
 Such previously unobtainable quantitative information can be used to
 support business cases for changes in the increased use of community
 services and its impact on clinical outcomes (disease progression), nurse
 visits and costing.
Journal: International Journal of Production Research 
Pages: 7238-7251 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1029647 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1029647 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7238-7251




Template-Type: ReDIF-Article 1.0
Author-Name: Aida Jebali 
Author-X-Name-First: Aida 
Author-X-Name-Last: Jebali 
Author-Name: Ali Diabat 
Author-X-Name-First: Ali 
Author-X-Name-Last: Diabat 
Title: A stochastic model for operating room planning under capacity constraints 
Abstract:
 The present paper describes a two-stage stochastic programme for operating
 room planning that takes into account capacity constraints of three
 hospital resources: operating rooms, beds in the intensive care unit (ICU)
 and beds in the ward (or medium care unit). Operating room planning
 consists of deciding on the elective surgeries to perform over each period
 of the planning horizon, while considering uncertainties related to
 surgery duration as well as patient length of stay in the ICU and the
 ward. Sample average approximation is then used to solve the planning
 problem, aiming to minimise the sum of patient-related costs and expected
 resource utilisation costs. Computational experiments are conducted to
 evaluate the performance of the proposed solution method. The obtained
 results highlight the robustness of operating room plans obtained by a
 stochastic approach, in comparison to those generated by a deterministic
 approach, and the importance of considering both ICU and ward beds in
 operating room planning.
Journal: International Journal of Production Research 
Pages: 7252-7270 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1033500 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1033500 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7252-7270




Template-Type: ReDIF-Article 1.0
Author-Name: Margit Sommersguter-Reichmann 
Author-X-Name-First: Margit 
Author-X-Name-Last: Sommersguter-Reichmann 
Author-Name: Marion S. Rauner 
Author-X-Name-First: Marion S. 
Author-X-Name-Last: Rauner 
Title: Benchmarking the rescue departments of the Austrian Red Cross using data envelopment analysis and fractional regression models 
Abstract:
 We performed a radial, input-oriented variable returns-to-scale data
 envelopment analysis to benchmark 52 rescue departments of the Austrian
 Red Cross from a single province. Three inputs (working hours of employed
 personnel/non-employed personnel and number of vehicles) and two output
 variables (duration-weighted number of two service transportation
 categories) were selected. First, we assessed the service production
 process of the Red Cross to obtain an insight into the level of
 performance, and performance differences among the rescue departments. We
 found that the average technical efficiency of the rescue departments
 amounted to almost 88%. The theoretically derived potentials of input
 reductions for inefficient rescue departments were, among others,
 restricted by several settings, which were analysed in the second step.
 Here, several socio-economic, environmental and institutional factors were
 investigated using a second stage regression analysis based on fractional
 regression models to find out whether they impacted on the performance of
 the rescue departments. We found a negative relationship between wintry
 weather conditions, measured as the number of ice days, and performance,
 while we identified a positive impact of the number of people aged
 64+&#xa0;and the number of hospital beds in the catchment area on Red
 Cross performance.
Journal: International Journal of Production Research 
Pages: 7271-7285 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1037022 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1037022 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7271-7285




Template-Type: ReDIF-Article 1.0
Author-Name: D. Prot 
Author-X-Name-First: D. 
Author-X-Name-Last: Prot 
Author-Name: T. Lap&#xe8;gue 
Author-X-Name-First: T. 
Author-X-Name-Last: Lap&#xe8;gue 
Author-Name: O. Bellenguez-Morineau 
Author-X-Name-First: O. 
Author-X-Name-Last: Bellenguez-Morineau 
Title: A two-phase method for the shift design and personnel task scheduling problem with equity objective 
Abstract:
 In this paper, we study the Shift Design and Personnel Task Scheduling
 Problem with Equity objective, initially introduced by Lap&#xe8;gue,
 Bellenguez-Morineau and Prot (&#x201c;A Constraint-based Approach for the
 Shift Design Personnal Task Scheduling Problem with Equity&#x201d;,
 <italic>Computers and Operations Research</italic> 40 (10): 2450--2465).
 This problem, arising in the company Biotrial, consists in designing the
 shifts of employees and assigning a set of tasks to qualified employees,
 so as to maximise the equity between employees. We propose a natural
 two-phase approach consisting in first designing shifts and then assigning
 tasks to employees, and we iterate between these two phases to improve
 solutions. We compare our experimental results with existing approaches
 and show that our approach outperforms previous known results.
Journal: International Journal of Production Research 
Pages: 7286-7298 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1037023 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1037023 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7286-7298




Template-Type: ReDIF-Article 1.0
Author-Name: Y. Kergosien 
Author-X-Name-First: Y. 
Author-X-Name-Last: Kergosien 
Author-Name: V. B&#xe9;langer 
Author-X-Name-First: V. 
Author-X-Name-Last: B&#xe9;langer 
Author-Name: P. Soriano 
Author-X-Name-First: P. 
Author-X-Name-Last: Soriano 
Author-Name: M. Gendreau 
Author-X-Name-First: M. 
Author-X-Name-Last: Gendreau 
Author-Name: A. Ruiz 
Author-X-Name-First: A. 
Author-X-Name-Last: Ruiz 
Title: A generic and flexible simulation-based analysis tool for EMS management 
Abstract:
 Emergency medical services (EMS) are dedicated to provide urgent medical
 care to any person requiring it and to ensure their transport to a
 hospital or care facility, if required. Moreover, in many contexts, EMS
 also have to provide transportation services for patients need to go from
 one hospital to another or between their home and the hospital. For such
 organisations, efficient strategies for managing the ambulance fleet at
 their disposal have to be selected, but the highly random and dynamic
 nature of the system under study makes this a challenging task. Most of
 the published studies which have considered these issues have done it
 focusing on a specific EMS context, one city or one territory for
 instance. However, it is possible to identify several common
 characteristics and processes from one EMS context to another. This is the
 purpose of the generic discrete event simulation-based analysis tool
 proposed here, which can be adapted to a wide range of EMS contexts. In
 particular, it explicitly considers the two types of tasks that can
 compose the mission of an EMS: serving emergency requests and providing
 transports between care units/hospitals/patients&#x2019; homes.
Journal: International Journal of Production Research 
Pages: 7299-7316 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1037405 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1037405 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7299-7316




Template-Type: ReDIF-Article 1.0
Author-Name: Jiafu Tang 
Author-X-Name-First: Jiafu 
Author-X-Name-Last: Tang 
Author-Name: Yu Wang 
Author-X-Name-First: Yu 
Author-X-Name-Last: Wang 
Title: An adjustable robust optimisation method for elective and emergency surgery capacity allocation with demand uncertainty 
Abstract:
 This article addresses the problem of allocating limited operating room
 (OR) capacity among subspecialties in hospitals where two types of demands
 exist: elective surgeries and emergency surgeries. In many medium- and
 small-scale hospitals, no OR capacity is affiliated with a particular
 subspecialty, but several subspecialties share the OR capacity in the
 hospital. The administrator needs to decide how much OR capacity to assign
 to each subspecialty and how much to reserve for emergency surgeries.
 Because such an allocation is usually decided several weeks or even months
 before, the only information about future demands is their range. We focus
 on finding a robust solution that handles disturbances in the surgery
 demand. An adjustable robust model is developed to solve this surgery
 capacity allocation problem with demand uncertainty. The worst-case
 revenue loss resulting from a shortage of OR resources is minimised. We
 examine the impact of conservativeness of the robust model on the revenue
 loss of the surgery department, which provides hospital administrators
 guidance for setting the adjustable parameters. An implementer-adversary
 algorithm is applied to solve the robust optimisation model. We present
 computational results comparing the proposed robust optimisation approach
 with a scenario-based stochastic optimisation; the results show that by
 adjusting the conservatism, the expected objective value realised by the
 robust solution is very close to that obtained by the stochastic
 programming approach. Moreover, the robust optimisation method has the
 benefit of limiting the worst-case outcome of the surgery capacity
 allocation problem.
Journal: International Journal of Production Research 
Pages: 7317-7328 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1056318 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056318 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7317-7328




Template-Type: ReDIF-Article 1.0
Author-Name: Jing Li 
Author-X-Name-First: Jing 
Author-X-Name-Last: Li 
Author-Name: Ming Dong 
Author-X-Name-First: Ming 
Author-X-Name-Last: Dong 
Author-Name: Wenhui Zhao 
Author-X-Name-First: Wenhui 
Author-X-Name-Last: Zhao 
Title: Admissions optimisation and premature discharge decisions in intensive care units 
Abstract:
 This paper studies the admission and premature discharge decisions in the
 intensive care unit (ICU). While the previous admission policy first come,
 first served treated all patients equally, this paper divides patients
 into two classes. One class (class 1) is the more critical patients who
 cannot be prematurely discharged to other hospital units. The other class
 (class 2) is patients who can be prematurely discharged to other hospital
 units in order to accommodate new class 1 patients. We formulate a dynamic
 programming model to determine the best policy for allocating available
 beds to different classes of patients and reducing premature discharging
 costs. By analysing the model, we conclude that there is a threshold (i.e.
 a fixed number of available beds) for class 2 patients in each time
 period. If the number of available beds is lower than the threshold, the
 request of a class 2 patient will be rejected. Otherwise, he/she will be
 accepted. We find that the survival benefits follow a marginal diminishing
 effect. The management team can decide how many beds should be allocated
 to ICU by considering the balance of budget and survival benefits. We also
 establish the lower and upper bounds of probability that a patient is
 admitted and prematurely discharged on the same day. The bounds can be
 used to evaluate our policy and adjust the parameter to improve the
 policy. The computational experiments illustrate that the proposed policy
 is better than the traditional policies and the obtained threshold is
 lower than the threshold that premature discharging is not permitted. The
 average survival benefits are computed with all initial states. The
 proposed method is effective and can help ICUs to obtain a relative high
 survival benefits per day.
Journal: International Journal of Production Research 
Pages: 7329-7342 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1059520 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1059520 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7329-7342




Template-Type: ReDIF-Article 1.0
Author-Name: Brecht Cardoen 
Author-X-Name-First: Brecht 
Author-X-Name-Last: Cardoen 
Author-Name: Jeroen Beli&#xeb;n 
Author-X-Name-First: Jeroen 
Author-X-Name-Last: Beli&#xeb;n 
Author-Name: Mario Vanhoucke 
Author-X-Name-First: Mario 
Author-X-Name-Last: Vanhoucke 
Title: On the design of custom packs: grouping of medical disposable items for surgeries 
Abstract:
 A custom pack combines medical disposable items into a single sterile
 package that is used for surgical procedures. Although custom packs are
 gaining importance in hospitals due to their potential benefits in
 reducing surgery setup times, little is known on methodologies to
 configure them, especially if the number of medical items, procedure types
 and surgeons is large. In this paper, we propose a mathematical
 programming approach to guide hospitals in developing or reconfiguring
 their custom packs. In particular, we are interested in minimising points
 of touch, which we define as a measure for physical contact between staff
 and medical materials. Starting from an integer non-linear programming
 model, we develop both an exact linear programming (LP) solution approach
 and an LP-based heuristic. Next, we also describe a simulated annealing
 approach to benchmark the mathematical programming methods. A
 computational experiment, based on real data of a medium-sized Belgian
 hospital, compares the optimised results with the performance of the
 hospital&#x2019;s current configuration settings and indicates how to
 improve future usage. Next to this base case, we introduce scenarios in
 which we examine to what extent the results are sensitive for waste, i.e.
 adding more items to the custom pack than is technically required for some
 of the custom pack&#x2019;s procedures, since this can increase its
 applicability towards other procedures. We point at some interesting
 insights that can be taken up by the hospital management to guide the
 configuration and accompanying negotiation processes.
Journal: International Journal of Production Research 
Pages: 7343-7359 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1061221 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1061221 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7343-7359




Template-Type: ReDIF-Article 1.0
Author-Name: Jie Song 
Author-X-Name-First: Jie 
Author-X-Name-Last: Song 
Author-Name: Jianpei Wen 
Author-X-Name-First: Jianpei 
Author-X-Name-Last: Wen 
Title: A non-cooperative game with incomplete information to improve patient hospital choice 
Abstract:
 In order to improve the accessibility of health care service, the
 hierarchical health care delivery system that includes the general
 hospital (GH) and the community health care center (CHC) has been
 gradually established in urban China. In this paper, we introduce a game
 theoretic framework that considers both the influence of static and
 dynamic factors on patients&#x2019; choices among health care facilities.
 We formulate a non-cooperative game with incomplete information and regard
 the equilibrium of this game as a best prediction of patients&#x2019;
 hospital choice results. We implement the proposed game theoretic
 framework by a case study. We provide quantitative analysis on the
 equilibrium to study how those factors affect patients&#x2019; hospital
 choices. Finally, to achieve the goal that alleviates the congestion of GH
 and balance the patient flow among GHs and CHCs, we implement two
 incentive policies in our model, along with analysing their effects on
 patients&#x2019; hospital choices. The non-cooperative game with
 incomplete information model functions as a quantitative tool to help the
 government decision-maker to improve the patient flow distribution in
 urban China.
Journal: International Journal of Production Research 
Pages: 7360-7375 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1077284 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1077284 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:24:p:7360-7375




Template-Type: ReDIF-Article 1.0
Author-Name: Chongjun Yan 
Author-X-Name-First: Chongjun 
Author-X-Name-Last: Yan 
Author-Name: Jiafu Tang 
Author-X-Name-First: Jiafu 
Author-X-Name-Last: Tang 
Author-Name: Bowen Jiang 
Author-X-Name-First: Bowen 
Author-X-Name-Last: Jiang 
Author-Name: Richard Y.K. Fung 
Author-X-Name-First: Richard Y.K. 
Author-X-Name-Last: Fung 
Title: Sequential appointment scheduling considering patient choice and service fairness 
Abstract:
 Effective appointment scheduling system is very important to the
 efficiency of the clinic and the satisfaction of the patients. In
 practice, the clinic scheduler usually assigns the patients to an
 available slot before the call terminates and the appointment time
 can&#x2019;t be adjusted any more. In this paper, a sequential appointment
 scheduling method is proposed to balance the benefits of clinic and
 patients&#x2019; satisfaction considering patient choice and service
 fairness simultaneously. It determines the optimal booking number of
 patients and optimal scheduling time for each patient to maximise the
 profit of the outpatient clinic over a session-day. The profit considered
 in this paper is the total revenue of all arriving patients minus the cost
 of waiting time, idle time and overtime, which not only considers the
 rewards from booking decision, but also precisely formulates the charge on
 service process depending on scheduling. A general patient choice
 behaviour is incorporated into the model as well. Two myopic scheduling
 algorithms are developed to optimally solve the sequential appointment
 scheduling problems with and without considering service fairness,
 respectively. Particularly, instead of exhaustive search in every step, a
 property is identified to speed the search process by reducing search
 space in the proposed myopic scheduling algorithms. After analysing the
 effects of model parameters on the optimal schedule and system
 performances, some insights are obtained to help clinics manage sequential
 appointment requests. The results show that the objective function
 evolution is unimodal and the allowance of patient choice can increase the
 number of patients seen in a day, but lower down the expected profit on
 account of less flexibility. The clinics provide uniform service to
 patients arriving in different intervals at the expense of less mean and
 larger variance of the profit.
Journal: International Journal of Production Research 
Pages: 7376-7395 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1081426 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1081426 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: C. Rodriguez 
Author-X-Name-First: C. 
Author-X-Name-Last: Rodriguez 
Author-Name: T. Garaix 
Author-X-Name-First: T. 
Author-X-Name-Last: Garaix 
Author-Name: X. Xie 
Author-X-Name-First: X. 
Author-X-Name-Last: Xie 
Author-Name: V. Augusto 
Author-X-Name-First: V. 
Author-X-Name-Last: Augusto 
Title: Staff dimensioning in homecare services with uncertain demands 
Abstract:
 The problem addressed in this paper is how to calculate the amount of
 personnel required to ensure the activity of a home health care (HHC)
 centre on a tactical horizon. Design of quantitative approaches for this
 question is challenging. The number of caregivers has to be determined for
 each profession in order to balance the coverage of patients in a region
 and the workforce cost over several months. Unknown demand in care and
 spatial dimensions, combination of skills to cover a care and individual
 trips visiting patients make the underlaying optimisation problem very
 hard. Few studies are dedicated to staff dimensioning for HHC compared to
 patient to nurses assignment/sequencing and centres location problems. We
 propose an original two-stage approach based on integer linear stochastic
 programming, which exploits historical medical data. The first stage
 calculates (near-)optimal levels of resources for possible demand
 scenarios, while the second stage computes the optimal number of caregiver
 for each profession to meet a target coverage indicator. For
 decision-makers, our algorithm gives the number of employees for each
 category required to satisfy the demand without any recourse (overtime,
 external resources) with fixed probability and confidence interval. The
 approach has been tested on various instances built from data of the
 French agency of hospitalisation data (ATIH).
Journal: International Journal of Production Research 
Pages: 7396-7410 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1081427 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1081427 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoyu Liu 
Author-X-Name-First: Xiaoyu 
Author-X-Name-Last: Liu 
Author-Name: Xiaoqiang Cai 
Author-X-Name-First: Xiaoqiang 
Author-X-Name-Last: Cai 
Author-Name: Ruiqing Zhao 
Author-X-Name-First: Ruiqing 
Author-X-Name-Last: Zhao 
Author-Name: Yanfei Lan 
Author-X-Name-First: Yanfei 
Author-X-Name-Last: Lan 
Title: Mutual referral policy for coordinating health care systems of different scales 
Abstract:
 We develop a model to formulate the mutual referral process in a health
 care system involving a city hospital and a community hospital, and derive
 the optimal mutual referral strategy between them in the subordination
 situation as a benchmark. We also concentrate on the subcontracting
 situation, where the city hospital plays a dominating role, offering
 contracts to induce the community hospital to follow the optimal mutual
 referral strategy. We introduce two complex contracts: fee-for-service via
 cost sharing (FFS-CS) and pay-for-performance via cost sharing (P4P-CS) to
 coordinate, and find that both contracts coordinate effectively,
 regardless of the scale of the system. In addition, we discuss four
 extreme cases: fee-for-service via no cost sharing (FFS-NCS),
 fee-for-service via total cost sharing (FFS-TCS), pay-for-performance via
 no cost sharing (P4P-NCS), and pay-for-performance via total cost sharing
 (P4P-TCS) and find that some can coordinate the health care system under
 certain circumstances, whereas others cannot. Through the numerical
 examples we discuss the applicability of the coordinating contracts and
 further find that FFS-CS outperforms P4P-CS in terms of applicability.
Journal: International Journal of Production Research 
Pages: 7411-7433 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1082039 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1082039 
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Template-Type: ReDIF-Article 1.0
Author-Name: Thibaud Monteiro 
Author-X-Name-First: Thibaud 
Author-X-Name-Last: Monteiro 
Author-Name: Nadine Meskens 
Author-X-Name-First: Nadine 
Author-X-Name-Last: Meskens 
Author-Name: Tao Wang 
Author-X-Name-First: Tao 
Author-X-Name-Last: Wang 
Title: Surgical scheduling with antagonistic human resource objectives 
Abstract:
 Daily operating theatre scheduling is a complex problem with strong
 constraints and various objectives to optimise. In this article, we aim
 not only to optimise the classical objectives of scheduling performance,
 such as the makespan and the cost of overtime, but also, particularly, to
 upgrade human resource management performance by means of two additional
 objectives: a short-term objective on the quality of teamwork and a
 long-term objective on the level of nurses&#x2019; skills. The quality of
 teamwork depends on affinities between team members, which also have a
 significant impact on the quality and the safety of surgery. It maintains
 the unity of surgical teams. Such unity is however unfavourable to
 nurses&#x2019; skill diversification. In order to counterbalance this
 tendency, the long-term objective proposed is for nurses to acquire the
 widest possible spectrum of skills, in order to be able to assist surgeons
 in unplanned and emergency surgery. Taking into account these two
 antagonistic human resources objectives contributes to patient safety
 through better team building. It is the main originality of this work. In
 the long term, this method reduces the impact of this antagonism. In
 addition, we use the multi-objective <italic>&#x3b5;</italic>-constraint
 method to obtain Pareto optimal solutions.
Journal: International Journal of Production Research 
Pages: 7434-7449 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1082040 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1082040 
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Template-Type: ReDIF-Article 1.0
Author-Name: Biao Yuan 
Author-X-Name-First: Biao 
Author-X-Name-Last: Yuan 
Author-Name: Ran Liu 
Author-X-Name-First: Ran 
Author-X-Name-Last: Liu 
Author-Name: Zhibin Jiang 
Author-X-Name-First: Zhibin 
Author-X-Name-Last: Jiang 
Title: A branch-and-price algorithm for the home health care scheduling and routing problem with stochastic service times and skill requirements 
Abstract:
 Home health care (HHC) is defined as providing medical and paramedical
 services for patients at their own domicile. In the HHC industry, it is
 crucial for health care organisations to assign caregivers to patients and
 devise reasonable visiting routes to save total operational cost and
 improve the service quality. However, some special constraints make the
 problem hard to solve. For example, patients&#x2019; service times are
 usually stochastic due to their varying health conditions; caregivers are
 organised in a hierarchical structure according to their skills to satisfy
 patients&#x2019; demands. In this paper, we address a HHC scheduling and
 routing problem with stochastic service times and skill requirements. A
 stochastic programming model with recourse is proposed to formulate the
 problem in which the expected penalty for late arrival at customers is
 considered. To solve the problem, it is equivalently transformed into a
 master problem and a pricing sub-problem. A column generation algorithm is
 developed to solve the relaxation of the master problem and obtain its
 lower bound. A label algorithm and several effective accelerating
 techniques are devised to solve the pricing sub-problem. To obtain
 feasible solutions, the column generation procedure is embedded within the
 branch and bound framework. The effectiveness of the proposed algorithm is
 validated through numerical experiments.
Journal: International Journal of Production Research 
Pages: 7450-7464 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1082041 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1082041 
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Template-Type: ReDIF-Article 1.0
Author-Name: Andreas F&#xfc;gener 
Author-X-Name-First: Andreas 
Author-X-Name-Last: F&#xfc;gener 
Author-Name: Jens O. Brunner 
Author-X-Name-First: Jens O. 
Author-X-Name-Last: Brunner 
Author-Name: Armin Podtschaske 
Author-X-Name-First: Armin 
Author-X-Name-Last: Podtschaske 
Title: Duty and workstation rostering considering preferences and fairness: a case study at a department of anaesthesiology 
Abstract:
 This research addresses a personnel scheduling problem at hospitals. We
 present two mixed integer linear programming models -- a duty-roster model
 and a workstation-roster model. The duty-roster model determines the
 assignment of physicians to 24-h and late duties whereas the
 workstation-roster model assigns physicians to actual workstations as
 operating rooms. The former serves as an input for the latter. In both
 models, we maximise the number of assignments subject to labour
 regulations and internal department-specific scheduling rules.
 Furthermore, we consider experience levels and qualifications in our
 models. To promote for job satisfaction, we take into account fairness
 aspects as well as individual physician preferences. Using real-world data
 from our cooperating department of anaesthesiology with 120 physicians, we
 set up a case study. Computational results indicate the superior quality
 compared to manual scheduling which is currently in use at our cooperation
 hospital. Furthermore, we develop an extensive computational study with
 5800 instances to test the models. We show that the computational burden
 is negligible and we derive managerial insight for the scheduling process.
Journal: International Journal of Production Research 
Pages: 7465-7487 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1082667 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1082667 
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Template-Type: ReDIF-Article 1.0
Author-Name: Carrie Ka Yuk Lin 
Author-X-Name-First: Carrie Ka Yuk 
Author-X-Name-Last: Lin 
Title: An adaptive scheduling heuristic with memory for the block appointment system of an outpatient specialty clinic 
Abstract:
 This work analysed the appointment system of outpatient clinics serving
 multiple patient classes with different flow sequences through the
 multi-phase-multi-server service system. Scarce resources are doctors,
 nurses and medical professionals with different start times and
 availability. Block appointment systems are typically used in public
 hospitals to help regulate patient flow while minimising patient waiting
 time, staff overtime and waiting room congestion. The patient scheduling
 problem in this complex environment is formulated by a mixed integer
 programme (MIP). Making use of waiting time information, an adaptive
 scheduling heuristic is designed to improve an initial schedule
 iteratively by identifying procedures with large average waiting times and
 reassigning their related patient classes to less congested time blocks
 probabilistically. An impact index based on the weighted multi-objective
 function is developed to allow servers select an available patient for the
 next treatment. A memory of distinct solutions is maintained to avoid
 recycling. Experiments are conducted based on a case study of an eye
 clinic in a public hospital. Performance is evaluated by comparing with
 the MIP and well-known dispatching rules for job shop scheduling problems.
 Sensitivity analysis is conducted for increase in appointment quota, two
 alternative staffing plans and changes in patient class distribution.
Journal: International Journal of Production Research 
Pages: 7488-7516 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1084060 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1084060 
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohan Priya 
Author-X-Name-First: Mohan 
Author-X-Name-Last: Priya 
Author-Name: Paulraj Ranjith Kumar 
Author-X-Name-First: Paulraj 
Author-X-Name-Last: Ranjith Kumar 
Title: A novel intelligent approach for predicting atherosclerotic individuals from big data for healthcare 
Abstract:
 Atherosclerosis is a condition in human circulatory, where the arteries
 become narrowed and hardened due to accumulation of plaque around artery
 wall. The growth of the disease is slow and asymptomatic. Currently,
 imaging methods are applied for predicting the disease progression;
 however, they are deficient in the required resolution and sensitivity for
 detection. In this work, clinical observations and habits of individuals
 are considered for assorting the pathologic community. Intelligent machine
 learning technique, decision tree forest is used for assorting the
 individuals. A case study was made in this work regarding the
 atherosclerosis disease progression and crucial features were extracted.
 Optimised missing value imputation strategy, iterative principal component
 analysis for STULONG data-set and efficient feature subset selection
 method, hybrid fast correlation-based filter (FCBF) have been employed for
 extracting the relevant features and ignoring the redundant features.
 Further proceeding with the methodology, our work has outperformed with
 extreme overall accuracy of about 99.47% compared with other
 state-of-the-art machine learning techniques.
Journal: International Journal of Production Research 
Pages: 7517-7532 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1087655 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1087655 
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Template-Type: ReDIF-Article 1.0
Author-Name: Li-chih Wang 
Author-X-Name-First: Li-chih 
Author-X-Name-Last: Wang 
Author-Name: Chen-yang Cheng 
Author-X-Name-First: Chen-yang 
Author-X-Name-Last: Cheng 
Author-Name: Ya-tsai Tseng 
Author-X-Name-First: Ya-tsai 
Author-X-Name-Last: Tseng 
Author-Name: Yi-fang Liu 
Author-X-Name-First: Yi-fang 
Author-X-Name-Last: Liu 
Title: Demand-pull replenishment model for hospital inventory management: a dynamic buffer-adjustment approach 
Abstract:
 Hospital inventory management faces a continually increasing challenge to
 ensure the availability of medical and surgical supplies at the lowest
 inventory cost. For overcoming the drawbacks of existing re-order point
 approaches commonly applied in hospital materials replenishment
 management, this research presents an innovative demand-pull replenishment
 approach named the dynamic drum-buffer-rope (DDBR) replenishment model.
 The DDBR model is implemented using a system dynamics approach in which
 two essential mechanisms -- the demand-pull characteristics and dynamic
 buffer-adjustment activities -- are simulated and experimented on. To
 determine appropriate buffer sizes and replenishment quantities, this
 research adopted Powell search algorithm to achieve the objective of no
 stock-out occurrence and low inventory cost. The evaluation of the
 proposed DDBR model in a real hospital case through a series of
 comparisons shows that the DDBR model can determine optimal replenishment
 timing and quantity for total inventory cost with no stock-out occurrence.
Journal: International Journal of Production Research 
Pages: 7533-7546 
Issue: 24 
Volume: 53 
Year: 2015 
Month: 12 
X-DOI: 10.1080/00207543.2015.1102353 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1102353 
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov 
Author-X-Name-First: Dmitry 
Author-X-Name-Last: Ivanov 
Author-Name: Scott J. Mason 
Author-X-Name-First: Scott J. 
Author-X-Name-Last: Mason 
Author-Name: Richard Hartl 
Author-X-Name-First: Richard 
Author-X-Name-Last: Hartl 
Title: Supply chain dynamics, control and disruption management 
Journal: International Journal of Production Research 
Pages: 1-7 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1114186 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1114186 
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Template-Type: ReDIF-Article 1.0
Author-Name: Tianjian Yang 
Author-X-Name-First: Tianjian 
Author-X-Name-Last: Yang 
Author-Name: Weiguo Fan 
Author-X-Name-First: Weiguo 
Author-X-Name-Last: Fan 
Title: Information management strategies and supply chain performance under demand disruptions 
Abstract:
 The operations management literature presents inadequate comprehensive
 understanding on information management strategies of mitigating supply
 chain disruption risks. By using control theory modelling and simulation,
 this study compares the disruption mitigation effects of three information
 management strategies. From the aspect of stability, the existing
 stability boundaries are revised by a new method in a two-echelon case. It
 shows that supply chains (SC) with popular information management
 strategies are not evidently more stable than traditional ones. From the
 aspect of disruption recovery time, an innovative two-echelon swiftest
 response problem under these information management strategies is
 formulated and solved. Results show that a collaborative planning,
 forecasting and replenishment (CPFR) SC with complete SC information
 performs the best. However, in a later operational risk mitigation test,
 an information sharing (IS) SC with partial information has the smallest
 bullwhip effect. From the aspect of demand amplification and frequency
 response, an innovative frequency--response plot of order amplification is
 proposed in a time-continuous SC with moving average forecasts. It implies
 the best frequency response for concurrently mitigating both operational
 and disruption risks coming from a CPFR SC. But for a certain SC structure
 there is still a balance between mitigating bullwhip effect and quick
 response. Moreover, it also implies that anti-bullwhip should exist in a
 certain condition, as realised in our numerical experiments.
Journal: International Journal of Production Research 
Pages: 8-27 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2014.991456 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.991456 
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Template-Type: ReDIF-Article 1.0
Author-Name: Marzieh Mehrjoo 
Author-X-Name-First: Marzieh 
Author-X-Name-Last: Mehrjoo 
Author-Name: Zbigniew J. Pasek 
Author-X-Name-First: Zbigniew J. 
Author-X-Name-Last: Pasek 
Title: Risk assessment for the supply chain of fast fashion apparel industry: a system dynamics framework 
Abstract:
 With the rapid progress of science and technology and continuously growing
 customer expectations, share of merchandise exhibiting characteristics of
 perishability is on the rise and a wide range of industries are affected
 by this phenomenon. This paper focuses on the fast fashion apparel
 industry due to its particular characteristics such as short life cycle
 products, volatile demand, low predictability, high level of impulse
 purchase, high level of price competition and global sourcing. A system
 dynamics model is proposed for analysing the behaviour and relationships
 of the fast fashion apparel industry with three supply chain levels. The
 Conditional Value at Risk measure is applied to quantify the risks
 associated with the supply chain of these products and also to determine
 the expected value of the losses and their corresponding probabilities.
 Multiple business situations for effective strategic planning and
 decision-making are generated. In particular, the impact of lead time and
 delivery delays on the supply chain performance (inventory, cost, backlog
 and risk) is analysed as the key to success for this industry is to
 satisfy customers&#x2019; needs in the shortest time.
Journal: International Journal of Production Research 
Pages: 28-48 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2014.997405 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.997405 
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Template-Type: ReDIF-Article 1.0
Author-Name: Kasin Ransikarbum 
Author-X-Name-First: Kasin 
Author-X-Name-Last: Ransikarbum 
Author-Name: Scott J. Mason 
Author-X-Name-First: Scott J. 
Author-X-Name-Last: Mason 
Title: Multiple-objective analysis of integrated relief supply and network restoration in humanitarian logistics operations 
Abstract:
 While logistics research recently has placed increased focus on disruption
 management, few studies have examined the response and recovery phases in
 post-disaster operations. We present a multiple objective, integrated
 network optimisation model for making strategic decisions in the supply
 distribution and network restoration phases of humanitarian logistics
 operations. Our model provides an equity-based solution for constrained
 capacity, budget and resource problems in post-disaster logistics
 management. We conduct designed experiments for this NP-hard problem to
 analyse important aspects of the integrated problem for both small- and
 large-sized networks: full vs. partial restoration and pooled vs. separate
 budgeting approach. Finally, we apply the model to a Hazus-generated
 regional case study based on an earthquake scenario and generate efficient
 Pareto frontiers to understand the trade-off between the objectives of
 interest.
Journal: International Journal of Production Research 
Pages: 49-68 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2014.977458 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.977458 
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Template-Type: ReDIF-Article 1.0
Author-Name: George A. Zsidisin 
Author-X-Name-First: George A. 
Author-X-Name-Last: Zsidisin 
Author-Name: Boyana N. Petkova 
Author-X-Name-First: Boyana N. 
Author-X-Name-Last: Petkova 
Author-Name: Lammertjan Dam 
Author-X-Name-First: Lammertjan 
Author-X-Name-Last: Dam 
Title: Examining the influence of supply chain glitches on shareholder wealth: does the reason matter? 
Abstract:
 This paper investigates how different reasons for supply chain glitches
 influence shareholder wealth. Prior research indicated that supply chain
 glitches can decrease shareholder wealth by a staggering 10.28%. We argue
 that the reason for the supply chain glitch is an important moderator for
 understanding how supply chain glitches affect shareholder wealth. In this
 paper we re-assess the effect of supply chain glitches on shareholder
 wealth for a new time period (i.e. 2001--2012) whilst including the
 moderators from the original study (growth prospects, firm size,
 debt-equity ratio and timing) and adding the reason for the supply chain
 glitch as an important new moderator. Our results show that on average
 supply chain glitches decrease shareholder wealth by 1.94%. Further, our
 results indicate that supply chain glitches that arise due to regulatory,
 catastrophic and infrastructural reasons trigger more significant negative
 reactions in financial markets as compared with glitches that occur from
 the supply side. We discuss the implications of our findings both for
 theory building and for business practice, and end with limitations and
 suggestions for future research.
Journal: International Journal of Production Research 
Pages: 69-82 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1015751 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1015751 
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenbo Shi 
Author-X-Name-First: Wenbo 
Author-X-Name-Last: Shi 
Author-Name: Tianke Feng 
Author-X-Name-First: Tianke 
Author-X-Name-Last: Feng 
Title: Examining supply contracts under cost and demand uncertainties from supplier&#x2019;s perspective: a real options approach 
Abstract:
 Supply contracts have been widely utilised by practitioners to mitigate
 supply chain risks and disruptions while maintaining flexibility and
 stability. It is, thus, not surprising that buyers&#x2019; economically
 rational decisions towards supply contracts have been well studied.
 Missing in the literature, however, is examination of potential values and
 risks of supply contracts from supplier&#x2019;s perspective. Motivated by
 this literature vacancy, this paper, using a real options approach,
 investigates a supplier&#x2019;s acceptance decision towards a supply
 contract with variable cost and supply demand uncertainties. Through
 analytical and numerical examinations, conditions under which it is
 economically viable for the supplier to accept the supply contract are
 derived. This study also uncovers the impacts of variable cost and supply
 demand uncertainties as well as contract duration on the supplier&#x2019;s
 acceptance decision. Also, there exists a range of contract duration
 beyond which the supplier should reject the supply contract offered by the
 client. To facilitate the understanding of this duration range, the
 corresponding shortest and longest contract duration is derived through
 numerical examples.
Journal: International Journal of Production Research 
Pages: 83-97 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1008110 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1008110 
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Template-Type: ReDIF-Article 1.0
Author-Name: Tadeusz Sawik 
Author-X-Name-First: Tadeusz 
Author-X-Name-Last: Sawik 
Title: On the risk-averse optimization of service level in a supply chain under disruption risks 
Abstract:
 The worst-case optimization of service level in the presence of supply
 chain disruption risks is considered for the two different service levels
 measures: the expected worst-case demand fulfillment rate and the expected
 worst-case order fulfillment rate. The optimization problem is formulated
 as a joint selection of suppliers and stochastic scheduling of customer
 orders under random disruptions of supplies. The suppliers are located in
 different geographic regions and the supplies are subject to random local
 and regional disruptions. The obtained combinatorial stochastic
 optimization problem is formulated as a mixed integer program with
 conditional service-at-risk as a worst-case service level measure. The
 risk-averse solutions that optimize the worst-case performance of a supply
 chain are compared for the two service level measures. In addition, to
 demonstrate the impact on the cost in the process of optimizing the
 worst-case service level, a joint optimization of expected cost and
 conditional service-at-risk using a weighted-sum approach is considered
 and illustrated with numerical examples. The findings indicate that the
 worst-case order fulfillment rate shows a higher service performance than
 the worst-case demand fulfillment rate. Maximization of the expected
 worst-case fraction of fulfilled customer orders better mitigates the
 impact of disruption risks. The supply portfolio is more diversified and
 the expected worst-case fraction of fulfilled orders is greater for most
 confidence levels. Finally, the results clearly show that worst-case
 service level is in opposition to cost.
Journal: International Journal of Production Research 
Pages: 98-113 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1016192 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1016192 
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Template-Type: ReDIF-Article 1.0
Author-Name: James J.H. Liou 
Author-X-Name-First: James J.H. 
Author-X-Name-Last: Liou 
Author-Name: Jolanta Tamo&#x161;aitien&#x117; 
Author-X-Name-First: Jolanta 
Author-X-Name-Last: Tamo&#x161;aitien&#x117; 
Author-Name: Edmundas K. Zavadskas 
Author-X-Name-First: Edmundas K. 
Author-X-Name-Last: Zavadskas 
Author-Name: Gwo-Hshiung Tzeng 
Author-X-Name-First: Gwo-Hshiung 
Author-X-Name-Last: Tzeng 
Title: New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management 
Abstract:
 Greening the supply chain is an increasingly important concern for many
 business enterprises and a challenge for logistics management. Critical
 functions within green supply chain management are internal improvements
 and selection of green suppliers. This study proposes a novel, hybrid
 model that addresses dependent relationships between various criteria and
 the vague information coming from decision-makers. The Decision-making
 Trial and Evaluation Laboratory (DEMATEL) technique structures the
 relationships among criteria, thereby constructing an influential network
 relationship map (INRM). Meanwhile the DEMATEL-based, analytical network
 process (ANP) method aids in obtaining influential weights of the
 criteria. Decision-makers may hold diverse opinions and preferences due to
 incomplete information, differences in knowledge or simply conflicts that
 are inherent between various departments. This can make it difficult to
 judge the performance of alternatives. One remedy is to apply a modified
 COmplex PRoportional ASsessment of alternatives with Grey relations. Next,
 this is applied to improve each criterion for integration of the
 performance values obtained in closing the aspiration level from different
 expert opinions based on INRM. An empirical example using data from a
 Taiwanese electronics company is provided to demonstrate our proposed
 method. The results can provide firms with a knowledge-based understanding
 of the source of some problems, thus reducing the performance gaps and
 closing the aspiration levels. Finally, there is a discussion on certain
 managerial implications.
Journal: International Journal of Production Research 
Pages: 114-134 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1010747 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1010747 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jihee Han 
Author-X-Name-First: Jihee 
Author-X-Name-Last: Han 
Author-Name: KwangSup Shin 
Author-X-Name-First: KwangSup 
Author-X-Name-Last: Shin 
Title: Evaluation mechanism for structural robustness of supply chain considering disruption propagation 
Abstract:
 This paper aims to develop a novel evaluation mechanism for assessing the
 structural robustness of a supply chain considering disruption
 propagation. Disruption propagation means that the impact of risks
 propagates to the whole supply chain along the connected structure. Based
 on the propagation model, a structural robustness evaluation mechanism is
 devised by integrating two quantitative metrics, average path length and
 in degree-out degree. To validate the proposed mechanism, the result of
 the quantitative assessment of the structural robustness on random
 networks is compared with the probability of network disruption due to the
 random risk. From the results of the statistical verifications and
 sensitivity analysis, it can be said that the proposed mechanism is better
 at explaining the robustness of a supply chain. In other words, all
 components of a network, such as nodes and arcs, and their relationships
 should be considered altogether, in order to more accurately measure the
 robustness. It may be possible to apply the proposed mechanism to the very
 first step of designing the supply chain. Especially, in the case of it
 being hard to redesign a supply chain structure after practically
 launching and operating the designed network, the proposed mechanism may
 be utilised to verify whether the planned supply chain is robust to risks
 or not.
Journal: International Journal of Production Research 
Pages: 135-151 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1047977 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047977 
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Template-Type: ReDIF-Article 1.0
Author-Name: Boris Sokolov 
Author-X-Name-First: Boris 
Author-X-Name-Last: Sokolov 
Author-Name: Dmitry Ivanov 
Author-X-Name-First: Dmitry 
Author-X-Name-Last: Ivanov 
Author-Name: Alexandre Dolgui 
Author-X-Name-First: Alexandre 
Author-X-Name-Last: Dolgui 
Author-Name: Alexander Pavlov 
Author-X-Name-First: Alexander 
Author-X-Name-Last: Pavlov 
Title: Structural quantification of the ripple effect in the supply chain 
Abstract:
 In recent years, remarkable advancements have been achieved in
 quantitative analysis methods for supply chain design (SCD). Typically,
 cost or service level optimisation has been included in the objective
 functions. At the same time, supply chain managers face the ripple effect
 that arises from vulnerability, instability and disruptions in supply
 chains. This research aimed to quantify the ripple effect in the supply
 chain from the structural perspective. The research agenda of this study
 includes issues of integrating operability objectives as new key
 performance indicators, e.g. resilience, stability, robustness into SCD
 decisions. The research is based on a simultaneous consideration of both
 static structural properties of SCD and execution dynamics subject to
 uncertainty and disruptions. Due to high dimensionality of real SCD
 problems, such integration can hardly be implemented in only one model. In
 this study, an original two-model multi-criteria approach is proposed in
 order to assess the potential ability of an SCD to remain stable and
 resilient. This modelling approach is based on a combined application of a
 static and a dynamic model. A multi-criteria approach relies on the
 analytic hierarchy process method. The results of this research can be
 used as an additional quantitative analysis tool in order to select an
 SCD. An additional application of the developed method is that it can be
 used at the control stage in order to adapt supply chain execution subject
 to the achievement of desired economic performance.
Journal: International Journal of Production Research 
Pages: 152-169 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1055347 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055347 
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Template-Type: ReDIF-Article 1.0
Author-Name: Yong Luo 
Author-X-Name-First: Yong 
Author-X-Name-Last: Luo 
Author-Name: Shi-zhao Wang 
Author-X-Name-First: Shi-zhao 
Author-X-Name-Last: Wang 
Author-Name: Xiao-chen Sun 
Author-X-Name-First: Xiao-chen 
Author-X-Name-Last: Sun 
Author-Name: Oscar D. Crisalle 
Author-X-Name-First: Oscar D. 
Author-X-Name-Last: Crisalle 
Title: Analysis of retailers&#x2019; coalition stability for supply chain based on LCS and stable set 
Abstract:
 To attain the general form of stable coalition structure, this paper
 addressed the problem of retailers&#x2019; coalition stability in a
 two-stage supply chain consisting of one supplier and multiple retailers.
 A profit gain function was established via introducing market gain
 coefficient and coalition cost coefficient for different coalition
 structures. Based on the function, the profit of each retailer in all
 kinds of coalition structures was analysed, and the general feature of a
 stable coalition structure was attained by the largest consistent set
 method and the stable set method. Furthermore, some insights were
 obtained. For example, stable coalition structures are equidistributed or
 approximate equidistributed; with supplier&#x2019;s cost increasing, the
 size of the retailers&#x2019; coalition increases. Finally, the above
 conclusions are verified by numerical simulation. The results of this
 paper provide a reference for retailers&#x2019; coalition in a supply
 chain, such as automobile or Information Technology supply chain.
Journal: International Journal of Production Research 
Pages: 170-185 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1055848 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055848 
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Template-Type: ReDIF-Article 1.0
Author-Name: Faicel Hnaien 
Author-X-Name-First: Faicel 
Author-X-Name-Last: Hnaien 
Author-Name: Alexandre Dolgui 
Author-X-Name-First: Alexandre 
Author-X-Name-Last: Dolgui 
Author-Name: Desheng Dash Wu 
Author-X-Name-First: Desheng Dash 
Author-X-Name-Last: Wu 
Title: Single-period inventory model for one-level assembly system with stochastic lead times and demand 
Abstract:
 Replenishment planning of an assembly system with one type of finished
 product assembled from <inline-formula id="ILM0001"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1066518_ilm0001.gif"/></inline-formula> different types
 of components is considered. The components are procured from
 <inline-formula id="ILM0002"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1066518_ilm0002.gif"/></inline-formula> diverse
 external suppliers to satisfy finished product demand. It is supposed that
 the component lead times and finished product demand are random discrete
 variables. The assembly company must determine what are the best
 quantities of components and when is the right time to order. The
 objective is to minimise the total cost which is composed of holding
 component costs, tardiness penalties, lost sales and surplus item costs
 for finished products. A single-period analytical model is proposed.
 Several properties of the objective function are proven. They are used to
 develop a Branch and Bound algorithm. Numerical tests for the algorithm
 are presented. Five heuristics based on Newsvendor model for lead time and
 demand are proposed and compared with the Branch and Bound algorithm.
 These tests show that the suggested Branch and Bound algorithm can solve
 large size problems within a short time. The proposed heuristics but one
 are not competitive with the Branch and Bound algorithm. The truncated
 version of Branch and Bound gives better results. The model suggested is
 better adapted to actual contract assembler environments, more realistic
 and can better approximate real-life industrial situations. The proposed
 exact algorithm provides optimal solutions for all discrete distributions
 of probabilities of lead times and demand. A new general approach to
 design such discrete optimisation algorithms is presented.
Journal: International Journal of Production Research 
Pages: 186-203 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1066518 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1066518 
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Template-Type: ReDIF-Article 1.0
Author-Name: Yingshuai Zhao 
Author-X-Name-First: Yingshuai 
Author-X-Name-Last: Zhao 
Author-Name: Xiaobo Zhao 
Author-X-Name-First: Xiaobo 
Author-X-Name-Last: Zhao 
Title: How a competing environment influences newsvendor ordering decisions 
Abstract:
 We conduct an experimental study on the decision biases in a scenario in
 which two newsvendors compete for a common market. If stock-out occurs at
 one newsvendor, the unsatisfied demand is reallocated to the competitor.
 Following the existing theory, an experiment of competing games with high-
 and low-profit settings is conducted with a control experiment of a
 standard newsvendor scenario for reference. The results indicate that
 compared with the single scenario, a competing environment can cause
 participants to significantly increase their ordering levels in the
 high-profit group and increase their ordering oscillations in the
 low-profit group. In addition, we propose a behavioural model by combining
 the logit choice rule and mental accounting. The model fits the
 experimental data satisfactorily, and the estimation of the parameters
 indicates that the participants in the high-profit group tend to ignore
 distractions from competitors, while the participants in the low-profit
 group are highly influenced by their competitors. Observations from this
 study suggest that managers should pay careful attention to different
 profit-margin products in a competing environment.
Journal: International Journal of Production Research 
Pages: 204-214 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1034330 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1034330 
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Template-Type: ReDIF-Article 1.0
Author-Name: Ulrike Ritzinger 
Author-X-Name-First: Ulrike 
Author-X-Name-Last: Ritzinger 
Author-Name: Jakob Puchinger 
Author-X-Name-First: Jakob 
Author-X-Name-Last: Puchinger 
Author-Name: Richard F. Hartl 
Author-X-Name-First: Richard F. 
Author-X-Name-Last: Hartl 
Title: A survey on dynamic and stochastic vehicle routing problems 
Abstract:
 Research on dynamic and stochastic vehicle routing problems received
 increasing interest in the last decade. It considers a novel problem
 class, aiming at an appropriate handling of dynamic events combined with
 the incorporation of stochastic information about possible future events.
 This survey summarises the recent literature in this area. Besides, the
 classification according to the available stochastic information, a new
 classification based on the point in time where substantial computational
 effort for determining decisions or decision policies arises, is
 introduced. Furthermore, the difference in solution quality is analysed
 between approaches which consider either purely dynamic or stochastic
 problems compared to those which consider both, stochastic and dynamic
 aspects. A graphical representation demonstrates the strength of the
 reviewed approaches incorporating dynamic and stochastic information. The
 survey also gives an overview on the intensity of research for the
 different problem classes and its benefit in recent years. Finally,
 guidelines and promising directions for further research are presented.
Journal: International Journal of Production Research 
Pages: 215-231 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1043403 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1043403 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Dongfei Fu 
Author-X-Name-First: Dongfei 
Author-X-Name-Last: Fu 
Author-Name: Clara M. Ionescu 
Author-X-Name-First: Clara M. 
Author-X-Name-Last: Ionescu 
Author-Name: El-Houssaine Aghezzaf 
Author-X-Name-First: El-Houssaine 
Author-X-Name-Last: Aghezzaf 
Author-Name: Robin De Keyser 
Author-X-Name-First: Robin 
Author-X-Name-Last: De Keyser 
Title: A constrained EPSAC approach to inventory control for a benchmark supply chain system 
Abstract:
 The design of an appropriate inventory control policy for a supply chain
 (SC) plays an essential role in tempering inventory instability and
 bullwhip effect. Several constraints are commonly encountered in actual
 operations so managers are required to take these physical restrictions
 into account when designing the inventory control policy. Model predictive
 control (MPC) appears as a promising solution to this issue, due to its
 capability of finding optimal control actions for a constrained SC system.
 Therefore, the inventory control problem for a benchmark SC is solved
 using the extended prediction self-adaptive control approach to MPC. To
 extend methodologies in our previous work, the control framework relies on
 generic process model and incorporates the physical constraints arising
 from practical operations to form the general constrained optimisation
 problems. The managers can choose from decentralised and centralised
 control structures according to specific informational and organisational
 factors of their SCs. The proposed control schemes in this study may be
 appropriate for industrial practice because the designed policy can bring
 a reduction of over 30% in operating cost and a significant increase of
 customer satisfaction level compared with that of the conventional policy.
Journal: International Journal of Production Research 
Pages: 232-250 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1070214 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1070214 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Richard Lackes 
Author-X-Name-First: Richard 
Author-X-Name-Last: Lackes 
Author-Name: Philipp Schl&#xfc;ter 
Author-X-Name-First: Philipp 
Author-X-Name-Last: Schl&#xfc;ter 
Author-Name: Markus Siepermann 
Author-X-Name-First: Markus 
Author-X-Name-Last: Siepermann 
Title: The impact of contract parameters on the supply chain performance under different power constellations 
Abstract:
 Reporting forecast data is a common method used to improve the functioning
 of supply chains (SCs) and to reduce supply shortages. Customers tend to
 report the maximum possible demand as a forecast if restrictions are
 missing. Such a forecast is useless for suppliers. Hence, special
 contracts are needed to enhance the value of forecast data and therefore
 the cooperation between SC partners. In this paper, such a contract is
 presented. It encourages the customer to report a more realistic forecast.
 Deviations from the reported forecast are punished in different ways: If
 the customer reported too much and wants to release less than what was
 reported, he has to pay a penalty. On the other hand, the customer has the
 flexibility to purchase more than reported to meet the demand on his
 outlet but at the cost of an additional fee. This paper analyses how
 different contract parameters affect the performance of the SC, in
 particular when the bargaining power of customer and supplier is not
 equally distributed. Results show that the supplier and therefore the SC
 is better off if the supplier leaves the contractual cost parameters
 untouched but hides the true value of flexibility, especially when the
 customer is less powerful than the supplier.
Journal: International Journal of Production Research 
Pages: 251-264 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1076943 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076943 
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Template-Type: ReDIF-Article 1.0
Author-Name: V.L.M. Spiegler 
Author-X-Name-First: V.L.M. 
Author-X-Name-Last: Spiegler 
Author-Name: A.T. Potter 
Author-X-Name-First: A.T. 
Author-X-Name-Last: Potter 
Author-Name: M.M. Naim 
Author-X-Name-First: M.M. 
Author-X-Name-Last: Naim 
Author-Name: D.R. Towill 
Author-X-Name-First: D.R. 
Author-X-Name-Last: Towill 
Title: The value of nonlinear control theory in investigating the underlying dynamics and resilience of a grocery supply chain 
Abstract:
 In an empirical context, a method to use nonlinear control theory in the
 dynamic analysis of supply chain resilience is developed and tested. The
 method utilises block diagram development, transfer function formulation,
 describing function representation of nonlinearities and simulation. Using
 both &#x2018;shock&#x2019; or step response and &#x2018;filter&#x2019; or
 frequency response lenses, a system dynamics model is created to analyse
 the resilience performance of a distribution centre replenishment system
 at a large grocery retailer. Potential risks for the retailer&#x2019;s
 resilience performance include the possibility of a mismatch between
 supply and demand, as well as serving the store inefficiently and causing
 on-shelf stock-outs. Thus, resilience is determined by investigating the
 dynamic behaviour of stock and shipment responses. The method allows
 insights into the nonlinear system control structures that would not be
 evident using simulation alone, including a better understanding of the
 influence of control parameters on dynamic behaviour, the identification
 of inventory offsets potentially leading to &#x2018;drift&#x2019;, the
 impact of nonlinearities on supply chain performance and the minimisation
 of simulation experiments.
Journal: International Journal of Production Research 
Pages: 265-286 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1076945 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076945 
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:1:p:265-286




Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoling Xu 
Author-X-Name-First: Xiaoling 
Author-X-Name-Last: Xu 
Author-Name: Jennifer Shang 
Author-X-Name-First: Jennifer 
Author-X-Name-Last: Shang 
Author-Name: Haiyan Wang 
Author-X-Name-First: Haiyan 
Author-X-Name-Last: Wang 
Author-Name: Wen-Chyuan Chiang 
Author-X-Name-First: Wen-Chyuan 
Author-X-Name-Last: Chiang 
Title: Optimal production and inventory decisions under demand and production disruptions 
Abstract:
 Unanticipated events may take place and disrupt demand and/or production
 in a supply chain. Conditional on the type, magnitude and duration of
 disruptions, changes may be called to revise the original production plan.
 We analyse different disruption scenarios and propose optimal
 production--inventory models for products facing demand and production
 disruptions. To lower the cost, we optimise the production run time,
 purchasing times and order quantity for the manufacturer. Numerical
 experiments are conducted to examine the influences of disruption time and
 magnitude on optimal production and purchasing decisions.
Journal: International Journal of Production Research 
Pages: 287-301 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1073402 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1073402 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:1:p:287-301




Template-Type: ReDIF-Article 1.0
Author-Name: Masoud Kamalahmadi 
Author-X-Name-First: Masoud 
Author-X-Name-Last: Kamalahmadi 
Author-Name: Mahour Mellat-Parast 
Author-X-Name-First: Mahour 
Author-X-Name-Last: Mellat-Parast 
Title: Developing a resilient supply chain through supplier flexibility and reliability assessment 
Abstract:
 In this study, we examine the optimal allocation of demand across a set of
 suppliers in a supply chain that is exposed to supply risk and
 environmental risk. A two-stage mixed-integer programming model is used to
 develop a flexible sourcing strategy under disruptions. Our model
 integrates supplier selection and demand allocation with transportation
 channel selection and provides contingency plans to mitigate the negative
 impacts of disruptions and minimise total network costs. Finally, a
 numerical example is presented to illustrate the model and provide
 insights. The findings suggest that developing contingency plans using
 flexibility in suppliers&#x2019; production capacity is an effective
 strategy for firms to mitigate the severity of disruptions. We also show
 that flexibility and reliability of the suppliers and regions play a
 significant role in determining contingency plans for during disruption.
 Findings generally show that highly flexible suppliers receive less
 allocation, and their flexible capacity is reserved for disruptions. For
 firms that do not incorporate risk management into supplier selection and
 allocation, the recommendation is to source from fewer, more reliable
 suppliers with less risk of disruption. Our findings also emphasise that
 the type of disruption has important implications for supplier selection
 and demand allocation. This study highlights the supply chain risk
 management strategy of regionalising as a means for minimising the impact
 of environmental disruptions.
Journal: International Journal of Production Research 
Pages: 302-321 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1088971 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1088971 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:1:p:302-321




Template-Type: ReDIF-Article 1.0
Author-Name: Aijun Liu 
Author-X-Name-First: Aijun 
Author-X-Name-Last: Liu 
Author-Name: John Fowler 
Author-X-Name-First: John 
Author-X-Name-Last: Fowler 
Author-Name: Michele Pfund 
Author-X-Name-First: Michele 
Author-X-Name-Last: Pfund 
Title: Dynamic co-ordinated scheduling in the supply chain considering flexible routes 
Abstract:
 In Supply chain (SC) environments, schedules inevitably experience various
 unexpected disruptions. In these cases, rescheduling is essential to
 minimise the negative impact on the performance of the system. In this
 study, a hybrid rescheduling technique is developed for solving
 coordinated manufacturing tasks scheduling problems with due date changes
 and machine breakdowns. According to the dynamic features of this problem,
 a strategy combined with event and periodic driven methods is proposed to
 improve the stability and robustness of manufacturing performance in a
 coordinated SC. Moreover, an application case is introduced to test and
 evaluate the effect of different initialisations in two types of
 disruption scenarios. The experimental results show that the proposed
 rescheduling technique has good effectiveness and efficiency in the
 coordinated manufacturing environment.
Journal: International Journal of Production Research 
Pages: 322-335 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1115908 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1115908 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:1:p:322-335




Template-Type: ReDIF-Article 1.0
Author-Name: Michael Phelan 
Author-X-Name-First: Michael 
Author-X-Name-Last: Phelan 
Author-Name: Se&#xe1;n McGarraghy 
Author-X-Name-First: Se&#xe1;n 
Author-X-Name-Last: McGarraghy 
Title: Grammatical evolution in developing optimal inventory policies for serial and distribution supply chains 
Abstract:
 Recently, there has been a growing literature on biologically inspired
 algorithms, particularly genetic algorithms and genetic programming,
 applied to supply chain modelling and inventory control optimisation. Due
 to the rigidity of the genetic algorithms approach, it is difficult to
 change the underlying model logic and add richness to the supply chain.
 While genetic programming provides a more flexible approach than that
 provided by genetic algorithms, to date its application has been limited
 to small supply chain modelling problems in relation to optimal inventory
 policies. This research applies Grammatical Evolution, a relatively new
 biologically inspired algorithm, to the field of supply chain
 optimisation, employing human readable rules called grammars. These
 grammars provide a single mechanism to describe a variety of complex
 structures and can incorporate the domain knowledge of the practitioner to
 bias the algorithm towards regions of the search space containing better
 solutions. Results are presented showing Grammatical Evolution is at least
 competitive in cost terms, and superior in flexibility, with these methods
 applicable to any supply chain of the serial or distribution type.
 Furthermore, Grammatical Evolution shows an adaptive ability that augurs
 well for supply chains in dynamic environments, such as disruption.
Journal: International Journal of Production Research 
Pages: 336-364 
Issue: 1 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1085653 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1085653 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:1:p:336-364




Template-Type: ReDIF-Article 1.0
Author-Name: Avi Herbon 
Author-X-Name-First: Avi 
Author-X-Name-Last: Herbon 
Title: Optimal piecewise-constant price under heterogeneous sensitivity to product freshness 
Abstract:
 When perishable products are priced uniformly, regardless of the amount of
 time remaining until expiration, consumers may gravitate towards fresher
 products, leaving some inventory unsold. This research considers dynamic
 pricing policies as well as replenishment policies in the context of
 perishable products with a fixed shelf life. Consumers are assumed to be
 heterogeneous in their sensitivity to freshness, i.e. their willingness to
 pay more for fresher products. We develop a model for identifying an
 optimal (profit-maximising) dynamic pricing policy and for evaluating the
 extent to which both the retailer and the consumer benefit from the
 implementation of a dynamic pricing policy as opposed to a static policy.
 The model assumes that the retailer is able to utilise knowledge regarding
 the heterogeneous characteristics of incoming customers (e.g. the retailer
 can gather specific information about customers&#x2019; historical
 purchases). Unexpectedly, it is proven that in an optimal pricing policy,
 the retailer should assign a lower price to fresher products and then
 raise the price as the products approach expiration. A numerical
 illustration shows that profits are strongly influenced by the volatility
 of consumer sensitivity to freshness; specifically, this variable has the
 potential to reduce optimal profits by up to 8%.
Journal: International Journal of Production Research 
Pages: 365-385 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2014.997402 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.997402 
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov 
Author-X-Name-First: Dmitry 
Author-X-Name-Last: Ivanov 
Author-Name: Alexandre Dolgui 
Author-X-Name-First: Alexandre 
Author-X-Name-Last: Dolgui 
Author-Name: Boris Sokolov 
Author-X-Name-First: Boris 
Author-X-Name-Last: Sokolov 
Author-Name: Frank Werner 
Author-X-Name-First: Frank 
Author-X-Name-Last: Werner 
Author-Name: Marina Ivanova 
Author-X-Name-First: Marina 
Author-X-Name-Last: Ivanova 
Title: A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0 
Abstract:
 Smart factories Industry 4.0 on the basis of collaborative cyber-physical
 systems represents a future form of industrial networks. Supply chains in
 such networks have dynamic structures which evolve over time. In these
 settings, short-term supply chain scheduling in smart factories Industry
 4.0 is challenged by temporal machine structures, different processing
 speed at parallel machines and dynamic job arrivals. In this study, for
 the first time, a dynamic model and algorithm for short-term supply chain
 scheduling in smart factories Industry 4.0 is presented. The peculiarity
 of the considered problem is the simultaneous consideration of both
 machine structure selection and job assignments. The scheduling approach
 is based on a dynamic non-stationary interpretation of the execution of
 the jobs and a temporal decomposition of the scheduling problem. The
 algorithmic realisation is based on a modified form of the continuous
 maximum principle blended with mathematical optimisation. A detailed
 theoretical analysis of the temporal decomposition and computational
 complexity is performed. The optimality conditions as well as the
 structural properties of the model and the algorithm are investigated.
 Advantages and limitations of the proposed approach are discussed.
Journal: International Journal of Production Research 
Pages: 386-402 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2014.999958 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.999958 
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Template-Type: ReDIF-Article 1.0
Author-Name: Teodor Gabriel Crainic 
Author-X-Name-First: Teodor Gabriel 
Author-X-Name-Last: Crainic 
Author-Name: Gilbert Laporte 
Author-X-Name-First: Gilbert 
Author-X-Name-Last: Laporte 
Title: Transportation in supply chain management: recent advances and research prospects 
Journal: International Journal of Production Research 
Pages: 403-404 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1120904 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1120904 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Anu Thomas 
Author-X-Name-First: Anu 
Author-X-Name-Last: Thomas 
Author-Name: Mohan Krishnamoorthy 
Author-X-Name-First: Mohan 
Author-X-Name-Last: Krishnamoorthy 
Author-Name: Jayendran Venkateswaran 
Author-X-Name-First: Jayendran 
Author-X-Name-Last: Venkateswaran 
Author-Name: Gaurav Singh 
Author-X-Name-First: Gaurav 
Author-X-Name-Last: Singh 
Title: Decentralised decision-making in a multi-party supply chain 
Abstract:
 In this paper, we consider multi-party coordination in a supply chain (SC)
 that consists of a set of independent producers and a set of resource
 managers. A decentralised decision-making approach is proposed for a coal
 SC, with three independent parties -- multiple mines, a rail operator and
 a terminal. The rail operator and the terminal act as common resource
 managers and connects the independent mines via a rail network. The
 objective of this SC is to efficiently use an independent rail operator to
 transport coal from different mines to meet the shipping demand at the
 terminal. The underlying coordination problem can be seen as a
 multi-resource constrained scheduling problem. A major part of this paper
 addresses the key challenges in a decentralised approach based on column
 generation (CG), which are to compute the value of a column, better upper
 bounds and to update the multipliers using decentralised methods. We have
 also discussed the mathematical models for different decision units, the
 CG algorithm and different strengthening methods. A comprehensive
 computational experiment based on randomly generated instances highlights
 the effect of decentralisation and the value of information-sharing. The
 proposed solution approaches can be extended to a multi-party case with
 any number of common resources.
Journal: International Journal of Production Research 
Pages: 405-425 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1096977 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1096977 
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Template-Type: ReDIF-Article 1.0
Author-Name: Yu-Chung Tsao 
Author-X-Name-First: Yu-Chung 
Author-X-Name-Last: Tsao 
Author-Name: Qinhong Zhang 
Author-X-Name-First: Qinhong 
Author-X-Name-Last: Zhang 
Author-Name: Tsung-Hui Chen 
Author-X-Name-First: Tsung-Hui 
Author-X-Name-Last: Chen 
Title: Multi-item distribution network design problems under volume discount on transportation cost 
Abstract:
 This study considers the distribution network design problems of
 multi-echelon, multi-item supply chains under volume (weight) discounts on
 transportation costs. Minimising the total network cost requires
 determining the following: (1) the service area of distribution centres
 (DCs); (2) the assignment of retail stores to DCs; and (3) the inventory
 volume at DCs. This study compares various replenishment policies and
 discusses the effects of such policies on distribution network design. In
 general, the results show that single-cluster replenishment is superior to
 joint cluster replenishment. However, joint cluster replenishment may be
 superior to single-cluster replenishment under volume (weight) discounts
 on transportation costs. The results additionally show that single-item
 replenishment is inferior to multi-item replenishment under volume
 (weight) discounts on transportation costs. All the problems are
 formulated as piecewise non-linear programming models with multiple
 variables. Algorithms are proposed for solving these piecewise non-linear
 programming problems. Several numerical studies demonstrate the solution
 procedures and the effects of changing parameters on decision-making.
Journal: International Journal of Production Research 
Pages: 426-443 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1018453 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1018453 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:426-443




Template-Type: ReDIF-Article 1.0
Author-Name: Li-Chih Wang 
Author-X-Name-First: Li-Chih 
Author-X-Name-Last: Wang 
Author-Name: Chen-Yang Cheng 
Author-X-Name-First: Chen-Yang 
Author-X-Name-Last: Cheng 
Author-Name: Wen-Kuan Wang 
Author-X-Name-First: Wen-Kuan 
Author-X-Name-Last: Wang 
Title: Flexible supply network planning for hybrid shipment: a case study of memory module industry 
Abstract:
 The modern supply chain network has geographically spread out across the
 globe. The performance of a customer service level is highly dependent on
 the effectiveness of its supply chain planning. To improve the service
 provided to downstream customers, planners must not only decide order
 allocation among multiple distribution centres but also consider reducing
 the order-to-delivery time. Directed shipment delivery from manufacturing
 sites provides the flexibility of direct shipment; however, it also makes
 order allocation more difficult. In this study, a flexible supply network
 planning (FSNP) model based on integer linear programming is developed for
 the memory module industry. In addition to multisite order allocation
 planning, the FSNP model explicitly considers directed shipment from
 manufacturing sites for reducing the order-to-delivery time. Furthermore,
 the combination of characteristics of the memory module industry, such as
 multilevel and multisite production environments, multiple-to-multiple
 product structures, transportation and production lead times and capacity
 constraints, makes FSNP highly complicated. The results of the experiments
 reveal that the FSNP model improves supply chain planning regarding order
 due date and inventory and transportation costs.
Journal: International Journal of Production Research 
Pages: 444-458 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1133939 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1133939 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Amirsaman Kheirkhah 
Author-X-Name-First: Amirsaman 
Author-X-Name-Last: Kheirkhah 
Author-Name: HamidReza Navidi 
Author-X-Name-First: HamidReza 
Author-X-Name-Last: Navidi 
Author-Name: Masume Messi Bidgoli 
Author-X-Name-First: Masume 
Author-X-Name-Last: Messi Bidgoli 
Title: A bi-level network interdiction model for solving the hazmat routing problem 
Abstract:
 In the current work, we considered the problem of hazardous material
 distribution where the distributer chooses the routes on the network, and
 a regulatory agency controls the behaviour of the distributer to traverse
 the specified routes. In these circumstances, the distributer sets to
 select some routes to minimise the total distributing costs. Mostly, this
 occurs due to selecting risky arcs in which more individuals are exposed
 to risk. To prevent this and increase the capability to deal with the risk
 of hazardous material transportation through roads, the regulatory agency
 obliges carriers to traverse through the most secure arcs, though imposing
 more distribution costs. The problem is modelled as a bi-level routing
 problem. The bi-level model is difficult to solve and may be ill-posed.
 Two meta-heuristic algorithms are proposed to solve the bi-level model,
 and some randomly generated problems are applied to show the applicability
 and efficiency of the proposed algorithms.
Journal: International Journal of Production Research 
Pages: 459-471 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1084061 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1084061 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:459-471




Template-Type: ReDIF-Article 1.0
Author-Name: Debjit Roy 
Author-X-Name-First: Debjit 
Author-X-Name-Last: Roy 
Author-Name: Akash Gupta 
Author-X-Name-First: Akash 
Author-X-Name-Last: Gupta 
Author-Name: Ren&#xe9; B.M. De Koster 
Author-X-Name-First: Ren&#xe9; B.M. 
Author-X-Name-Last: De Koster 
Title: A non-linear traffic flow-based queuing model to estimate container terminal throughput with AGVs 
Abstract:
 Efficient handling of containers at a terminal can reduce the overall
 vessel sojourn times and minimise operational costs. The internal
 transport of containers in these terminals is performed by vehicles that
 share a common guide path. The throughput capacity of a terminal may
 increase by increasing the number of vehicles; however, simultaneously
 congestion may reduce the effective vehicle speed. We model this situation
 accurately using a traffic flow-based closed queuing network model. The
 vehicle internal transport is modelled using a load-dependent server that
 captures the interaction between the number of vehicles in a transport
 segment and the effective vehicle speed. Using a non-linear traffic flow
 model, we show that the throughput reductions due to vehicle congestion
 can be as large as 85%. Hence, the effect of vehicle congestion during
 internal transport cannot be ignored. The model can also be used to
 determine the appropriate number of vehicles required to achieve the
 required terminal throughput by explicitly considering the effect of
 vehicle congestion.
Journal: International Journal of Production Research 
Pages: 472-493 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1056321 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056321 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: W. Nassief 
Author-X-Name-First: W. 
Author-X-Name-Last: Nassief 
Author-Name: I. Contreras 
Author-X-Name-First: I. 
Author-X-Name-Last: Contreras 
Author-Name: R. As&#x2019;ad 
Author-X-Name-First: R. 
Author-X-Name-Last: As&#x2019;ad 
Title: A mixed-integer programming formulation and Lagrangean relaxation for the cross-dock door assignment problem 
Abstract:
 In a cross-dock, goods are unloaded from incoming trucks, consolidated
 according to their destinations, and then, loaded into outgoing trucks
 with little or no storage in between. In this paper, we study the
 cross-dock door assignment problem in which the assignment of incoming
 trucks to strip doors, and outgoing trucks to stack doors is determined,
 with the objective of minimising the total material handling cost. We
 present a new mixed integer programming formulation which is embedded into
 a Lagrangean relaxation that exploits the special structure of the problem
 to obtain bounds on the optimal solution value. A primal heuristic is used
 at every iteration of the Lagrangean relaxation to obtain high quality
 feasible solutions. Computational results obtained on benchmark instances
 (with up to 20 origins and destinations, and 10 strip and stack doors) and
 on a new and more difficult set of instances (with up to 50 origins and
 destinations, and 30 strip and stack doors) confirm the efficiency of the
 algorithm.
Journal: International Journal of Production Research 
Pages: 494-508 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2014.1003664 
File-URL: http://hdl.handle.net/10.1080/00207543.2014.1003664 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
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Template-Type: ReDIF-Article 1.0
Author-Name: Vincent F. Yu 
Author-X-Name-First: Vincent F. 
Author-X-Name-Last: Yu 
Author-Name: Parida Jewpanya 
Author-X-Name-First: Parida 
Author-X-Name-Last: Jewpanya 
Author-Name: Voratas Kachitvichyanukul 
Author-X-Name-First: Voratas 
Author-X-Name-Last: Kachitvichyanukul 
Title: Particle swarm optimization for the multi-period cross-docking distribution problem with time windows 
Abstract:
 Cross-docking has emerged as a new technique in supply chain management to
 replace the warehouse concept in the retail industry. This paper proposes
 a multi-period cross-docking distribution problem that consists of
 manufacturers, cross-docks and customers. This model is formulated for
 cases that consider multiple products, consolidation of customer orders
 and time windows that are available in multiple periods. The objective
 function is to minimise the total cost, which includes transportation
 cost, inventory cost and penalty cost. The penalty cost arises when demand
 remains in each period that cannot be satisfied. To deal with the
 complexity of the problem, an algorithm is developed based on particle
 swarm optimisation (PSO) with multiple social learning terms, GLNPSO, with
 two solution representations. The solution representations are a
 one-period solution representation (OP-SR) and a multi-period solution
 representation (MP-SR). The GLNPSO-based algorithm performs well in
 solving this problem. Moreover, both representations are proven effective
 when comparing the solution quality and computational time with those
 results obtained from CPLEX. In terms of quality, the MP-SR solution is
 better than the OP-SR solution for both stable and fluctuating demand
 instances. However, MP-SR requires more computational effort than OP-SR.
Journal: International Journal of Production Research 
Pages: 509-525 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1037933 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1037933 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:509-525




Template-Type: ReDIF-Article 1.0
Author-Name: Vincent F. Yu 
Author-X-Name-First: Vincent F. 
Author-X-Name-Last: Yu 
Author-Name: Shin-Yu Lin 
Author-X-Name-First: Shin-Yu 
Author-X-Name-Last: Lin 
Title: Solving the location-routing problem with simultaneous pickup and delivery by simulated annealing 
Abstract:
 The study concerns the location-routing problem with simultaneous pickup
 and delivery (LRPSPD) in which the pickup and delivery take place at the
 same time for each customer. The goal is to determine the facility
 locations and vehicle routes in order to minimise the total system cost as
 a sum of facility opening cost, vehicle fixed cost and vehicle travel
 cost. A simulated annealing (SA) heuristic is proposed for the problem and
 extensive computational experiments are conducted. The results show that
 the proposed SA effectively solves LRPSPD and outperforms existing exact
 approaches in terms of solution quality.
Journal: International Journal of Production Research 
Pages: 526-549 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1085655 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1085655 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:526-549




Template-Type: ReDIF-Article 1.0
Author-Name: Jiahong Zhao 
Author-X-Name-First: Jiahong 
Author-X-Name-Last: Zhao 
Author-Name: Fumin Zhu 
Author-X-Name-First: Fumin 
Author-X-Name-Last: Zhu 
Title: A multi-depot vehicle-routing model for the explosive waste recycling 
Abstract:
 The explosive waste recycling is a significant concern because it has
 immense impacts on economy and safety during its transportation among
 multiple depots. A number of studies on the hazardous waste management
 have been documented in the past. However, the vehicle-routing
 optimisation, including the tour planning, the vehicle acquisition and the
 return-trip design of such activities, has been overlooked. In this study,
 we develop a multi-depot vehicle-routing model with the minimisations of
 total cost and total risk. Unlike other works in the literature, this
 model is formulated through the two-commodity flow formulation, and it is
 characterised by simultaneously planning tours and vehicle acquisitions
 for the explosive waste collection, and designing the return-trips between
 collection centres and recycling centres. To solve this bi-objective
 problem, a modified lexicographic weighted Tchebycheff method is proposed.
 A case study in Nanchuan of South-west China and related test instances
 are provided to elucidate the developed approach.
Journal: International Journal of Production Research 
Pages: 550-563 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1111533 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1111533 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Henrik Andersson 
Author-X-Name-First: Henrik 
Author-X-Name-Last: Andersson 
Author-Name: Marielle Christiansen 
Author-X-Name-First: Marielle 
Author-X-Name-Last: Christiansen 
Author-Name: Guy Desaulniers 
Author-X-Name-First: Guy 
Author-X-Name-Last: Desaulniers 
Title: A new decomposition algorithm for a liquefied natural gas inventory routing problem 
Abstract:
 We consider an inventory routing problem (IRP) in the liquefied natural
 gas (LNG) supply chain, called the LNG-IRP. Here, an actor is responsible
 for the LNG production and inventory management at the liquefaction
 plants, the routing and scheduling of a heterogeneous fleet of LNG ships,
 as well as the inventories and sales at the regasification terminals.
 Furthermore, all ports have a limited number of berths available for
 loading and unloading. The LNG-IRP is more complicated than many other
 maritime inventory routing problems because a constant rate of the cargo
 evaporates in the tanks each day and is used as fuel during
 transportation. In addition, a variable number of tanks are unloaded at
 the regasification terminals. We introduce a new path flow formulation for
 this problem arising from a novel decomposition scheme based on parts of a
 ship schedule, called duties. A ship schedule for the entire planning
 horizon can be divided into duties consisting of a visit to a liquefaction
 plant, then one or two visits to a regasification terminal before ending
 in a liquefaction plant. The solution method suggested is based on a
 priori generation of duties, and the formulation is strengthened by valid
 inequalities. The same problem was previously solved by a
 branch-price-and-cut algorithm for a schedule-based formulation.
 Computational results show that the new formulation provides tighter
 bounds than the previous schedule-based formulation. Furthermore, on a set
 of 27 benchmark instances, the proposed algorithm clearly outperforms the
 previous branch-price-and-cut algorithm both with regard to computational
 time and the number of problems solved within a 10-h time limit.
Journal: International Journal of Production Research 
Pages: 564-578 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1037024 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1037024 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:564-578




Template-Type: ReDIF-Article 1.0
Author-Name: F. Hooshmand Khaligh 
Author-X-Name-First: F. 
Author-X-Name-Last: Hooshmand Khaligh 
Author-Name: S.A. MirHassani 
Author-X-Name-First: S.A. 
Author-X-Name-Last: MirHassani 
Title: A mathematical model for vehicle routing problem under endogenous uncertainty 
Abstract:
 In this study, a multistage stochastic programming (SP) model is presented
 for a variant of single-vehicle routing problem with stochastic demands
 from a dynamic viewpoint. It is assumed that the actual demand of a
 customer becomes known only when the customer is visited. This problem
 falls into the category of SP with endogenous uncertainty and hence, the
 scenario tree is decision-dependent. Therefore, nonanticipativity of
 decisions is ensured by conditional constraints making up a large portion
 of total constraints. Thus, a novel approach is proposed that considerably
 reduces the problem size without any effect on the solution space.
 Computational results on some test problems are reported.
Journal: International Journal of Production Research 
Pages: 579-590 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1057625 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1057625 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:579-590




Template-Type: ReDIF-Article 1.0
Author-Name: Morteza Keshtkaran 
Author-X-Name-First: Morteza 
Author-X-Name-Last: Keshtkaran 
Author-Name: Koorush Ziarati 
Author-X-Name-First: Koorush 
Author-X-Name-Last: Ziarati 
Author-Name: Andrea Bettinelli 
Author-X-Name-First: Andrea 
Author-X-Name-Last: Bettinelli 
Author-Name: Daniele Vigo 
Author-X-Name-First: Daniele 
Author-X-Name-Last: Vigo 
Title: Enhanced exact solution methods for the Team Orienteering Problem 
Abstract:
 The Team Orienteering Problem (TOP) is one of the most investigated
 problems in the family of vehicle routing problems with profits. In this
 paper, we propose a Branch-and-Price approach to find proven optimal
 solutions to TOP. The pricing sub-problem is solved by a bounded
 bidirectional dynamic programming algorithm with decremental state space
 relaxation featuring a two-phase dominance rule relaxation. The new method
 is able to close 17 previously unsolved benchmark instances. In addition,
 we propose a Branch-and-Cut-and-Price approach using subset-row
 inequalities and show the effectiveness of these cuts in solving TOP.
Journal: International Journal of Production Research 
Pages: 591-601 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1058982 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1058982 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:591-601




Template-Type: ReDIF-Article 1.0
Author-Name: Ana Maria Anaya-Arenas 
Author-X-Name-First: Ana Maria 
Author-X-Name-Last: Anaya-Arenas 
Author-Name: Thomas Chabot 
Author-X-Name-First: Thomas 
Author-X-Name-Last: Chabot 
Author-Name: Jacques Renaud 
Author-X-Name-First: Jacques 
Author-X-Name-Last: Renaud 
Author-Name: Angel Ruiz 
Author-X-Name-First: Angel 
Author-X-Name-Last: Ruiz 
Title: Biomedical sample transportation in the province of Quebec: a case study 
Abstract:
 Biomedical sample management plays a central role in an efficient health
 care system and requires important resources. Based on our collaboration
 with the Quebec&#x2019;s <italic>Minist&#xe8;re de la Sant&#xe9; et des
 Services sociaux</italic> (Ministry of Health and Social Services), this
 article describes the challenging context of biomedical sample
 transportation in the Canadian province of Quebec. It is modelled on a
 variant of the multi-trip vehicle routing problem with time windows where
 routes need to be planned from a <italic>laboratory</italic> to satisfy
 the multiple pick-up requests of each <italic>sample collection
 centre</italic> under some practical constraints. We propose and evaluate
 two alternative mathematical formulations, as well as fast heuristics, to
 minimise total transportation distances. The performance of the proposed
 methods is assessed over a large case study based on the network of
 laboratories in the province of Quebec.
Journal: International Journal of Production Research 
Pages: 602-615 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1018455 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1018455 
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Template-Type: ReDIF-Article 1.0
Author-Name: Kamal Lamsal 
Author-X-Name-First: Kamal 
Author-X-Name-Last: Lamsal 
Author-Name: Philip C. Jones 
Author-X-Name-First: Philip C. 
Author-X-Name-Last: Jones 
Author-Name: Barrett W. Thomas 
Author-X-Name-First: Barrett W. 
Author-X-Name-Last: Thomas 
Title: Continuous time scheduling for sugarcane harvest logistics in Louisiana 
Abstract:
 Despite a growing global appetite for sugar as both a foodstuff and a fuel
 source, there exists limited literature that explores sugarcane
 operations. In this paper, we look at the scheduling harvest and logistics
 operations in the state of Louisiana in the United States. These
 operations account for significant portions of the total sugarcane
 production costs. We develop an integer programming model for coordinating
 harvest and transport of sugarcane. The model seeks to reduce vehicle
 waiting time at the mill by maximising the minimum gap between two
 successive arrivals at the mill. To help improve tractability, we
 introduce valid inequalities and optimality cuts. We also demonstrate how
 to adapt solutions from a previous discrete-time model. Our results show
 that arrivals can easily be coordinated to reduce truck waiting time at
 the mill.
Journal: International Journal of Production Research 
Pages: 616-627 
Issue: 2 
Volume: 54 
Year: 2016 
Month: 1 
X-DOI: 10.1080/00207543.2015.1052156 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1052156 
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehdi Amiri-Aref 
Author-X-Name-First: Mehdi 
Author-X-Name-Last: Amiri-Aref 
Author-Name: Reza Zanjirani Farahani 
Author-X-Name-First: Reza 
Author-X-Name-Last: Zanjirani Farahani 
Author-Name: Nikbakhsh Javadian 
Author-X-Name-First: Nikbakhsh 
Author-X-Name-Last: Javadian 
Author-Name: Walid Klibi 
Author-X-Name-First: Walid 
Author-X-Name-Last: Klibi 
Title: A rectilinear distance location--relocation problem with a probabilistic restriction: mathematical modelling and solution approaches 
Abstract:
 In this study, we have considered a multi-period centre facility
 location--relocation problem in the presence of a probabilistic polyhedral
 barrier uniformly distributed on a horizontal barrier route in rectilinear
 plane. The objective function of this location--relocation problem is the
 minimisation of the cost of maximum expected rectilinear barrier distance
 from demand points to the new facility plus the relocation cost (i.e. a
 changeover cost at the beginning of each period) in the form of a mixed
 integer quadratic-constrained mathematical programming. The computational
 results show that the non-linear solver of commercial software LINGO is
 only effective in solving small-sized problems. A linear approximation for
 the system constraints is proposed so that a new mixed integer linear
 programming model is generated which is solvable via CPLEX optimisation
 software. Moreover, we proposed a problem decomposition procedure that
 reduces the multi-period problem into a number of single-period problems
 with some modifications. To show the efficiency of the model and solution
 methodologies, a broad range of numerical examples are performed. Results
 indicate that the developed problem decomposition procedure obtains the
 near-optimal solution comparatively with the results obtained from the
 non-linear solver of LINGO, and that the lower bound problem can be useful
 for large-sized problems in a reasonable time. Moreover, a practical case
 example to show the model validity in real world is solved and to reality
 check from practice, results are compared with the problem without
 barrier.
Journal: International Journal of Production Research 
Pages: 629-646 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1013642 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1013642 
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Template-Type: ReDIF-Article 1.0
Author-Name: Lei Li 
Author-X-Name-First: Lei 
Author-X-Name-Last: Li 
Author-Name: YanLing Qian 
Author-X-Name-First: YanLing 
Author-X-Name-Last: Qian 
Author-Name: Kai Du 
Author-X-Name-First: Kai 
Author-X-Name-Last: Du 
Author-Name: YongMin Yang 
Author-X-Name-First: YongMin 
Author-X-Name-Last: Yang 
Title: Analysis of approximately balanced production lines 
Abstract:
 This paper develops two analytical formulas for estimating the throughput
 of a reliable production line with exponential service times and finite
 intermediate buffers. The formulas apply in the case of an approximately
 balanced line with identical buffers or near optimal buffer allocations,
 where the processing times of the machines are close to each other but not
 necessarily the same. The derivation of the formulas is based on the
 standard decomposition method. Moreover, it is proved that, in general
 cases, both formulas provide upper bounds for the throughput obtained by
 the decomposition method. Numerical experiments show that the proposed
 formulas achieve good accuracy for approximately balanced production
 lines. Finally, the formulas are applied to the buffer allocation problem,
 and two closed-form expressions are obtained for estimating the smallest
 buffer capacity which is necessary to achieve the desired throughput.
Journal: International Journal of Production Research 
Pages: 647-664 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1015750 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1015750 
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Template-Type: ReDIF-Article 1.0
Author-Name: Yifei Zhao 
Author-X-Name-First: Yifei 
Author-X-Name-Last: Zhao 
Author-Name: Stein W. Wallace 
Author-X-Name-First: Stein W. 
Author-X-Name-Last: Wallace 
Title: Appraising redundancy in facility layout 
Abstract:
 Introducing redundancy into facility layout designs reduces material
 handling costs by shortening the total distance travelled by materials and
 tools, since redundancy allows for shorter flow routes. In our setting,
 jobs and volumes (demands) are random, and machines have limited
 capacities. We present a model for determining which machine types should
 be duplicated (i.e. having more copies than necessary), given the number
 of extra positions available in the facility. The model is naturally an
 extension of the quadratic assignment model, and hence very hard, if not
 impossible, to solve exactly for even moderate problem dimensions. A
 myopic approach is proposed. We show numerically that the myopic approach
 is valid, before we, qualitatively, based on the approach, describe a
 decision-rule determining a good choice of redundant machine types. This
 very simple description produces the optimal choice of redundant machine
 types in most situations. In this way, our results add to the
 understanding of the problem itself, not just to its solution.
Journal: International Journal of Production Research 
Pages: 665-679 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1030041 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1030041 
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Template-Type: ReDIF-Article 1.0
Author-Name: &#x130;. Esra B&#xfc;y&#xfc;ktahtak&#x131;n 
Author-X-Name-First: &#x130;. Esra 
Author-X-Name-Last: B&#xfc;y&#xfc;ktahtak&#x131;n 
Author-Name: Joseph C. Hartman 
Author-X-Name-First: Joseph C. 
Author-X-Name-Last: Hartman 
Title: A mixed-integer programming approach to the parallel replacement problem under technological change 
Abstract:
 The parallel replacement problem under economies of scale (PRES)
 determines minimum cost replacement policies for each asset in a group of
 assets that operate in parallel and are subject to fixed and variable
 purchase costs. We study the mixed-integer programming formulation of PRES
 under technological change by incorporating capacity gains into the model
 such that newer, technologically advanced assets have higher capacity than
 assets purchased earlier. We provide optimal solution characteristics and
 insights about the economics of the problem and derive associated cutting
 planes for optimising the problem. Computational experiments illustrate
 that the inequalities are quite effective in solving PRES under
 technological change instances.
Journal: International Journal of Production Research 
Pages: 680-695 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1030470 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1030470 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohd Norzaimi Che Ani 
Author-X-Name-First: Mohd Norzaimi 
Author-X-Name-Last: Che Ani 
Author-Name: Jeng Feng Chin 
Author-X-Name-First: Jeng Feng 
Author-X-Name-Last: Chin 
Title: Self-reinforcing mechanisms for cellularisation: a longitudinal case study 
Abstract:
 Firms that adopt cellular manufacturing (CM) often need to restructure
 their products, personnel, equipment, factory management and organisation
 culture. Despite voluminous literature on CM, only a few case studies
 related to cellularisation exist. Therefore, to enhance understanding in
 this area, this paper presents a longitudinal case study on
 cellularisation in an electronic assembly plant. Six years of data were
 collected from the observations and discussions of an industrialist and an
 academician. Events instrumental to the persistence of CM were
 highlighted, with reference to path dependence analysis. Cellularisation
 is not entirely evolutionary or teleological but is an interplay of the
 two; it is significantly influenced by the positive feedback of
 self-reinforcing mechanisms after departing from critical junctures. The
 observed self-reinforcing mechanisms were expounded and divided into six
 categories.
Journal: International Journal of Production Research 
Pages: 696-711 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1033030 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1033030 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Aline A.S. Leao 
Author-X-Name-First: Aline A.S. 
Author-X-Name-Last: Leao 
Author-Name: Franklina M.B. Toledo 
Author-X-Name-First: Franklina M.B. 
Author-X-Name-Last: Toledo 
Author-Name: Jos&#xe9; Fernando Oliveira 
Author-X-Name-First: Jos&#xe9; Fernando 
Author-X-Name-Last: Oliveira 
Author-Name: Maria Ant&#xf3;nia Carravilla 
Author-X-Name-First: Maria Ant&#xf3;nia 
Author-X-Name-Last: Carravilla 
Title: A semi-continuous MIP model for the irregular strip packing problem 
Abstract:
 Solving nesting problems involves the waste minimisation in cutting
 processes, and therefore it is not only economically relevant for many
 industries but has also an important environmental impact, as the raw
 materials that are cut are usually a natural resource. However, very few
 exact approaches have been proposed in the literature for the nesting
 problem (also known as irregular packing problem), and the majority of the
 known approaches are heuristic algorithms, leading to suboptimal
 solutions. The few mathematical programming models known for this problem
 can be divided into discrete and continuous models, based on how the
 placement coordinates of the pieces to be cut are dealt with. In this
 paper, we propose an innovative semi-continuous mixed-integer programming
 model for two-dimensional cutting and packing problems with irregular
 shaped pieces. The model aims to exploit the advantages of the two
 previous classes of approaches and discretises the <inline-formula
 id="ILM0001"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1041571_ilm0001.gif"/></inline-formula>-axis while
 keeping the <inline-formula id="ILM0002"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1041571_ilm0002.gif"/></inline-formula>-coordinate
 continuous. The board can therefore be seen as a set of stripes.
 Computational results show that the model, when solved by a commercial
 solver, can deal with large problems and determine the optimal solution
 for smaller instances, but as it happens with discrete models, the optimal
 solution value depends on the discretisation step that is used.
Journal: International Journal of Production Research 
Pages: 712-721 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1041571 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1041571 
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Template-Type: ReDIF-Article 1.0
Author-Name: Olcay Polat 
Author-X-Name-First: Olcay 
Author-X-Name-Last: Polat 
Author-Name: Can B. Kalayci 
Author-X-Name-First: Can B. 
Author-X-Name-Last: Kalayci 
Author-Name: &#xd6;zcan Mutlu 
Author-X-Name-First: &#xd6;zcan 
Author-X-Name-Last: Mutlu 
Author-Name: Surendra M. Gupta 
Author-X-Name-First: Surendra M. 
Author-X-Name-Last: Gupta 
Title: A two-phase variable neighbourhood search algorithm for assembly line worker assignment and balancing problem type-II: an industrial case study 
Abstract:
 The assembly line worker assignment and balancing problem type-II
 (ALWABP-2) occurs when workers and tasks (where task times depend on
 workers&#x2019; skills) are to be simultaneously assigned to a fixed
 number of workstations with the goal of minimising the cycle time. In this
 study, a two-phase variable neighbourhood search (VNS) algorithm is
 proposed to solve the ALWABP-2 due to the NP-hard nature of this problem.
 In the first phase of the algorithm, a VNS approach is applied to assign
 tasks to workstations with the aim of minimising the cycle time while in
 the second phase, a variable neighbourhood descent method is applied to
 assign workers to workstations. The performance of the proposed algorithm
 is tested on well-known benchmark instances. In addition, the proposed
 algorithm has been used to solve a real case study from a consumer
 electronics company that manufactures LCD TVs. The results show that the
 algorithm is superior to the methods reported in the literature in terms
 of its higher efficiency and robustness. Furthermore, the algorithm is
 easy to implement and significantly improves the performance of the final
 assembly line for the investigated LCD TV real case study.
Journal: International Journal of Production Research 
Pages: 722-741 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1055344 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055344 
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Template-Type: ReDIF-Article 1.0
Author-Name: Adil Baykaso&#x11f;lu 
Author-X-Name-First: Adil 
Author-X-Name-Last: Baykaso&#x11f;lu 
Author-Name: Fehmi Burcin Ozsoydan 
Author-X-Name-First: Fehmi Burcin 
Author-X-Name-Last: Ozsoydan 
Title: An improved approach for determination of index positions on CNC magazines with cutting tool duplications by integrating shortest path algorithm 
Abstract:
 Optimisation of automatic tool changer (ATC) indexing problem, where
 cutting tools are allocated to the stations on a turret magazine of a CNC
 machine, is one of the challenging problems in machining. The aim of the
 problem is to minimise the total indexing time of ATC. This problem
 becomes even more challenging if duplication of cutting tools is allowed
 and a bidirectional ATC is used. The problem has a unique feature which
 has not been stressed yet by other researchers, that is, although ATC
 indexing (master problem) is the main optimisation problem, objective
 function evaluation of this problem is a standalone optimisation problem
 (sub problem) indeed. Although an approximation algorithm does not
 guarantee optimality for the master problem, the subproblem must be solved
 optimally; otherwise, deficiencies arising from ill-defined objective
 function might be encountered. Considering this interesting future, a
 novel methodology, which employs a shortest path algorithm, is developed.
 Thus, the subproblem of this complicated problem can be optimally solved.
 Moreover, two metaheuristics, based on threshold accepting and descent
 first improvement greedy methodologies, are proposed for generating
 efficient solutions. Finally, several benchmarking instances are generated
 and solved to test the proposed algorithms.
Journal: International Journal of Production Research 
Pages: 742-760 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1055351 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055351 
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Template-Type: ReDIF-Article 1.0
Author-Name: Maurizio Faccio 
Author-X-Name-First: Maurizio 
Author-X-Name-Last: Faccio 
Author-Name: Mauro Gamberi 
Author-X-Name-First: Mauro 
Author-X-Name-Last: Gamberi 
Author-Name: Marco Bortolini 
Author-X-Name-First: Marco 
Author-X-Name-Last: Bortolini 
Title: Hierarchical approach for paced mixed-model assembly line balancing and sequencing with jolly operators 
Abstract:
 In order to increase flexibility and reduce costs, several companies adopt
 mixed-model assembly lines whose output products are variations of the
 same basic model with specific and distinctive attributes. Unfortunately,
 such attributes typically lead to variations in the task process times. In
 the case of un-paced buffered assembly lines, these variations are
 smoothed by buffers with consequences in terms of work-in-progress, costs,
 space utilisation and lower productivity control. To face such weaknesses,
 some companies adopt paced un-buffered assembly lines where the cycle time
 is controlled by the continuous/synchronous moving of the products from
 the first to the last assembly station. In such contexts, the possibility
 of assembling different models with different assembly times can be
 managed through the use of supplementary flexible workforce. This article
 introduces an innovative balancing and sequencing hierarchical approach
 for paced mixed-model assembly lines using supplementary flexible
 workforce called &#x2018;jolly operators&#x2019;. The goals are to
 minimise the number of jolly operators and to limit the occurrence of
 work-overloads, which typically result in out-of-the-line assembly
 completion. The proposed approach is preliminary validated and applied to
 a case study from an Italian company assembling industrial air-dryers.
Journal: International Journal of Production Research 
Pages: 761-777 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1059965 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1059965 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:3:p:761-777




Template-Type: ReDIF-Article 1.0
Author-Name: G. Manita 
Author-X-Name-First: G. 
Author-X-Name-Last: Manita 
Author-Name: I. Chaieb 
Author-X-Name-First: I. 
Author-X-Name-Last: Chaieb 
Author-Name: O. Korbaa 
Author-X-Name-First: O. 
Author-X-Name-Last: Korbaa 
Title: A new approach for loop machine layout problem integrating proximity constraints 
Abstract:
 This paper focuses on the machine arrangement problem on common loop
 network in a flexible manufacturing system. Existing studies aim to place
 machines at pre-fixed positions around a loop network. This problem is
 considered as a permutation problem that aims to find the best combination
 to reduce generated costs. In this work, we try to add more complexity to
 this problem by respecting the proximity constraints, defined by the
 experts, between the machines. To do this, we propose an algorithm based
 on direct distance measure. Logically, proximity constraints are checked
 using direct distances but costs are calculated using travelled distances.
 Throughout this study, we seek the best machine layout in four transport
 system configuration types to minimise the sum of flow time distances.
 Comparing our algorithm results with two hybrid genetic algorithms, the
 empirical results show that the proposed algorithm provides the most
 suitable solutions.
Journal: International Journal of Production Research 
Pages: 778-798 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1064178 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064178 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:3:p:778-798




Template-Type: ReDIF-Article 1.0
Author-Name: Ali Derakhshan Asl 
Author-X-Name-First: Ali 
Author-X-Name-Last: Derakhshan Asl 
Author-Name: Kuan Yew Wong 
Author-X-Name-First: Kuan Yew 
Author-X-Name-Last: Wong 
Author-Name: Manoj Kumar Tiwari 
Author-X-Name-First: Manoj Kumar 
Author-X-Name-Last: Tiwari 
Title: Unequal-area stochastic facility layout problems: solutions using improved covariance matrix adaptation evolution strategy, particle swarm optimisation, and genetic algorithm 
Abstract:
 Determining the locations of departments or machines in a shop floor is
 classified as a facility layout problem. This article studies unequal-area
 stochastic facility layout problems where the shapes of departments are
 fixed during the iteration of an algorithm and the product demands are
 stochastic with a known variance and expected value. These problems are
 non-deterministic polynomial-time hard and very complex, thus
 meta-heuristic algorithms and evolution strategies are needed to solve
 them. In this paper, an improved covariance matrix adaptation evolution
 strategy (CMA ES) was developed and its results were compared with those
 of two improved meta-heuristic algorithms (i.e. improved particle swarm
 optimisation [PSO] and genetic algorithm [GA]). In the three proposed
 algorithms, the swapping method and two local search techniques which
 altered the positions of departments were used to avoid local optima and
 to improve the quality of solutions for the problems. A real case and two
 problem instances were introduced to test the proposed algorithms. The
 results showed that the proposed CMA ES has found better layouts in
 contrast to the proposed PSO and GA.
Journal: International Journal of Production Research 
Pages: 799-823 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1070217 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1070217 
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Template-Type: ReDIF-Article 1.0
Author-Name: Daria Battini 
Author-X-Name-First: Daria 
Author-X-Name-Last: Battini 
Author-Name: Xavier Delorme 
Author-X-Name-First: Xavier 
Author-X-Name-Last: Delorme 
Author-Name: Alexandre Dolgui 
Author-X-Name-First: Alexandre 
Author-X-Name-Last: Dolgui 
Author-Name: Alessandro Persona 
Author-X-Name-First: Alessandro 
Author-X-Name-Last: Persona 
Author-Name: Fabio Sgarbossa 
Author-X-Name-First: Fabio 
Author-X-Name-Last: Sgarbossa 
Title: Ergonomics in assembly line balancing based on energy expenditure: a multi-objective model 
Abstract:
 In many assembly systems, ergonomics can have great impact on productivity
 and human safety. Traditional assembly systems optimisation approaches
 consider only time and cost variables, while few studies include also
 ergonomics aspects. In this study, a new multi-objective model for solving
 assembly line balancing problem is developed and discussed in order to
 include also the ergonomics aspect. First, based on main features of
 assembly workstations, the energy expenditure concept is used in order to
 estimate the ergonomics level, thanks to a new technique, called
 Predetermined Motion Energy System, which helps rapidly estimate the
 energy expenditure values. Then, a multi-objective approach, based on four
 different objective functions, is introduced in order to define the
 efficient frontiers of optimal solutions. To complete the study, a simple
 numerical example for a real case is presented to analyse the behaviour of
 Pareto frontiers varying several parameters linked to the energy and time
 value.
Journal: International Journal of Production Research 
Pages: 824-845 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1074299 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1074299 
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Template-Type: ReDIF-Article 1.0
Author-Name: Farouq Alhourani 
Author-X-Name-First: Farouq 
Author-X-Name-Last: Alhourani 
Title: Cellular manufacturing system design considering machines reliability and parts alternative process routings 
Abstract:
 Cell formation is an important problem in the design of cellular
 manufacturing systems (CMS). Most cell formation methods appeared in the
 literature assume that each part has one process plan, and all machines
 are 100% reliable with unlimited capacity. However, this is not realistic
 in manufacturing systems. Considering machines reliability in addition to
 machines capacity and machine duplicates during the part route selection
 process help to obtain better machine grouping and minimum total cost for
 CMS. Considering these factors in addition to operations sequence and
 production volumes makes the problem more complex but more realistic. Most
 of the methods appeared in the literature to solve such problems use
 mathematical programming procedures that take large amount of
 computational efforts. Procedures using similarity coefficient method are
 more flexible in incorporating various important production data and lend
 easily to computer applications. A new similarity coefficient equation
 that incorporates all these production factors is developed. Also, a
 procedure that captures the similarity between machine groups and
 minimises the total CMS cost is developed. The procedure utilises
 functional cells to eliminate intercellular moves and achieve
 &#x2018;one-piece flow&#x2019; practise. The methodology is compared with
 other methods in the literature and found to be more effective.
Journal: International Journal of Production Research 
Pages: 846-863 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1083626 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1083626 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:3:p:846-863




Template-Type: ReDIF-Article 1.0
Author-Name: Ying Mei 
Author-X-Name-First: Ying 
Author-X-Name-Last: Mei 
Author-Name: Zhigang Zeng 
Author-X-Name-First: Zhigang 
Author-X-Name-Last: Zeng 
Author-Name: Ding Feng 
Author-X-Name-First: Ding 
Author-X-Name-Last: Feng 
Author-Name: Yiliu (Paul) Tu 
Author-X-Name-First: Yiliu (Paul) 
Author-X-Name-Last: Tu 
Title: A method for man hour optimisation and workforce allocation problem with discrete and non-numerical constraints in large-scale one-of-a-kind production 
Abstract:
 In one-of-a-kind production (OKP), how to coordinate workforce allocations
 to obtain reasonable man-hour has the practical significance. However,
 plenty of variables and complicated operation relationships are involved,
 which implies the man-hour optimisation in OKP belongs to a constrained
 mixed discrete optimisation problem. In this article, to deal with the
 man-hour optimisation in large-scale OKP which often refers to complex
 production, e.g. shipbuilding, we introduce a top-down refinement method
 to specialise the product design and production decomposition in OKP,
 which also indicates the operation relationships of the interim product
 production processes. Consequently, we suggest three basic task structures
 which are with wide adaptability in OKP industry: tandem structure,
 parallel structure and double-level-nested parallel structure. Meanwhile,
 for the double-level-nested parallel structure, a method based on matrix
 real-coded genetic algorithm and dynamic programming is presented to solve
 the man-hour optimisation and labour force allocation problem. Through the
 case studies, including an industrial implementation in the shipbuilding
 interim product (i.e. a hull block) production, our optimisation method
 demonstrates significant potential to improve the production efficiency.
Journal: International Journal of Production Research 
Pages: 864-877 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1088972 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1088972 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Masood Fathi 
Author-X-Name-First: Masood 
Author-X-Name-Last: Fathi 
Author-Name: Victoria Rodr&#xed;guez 
Author-X-Name-First: Victoria 
Author-X-Name-Last: Rodr&#xed;guez 
Author-Name: Dalila B.M.M. Fontes 
Author-X-Name-First: Dalila B.M.M. 
Author-X-Name-Last: Fontes 
Author-Name: Maria Jesus Alvarez 
Author-X-Name-First: Maria Jesus 
Author-X-Name-Last: Alvarez 
Title: A modified particle swarm optimisation algorithm to solve the part feeding problem at assembly lines 
Abstract:
 The Assembly Line Part Feeding Problem (ALPFP) is a complex combinatorial
 optimisation problem concerned with the delivery of the required parts to
 the assembly workstations in the right quantities at the right time.
 Solving the ALPFP includes simultaneously solving two sub-problems, namely
 tour scheduling and tow-train loading. In this article, we first define
 the problem and formulate it as a multi-objective mixed-integer linear
 programming model. Then, we carry out a complexity analysis, proving the
 ALPFP to be NP-complete. A modified particle swarm optimisation (MPSO)
 algorithm incorporating mutation as part of the position updating scheme
 is subsequently proposed. The MPSO is capable of finding very good
 solutions with small time requirements. Computational results are
 reported, demonstrating the efficiency and effectiveness of the proposed
 MPSO.
Journal: International Journal of Production Research 
Pages: 878-893 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1090032 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1090032 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:3:p:878-893




Template-Type: ReDIF-Article 1.0
Author-Name: Suvankar Ghosh 
Author-X-Name-First: Suvankar 
Author-X-Name-Last: Ghosh 
Author-Name: O. Felix Offodile 
Author-X-Name-First: O. Felix 
Author-X-Name-Last: Offodile 
Title: A real options model of phased migration to cellular manufacturing 
Abstract:
 The literature is replete with models that examine various aspects of
 cellular manufacturing (CM), such as optimisation of cell layouts.
 However, many firms may realise zero to marginal returns from CM. Given
 this uncertainty, the manager should first determine the value of CM to
 the firm before deploying it. Although traditional valuation models
 employing discounted cash flow analysis allow for uncertainty, they treat
 future investments as fixed when computing the investment&#x2019;s present
 value. The real options (RO) logic of valuation allows the manager to
 exercise the option to invest in or abandon a project based on expected
 outcomes. Future investments are thus options. This paper presents an RO
 model for CM migration that addresses whether a firm should migrate to CM;
 and it prescribes the <italic>sequence</italic> of cell deployment, which
 has not been addressed in the literature. Our model is also much more
 transparent and accessible to practitioners, with an accompanying software
 tool for prospective users. Finally, we use simulation extensively to
 discover the drivers of the optimal cell deployment sequence. Our results
 show that there is a complex interplay between net present value, speed of
 cellularisation, inter-cell learning and volatility in terms of their
 influence on the cell sequence.
Journal: International Journal of Production Research 
Pages: 894-906 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1095367 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1095367 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:3:p:894-906




Template-Type: ReDIF-Article 1.0
Author-Name: Marcus Ritt 
Author-X-Name-First: Marcus 
Author-X-Name-Last: Ritt 
Author-Name: Alysson M. Costa 
Author-X-Name-First: Alysson M. 
Author-X-Name-Last: Costa 
Author-Name: Crist&#xf3;bal Miralles 
Author-X-Name-First: Crist&#xf3;bal 
Author-X-Name-Last: Miralles 
Title: The assembly line worker assignment and balancing problem with stochastic worker availability 
Abstract:
 Assembly lines can be employed successfully in sheltered work centres to
 better include persons with disabilities in the labour market as well as
 to improve production efficiency. The optimal assignment of a
 heterogeneous workforce is known as the assembly line worker assignment
 and balancing problem (ALWABP). These assembly lines are characterised not
 only by a heterogeneous workforce, but also by high levels of absenteeism,
 which makes it more difficult to obtain stable and efficient line
 balancing solutions. In this paper, an extension of the ALWABP to minimise
 the expected cycle time under uncertain worker availability is proposed.
 We model this problem as a two-stage mixed integer program, and propose
 local search heuristics for solving it. Computational experiments show
 that stochastic modelling can help to improve the line&#x2019;s efficiency
 and that the proposed heuristics produce good results for instances of
 practical size.
Journal: International Journal of Production Research 
Pages: 907-922 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1108534 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1108534 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Chunfeng Liu 
Author-X-Name-First: Chunfeng 
Author-X-Name-Last: Liu 
Author-Name: Jufeng Wang 
Author-X-Name-First: Jufeng 
Author-X-Name-Last: Wang 
Author-Name: Joseph Y.-T. Leung 
Author-X-Name-First: Joseph Y.-T. 
Author-X-Name-Last: Leung 
Author-Name: Kai Li 
Author-X-Name-First: Kai 
Author-X-Name-Last: Li 
Title: Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm 
Abstract:
 We consider a joint decision model of cell formation and task scheduling
 in cellular manufacturing system under dual-resource constrained (DRC)
 setting. On one hand, machines and workers are multi-functional and/or
 multi-skilled, and they are grouped into workstations and cells. On the
 other hand, there is a processing sequence among operations of the parts
 which needs to be dispatched to the desirable workstations for processing.
 Inter-cell movements of parts can reduce the processing times and the
 makespan but will increase the inter-cell material handling costs. The
 objective of the problem is to minimise the material handling costs as
 well as the fixed and operating costs of machines and workers. Due to the
 NP-hardness of the problem, we propose an efficient discrete bacteria
 foraging algorithm (DBFA) with elaborately designed solution
 representation and bacteria evolution operators to solve the proposed
 problem. We tested our algorithm using randomly generated instances with
 different sizes and settings by comparing with the original bacteria
 foraging algorithm and a genetic algorithm. Our results show that the
 proposed DBFA has better performance than the two compared algorithms with
 the same running time.
Journal: International Journal of Production Research 
Pages: 923-944 
Issue: 3 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1113328 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1113328 
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Template-Type: ReDIF-Article 1.0
Author-Name: I.M. Coelho 
Author-X-Name-First: I.M. 
Author-X-Name-Last: Coelho 
Author-Name: P.L.A. Munhoz 
Author-X-Name-First: P.L.A. 
Author-X-Name-Last: Munhoz 
Author-Name: L.S. Ochi 
Author-X-Name-First: L.S. 
Author-X-Name-Last: Ochi 
Author-Name: M.J.F. Souza 
Author-X-Name-First: M.J.F. 
Author-X-Name-Last: Souza 
Author-Name: C. Bentes 
Author-X-Name-First: C. 
Author-X-Name-Last: Bentes 
Author-Name: R. Farias 
Author-X-Name-First: R. 
Author-X-Name-Last: Farias 
Title: An integrated CPU--GPU heuristic inspired on variable neighbourhood search for the single vehicle routing problem with deliveries and selective pickups 
Abstract:
 Environmental issues have become increasingly important to industry and
 business in recent days. This trend forces the companies to take
 responsibility for product recovery, and proper recycling and disposal,
 moving towards the design of sustainable green supply chains. This paper
 addresses the backward stream in transportation of products, by means of
 reverse logistics applied to vehicle routing. This problem, called single
 vehicle routing problem with deliveries and selective pickups, consists in
 finding a route that starts from the depot and visits all delivery
 customers. Some pickup customers may also be visited, since the capacity
 of the truck is not exceeded, and there is also a revenue associated with
 each pickup. We develop an algorithm inspired on the variable
 neighbourhood search metaheuristic that explores the power of modern
 graphics processing unit (GPU) to provide routes in reasonable
 computational time. The proposed algorithm called four-neighbourhood
 variable neighbourhood search (FN-VNS) includes a novel high-quality
 initial solution generator, a CPU--GPU integrated perturbation strategy
 and four different neighbourhood searches implemented purely in GPU for
 the local search phase. Our experimental results show that FN-VNS is able
 to improve the quality of the solution for 51 instances out of 68
 instances taken from the literature. Finally, we obtained speedups up to
 14.49 times, varying from 17.42 up to 76.84 for each local search,
 measured over a set of new large-size instances.
Journal: International Journal of Production Research 
Pages: 945-962 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1035811 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1035811 
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Template-Type: ReDIF-Article 1.0
Author-Name: G.M. Komaki 
Author-X-Name-First: G.M. 
Author-X-Name-Last: Komaki 
Author-Name: Ehsan Teymourian 
Author-X-Name-First: Ehsan 
Author-X-Name-Last: Teymourian 
Author-Name: Vahid Kayvanfar 
Author-X-Name-First: Vahid 
Author-X-Name-Last: Kayvanfar 
Title: Minimising makespan in the two-stage assembly hybrid flow shop scheduling problem using artificial immune systems 
Abstract:
 Two-stage hybrid flow shop (HFS) scheduling problem followed by single
 assembly machine is addressed in this paper. To produce the final product,
 parts need to be processed on the HFS stages and thereafter, several parts
 are joined under the assembly operations based on the predefined Bill of
 Materials of the product. The aim of this research is to find the schedule
 which minimises completion time of the last product, i.e. makespan. For
 the considered problem, lower bound, heuristic algorithms and two
 metaheuristic techniques based on artificial immune system are developed.
 Computational results demonstrate that the proposed lower bound and
 heuristic algorithms outperform the existent lower bounds and heuristic
 algorithms.
Journal: International Journal of Production Research 
Pages: 963-983 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1035815 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1035815 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhuxi Chen 
Author-X-Name-First: Zhuxi 
Author-X-Name-Last: Chen 
Author-Name: Xiaoping Li 
Author-X-Name-First: Xiaoping 
Author-X-Name-Last: Li 
Author-Name: Jatinder N.D. Gupta 
Author-X-Name-First: Jatinder N.D. 
Author-X-Name-Last: Gupta 
Title: Sequencing the storages and retrievals for flow-rack automated storage and retrieval systems with duration-of-stay storage policy 
Abstract:
 Sequencing of storages and retrievals is an important topic in the
 automated storage and retrieval system (AS/RS), which largely influences
 the throughput performance and the operational cost of an AS/RS. In this
 paper, the problem of sequencing the storages and retrievals in a
 flow-rack AS/RS with duration-of-stay storage policy is analysed and a
 two-step heuristic called the grouping-matching method is proposed for
 minimising the total travel time of operations. The proposed
 grouping-matching method assigns unit-loads into groups in the grouping
 step and matches groups and bins of flow rack in the matching step. Two
 grouping heuristics are designed for the grouping step. The matching
 subproblem is formulated as an assignment to be solved. Simulation
 experiments are conducted to evaluate the effectiveness and efficiency of
 the grouping-matching method and the two grouping heuristics used for the
 grouping subproblem.
Journal: International Journal of Production Research 
Pages: 984-998 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1035816 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1035816 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Younes Rahmani 
Author-X-Name-First: Younes 
Author-X-Name-Last: Rahmani 
Author-Name: Wahiba Ramdane Cherif-Khettaf 
Author-X-Name-First: Wahiba 
Author-X-Name-Last: Ramdane Cherif-Khettaf 
Author-Name: Ammar Oulamara 
Author-X-Name-First: Ammar 
Author-X-Name-Last: Oulamara 
Title: The two-echelon multi-products location-routing problem with pickup and delivery: formulation and heuristic approaches 
Abstract:
 The two-echelon location-routing problem (LRP-2E) considers the
 first-level routes that serve from one depot a set of processing centres,
 which must be located and the second-level routes that serve customers
 from the opened processing centres. In this paper, we consider an
 extension of the LRP-2E, where the second-level routes include three
 constraints that have not been considered simultaneously in the location
 routing literature, namely multi-product, pickup and delivery, and the use
 of the processing centre as intermediate facility in the second-level
 routes. This new variant is named two-Echelon Multi-products
 Location-Routing problem with Pickup and Delivery (LRP-MPPD-2E). The
 objective of LRP-MPPD-2E is to minimise both the location and the routing
 costs, considering the new constraints. The first echelon deals with the
 selection of processing centres from a set of potential sites
 simultaneously with the construction of the first-level routes, such that
 each route starts from the main depot, visits the selected processing
 centres and returns to the main depot. The second echelon aims at
 assigning customers to the selected processing centres and defining the
 second-level routes. Each second-level route, starts at a processing
 centre, visits a set of customers, through one or several processing
 centres, and then returns to the first processing centre. We present a
 mixed-integer linear model for the problem and use a Cplex solver to solve
 small-scale instances. Furthermore, we propose non-trivial extensions of
 the nearest neighbour and insertion approaches. We also develop
 clustering-based approaches that have not been extensively investigated
 with regards to location routing. Computational experiments are conducted
 to evaluate and to compare the performances of the proposed approaches.
 The results confirm the effectiveness of clustering approaches.
Journal: International Journal of Production Research 
Pages: 999-1019 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1040127 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1040127 
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Template-Type: ReDIF-Article 1.0
Author-Name: Athakorn Kengpol 
Author-X-Name-First: Athakorn 
Author-X-Name-Last: Kengpol 
Author-Name: Sopida Tuammee 
Author-X-Name-First: Sopida 
Author-X-Name-Last: Tuammee 
Title: The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: an empirical study 
Abstract:
 The objective of this research was to develop a decision support framework
 (DSF) to assess quantitative risk in multimodal green logistics. This risk
 assessment is the combination of a number of models, the failure mode and
 effects analysis, the risk contour plot, the quantitative risk assessment,
 the analytic hierarchy process and the data envelopment analysis which can
 support a user to perform risk assessment in various decisions. The
 contribution of this research is that the risk assessment model can
 generate an optimal green logistics route in accordance with weight from
 the user. The highlight of this DSF is that the quantitative assessment
 model can reduce bias on risk assessment of logistics route. An in-depth
 case study, recommendations, limitations and further research are also
 provided.
Journal: International Journal of Production Research 
Pages: 1020-1038 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1041570 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1041570 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Fuqing Zhao 
Author-X-Name-First: Fuqing 
Author-X-Name-Last: Zhao 
Author-Name: Zhongshi Shao 
Author-X-Name-First: Zhongshi 
Author-X-Name-Last: Shao 
Author-Name: Junbiao Wang 
Author-X-Name-First: Junbiao 
Author-X-Name-Last: Wang 
Author-Name: Chuck Zhang 
Author-X-Name-First: Chuck 
Author-X-Name-Last: Zhang 
Title: A hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search for job shop scheduling problems 
Abstract:
 Job shop scheduling problem (JSSP) is a typical NP-hard problem. In order
 to improve the solving efficiency for JSSP, a hybrid differential
 evolution and estimation of distribution algorithm based on neighbourhood
 search is proposed in this paper, which combines the merits of Estimation
 of distribution algorithm and Differential evolution (DE). Meanwhile, to
 strengthen the searching ability of the proposed algorithm, a chaotic
 strategy is introduced to update the parameters of DE. Two mutation
 operators are adopted. A neighbourhood search (NS) algorithm based on
 blocks on critical path is used to further improve the solution quality.
 Finally, the parametric sensitivity of the proposed algorithm has been
 analysed based on the Taguchi method of design of experiment. The proposed
 algorithm was tested through a set of typical benchmark problems of JSSP.
 The results demonstrated the effectiveness of the proposed algorithm for
 solving JSSP.
Journal: International Journal of Production Research 
Pages: 1039-1060 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1041575 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1041575 
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Th&#xfc;rer 
Author-X-Name-First: Matthias 
Author-X-Name-Last: Th&#xfc;rer 
Author-Name: Mark Stevenson 
Author-X-Name-First: Mark 
Author-X-Name-Last: Stevenson 
Author-Name: Ting Qu 
Author-X-Name-First: Ting 
Author-X-Name-Last: Qu 
Title: Job sequencing and selection within workload control order release: an assessment by simulation 
Abstract:
 Recent research has highlighted the potential impact of pool sequencing on
 order release performance but it suffered from two shortcomings. First,
 arguably the best release solution for workload control in practice
 combines periodic with continuous release. Although the two types of
 releases serve different functions, recent work assumed the same
 sequencing rule should be used for both. Here, the use of different
 sequencing rules for periodic and continuous releases is evaluated. Using
 a job-shop simulation, we demonstrate that the rule applied during
 continuous releases has only a negligible impact on performance.
 Therefore, jobs can be pulled intermediately from the pool by workers
 using a more straightforward sequencing rule than the one applied for
 periodic release. Second, it was assumed that all jobs in the pool are
 sequenced and then a subset is selected for release. But for some
 load-oriented sequencing rules, the priority value used for sequencing
 jobs should be updated after each job selection from the pool. Our
 simulation results show that although this may improve load balancing at
 release, it does not in fact improve overall shop performance. Therefore,
 the greedy heuristic of first sequencing and then selecting jobs can be
 maintained, which allows the release decision-making process to retain its
 simplicity. The work has important implications for the use of sequencing
 rules in practice.
Journal: International Journal of Production Research 
Pages: 1061-1075 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1047978 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047978 
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Template-Type: ReDIF-Article 1.0
Author-Name: Nadjib Brahimi 
Author-X-Name-First: Nadjib 
Author-X-Name-Last: Brahimi 
Author-Name: Tarik Aouam 
Author-X-Name-First: Tarik 
Author-X-Name-Last: Aouam 
Title: Multi-item production routing problem with backordering: a MILP approach 
Abstract:
 The aim of this paper is to present mixed integer linear programming
 formulations for the production routing problem with backordering (PRP-B)
 and a new hybrid heuristic to solve the problem. The PRP-B is considered
 in the context of a supply chain consisting of a production facility with
 limited production and storage capacities and geographically dispersed
 points of sale with limited storage capacities. The PRP-B integrates
 multiple item lot sizing decisions and vehicle routing decisions to the
 points of sale, where backordering of end customer demands is allowed at a
 penalty. Two integrated mixed integer programming models are formulated
 and a solution procedure consisting of a relax-and-fix heuristic combined
 with a local search algorithm is proposed. The numerical results show that
 this hybrid heuristic outperforms a state-of-the-art MIP commercial
 solver, in terms of solution quality and CPU times.
Journal: International Journal of Production Research 
Pages: 1076-1093 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1047971 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047971 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Victor Cransberg 
Author-X-Name-First: Victor 
Author-X-Name-Last: Cransberg 
Author-Name: Martin Land 
Author-X-Name-First: Martin 
Author-X-Name-Last: Land 
Author-Name: Christian Hicks 
Author-X-Name-First: Christian 
Author-X-Name-Last: Hicks 
Author-Name: Mark Stevenson 
Author-X-Name-First: Mark 
Author-X-Name-Last: Stevenson 
Title: Handling the complexities of real-life job shops when implementing workload control: a decision framework and case study 
Abstract:
 The workload control literature highlights the importance of balancing the
 shop floor workload, but also acknowledges that this can conflict with
 processing the most urgent orders -- hence, there is a trade-off. In
 practice, shops contain many complexities, e.g. simultaneous batching and
 sequence-dependent set-up times that may conflict with processing the most
 urgent orders and require other solutions than workload balancing to avoid
 capacity losses. This adds to the trade-off dilemma, which traditionally
 only considers timing and balancing. This paper develops a framework that
 determines whether to address a complexity through order release or
 dispatching. It comprises two dimensions: (i) the typical position of a
 complexity in the routing of an order and (ii) the criticality of the
 complexity. A case study is presented, which demonstrates the
 framework&#x2019;s utility and illustrates the development of specific
 solutions designed to handle the complexities. Most complexities present
 in the case require handling at the order release stage. The challenges of
 handling multiple complexities at this decision level are evaluated.
 Finally, the implications for managers and future research are outlined.
Journal: International Journal of Production Research 
Pages: 1094-1109 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1047974 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047974 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Shih-Wei Lin 
Author-X-Name-First: Shih-Wei 
Author-X-Name-Last: Lin 
Author-Name: Kuo-Ching Ying 
Author-X-Name-First: Kuo-Ching 
Author-X-Name-Last: Ying 
Author-Name: Wen-Jie Wu 
Author-X-Name-First: Wen-Jie 
Author-X-Name-Last: Wu 
Author-Name: Yen-I Chiang 
Author-X-Name-First: Yen-I 
Author-X-Name-Last: Chiang 
Title: Multi-objective unrelated parallel machine scheduling: a Tabu-enhanced iterated Pareto greedy algorithm 
Abstract:
 This work proposes a high-performance algorithm for solving the
 multi-objective unrelated parallel machine scheduling problem. The
 proposed approach is based on the iterated Pareto greedy (IPG) algorithm
 but exploits the accessible Tabu list (TL) to enhance its performance. To
 demonstrate the superior performance of the proposed Tabu-enhanced
 iterated Pareto greedy (TIPG) algorithm, its computational results are
 compared with IPG and existing algorithms on the same benchmark problem
 set. Experimental results reveal that incorporating the accessible TL can
 eliminate ineffective job moves, causing the TIPG algorithm to outperform
 state-of-the-art approaches in the light of five multi-objective
 performance metrics. This work contributes a useful theoretical and
 practical optimisation method for solving this problem.
Journal: International Journal of Production Research 
Pages: 1110-1121 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1047981 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047981 
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Template-Type: ReDIF-Article 1.0
Author-Name: Cheng-Hsiang Liu 
Author-X-Name-First: Cheng-Hsiang 
Author-X-Name-Last: Liu 
Title: Mathematical programming formulations for single-machine scheduling problems while considering renewable energy uncertainty 
Abstract:
 Carbon dioxide (CO<sub>2</sub>) in particular is by far the primary driver
 of global warming. One of the most effective ways to reduce CO<sub>2</sub>
 emissions is to increase the amount of power from renewable energy. A key
 challenge in utilising renewable energies, such as wind and solar, is
 their uncertainty in terms of when and to what degree and force renewable
 energies will become available next time. This study uses interval number
 theory for renewable energy in uncertainty modelling and proposes two
 novel interval single-machine scheduling problems, <inline-formula
 id="ILM0001"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1048380_ilm0001.gif"/></inline-formula> and
 <inline-formula id="ILM0002"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1048380_ilm0002.gif"/></inline-formula>. A solution
 procedure is formulated to optimise these problems with interval numbers
 using interval arithmetic. Additionally, this study derives Pareto-optimal
 solutions of the bi-objective optimisation problem, <inline-formula
 id="ILM0003"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1048380_ilm0003.gif"/></inline-formula>, using the
 lexicographic-weighted Tchebycheff method. Some managerial implications
 are obtained by parameter analysis. Analytical results offer
 decision-makers an intuitive view of how these factors impact scheduling
 results and provide practical guidelines for real-life production.
Journal: International Journal of Production Research 
Pages: 1122-1133 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1048380 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1048380 
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Template-Type: ReDIF-Article 1.0
Author-Name: Federico Trigos 
Author-X-Name-First: Federico 
Author-X-Name-Last: Trigos 
Author-Name: Eduardo M. L&#xf3;pez 
Author-X-Name-First: Eduardo M. 
Author-X-Name-Last: L&#xf3;pez 
Title: Maximising profit for multiple-product, single-period, single-machine manufacturing under sequential set-up constraints that depend on lot size 
Abstract:
 The classical problem of order acceptance/rejection in make-to-order
 environments, when aiming to maximise profit with machine set-ups is
 extended in this paper to multiple set-ups depending on manufacturing
 batch size. In this case, if the manufacturing batch is larger than
 certain product-dependent bounds, not only is the initial set-up required
 but also periodic reset-ups are in order, generating sub-batches of the
 same order, such as tool resharpening and machine recalibration. A network
 formulation provides the basis for identifying effective algorithms to
 obtain a solution to the problem. A binary programming model (BPM) and a
 dynamic programming formulation (DPF) are proposed to solve the problem to
 optimality. In addition, two heuristics are developed to obtain lower
 bounds on maximum profit: each attempt to maximise customer satisfaction
 under production time restrictions, and to provide an extension to the
 classical knapsack problem. Numerical experimentation shows that
 computational time is not an issue when BPM and heuristics are applied,
 but the cost of commercial solvers for BPM algorithms might be
 problematic. However, if the aim is to code the DPF in-house, the curse of
 dimensionality in dynamic programming must be addressed, although dynamic
 programming does yield a full sensitivity analysis, which is useful for
 decision-making.
Journal: International Journal of Production Research 
Pages: 1134-1151 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1055348 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055348 
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Template-Type: ReDIF-Article 1.0
Author-Name: Du-Juan Wang 
Author-X-Name-First: Du-Juan 
Author-X-Name-Last: Wang 
Author-Name: Yunqiang Yin 
Author-X-Name-First: Yunqiang 
Author-X-Name-Last: Yin 
Author-Name: Shuenn-Ren Cheng 
Author-X-Name-First: Shuenn-Ren 
Author-X-Name-Last: Cheng 
Author-Name: T.C.E. Cheng 
Author-X-Name-First: T.C.E. 
Author-X-Name-Last: Cheng 
Author-Name: Chin-Chia Wu 
Author-X-Name-First: Chin-Chia 
Author-X-Name-Last: Wu 
Title: Due date assignment and scheduling on a single machine with two competing agents 
Abstract:
 We study a single-machine due date assignment and scheduling problem
 involving two agents each seeking to optimise its own performance. We
 consider three due date assignment methods, namely the common, slack and
 unrestricted due date assignment methods. For each due date assignment
 method, we consider two types of optimisation problem, namely a linear
 combination optimisation problem (minimising the total integrated cost of
 the two agents) and a constrained optimisation problem (minimising the
 objective of one agent, subject to an upper bound on the objective of the
 other agent). We present a polynomial-time dynamic programming algorithm
 to solve the linear combination optimisation problem, and show that the
 constrained optimisation problem is <inline-formula
 id="ILM0001"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1056317_ilm0001.gif"/></inline-formula>-hard in the
 ordinary sense and admits a fully polynomial-time approximation scheme.
Journal: International Journal of Production Research 
Pages: 1152-1169 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1056317 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056317 
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Template-Type: ReDIF-Article 1.0
Author-Name: Nita P.A. Hidayat 
Author-X-Name-First: Nita P.A. 
Author-X-Name-Last: Hidayat 
Author-Name: Andi Cakravastia 
Author-X-Name-First: Andi 
Author-X-Name-Last: Cakravastia 
Author-Name: T.M.A. Ari Samadhi 
Author-X-Name-First: T.M.A. Ari 
Author-X-Name-Last: Samadhi 
Author-Name: Abdul Hakim Halim 
Author-X-Name-First: Abdul Hakim 
Author-X-Name-Last: Halim 
Title: A batch scheduling model for <italic>m</italic> heterogeneous batch processor 
Abstract:
 This research addresses a batch scheduling problem for single item parts
 with multi due date on <italic>m</italic> heterogeneous batch processors.
 The objective is to minimise total actual flowtime of parts through the
 shop. The total actual flowtime of parts in a batch is the multiplication
 of the interval between batch arrival time and the due date by the number
 of parts in the batch. Using the actual flowtime as the objective means it
 is oriented to satisfy the due date as a commitment to customers, and
 simultaneously to minimise the length of time of the parts spending in the
 shop. An algorithm to solve this problem is proposed.
Journal: International Journal of Production Research 
Pages: 1170-1185 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1056322 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056322 
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Template-Type: ReDIF-Article 1.0
Author-Name: Lu Liu 
Author-X-Name-First: Lu 
Author-X-Name-Last: Liu 
Author-Name: Jian-Jun Wang 
Author-X-Name-First: Jian-Jun 
Author-X-Name-Last: Wang 
Author-Name: Xiao-Yuan Wang 
Author-X-Name-First: Xiao-Yuan 
Author-X-Name-Last: Wang 
Title: Single machine due-window assignment scheduling with resource-dependent processing times to minimise total resource consumption cost 
Abstract:
 This paper considers a single-machine scheduling problem involving convex
 resource-dependent processing times and due-window assignment
 simultaneously. The goal is to minimise the total resource consumption
 cost under the constraint that the schedule cost involving earliness,
 tardiness, window location, window size and makespan does not exceed a
 given limit for two popular due window assignment methods: the common flow
 allowance (slack) due window assignment method (referred to SLKW) and the
 common due window assignment method (referred to CONW). We show that the
 problem can be solved in polynomial time. Some extensions of the problem
 are also given.
Journal: International Journal of Production Research 
Pages: 1186-1195 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1056323 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056323 
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Template-Type: ReDIF-Article 1.0
Author-Name: Kfir Arviv 
Author-X-Name-First: Kfir 
Author-X-Name-Last: Arviv 
Author-Name: Helman Stern 
Author-X-Name-First: Helman 
Author-X-Name-Last: Stern 
Author-Name: Yael Edan 
Author-X-Name-First: Yael 
Author-X-Name-Last: Edan 
Title: Collaborative reinforcement learning for a two-robot job transfer flow-shop scheduling problem 
Abstract:
 A two-robot flow-shop scheduling problem with <italic>n</italic> identical
 jobs and <italic>m</italic> machines is defined and evaluated <italic>for
 four</italic> robot collaboration levels <italic>corresponding to
 different levels of</italic> information sharing, learning and
 assessment<bold>:</bold> <italic>Full</italic> -- robots work together,
 performing self and joint learning sharing full information;
 <italic>Pull</italic> -- one robot decides when and if to learn from the
 other robot; <italic>Push</italic> -- one robot may force the second to
 learn from it and <italic>None</italic> -- each robot learns independently
 with no information sharing. Robots operate on parallel tracks,
 transporting jobs between successive machines, returning empty to a
 machine to move another job. The objective is to obtain a robot schedule
 that minimises makespan (<italic>C</italic><sub>max</sub>) for machines
 with varying processing times. A new reinforcement learning algorithm is
 developed, using dual <italic>Q</italic>-<italic>learning</italic>
 functions. A novel feature in the collaborative algorithm is the
 assignment of different reward functions to robots; minimising robot idle
 time and minimising job waiting time. Such delays increase makespan.
 Simulation analyses with fast, medium and slow speed robots indicated that
 <italic>Full</italic> collaboration with a fast--fast robot pair was best
 according to minimum average upper bound error. The new collaborative
 algorithm provides a tool for finding optimal and near-optimal solutions
 to difficult collaborative multi-robot scheduling problems.
Journal: International Journal of Production Research 
Pages: 1196-1209 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1057297 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1057297 
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Template-Type: ReDIF-Article 1.0
Author-Name: Andr&#xe1;s Kov&#xe1;cs 
Author-X-Name-First: Andr&#xe1;s 
Author-X-Name-Last: Kov&#xe1;cs 
Title: Integrated task sequencing and path planning for robotic remote laser welding 
Abstract:
 This paper investigates the problem of integrated task sequencing and path
 planning in Remote Laser Welding (RLW). It is shown that finding the
 appropriate order of welding tasks is crucial for exploiting the
 efficiency of this new joining technology, and this can be achieved only
 if the robot path is considered already at the time of sequencing. For
 modelling the problem, a novel extension of the well-know Travelling
 Salesman Problem with neighbourhoods and durative visits, denoted as
 TSP-ND, is introduced. Basic properties of this problem are formally
 proven, and a GRASP meta-heuristic algorithm is proposed for solving it.
 Extensive computational experiments demonstrate that the novel approach
 solves efficiently industrially relevant problems, and it achieves
 substantial improvement in cycle time compared to the single earlier
 approach in the literature dedicated to RLW, as well as compared to a
 decomposition approach to solving the TSP-ND model.
Journal: International Journal of Production Research 
Pages: 1210-1224 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1057626 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1057626 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaocong Ji 
Author-X-Name-First: Xiaocong 
Author-X-Name-Last: Ji 
Author-Name: Zhihai Zhang 
Author-X-Name-First: Zhihai 
Author-X-Name-Last: Zhang 
Author-Name: Simin Huang 
Author-X-Name-First: Simin 
Author-X-Name-Last: Huang 
Author-Name: Lefei Li 
Author-X-Name-First: Lefei 
Author-X-Name-Last: Li 
Title: Capacitated disassembly scheduling with parts commonality and start-up cost and its industrial application 
Abstract:
 This paper discusses the capacitated disassembly scheduling with parts
 commonality and start-up cost, which has broad applications in
 remanufacturing and many other production systems. The problem is
 formulated as a mixed-integer programming model. A Lagrangian heuristic is
 developed, where the lower bound problem reduces to a linear model, and
 the upper bound can be obtained with a two-stage procedure in polynomial
 time. The algorithm is tested on randomly generated problems. The results
 reveal that the approach outperforms CPLEX significantly for all the test
 instances, and for real-scale problem it provides sufficiently good
 solutions within acceptable time. Sensitivity studies on capacity, parts
 commonality and start-up cost are also conducted, which provide some
 useful insights for industrial managers. Moreover, a real-world case from
 a valve disassembly factory is studied, which illustrates the application
 of the proposed approach and gives managerial insights. Finally,
 conclusions are drawn and some potential extensions are discussed.
Journal: International Journal of Production Research 
Pages: 1225-1243 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1058536 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1058536 
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Template-Type: ReDIF-Article 1.0
Author-Name: Min Ji 
Author-X-Name-First: Min 
Author-X-Name-Last: Ji 
Author-Name: Xin Zhang 
Author-X-Name-First: Xin 
Author-X-Name-Last: Zhang 
Author-Name: Xiaoying Tang 
Author-X-Name-First: Xiaoying 
Author-X-Name-Last: Tang 
Author-Name: T.C.E. Cheng 
Author-X-Name-First: T.C.E. 
Author-X-Name-Last: Cheng 
Author-Name: Guiyi Wei 
Author-X-Name-First: Guiyi 
Author-X-Name-Last: Wei 
Author-Name: Yuanyuan Tan 
Author-X-Name-First: Yuanyuan 
Author-X-Name-Last: Tan 
Title: Group scheduling with group-dependent multiple due windows assignment 
Abstract:
 We consider single-machine group scheduling with group-dependent multiple
 due windows assignment. In the group technology environment, the jobs are
 divided into groups in advance according to their processing similarities,
 and all the jobs of the same group are processed consecutively in order to
 improve production efficiency. A sequence-independent machine set-up time
 precedes the processing of the first job of each group. Each group has
 group-dependent multiple due windows. The objective is to find the optimal
 job sequence, the set of jobs assigned to each due window sequence, the
 optimal group sequence, and the optimal due window assignment to minimise
 a total cost that comprises the earliness and tardiness penalties and the
 due window starting time and due window size costs. For the case where the
 number of jobs assigned to each due window in each group is given in
 advance, we show that the problem is solvable in <inline-formula
 id="ILM0001"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1058538_ilm0001.gif"/></inline-formula> time, where
 <italic>n</italic> is the total number of jobs. For the case where the
 number of jobs assigned to each due window in each group is unknown, we
 give an <inline-formula id="ILM0002"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1058538_ilm0002.gif"/></inline-formula> time algorithm
 to solve the problem, where <inline-formula id="ILM0003"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1058538_ilm0003.gif"/></inline-formula> and
 <italic>h</italic><sub><italic>i</italic></sub> is the number of due
 window of the <italic>i</italic>th group.
Journal: International Journal of Production Research 
Pages: 1244-1256 
Issue: 4 
Volume: 54 
Year: 2016 
Month: 2 
X-DOI: 10.1080/00207543.2015.1058538 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1058538 
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Template-Type: ReDIF-Article 1.0
Author-Name: Dwayne Cole 
Author-X-Name-First: Dwayne 
Author-X-Name-Last: Cole 
Author-Name: Burak Kazaz 
Author-X-Name-First: Burak 
Author-X-Name-Last: Kazaz 
Author-Name: Scott Webster 
Author-X-Name-First: Scott 
Author-X-Name-Last: Webster 
Title: Final purchase and trade-in decisions in response to a component phase-out announcement: a deterministic analysis 
Abstract:
 We investigate a problem faced by a durable goods manufacturer of a
 product that is no longer manufactured but still under warranty. A
 supplier announces that a component of the product will be phased out and
 specifies a deadline for the final order. A common response in traditional
 practice is to place a final order sufficient to cover future warranty
 claims. We analyse and compare this policy with two policies that use
 trade-in programmes to supplement the final order quantity: (i) A full
 trade-in policy where the firm issues a one-time offer to the entire
 population that has the product under warranty, and (ii) a matching
 trade-in policy where the firm issues a trade-in offer to a fraction of
 the warranty population in each period. Our analysis of a deterministic
 model leads to two main conclusions. First, we find that the savings from
 the use of a trade-in programme can be significant, and we identify
 easy-to-estimate measures that drive the magnitude of savings. Second, we
 find that a full trade-in policy is likely to be preferred over a matching
 trade-in policy. The policy is also easier and more practical to
 implement. However, if uncertainty in warranty demand is introduced, then
 a firm may benefit by combining elements of both policies -- an initial
 offer to a sizable fraction of the warranty population followed by
 periodic offers to remaining segments over time.
Journal: International Journal of Production Research 
Pages: 1257-1272 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1061225 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1061225 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jong Beom Jin 
Author-X-Name-First: Jong Beom 
Author-X-Name-Last: Jin 
Author-Name: Choon Seong Leem 
Author-X-Name-First: Choon Seong 
Author-X-Name-Last: Leem 
Author-Name: Choong Hyun Lee 
Author-X-Name-First: Choong Hyun 
Author-X-Name-Last: Lee 
Title: Research issues and trends in industrial productivity over 44 years 
Abstract:
 The purpose of this study is to determine the major issues and potential
 megatrends in productivity over the past 44&#xa0;years. Specifically, this
 has been done by reviewing the productivity literature and productivity
 trends in the area of manufacturing. Using this, a foundation for the
 direction of future productivity research is suggested. In this study,
 productivity-related trends and technology policy data were analysed to
 derive an initial productivity-related framework. In addition, a
 productivity issue framework for the academic fields was created by
 analysing productivity-related literature. Subsequently, trends in
 productivity studies as well as megatrends were analysed by placing common
 core issues in two categories. From an analysis of productivity trends, an
 initial framework of sixteen productivity issues and a productivity issue
 framework comprising nine productivity issues from our literature analysis
 were established. By integrating the two frameworks, major
 productivity-related issues and six megatrends were identified. Our
 expectation is that the results of this study will serve as a foundation
 for the future academic studies as well as document manufacturing
 companies&#x2019; strategic methods addressing productivity.
Journal: International Journal of Production Research 
Pages: 1273-1284 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1064181 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064181 
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Template-Type: ReDIF-Article 1.0
Author-Name: Subrata Mitra 
Author-X-Name-First: Subrata 
Author-X-Name-Last: Mitra 
Title: Optimal pricing and core acquisition strategy for a hybrid manufacturing/remanufacturing system 
Abstract:
 Remanufacturing is one of the product recovery options where the quality
 of used products (cores) is upgraded to &#x2018;as-good-as-new&#x2019;
 conditions. In this article, we consider a monopolist firm selling new and
 remanufactured products to quality-conscious primary customers and
 price-sensitive secondary customers, respectively, with one-way
 substitution, i.e. some primary customers may substitute new products by
 remanufactured products while secondary customers can never afford to buy
 new products. We develop economic models under two scenarios -- when the
 supply of cores is unconstrained and when manufacturers have to procure
 cores at an acquisition price. The major observations of the article are
 as follows. A firm is better off when there is no constraint on the supply
 of cores. Even when cores have to be acquired at an acquisition price, the
 profitability is higher than that when the firm does not engage in
 remanufacturing activities. When a larger number of primary customers
 replace new products with remanufactured products, there is partial
 cannibalization of new product sales; however, the combined market share
 and profitability of the firm increase. When core supply is constrained
 and customers are less sensitive to core prices, the limited supply of
 cores may render remanufacturing an infeasible option for the firm.
 Therefore, firms should not only generate awareness among primary
 customers to buy remanufactured products, but also step up efforts to
 ensure a steady supply of cores. We conclude the article with managerial
 implications and directions for future research.
Journal: International Journal of Production Research 
Pages: 1285-1302 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1067376 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1067376 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jin Cao 
Author-X-Name-First: Jin 
Author-X-Name-Last: Cao 
Author-Name: Zhibin Jiang 
Author-X-Name-First: Zhibin 
Author-X-Name-Last: Jiang 
Author-Name: Kangzhou Wang 
Author-X-Name-First: Kangzhou 
Author-X-Name-Last: Wang 
Title: Customer demand prediction of service-oriented manufacturing incorporating customer satisfaction 
Abstract:
 With the emergence of individualised and personalised customer demands,
 the interaction of service and product has come into the sight of
 manufacturers and thus promoted the arising of service-oriented
 manufacturing (SOM), a new business mode that combines manufacturing and
 service. Be similar to the conventional manufacturing, the customer demand
 prediction (CDP) of SOM is very important since it is the foundation of
 the following manufacturing stages. As there are always tight and frequent
 interactions between service providers and customers in SOM, the customer
 satisfaction would significantly influence the customer demand of the
 following purchasing periods. To cope with this issue, a novel CDP
 approach for SOM incorporating customer satisfaction is proposed. Firstly,
 the structural relationships among customer satisfaction index and the
 influence factors are quantitatively modelled by using the structural
 equation model. Secondly, to reduce the adverse effect of multiple
 structural input data and small sample size, the least square support
 vector mechanism is employed to predict customer demand. Finally, the CDP
 of the air conditioner compressor which is a typical SOM product is
 implemented as the real-case example, and the effectiveness and validity
 of the proposed approach is elaborated from the prediction results
 analysis and comparison.
Journal: International Journal of Production Research 
Pages: 1303-1321 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1067377 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1067377 
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Template-Type: ReDIF-Article 1.0
Author-Name: Fatemeh Firouzi 
Author-X-Name-First: Fatemeh 
Author-X-Name-Last: Firouzi 
Author-Name: Mohamad Y. Jaber 
Author-X-Name-First: Mohamad Y. 
Author-X-Name-Last: Jaber 
Author-Name: Enzo Baglieri 
Author-X-Name-First: Enzo 
Author-X-Name-Last: Baglieri 
Title: Trust in supply forecast information sharing 
Abstract:
 In this paper, we investigate the role of trust in supply forecast
 signalling in a supply chain with a supplier and a manufacturer in a
 one-shot game. It is assumed that the supplier faces a random yield
 uncertainty that is multiplied by the manufacturer&#x2019;s order
 quantity. The supplier has a private forecast of yield risk. Based on the
 information, the supplier decides whether to share its forecast
 truthfully, or not to share. On the other hand, the manufacturer is faced
 with two ordering strategies. If it trusts the supplier&#x2019;s report,
 then it updates its belief on the yield risk providing a forecast signal
 by the supplier. Otherwise, it orders based on its prior belief. We
 analytically obtain the optimal order quantity where the random yield
 uncertainty follows uniform distribution. The intuitive result indicates
 that the supplier has a tendency to deviate from reporting true forecast
 information. The numerical results support the intuitive conclusion.
Journal: International Journal of Production Research 
Pages: 1322-1333 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1068961 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1068961 
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Template-Type: ReDIF-Article 1.0
Author-Name: Guowei Liu 
Author-X-Name-First: Guowei 
Author-X-Name-Last: Liu 
Author-Name: Suresh P. Sethi 
Author-X-Name-First: Suresh P. 
Author-X-Name-Last: Sethi 
Author-Name: Jianxiong Zhang 
Author-X-Name-First: Jianxiong 
Author-X-Name-Last: Zhang 
Title: Myopic vs. far-sighted behaviours in a revenue-sharing supply chain with reference quality effects 
Abstract:
 In this paper, we consider a dynamic supply chain where a manufacturer
 produces and distributes a featured product through an exclusive retailer
 to end consumers. The manufacturer decides the product quality and
 wholesale price, while the retailer sets the retail price in the presence
 of a revenue-sharing contract and consumers&#x2019; reference quality
 effects. The objective of this study is to investigate the impacts of
 myopic behaviour regarding the reference quality on the product quality
 and pricing strategies and profits of both members. Our results suggest
 that the manufacturer&#x2019;s myopia leads to a higher quality, higher
 price strategy and a higher quality--price ratio which benefits consumers.
 Meanwhile, relative to the far-sighted behaviour, myopia results in a more
 quality-sensitive but less price-sensitive market demand. What&#x2019;s
 more, we find that the manufacturer is apt to act in a far-sighted way,
 but the retailer isn&#x2019;t always willing to cooperate with a
 far-sighted manufacturer. Taking myopic strategies for both members is
 likely to gain a high profit of the whole supply chain for a relatively
 high marginal contribution of product quality on demand and a relatively
 low revenue-sharing proportion.
Journal: International Journal of Production Research 
Pages: 1334-1357 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1068962 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1068962 
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Template-Type: ReDIF-Article 1.0
Author-Name: S.A. Torabi 
Author-X-Name-First: S.A. 
Author-X-Name-Last: Torabi 
Author-Name: J. Namdar 
Author-X-Name-First: J. 
Author-X-Name-Last: Namdar 
Author-Name: S.M. Hatefi 
Author-X-Name-First: S.M. 
Author-X-Name-Last: Hatefi 
Author-Name: F. Jolai 
Author-X-Name-First: F. 
Author-X-Name-Last: Jolai 
Title: An enhanced possibilistic programming approach for reliable closed-loop supply chain network design 
Abstract:
 Most of current logistics network design models in the literature
 typically assume that facilities are always available and absolutely
 reliable while in practice, they are always subject to several operational
 and disruption risks. This paper proposes a reliable closed-loop supply
 chain network design model, which accounts for both partial and complete
 facility disruptions as well as the uncertainty in the critical input
 data. The proposed model is of mixed integer possibilistic linear
 programming type that aims to minimise simultaneously the total cost of
 opening new facilities and the expected cost of disruption scenarios. An
 enhanced possibilistic programming approach is proposed to deal with the
 epistemic uncertainty in input data. Furthermore, the
 <italic>p</italic>-robustness criterion is used to limit the cost of
 disruption scenarios and protect the designed network against random
 facility disruptions. Several numerical experiments along with sensitivity
 analyses on uncertain parameters are conducted to illustrate the
 significance and applicability of the developed model as well as the
 effectiveness of the proposed solution approach. Our results demonstrate
 that operational and disruption risks considerably affect the whole
 structure of the designed network and they must be taken into account when
 designing a reliable closed-loop logistics network.
Journal: International Journal of Production Research 
Pages: 1358-1387 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1070215 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1070215 
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Template-Type: ReDIF-Article 1.0
Author-Name: Fu-Kwun Wang 
Author-X-Name-First: Fu-Kwun 
Author-X-Name-Last: Wang 
Author-Name: Yeneneh Tamirat 
Author-X-Name-First: Yeneneh 
Author-X-Name-Last: Tamirat 
Title: Multiple comparisons with the best for supplier selection with linear profiles 
Abstract:
 In some manufacturing processes, the quality of a process or product is
 characterised by a linear profile. Comparing the process yield of multiple
 suppliers with linear profiles is an important task in supplier
 evaluation. In this study, we consider linear profiles with two-sided
 specifications and present the multiple comparisons with the best method
 based on the process yield index to select the best supplier. A subset
 contains the best supplier determined from the confidence interval of the
 difference between the process yield indices of the unknown best supplier
 and all of the suppliers. A simulation study is used to conduct the
 statistical power analysis. The results confirm that the larger the number
 of levels or the number of profiles, the larger the power of test. The
 simulation results indicate that our proposed method can effectively
 identify the best supplier. Two real examples are used to illustrate the
 applications of our proposed method.
Journal: International Journal of Production Research 
Pages: 1388-1397 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1070216 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1070216 
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Template-Type: ReDIF-Article 1.0
Author-Name: Saurabh Ambulkar 
Author-X-Name-First: Saurabh 
Author-X-Name-Last: Ambulkar 
Author-Name: Jennifer V. Blackhurst 
Author-X-Name-First: Jennifer V. 
Author-X-Name-Last: Blackhurst 
Author-Name: David E. Cantor 
Author-X-Name-First: David E. 
Author-X-Name-Last: Cantor 
Title: Supply chain risk mitigation competency: an individual-level knowledge-based perspective 
Abstract:
 Supply chain managers are responsible for making decisions regarding
 supply chain risk in order to mitigate the impact of supply chain
 disruptions. This study develops and tests a theoretical model that
 leverages the individual-level knowledge-based view perspective to
 understand the process through which risk mitigation orientation of the
 supply chain manager contributes to his/her absorptive capacity. A supply
 chain manager&#x2019;s absorptive capacity, in turn, enhances his/her
 ability to effectively mitigate supply chain risk. Study findings
 demonstrate that supply chain managers with high-risk mitigation
 orientation have greater level of absorptive capacity which enhances their
 risk mitigation competency. This study represents the first development
 and testing of a model that examines individual-level knowledge management
 factors that affect supply chain risk mitigation competency. This research
 emphasises the importance of the individual supply chain manager in
 managing risk and illustrates how theoretical perspectives from the
 knowledge management, supply chain risk and organisational behaviour
 literature can be fruitfully adopted to explain behaviour in the field of
 supply chain risk management.
Journal: International Journal of Production Research 
Pages: 1398-1411 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1070972 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1070972 
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Template-Type: ReDIF-Article 1.0
Author-Name: Konrad Zimmer 
Author-X-Name-First: Konrad 
Author-X-Name-Last: Zimmer 
Author-Name: Magnus Fr&#xf6;hling 
Author-X-Name-First: Magnus 
Author-X-Name-Last: Fr&#xf6;hling 
Author-Name: Frank Schultmann 
Author-X-Name-First: Frank 
Author-X-Name-Last: Schultmann 
Title: Sustainable supplier management -- a review of models supporting sustainable supplier selection, monitoring and development 
Abstract:
 In the last two decades, pressure from various stakeholders has forced
 many companies to establish environmental and social improvements both in
 their company and their supply chains. The growing number of journal
 publications and conference proceedings confirms this change also in
 academia. The aim of this paper is to analyse and review scientific
 literature on sustainable supplier management (SSM) with a focus on formal
 models supporting decision-making in sustainable supplier selection,
 monitoring and development. For this purpose, a framework on SSM is
 proposed and a comprehensive content analysis including a criteria
 analysis is carried out. Beyond this, in total 143 peer-reviewed
 publications between 1997 and 2014 have been analysed to identify both
 established and overlooked research fields. Major findings are the rapidly
 growing interest of this topic in academia in recent years, the
 predominance of Analytic Hierarchy Process, Analytic Network Process and
 fuzzy-based approaches, the focus on the final evaluation and selection
 process step and the rare investigation of social and quantitative
 metrics. This review may be useful for practitioners and scientists as it
 outlines major characteristics in this field, which can serve as a basis
 for further research.
Journal: International Journal of Production Research 
Pages: 1412-1442 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1079340 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1079340 
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Template-Type: ReDIF-Article 1.0
Author-Name: Pezhman Ghadimi 
Author-X-Name-First: Pezhman 
Author-X-Name-Last: Ghadimi 
Author-Name: Amir Hossein Azadnia 
Author-X-Name-First: Amir Hossein 
Author-X-Name-Last: Azadnia 
Author-Name: Cathal Heavey 
Author-X-Name-First: Cathal 
Author-X-Name-Last: Heavey 
Author-Name: Alexandre Dolgui 
Author-X-Name-First: Alexandre 
Author-X-Name-Last: Dolgui 
Author-Name: Birkan Can 
Author-X-Name-First: Birkan 
Author-X-Name-Last: Can 
Title: A review on the buyer--supplier dyad relationships in sustainable procurement context: past, present and future 
Abstract:
 Sustainable development is currently being applied in most fields of
 research. Procurement, focused on the buyer--supplier dyad, is one such
 discipline where sustainability is being widely applied. This paper
 provides a review of these research studies, conducting a systematic
 content analysis in order to present the state of the art in this domain.
 The paper carries out a detailed review of articles in international
 scientific journals and well-known international conferences related to
 green and sustainable supplier selection published between 2008 and 2014
 inclusive. Seven designed research questions are proposed and answered
 based on this bibliography. Interesting results are reported in each
 section and gaps in the current body of literature are identified. The
 purpose of this review is to provide important future directions and
 limitations in this research topic.
Journal: International Journal of Production Research 
Pages: 1443-1462 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1079341 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1079341 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Kannan Govindan 
Author-X-Name-First: Kannan 
Author-X-Name-Last: Govindan 
Author-Name: P.C. Jha 
Author-X-Name-First: P.C. 
Author-X-Name-Last: Jha 
Author-Name: Kiran Garg 
Author-X-Name-First: Kiran 
Author-X-Name-Last: Garg 
Title: Product recovery optimization in closed-loop supply chain to improve sustainability in manufacturing 
Abstract:
 When business practices shift from a traditional open supply chain to a
 closed loop instead, the environmental and societal issues are efficiently
 integrated in business development. However, even an efficiently
 integrated shift introduces a number of trade-offs due to the
 contradictory goals that emerge from that business&#x2019;s economical,
 environmental and social dimensions. In this paper, we propose a
 multi-objective mixed integer mathematical problem for a generic
 closed-loop supply chain (CLSC) network to rationalise how a
 system&#x2019;s product recovery helps to improve manufacturing
 sustainability. The CLSC network proposed in this study consists of a
 hybrid manufacturing facility, warehouse, distribution centres, collection
 centres and a hybrid recovery facility (HRF). The proposed model
 determines the best location for the HRF and optimal flow of products,
 recovered parts and material in the network while it simultaneously
 maximises profit, saves activity costs, helps to decrease the harmful
 effects of the manufacturing process and makes a positive impact on
 societal development. To validate the model, a numerical illustration with
 the help of a case study from an electrical manufacturing industry is
 offered. The results authenticate the approach of the model towards the
 fulfilment of various environmental regulations. A sensitivity analysis,
 completed on demand, and the return rate also assists decision-makers to
 manage their decisions with a broader insight towards manufacturing
 sustainability.
Journal: International Journal of Production Research 
Pages: 1463-1486 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1083625 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1083625 
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohannad Radhi 
Author-X-Name-First: Mohannad 
Author-X-Name-Last: Radhi 
Author-Name: Guoqing Zhang 
Author-X-Name-First: Guoqing 
Author-X-Name-Last: Zhang 
Title: Optimal configuration of remanufacturing supply network with return quality decision 
Abstract:
 This research studies the configuration problem of a remanufacturing
 production network together with the decision for return quality
 thresholds, in which, the manufacturer has multiple remanufacturing
 facilities to satisfy different market demands. Quality of returns is
 stochastic, while demand for remanufactured products is either stochastic
 or deterministic. The problem we considered is to determine facilities to
 operate, minimum quality to accept into each operating facility, return
 quantity and demand allocation simultaneously so that the system&#x2019;s
 profit is maximised. The problem is formulated as a mixed integer
 non-linear programming model. Through the use of a numerical example, the
 impact of quantity of returns, total spending, quality uncertainty, demand
 uncertainty and transportation cost on the remanufacturing system is
 analysed.
Journal: International Journal of Production Research 
Pages: 1487-1502 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1086034 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1086034 
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Template-Type: ReDIF-Article 1.0
Author-Name: S. Saha 
Author-X-Name-First: S. 
Author-X-Name-Last: Saha 
Author-Name: S.P. Sarmah 
Author-X-Name-First: S.P. 
Author-X-Name-Last: Sarmah 
Author-Name: Ilkyeong Moon 
Author-X-Name-First: Ilkyeong 
Author-X-Name-Last: Moon 
Title: Dual channel closed-loop supply chain coordination with a reward-driven remanufacturing policy 
Abstract:
 This paper investigates a reward-driven policy, employed in a closed-loop
 supply chain (CLSC), for acquiring used products earmarked for
 remanufacture. Under the examined model, a single manufacturer sells
 products through a retailer as well as directly to end users in a forward
 supply chain. In the reverse supply chain, three different modes of
 collection are employed to capture used products for remanufacture: they
 are through a third party, directly by the manufacturer and from the
 retailer. Mathematical models for both non-cooperative and centralised
 scenarios are developed to characterise the pricing decisions and
 remanufacturing strategies that indicate individual and overall supply
 chain performance. Optimality of all the proposed models is examined with
 theory. To coordinate and achieve a win--win outcome for channel members,
 we proposed a three-way discount mechanism for the manufacturer. Extended
 numerical investigation provides insights on ways to manage an efficient
 reward-driven CLSC in a dual-channel environment.
Journal: International Journal of Production Research 
Pages: 1503-1517 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1090031 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1090031 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Yeu-Shiang Huang 
Author-X-Name-First: Yeu-Shiang 
Author-X-Name-Last: Huang 
Author-Name: Ming-Chi Li 
Author-X-Name-First: Ming-Chi 
Author-X-Name-Last: Li 
Author-Name: Jyh-Wen Ho 
Author-X-Name-First: Jyh-Wen 
Author-X-Name-Last: Ho 
Title: Determination of the optimal degree of information sharing in a two-echelon supply chain 
Abstract:
 Information sharing is beneficial for supply chains, but often has
 marginally decreasing impacts on profit due to the costly expense of
 collecting more detailed information. This study aims to determine the
 optimal degree of information sharing with consideration of the trade-off
 between the cost of collecting information and the benefits gained by
 utilising it to enhance the profit of a two-echelon supply chain. Based on
 the analytical results, the profit that the supplier gains from
 information sharing can stem from the decrease in inventory cost after
 having more accurate information about demand. Furthermore, the impacts
 that the cost of collecting information has on the optimal degree of
 information sharing are investigated, and the results show that the
 optimal degree of information sharing is positively correlated to the
 correlation of successive market demand, that is, when the demand for
 successive periods is more correlated, information sharing becomes more
 valuable, and hence the optimal degree of information sharing increases.
Journal: International Journal of Production Research 
Pages: 1518-1534 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1092615 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1092615 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: James M. Wilson 
Author-X-Name-First: James M. 
Author-X-Name-Last: Wilson 
Title: The origin of material requirements planning in Frederick W. Taylor&#x2019;s planning office 
Abstract:
 Material Requirements Planning (MRP) systems appeared without significant
 provenance. Their theoretical and practical antecedents can be traced to
 Frederick W. Taylor&#x2019;s <italic>Shop Management</italic> that
 described a production planning and control system comprised of functional
 foremen and clerks. This system failed for it was too complex, unwieldy
 and expensive. Nevertheless, some elements survived -- for although the
 whole was unmanageable, a few individual functions survived as independent
 sub-systems. These continued in use; with Taylor&#x2019;s planning office
 (PO) remaining an ideal and well-known theoretical construct. The PO
 imposed unbearable information processing demands on contemporary manual
 systems. But from the mid-1930s, accounting machines started providing
 more capable information technologies that first allowed these individual
 elements to be implemented as stand-alone applications. Later they were
 then integrated into more full systems. Taylor&#x2019;s PO provided the
 sub-system pieces and the conceptual framework for their subsequent
 recombination and extension. This paper traces the evolution of production
 planning and control systems from Taylor&#x2019;s PO to MRP systems. Not
 only are the linkages between production management thinking in the
 different periods unappreciated, but so too are the technological
 relationships between the information technologies used.
Journal: International Journal of Production Research 
Pages: 1535-1553 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1092616 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1092616 
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Template-Type: ReDIF-Article 1.0
Author-Name: Alptekin Ulutas 
Author-X-Name-First: Alptekin 
Author-X-Name-Last: Ulutas 
Author-Name: Nagesh Shukla 
Author-X-Name-First: Nagesh 
Author-X-Name-Last: Shukla 
Author-Name: Senevi Kiridena 
Author-X-Name-First: Senevi 
Author-X-Name-Last: Kiridena 
Author-Name: Peter Gibson 
Author-X-Name-First: Peter 
Author-X-Name-Last: Gibson 
Title: A utility-driven approach to supplier evaluation and selection: empirical validation of an integrated solution framework 
Abstract:
 Supplier evaluation and selection (SES) problems have long been studied,
 leading to the development of a wide range of individual and hybrid models
 for solving them. However, the lack of widespread diffusion of existing
 SES models in the industry points to a need for simpler models that can
 systematically evaluate both qualitative and quantitative attributes of
 potential suppliers while enhancing the flexibility decision-makers need
 to account for relevant situational factors. Furthermore, empirical
 validations of existing models in SES have been few and far between. With
 a view to addressing these issues, this paper proposes an integrated
 solution framework that can be used to evaluate both tangible and
 intangible attributes of potential suppliers. The proposed framework
 combines three individual methods, namely the fuzzy analytic hierarchy
 process, fuzzy complex proportional assessment and fuzzy linear
 programming. The framework is validated through application in a Turkish
 textile company. The results generated using the proposed framework is
 compared with the actual historical data collected from the company.
 Additionally, a feasibility assessment is conducted on the sample supplier
 selection criteria employed, as well as assessment of the results
 generated using the proposed model.
Journal: International Journal of Production Research 
Pages: 1554-1567 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1098787 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1098787 
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Template-Type: ReDIF-Article 1.0
Author-Name: Maur&#xed;cio Fontoura Blos 
Author-X-Name-First: Maur&#xed;cio Fontoura 
Author-X-Name-Last: Blos 
Author-Name: S&#xe9;rgio Luiz Hoeflich 
Author-X-Name-First: S&#xe9;rgio Luiz 
Author-X-Name-Last: Hoeflich 
Author-Name: Eduardo M&#xe1;rio Dias 
Author-X-Name-First: Eduardo M&#xe1;rio 
Author-X-Name-Last: Dias 
Author-Name: Hui-Ming Wee 
Author-X-Name-First: Hui-Ming 
Author-X-Name-Last: Wee 
Title: A note on supply chain risk classification: discussion and proposal 
Abstract:
 The main objective of this note is to complement the excellent work on
 supply chain risk classification by Rangel et al. [International Journal
 of Production Research, vol. 52 (7), 2014]. In this note, we consider the
 use of ISO/IEC (International Organisation for
 Standardisation/International Electrotechnical Commission) norms to
 support the supply chain risk classification. Its purpose is to develop,
 maintain and promote standards in the fields of information technology and
 information communications technology. Therefore, to improve on the work
 by Rangel et al. (2014), ISO 27036 (<italic>Information Security for
 Supplier Relationship</italic>) and ISO 28000 (<italic>Specification for
 Security Management Systems for the Supply Chain</italic>) are aligned
 with ISO 31000 (<italic>Risk Management--Risk Assessment
 Techniques</italic>). Furthermore, since supply chain risk management does
 not have a standardised process, these norms, particularly ISO 31000, can
 serve as a guide to improve its implementation.
Journal: International Journal of Production Research 
Pages: 1568-1569 
Issue: 5 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1067375 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1067375 
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Template-Type: ReDIF-Article 1.0
Author-Name: Umit Bititci 
Author-X-Name-First: Umit 
Author-X-Name-Last: Bititci 
Author-Name: Paola Cocca 
Author-X-Name-First: Paola 
Author-X-Name-Last: Cocca 
Author-Name: Aylin Ates 
Author-X-Name-First: Aylin 
Author-X-Name-Last: Ates 
Title: Impact of visual performance management systems on the performance management practices of organisations 
Abstract:
 The purpose of this paper was to explore how visual strategy and
 performance management techniques impact performance measurement and
 management practices of organisations. A novel visual performance
 management approach is developed and implemented in qualitative case
 studies with seven manufacturing SMEs across Europe. The implementation
 cases demonstrate that visual management systems serve to support ongoing
 strategy development and implementation, facilitate performance
 measurement and review, enable people engagement, improve internal and
 external communication, enhance collaboration and integration, support the
 development of a continuous improvement culture and foster innovation.
 Additional explorative and longitudinal research is required to understand
 the long-term impact of such approaches in both small and larger
 organisations.
Journal: International Journal of Production Research 
Pages: 1571-1593 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1005770 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005770 
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Template-Type: ReDIF-Article 1.0
Author-Name: Dong Ding 
Author-X-Name-First: Dong 
Author-X-Name-Last: Ding 
Author-Name: Fugee Tsung 
Author-X-Name-First: Fugee 
Author-X-Name-Last: Tsung 
Author-Name: Jian Li 
Author-X-Name-First: Jian 
Author-X-Name-Last: Li 
Title: Directional control schemes for processes with mixed-type data 
Abstract:
 Mixed-type data consisting of both continuous observations and categorical
 observations are becoming prevalent in manufacturing processes and service
 management. The majority of existing statistical process control tools are
 designed to monitor either continuous data or categorical data but seldom
 both. In this article, we propose a directional exponentially weighted
 moving average control scheme composed of monitoring and diagnosis for
 mixed-type data. We assume that there is a latent unknown continuous
 distribution that determines the attribute levels of a categorical
 variable, and represent both continuous data and categorical data by
 standardised ranks. The proposed control chart also incorporates
 directional information to facilitate diagnosing the shift direction.
 Monte Carlo simulations demonstrate the efficiency of the proposed control
 scheme.
Journal: International Journal of Production Research 
Pages: 1594-1609 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1023402 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1023402 
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Template-Type: ReDIF-Article 1.0
Author-Name: Yiqian Cui 
Author-X-Name-First: Yiqian 
Author-X-Name-Last: Cui 
Author-Name: Junyou Shi 
Author-X-Name-First: Junyou 
Author-X-Name-Last: Shi 
Author-Name: Zili Wang 
Author-X-Name-First: Zili 
Author-X-Name-Last: Wang 
Title: Intermittent failure process and false alarm interaction modelling of threshold-based monitoring built-in tests (BITs) 
Abstract:
 Built-in tests (BITs) are widely used in manufacturing and production
 systems to find whether system failures occur, whereas the problem of BIT
 false alarms caused by intermittent failures adds to much trouble for the
 precise failure detection and diagnosis. Fighting with false alarms caused
 by intermittent failures is an urgent issue. However, the nature and
 temporal regularity of intermittent failures are not fully exploited, as
 well as the relationship between intermittent failure and BIT false
 alarms. The present paper introduces the method of constructing failure
 test profile for false alarm assessments. Probabilistic models are
 proposed of the failure evolution process, as well as the interactions
 between intermittent failures and false alarms. The false alarm time
 expectation is derived with the given model, serving as the foundation for
 the optimisation problem to find the best test threshold to enable the
 highest BIT capability. A numerical analysis is made to illustrate the
 proposed model and examine the threshold determination method. An
 application study is also carried out to show how the model can be
 applicable in real engineering practices.
Journal: International Journal of Production Research 
Pages: 1610-1626 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1023403 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1023403 
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Template-Type: ReDIF-Article 1.0
Author-Name: Weiqiang Jia 
Author-X-Name-First: Weiqiang 
Author-X-Name-Last: Jia 
Author-Name: Zhenyu Liu 
Author-X-Name-First: Zhenyu 
Author-X-Name-Last: Liu 
Author-Name: Zhiyun Lin 
Author-X-Name-First: Zhiyun 
Author-X-Name-Last: Lin 
Author-Name: Chan Qiu 
Author-X-Name-First: Chan 
Author-X-Name-Last: Qiu 
Author-Name: Jianrong Tan 
Author-X-Name-First: Jianrong 
Author-X-Name-Last: Tan 
Title: Quantification for the importance degree of engineering characteristics with a multi-level hierarchical structure in QFD 
Abstract:
 Quantification for the importance degree of engineering characteristics
 (ECs) is an essential problem in quality function deployment. In
 real-world scenario, it is sometimes difficult to directly evaluate the
 correlation degree between ECs and customer requirements (CRs) as ECs are
 too abstract. Thus, the target ECs have to be further decomposed into
 several more detailed basic ECs and organised by a multi-level
 hierarchical structure. The paper investigates the quantification problem
 for the importance degree of such target ECs and tackles two critical
 issues. The first issue is how to deal with the uncertainties including
 fuzziness and incompleteness involved during the evaluation process. A
 fuzzy evidential reasoning algorithm-based approach is proposed to tackle
 this issue and derive the correlation degree between each of the basic ECs
 and the whole CRs. The second issue is how to deal with the interactions
 among the basic ECs decomposed from the same target EC during the
 aggregation process. A <italic>&#x3bb;</italic>-fuzzy measure and fuzzy
 discrete Choquet integral-based approach is proposed to tackle this issue
 and aggregate these basic ECs. Final importance degree of the target ECs
 can then be obtained. At the end of this paper, a case study is presented
 to verify the feasibility and effectiveness of the method we propose.
Journal: International Journal of Production Research 
Pages: 1627-1649 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1041574 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1041574 
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Template-Type: ReDIF-Article 1.0
Author-Name: J. Zhang 
Author-X-Name-First: J. 
Author-X-Name-Last: Zhang 
Author-Name: W. Qin 
Author-X-Name-First: W. 
Author-X-Name-Last: Qin 
Author-Name: L.H. Wu 
Author-X-Name-First: L.H. 
Author-X-Name-Last: Wu 
Title: A performance analytical model of automated material handling system for semiconductor wafer fabrication system 
Abstract:
 To effectively analyse and evaluate the performances of closed-loop
 automated material handling system (AMHS) with shortcut and blocking in
 semiconductor wafer fabrication system, a modified Markov chain model
 (MMCM) has been proposed. The system characteristics, such as vehicle
 blockage and system&#x2019;s shortcut configuration, are well considered
 in the MMCM. The state space explosion problem and computational challenge
 due to the increase of AMHS scale can be effectively eliminated. With
 production data from Interbay material handling system of a 300-mm
 semiconductor wafer fabrication line, the proposed MMCM is compared with
 simulation analysis model. The results demonstrate that the proposed MMCM
 is an effective modelling methodology for AMHS&#x2019;s performance
 analysis at system design stage.
Journal: International Journal of Production Research 
Pages: 1650-1669 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1047980 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047980 
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Template-Type: ReDIF-Article 1.0
Author-Name: K.P. Tran 
Author-X-Name-First: K.P. 
Author-X-Name-Last: Tran 
Author-Name: P. Castagliola 
Author-X-Name-First: P. 
Author-X-Name-Last: Castagliola 
Author-Name: G. Celano 
Author-X-Name-First: G. 
Author-X-Name-Last: Celano 
Title: Monitoring the ratio of two normal variables using Run Rules type control charts 
Abstract:
 Recent studies show that Shewhart-type control charts monitoring the ratio
 of two normal random variables are useful to perform continuous
 surveillance in several manufacturing environments; anyway, they have a
 poor statistical sensitivity in the detection of small or moderate process
 shifts. The statistical sensitivity of a Shewhart control chart can be
 improved by implementing supplementary Run Rules. In this paper, we
 investigate the performance of Phase II Run Rules Shewhart control charts
 monitoring the ratio with each subgroup consisting of <inline-formula
 id="ILM0001"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1047982_ilm0001.gif"/></inline-formula> sample units. A
 Markov chain methodology coupled with an efficient normal approximation of
 the ratio distribution is used to evaluate the statistical performance of
 these charts. We provide an extensive numerical analysis consisting of
 several tables and figures to discuss the statistical performance of the
 investigated charts for deterministic and random shift sizes affecting the
 in-control ratio. An illustrative example from the food industry is
 provided for illustration.
Journal: International Journal of Production Research 
Pages: 1670-1688 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1047982 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047982 
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Template-Type: ReDIF-Article 1.0
Author-Name: Sandra Transchel 
Author-X-Name-First: Sandra 
Author-X-Name-Last: Transchel 
Author-Name: Saurabh Bansal 
Author-X-Name-First: Saurabh 
Author-X-Name-Last: Bansal 
Author-Name: Mrinmay Deb 
Author-X-Name-First: Mrinmay 
Author-X-Name-Last: Deb 
Title: Managing production of high-tech products with high production quality variability 
Abstract:
 We consider production systems in technology industries where output
 quality of a single production run has a large variance. Firms operating
 such systems classify products into different quality bins and sell units
 in one bin at the same tagged quality level and the same price. Consumers
 have heterogeneous quality preferences and choose that quality that
 maximises their net utility. We examine firms&#x2019; assortment,
 production and pricing problem. We present a three-stage solution
 procedure that optimises the production quantity, quality specification
 and number of bins. In that regard, we show that for a manufacturing
 technology with known quality distribution and known distribution of
 customers&#x2019; quality preference, the optimal assortment and
 production quantity are set such that on average, the demand of each bin
 is exactly fulfilled. We examine the impact of an improved manufacturing
 technology, variation in consumer preferences and changing price premium
 on the optimal assortment, lot size, market share, yield loss and the
 overall profitability. We further show that when the quality distribution
 of the manufacturing process is unknown, downward substitution leads to
 product offering of higher quality and higher prices. Finally, we discuss
 practical considerations for pricing, technology and optimal product
 offerings, and explain the proliferation of bins witnessed in the last
 decade in the processor industry.
Journal: International Journal of Production Research 
Pages: 1689-1707 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1053579 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1053579 
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Template-Type: ReDIF-Article 1.0
Author-Name: Ant&#xf3;nio Pedro Lacerda 
Author-X-Name-First: Ant&#xf3;nio Pedro 
Author-X-Name-Last: Lacerda 
Author-Name: Ana Raquel Xambre 
Author-X-Name-First: Ana Raquel 
Author-X-Name-Last: Xambre 
Author-Name: Helena Maria Alvelos 
Author-X-Name-First: Helena Maria 
Author-X-Name-Last: Alvelos 
Title: Applying Value Stream Mapping to eliminate waste: a case study of an original equipment manufacturer for the automotive industry 
Abstract:
 Since its beginning, lean manufacturing has built a worldwide reputation
 based on results related to production improvement and cost reduction in
 several companies. This management philosophy focuses on customer value
 creation through the elimination of production wastes. Lean methods and
 techniques have spread their scope from the automotive industry to a wide
 range of industries and services. This article presents a case study that
 describes the use of the lean tool value stream mapping in the production
 process of automotive parts for a major automotive company. At the
 beginning of the project, relevant data from the process were collected
 and analysed. Subsequently, the initial process was mapped, the related
 wastes were identified, and then future processes were mapped and
 financial results were estimated. The proposals were presented on
 <italic>kaizen</italic> meetings, the action plan was discussed and the
 decision regarding which option to choose was taken. Consequently, the
 Cycle Time and the level of the workforce were reduced, the process was
 improved and savings were obtained.
Journal: International Journal of Production Research 
Pages: 1708-1720 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1055349 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055349 
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Template-Type: ReDIF-Article 1.0
Author-Name: Hakan Tarakci 
Author-X-Name-First: Hakan 
Author-X-Name-Last: Tarakci 
Title: Two types of learning effects on maintenance activities 
Abstract:
 This paper studies a manufacturer with a system prone to failure. The
 manufacturer performs two types of maintenance activities: preventive
 maintenance (PM), performed periodically, resets the system, and Minimal
 Repair (MR), performed after breakdowns, restores the system to working
 condition. It is assumed that two different types of learning take place:
 (i) repetition learning: due to the repetitive nature of PM, the
 manufacturer gains experience and learns to perform the PM activities
 faster and at a lower cost and (ii) failure learning: each failure gives
 the manufacturer the opportunity to find the root causes, to learn from
 mistakes and to improve the system. This paper, the first one to quantify
 failure learning in maintenance literature, assumes that such learning can
 then be applied during the next PM activity, which brings down the failure
 rate for the next PM cycle. For the increasing failure rate case,
 repetition learning increases the PM frequency, whereas failure learning
 causes the manufacturer to reduce the optimal number of PM activities.
 However, for the constant failure rate, repetition learning has no effect
 on the PM frequency, whereas failure learning may actually increase it.
Journal: International Journal of Production Research 
Pages: 1721-1734 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1055847 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055847 
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Template-Type: ReDIF-Article 1.0
Author-Name: Debjit Roy 
Author-X-Name-First: Debjit 
Author-X-Name-Last: Roy 
Title: Semi-open queuing networks: a review of stochastic models, solution methods and new research areas 
Abstract:
 Capturing the waiting times (at an external queue) for a customer to
 access a movable resource is an important step towards measuring customer
 service and system performance in manufacturing, logistics, communication
 and health care systems. Such waiting time measures are typically used for
 sizing resource and buffer capacities, and thereby minimising customer
 waiting time probabilities. In this regard, semi-open queuing networks
 (SOQNs), which decouple the arriving customers/transactions from the
 network resources using a synchronisation station (also known as a
 semaphore queue), can potentially capture the customer/transaction waiting
 times/costs more precisely and provide a rich network modelling construct.
 Hence, modelling manufacturing or service systems using SOQNs is an
 important step towards measuring customer flow times (sojourn times)
 wherein the customer waiting times at an external queue are a critical
 component. In this paper, we present several stochastic models for
 manufacturing and service systems using SOQNs and also discuss the
 potential applications of SOQNs. We then review the solution methods for
 SOQNs and also compare the numerical accuracies for three promising
 methods. Finally, we include the potential research areas in SOQNs.
Journal: International Journal of Production Research 
Pages: 1735-1752 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1056316 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056316 
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Template-Type: ReDIF-Article 1.0
Author-Name: Chenglong Li 
Author-X-Name-First: Chenglong 
Author-X-Name-Last: Li 
Author-Name: Qin Su 
Author-X-Name-First: Qin 
Author-X-Name-Last: Su 
Author-Name: Min Xie 
Author-X-Name-First: Min 
Author-X-Name-Last: Xie 
Title: Economic modelling for statistical process control subject to a general quality deterioration 
Abstract:
 The applications of control chart have traditionally focused on the
 detection of step shifts in process mean. However, changes are usually
 gradual, not as perfect step shifts. The common consideration of a shift
 as a step function does not always adequately describe what actually
 happens in practice. Hence, there is a need for more realistic assumptions
 to be incorporated. This paper employs a Markov chain approach and
 provides a way to quantitatively measure the economic performance of
 control charts in the presence of a more general quality deterioration
 mechanism. The finite production run is considered in the model as it has
 become a very important production mode at present and the process failure
 mechanism is described by geometric distribution. The chart properties,
 particularly on the issues of the quality deterioration mechanism, are
 investigated. The findings provide critical insights on the use of step
 shift assumption when designing control charts.
Journal: International Journal of Production Research 
Pages: 1753-1770 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1056324 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056324 
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhen He 
Author-X-Name-First: Zhen 
Author-X-Name-Last: He 
Author-Name: Ling Zuo 
Author-X-Name-First: Ling 
Author-X-Name-Last: Zuo 
Author-Name: Min Zhang 
Author-X-Name-First: Min 
Author-X-Name-Last: Zhang 
Author-Name: Fadel M. Megahed 
Author-X-Name-First: Fadel M. 
Author-X-Name-Last: Megahed 
Title: An image-based multivariate generalized likelihood ratio control chart for detecting and diagnosing multiple faults in manufactured products 
Abstract:
 Image-capturing systems are increasingly being used in manufacturing shop
 floors since they can reliably capture important aesthetic information
 pertaining to the quality of manufactured parts in real time.
 State-of-the-art image-monitoring applications have focused on the
 detection of a single fault; however, the number of fault clusters per
 image in industrial applications can be numerous. To address this issue,
 we propose the use of a multivariate generalized likelihood ratio (MGLR)
 control chart for monitoring industrial products whose quality is
 described by a specific pattern (e.g. uniform patterns in LED screens or
 decorative patterns in textile products). Our method is specifically
 designed for greyscale images that are typical outputs of real-time
 industrial image-capturing systems. Extensive computer simulations show
 that the proposed method can detect the occurrence of single and multiple
 faults. We also present an experimental study to highlight how
 practitioners can implement and make use of the MGLR control chart in
 image-monitoring applications.
Journal: International Journal of Production Research 
Pages: 1771-1784 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1062569 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1062569 
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Template-Type: ReDIF-Article 1.0
Author-Name: Hatice Ucar Guner 
Author-X-Name-First: Hatice Ucar 
Author-X-Name-Last: Guner 
Author-Name: Ratna Babu Chinnam 
Author-X-Name-First: Ratna Babu 
Author-X-Name-Last: Chinnam 
Author-Name: Alper Murat 
Author-X-Name-First: Alper 
Author-X-Name-Last: Murat 
Title: Simulation platform for anticipative plant-level maintenance decision support system 
Abstract:
 Global competition and increasing customer expectations are forcing
 automobile manufacturers to improve their operations. Maintenance, being
 one of the most critical components in many industries, has a direct
 impact on the improvement of the overall production performance. In this
 paper, we introduce an anticipative plant-level maintenance decision
 support system (APMDSS) that provides guidance on corrective and
 preventive maintenance priorities based on the equipment bottleneck ranks
 with the objective of improving daily plant throughput. APMDSS anticipates
 the plant dynamics (i.e. bottlenecks, hourly buffer levels and likelihood
 of machine breakdowns) for upcoming shifts using starting state
 information of the production shift (e.g. equipment maintenance history,
 operational status of machines, buffer levels and scheduled production
 model mix). We also evaluate the performance of APMDSS using real data
 from an automotive body shop experiencing routine throughput difficulties
 due to frequent machine breakdowns. The results are compared with other
 methods from the literature and found to be superior in many settings.
Journal: International Journal of Production Research 
Pages: 1785-1803 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1064179 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064179 
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Template-Type: ReDIF-Article 1.0
Author-Name: Haiping Zhu 
Author-X-Name-First: Haiping 
Author-X-Name-Last: Zhu 
Author-Name: Cong Zhang 
Author-X-Name-First: Cong 
Author-X-Name-Last: Zhang 
Author-Name: Yuhao Deng 
Author-X-Name-First: Yuhao 
Author-X-Name-Last: Deng 
Title: Optimisation design of attribute control charts for multi-station manufacturing system subjected to quality shifts 
Abstract:
 The qualities of products are a major concern in any production system;
 thus implementing efficient inspection policies is of great importance to
 reduce quality-related costs. This article addresses the problem of
 finding optimal inspection policies for the multi-station manufacturing
 system (MMS) subjected to quality shifts to minimise total quality-related
 cost. Each station of the MMS may stay at either in-control condition or
 out-of-control condition, which may lead to different nonconforming
 product rates. Markov chain method is used to calculate the steady-state
 probability distribution (SSPD). Based on the SSPD, the cost structure of
 this MMS is analysed. The economical optimisation model of attribute
 control charts (ACCs) is then established, in which the decision variables
 are the control chart parameters: sampling interval, sample size and
 control limit. The ACCs optimisation model is resolved by the proposed
 integrated algorithm combining heuristic rule and tabu search. This
 approach is verified through an application case taken from a mobile phone
 shell production company. The results of comparative analysis show that
 the proposed model is much more economical than both the current outgoing
 inspection strategy and the regular <italic>np</italic> control chart. The
 sensitivity analysis of four input parameters is also conducted.
Journal: International Journal of Production Research 
Pages: 1804-1821 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1076190 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076190 
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Template-Type: ReDIF-Article 1.0
Author-Name: Shichang Du 
Author-X-Name-First: Shichang 
Author-X-Name-Last: Du 
Author-Name: Rui Zhang 
Author-X-Name-First: Rui 
Author-X-Name-Last: Zhang 
Title: Modelling and joint monitoring of input and output of systems with arbitrary order autoregressive disturbance 
Abstract:
 Considerable studies have been done on modelling and joint monitoring of
 input and output of systems with autoregressive moving average (ARMA)
 disturbance. Most of these studies focus on systems with ARMA (1, 1)
 disturbance. However, many kinds of systems are not conform to ARMA(1, 1)
 disturbance. Motivated by the fact that an autoregressive (AR) model with
 high order can be implemented to approximate the stationary ARMA model at
 any precision, a new generic model and a joint monitoring scheme of
 systems with arbitrary order AR(<italic>p</italic>) disturbance are
 developed. A minimum mean squared error (MMSE) controller with arbitrary
 order AR disturbance is designed to reduce the system variability. The
 mathematical expectation and average run length of MMSE-controlled outputs
 are derived. A new joint chart for monitoring the input and output
 simultaneously is explored. Two out-of-control rules for the joint
 monitoring chart are developed. The monitoring performances of the input
 chart, the output chart and the joint monitoring chart are also discussed.
 The results of simulation experiments and case studies validate the
 effectiveness of the developed model and joint monitoring chart.
Journal: International Journal of Production Research 
Pages: 1822-1838 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1078921 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1078921 
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Template-Type: ReDIF-Article 1.0
Author-Name: Shih-Wen Liu 
Author-X-Name-First: Shih-Wen 
Author-X-Name-Last: Liu 
Author-Name: Chien-Wei Wu 
Author-X-Name-First: Chien-Wei 
Author-X-Name-Last: Wu 
Title: A quick switching sampling system by variables for controlling lot fraction nonconforming 
Abstract:
 This article develops a new sampling scheme by variables inspection,
 namely a quick switching sampling (QSS) system based on the process yield
 index for lot determination when the quality characteristic is normally
 distributed with two specification limits. The QSS system can provide a
 flexible sampling procedure by switching decision policies, normal
 inspection and tightened inspection. The operating characteristic curve of
 the proposed QSS system is derived and required to pass through two
 designed points, acceptable quality level and limiting quality level for
 satisfying risks simultaneously suffered by the producer and the consumer.
 The proposed sampling system&#x2019;s performance is investigated and a
 comparison with the conventional variables single sampling (VSS) plan is
 also examined. The results indicate that the proposed system outperforms
 the VSS plan by requiring a smaller sample size for inspection while
 retaining the same protection. For practical purposes, the plan
 parameters&#x2019; tables are provided on the basis of various selected
 quality requirements and risks. Finally, we demonstrate the proposed
 sampling system using an example taken from a silicone LED lens industry.
Journal: International Journal of Production Research 
Pages: 1839-1849 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1084062 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1084062 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:6:p:1839-1849




Template-Type: ReDIF-Article 1.0
Author-Name: Andrea Matta 
Author-X-Name-First: Andrea 
Author-X-Name-Last: Matta 
Author-Name: Francesca Simone 
Author-X-Name-First: Francesca 
Author-X-Name-Last: Simone 
Title: Analysis of two-machine lines with finite buffer, operation-dependent and time-dependent failure modes 
Abstract:
 An analytical model for evaluating the throughput of two-machine lines,
 characterised by intermediate buffer with finite capacity, deterministic
 processing times and multiple failure modes for each machine is presented
 in this paper. Both operation-dependent failure and time-dependent failure
 are captured in a unique model as extension of the existing literature
 that was dealing with either one of them. Each machine has two failure
 modes, one is operation-dependent and the other is time-dependent. Time to
 failure and time to repair are assumed to be geometrically distributed.
 The presented method calculates the steady-state probabilities of the
 manufacturing system with a computational effort that depends only on the
 number of failure modes and not on the buffer capacity. A performance
 comparison of the proposed model with existing techniques is also
 reported, the aim is to show the error introduced by an analytical model
 that considers the operation-dependent failure mode as approximation of
 the time-dependent one.
Journal: International Journal of Production Research 
Pages: 1850-1862 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1085654 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1085654 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:6:p:1850-1862




Template-Type: ReDIF-Article 1.0
Author-Name: Mark Zais 
Author-X-Name-First: Mark 
Author-X-Name-Last: Zais 
Author-Name: Dan Zhang 
Author-X-Name-First: Dan 
Author-X-Name-Last: Zhang 
Title: A Markov chain model of military personnel dynamics 
Abstract:
 Personnel retention is one of the most significant challenges faced by the
 US Army. Central to the problem is understanding the incentives of the
 stay-or-leave decision for military personnel. Using three years of data
 from the US Department of Defense, we construct and estimate a Markov
 chain model of military personnel. Unlike traditional classification
 approaches, such as logistic regression models, the Markov chain model
 allows us to describe military personnel dynamics over time and answer a
 number of managerially relevant questions. Building on the Markov chain
 model, we construct a finite-horizon stochastic dynamic programming model
 to study the monetary incentives of stay-or-leave decisions. The dynamic
 programming model computes the expected pay-off of staying versus leaving
 at different stages of the career of military personnel, depending on
 employment opportunities in the civilian sector. We show that the
 stay-or-leave decisions from the dynamic programming model possess
 surprisingly strong predictive power, without requiring personal
 characteristics that are typically employed in classification approaches.
 Furthermore, the results of the dynamic programming model can be used as
 an input in classification methods and lead to more accurate predictions.
 Overall, our work presents an interesting alternative to classification
 methods and paves the way for further investigations on personnel
 retention incentives.
Journal: International Journal of Production Research 
Pages: 1863-1885 
Issue: 6 
Volume: 54 
Year: 2016 
Month: 3 
X-DOI: 10.1080/00207543.2015.1108533 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1108533 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:6:p:1863-1885




Template-Type: ReDIF-Article 1.0
Author-Name: Ali Ekici 
Author-X-Name-First: Ali 
Author-X-Name-Last: Ekici 
Author-Name: Ba&#x1e63;ak Altan 
Author-X-Name-First: Ba&#x1e63;ak 
Author-X-Name-Last: Altan 
Author-Name: Okan &#xd6;rsan &#xd6;zener 
Author-X-Name-First: Okan &#xd6;rsan 
Author-X-Name-Last: &#xd6;zener 
Title: Pricing decisions in a strategic single retailer/dual suppliers setting under order size constraints 
Abstract:
 In this paper, we study a duopolistic market of suppliers competing for
 the business of a retailer. The retailer sets the order cycle and
 quantities from each supplier to minimize its annual costs. Different from
 other studies in the literature, our work simultaneously considers the
 order size restriction and the benefit of order consolidation, and shows
 non-trivial pricing behaviour of the suppliers under different settings.
 Under asymmetric information setting, we formulate the pricing problem of
 the preferred supplier as a non-linear programming problem and use
 Karush--Kuhn--Tucker conditions to find the optimal solution. In general,
 unless the preferred supplier has high-order size limit, it prefers
 sharing the market with its competitor when retailer&#x2019;s demand,
 benefit of order consolidation or fixed cost of ordering from the
 preferred supplier is high. We model the symmetric information setting as
 a two-agent non-zero sum pricing game and establish the equilibrium
 conditions. We show that a supplier might set a &#x2018;threshold
 price&#x2019; to capture the entire market if its per unit fixed ordering
 cost is sufficiently small. Finally, we prove that there exists a
 joint-order Nash equilibrium only if the suppliers set identical prices
 low enough to make the retailer place full-size orders from both.
Journal: International Journal of Production Research 
Pages: 1887-1898 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1054451 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1054451 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:1887-1898




Template-Type: ReDIF-Article 1.0
Author-Name: Juzhi Zhang 
Author-X-Name-First: Juzhi 
Author-X-Name-Last: Zhang 
Author-Name: Qinglong Gou 
Author-X-Name-First: Qinglong 
Author-X-Name-Last: Gou 
Author-Name: Feng Yang 
Author-X-Name-First: Feng 
Author-X-Name-Last: Yang 
Author-Name: Liang Liang 
Author-X-Name-First: Liang 
Author-X-Name-Last: Liang 
Title: Online hot selling period and its impact on e-retailer&#x2019;s pricing strategies 
Abstract:
 The express delivery industry is often overloaded in some hot online
 selling seasons, which causes consumers&#x2019; dissatisfaction. Under
 such a circumstance, the e-retailer can utilise two opposite strategies,
 i.e. to set-up either a low price with a pre-announced markdown pricing
 (PMDP) strategy, or a high price with a pre-announced markup pricing
 (PMUP) strategy for the hot selling period. As both the prices and the
 express service quality are different between the regular period and the
 hot selling period, consumers can strategically choose their purchase
 time, which will in turn influences the e-retailer&#x2019;s pricing
 strategy. To investigate under what condition one pricing strategy will
 dominate the other, we propose a two period pricing model in which the
 selling season are divided into regular and hot selling period, and all
 consumers are assumed to be strategic. The e-retailer determines the
 prices over the two kinds of periods to maximise its profit. The
 comparison shows that a PMUP (resp. PMDP) strategy is preferred when the
 overloading degree in the hot selling period is slight (resp. heavy).
 Furthermore, we extend our model by incorporating the competition of
 traditional retailers.
Journal: International Journal of Production Research 
Pages: 1899-1918 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1057300 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1057300 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:1899-1918




Template-Type: ReDIF-Article 1.0
Author-Name: Michelle M.H. &#x15e;eref 
Author-X-Name-First: Michelle M.H. 
Author-X-Name-Last: &#x15e;eref 
Author-Name: Janice E. Carrillo 
Author-X-Name-First: Janice E. 
Author-X-Name-Last: Carrillo 
Author-Name: Arda Yenipazarli 
Author-X-Name-First: Arda 
Author-X-Name-Last: Yenipazarli 
Title: Multi-generation pricing and timing decisions in new product development 
Abstract:
 When planning for the introduction of a stream of new products into the
 marketplace, managers must consider both the timing and dynamic pricing
 decisions to determine an appropriate entry strategy into the marketplace.
 Literature in new product development (NPD) typically addresses optimal
 timing and pricing decisions independently. We develop an analytical model
 of coordinated product timing and pricing decisions when there are two
 generations of a new product under consideration. Factors driving the
 timing and pricing decisions include the unit sales and cost relationships
 for each generation as well as NPD costs for introducing the next
 generation of products. We derive analytic results that characterise the
 optimal timing and pricing strategies for a single product rollover
 scenario. We analyse several numerical examples to illustrate the
 interplay between optimal pricing and time-to-market strategies under more
 general settings.
Journal: International Journal of Production Research 
Pages: 1919-1937 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1061220 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1061220 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:1919-1937




Template-Type: ReDIF-Article 1.0
Author-Name: Yusen Xia 
Author-X-Name-First: Yusen 
Author-X-Name-Last: Xia 
Title: Responding to supplier temporary price discounts in a supply chain through ordering and pricing decisions 
Abstract:
 This paper considers a one-retailer and one-supplier supply chain and
 addresses the question of how a retailer should use its ordering and
 pricing decisions to respond to its supplier&#x2019;s temporary price
 discounts. The paper considers a hybrid environment -- somewhere between
 deterministic and stochastic modelling approaches -- that is, the retailer
 does not know when the next promotion from its supplier will occur but,
 once the promotion is announced, all its details are deterministic and
 often there is some time remaining before the promotion actually starts.
 We include in the objective function penalties on deviations from the
 original plan and explore the properties of the retailer&#x2019;s ordering
 and pricing decisions under fixed and flexible set-up scenarios. We show
 that, when the set-up epochs are fixed, the retailer&#x2019;s order
 quantities are monotonic and non-decreasing in situations where retail
 prices can be either fixed or flexible. When the set-up epochs are
 flexible, the ordering cycle is identical. Finally, we use some numerical
 examples to illustrate the proposed approach.
Journal: International Journal of Production Research 
Pages: 1938-1950 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1061224 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1061224 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:1938-1950




Template-Type: ReDIF-Article 1.0
Author-Name: Fuguo Zhao 
Author-X-Name-First: Fuguo 
Author-X-Name-Last: Zhao 
Author-Name: Desheng Wu 
Author-X-Name-First: Desheng 
Author-X-Name-Last: Wu 
Author-Name: Liang Liang 
Author-X-Name-First: Liang 
Author-X-Name-Last: Liang 
Author-Name: Alexandre Dolgui 
Author-X-Name-First: Alexandre 
Author-X-Name-Last: Dolgui 
Title: Lateral inventory transshipment problem in online-to-offline supply chain 
Abstract:
 Online-to-offline (OTO) is a new commercial model with enormous market
 potential. Online customer orders are forwarded to the offline
 brick-and-mortar store to fulfil, which is a combination of dual-channel
 supply chain. OTO overcomes many disadvantages of the traditional
 dual-channel supply chain, but still faces uncertain market demand. To
 reduce the inventory risk caused by demand uncertainty, lateral inventory
 transshipment is employed in this paper to pool inventory risk in OTO
 supply chain. We model centralised OTO and decentralised OTO with/without
 transshipment, and then analyse different scenarios. Our results
 demonstrate that there exists a unique Nash equilibrium of inventory order
 levels in dual channels and an optimal transshipment price to maximise the
 profit of the entire supply chain. Finally, we provide a numerical example
 of uniform demand distribution. Our analyses offer many managerial
 insights and show that transshipment always benefits the OTO supply chain.
Journal: International Journal of Production Research 
Pages: 1951-1963 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1070971 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1070971 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:1951-1963




Template-Type: ReDIF-Article 1.0
Author-Name: Moncer Hariga 
Author-X-Name-First: Moncer 
Author-X-Name-Last: Hariga 
Author-Name: Christoph H. Glock 
Author-X-Name-First: Christoph H. 
Author-X-Name-Last: Glock 
Author-Name: Taebok Kim 
Author-X-Name-First: Taebok 
Author-X-Name-Last: Kim 
Title: Integrated product and container inventory model for a single-vendor single-buyer supply chain with owned and rented returnable transport items 
Abstract:
 This study considers a single vendor supplying a single retailer with a
 finished product packed in returnable transport items (RTIs), such as
 containers, pallets or crates, to facilitate its safe shipment. Once
 received at the retailer&#x2019;s site, the RTIs are emptied, cleaned,
 repaired if needed and returned to the vendor to be used for the next
 shipment. Because of unexpected events, such as damage of RTIs and/or
 shortage of labour to empty RTIs, the RTI return time is considered
 stochastic in this study. In case the return of empty RTIs is delayed, the
 vendor has the option to rent RTIs from a nearby service provider to avoid
 disruptions in the delivery schedule and finished product shortages at the
 buyer&#x2019;s premise. We formulate the problem of coordinating the flow
 of both the finished product and RTIs and minimising the supply chain wide
 costs as a mixed-integer non-linear programme. For a convex objective
 function, we develop an efficient solution procedure that generates the
 optimal replenishment cycle, the optimal number of RTIs and the optimal
 number of trucks. The general optimisation model and the solution
 procedure are illustrated for the case where the RTI return time is
 exponentially distributed. In addition, we conduct an experimental study
 to assess the impact of the problem parameters on the decision variables.
 It is found that renting RTIs is especially beneficial in case both
 shortage cost and the risk of late RTI returns are high. In addition, the
 average RTI return time is found to be critical for the performance of the
 supply chain.
Journal: International Journal of Production Research 
Pages: 1964-1979 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1071896 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1071896 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:1964-1979




Template-Type: ReDIF-Article 1.0
Author-Name: Bo He 
Author-X-Name-First: Bo 
Author-X-Name-Last: He 
Author-Name: He Huang 
Author-X-Name-First: He 
Author-X-Name-Last: Huang 
Author-Name: Kaifu Yuan 
Author-X-Name-First: Kaifu 
Author-X-Name-Last: Yuan 
Title: Managing supply disruption through procurement strategy and price competition 
Abstract:
 When facing supply disruptions, the emergency procurement strategy and the
 optimal allocation procurement strategy are widely used strategies to
 manage supply risks. In this paper, buyers use these types of procurement
 strategies under the threat of supply disruption and engage in price
 competition. The structural properties of the procurement strategies are
 characterised by their reliability thresholds. We find that reliability
 thresholds play a critical role in buyer procurement strategy choices,
 which are related to the sales price, underage cost and differentials in
 unit procurement cost. A solution procedure is proposed to determine the
 equilibrium strategy profile. The effects of reliability levels and costs
 on the equilibrium prices, expected profits and equilibrium strategy
 profiles are explored. We extend the basic model to investigate the case
 of symmetric competition where buyers can freely choose their procurement
 strategy. The results show that in most cases, the competing buyers will
 choose the same strategy, whether an optimal allocation strategy with
 single sourcing or an emergency procurement strategy with dual sourcing.
 In a special parameter setting, the buyers will choose either strategy
 because they yield identical expected profits; this leads to multiple
 equilibria. We also find the equilibrium to be Pareto efficient.
Journal: International Journal of Production Research 
Pages: 1980-1999 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1074297 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1074297 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:1980-1999




Template-Type: ReDIF-Article 1.0
Author-Name: Ali Kefeli 
Author-X-Name-First: Ali 
Author-X-Name-Last: Kefeli 
Author-Name: Reha Uzsoy 
Author-X-Name-First: Reha 
Author-X-Name-Last: Uzsoy 
Title: Identifying potential bottlenecks in production systems using dual prices from a mathematical programming model 
Abstract:
 The importance of identifying bottlenecks in production systems for
 effective production control and continuous improvement is well
 recognised. A useful definition of a bottleneck is the station to whose
 performance the performance of the overall production system is most
 sensitive. However, obtaining accurate estimates of the impact of changes
 in a given station's performance on the performance of a production system
 is often difficult. This paper uses the dual prices associated with
 production resources in a production planning model to support the
 identification of bottlenecks as the product mix in the system changes
 over time. The planning model considers queueing behaviour at production
 resources using non-linear clearing functions. Relationships between the
 dual prices of different resources are derived, and the bottleneck
 information obtained is compared to that from a model that does not
 consider queueing behaviour.
Journal: International Journal of Production Research 
Pages: 2000-2018 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1076182 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076182 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:2000-2018




Template-Type: ReDIF-Article 1.0
Author-Name: Chao Fang 
Author-X-Name-First: Chao 
Author-X-Name-Last: Fang 
Author-Name: Xiangxiang Liao 
Author-X-Name-First: Xiangxiang 
Author-X-Name-Last: Liao 
Author-Name: Min Xie 
Author-X-Name-First: Min 
Author-X-Name-Last: Xie 
Title: A hybrid risks-informed approach for the selection of supplier portfolio 
Abstract:
 In conventional supplier selection approaches, cost consideration is
 usually emphasised and it renders a vulnerable supply chain with various
 risks. This article aims to develop a quantitative approach for modelling
 both supply chain operational risks and disruption risks to support
 decision-making with regard to order allocation and risk mitigation. We
 introduce two types of risk evaluation models: value-at-risk (VaR) and
 conditional value-at-risk (CVaR). Specifically, VaR is used to measure
 operational risks caused by improper selection and operations of a
 supplier portfolio to the stochastic demand, which may frequently occur
 but result in relatively small losses to supply chains; CVaR is used to
 evaluate disruption risks that are less frequent and tend to cause
 significant damage. After incorporating risk factors into a
 probability-based multi-criteria optimisation model, different methods and
 parameters are compared and tested to determine the factors that may
 influence the supplier selection process. Computational examples by
 simulation are presented to illustrate the approach and how
 decision-makers make trade-offs between costs and hybrid risks.
Journal: International Journal of Production Research 
Pages: 2019-2034 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1076947 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076947 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:2019-2034




Template-Type: ReDIF-Article 1.0
Author-Name: Ghazaleh Ahmadi 
Author-X-Name-First: Ghazaleh 
Author-X-Name-Last: Ahmadi 
Author-Name: S. Ali Torabi 
Author-X-Name-First: S. Ali 
Author-X-Name-Last: Torabi 
Author-Name: Reza Tavakkoli-Moghaddam 
Author-X-Name-First: Reza 
Author-X-Name-Last: Tavakkoli-Moghaddam 
Title: A bi-objective location-inventory model with capacitated transportation and lateral transshipments 
Abstract:
 We integrate location and inventory decisions in a three-echelon
 distribution network model with multiple products, capacitated in-house
 fleet and proactive transshipments between depots. The problem was
 originally motivated by the real-life case of a leading company in
 consumers&#x2019; household goods. The company offers a wide range of
 products which are different from demand pattern and shortage viewpoints.
 One of the product groups has seasonal trend with possibly lost sales
 during high seasons and backlog in low seasons, while the others lack any
 seasonal trend and get backlogged if any shortage occurs. A two-step
 process consisting of a new practical customer classification framework
 and a new mathematical model is developed. Total profit and
 customers&#x2019; dissatisfaction in the form of a new service-level
 measure are considered as the objective functions. To study the effects of
 transportation capacity on the network&#x2019;s performance, a second
 scenario with inclusion of third-party transportation resources is
 presented. Due to unavailability or insufficiency of required objective
 data about production capacities and demands, they are assumed to be
 imprecise (i.e. possibilistic). After converting the original fuzzy model
 to its equivalent crisp formulation, an interactive solution procedure is
 applied to deal with the trade-off between the conflicting objectives.
 Useful managerial insights are also derived from the numerical
 experiments.
Journal: International Journal of Production Research 
Pages: 2035-2056 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1082042 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1082042 
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:2035-2056




Template-Type: ReDIF-Article 1.0
Author-Name: Jun Yang 
Author-X-Name-First: Jun 
Author-X-Name-Last: Yang 
Author-Name: Wei Lu 
Author-X-Name-First: Wei 
Author-X-Name-Last: Lu 
Author-Name: He Xu 
Author-X-Name-First: He 
Author-X-Name-Last: Xu 
Title: Positive implications of market valuation under asymmetric quality information 
Abstract:
 We investigate a buyer&#x2019;s contract design problem in which the
 buyer&#x2019;s supplier has private quality cost information and is
 concerned with market valuation. We characterise the parameters of the
 contract menu (including quantity, quality level and transfer payment) and
 determine the market price. Our results show that the supplier&#x2019;s
 market value concern (MVC) has positive implications and mitigates the
 distortion of quality level. Although both the buyer and the entire chain
 system benefit from this MVC, it may give advantage or disadvantage to the
 supplier of the low-cost type, depending on this supplier&#x2019;s
 efficiency and the extent of the MVC. Numerical study reveals that the
 buyer is insensitive to the pricing decision, which suggests that
 contracts subject to the optimal market price without MVC serve as a good
 heuristic.
Journal: International Journal of Production Research 
Pages: 2057-2074 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1090033 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1090033 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:2057-2074




Template-Type: ReDIF-Article 1.0
Author-Name: Yao-Yu Wang 
Author-X-Name-First: Yao-Yu 
Author-X-Name-Last: Wang 
Author-Name: Jiasen Sun 
Author-X-Name-First: Jiasen 
Author-X-Name-Last: Sun 
Author-Name: Jian-Cai Wang 
Author-X-Name-First: Jian-Cai 
Author-X-Name-Last: Wang 
Title: Equilibrium markup pricing strategies for the dominant retailers under supply chain to chain competition 
Abstract:
 Markup pricing policies have been widely employed in the retailing
 industry. Under such policies, a retailer requires a retail margin over
 the wholesale price charged by the supplier to guarantee her
 profitability. This paper investigates and compares the performance of two
 commonly used markup pricing policies, namely, fixed-dollar markup and
 percentage markup, for the dominant retailers facing chain-to-chain
 competition. Our results demonstrate that the equilibrium pricing strategy
 for the dominant retailers seeking to maximise their respective profits is
 [PP]-strategy (i.e. both retailers select the percentage markup pricing
 policy), no matter what the demand curve and the level of chain-to-chain
 competition are. Unfortunately, this equilibrium will get in the
 prisoner&#x2019;s dilemma since the percentage markup pricing strategy
 might yield lower profits for the retailers and suppliers compared to its
 fixed-dollar counterpart when the level of chain-to-chain competition is
 high enough under the linear demand, which is contrast to the literature.
 If the criteria for the dominant retailers to select which markup pricing
 policy to offer is the whole channel&#x2019;s profit obtained under the
 decentralised decision-making scenario instead of themselves,
 [PP]-strategy is the dominant strategy and the unique Nash equilibrium of
 the pricing policy choice game regardless of the competitive intensity
 under the iso-elastic demand. This result holds true for the linear demand
 only when the level of chain-to-chain competition is below certain
 threshold; otherwise, both [FF] (i.e. both retailers select the
 fixed-dollar markup pricing policy) and [PP] can be the equilibrium
 pricing strategy.
Journal: International Journal of Production Research 
Pages: 2075-2092 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1101174 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1101174 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:2075-2092




Template-Type: ReDIF-Article 1.0
Author-Name: Jing Chen 
Author-X-Name-First: Jing 
Author-X-Name-Last: Chen 
Author-Name: Bintong Chen 
Author-X-Name-First: Bintong 
Author-X-Name-Last: Chen 
Title: Competing with customer returns policies 
Abstract:
 Return of products purchased by customers is a common phenomenon in the
 retail industry and results in costs to retailers. In practice, most
 retailers implement a full-refund policy, but the terms of customer
 returns policies vary. A customer returns policy serves as a post-customer
 service, and is a determinant factor in the customer&#x2019;s decision to
 purchase the product, in addition to other factors, such as the price of
 the product. In this paper, for competing retailers who face customer
 returns, competition from multiple retailers and uncertain customer
 valuations of the product, we develop a model to examine when retailers
 can survive and what pricing strategy they should implement in a
 competitive market. We identify the co-existence conditions for multiple
 retailers and the existence conditions of a Nash equilibrium among
 competing retailers. We also show the impact of customer returns on the
 retailers&#x2019; pricing and market share, as well as on profits in a
 competitive market. Numerical examples are included to illustrate the
 major results discussed in the paper.
Journal: International Journal of Production Research 
Pages: 2093-2107 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1106019 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106019 
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehmet G&#xfc;m&#xfc;&#x15f; 
Author-X-Name-First: Mehmet 
Author-X-Name-Last: G&#xfc;m&#xfc;&#x15f; 
Author-Name: Philip Kaminsky 
Author-X-Name-First: Philip 
Author-X-Name-Last: Kaminsky 
Author-Name: Sameer Mathur 
Author-X-Name-First: Sameer 
Author-X-Name-Last: Mathur 
Title: The impact of product substitution and retail capacity on the timing and depth of price promotions: theory and evidence 
Abstract:
 We investigate the impact of store capacity and extent of inter-product
 substitution in a retailer&#x2019;s assortment on the optimal timing and
 depth of price promotions. We develop a stylised model of a monopolistic
 retailer selling two substitutable products over time, where demand for
 each product in each period is a function of the prices of both products
 in that and earlier periods as well as the degree of substitution between
 the two periods. We present closed-form solutions to limiting cases of the
 model, and observe the following: When retailers optimise profits, (1)
 price promotions are relatively deeper in both absolute and relative terms
 at higher capacity stores than at low capacity stores, (2) price
 promotions for more expensive products are relatively deeper (shallower)
 in both absolute and relative terms than price promotions for cheaper
 products if the degree of substitution is low (high) and (3) the products
 are sequentially promoted if the degree of substitution is low, and
 simultaneously promoted if the degree of substitution is high. To confirm
 that these insights from a simple stylised two-product model are relevant
 in practice, we survey price promotions within the shampoo and detergent
 assortments of four mass-market retailers, and observe behaviour
 corresponding to the results from our stylised model.
Journal: International Journal of Production Research 
Pages: 2108-2135 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1108536 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1108536 
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Template-Type: ReDIF-Article 1.0
Author-Name: Shaorui Li 
Author-X-Name-First: Shaorui 
Author-X-Name-Last: Li 
Author-Name: Vaidyanathan Jayaraman 
Author-X-Name-First: Vaidyanathan 
Author-X-Name-Last: Jayaraman 
Author-Name: Antony Paulraj 
Author-X-Name-First: Antony 
Author-X-Name-Last: Paulraj 
Author-Name: Kuo-chung Shang 
Author-X-Name-First: Kuo-chung 
Author-X-Name-Last: Shang 
Title: Proactive environmental strategies and performance: role of green supply chain processes and green product design in the Chinese high-tech industry 
Abstract:
 Though many firms still believe that passive environmental strategies are
 sufficient, it is pertinent that they move beyond this belief and take a
 proactive supply chain-wide environmental stance so as to create a
 sustainable environment. In this paper, we seek to extend current work
 within green supply chain management by considering multiple green supply
 chain capabilities and performance measures. We hypothesise the linkage
 between environmental orientation, green supply chain capabilities and
 performance by drawing upon stakeholder theory and natural resource-based
 view. More importantly, our study is the first to distinguish between
 product and process-related capabilities in the green supply chain area
 and study their direct and mediating role with respect to environmental
 and financial performance measures. Using survey data collected from 256
 Chinese-based high-tech firms, we analyse several hypothesised
 relationships. Our results provide strong support for the significant role
 that green product design and green supply chain processes can play in
 improving firms&#x2019; environmental and financial performance.
 Interestingly, our results also suggest that green product design may not
 have a direct impact on financial performance.
Journal: International Journal of Production Research 
Pages: 2136-2151 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1111532 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1111532 
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Template-Type: ReDIF-Article 1.0
Author-Name: Maryam Esmaeili 
Author-X-Name-First: Maryam 
Author-X-Name-Last: Esmaeili 
Author-Name: Ghazaleh Allameh 
Author-X-Name-First: Ghazaleh 
Author-X-Name-Last: Allameh 
Author-Name: Taraneh Tajvidi 
Author-X-Name-First: Taraneh 
Author-X-Name-Last: Tajvidi 
Title: Using game theory for analysing pricing models in closed-loop supply chain from short- and long-term perspectives 
Abstract:
 Closed-loop supply chain (CLSC) management is an environmental approach to
 supply chain management that aims to prevent hazardous material from
 entering the nature by means of creating a reverse flow. This paper
 studies the short- and long-term behaviour of agents in implementing the
 appropriate collecting strategy in a two-echelon CLSC. In short-term,
 based on the Stackelberg game, several novel pricing models for different
 collecting strategies are proposed and compared. Then, the optimal
 policies of the pricing decisions are determined for each model. The
 long-term behaviour of companies in implementing collecting process is
 examined by evolutionary game theory and the most stable strategy is
 selected. Furthermore, a numerical example is presented to compare the
 different collecting structures. Finally, a managerial insight is provided
 to indicate the effect of key parameters such as remanufacturing rate,
 marketing elasticity and government subsidies on selecting the appropriate
 strategy.
Journal: International Journal of Production Research 
Pages: 2152-2169 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1115907 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1115907 
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Template-Type: ReDIF-Article 1.0
Author-Name: W.C. Tsai 
Author-X-Name-First: W.C. 
Author-X-Name-Last: Tsai 
Title: A dynamic sourcing strategy considering supply disruption risks 
Abstract:
 This study presents a formulation that supports decision-making by
 determining the optimal number of standby suppliers required to respond to
 supply failure risks. The problem of supply failure is modelled through a
 standby approach, in which failure is time-dependent. The probabilities of
 supply interruption, financial loss caused by supply failure, and
 operating cost of working with suppliers are modelled to yield the
 expected total cost, which enables organisations to determine the optimal
 number of suppliers. Two possible modes of substitution failure are
 considered in the standby model to enhance the analysis. A set of
 sensitivity analyses are performed for several input parameters to
 illustrate the model&#x2019;s behaviour. The analysis provides an optimal
 sourcing strategy depending on a combination of supply risk, operational
 cost vs. loss ratio and length of the supply period. The proposed model
 indicates the benefits of cost savings, unlike other dynamic models that
 use multiple suppliers simultaneously.
Journal: International Journal of Production Research 
Pages: 2170-2184 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1129465 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1129465 
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Template-Type: ReDIF-Article 1.0
Author-Name: Rajesh Kumar 
Author-X-Name-First: Rajesh 
Author-X-Name-Last: Kumar 
Author-Name: Parthasarathy Ramachandran 
Author-X-Name-First: Parthasarathy 
Author-X-Name-Last: Ramachandran 
Title: Revenue management in remanufacturing: perspectives, review of current literature and research directions 
Abstract:
 The pace of development in the world has increased over the years and with
 it, the use of hi-tech gadgets, consumer durables, automobiles, etc. has
 also gone up. In this context, as resources become more and more scarce,
 there are multiple challenges that emerge both from a sustainable
 development perspective, and from the perspective of meeting profitability
 objectives of a firm. Remanufacturing has come up in a big way as an
 answer to these challenges, but firms are struggling with respect to
 revenue management of this nascent area. We assess the current literature
 and distil the key factors that firms need to consider as they assimilate
 remanufacturing in their operations and revenue management strategy. We
 provide an assessment of white spaces in research in this area and also
 outline the directions for future research.
Journal: International Journal of Production Research 
Pages: 2185-2201 
Issue: 7 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2016.1141255 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1141255 
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Template-Type: ReDIF-Article 1.0
Author-Name: Nico Dellaert 
Author-X-Name-First: Nico 
Author-X-Name-Last: Dellaert 
Author-Name: Ezgi Cayiroglu 
Author-X-Name-First: Ezgi 
Author-X-Name-Last: Cayiroglu 
Author-Name: Jully Jeunet 
Author-X-Name-First: Jully 
Author-X-Name-Last: Jeunet 
Title: Assessing and controlling the impact of hospital capacity planning on the waiting time 
Abstract:
 In the literature, tactical plans of elective patients aim at increasing
 hospital efficiency through a better resource utilisation, although
 hospitals claim that patient satisfaction, usually measured by the waiting
 time, is also important. In this regard, the purpose of this paper is to
 show how patient satisfaction can be associated with any tactical plan, by
 developing a method to compute exact waiting time distributions. We also
 present a procedure to calculate the exact levels of resource utilisation.
 Therefore, with our procedures, hospital managers can determine the
 operational performance of their tactical plan. We then explore two
 strategies to improve tactical plans in terms of waiting time: slack
 planning and smooth allocation. A case study based on data from a Dutch
 cardiothoracic surgery centre shows that slack planning leads to a
 trade-off between waiting time and hospital efficiency. When slack
 planning is combined to smooth allocation, additional improvements of the
 waiting time can be reached.
Journal: International Journal of Production Research 
Pages: 2203-2214 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1051668 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1051668 
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Template-Type: ReDIF-Article 1.0
Author-Name: Christian B&#xfc;scher 
Author-X-Name-First: Christian 
Author-X-Name-Last: B&#xfc;scher 
Author-Name: Tobias Meisen 
Author-X-Name-First: Tobias 
Author-X-Name-Last: Meisen 
Author-Name: Daniel Schilberg 
Author-X-Name-First: Daniel 
Author-X-Name-Last: Schilberg 
Author-Name: Sabina Jeschke 
Author-X-Name-First: Sabina 
Author-X-Name-Last: Jeschke 
Title: VPI-FP: an integrative information system for factory planning 
Abstract:
 Nowadays, one of the main challenges in factory planning is the consistent
 and coherent information modelling along planning processes. Despite the
 current efforts in the fields of virtual production as well as digital and
 virtual factory, planning and simulation applications mostly support only
 the analysis and the optimisation of single planning aspects. However, to
 match nowadays challenges, planners require solutions that provide an
 integrated view to evaluate planning scenarios in advance and to achieve
 increasing production quality and efficiency. The concept of virtual
 production intelligence (VPI) provides a basic concept for such an
 integrative information system that enables planners to integrate, to
 aggregate and to analyse data gathered during one planning project as well
 as to compare different projects. In this study, we present such an
 information system for factory planning using the concept of the VPI. The
 focus lies in particular on the information modelling as well as the
 information integration and evaluation. Therefore, the study presents
 theoretical basics and implementations of the VPI platform within a
 precise application scenario in factory planning. This is to process and
 provide a consolidated information base along the whole planning process
 to support factory planning projects.
Journal: International Journal of Production Research 
Pages: 2215-2226 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1057298 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1057298 
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Template-Type: ReDIF-Article 1.0
Author-Name: Lin Tang 
Author-X-Name-First: Lin 
Author-X-Name-Last: Tang 
Author-Name: Li Zheng 
Author-X-Name-First: Li 
Author-X-Name-Last: Zheng 
Author-Name: Hui Cao 
Author-X-Name-First: Hui 
Author-X-Name-Last: Cao 
Author-Name: Ningjian Huang 
Author-X-Name-First: Ningjian 
Author-X-Name-Last: Huang 
Title: An improved multi-objective genetic algorithm for heterogeneous coverage RFID network planning 
Abstract:
 Recent research has demonstrated the potential benefits of radio frequency
 identification (RFID) technology in the supply chain and production
 management via its item-level visibility. However, the RFID coverage
 performance is largely impacted by the surrounding environment and
 potential collisions between the RFID devices. Thus, through RFID network
 planning (RNP) to achieve the desired coverage within the budget becomes a
 key factor for success. In this study, we establish a novel and generic
 multi-objective RNP model by simultaneously optimising two conflicted
 objectives with satisfying the heterogeneous coverage requirements. Then,
 we design an improved multi-objective genetic algorithm (IMOGA)
 integrating a divide-and-conquer greedy heuristic algorithm to solve the
 model. We further construct a number of computational cases abstracted
 from an automobile mixed-model assembly line to illustrate how the
 proposed model and algorithm are applied in a real RNP application. The
 results show that the proposed IMOGA achieves highly competitive solutions
 compared with Pareto optimal solutions and the solutions given by four
 recently developed well-known multi-objective evolutionary and swarm-based
 optimisers (SPEA2, NSGA-II, MOPSO and MOPS-super-2O) in terms of solution
 quality and computational robustness.
Journal: International Journal of Production Research 
Pages: 2227-2240 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1057299 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1057299 
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Template-Type: ReDIF-Article 1.0
Author-Name: Qifeng Cheng 
Author-X-Name-First: Qifeng 
Author-X-Name-Last: Cheng 
Author-Name: Shiwei Ning 
Author-X-Name-First: Shiwei 
Author-X-Name-Last: Ning 
Author-Name: Xiaohua Xia 
Author-X-Name-First: Xiaohua 
Author-X-Name-Last: Xia 
Author-Name: Fan Yang 
Author-X-Name-First: Fan 
Author-X-Name-Last: Yang 
Title: Modelling of coal trade process for the logistics enterprise and its optimisation with stochastic predictive control 
Abstract:
 In the paper, a typical coal trade process is described and modelled,
 where one logistics enterprise with blending equipments lies in the core
 and two types of common contracts are elucidated to define constraints. A
 mixed-integer model is built and featured by addressing contract
 violation, blending operation, real-time price information and arbitrarily
 distributed stochastic demands. To deal with the stochastic demands,
 probabilistic constraints are formed. Accordingly, stochastic model
 predictive control strategy with both receding horizon and decreasing
 horizon formulations is developed to handle the probabilistic constraints
 and exploit the value of newest price information. By solving a series of
 mixed-integer linear programmes, optimal coal trade decisions for the
 logistics enterprise can be obtained, including procurement decision,
 selling decision and operational decision of the blending equipments.
 Thorough simulation experiments are carried out and compared with three
 different strategies, which interpret the effectiveness of the proposed
 strategy.
Journal: International Journal of Production Research 
Pages: 2241-2259 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1062568 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1062568 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jelle de Vries 
Author-X-Name-First: Jelle 
Author-X-Name-Last: de Vries 
Author-Name: Ren&#xe9; de Koster 
Author-X-Name-First: Ren&#xe9; 
Author-X-Name-Last: de Koster 
Author-Name: Daan Stam 
Author-X-Name-First: Daan 
Author-X-Name-Last: Stam 
Title: Exploring the role of picker personality in predicting picking performance with pick by voice, pick to light and RF-terminal picking 
Abstract:
 Order pickers and individual differences between them could have a
 substantial impact on picking performance, but are largely ignored in
 studies on order picking. This paper explores the role of individual
 differences in picking performance with various picking tools (pick by
 voice, RF-terminal picking and pick to light) and methods (parallel, zone
 and dynamic zone picking). A unique realistic field experiment with 101
 participants (academic students, vocational students and professional
 pickers) is employed to investigate the influence of individual
 differences, especially the&#xa0;Big Five personality traits, on picking
 performance in terms of productivity and quality. The results suggest that
 (PbV) performs better than RF-terminal picking, and that Neuroticism,
 Extraversion, Conscientiousness and the age of the picker play a
 significant role in predicting picking performance with voice and
 RF-terminals. Furthermore, achieving higher productivity appears to be
 possible without sacrificing quality. Managers can increase picking
 performance by incorporating the insights in assigning the right pickers
 to work with a particular picking tool or method, leading to increased
 picking performance and reduced warehousing costs.
Journal: International Journal of Production Research 
Pages: 2260-2274 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1064184 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064184 
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Template-Type: ReDIF-Article 1.0
Author-Name: Cheng-Hsiang Liu 
Author-X-Name-First: Cheng-Hsiang 
Author-X-Name-Last: Liu 
Title: Solving the bi-objective optimisation problem with periodic delivery operations using a lexicographic method 
Abstract:
 Periodic deliveries are typical in a number of real-life applications.
 Minimising the number of vehicles required to make deliveries to a set of
 customers with known delivery frequencies is called the problem of vehicle
 minimisation for periodic deliveries (VMPD). Catering to the welfare of
 vehicle drivers has now become very important. Consequently, this work
 integrates the vehicle load balance factor into the VMPD problem by
 considering both the number of vehicles required to make periodic
 deliveries and the load balance between vehicles. This work presents
 integer programming formulations and applies a lexicographic method to
 this bi-objective VMPD problem. This work also examines whether
 decomposition can significantly reduce the size and difficulty of basic
 integer programming formulation in order to output close-to-optimal
 schedules for large problems within a reasonable computational time. A
 greedy balancing algorithm is also proposed to use it along with a
 decomposed integer programming formulation to yield a satisfactory
 solution in a relatively short time. Computational experiments demonstrate
 the better competitiveness of the proposed approaches compared to that of
 the existing approaches.
Journal: International Journal of Production Research 
Pages: 2275-2283 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1070969 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1070969 
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Template-Type: ReDIF-Article 1.0
Author-Name: Andreas Goerler 
Author-X-Name-First: Andreas 
Author-X-Name-Last: Goerler 
Author-Name: Stefan Vo&#xdf; 
Author-X-Name-First: Stefan 
Author-X-Name-Last: Vo&#xdf; 
Title: Dynamic lot-sizing with rework of defective items and minimum lot-size constraints 
Abstract:
 In most production processes, defective items may result from an imperfect
 production system and the need of reworking them is inevitable in many
 production environments. Despite the great importance of rework in
 real-world manufacturing, the body of literature is very limited. This
 paper deals with the effects of defective items and rework on the
 Capacitated Lot-Sizing Problem (CLSP). We present a mixed-integer
 programming formulation of the CLSP with rework of defective items and
 minimum lot-size constraints on production lots. The formulation describes
 an imperfect production process that leads to a fraction of defective
 items that have to be reworked before they can be sold to customers.
 Detailed numerical experiments show that while the occurrence of defective
 items significantly increases the computational times, reasonably sized
 minimum lot-size constraints, besides their practical importance, can be a
 good strategy to accelerate the solution process.
Journal: International Journal of Production Research 
Pages: 2284-2297 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1070970 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1070970 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Gerald Oeser 
Author-X-Name-First: Gerald 
Author-X-Name-Last: Oeser 
Author-Name: Pietro Romano 
Author-X-Name-First: Pietro 
Author-X-Name-Last: Romano 
Title: An empirical examination of the assumptions of the Square Root Law for inventory centralisation and decentralisation 
Abstract:
 The Square Root Law (SRL) is a popular formula for assessing inventory
 levels at varying numbers of warehouses. Its popularity is probably due to
 its simplicity and the ample opportunities for its application to the
 managerial dilemma of inventory centralisation vs. decentralisation.
 However, researchers disagree about which parts of inventory it can be
 applied to and its underlying assumptions. To address these questions,
 this study algebraically derives the assumptions necessary for the SRL to
 apply to regular, safety and total stock. Afterwards, the paper
 empirically examines to what extent these assumptions hold in practice by
 analysing four case studies and data from a sample of 280 German
 manufacturing and trading companies. Most companies do not fulfil the
 assumptions of the SRL and therefore cannot apply it with accurate
 results. Trading companies, however, seem to fulfil more assumptions than
 manufacturing ones, retailers more than wholesalers, industrial goods
 manufacturers more than consumer goods manufacturers. Although the SRL has
 traditionally been mainly considered for safety stock, companies,
 especially trading companies, appear to rather fulfil the assumptions for
 applying the SRL to cycle stock. Some assumptions seem to be
 complementary, whereas others appear to be competing, so that it is
 difficult to fulfil all of them.
Journal: International Journal of Production Research 
Pages: 2298-2319 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1071895 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1071895 
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Template-Type: ReDIF-Article 1.0
Author-Name: Tomoaki Yamazaki 
Author-X-Name-First: Tomoaki 
Author-X-Name-Last: Yamazaki 
Author-Name: Keisuke Shida 
Author-X-Name-First: Keisuke 
Author-X-Name-Last: Shida 
Author-Name: Takashi Kanazawa 
Author-X-Name-First: Takashi 
Author-X-Name-Last: Kanazawa 
Title: An approach to establishing a method for calculating inventory 
Abstract:
 In periodic review inventory systems, inventory is classified into cycle
 stock and safety stock. Cycle stock is defined as inventory that absorbs
 differences between supply and demand frequencies. It can be calculated
 without deficiency or excess because a method has been established for
 ensuring that the minimum on-hand inventory during a periodic review is
 zero. Safety stock is defined as inventory that absorbs various
 differences between supply and demand. Unlike for cycle stock, a method
 for calculating safety stock without deficiency or excess remains to be
 established. An approach is proposed to establishing a method for
 calculating inventory in which inventory is classified on the basis of the
 holding purpose and the calculation factors indicate solutions. This
 approach was applied to inventory held to absorb, on the basis of
 fluctuations in demand, the difference in terms of time and quantity
 between supply and demand. Stock held for this purpose is referred to as
 &#x2018;fluctuation stock&#x2019;. The objective is to establish a method
 for calculating fluctuation stock so that the minimum on-hand inventory
 during a periodic review is zero and to clarify the relationship between
 fluctuation stock and safety stock.
Journal: International Journal of Production Research 
Pages: 2320-2331 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1076179 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076179 
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Template-Type: ReDIF-Article 1.0
Author-Name: Ravi Ramya 
Author-X-Name-First: Ravi 
Author-X-Name-Last: Ramya 
Author-Name: Chandrasekharan Rajendran 
Author-X-Name-First: Chandrasekharan 
Author-X-Name-Last: Rajendran 
Author-Name: Hans Ziegler 
Author-X-Name-First: Hans 
Author-X-Name-Last: Ziegler 
Title: Capacitated lot-sizing problem with production carry-over and set-up splitting: mathematical models 
Abstract:
 This work proposes mathematical models (MMs) for the capacitated
 lot-sizing problem with production carry-over and set-up splitting, which
 can handle two scenarios, namely (1) situation/scenario where the set-up
 costs and holding costs are product dependent and time independent, and
 with no backorders or lost sales, and (2) situation where the set-up costs
 and holding costs are product dependent and time dependent, and with no
 backorders or lost sales. Previously, in an existing study the authors had
 developed a MM for the same problem and situation where the set-up costs
 and holding costs are product dependent and time independent, i.e. our
 Scenario 1. We compare our proposed models with the model in the existing
 study that appears to be incorrect.
Journal: International Journal of Production Research 
Pages: 2332-2344 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1076942 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076942 
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Template-Type: ReDIF-Article 1.0
Author-Name: Madalena Moreira 
Author-X-Name-First: Madalena 
Author-X-Name-Last: Moreira 
Author-Name: Benny Tjahjono 
Author-X-Name-First: Benny 
Author-X-Name-Last: Tjahjono 
Title: Applying performance measures to support decision-making in supply chain operations: a case of beverage industry 
Abstract:
 Performance measurement systems (PMS) have commonly been applied to
 evaluate and reward performances at managerial levels, especially in the
 context of supply chain management. However, evidence suggests that the
 effective use of PMS can also positively influence the behaviour and
 improve performance at an operational level. The motivation is to
 accomplish organisational goals, namely to increase supply chain
 flexibility by responding to evermore-varying customer demands in a timely
 manner. The purpose of the study described in this paper was to develop a
 conceptual framework that adopts performance measures for ex-ante
 decision-making at an operational level within the supply chain. To guide
 the research, five questions were asked and subsequently key gaps have
 been identified. In an attempt to fill the gaps, a case study at a major
 global brand beverage company has been carried out, and as a result, a
 conceptual framework of the PMS has been developed. Overall, the research
 offers a foundation of the applicability and impact of PMS in the supply
 chain and provides a framework that attends to some of the potential uses
 of PMS that so far have not been practically applied. The outcomes from
 the testing indicate that the initial gaps identified in the literature
 have been addressed and that the framework is judicious with scope for
 practical applicability. The framework is deemed worthy of further testing
 in different operational contexts of the supply chain.
Journal: International Journal of Production Research 
Pages: 2345-2365 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1076944 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076944 
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Template-Type: ReDIF-Article 1.0
Author-Name: Chao Lu 
Author-X-Name-First: Chao 
Author-X-Name-Last: Lu 
Author-Name: Ruiyou Zhang 
Author-X-Name-First: Ruiyou 
Author-X-Name-Last: Zhang 
Author-Name: Shixin Liu 
Author-X-Name-First: Shixin 
Author-X-Name-Last: Liu 
Title: A 0-1 integer programming model and solving strategies for the slab storage problem 
Abstract:
 We consider the slab storage problem (SSP) in slab yard operations. A set
 of slabs enter a slab yard in a specific order. A proper stack needs to be
 selected for each inbound slab, so that the number of relocations in the
 subsequent retrieval stage is minimised. We present a 0-1 integer
 programming model of the SSP that minimises the lower bound of the number
 of relocations. Four solving strategies are derived from several
 interesting properties of the mathematical model to speed up the solving
 process of the model. Making use of randomly generated instances and
 practical instances, we testify the effectiveness of the solving
 strategies and study the influence of problem parameters on the
 computational time of the model. Computational results show that the
 solving strategies can effectively reduce the computational time of the
 model and is applicable in medium-sized practical instances.
Journal: International Journal of Production Research 
Pages: 2366-2376 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1076949 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076949 
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Template-Type: ReDIF-Article 1.0
Author-Name: Ashesh Kumar Sinha 
Author-X-Name-First: Ashesh Kumar 
Author-X-Name-Last: Sinha 
Author-Name: Thomas Davich 
Author-X-Name-First: Thomas 
Author-X-Name-Last: Davich 
Author-Name: Ananth Krishnamurthy 
Author-X-Name-First: Ananth 
Author-X-Name-Last: Krishnamurthy 
Title: Optimisation of production and subcontracting strategies 
Abstract:
 We consider the problem of optimising production and subcontracting
 decisions in a supply chain manufacturing engineered products. The supply
 chain manager can use a combination of internal production capacities,
 available capacity at qualified subcontractors, make capital investments
 and process improvements to minimise costs associated with production and
 penalties for not meeting desired operational metrics. We formulate this
 as an optimisation problem that requires simultaneous solution of a
 mathematical programming problem and queuing network model. We propose an
 efficient iterative approach to solve this problem and conduct numerical
 studies to demonstrate the effectiveness of the approach.
Journal: International Journal of Production Research 
Pages: 2377-2393 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1077285 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1077285 
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Template-Type: ReDIF-Article 1.0
Author-Name: Carlos Herrera 
Author-X-Name-First: Carlos 
Author-X-Name-Last: Herrera 
Author-Name: Sana Belmokhtar-Berraf 
Author-X-Name-First: Sana 
Author-X-Name-Last: Belmokhtar-Berraf 
Author-Name: Andr&#xe9; Thomas 
Author-X-Name-First: Andr&#xe9; 
Author-X-Name-Last: Thomas 
Author-Name: V&#xed;ctor Parada 
Author-X-Name-First: V&#xed;ctor 
Author-X-Name-Last: Parada 
Title: A reactive decision-making approach to reduce instability in a master production schedule 
Abstract:
 One of the primary factors that impact the master production scheduling
 performance is demand fluctuation, which leads to frequently updated
 decisions, thereby causing instability. Consequently, global cost
 deteriorates, and productivity decreases. A reactive approach based on
 parametric mixed-integer programming&#xa0;(MIP) is proposed that aims to
 provide a set of plans such that a compromise between production cost and
 production stability is ensured. Several stability measures and their
 corresponding MIP model are proposed. An experimental study is performed
 to highlight the effectiveness of the reactive approach with regard to the
 proposed performance measures. It is observed that an improvement in
 stability does not mean a significant increase in the total production
 cost. Furthermore, the procedure yields a set of plans that in practice
 would enable flexible management of production.
Journal: International Journal of Production Research 
Pages: 2394-2404 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1078516 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1078516 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaolong Guo 
Author-X-Name-First: Xiaolong 
Author-X-Name-Last: Guo 
Author-Name: Yugang Yu 
Author-X-Name-First: Yugang 
Author-X-Name-Last: Yu 
Author-Name: Ren&#xe9; B.M. De Koster 
Author-X-Name-First: Ren&#xe9; B.M. 
Author-X-Name-Last: De Koster 
Title: Impact of required storage space on storage policy performance in a unit-load warehouse 
Abstract:
 The performance of a storage policy in a warehouse is usually evaluated on
 the basis of the average one-way travel distance/time needed to
 store/retrieve a load. Dividing the storage space into zones based on item
 turnover frequency can reduce the travel distance. However, for a given
 number of stored items, a larger number of storage zones also requires
 more storage space, because of reduced space sharing between the items,
 which increases travel time. This study considers the required space
 consumption by storage zoning in comparing the performance of random, full
 turnover-based and class-based storage policies for a unit-load warehouse
 operated by a forklift in single-command mode. A generalised travel
 distance model that considers the required space consumption is developed
 to compare the performance of these policies. Results show that the
 one-way travel distance of a random policy decreases with the increase in
 skewness of the demand curve. By considering the required space
 consumption, a class-based storage policy performs generally better than a
 full turnover-based policy. In addition, the optimal warehouse shape
 factor (ratio of warehouse width to depth) appears to decrease with the
 skewness of the demand curve. Warehouse managers are advised to adopt a
 wide-shallow warehouse layout when the item demands are approximately
 equal, whereas a narrow-deep layout is preferred when the demand curves
 are steep.
Journal: International Journal of Production Research 
Pages: 2405-2418 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1083624 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1083624 
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Template-Type: ReDIF-Article 1.0
Author-Name: Han Wu 
Author-X-Name-First: Han 
Author-X-Name-Last: Wu 
Author-Name: Gerald Evans 
Author-X-Name-First: Gerald 
Author-X-Name-Last: Evans 
Author-Name: Ki-Hwan Bae 
Author-X-Name-First: Ki-Hwan 
Author-X-Name-Last: Bae 
Title: Production control in a complex production system using approximate dynamic programming 
Abstract:
 Development of an efficient production and inventory control policy for a
 production system with multiple working stations, intermediate components
 and end products is difficult. In particular, uncertain demand and large
 changeover times at the work stations cause significant problems. In this
 paper, we consider an assembly line for dishwashers which require multiple
 types of wire racks that must be fabricated and coated at different work
 centres before supplying the assembly lines. An approximate dynamic
 programming (ADP) method is proposed to address the complexities
 associated with such a system. In addition, an Artificial Neural Network
 model is designed to approximate state values of the system, thus helping
 the system to make decisions at particular states. A near optimal
 production and inventory control policy is developed through an ADP
 algorithm. The proposed method can be extended to any similar system.
Journal: International Journal of Production Research 
Pages: 2419-2432 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1086035 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1086035 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Torbj&#xf8;rn H. Netland 
Author-X-Name-First: Torbj&#xf8;rn H. 
Author-X-Name-Last: Netland 
Title: Critical success factors for implementing lean production: the effect of contingencies 
Abstract:
 To facilitate the implementation of lean production, practitioners and
 researchers have suggested an array of critical success factors (CSFs).
 However, despite a broad consensus about what needs to be done, companies
 still struggle to implement lean. Contingency theory posits the
 explanation that the common advice is not universal but is instead
 contingent on the situation. This paper investigates how contingency
 variables influence what practitioners see as success factors for
 implementing lean. A survey asked 432 practitioners from 83 factories
 belonging to two multinational companies for their opinions about what
 managers should do to ensure the success of the factory-level
 implementation of lean production. The survey responses were grouped into
 general success factors, which were then tested for differences across
 four contingency variables: corporation, factory size, stage of lean
 implementation and national culture. In general, the analysis supports a
 generic list of CSFs, but with some minor exceptions. For example, the
 stage of lean implementation in a factory influences to a slight extent
 which factors are perceived as more effectual than others. The paper
 contributes to the literature on lean production and offers several
 recommendations for managers striving to implement lean in their firms.
Journal: International Journal of Production Research 
Pages: 2433-2448 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1096976 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1096976 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xinsheng Xu 
Author-X-Name-First: Xinsheng 
Author-X-Name-Last: Xu 
Author-Name: Zhiqing Meng 
Author-X-Name-First: Zhiqing 
Author-X-Name-Last: Meng 
Author-Name: Ping Ji 
Author-X-Name-First: Ping 
Author-X-Name-Last: Ji 
Author-Name: Chuangyin Dang 
Author-X-Name-First: Chuangyin 
Author-X-Name-Last: Dang 
Author-Name: Hongwei Wang 
Author-X-Name-First: Hongwei 
Author-X-Name-Last: Wang 
Title: On the newsvendor model with conditional Value-at-Risk of opportunity loss 
Abstract:
 To manage the risk arising from uncertainty in market demand, this paper
 introduces the Conditional Value-at-Risk (CVaR) measure into the decision
 framework of the newsvendor who aims to minimise his opportunity loss. It
 is found under the CVaR measure that the newsvendor&#x2019;s optimal order
 quantity is increasing in the confidence level when the understock loss is
 bigger than the overstock loss. This implies that an over-ordering may be
 even more caused by the newsvendor&#x2019;s risk aversion about
 opportunity loss than risk seeking behaviour. Under this optimal order
 quantity, it is proved that the newsvendor&#x2019;s expected profit and
 expected opportunity loss are decreasing and increasing in the confidence
 level, respectively. Furthermore, some management insights are presented
 to facilitate the risk management of the newsvendor model.
Journal: International Journal of Production Research 
Pages: 2449-2458 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1100765 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1100765 
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Template-Type: ReDIF-Article 1.0
Author-Name: Arun Kr. Purohit 
Author-X-Name-First: Arun Kr. 
Author-X-Name-Last: Purohit 
Author-Name: Devendra Choudhary 
Author-X-Name-First: Devendra 
Author-X-Name-Last: Choudhary 
Author-Name: Ravi Shankar 
Author-X-Name-First: Ravi 
Author-X-Name-Last: Shankar 
Title: Inventory lot-sizing with supplier selection under non-stationary stochastic demand 
Abstract:
 Inventory lot-sizing and supplier selection problem has been studied in
 the literature considering mainly time-varying deterministic demand.
 However, in real life, most of the products exhibit non-stationary
 stochastic demand. In this context, we propose an integer linear
 programming model for inventory lot-sizing and supplier selection problem
 under non-stationary stochastic demand with all-units quantity discounts
 and fill rate constraints. Through detailed analysis of experimental
 results, we show the impacts of fill rate requirements and demand
 coefficient of variation on costs, inventory levels and order allocations.
Journal: International Journal of Production Research 
Pages: 2459-2469 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1102354 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1102354 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jury Gualandris 
Author-X-Name-First: Jury 
Author-X-Name-Last: Gualandris 
Author-Name: Matteo Kalchschmidt 
Author-X-Name-First: Matteo 
Author-X-Name-Last: Kalchschmidt 
Title: Developing environmental and social performance: the role of suppliers&#x2019; sustainability and buyer--supplier trust 
Abstract:
 We explore how environmental and social performance of manufacturing firms
 can be improved as sustainable supply chain management (SSCM) develops and
 evolves within a firm from internal to external practices. Importantly,
 this study considers how key suppliers&#x2019; sustainability performance
 and buyer--supplier trust mediate and moderate such a development. A
 conceptual framework is developed which relies on resource-based theories
 and emerging empirical evidence. Then, partial least square methodology is
 applied on survey data from a sample of Italian manufacturing firms.
 Results show that manufacturing firms&#x2019; sustainability performance
 improves as SSCM develops; however, while internal practices have a direct
 impact on performance, the effect of external practices on a manufacturing
 firm&#x2019;s sustainability performance is fully mediated by key
 suppliers&#x2019; sustainability performance. Yet, buyer--supplier trust
 significantly influences the scope of such gains. Since evidence suggests
 that manufacturing firms are still struggling with how to leverage supply
 chain innovation potential for sustainable development, this study
 provides a timely and valuable contribution.
Journal: International Journal of Production Research 
Pages: 2470-2486 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1106018 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106018 
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Template-Type: ReDIF-Article 1.0
Author-Name: Rafael Diaz 
Author-X-Name-First: Rafael 
Author-X-Name-Last: Diaz 
Title: Using dynamic demand information and zoning for the storage of non-uniform density stock keeping units 
Abstract:
 The warehouse order-picking operation is one of the most labour-intense
 activities that has an important impact on responsiveness and efficiency
 of the supply chain. An understanding of the impact of the simultaneous
 effects of customer demand patterns and order clustering, considering
 physical restrictions in product storage, is critical for improving
 operational performance. Storage restrictions may include storing
 non-uniform density stock keeping units (SKUs) whose dimensions and weight
 constrain the order-picking operation given that a priority must be
 followed. In this paper, a heuristic optimisation based on a quadratic
 integer programming is employed to generate a layout solution that
 considers customer demand patterns and order clustering. A simulation
 model is used to investigate the effects of creating and implementing
 these layout solutions in conjunction with density zones to account for
 restrictions in non-uniform density SKUs. Results from combining layout
 optimisation heuristics and density zoning indicate statistical
 significant differences between assignments that ignore the aforementioned
 factors and those that recognise it.
Journal: International Journal of Production Research 
Pages: 2487-2498 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1106605 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106605 
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Template-Type: ReDIF-Article 1.0
Author-Name: B.C. Giri 
Author-X-Name-First: B.C. 
Author-X-Name-Last: Giri 
Author-Name: S. Bardhan 
Author-X-Name-First: S. 
Author-X-Name-Last: Bardhan 
Author-Name: T. Maiti 
Author-X-Name-First: T. 
Author-X-Name-Last: Maiti 
Title: Coordinating a three-layer supply chain with uncertain demand and random yield 
Abstract:
 The paper considers a three-layer supply chain involving one raw-material
 supplier, one manufacturer and one retailer. The market demand is assumed
 to be stochastic and productions at the raw-material supplier and
 manufacturer are subject to random yield. The centralised model is studied
 as the benchmark case. The decentralised model is solved and Nash
 equilibrium solutions are obtained. It is shown that buyback contract
 fails to coordinate such a supply chain. However, a composite contract
 framed combining buyback, and sales rebate and penalty contracts is shown
 to coordinate the supply chain. Numerical examples are provided to
 illustrate the developed models.
Journal: International Journal of Production Research 
Pages: 2499-2518 
Issue: 8 
Volume: 54 
Year: 2016 
Month: 4 
X-DOI: 10.1080/00207543.2015.1119324 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1119324 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Tone Lerher 
Author-X-Name-First: Tone 
Author-X-Name-Last: Lerher 
Title: Travel time model for double-deep shuttle-based storage and retrieval systems 
Abstract:
 Technological developments in the global supply chain have changed
 processes in warehousing. This reflects in short response time in handling
 the orders, which has a consequence on high automation degree in
 warehousing. An important part of automated warehouses is presented by
 shuttle-based storage and retrieval systems (SBS/RS), which are used in
 practice when demand for the throughput capacity is high. In this paper,
 analytical travel time model for the computation of cycle times for
 double-deep SBS/RS is presented. The advantage of the double-deep SBS/RS
 is that fewer aisles are needed, which results in a more efficient use of
 floor space. The proposed model considers the real operating
 characteristics of the elevators lifting table and the shuttle carrier
 with the condition of rearranging blocking totes to the nearest free
 storage location during the retrieval process of the shuttle carrier.
 Assuming uniform distributed storage locations and the probability theory,
 the expressions for the single and dual-command cycle of the elevators
 lifting table and the shuttle carrier have been determined. The proposed
 model enables the calculation of the expected cycle time for single- and
 dual-command cycles, from which the performance of the double-deep SBS/RS
 can be evaluated. The analysis show that regarding examined type of the
 double-deep SBS/RS, the results of the proposed analytical travel time
 model demonstrate good performances for evaluating double-deep SBS/RS.
Journal: International Journal of Production Research 
Pages: 2519-2540 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1061717 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1061717 
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Template-Type: ReDIF-Article 1.0
Author-Name: Lei Zhao 
Author-X-Name-First: Lei 
Author-X-Name-Last: Zhao 
Author-Name: Jihua Zhang 
Author-X-Name-First: Jihua 
Author-X-Name-Last: Zhang 
Author-Name: Jinxing Xie 
Author-X-Name-First: Jinxing 
Author-X-Name-Last: Xie 
Title: Impact of demand price elasticity on advantages of cooperative advertising in a two-tier supply chain 
Abstract:
 This paper focuses on pricing and vertical cooperative advertising
 decisions in a two-tier supply chain. Using a Stackelberg game model where
 the manufacturer acts as the game leader and the retailer acts as the game
 follower, we obtain closed-form equilibrium solution and explicitly show
 how pricing and advertising decisions are made. When market demand
 decreases exponentially with respect to the retail price and increases
 with respect to national and local advertising expenditures in an additive
 way, the manufacturer benefits from providing percentage reimbursement for
 the retailer&#x2019;s local advertising expenditure when demand price
 elasticity is large enough. Whether the manufacturer benefits from
 cooperative advertising is also closely related to supply chain
 member&#x2019;s relative advertising efficiency. In the decision for
 adopting coop advertising strategy, it is critical for the manufacturer to
 identify how market demand depends on national and local advertisements.
 The findings from this research can enhance our understanding of
 cooperative advertising decisions in a two-tier supply chain with
 price-dependent demand.
Journal: International Journal of Production Research 
Pages: 2541-2551 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1096978 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1096978 
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Template-Type: ReDIF-Article 1.0
Author-Name: Manojit Chattopadhyay 
Author-X-Name-First: Manojit 
Author-X-Name-Last: Chattopadhyay 
Author-Name: Sourav Sengupta 
Author-X-Name-First: Sourav 
Author-X-Name-Last: Sengupta 
Author-Name: B.S. Sahay 
Author-X-Name-First: B.S. 
Author-X-Name-Last: Sahay 
Title: Visual hierarchical clustering of supply chain using growing hierarchical self-organising map algorithm 
Abstract:
 The study identifies a need for efficient and robust visual clustering
 approach that can potentially deal with complex supply chain clustering
 problems. Based on the underlying philosophy of group technology, a
 growing hierarchical self-organising map algorithm (GHSOM) is proposed to
 identify a lower two-dimension visual clustering map that can effectively
 address supply chain clustering problems. The proposed approach provides
 optimal solutions by decomposing a large-sized supply chain problem into
 independent, small, manageable problems. It facilitates simple
 decision-making by exploring similar clusters that are represented by the
 neighbouring branches in the GHSOM map structure. Unlike other approaches
 in literature, the proposed approach can further attain good topological
 ordered representations of the various work order families, to be
 processed by clusters of supply units along with information on
 hierarchical sub-cell formation as identifiable from the visually
 navigable map. The proposed approach has been successfully applied on 16
 benchmarked problems. The performance of GHSOM based on grouping efficacy
 measure outperformed the best results in literature.
Journal: International Journal of Production Research 
Pages: 2552-2571 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1101175 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1101175 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Dirk Pieter van Donk 
Author-X-Name-First: Dirk Pieter 
Author-X-Name-Last: van Donk 
Author-Name: Ron van Doorne 
Author-X-Name-First: Ron 
Author-X-Name-Last: van Doorne 
Title: The impact of the customer order decoupling point on type and level of supply chain integration 
Abstract:
 Literature suggests that more supply chain (SC) integration increases of
 SC performance. However, recent research shows that contextual factors
 affect the effectiveness of SC integration efforts. Specifically, the
 location of the customer order decoupling point (CODP) might be such a
 factor, but there is limited empirical evidence. This study explores the
 impact of the location of the CODP on SC integration. It empirically
 investigates upstream, internal and downstream SC integration efforts in
 twelve metal parts producing Dutch companies to offer a comprehensive view
 of the effects of the location of the CODP on SC integration. Our results
 show a clear relationship between SC integration and the location of the
 CODP. Specifically, make-to-order (MTO), assemble-to-order (ATO) and
 make-to-stock (MTS) companies show relatively high levels in upstream,
 internal and downstream SC integration, respectively. Moreover, MTO
 companies mainly share forecast information and engage in joint R&D with
 their suppliers, ATO companies focus on internal SC integration using
 information systems and planning, while MTS companies interact with their
 customers intensively to exchange forecast information. Our study adds to
 the insight on the application of SC integration in different situations
 and offers initial evidence for the effects of the location of the CODP on
 SC integration.
Journal: International Journal of Production Research 
Pages: 2572-2584 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1101176 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1101176 
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Template-Type: ReDIF-Article 1.0
Author-Name: Gregory M. Kellar 
Author-X-Name-First: Gregory M. 
Author-X-Name-Last: Kellar 
Author-Name: George G. Polak 
Author-X-Name-First: George G. 
Author-X-Name-Last: Polak 
Author-Name: Xinhui Zhang 
Author-X-Name-First: Xinhui 
Author-X-Name-Last: Zhang 
Title: Synchronization, cross-docking, and decoupling in supply chain networks 
Abstract:
 At any distribution centre (DC), the decision of whether to synchronise
 inbound and outbound flows for cross-docking, or to decouple these flows
 by maintaining inventory, has a significant impact on supply chain
 performance. Key drivers of this decision, in turn, are the sizes of the
 discrete lots that comprise the flows. Thus, we formulate an original
 optimisation model that determines order lot-sizing decisions to minimise,
 for given constant arc flows, the sum of ordering cost and pipeline
 inventory cost on arcs and buffer inventory at DCs. The model employs an
 average throughput as a surrogate to estimate buffer inventory at
 facilities at which synchronisation is not economical and therefore serves
 to decouple inbound and outbound flows. Perfect lot-for-lot matching of
 shipments would impose very restrictive constraints on supply chain
 operations, but equality of average throughput indicates an innovative,
 relaxed mode of synchronisation. This mode is practicable for
 cross-docking by means of bulk-breaking or consolidation of shipments. A
 heuristic approach based on the Lagrangian relaxation and subgradient
 optimisation is developed for the non-linear mixed-general integer
 optimisation model, which is illustrated by numerical examples and tested
 using a benchmark data set.
Journal: International Journal of Production Research 
Pages: 2585-2599 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1107195 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1107195 
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Template-Type: ReDIF-Article 1.0
Author-Name: Hossein Salehi 
Author-X-Name-First: Hossein 
Author-X-Name-Last: Salehi 
Author-Name: Ata Allah Taleizadeh 
Author-X-Name-First: Ata Allah 
Author-X-Name-Last: Taleizadeh 
Author-Name: Reza Tavakkoli-Moghaddam 
Author-X-Name-First: Reza 
Author-X-Name-Last: Tavakkoli-Moghaddam 
Title: An EOQ model with random disruption and partial backordering 
Abstract:
 Perfect quality of batches is an assumption in the classic economic order
 quantity (EOQ) model (of inventory management); however, in practice some
 disruptions may occur in a supply chain. This paper presents an EOQ model
 with random disruption and partial backorders. So, when shortage occurs
 (due to quality problems or normal shortages), some customers are willing
 to wait for delivery until the next period. There is a finite probability
 that batches may be defective so an &#x2018;all or none&#x2019; policy is
 used after inspection of batches. The optimal inventory cost and the
 corresponding decision variables are studied. A solution method is
 proposed to optimise the inventory cost, and then two numerical examples
 and a sensitivity analysis are provided to illustrate the results.
Journal: International Journal of Production Research 
Pages: 2600-2609 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1110634 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1110634 
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Template-Type: ReDIF-Article 1.0
Author-Name: Alessandro Andriolo 
Author-X-Name-First: Alessandro 
Author-X-Name-Last: Andriolo 
Author-Name: Daria Battini 
Author-X-Name-First: Daria 
Author-X-Name-Last: Battini 
Author-Name: Alessandro Persona 
Author-X-Name-First: Alessandro 
Author-X-Name-Last: Persona 
Author-Name: Fabio Sgarbossa 
Author-X-Name-First: Fabio 
Author-X-Name-Last: Sgarbossa 
Title: A new bi-objective approach for including ergonomic principles into EOQ model 
Abstract:
 Worldwide, production systems are demanding new procedures and tools
 towards responsible inventory management, both in theory and in practice.
 In real industrial environment, manual fmaterial handling activities such
 as loading/unloading and stocking/picking operations are performed daily
 when a purchase/production material order is processed into industrial
 plants, and can be source of work-related musculoskeletal disorders. Only
 in the last four years, environmental and social aspects of the production
 systems have been progressively introduced in lot-sizing international
 theory, mostly in order to address the increasing request of
 &#x2018;sustainability&#x2019; in modern society. Research in the
 lot-sizing area is fundamentally driven by the first basic model and by a
 large set of succeeding incremental steps, developed in order to better
 reflect real industrial problems and constraints. The social impact of
 economic order quantity policies has not been thoroughly investigated and
 is often discussed only via a descriptive approach. This work develops a
 new two-step approach capable of considering the social impact of
 lot-sizing procedures in terms of &#x2018;ergonomics&#x2019; along with
 traditional annual logistic costs. Such approach divides the lot-sizing
 decisions in two main types: &#x2018;In-house&#x2019;, where the most
 influential decision variable is the size of the packaging units to move
 within the plant; &#x2018;In-bound&#x2019;, where the optimal number of
 ergonomic bins to purchase per order determines the minimum total cost.
 The outcome is what is defined as the &#x2018;ergonomic lot-size&#x2019;,
 which permits companies to reduce the ergonomic risks for their workers,
 while continuing to be profitable and efficient in assembly line part
 feeding.
Journal: International Journal of Production Research 
Pages: 2610-2627 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1113324 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1113324 
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Template-Type: ReDIF-Article 1.0
Author-Name: A.C. Diamantidis 
Author-X-Name-First: A.C. 
Author-X-Name-Last: Diamantidis 
Author-Name: S.I. Koukoumialos 
Author-X-Name-First: S.I. 
Author-X-Name-Last: Koukoumialos 
Author-Name: M.I. Vidalis 
Author-X-Name-First: M.I. 
Author-X-Name-Last: Vidalis 
Title: Performance evaluation of a push--pull merge system with multiple suppliers, an intermediate buffer and a distribution centre with parallel machines/channels 
Abstract:
 This paper examines a push--pull merge system with external demand.
 Multiple reliable non-identical suppliers feed a buffer that is located
 immediately upstream a distribution centre (DC) with parallel identical
 reliable machines. The DC performs another operation on the items stored
 in the preceding buffer and the finished products are stored in another
 buffer (the finished products buffer) immediately downstream the DC.
 Customers arrive to the system according to a Poisson process with given
 intensity <italic>&#x3bb;</italic> and remove a finished product from the
 buffer of finished products. The size of a customer demand is equal to
 one. Both suppliers and the identical machines at DC have exponential
 service rates. The considered system is modelled as a continuous-time
 Markov process with discrete states. An algorithm that generates the
 transition matrix for any value of the parameters of the system is
 developed and all possible transition equations are derived and solved
 analytically. Once the transition matrix is known the performance measures
 of the model under consideration can be easily evaluated.
Journal: International Journal of Production Research 
Pages: 2628-2652 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1113325 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1113325 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jordi Pereira 
Author-X-Name-First: Jordi 
Author-X-Name-Last: Pereira 
Author-Name: Mariona Vil&#xe0; 
Author-X-Name-First: Mariona 
Author-X-Name-Last: Vil&#xe0; 
Title: A new model for supply chain network design with integrated assembly line balancing decisions 
Abstract:
 Supply chain network design aims at the integration of the different
 actors of a supply chain within a single framework in order to optimise
 the total profit of the system. In this paper, we consider the integration
 of line balancing issues within the tactical decisions of the supply
 chain, and we offer a novel model and a solution approach for the problem.
 The new approach decomposes the problem into multiple line balancing
 problems and a mixed integer linear model, which is easier to solve than
 the previously available non-linear mixed integer formulation. The results
 show that the new method is able to solve previously studied models within
 a fraction of the reported running times, and also allows us to solve
 larger instances than those reported in earlier works. Finally, we also
 provide some analysis on the influence of the cost structure, the demand
 and the structure of the assembly process on the final configuration of
 the assemblies and the distribution network.
Journal: International Journal of Production Research 
Pages: 2653-2669 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1115910 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1115910 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiang T.R. Kong 
Author-X-Name-First: Xiang T.R. 
Author-X-Name-Last: Kong 
Author-Name: Jian Chen 
Author-X-Name-First: Jian 
Author-X-Name-Last: Chen 
Author-Name: Hao Luo 
Author-X-Name-First: Hao 
Author-X-Name-Last: Luo 
Author-Name: George Q. Huang 
Author-X-Name-First: George Q. 
Author-X-Name-Last: Huang 
Title: Scheduling at an auction logistics centre with physical internet 
Abstract:
 Auction logistics centre (ALC) performs transshipment operation on auction
 products from their inbound-from-supplier transporters to their
 outbound-to-client transporters with goods trading functions. Major
 third-party trading service providers have solved technological problems
 of dealing with millions of simultaneous biddings. But logistics that
 fulfils the massive and lumpy auction demands in the centre is still
 challengeable. The lack of process visibility and synchronised schedule
 has made the congestion on material flow, especially for the trolley
 loading and auction trading stages. Space resource is wasted and auction
 products deteriorate as holding time increases. This paper aims to provide
 a first demonstration of scheduling for auctions of perishable goods using
 Physical Internet (PI). PI-enabled scheduling is vital to facilitate the
 decision-making process while ensuring required throughput time with large
 trading volumes. A PI-ALC is created to automate the flow of information
 and enable the flexible implementation of scheduling. Following the hybrid
 flowshop classification, a timely operation scheduling model is developed.
 A heuristic-based solution approach is proposed to minimise either
 makespan or value loss using a set of dispatching rules. Simulation
 experiments show that the dispatching--picking mechanisms have
 statistically significant interaction impacts on both performance
 criteria. Decision-makers should strike a balance between minimising
 makespan and value loss based upon the growth in the frozen buffer size.
 Finally, the sensitivity analyses justify that schedulers can flexibly
 select dispatching rules under various demand patterns and operation time
 windows, as well as system configurations and trolley sizes.
Journal: International Journal of Production Research 
Pages: 2670-2690 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1117149 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1117149 
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Template-Type: ReDIF-Article 1.0
Author-Name: Heng Kuang 
Author-X-Name-First: Heng 
Author-X-Name-Last: Kuang 
Author-Name: S. Jack Hu 
Author-X-Name-First: S. Jack 
Author-X-Name-Last: Hu 
Author-Name: Jeonghan Ko 
Author-X-Name-First: Jeonghan 
Author-X-Name-Last: Ko 
Title: A dynamic programming approach to integrated assembly planning and supplier assignment with lead time constraints 
Abstract:
 As manufacturers face fierce competition in the global market,
 responsiveness has become an important competitiveness factor in addition
 to quality and cost. One essential responsiveness strategy is to reduce
 product development and lead times by integrating assembly planning with
 supplier assignment. This paper addresses the problem of integrated
 assembly and supply chain design under lead-time constraints by
 formulating and solving an optimisation problem with minimal total supply
 chain costs. This new time-constrained joint optimisation problem belongs
 to an NP-hard resource-constrained scheduling problem. To model this
 problem effectively, we develop a novel Hyper AND/OR graph and apply it
 for integrating assembly and supply chain decisions. We also develop a
 dynamic programming model and associated algorithm in order to solve the
 integrated optimisation problem with pseudo-polynomial time complexity in
 practice. Numerical case studies validate that the methods developed can
 solve the integrated decision-making problem optimally and efficiently.
 This paper overcomes the limitations of previous studies on concurrent
 assembly decomposition and supplier selection, which optimises cost
 without time constraints. The models and results of this research can be
 applied to a variety of areas including assembly design, maintenance
 module planning and supply chain restructuring.
Journal: International Journal of Production Research 
Pages: 2691-2708 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1118575 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1118575 
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Template-Type: ReDIF-Article 1.0
Author-Name: Dega Nagaraju 
Author-X-Name-First: Dega 
Author-X-Name-Last: Nagaraju 
Author-Name: A. Ramakrishna Rao 
Author-X-Name-First: A. 
Author-X-Name-Last: Ramakrishna Rao 
Author-Name: S. Narayanan 
Author-X-Name-First: S. 
Author-X-Name-Last: Narayanan 
Author-Name: P. Pandian 
Author-X-Name-First: P. 
Author-X-Name-Last: Pandian 
Title: Optimal cycle time and inventory decisions in coordinated and non-coordinated two-echelon inventory system under inflation and time value of money 
Abstract:
 In this paper, a mathematical model is developed for a coordinated and
 non-coordinated two-echelon inventory system comprising of a single
 manufacturer and a single retailer. The objective of the model is to
 demonstrate the optimality of cycle time and inventory decisions under the
 phenomena of different inflation rates at the manufacturer and retailer
 points. Also, it is aimed at determining the annual net revenue of the
 supply chain (SC). In the proposed model, the present value of the
 inflated ordering/set-up costs, purchase/unit costs, carrying costs and
 the gross revenue is computed for the retailer, manufacturer and the SC. A
 numerical example is devised to illustrate the optimality of decision
 variables and the objective function. Also, the sensitivity analysis is
 carried out. Results show that the present value of the annual net revenue
 of the retailer, manufacturer and SC decreases with increased inflation
 rate at the retailer and decreased inflation rate at the manufacturer
 simultaneously.
Journal: International Journal of Production Research 
Pages: 2709-2730 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1126679 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1126679 
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Template-Type: ReDIF-Article 1.0
Author-Name: Kangzhou Wang 
Author-X-Name-First: Kangzhou 
Author-X-Name-Last: Wang 
Author-Name: Shulin Lan 
Author-X-Name-First: Shulin 
Author-X-Name-Last: Lan 
Author-Name: Zhibin Jiang 
Author-X-Name-First: Zhibin 
Author-X-Name-Last: Jiang 
Title: Impact of customer impatience on a production service system 
Abstract:
 In this paper, we explore the impact of customer impatience on the
 performance of a production service system that consists of one production
 inventory subsystem and one service subsystem. It is inevitable that the
 un-storability of service makes customers wait in the production service
 system. Waiting for service easily leads to impatient behaviors. The
 impact of two kinds of impatient behaviors balk and reneging on the
 production service system performance is examined. The problem is
 formulated as a Markov system, then the stationary probability of the
 system is derived to conduct the performance evaluation. The results show
 that customer impatience has the different impact patterns on the two
 subsystems (i.e. production inventory subsystem and service subsystem) of
 the production service system. Specifically, customer impatience leads to
 the performance improvement of one subsystem along with the performance
 deterioration of the other subsystem. Meanwhile, service capacity plays an
 important role in the influence extent of customer impatience on the
 system performance. In addition, lower customer impatience does not
 necessarily improve system profit. Therefore, the management of the
 production service system with impatient customers will be more
 intractable. Some managerial insights and suggestions are proposed.
Journal: International Journal of Production Research 
Pages: 2731-2749 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1126680 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1126680 
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Template-Type: ReDIF-Article 1.0
Author-Name: Sheng-Pen Wang 
Author-X-Name-First: Sheng-Pen 
Author-X-Name-Last: Wang 
Author-Name: Wenyih Lee 
Author-X-Name-First: Wenyih 
Author-X-Name-Last: Lee 
Title: A note on &#x2018;A two-level supply chain with consignment stock agreement and stock-dependent demand&#x2019; 
Abstract:
 This note points out that the cost functions within Zanoni and Jaber
 [Zanoni, S. and M. Y. Jaber. 2015. &#x201c;A Two-level Supply Chain with
 Consignment Stock Agreement and Stock-dependent Demand.&#x201d;
 <italic>International Journal of Production Research</italic> 53:
 3561--3572] might be incorrect due to misuse of demand representation. By
 incorporating Braglia and Zavanella&#x2019;s consignment stock model and
 relaxing the zero-inventory reordering constraint, Zanoni and Jaber made
 extensions of the integrated vendor--buyer supply chain with
 stock-dependent demand in Sajadieh, Thorstenson, and Akbari Jokar&#x2019;s
 proposed model. However, Sajadieh, Thorstenson, and Akbari Jokar&#x2019;s
 model has different scenarios than Braglia and Zavanella&#x2019;s model,
 and these inconsistencies cause false formulation in Zanoni and
 Jaber&#x2019;s paper. In this note, we first formulate the justified cost
 functions and then present characteristics of the corrected model.
Journal: International Journal of Production Research 
Pages: 2750-2756 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1130872 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1130872 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Juin-Ming Tsai 
Author-X-Name-First: Juin-Ming 
Author-X-Name-Last: Tsai 
Author-Name: Shiu-Wan Hung 
Author-X-Name-First: Shiu-Wan 
Author-X-Name-Last: Hung 
Title: Supply chain relationship quality and performance in technological turbulence: an artificial neural network approach 
Abstract:
 A well-functioning supply chain management relationship cannot only
 develop seamless coordination with valuable members, but also improve
 operational efficiency to secure greater market share, increased profits
 and reduced costs. An accurate decision-making system considering
 multifactor relationship quality is highly desired. This study offers an
 alternative perspective and characterisation of the supply chain
 relationship quality and performance. A decision-making model is proposed
 with an artificial neural network approach for supply chain continuous
 performance improvement. Supply chain performance is analysed via a
 supervised learning back-propagation neural network. An
 &#x2018;inverse&#x2019; neural network model is proposed to predict the
 supply chain relationship quality conditions. Optimal performance
 parameters can be obtained using the proposed neural network scheme,
 providing significant advantages in terms of improved relationship
 quality. This study demonstrates a new solution with the combination of
 qualitative and quantitative methods for performance improvement. The
 overall accuracy rate of the decision-making model is 88.703%. The results
 indicated that trust has the greatest influence on the supply chain
 performance. Relationship quality among supply chain partners impacts
 performance positively as the pace of technological turbulence increases.
Journal: International Journal of Production Research 
Pages: 2757-2770 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1140919 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1140919 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Nana Bryan 
Author-X-Name-First: Nana 
Author-X-Name-Last: Bryan 
Author-Name: Mandyam M. Srinivasan 
Author-X-Name-First: Mandyam M. 
Author-X-Name-Last: Srinivasan 
Author-Name: S. Viswanathan 
Author-X-Name-First: S. 
Author-X-Name-Last: Viswanathan 
Title: Managing supply systems with partial information on shipment locations 
Abstract:
 This paper studies a supply system for a retailer who orders a single
 product from one manufacturer. Orders filled by the manufacturer pass
 through multiple transportation stages before reaching the retailer. Each
 stage represents either a physical location or a step in the delivery
 process. The lead time for a new order depends on the location of
 shipments against prior orders in transit. Shipments are not allowed to
 cross over in time. Thus, the movement of each shipment depends on the
 movements of shipments ahead of it and the resulting congestion. The
 retailer is able to track shipments as they move through the
 transportation channel. The retailer adopts an ordering policy that
 minimises the sum of his one-period holding and shortage costs, using
 available status information of shipments already in transit. The case
 where practical constraints prevent the retailer from obtaining a complete
 status of shipments at all stages in the transportation channel is
 considered. The methodology developed evaluates the value of partial
 shipment tracking information, and uses it to determine the optimal
 placement of a limited number of tracking devices. The methodology can
 also be used to evaluate the cost--benefit of placing additional tracking
 devices in the supply system.
Journal: International Journal of Production Research 
Pages: 2771-2779 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1142132 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1142132 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Toyin Clottey 
Author-X-Name-First: Toyin 
Author-X-Name-Last: Clottey 
Title: Development and evaluation of a rolling horizon purchasing policy for cores 
Abstract:
 A number of companies utilise end-of-use products (i.e. cores) for
 remanufacturing or recycling. An adequate supply of cores is needed for
 such activities. Establishing a purchasing policy for cores, over a finite
 planning horizon, requires multi-step ahead forecasts. Such forecasts are
 complicated by the fact that the number of cores in any future period
 depends upon previous sales and recent returns of the product. Distributed
 lag models have been used to capture this dependency for single-period
 ahead forecasts. We develop an approach to use distributed lag models to
 make multi-period ahead forecasts of net demand (i.e. demand minus
 returns), and investigate the cost implications, at a prescribed service
 level, of using such forecasts to purchase cores on a rolling horizon
 basis. Our results indicate that the effects of errors in the sales
 forecasts are negligible if sales follow an autoregressive pattern but are
 substantial when sales are more random. Dynamic estimation of the
 parameters in a rolling horizon environment yielded the most cost savings
 at high prescribed service levels (i.e. >0.95). Collectively, our results
 demonstrate the conditions in which companies can best leverage the
 dynamic nature of distributed lag models to reduce the acquisition costs
 over a finite horizon.
Journal: International Journal of Production Research 
Pages: 2780-2790 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1142133 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1142133 
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers. 
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Template-Type: ReDIF-Article 1.0
Author-Name: S. Jayaswal 
Author-X-Name-First: S. 
Author-X-Name-Last: Jayaswal 
Author-Name: E.M. Jewkes 
Author-X-Name-First: E.M. 
Author-X-Name-Last: Jewkes 
Title: Price and lead time differentiation, capacity strategy and market competition 
Abstract:
 We study a duopoly market in which customers are heterogeneous, and can be
 segmented as price or time sensitive. Each firm tailors (differentiates)
 its products/services for the two customer classes solely based on
 guaranteed lead time and the corresponding price. Our objective is to
 understand how competition affects price and lead time differentiation of
 the firms in the presence of different operations strategy (shared versus
 dedicated capacity), product substitution and asymmetry between the
 competing firms. Our results suggest that when firms use dedicated
 resources to serve the two market segments, pure price competition always
 tends to decrease individual prices as well as price differentiation,
 irrespective of the market behaviour. Further, the effect of competition
 is more pronounced when customers are allowed to self-select, thereby
 introducing substitutability between the two product options. On the other
 hand, when firms compete in time, in addition to price, the effect of
 competition on product differentiation depends crucially on the behaviour
 of the market. Our results further suggest that the firm with a larger
 market base should always maintain a larger price and lead time
 differentiation between the two market segments. Similarly, the firm with
 a capacity cost advantage should also maintain a larger lead time
 differentiation.
Journal: International Journal of Production Research 
Pages: 2791-2806 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1145816 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1145816 
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Template-Type: ReDIF-Article 1.0
Author-Name: Ata Allah Taleizadeh 
Author-X-Name-First: Ata Allah 
Author-X-Name-Last: Taleizadeh 
Author-Name: Mahsa Noori-daryan 
Author-X-Name-First: Mahsa 
Author-X-Name-Last: Noori-daryan 
Author-Name: Kannan Govindan 
Author-X-Name-First: Kannan 
Author-X-Name-Last: Govindan 
Title: Pricing and ordering decisions of two competing supply chains with different composite policies: a Stackelberg game-theoretic approach<xref ref-type="fn" rid="FN0001"/> 
Abstract:
 In today&#x2019;s global highly competitive markets, competition happens
 among supply chains instead of companies, as the members of supply chains.
 So, the partners of the chains seek to apply efficient coordinating
 strategies like discount, return, refund, buyback, or the other
 coordinating policies to abate the operation costs of the chains and
 subsequently increase market shares. Hence, because of the importance and
 application of these strategies in the current non-exclusive markets, in
 this study, we introduce different composite coordinating strategies to
 enhance the coordination of the supply chains. Here, we consider two
 competing supply chains where both chains launch the same product under
 different brands to the market by applying different composite
 coordinating strategies. Each supply chain comprises one manufacturer and
 a group of non-competing retailers where the manufacturer receives raw
 materials from an outside supplier and transforms them into a finished
 product; then, the products are sold to the retailers to satisfy the
 demands of market. In the first chain, a composite (QFF) policy, which is
 the combination of quantity and freight discount, as well as free shipping
 quantity policies, are considered between upstream and downstream members
 while in the second one, different composite polices are considered
 between upstream and downstream members such that the supplier offers a
 composite policy, as the first chain, to the manufacturer and the
 manufacturer proposes a composite (QPR) policy, which is the combination
 of quantity discount and partial-refund customer return policies, to the
 retailers. The main objective of the paper is to determine the optimal
 selling prices and the order quantities of the manufacturer and the
 retailers in each chain in presence of different composite coordinating
 strategies. A Stackelberg game-theoretic approach is employed between the
 members of each chain where the manufacturer is a follower and the
 retailers are leaders. The concavity of profit functions is proved.
 Finally, the applicability of the models is justified by presented
 numerical examples. Moreover, the effects of these strategies on the
 decisions of the chains&#x2019; partners are examined.
Journal: International Journal of Production Research 
Pages: 2807-2836 
Issue: 9 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1154621 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154621 
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Template-Type: ReDIF-Article 1.0
Author-Name: Guilherme Luz Tortorella 
Author-X-Name-First: Guilherme Luz 
Author-X-Name-Last: Tortorella 
Author-Name: Giuliano Almeida Marodin 
Author-X-Name-First: Giuliano Almeida 
Author-X-Name-Last: Marodin 
Author-Name: Diego de Castro Fettermann 
Author-X-Name-First: Diego de Castro 
Author-X-Name-Last: Fettermann 
Author-Name: Flavio Sanson Fogliatto 
Author-X-Name-First: Flavio Sanson 
Author-X-Name-Last: Fogliatto 
Title: Relationships between lean product development enablers and problems 
Abstract:
 The lean product development (LPD) approach uses lean principles and
 enablers (tools, techniques and practices) to reduce waste and
 continuously improve the product development processes (PDP). Other than
 reducing product development lead time, LPD also aims at improving quality
 by reducing problems that might occur during the process. Several LPD
 enablers are proposed in the existing literature; however, there is
 limited knowledge on how these enablers may effectively counteract the
 occurrence of problems in the PDP. We empirically tested the association
 between 4 groups of LPD enablers and 11 groups of LPD problems in a sample
 of 64 companies that are undergoing lean implementation in the shop floor
 and administrative areas. There are two major contributions here. First,
 we propose an empirically validated instrument for assessing the adoption
 of LPD enablers and the incidence of LPD problems in companies filling an
 existing gap in the literature. Second, we provide understanding on how
 LPD enablers can mitigate the incidence of LPD problems, allowing
 companies undergoing lean implementation to better manage their PDP.
 Moreover, some results demonstrate that the association between enablers
 and problems may not be as suggested in the existing literature.
Journal: International Journal of Production Research 
Pages: 2837-2855 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1106020 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106020 
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Template-Type: ReDIF-Article 1.0
Author-Name: Carlos Vila 
Author-X-Name-First: Carlos 
Author-X-Name-Last: Vila 
Author-Name: Juan Carlos Albi&#xf1;ana 
Author-X-Name-First: Juan Carlos 
Author-X-Name-Last: Albi&#xf1;ana 
Title: An approach to conceptual and embodiment design within a new product development lifecycle framework 
Abstract:
 The design of new innovative products is the result of an accurate and
 precise management of knowledge sources all over its life cycle, such as
 technology, market, competitors and suppliers. The work contributes with a
 framework that shows how the knowledge sources influence in the
 state-of-the-art and market needs so that they become opportunities for
 innovating products addressing the whole product life cycle. It provides a
 systematic path from the early generation of ideas to the production of a
 new product proposal. Through a deep analysis of previous research works
 of new product innovation life cycle development frameworks and linking it
 with knowledge management, strategic planning and scorecards, we came out
 with a structured contribution. The result considers the concurrent
 activities and its relationships all the way through the product life
 cycle that can help in creativity and innovation, combined with a process
 management proposal. Managing the sources of knowledge in highly dynamic
 markets and technologies is one of the major difficulties involved in
 innovative products design and development. The emerging knowledge from
 external sources is confronted with organisation internal knowledge and
 experience in order to achieve the first product correct.
Journal: International Journal of Production Research 
Pages: 2856-2874 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1110632 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1110632 
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Template-Type: ReDIF-Article 1.0
Author-Name: C&#xe9;sar Camis&#xf3;n 
Author-X-Name-First: C&#xe9;sar 
Author-X-Name-Last: Camis&#xf3;n 
Author-Name: Alba Puig-Denia 
Author-X-Name-First: Alba 
Author-X-Name-Last: Puig-Denia 
Title: Are quality management practices enough to improve process innovation? 
Abstract:
 The popularity of quality management as a system for continuous
 improvement has not been accompanied by deep theoretical understanding of
 its effects on process innovation. In this work, the resource-based view
 serves as the basis for the construction of a model designed to explain
 the effects of quality management practices (QMP) on process innovation
 performance and the mediating role of dynamic capabilities in this
 relationship. The empirical data were analysed using the structural
 equation modelling technique by examining 6 competing models that
 represent full, partial mediation and non-mediation relationships on a
 sample of 550 Spanish industrial companies. The findings indicate that the
 implementation level of QMP is not directly related to process innovation
 performance, but learning and technological capabilities fully mediate
 this relationship. Therefore, QMP needs to enhance and develop dynamic
 capabilities to effectively achieve the improvement and transformation of
 a firm&#x2019;s processes.
Journal: International Journal of Production Research 
Pages: 2875-2894 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1113326 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1113326 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jitender Madaan 
Author-X-Name-First: Jitender 
Author-X-Name-Last: Madaan 
Author-Name: Felix T.S. Chan 
Author-X-Name-First: Felix T.S. 
Author-X-Name-Last: Chan 
Author-Name: Ben Niu 
Author-X-Name-First: Ben 
Author-X-Name-Last: Niu 
Title: Strategies for evaluating performance of flexibility in product recovery system 
Abstract:
 In view of the increasing business opportunities with changing customer
 attitudes and stricter legislations, the handling of returns has become a
 daunting challenge. The need for decision models for evaluating return
 performance has been observed in the academia and the corporate world. To
 improve return system performance, integrated flexible reverse enterprise
 systems have attracted attention from researchers as well as
 practitioners. This paper addresses these critical issues and proposes a
 novel integrated and Flexible recovery system decision model. The proposed
 model aims to facilitate enterprises in assessing their product recovery
 system capability, and in improving overall performance. The proposed
 model is a natural extension of several well-grounded policies for
 conventional reverse supply chains and can be verified on a simulation
 platform.
Journal: International Journal of Production Research 
Pages: 2895-2906 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1120899 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1120899 
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Template-Type: ReDIF-Article 1.0
Author-Name: Koichi Murata 
Author-X-Name-First: Koichi 
Author-X-Name-Last: Murata 
Author-Name: Hiroshi Katayama 
Author-X-Name-First: Hiroshi 
Author-X-Name-Last: Katayama 
Title: Performance evaluation of a visual management system for effective case transfer 
Abstract:
 Visual management (VM) has become an important management tool for the
 smooth management of global supply chains. The target of VM systems is to
 harmonise communication. For example, in the production sector, VM
 provides solutions for various issues such as the quick detection of an
 abnormal situation, continuous maintenance of a safe environment,
 prevention of an operation miss and knowledge sharing. However, the
 development of VM cases has been uncontrolled, which is considered
 problematic. A system for the strategic enhancement of VM is necessary.
 Recognising this need, this study presents a model for the performance
 evaluation of relevant cases and validates the utility of the model, which
 is the initial step in developing a strategic enhancement system for VM.
Journal: International Journal of Production Research 
Pages: 2907-2921 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1125542 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1125542 
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuri Yatsenko 
Author-X-Name-First: Yuri 
Author-X-Name-Last: Yatsenko 
Author-Name: Natali Hritonenko 
Author-X-Name-First: Natali 
Author-X-Name-Last: Hritonenko 
Title: Asset replacement under improving operating and capital costs: a practical approach 
Abstract:
 We analyse the serial asset replacement problem under incomplete data
 about technological change that that affects the capital cost, operating
 cost and salvage value of newer assets. We construct an efficient
 discrete-time algorithm for this problem in the case where only partial
 information is available about future costs of new assets. The algorithm
 is based on introducing a corrected annual capital recovery factor into
 the classic Economic Life method. It produces the same lifetime of the
 first asset as the benchmark infinite-horizon cost minimisation when the
 operating cost, capital cost and salvage value of new assets decrease
 proportionally. The algorithm has the same complexity as the Economic Life
 method but performs much better under improving technology. Numeric
 simulation demonstrates a superior efficiency of the suggested algorithm
 vs. existing methods in practical situations when only few discrete
 measurements of technological change are available.
Journal: International Journal of Production Research 
Pages: 2922-2933 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1135259 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1135259 
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Template-Type: ReDIF-Article 1.0
Author-Name: Thomas Czumanski 
Author-X-Name-First: Thomas 
Author-X-Name-Last: Czumanski 
Author-Name: Hermann L&#xf6;dding 
Author-X-Name-First: Hermann 
Author-X-Name-Last: L&#xf6;dding 
Title: State-based analysis of labour productivity 
Abstract:
 Establishing efficient continuous improvement processes requires
 industrial companies to analyse their productivity quickly on different
 work system levels and to link productivity losses with suitable
 improvement measures in the course of productivity management. Common
 productivity analyses are either narrowed to certain functions of a
 production process or they do not possess a sufficient level of detail to
 derive goal-oriented improvement measures. The challenge is to gain
 production data with a relatively low effort and to gain broad
 transparency over productivity losses from the work place to the company
 level at the same time. This paper presents a new methodology for the
 comprehensive analysis of the various impacts on labour productivity,
 relying on state-based modelling of worker activities in serial
 production. Typical application areas include the automotive industry or
 the production of home appliances. The approach combines straightforward
 data acquisition methods with a structured evaluation process as
 foundation for the productivity management on different work system
 levels, including work stations, production lines, production segments and
 the plant. An integrated matching procedure processes the analysis results
 and yields a set of applicable improvement methods from a definable
 toolset. Compared with existing methodologies, the underlying model
 promises a reduced data acquisition effort and high usability. Its
 potential for practical application is shown with two industrial case
 studies.
Journal: International Journal of Production Research 
Pages: 2934-2950 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1137372 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1137372 
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Template-Type: ReDIF-Article 1.0
Author-Name: Sanket Bhat 
Author-X-Name-First: Sanket 
Author-X-Name-Last: Bhat 
Author-Name: Ananth Krishnamurthy 
Author-X-Name-First: Ananth 
Author-X-Name-Last: Krishnamurthy 
Title: Interactive effects of seasonal-demand characteristics on manufacturing systems 
Abstract:
 In this paper, we identify different characteristics of seasonal demands
 and analyse their impact on manufacturing systems. In particular, we
 consider a single-stage production facility that has flexibility to adjust
 its production rates or inventory target levels. Using Markov decision
 process formulation, we analyse a model that minimises the total cost
 under infinite horizon discounted and average cost criteria. Through
 extensive numerical studies, we reveal several insights related to the
 individual and joint impact of seasonal demand characteristics that are of
 practical interests to manufacturers.
Journal: International Journal of Production Research 
Pages: 2951-2964 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1138150 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1138150 
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Template-Type: ReDIF-Article 1.0
Author-Name: Nuno O. Fernandes 
Author-X-Name-First: Nuno O. 
Author-X-Name-Last: Fernandes 
Author-Name: Martin J. Land 
Author-X-Name-First: Martin J. 
Author-X-Name-Last: Land 
Author-Name: S. Carmo-Silva 
Author-X-Name-First: S. 
Author-X-Name-Last: Carmo-Silva 
Title: Aligning workload control theory and practice: lot splitting and operation overlapping issues 
Abstract:
 This paper addresses the problem of lot splitting in the context of
 workload control (WLC). Past studies on WLC assumed that jobs released to
 the shop floor proceed through the different stages of processing without
 being split. However, in practice, large jobs are often split into smaller
 transfer sublots so that they can move more quickly and independently
 through the production process and allow operations overlapping relating
 to the same job. This paper assesses the performance of different lot
 splitting policies for job release and dispatching strategies under lot
 splitting. A new dispatching rule was designed to specifically take
 advantage of lot splitting and operations overlapping in the context of
 WLC. Discrete-event simulation is used to assess system performance in
 relation to the ability to provide shorter delivery times and on time
 deliveries. Results highlight the importance of releasing the sublots of
 the same job together and demonstrate that combining an effective lot
 splitting policy with an appropriate dispatching rule can enhance the
 performance of production systems.
Journal: International Journal of Production Research 
Pages: 2965-2975 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1143134 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1143134 
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Template-Type: ReDIF-Article 1.0
Author-Name: Pardeep Gupta 
Author-X-Name-First: Pardeep 
Author-X-Name-Last: Gupta 
Author-Name: Sachit Vardhan 
Author-X-Name-First: Sachit 
Author-X-Name-Last: Vardhan 
Title: Optimizing OEE, productivity and production cost for improving sales volume in an automobile industry through TPM: a case study 
Abstract:
 The aim of this paper is to investigate how increase in sales volume has
 evolved by improving overall equipment effectiveness (OEE) of machines,
 plant productivity and production cost through total productive
 maintenance (TPM) initiatives in a reputed tractors manufacturing industry
 in India. In the present scenario of global competitive market, the
 manufacturing industry needs to improve their operational performance for
 surviving and prospering. TPM is practised by industry as a business tool
 for rapid and continuous improvement in its manufacturing capabilities.
 OEE offers a powerful control tool to overcome production deficiencies and
 operational performance constrains. Productivity and manufacturing cost
 are also crucial operational measures to analyse the manufacturing
 performance. In this study, evaluation and analysis of the methodology
 adopted for improving sales volume through TPM initiatives was carried out
 using an interactive research approach. The industrial example on the
 application of OEE tool demonstrates that it has a remarkable potential to
 enhance the equipment effectiveness. The empirical findings of the study
 reveal that augmented OEE and productivity, and reduced production cost
 resulted to double the sales revenue and triple the profit within a period
 of three years. The industry also achieved notably tangible and intangible
 benefits with the TPM implementation.
Journal: International Journal of Production Research 
Pages: 2976-2988 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1145817 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1145817 
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Template-Type: ReDIF-Article 1.0
Author-Name: Gendao Li 
Author-X-Name-First: Gendao 
Author-X-Name-Last: Li 
Author-Name: Yu Zhou 
Author-X-Name-First: Yu 
Author-X-Name-Last: Zhou 
Title: Strategically decentralise when encroaching on a dominant supplier 
Abstract:
 A manufacturer may encroach on his suppliers by developing substitutable
 components. In the presence of encroachment, the manufacturer could
 assemble products using (high-end) components purchased from the supplier,
 and assemble products using (low-end) components produced in-house. Thus,
 the manufacturer must deliberate on how to manage the expanded
 organisation consisting of competing product divisions. In this paper, we
 examine the quintessential organisational structure decision -- the
 centralisation versus decentralisation choice -- from the perspective of
 the manufacturer. Our model assumes that the supplier is a dominant
 player, moving first by pricing the high-end component, and consumers have
 a higher willingness-to-pay of the product containing the high-end
 component. In such a context, we find that the manufacturer may encroach
 on the supplier even if producing the low-end component costs more than
 producing the high-end one. The supplier should strategically price to
 deter or accommodate downstream encroachment contingent on the
 manufacturer&#x2019;s organisational structure decision. If the unit cost
 of low-end components is high enough, product-based decentralisation is
 preferred to centralisation due to the supplier&#x2019;s lower wholesale
 price. Furthermore, the manufacturer&#x2019;s strategic decentralisation
 always hurts the supplier, always benefits the customers and could benefit
 or hurt the entire supply chain under certain conditions.
Journal: International Journal of Production Research 
Pages: 2989-3005 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1150613 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1150613 
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Template-Type: ReDIF-Article 1.0
Author-Name: Christer W. Elverum 
Author-X-Name-First: Christer W. 
Author-X-Name-Last: Elverum 
Author-Name: Torgeir Welo 
Author-X-Name-First: Torgeir 
Author-X-Name-Last: Welo 
Title: Leveraging prototypes to generate value in the concept-to-production process: a qualitative study of the automotive industry 
Abstract:
 Prototypes are important tools in the development and production of new
 products. In the engineering design literature, prototypes are mainly
 perceived as tools for validating and verifying aspects of a design in the
 late stages of the design process. However, several studies have found
 that prototypes are important in the earlier design stages as well, and it
 is currently unknown how prototypes contribute to add value within the
 overall value chains of a business system. Using a case-study approach, we
 investigate this topic seeking to answer the question of how prototypes
 and rapid prototyping add value in the various stages of the new product
 development process in the automotive industry. Based on our findings, we
 propose that the value of prototypes can be divided into the following
 three categories: the artefact, i.e. the prototype; the process, i.e.
 prototyping; or the experiment, i.e. the data generated from experimenting
 with the artefact. Finally, we argue that prototypes add value to both the
 production and knowledge value stream.
Journal: International Journal of Production Research 
Pages: 3006-3018 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1152406 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1152406 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian Jin 
Author-X-Name-First: Jian 
Author-X-Name-Last: Jin 
Author-Name: Ying Liu 
Author-X-Name-First: Ying 
Author-X-Name-Last: Liu 
Author-Name: Ping Ji 
Author-X-Name-First: Ping 
Author-X-Name-Last: Ji 
Author-Name: Hongguang Liu 
Author-X-Name-First: Hongguang 
Author-X-Name-Last: Liu 
Title: Understanding big consumer opinion data for market-driven product design 
Abstract:
 Big consumer data provide new opportunities for business administrators to
 explore the value to fulfil customer requirements (CRs). Generally, they
 are presented as purchase records, online behaviour, etc. However,
 distinctive characteristics of big data, Volume, Variety, Velocity and
 Value or &#x2018;4Vs&#x2019;, lead to many conventional methods for
 customer understanding potentially fail to handle such data. A visible
 research gap with practical significance is to develop a framework to deal
 with big consumer data for CRs understanding. Accordingly, a research
 study is conducted to exploit the value of these data in the perspective
 of product designers. It starts with the identification of product
 features and sentiment polarities from big consumer opinion data. A Kalman
 filter method is then employed to forecast the trends of CRs and a
 Bayesian method is proposed to compare products. The objective is to help
 designers to understand the changes of CRs and their competitive
 advantages. Finally, using opinion data in Amazon.com, a case study is
 presented to illustrate how the proposed techniques are applied. This
 research is argued to incorporate an interdisciplinary collaboration
 between computer science and engineering design. It aims to facilitate
 designers by exploiting valuable information from big consumer data for
 market-driven product design.
Journal: International Journal of Production Research 
Pages: 3019-3041 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1154208 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154208 
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Template-Type: ReDIF-Article 1.0
Author-Name: Charbel Jos&#xe9; Chiappetta Jabbour 
Author-X-Name-First: Charbel Jos&#xe9; Chiappetta 
Author-X-Name-Last: Jabbour 
Author-Name: Ana Beatriz Lopes de Sousa Jabbour 
Author-X-Name-First: Ana Beatriz Lopes 
Author-X-Name-Last: de Sousa Jabbour 
Author-Name: Kannan Govindan 
Author-X-Name-First: Kannan 
Author-X-Name-Last: Govindan 
Author-Name: Thiago Pignatti de Freitas 
Author-X-Name-First: Thiago Pignatti 
Author-X-Name-Last: de Freitas 
Author-Name: Davi Fouad Soubihia 
Author-X-Name-First: Davi Fouad 
Author-X-Name-Last: Soubihia 
Author-Name: Devika Kannan 
Author-X-Name-First: Devika 
Author-X-Name-Last: Kannan 
Author-Name: Hengky Latan 
Author-X-Name-First: Hengky 
Author-X-Name-Last: Latan 
Title: Barriers to the adoption of green operational practices at Brazilian companies: effects on green and operational performance 
Abstract:
 The objective of this paper is to verify to what degree the internal and
 external barriers (I/EBs) to environmental management affect the adoption
 of green operational practices (GOPs) and to determine whether they
 influence the firms&#x2019; operational and green performance in a sample
 of Brazilian companies. A conceptual framework with 8 hypotheses is
 proposed and tested at 75 companies using Partial Least Squares-Structural
 Equation Modeling (PLS-SEM) with WarpPLS 4.0. The main results show that
 (a) the proposed framework obtained an adequate statistical adjustment,
 (b) the internal barriers (IBs) are more significant than the EBs when
 adopting GOPs, (c) GOPs relate directly to the firms&#x2019; green and
 operational performance (OP), (d) the IBs also indirectly influence the
 firms&#x2019; green and OP and (e) the firm size does not significantly
 influence its green and OP. This work contributes to the literature by
 showing that companies which are looking for green competitive advantages
 should try to reduce their IBs. Also, policy-makers should pay attention
 not only to legislation that promotes ecological modernisation, but also
 to create a strong set of initiatives to overcome IBs, regardless of the
 size of the firms.
Journal: International Journal of Production Research 
Pages: 3042-3058 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1154997 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154997 
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Template-Type: ReDIF-Article 1.0
Author-Name: Choon Khai Tay 
Author-X-Name-First: Choon Khai 
Author-X-Name-Last: Tay 
Author-Name: Song Lin Chen 
Author-X-Name-First: Song Lin 
Author-X-Name-Last: Chen 
Title: Cost estimation of a service family based on modularity 
Abstract:
 Companies are competing to offer high varieties of customised services on
 top of customised products to increase revenues and customer satisfaction.
 By adopting product family design methodologies, new concepts such as
 service families and service platforms are adopted in the service sectors.
 Despite that, increasing diversity in service offerings induces complexity
 and difficulty in service cost estimation. This research presents a
 service family cost estimation methodology that is based on service
 modularity and activity based costing (ABC). A service family is
 identified by selecting a set of similar services. Subsequently,
 activities of each service are identified with an activity diagram. The
 service family is then decomposed into functional and physical elements,
 where service modules are identified. Service activities are then mapped
 into relevant service modules using <italic>k</italic>-mean clustering
 algorithms, and activities of each service module are segregated into
 common and specific services using un-weighted pair group method with
 arithmetic mean. Finally, modified two-stage ABC methodology is applied to
 estimate the costs for a service family. To demonstrate the applicability
 of the proposed methodology, a case study is carried out to estimate the
 cost for a family of aircraft engines.
Journal: International Journal of Production Research 
Pages: 3059-3079 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1156781 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1156781 
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Template-Type: ReDIF-Article 1.0
Author-Name: Shuyu Zhou 
Author-X-Name-First: Shuyu 
Author-X-Name-Last: Zhou 
Author-Name: Yeming (Yale) Gong 
Author-X-Name-First: Yeming (Yale) 
Author-X-Name-Last: Gong 
Author-Name: Ren&#xe9; de Koster 
Author-X-Name-First: Ren&#xe9; 
Author-X-Name-Last: de Koster 
Title: Designing self-storage warehouses with customer choice 
Abstract:
 Self-storage warehousing is a rapidly growing industry where consumers or
 companies can rent storage space for personal or company use, over a
 certain horizon. This paper addresses the question of how to design the
 facilities so that revenue can be maximised over a finite horizon,
 considering multiple demand requirements with respect to size, pricing,
 location within the facility, climate control, security or outside access,
 among others. Using a customer choice model to specify the probability of
 purchase for each fare product as a function of the set of fare products
 offered, we propose methods to design self-storage warehouses while
 allowing different customer choice behaviours. We model the problem as a
 mixed-integer program and solve it using column generation and
 branch-and-price algorithms. In addition, we study the impact of re-layout
 and methods to modify facility layout, since self-storage facilities are
 relatively flexible in layout and individual storage compartments can be
 adapted to changes in demand. We validate our model using the data of four
 self-storage warehouses, and show our method can improve the expected
 revenue by nearly 11% on average for these cases.
Journal: International Journal of Production Research 
Pages: 3080-3104 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1158880 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1158880 
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Template-Type: ReDIF-Article 1.0
Author-Name: Petrit (Pete) Dode 
Author-X-Name-First: Petrit (Pete) 
Author-X-Name-Last: Dode 
Author-Name: Michael Greig 
Author-X-Name-First: Michael 
Author-X-Name-Last: Greig 
Author-Name: Saeed Zolfaghari 
Author-X-Name-First: Saeed 
Author-X-Name-Last: Zolfaghari 
Author-Name: W. Patrick Neumann 
Author-X-Name-First: W. Patrick 
Author-X-Name-Last: Neumann 
Title: Integrating human factors into discrete event simulation: a proactive approach to simultaneously design for system performance and employees&#x2019; well being 
Abstract:
 The aim of this research is to: (1) Develop an approach to integrating
 both human fatigue-recovery patterns and human learning into Discrete
 Event Simulation models of a production system to predict productivity and
 quality; (2) Validate the predicted fatigue against operators&#x2019;
 perceived fatigue; and (3) Demonstrate how this Human Factors-enabled
 simulation approach can be applied in a case study comparing two
 manufacturing line designs in the context of electronics assembly. The new
 approach can predict the accumulation of operator fatigue, fatigue-related
 quality effects and productivity changes based on system design
 configurations. In the demonstration comparison, fatigue dosage was 7--33%
 lower in the proposed system where HF was taken into consideration at the
 engineering design (ED) stage. In the existing system, the fatigue dose
 measure correlated with quality deficits with 26% of the variance
 accounted for -- a large portion given the multi-causal nature of
 production deficits. ED models that do not include human aspects may
 provide unreliable results in terms of productivity and quality estimates.
 This research shows that it is possible to design production systems that
 are more productive while being less hazardous for the system operator.
Journal: International Journal of Production Research 
Pages: 3105-3117 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1166287 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1166287 
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Template-Type: ReDIF-Article 1.0
Author-Name: Julien Gardan 
Author-X-Name-First: Julien 
Author-X-Name-Last: Gardan 
Title: Additive manufacturing technologies: state of the art and trends 
Abstract:
 The rapid prototyping has been developed from the 1980s to produce models
 and prototypes until the technologies evolution today. Nowadays, these
 technologies have other names such as 3D printing or additive
 manufacturing, and so forth, but they all have the same origins from rapid
 prototyping. The design and manufacturing process stood the same until new
 requirements such as a better integration on production line, a largest
 series of manufacturing or the reduce weight of products due to heavy
 costs of machines and materials. The ability to produce complex geometries
 allows proposing of design and manufacturing solutions in the industrial
 field in order to be ever more effective. The additive manufacturing (AM)
 technology develops rapidly with news solutions and markets which
 sometimes need to demonstrate their reliability. The community needs to
 survey some evolutions such as the new exchange format, the faster 3D
 printing systems, the advanced numerical simulation or the emergence of
 new use. This review is addressed to persons who wish have a global view
 on the AM and improve their understanding. We propose to review the
 different AM technologies and the new trends to get a global overview
 through the engineering and manufacturing process. This article describes
 the engineering and manufacturing cycle with the 3D model management and
 the most recent technologies from the evolution of additive manufacturing.
 Finally, the use of AM resulted in new trends that are exposed below with
 the description of some new economic activities.
Journal: International Journal of Production Research 
Pages: 3118-3132 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2015.1115909 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1115909 
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Template-Type: ReDIF-Article 1.0
Author-Name: Marta P&#xe9;rez P&#xe9;rez 
Author-X-Name-First: Marta 
Author-X-Name-Last: P&#xe9;rez P&#xe9;rez 
Author-Name: Ana Mar&#xed;a Serrano Bedia 
Author-X-Name-First: Ana Mar&#xed;a 
Author-X-Name-Last: Serrano Bedia 
Author-Name: Mar&#xed;a Concepci&#xf3;n L&#xf3;pez Fern&#xe1;ndez 
Author-X-Name-First: Mar&#xed;a Concepci&#xf3;n 
Author-X-Name-Last: L&#xf3;pez Fern&#xe1;ndez 
Title: A review of manufacturing flexibility: systematising the concept 
Abstract:
 The present work is an attempt to contribute to the conceptual
 systematisation of the manufacturing flexibility types by synthesising the
 vast literature available after a systematic review. We classified the
 papers in two perspectives (hierarchical and strategic), and engaged in a
 systematic process of standardisation of the definitions and names of
 various flexibility types leading to a better understanding of them. This
 process allowed us to clearly show: (a) the existence of a broader
 consensus in the field than expected; (b) that problems are limited to
 concrete aspects related to the level of analysis or the scope of certain
 flexibility types; (c) the possibility of a theoretical integration
 between the two perspectives which would permit a standardisation of the
 names and definitions for the flexibility types which make up the
 manufacturing flexibility construct.
Journal: International Journal of Production Research 
Pages: 3133-3148 
Issue: 10 
Volume: 54 
Year: 2016 
Month: 5 
X-DOI: 10.1080/00207543.2016.1138151 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1138151 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jbid Arsenyan 
Author-X-Name-First: Jbid 
Author-X-Name-Last: Arsenyan 
Author-Name: G&#xfc;l&#xe7;in B&#xfc;y&#xfc;k&#xf6;zkan 
Author-X-Name-First: G&#xfc;l&#xe7;in 
Author-X-Name-Last: B&#xfc;y&#xfc;k&#xf6;zkan 
Title: An integrated fuzzy approach for information technology planning in collaborative product development 
Abstract:
 Collaborative product development (CPD) processes are generally based on
 technological infrastructures. Various information technologies (IT) are
 proposed every day to facilitate collaboration, integration, co-design and
 co-development processes. In this highly uncertain environment, a
 systematic methodology is essential to plan the IT infrastructure needed
 to start and maintain a collaborative process. This study offers an
 integrated IT planning methodology combining fuzzy quality function
 deployment, fuzzy axiomatic design and fuzzy rule-based systems. The
 methodology is tested in a CPD case and the outcome presents an
 improvement path for IT for each of the collaborative parties.
Journal: International Journal of Production Research 
Pages: 3149-3169 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1043032 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1043032 
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Template-Type: ReDIF-Article 1.0
Author-Name: J. P&#xe9;rez 
Author-X-Name-First: J. 
Author-X-Name-Last: P&#xe9;rez 
Author-Name: S. Maldonado 
Author-X-Name-First: S. 
Author-X-Name-Last: Maldonado 
Author-Name: V. Marianov 
Author-X-Name-First: V. 
Author-X-Name-Last: Marianov 
Title: A reconfiguration of fire station and fleet locations for the Santiago Fire Department 
Abstract:
 The geographical distribution of the population of the city of Santiago,
 Chile, has changed significantly in recent years. In spite of this fact,
 the location of the fire stations has remained unchanged. We propose a
 model for the optimal location of the fire stations and a fleet assignment
 for the Santiago Fire Department (SFD), aimed at maximising the number of
 events attended to with a predefined standard response. The results of the
 model are compared with respect to the current location of fire stations
 and fleet assignment in the SFD. There are different types of resources
 (stations and vehicles), and different types of events in which the same
 types of vehicles are used. We analyse various possible current and future
 scenarios, using a forecast based on historical data. Our results show
 that by optimally reallocating the resources a 10--30% increase can be
 achieved in the number of emergency calls that are attended to with an
 adequate response in time and number of vehicles, without the need for
 additional fire stations or vehicles. Thus our contribution is empirical
 and relies on the real world application which is being considered by
 Chilean government.
Journal: International Journal of Production Research 
Pages: 3170-3186 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1071894 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1071894 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jinho Kim 
Author-X-Name-First: Jinho 
Author-X-Name-Last: Kim 
Author-Name: Myong K. Jeong 
Author-X-Name-First: Myong K. 
Author-X-Name-Last: Jeong 
Author-Name: Elsayed A. Elsayed 
Author-X-Name-First: Elsayed A. 
Author-X-Name-Last: Elsayed 
Author-Name: K.N. Al-Khalifa 
Author-X-Name-First: K.N. 
Author-X-Name-Last: Al-Khalifa 
Author-Name: A.M.S. Hamouda 
Author-X-Name-First: A.M.S. 
Author-X-Name-Last: Hamouda 
Title: An adaptive step-down procedure for fault variable identification 
Abstract:
 In a process with a large number of process variables (high-dimensional
 process), identifying which variables cause an out-of-control signal is a
 challenging issue for quality engineers. In this paper, we propose an
 adaptive step-down procedure using conditional <italic>T</italic>-super-2
 statistic for fault variable identification. While existing procedures
 focus on selecting variables that have strong evidence of a change, the
 proposed step-down procedure selects a variable having the weakest
 evidence of a change at each step based on the variables that are selected
 in previous steps. The information of selected unchanged variables is
 effectively utilised in obtaining a powerful conditional
 <italic>T</italic>-super-2 test statistic for identifying the changed
 elements of the mean vector. The proposed procedure is designed to utilise
 the correlation information between fault and non-fault variables for the
 efficient fault variables identification. Further, the simulation results
 show that the proposed procedure has the better diagnostic performance
 compared with existing methods in terms of fault variable identification
 and computational complexity, especially when the number of the variables
 is high and the number of fault variables is small.
Journal: International Journal of Production Research 
Pages: 3187-3200 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1076948 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076948 
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Template-Type: ReDIF-Article 1.0
Author-Name: Linhan Ouyang 
Author-X-Name-First: Linhan 
Author-X-Name-Last: Ouyang 
Author-Name: Yizhong Ma 
Author-X-Name-First: Yizhong 
Author-X-Name-Last: Ma 
Author-Name: Jai-Hyun Byun 
Author-X-Name-First: Jai-Hyun 
Author-X-Name-Last: Byun 
Author-Name: Jianjun Wang 
Author-X-Name-First: Jianjun 
Author-X-Name-Last: Wang 
Author-Name: Yiliu Tu 
Author-X-Name-First: Yiliu 
Author-X-Name-Last: Tu 
Title: An interval approach to robust design with parameter uncertainty 
Abstract:
 In robust design, it is common to estimate empirical models that relate an
 output response variable to controllable input variables and
 uncontrollable noise variables from experimental data. However, when
 determining the optimal input settings that minimise output variability,
 parameter uncertainties in noise factors and response models are typically
 neglected. This article presents an interval robust design approach that
 takes parameter uncertainties into account through the confidence regions
 for these unknown parameters. To avoid obtaining an overly conservative
 design, the worst and best cases of mean squared error are both adopted to
 build an optimisation approach. The midpoint and radius of the interval
 are used to measure the location and dispersion performances,
 respectively. Meanwhile, a data-driven method is applied to obtain the
 relative weights of the location and dispersion performances in the
 optimisation approach. A simulation example and a case study using
 automobile manufacturing data from the dimensional tolerance design
 process are used to demonstrate the effectiveness of the proposed
 approach. The proposed approach of considering both uncertainties is shown
 to perform better than other approaches.
Journal: International Journal of Production Research 
Pages: 3201-3215 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1078920 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1078920 
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Template-Type: ReDIF-Article 1.0
Author-Name: Moshe Mann 
Author-X-Name-First: Moshe 
Author-X-Name-Last: Mann 
Author-Name: Boaz Zion 
Author-X-Name-First: Boaz 
Author-X-Name-Last: Zion 
Author-Name: Itzhak Shmulevich 
Author-X-Name-First: Itzhak 
Author-X-Name-Last: Shmulevich 
Author-Name: Dror Rubinstein 
Author-X-Name-First: Dror 
Author-X-Name-Last: Rubinstein 
Title: Determination of robotic melon harvesting efficiency: a probabilistic approach 
Abstract:
 To automate the harvesting of melons, a mobile Cartesian robot is
 developed that traverses at a constant velocity over a row of precut
 melons whose global coordinates are known. The motion planner is
 programmed to have the robot harvest as many melons as possible. Numerous
 simulations of the robot over a field with different sets of randomly
 distributed melons resulted in nearly identical percentages of melons
 harvested. This result holds true over a wide range of robot dimensions,
 motor capabilities, velocities and melon distributions. Using
 probabilistic methods, we derive these results by modelling the robotic
 harvesting procedure as a stochastic process. In this simplified model, a
 harvest ratio is predicted analytically using Poisson and geometric
 distributions. Further analysis demonstrates that this model of robotic
 harvesting is an example of an infinite length Markov chain. Applying the
 mathematical tools of Markov processes to our model yields a formula for
 the harvest percentage that is in strong agreement with the results of the
 simulation. The significance of the approach is demonstrated in two of its
 applications: to select the most efficient actuators for maximal melon
 harvesting and determine the set of optimal velocities along a row of
 melons of varying densities.
Journal: International Journal of Production Research 
Pages: 3216-3228 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1081428 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1081428 
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Template-Type: ReDIF-Article 1.0
Author-Name: Michael Leyer 
Author-X-Name-First: Michael 
Author-X-Name-Last: Leyer 
Author-Name: Daniel Kronsbein 
Author-X-Name-First: Daniel 
Author-X-Name-Last: Kronsbein 
Author-Name: Richard Willis 
Author-X-Name-First: Richard 
Author-X-Name-Last: Willis 
Author-Name: Ayon Chakraborty 
Author-X-Name-First: Ayon 
Author-X-Name-Last: Chakraborty 
Author-Name: J&#xfc;rgen Moormann 
Author-X-Name-First: J&#xfc;rgen 
Author-X-Name-Last: Moormann 
Title: Implementation of service systems on the shop-floor level in financial service companies. Empirical evidence from Australia and Germany 
Abstract:
 This article presents the practices of Australian and German financial
 service providers regarding the implementation of shop-floor control
 within different types of service systems. The results delivered in this
 article should serve as a guideline for future research to develop and
 adapt methods for shop-floor control in financial service systems.
 Interviews with 25 experts from the Australian and German financial
 services industry reveal novel insights into the practice of shop-floor
 control, suggesting that methods and concepts from manufacturing are only
 used to a limited extent for shop-floor control. Shop-floor control is
 mostly used to react quickly to unexpected deviations due to a low usage
 of forecasts and information systems. Thus, there seems to be improvement
 potential in the financial services industry in comparison with in the
 manufacturing industry in terms of shop-floor control. Further research
 within the production research area should use the empirical insights to
 test and adapt existing methods and to develop new ones, taking cultural
 differences into account.
Journal: International Journal of Production Research 
Pages: 3229-3242 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1085656 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1085656 
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Template-Type: ReDIF-Article 1.0
Author-Name: Lei Li 
Author-X-Name-First: Lei 
Author-X-Name-Last: Li 
Author-Name: YanLing Qian 
Author-X-Name-First: YanLing 
Author-X-Name-Last: Qian 
Author-Name: Yong Min Yang 
Author-X-Name-First: Yong Min 
Author-X-Name-Last: Yang 
Author-Name: Kai Du 
Author-X-Name-First: Kai 
Author-X-Name-Last: Du 
Title: A fast algorithm for buffer allocation problem 
Abstract:
 In this paper, we address the problem of seeking optimal buffer
 configurations in unreliable production lines with the objective of
 maximising their production rates. A fast algorithm is proposed for
 solving the problem. The key idea is to decompose a long production line
 into a set of overlapping three-machine two-buffer systems. The
 performance of the algorithm is demonstrated by a comparison with the
 degraded ceiling (DC) algorithm. Numerical results show that the proposed
 algorithm is almost as accurate as the DC algorithm, but it is much
 faster, especially for long production lines.
Journal: International Journal of Production Research 
Pages: 3243-3255 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1092612 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1092612 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoming Yan 
Author-X-Name-First: Xiaoming 
Author-X-Name-Last: Yan 
Author-Name: Yong Wang 
Author-X-Name-First: Yong 
Author-X-Name-Last: Wang 
Author-Name: Zhaofu Hong 
Author-X-Name-First: Zhaofu 
Author-X-Name-Last: Hong 
Title: Comparison of Bertrand and Cournot competitions under random yield 
Abstract:
 We look at a Bertrand model in which each firm may be unreliable with
 random yield, so the total quantity brought into market is uncertain.
 Under mild conditions, the Bertrand model with random yield has a unique
 Nash equilibrium, in which the prices and production quantities are
 determined by each firm&#x2019;s production cost and reliability. In the
 case of symmetric firms, we compare Bertrand competition with Cournot
 competition by numerical examples, and find that Bertrand competition
 yields lower prices and less profits than Cournot competition.
 Furthermore, in the case of symmetric firms with 0--1 yields, we
 explicitly show that Bertrand competition yields lower prices and less
 profits than Cournot competition, and the comparison between the
 quantities of Bertrand and Cournot competition is dependent on the value
 of reliability. When the reliability is high, Cournot competition yields
 less quantities than Bertrand competition. Otherwise, the other hand
 holds.
Journal: International Journal of Production Research 
Pages: 3256-3276 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1092614 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1092614 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Zafar Iqbal 
Author-X-Name-First: Zafar 
Author-X-Name-Last: Iqbal 
Author-Name: Nigel P. Grigg 
Author-X-Name-First: Nigel P. 
Author-X-Name-Last: Grigg 
Author-Name: K. Govindaraju 
Author-X-Name-First: K. 
Author-X-Name-Last: Govindaraju 
Author-Name: Nicola M. Campbell-Allen 
Author-X-Name-First: Nicola M. 
Author-X-Name-Last: Campbell-Allen 
Title: A distance-based methodology for increased extraction of information from the roof matrices in QFD studies 
Abstract:
 Quality Function Deployment (QFD) is a process in which customer needs are
 operationalised into deliverable Technical Characteristics (TCs) at the
 design stage. A system of matrices known as the House of Quality (HOQ)
 works collectively to produce Final Weightings (FWs) for TCs, enabling
 prioritisation and focusing design activity. In prioritising TCs, QFD
 practitioners often fail to fully integrate the diverse information within
 the HOQ. In this article, we address the inclusion of &#x2018;Roof Matrix
 Correlations&#x2019; (RMCs). We show that, while other heuristics have
 been developed to integrate RMCs, they each have limitations and only
 result in changes to the FW values. We present a methodology based on the
 Manhattan Distance Measure (MDM) that integrates RMC data into the FWs,
 but also measures the overall nature and level of intercorrelation within
 the matrix. This facilitates a more efficient selection of TCs because the
 MDM provides a consistent informational basis for substituting negatively
 correlated TCs with better alternatives, and reducing duplication of
 effort in cases of highly positively correlated TCs. Application of the
 method is illustrated through re-analysis of a well-known, published QFD
 example. Our approach can help practitioners to avoiding duplicating
 effort or to address contradictions between TCs in a timely fashion.
Journal: International Journal of Production Research 
Pages: 3277-3293 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1094585 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1094585 
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Template-Type: ReDIF-Article 1.0
Author-Name: Roberto Campos Leoni 
Author-X-Name-First: Roberto Campos 
Author-X-Name-Last: Leoni 
Author-Name: Marcela Aparecida Guerreiro Machado 
Author-X-Name-First: Marcela Aparecida Guerreiro 
Author-X-Name-Last: Machado 
Author-Name: Antonio Fernando Branco Costa 
Author-X-Name-First: Antonio Fernando Branco 
Author-X-Name-Last: Costa 
Title: The <italic>T</italic>-super-2 chart with mixed samples to control bivariate autocorrelated processes 
Abstract:
 In this paper, we propose the use of the <italic>T</italic>-super-2 chart
 with the mixed sampling strategy (MS) to monitor the mean vector of
 bivariate processes with observations that fit to a first-order vector
 autoregressive model. With the MS, rational subgroups of size n are taken
 from the process and the selected units are regrouped to form the mixed
 samples. The units of the mixed samples are units selected from the last
 two rational subgroups. The aim of the proposed sampling strategy is to
 reduce the negative effect of the autocorrelation on the performance of
 the <italic>T</italic>-super-2 chart. When the two variables are
 autocorrelated, the MS always enhances the <italic>T</italic>-super-2
 chart performance, however, the mixed samples are not recommended for
 bivariate processes with only one autocorrelated variable which is rarely
 affected by the assignable cause.
Journal: International Journal of Production Research 
Pages: 3294-3310 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1102983 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1102983 
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Template-Type: ReDIF-Article 1.0
Author-Name: X.J. Wang 
Author-X-Name-First: X.J. 
Author-X-Name-Last: Wang 
Author-Name: S.H. Choi 
Author-X-Name-First: S.H. 
Author-X-Name-Last: Choi 
Title: Impacts of carbon emission reduction mechanisms on uncertain make-to-order manufacturing 
Abstract:
 Lot sizing in queuing networks is pivotal to batch manufacturing,
 especially in stochastic environments. Despite development in lot sizing
 optimisation, the results are often rendered unrealistic because few
 studies have considered the impacts of relevant environmental regulation
 policies on production planning. This paper incorporates stochastic lot
 sizing optimisation with two dominant carbon emission reduction mechanisms
 -- the carbon emission constraint and the cap-and-trade system -- to
 examine their operational and environmental impacts on make-to-order
 manufacturing. It also compares these two mechanisms in environmental
 conservation. Numerical experiments validate the importance of considering
 the carbon emission regulations to traditional production planning
 problems. The results highlight that the market-based characteristics of
 the cap-and-trade mechanism motivate firms with economic benefits to adopt
 low-carbon technologies and environmental-friendly facilities to curb
 greenhouse gases emission. In contrast, the carbon emission constraint
 mechanism is like administrative orders to force out outmoded industries
 and outdated technologies.
Journal: International Journal of Production Research 
Pages: 3311-3328 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1106606 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106606 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jorge M. Sim&#xf5;es 
Author-X-Name-First: Jorge M. 
Author-X-Name-Last: Sim&#xf5;es 
Author-Name: Carlos F. Gomes 
Author-X-Name-First: Carlos F. 
Author-X-Name-Last: Gomes 
Author-Name: Mahmoud M. Yasin 
Author-X-Name-First: Mahmoud M. 
Author-X-Name-Last: Yasin 
Title: Changing role of maintenance in business organisations: measurement versus strategic orientation 
Abstract:
 The purpose of this study is to examine the nature of performance measures
 utilised by the maintenance function in today&#x2019;s business
 organisations. In the process, the increasing variety and significance of
 these measures are addressed from operational and strategic perspectives.
 A survey-based research method was utilised to gather the research data.
 Several statistical procedures were utilised to analyse the data. The
 findings of this study point to the multifaceted nature of the maintenance
 measures and measurement. Multiple categories of maintenance measures were
 identified. These categories varied from the machine-specific, to measures
 impacting organisational performance. The relative lack of emphasis placed
 on the environment and strategic facets of maintenance is noted. The
 findings of this study have direct implications to organisations, which
 are attempting to measure the effectiveness of their maintenance efforts.
 The need to align the maintenance performance efforts with the
 organisational strategic direction is emphasised. In this context, the
 integration of the maintenance performance information systems with the
 overall organisational performance management information system might
 facilitate the needed alignment. This study utilises 120 maintenance
 measures. As such, it represents a comprehensive view of the maintenance
 effort.
Journal: International Journal of Production Research 
Pages: 3329-3346 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1106611 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106611 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingui Xie 
Author-X-Name-First: Jingui 
Author-X-Name-Last: Xie 
Author-Name: Ping Cao 
Author-X-Name-First: Ping 
Author-X-Name-Last: Cao 
Author-Name: Boray Huang 
Author-X-Name-First: Boray 
Author-X-Name-Last: Huang 
Author-Name: Marcus Eng Hock Ong 
Author-X-Name-First: Marcus Eng Hock 
Author-X-Name-Last: Ong 
Title: Determining the conditions for reverse triage in emergency medical services using queuing theory 
Abstract:
 In emergency health care, there are situations where the less wounded are
 treated in preference to the more severely wounded, so called
 <italic>reverse triage</italic>. This may arise in situations such as war
 where soldiers are required to return to the battlefield as quickly as
 possible, or disaster situations where medical resources are limited in
 order to conserve resources for those likely to survive without requiring
 advanced medical care. This article is to study the reverse triage in
 time-critical systems, where conditions of patients may deteriorate while
 waiting for treatment. A queueing model with transfers and abandonments is
 developed to study the health care system. Using smoothed rate truncation
 method, sufficient conditions of reverse triage are derived, under which
 non-critical patients are treated with priority. For other conditions, the
 optimal policy is very complicated. We suggest a dynamic control policy
 according to the system state rather than any static priority policies.
Journal: International Journal of Production Research 
Pages: 3347-3364 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1109718 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1109718 
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Template-Type: ReDIF-Article 1.0
Author-Name: Baocai Guo 
Author-X-Name-First: Baocai 
Author-X-Name-Last: Guo 
Author-Name: Bing Xing Wang 
Author-X-Name-First: Bing Xing 
Author-X-Name-Last: Wang 
Title: The variable sampling interval <italic>S</italic>-super-2 chart with known or unknown in-control variance 
Abstract:
 The <inline-formula id="ILM0004"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1109720_ilm0004.gif"/></inline-formula> chart has been
 known as a powerful tool to monitor the variability of the normal process.
 This paper considers the variable sampling interval (VSI) <inline-formula
 id="ILM0005"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1109720_ilm0005.gif"/></inline-formula> chart to
 improve the performance of the original <inline-formula
 id="ILM0006"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1109720_ilm0006.gif"/></inline-formula> chart. A VSI
 <inline-formula id="ILM0007"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1109720_ilm0007.gif"/></inline-formula> chart based on
 the average run length (ARL) unbiased and average time to signal (ATS)
 unbiased criteria is developed when the in-control variance is known. The
 performance of the proposed chart is investigated in terms of the mean and
 standard deviation of the RL and total time to signal. The impact of
 parameter estimation on the proposed VSI <inline-formula
 id="ILM0008"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1109720_ilm0008.gif"/></inline-formula> chart is also
 evaluated. The results show that the performance of the control chart is
 seriously different from the known parameter case when the parameter is
 estimated. Then, a new VSI <inline-formula id="ILM0009"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1109720_ilm0009.gif"/></inline-formula> chart with the
 desired in-control ARL and ATS is considered when the in-control variance
 is estimated. In evaluating the usefulness of the VSI feature, the VSI
 <inline-formula id="ILM0010"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1109720_ilm0010.gif"/></inline-formula> charts are
 compared with the fixed sampling interval (FSI) versions in terms of their
 statistical properties. The comparison results show that the VSI
 <inline-formula id="ILM0011"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1109720_ilm0011.gif"/></inline-formula> chart can
 detect the shifts in the process variance quicker than the corresponding
 FSI chart, regardless of whether the in-control variance is known or
 unknown. Finally, two examples are used to illustrate the proposed control
 chart.
Journal: International Journal of Production Research 
Pages: 3365-3379 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1109720 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1109720 
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Template-Type: ReDIF-Article 1.0
Author-Name: Heechul Bae 
Author-X-Name-First: Heechul 
Author-X-Name-Last: Bae 
Author-Name: Ilkyeong Moon 
Author-X-Name-First: Ilkyeong 
Author-X-Name-Last: Moon 
Author-Name: Wonyoung Yun 
Author-X-Name-First: Wonyoung 
Author-X-Name-Last: Yun 
Title: A time-varying lot sizes approach for the economic lot scheduling problem with returns 
Abstract:
 We consider the economic lot scheduling problem with returns by assuming
 that each item is returned by a constant rate of demand. The goal is to
 find production frequencies, production sequences, production times, as
 well as idle times for several items subject to returns at a single
 facility. We propose a heu ristic algorithm based on a time-varying (TV)
 lot sizes approach. The problem is decomposed into two distinct portions:
 in the first, we find a combinatorial part (production frequencies and
 sequences) and in the second, we determine a continuous part (production
 and idle times) in a specific production sequence. We report computational
 results that show that, in many cases, the proposed TV lot sizes approach
 with consideration of returns yields a relatively minor error.
Journal: International Journal of Production Research 
Pages: 3380-3396 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1110633 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1110633 
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov 
Author-X-Name-First: Dmitry 
Author-X-Name-Last: Ivanov 
Author-Name: Alexandre Dolgui 
Author-X-Name-First: Alexandre 
Author-X-Name-Last: Dolgui 
Author-Name: Boris Sokolov 
Author-X-Name-First: Boris 
Author-X-Name-Last: Sokolov 
Author-Name: Frank Werner 
Author-X-Name-First: Frank 
Author-X-Name-Last: Werner 
Title: Schedule robustness analysis with the help of attainable sets in continuous flow problem under capacity disruptions 
Abstract:
 Continuous flow scheduling problems have their place in many industries
 such as gas, oil, chemicals, glass and fluids production as well as
 production of granular goods and steel details. The disruptions in
 processing capacities may result in schedule performance decrease. In this
 paper, we develop a new method for robustness analysis of those schedules
 that are formulated in continuous time in the state-space domain. The
 developed method is based on attainable sets (ASs) that allow computing a
 form to represent the states and performance of schedules in regard to
 different capacity degradation levels. Having such a form, it becomes
 possible to estimate the schedule robustness. The technical development
 and approximation of ASs are presented. A robustness index is developed on
 the basis of the minimax regret approach, and it can be used for
 decision-makers regarding the trade-off &#x2018;performance vs.
 robustness&#x2019;. As such, it becomes possible to compare maximal
 possible profits in situations without disruptions and realistic profits
 subject to some robustness investments and costs of protection against
 disruptions. With the presented results, it becomes possible to obtain ASs
 for interval data with no a priori information about perturbation impacts,
 i.e. for non-stationary perturbations. ASs permit to consider
 perturbations and schedule performances as <italic>time
 functions</italic>. Perturbation functions may be set up for different
 uncertainty scenarios, including interval perturbations.
Journal: International Journal of Production Research 
Pages: 3397-3413 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1129467 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1129467 
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Template-Type: ReDIF-Article 1.0
Author-Name: Wen Su 
Author-X-Name-First: Wen 
Author-X-Name-Last: Su 
Author-Name: Xiaolei Xie 
Author-X-Name-First: Xiaolei 
Author-X-Name-Last: Xie 
Author-Name: Jingshan Li 
Author-X-Name-First: Jingshan 
Author-X-Name-Last: Li 
Author-Name: Li Zheng 
Author-X-Name-First: Li 
Author-X-Name-Last: Zheng 
Title: Improving energy efficiency in Bernoulli serial lines: an integrated model 
Abstract:
 In this paper, we present an integrated model of both productivity and
 energy consumptions in serial production lines with two machines.
 Bernoulli reliability is assumed for both machines and the capacity of the
 buffer is finite. The energy consumption of each machine includes the
 energy required to set up the machine until it is ready for processing,
 and the additional energy needed to carry out the processing operation to
 make the product. The former is typically fixed for a specific
 manufacturing process, while the latter is proportional to the processing
 rate. The objective of the model is to minimise energy consumption, while
 maintaining the desired production rate. Specifically, analytical
 investigation has been carried out to discover the conditions that energy
 consumption can be minimised with and without the constraints of workforce
 or machine processing capability. Optimal allocations of them under
 different scenarios have been derived. Insights for reducing energy
 consumption while still ensuring desired productivity have been obtained.
Journal: International Journal of Production Research 
Pages: 3414-3428 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2016.1138152 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1138152 
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Template-Type: ReDIF-Article 1.0
Author-Name: Y&#x131;lmaz Delice 
Author-X-Name-First: Y&#x131;lmaz 
Author-X-Name-Last: Delice 
Author-Name: Emel K&#x131;z&#x131;lkaya Aydo&#x11f;an 
Author-X-Name-First: Emel 
Author-X-Name-Last: K&#x131;z&#x131;lkaya Aydo&#x11f;an 
Author-Name: U&#x11f;ur &#xd6;zcan 
Author-X-Name-First: U&#x11f;ur 
Author-X-Name-Last: &#xd6;zcan 
Title: Stochastic two-sided U-type assembly line balancing: a genetic algorithm approach 
Abstract:
 In this paper, a novel stochastic two-sided U-type assembly line balancing
 (STUALB) procedure, an algorithm based on the genetic algorithm and a
 heuristic priority rule-based procedure to solve STUALB problem are
 proposed. With this new proposed assembly line design, all advantages of
 both two-sided assembly lines and U-type assembly lines are combined. Due
 to the variability of the real-life conditions, stochastic task times are
 also considered in the study. The proposed approach aims to minimise the
 number of positions (i.e. the U-type assembly line length) as the primary
 objective and to minimise the number of stations (i.e. the number of
 operators) as a secondary objective for a given cycle time. An example
 problem is solved to illustrate the proposed approach. In order to
 evaluate the efficiency of the proposed algorithm, test problems taken
 from the literature are used. The experimental results show that the
 proposed approach performs well.
Journal: International Journal of Production Research 
Pages: 3429-3451 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2016.1140918 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1140918 
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Template-Type: ReDIF-Article 1.0
Author-Name: Thomas Boucher 
Author-X-Name-First: Thomas 
Author-X-Name-Last: Boucher 
Author-Name: Yuchen Li 
Author-X-Name-First: Yuchen 
Author-X-Name-Last: Li 
Title: Technical note: systematic bias in stochastic learning 
Abstract:
 The learning curve is a fundamental model used by engineers in cost
 estimating. In industry, it is typical to use the deterministic model for
 projecting cost, which is also suggested in standard textbooks. However,
 the parameters for the model are obtained from actual data, which usually
 come from a stochastic process. In this technical note, we investigate a
 particular phenomenon of the stochastic learning model that indicates that
 a bias may exist in the parameter estimates simply due to random behaviour
 in learning. The findings suggest that, on average, projections of cost
 from a model whose parameters are estimated from early data points are, on
 average, optimistic about the future cost reduction.
Journal: International Journal of Production Research 
Pages: 3452-3463 
Issue: 11 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1117674 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1117674 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xuesong Feng 
Author-X-Name-First: Xuesong 
Author-X-Name-Last: Feng 
Author-Name: Mitsuru Saito 
Author-X-Name-First: Mitsuru 
Author-X-Name-Last: Saito 
Author-Name: Yi Liu 
Author-X-Name-First: Yi 
Author-X-Name-Last: Liu 
Title: Improve urban passenger transport management by rationally forecasting traffic congestion probability 
Abstract:
 A Bayesian network (BN) approach is proposed in this study to analyse the
 overall traffic congestion probability of an urban road network in
 consideration of the influence of applying various transport policies. The
 continually expanding urbanised region of Beijing has been chosen as the
 study area because of its rapid expansion and motorisation, which lead to
 the severe traffic congestion occurring nearly every day. It is
 demonstrated that the proposed BN approach is able to rationally predict
 the probability of the overall traffic congestion that will take place
 given a certain transport policy. It is also proven that increasing the
 number of buses providing convenient passenger transport service in the
 urbanised region of Beijing will most effectively reduce the probability
 of the traffic congestion in this area, especially when the newly
 constructed roads in the same region are put into use.
Journal: International Journal of Production Research 
Pages: 3465-3474 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1062570 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1062570 
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Template-Type: ReDIF-Article 1.0
Author-Name: Hui Zhu 
Author-X-Name-First: Hui 
Author-X-Name-Last: Zhu 
Author-Name: Min Li 
Author-X-Name-First: Min 
Author-X-Name-Last: Li 
Author-Name: Zhangjin Zhou 
Author-X-Name-First: Zhangjin 
Author-X-Name-Last: Zhou 
Author-Name: Yun You 
Author-X-Name-First: Yun 
Author-X-Name-Last: You 
Title: Due-window assignment and scheduling with general position-dependent processing times involving a deteriorating and compressible maintenance activity 
Abstract:
 In this paper, we consider common due-window assignment and scheduling
 problems with general position-dependent processing times involving
 deteriorating and compressible maintenance activity on a single machine.
 Two models associated with maintenance activity are examined in this
 article, in which the maintenance length is assumed to be either
 time-dependent and compressible or position-dependent and compressible.
 The objective is to find jointly the location and size of due-window,
 position of maintenance as well as resource amount allocated to it, and
 job sequence to minimise a total cost function based on earliness,
 tardiness, window location, window size and resource cost. We show that
 the problem considered in each of the two models&#x2019; setting can be
 optimally solved with polynomial time algorithm by reducing to assignment
 problem. Finally, two examples are provided to illustrate the solution
 procedures.
Journal: International Journal of Production Research 
Pages: 3475-3490 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1067379 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1067379 
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei Li 
Author-X-Name-First: Wei 
Author-X-Name-Last: Li 
Author-Name: Theodor I. Freiheit 
Author-X-Name-First: Theodor I. 
Author-X-Name-Last: Freiheit 
Title: An effective heuristic for adaptive control of job sequences subject to variation in processing times 
Abstract:
 Variation in sequential task processing times is common in manufacturing
 systems. This type of disturbance challenges most scheduling methods since
 they cannot fundamentally change job sequences to adaptively control
 production performance as jobs enter the system because actual processing
 times, are not known in advance. Some research literature indicates that
 simple rules are more suitable than algorithmic scheduling methods for
 adaptive control. In this work, a &#x2018;state space -- average
 processing time&#x2019; (SS-APT) heuristic is proposed and compared to
 four most commonly used scheduling rules and two well-established
 heuristics based on Taillard&#x2019;s benchmarks. It is shown that the
 adaptive control is made possible under variation in processing times
 given the flexibility and strong performance of the SS-APT heuristic,
 especially for work-in-process inventory control.
Journal: International Journal of Production Research 
Pages: 3491-3507 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1073403 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1073403 
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohamed Bendraouche 
Author-X-Name-First: Mohamed 
Author-X-Name-Last: Bendraouche 
Author-Name: Mourad Boudhar 
Author-X-Name-First: Mourad 
Author-X-Name-Last: Boudhar 
Title: Scheduling with agreements: new results 
Abstract:
 In this paper, the problem of scheduling with agreements (SWA) is
 considered. In scheduling, this consists of a set of jobs non-preemptively
 on identical machines subject to constraints that only some specific jobs
 can be scheduled concurrently on different machines. These constraints are
 given by an agreement graph and the aim is to minimise the makespan. In
 the case of two machines we extend two NP-hardness results of SWA with
 processing times at most three that hold for bipartite agreement graphs to
 more general agreement graphs. Complexity results of SWA are established
 in the case of split and complement of bipartite graphs. We also present
 some approximation results for SWA.
Journal: International Journal of Production Research 
Pages: 3508-3522 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1073860 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1073860 
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Template-Type: ReDIF-Article 1.0
Author-Name: Harmen W. Bouma 
Author-X-Name-First: Harmen W. 
Author-X-Name-Last: Bouma 
Author-Name: Ruud H. Teunter 
Author-X-Name-First: Ruud H. 
Author-X-Name-Last: Teunter 
Title: The routed inventory pooling problem with multiple lateral transshipments 
Abstract:
 We consider a single item, single-period inventory problem with two
 identical retailers who can pool stocks at multiple predetermined points
 in time. Since routing decisions are often taken at the multi-item level
 in practice, we use a predetermined route for redistribution at the
 single-item level. The objective is to determine order-up-to levels and
 transshipment decisions that minimise the sum of inventory holding,
 backorder and fixed as well as variable transshipment costs. We present a
 Dynamic Programming formulation to solve the problem and we compare the
 performance of our routed pooling policy to situations without pooling and
 with complete pooling in an extensive numerical study. The results reveal
 when routed pooling performs well and when multiple pooling moments
 provide significant benefits.
Journal: International Journal of Production Research 
Pages: 3523-3533 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1082668 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1082668 
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Template-Type: ReDIF-Article 1.0
Author-Name: M. Henneberg 
Author-X-Name-First: M. 
Author-X-Name-Last: Henneberg 
Author-Name: J.S. Neufeld 
Author-X-Name-First: J.S. 
Author-X-Name-Last: Neufeld 
Title: A constructive algorithm and a simulated annealing approach for solving flowshop problems with missing operations 
Abstract:
 In many practical cases of flowshop environments and especially in
 flowline manufacturing cells, some or all jobs may not require processing
 on all machines. Hence, this paper focuses on the flowshop scheduling
 problem with missing operations. A modification of the constructive
 NPS-set heuristic is proposed, which generates non-permutation schedules
 effectively. Furthermore, a two-phase simulated annealing (SA) method is
 presented that specifically considers missing operations in its procedure.
 The modified NPS-set heuristic and the two-phase SA are tested and
 statistically evaluated by an extensive computational study for total flow
 time criteria. The results show that the modified NPS-set heuristic as
 well as the specific consideration of missing operations can enhance the
 algorithms&#x2019; performance significantly.
Journal: International Journal of Production Research 
Pages: 3534-3550 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1082670 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1082670 
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Template-Type: ReDIF-Article 1.0
Author-Name: Lin-Hui Sun 
Author-X-Name-First: Lin-Hui 
Author-X-Name-Last: Sun 
Author-Name: Kai Cui 
Author-X-Name-First: Kai 
Author-X-Name-Last: Cui 
Author-Name: Ju-hong Chen 
Author-X-Name-First: Ju-hong 
Author-X-Name-Last: Chen 
Author-Name: Jun Wang 
Author-X-Name-First: Jun 
Author-X-Name-Last: Wang 
Title: Due date assignment and convex resource allocation scheduling with variable job processing times 
Abstract:
 This is a study of a earliness and tardiness sequencing and scheduling
 problem on a single machine. The processing time for job <inline-formula
 id="ILM0001"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1083628_ilm0001.gif"/></inline-formula> depends on its
 position in a sequence, its starting time, and its allocation of
 non-renewable resource. For three due date assignment methods i.e. the
 common due date, the slack due date and the unrestricted due date our goal
 is to find the optimal schedule, due dates, and resource allocations of
 jobs. We prove that three versions of the problem can be solved in
 polynomial time, respectively.
Journal: International Journal of Production Research 
Pages: 3551-3560 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1083628 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1083628 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jin Deng 
Author-X-Name-First: Jin 
Author-X-Name-Last: Deng 
Author-Name: Ling Wang 
Author-X-Name-First: Ling 
Author-X-Name-Last: Wang 
Author-Name: Sheng-yao Wang 
Author-X-Name-First: Sheng-yao 
Author-X-Name-Last: Wang 
Author-Name: Xiao-long Zheng 
Author-X-Name-First: Xiao-long 
Author-X-Name-Last: Zheng 
Title: A competitive memetic algorithm for the distributed two-stage assembly flow-shop scheduling problem 
Abstract:
 This article addresses the distributed two-stage assembly flow-shop
 scheduling problem (DTSAFSP) with makespan minimisation criterion. A mixed
 integer linear programming model is presented, and a competitive memetic
 algorithm (CMA) is proposed. When designing the CMA, a simple encoding
 scheme is proposed to represent the factory assignment and the job
 processing sequence; and a ring-based neighbourhood structure is designed
 for competition and information sharing. Moreover, some knowledge-based
 local search operators are developed to enhance the exploitation ability.
 The influence of parameter setting on the CMA is investigated using the
 analysis of variance method. Extensive computational tests and comparisons
 are carried out, which demonstrate the effectiveness of the proposed CMA
 in solving the DTSAFSP.
Journal: International Journal of Production Research 
Pages: 3561-3577 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1084063 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1084063 
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Template-Type: ReDIF-Article 1.0
Author-Name: Israel Tirkel 
Author-X-Name-First: Israel 
Author-X-Name-Last: Tirkel 
Author-Name: Gad Rabinowitz 
Author-X-Name-First: Gad 
Author-X-Name-Last: Rabinowitz 
Author-Name: David Price 
Author-X-Name-First: David 
Author-X-Name-Last: Price 
Author-Name: Doug Sutherland 
Author-X-Name-First: Doug 
Author-X-Name-Last: Sutherland 
Title: Wafer fabrication yield learning and cost analysis based on in-line inspection 
Abstract:
 Wafer fabrication is characterised with advanced equipment, complex
 processes and high cost. Good production output, measured by yield given
 total throughput, should rapidly increase while considering the associated
 cost. Yield improvement models based on inspection usually consider the
 effect of excursion monitoring, while this work considers the effect of
 learning from experience as well. It assumes a production model where each
 machine&#x2019;s output is inspected via wafers it processes, triggering
 repair if required. The yield improvement is modelled as a function of
 machine&#x2019;s quality performance, accumulated inspections, inspection
 capacity and inspection rate. It exhibits a sigmoid shape curve with slow
 rise in startup, acceleration in ramp and almost a plateau in high volume
 manufacturing. Higher inspection rate enables more inspections over time,
 faster learning and higher yield. Yet, higher inspection rate at constant
 capacity prolongs the response time and can further drive lower yield.
 Clearly, higher inspection capacity enables faster yield improvement, but
 also increases equipment and operations costs. The cost analysis developed
 here illustrates the preferred inspection capacity and inspection rate,
 for minimising the overall cost combined of yield loss and inspection
 cost. It also shows preference to error with higher, rather than with
 lower, inspection capacity.
Journal: International Journal of Production Research 
Pages: 3578-3590 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1106609 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106609 
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu 
Author-X-Name-First: Ming 
Author-X-Name-Last: Liu 
Author-Name: Shijin Wang 
Author-X-Name-First: Shijin 
Author-X-Name-Last: Wang 
Author-Name: Chengbin Chu 
Author-X-Name-First: Chengbin 
Author-X-Name-Last: Chu 
Author-Name: Feng Chu 
Author-X-Name-First: Feng 
Author-X-Name-Last: Chu 
Title: An improved exact algorithm for single-machine scheduling to minimise the number of tardy jobs with periodic maintenance 
Abstract:
 In this paper, we investigate a single-machine scheduling problem with
 periodic maintenance, which is motivated by various industrial
 applications (e.g. tool changes). The pursued objective is to minimise the
 number of tardy jobs, because it is one of the important criteria for the
 manufacturers to avoid the loss of customers. The strong NP-hardness of
 the problem is shown. To improve the state-of-the-art exact algorithm, we
 devise a new branch-and-bound algorithm based on an efficient lower
 bounding procedure and several new dominance properties. Numerical
 experiments are conducted to demonstrate the efficiency of our exact
 algorithm.
Journal: International Journal of Production Research 
Pages: 3591-3602 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1108535 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1108535 
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Template-Type: ReDIF-Article 1.0
Author-Name: Md. Shahriar J. Hossain 
Author-X-Name-First: Md. Shahriar J. 
Author-X-Name-Last: Hossain 
Author-Name: Bhaba R. Sarker 
Author-X-Name-First: Bhaba R. 
Author-X-Name-Last: Sarker 
Title: Optimal locations of on-line and off-line rework stations in a serial production system 
Abstract:
 The production rate and product quality are two vital concerns for any
 manufacturing industry. Number of defective items reduces production rate
 and increases unit production cost. Moreover, if nonconforming items reach
 to the customers then manufacturer&#x2019;s goodwill may drastically go
 down. Thus, quality inspection is treated as an inherent part of
 manufacturing. In this research, an <italic>N</italic>-stage serial
 production line with an inspection station at the end of it is considered
 to make decisions concerning this issue. On detecting a defective item at
 the end of the line it is scrapped or repaired at regular workstation or
 is sent to an off-line rework station for repair. Assuming each
 workstation produces a single type of defect a unit cost function is
 developed for alternative decisions on each type of defect. In order to
 minimise the unit cost of production and determine an appropriate decision
 for individual defect types, a fractional mixed integer nonlinear
 programming is formulated. After transformation to a mixed integer linear
 programming problem it is solved optimally. A small problem from garments
 industry is described in detail to show the solution procedure with a
 branch and bound method. Empirical tests with up to 40 workstations are
 permed to show the efficiency of the solution process.
Journal: International Journal of Production Research 
Pages: 3603-3621 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1117676 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1117676 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jing-nan Shen 
Author-X-Name-First: Jing-nan 
Author-X-Name-Last: Shen 
Author-Name: Ling Wang 
Author-X-Name-First: Ling 
Author-X-Name-Last: Wang 
Author-Name: Huan-yu Zheng 
Author-X-Name-First: Huan-yu 
Author-X-Name-Last: Zheng 
Title: A modified teaching--learning-based optimisation algorithm for bi-objective re-entrant hybrid flowshop scheduling 
Abstract:
 In this paper, a modified teaching--learning-based optimisation (mTLBO)
 algorithm is proposed to solve the re-entrant hybrid flowshop scheduling
 problem (RHFSP) with the makespan and the total tardiness criteria. Based
 on the simple job-based representation, a novel decoding method named
 equivalent due date-based permutation schedule is proposed to transfer an
 individual to a feasible schedule. At each generation, a number of
 superior individuals are selected as the teachers by the Pareto-based
 ranking phase. To enhance the exploitation ability in the promising area,
 the insertion-based local search is embedded in the search framework as
 the training phase for the TLBO. Due to the characteristics of the
 permutation-based discrete optimisation, the linear order crossover
 operator and the swap operator are adopted to imitate the interactions
 among the individuals in both the teaching phase and the learning phase.
 To store the non-dominated solutions explored during the search process,
 an external archive is used and updated when necessary. The influence of
 the parameter setting on the mTLBO in solving the RHFSP is investigated,
 and numerical tests with some benchmarking instances are carried out. The
 comparative results show that the proposed mTLBO outperforms the existing
 algorithms significantly.
Journal: International Journal of Production Research 
Pages: 3622-3639 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1120900 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1120900 
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Template-Type: ReDIF-Article 1.0
Author-Name: R.P. Manatkar 
Author-X-Name-First: R.P. 
Author-X-Name-Last: Manatkar 
Author-Name: Kondapaneni Karthik 
Author-X-Name-First: Kondapaneni 
Author-X-Name-Last: Karthik 
Author-Name: Sri Krishna Kumar 
Author-X-Name-First: Sri Krishna 
Author-X-Name-Last: Kumar 
Author-Name: Manoj Kumar Tiwari 
Author-X-Name-First: Manoj Kumar 
Author-X-Name-Last: Tiwari 
Title: An integrated inventory optimization model for facility location-allocation problem 
Abstract:
 This paper presents an integrated inventory distribution optimisation
 model for multiple products in a multi-echelon supply chain environment.
 Inventory, transportation and location decisions are considered. The
 objective is to offer practical guideline to the steel retail supply chain
 practitioners in choosing the correct distribution centre, finding out
 inventory level at individual inventory keeping points (retailers and
 distribution centres) point thereby helping them in reducing overall
 distribution cost. The framework presented endorses systems approach and
 suggests near-optimal approach to calculating inventory for an individual
 distributor and his retailers. Two algorithms are used to solve this
 problem, a novel hybrid Multi-objective Self-learning particle swarm
 optimiser and Non-dominated sorting genetic algorithm-II. The model and
 solution methods are tested on real data-sets obtained from organisations
 in the steel retail environment. The actual data on inventory holding,
 ordering and transportation costs of distributors and retailers are used
 as inputs. The decisions like choosing correct set of Distribution
 centres, keeping optimal regular and safety stock inventory levels are
 arrived at by applying practical constraints in the supply chain. Model
 developed assists in effective and efficient distribution of the products
 manufactured from the optimal location at minimal cost.
Journal: International Journal of Production Research 
Pages: 3640-3658 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1120903 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1120903 
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Template-Type: ReDIF-Article 1.0
Author-Name: Fateme Akhoondi 
Author-X-Name-First: Fateme 
Author-X-Name-Last: Akhoondi 
Author-Name: M.M. Lotfi 
Author-X-Name-First: M.M. 
Author-X-Name-Last: Lotfi 
Title: A heuristic algorithm for master production scheduling problem with controllable processing times and scenario-based demands 
Abstract:
 Master production scheduling (MPS) is widely used by manufacturing
 industries in order to handle the production scheduling decisions in the
 production planning hierarchy. The classical approach to MPS assumes
 infinite capacity, fixed (i.e. non-controllable) processing times and a
 single pre-determined scenario for the demand forecasts. However, the
 deterministic optimisation approaches are sometimes not suitable for
 addressing the real-world problems with high uncertainty and flexibility.
 Accordingly, in this paper, we propose a new practical model for designing
 an optimal MPS for the environments in which processing times may be
 controllable by allocating resources such as facilities, energy or
 manpower. Due to the NP-hardness of our model, an efficient heuristic
 algorithm using local search technique and theory of constraints is
 developed and analysed. The computational results especially for
 large-sized test problems show that the average optimality gap of proposed
 algorithm is four times lower than that of exact solution using GAMS while
 it consumes also significantly smaller run times. Also, the analysis of
 computational results confirms that considering the controllable
 processing times may improve the solution space and help to more
 efficiently utilise the available resources. According to the model
 structure and performance of the algorithm, it may be proposed for solving
 large and complex real-world problems particularly the machining and steel
 industries.
Journal: International Journal of Production Research 
Pages: 3659-3676 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1125032 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1125032 
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Template-Type: ReDIF-Article 1.0
Author-Name: Qin Chen 
Author-X-Name-First: Qin 
Author-X-Name-Last: Chen 
Author-Name: ShiLong Liao 
Author-X-Name-First: ShiLong 
Author-X-Name-Last: Liao 
Author-Name: ZhongZhen Wu 
Author-X-Name-First: ZhongZhen 
Author-X-Name-Last: Wu 
Author-Name: ShuPing Yi 
Author-X-Name-First: ShuPing 
Author-X-Name-Last: Yi 
Title: Comparative analysis of the performance of a novel U-shaped &#x2018;chasing-overtaking&#x2019; production line 
Abstract:
 Fluctuations in market demands, increased mobility of workers and changing
 employment practices as well as companies&#x2019; increased respect for
 individual differences of workers have led to the phenomenon that workers
 with large efficiency differences work together in the same production
 line in manufacturing companies. In a traditional travelling production
 line (TrPL), low-efficiency workers can block the work of higher
 efficiency workers. To increase the production capacity of a travelling
 line composed of workers with different efficiencies, a chasing-overtaking
 mechanism was established and used to achieve line production capacity and
 efficiency improvement. A formula to calculate the production capacity of
 two workers with different efficiencies was derived and validated. A
 simulation performed to analyse the differences between the
 &#x2018;chasing-overtaking&#x2019; production line (COPL), TrPL and the
 classic &#x2018;bucket brigade&#x2019; production line (BBPL) with respect
 to production capacity, working time utilisation and equipment utilisation
 demonstrated that the COPL provides good production capacity and
 adaptability to worker differences. Finally, the statistical analysis
 verified that the COPL has a higher production capacity, average worker
 working hour utilisation rate and equipment utilisation rate than the BBPL
 and TrPL.
Journal: International Journal of Production Research 
Pages: 3677-3690 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1125033 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1125033 
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Template-Type: ReDIF-Article 1.0
Author-Name: Du-Juan Wang 
Author-X-Name-First: Du-Juan 
Author-X-Name-Last: Wang 
Author-Name: Yunqiang Yin 
Author-X-Name-First: Yunqiang 
Author-X-Name-Last: Yin 
Author-Name: Mengqi Liu 
Author-X-Name-First: Mengqi 
Author-X-Name-Last: Liu 
Title: Bicriteria scheduling problems involving job rejection, controllable processing times and rate-modifying activity 
Abstract:
 This paper addresses the bicriteria scheduling problems with simultaneous
 consideration of job rejection, controllable processing times and
 rate-modifying activity on a single machine. A job is either rejected, in
 which case a rejection penalty will be incurred, or accepted and processed
 on the machine. The rate-modifying activity is an activity on the machine
 that changes the processing times of the jobs scheduled after the
 activity. The processing time of a job scheduled after the rate-modifying
 activity decreases with a job-dependent factor. The processing time of
 each job can also be controlled by allocating extra resource which is
 either a linear or a convex function of the amount of a common
 continuously divisible resource allocated to the job. The objective is to
 determine the rejected job set, the accepted job sequence, the time
 (location) of the rate-modifying activity and the resource allocation that
 jointly find the trade-off between two criteria, where the first criterion
 is measured as the sum of total completion time and resource consumption
 cost while the second criterion is the total rejection cost. We consider
 four different models for treating the two criteria. The computational
 complexity status and solution procedures are provided for the problems
 under consideration.
Journal: International Journal of Production Research 
Pages: 3691-3705 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1136081 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1136081 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xin Feng 
Author-X-Name-First: Xin 
Author-X-Name-Last: Feng 
Author-Name: Feifeng Zheng 
Author-X-Name-First: Feifeng 
Author-X-Name-Last: Zheng 
Author-Name: Yinfeng Xu 
Author-X-Name-First: Yinfeng 
Author-X-Name-Last: Xu 
Title: Robust scheduling of a two-stage hybrid flow shop with uncertain interval processing times 
Abstract:
 This paper studies the makespan minimisation scheduling problem in a
 two-stage hybrid flow shop. The first stage has one machine and the second
 stage has <italic>m</italic> identical parallel machines. Neither the
 processing time nor probability distribution of the processing time of
 each job is uncertain. We propose a robust (min--max regret) scheduling
 model. To solve the robust scheduling problem, which is NP-hard, we first
 derive some properties of the worst-case scenario for a given schedule. We
 then propose both exact and heuristic algorithms to solve this problem. In
 addition, computational experiments are conducted to evaluate the
 performance of the proposed algorithms.
Journal: International Journal of Production Research 
Pages: 3706-3717 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2016.1162341 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1162341 
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Template-Type: ReDIF-Article 1.0
Author-Name: Klaus Altendorfer 
Author-X-Name-First: Klaus 
Author-X-Name-Last: Altendorfer 
Author-Name: Thomas Felberbauer 
Author-X-Name-First: Thomas 
Author-X-Name-Last: Felberbauer 
Author-Name: Herbert Jodlbauer 
Author-X-Name-First: Herbert 
Author-X-Name-Last: Jodlbauer 
Title: Effects of forecast errors on optimal utilisation in aggregate production planning with stochastic customer demand 
Abstract:
 The hierarchical structure of production planning has the advantage of
 assigning different decision variables to their respective time horizons
 and therefore ensures their manageability. However, the restrictive
 structure of this top-down approach implying that upper level decisions
 are the constraints for lower level decisions also has its shortcomings.
 One problem that occurs is that deterministic mixed integer decision
 problems are often used for long-term planning, but the real production
 system faces a set of stochastic influences. Therefore, a planned
 utilisation factor has to be included into this deterministic aggregate
 planning problem. In practice, this decision is often based on past data
 and not consciously taken. In this paper, the effect of long-term forecast
 error on the optimal planned utilisation factor is evaluated for a
 production system facing stochastic demand and the benefit of exploiting
 this decision&#x2019;s potential is discussed. Overall costs including
 capacity, backorder and inventory costs, are determined with simulation
 for different multi-stage and multi-item production system structures. The
 results show that the planned utilisation factor used in the aggregate
 planning problem has a high influence on optimal costs. Additionally, the
 negative effect of forecast errors is evaluated and discussed in detail
 for different production system environments.
Journal: International Journal of Production Research 
Pages: 3718-3735 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2016.1162918 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1162918 
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Template-Type: ReDIF-Article 1.0
Author-Name: Hamidreza Zahedi 
Author-X-Name-First: Hamidreza 
Author-X-Name-Last: Zahedi 
Author-Name: Christian Mascle 
Author-X-Name-First: Christian 
Author-X-Name-Last: Mascle 
Author-Name: Pierre Baptiste 
Author-X-Name-First: Pierre 
Author-X-Name-Last: Baptiste 
Title: A quantitative evaluation model to measure the disassembly difficulty; application of the semi-destructive methods in aviation End-of-Life 
Abstract:
 Sustainable decommissioning of aircraft with a high content of metallic
 and non-metallic components is a current challenge in the industry. This
 process has historically appeared to be economically, environmentally and
 socially unviable. Literature indicates that, unlike entirely destructive
 and totally non-destructive techniques, semi-destructive disassembly may
 bring significant benefits. However, despite their use in a wide variety
 of applications, there are currently no feasible solutions on how to
 measure the associated physical difficulties and required efforts without
 any dependencies on expert views or filling out spreadsheet-like forms. In
 this paper, a new model is developed to accurately evaluate the
 disassembly easiness of an airframe quantitatively incorporating both
 product and process features. Based on a real disassembly of a passenger
 jet, the cutting and thrust force vectors are selected to evaluate and
 find the best operation sets. An airliner Horizontal Stabiliser is
 analysed as a case study. The results indicate that minor drilling, as a
 hybrid operation, can reduce the disassembly efforts significantly while
 offering an increased material recovery chance. Such quantitative
 evaluation can help to: proceed with a viable End-of-Life strategy; and
 implement newer approaches like automated disassembly by designing better
 disassembly robots, tool selection and process control.
Journal: International Journal of Production Research 
Pages: 3736-3748 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2016.1165877 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165877 
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Template-Type: ReDIF-Article 1.0
Author-Name: Christopher Durugbo 
Author-X-Name-First: Christopher 
Author-X-Name-Last: Durugbo 
Title: Collaborative networks: a systematic review and multi-level framework 
Abstract:
 Collaborative networks (CNs) leverage the improving sociability and
 usability features of information technology to enable and enhance
 partnering that delivers competitive solutions. This partnering is
 motivated by business, supply chain, market and technological evolutions
 that create uncertainty and pressure on independently operating firms.
 Accordingly, literature on CNs has enhanced practice by shedding light on
 the collaboration patterns that underlie CNs and the different management
 mechanisms that are required to cope with the complexity of CNs. The
 purpose of this article is to systematically review the state-of-the-art
 of research for CNs with a view to identifying future research potentials
 and directions. It offers an assembling, critical appraisal and synthesis
 of the literature on CNs and focuses on the logic and management of CNs.
 It contributes to knowledge by outlining a multi-level framework of CNs
 based on the review findings. It is anticipated that the review will serve
 as the foundation for breaking new grounds in research and further advance
 the discipline of CNs.
Journal: International Journal of Production Research 
Pages: 3749-3776 
Issue: 12 
Volume: 54 
Year: 2016 
Month: 6 
X-DOI: 10.1080/00207543.2015.1122249 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1122249 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xue Chang 
Author-X-Name-First: Xue 
Author-X-Name-Last: Chang 
Author-Name: Jing Li 
Author-X-Name-First: Jing 
Author-X-Name-Last: Li 
Author-Name: Daniel Rodriguez 
Author-X-Name-First: Daniel 
Author-X-Name-Last: Rodriguez 
Author-Name: Qun Su 
Author-X-Name-First: Qun 
Author-X-Name-Last: Su 
Title: Agent-based simulation of pricing strategy for agri-products considering customer preference 
Abstract:
 Agri-products typically have short life cycles and are perishable. The
 price of perishable goods is influenced by many factors. Customers in a
 market have different preferences with regard to price, the quality of the
 product and the brand. Though studies on pricing strategies that consider
 customer preference are rare, this paper addresses the problem of optimal
 pricing strategy for retailers considering customer preferences.
 Traditional mathematical methods cannot adequately describe the
 complexities of customer preference. Due to these complexities, this paper
 proposes an agent-based simulation model composed of six retailers and
 hundreds of customers, each with personal preferences. The different
 retailers set prices according to freshness, inventory, cost and other
 factors. Due to the perishable nature of the products considered, this
 paper proposes a new categorising price strategy that sets prices
 according to different degrees of treatments. By comparing the final
 profit of all retailers at the end of a simulation, the categorising price
 strategy is demonstrated to be the optimal strategy if customers with
 different preferences are randomly distributed. Furthermore, based on the
 model, the paper studies how optimal strategies are influenced by the
 proportion of customers with different preferences.
Journal: International Journal of Production Research 
Pages: 3777-3795 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1120901 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1120901 
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Template-Type: ReDIF-Article 1.0
Author-Name: Qianqian Yuan 
Author-X-Name-First: Qianqian 
Author-X-Name-Last: Yuan 
Author-Name: Shilling Song 
Author-X-Name-First: Shilling 
Author-X-Name-Last: Song 
Author-Name: Feng Yang 
Author-X-Name-First: Feng 
Author-X-Name-Last: Yang 
Title: Advertising for price-sensitive products with multi-attribute considered 
Abstract:
 This study provides a framework for a marketing manager to make
 advertising decisions for price-sensitive products. One promotion, price
 discount, is offered at the same time as local advertising and national
 advertising. Unlike previous studies that mainly considered sales profit
 as the primary goal, this study considers two other attributes, goodwill
 and customer scale, in making advertising investments. In all cases, a
 strategy with larger values of these attributes is better. However,
 maximising these three attributes simultaneously is difficult or
 impossible, so managers must balance trade-offs between them. We utilise
 the stochastic multi-attributes analysis in this paper. This method is a
 multi-attributes decision support technique based on exploring the weight
 space, helping managers make optimal advertising decisions regarding these
 three attributes. A numerical example is presented to illustrate the
 proposed approach.
Journal: International Journal of Production Research 
Pages: 3796-3807 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1148274 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1148274 
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Template-Type: ReDIF-Article 1.0
Author-Name: Guowei Dou 
Author-X-Name-First: Guowei 
Author-X-Name-Last: Dou 
Author-Name: Ping He 
Author-X-Name-First: Ping 
Author-X-Name-Last: He 
Author-Name: Xiaoyan Xu 
Author-X-Name-First: Xiaoyan 
Author-X-Name-Last: Xu 
Title: One-side value-added service investment and pricing strategies for a two-sided platform 
Abstract:
 To widen user participation and increase profit, two-sided platforms may
 invest on value-added services (VASs) for users. Due to the cross-market
 network externality, the investment for one side would affect the utility
 of users on two sides, thus affect the demand and profit of the platform.
 In this paper, we investigate one-side VAS investment and pricing
 strategies for a two-sided platform. It is revealed that it is optimal to
 invest at the maximum level for any marginal investing cost below a
 certain threshold, and to decrease the investment when the marginal
 investing cost increases above the threshold. We find that compared with
 the case of no investment, the invested user side will always be priced
 higher, while the uninvested user side may either be priced higher or
 lower, depending on the relative magnitude of mutual cross-market network
 externalities. If both sides are priced higher after the investment, the
 price increment for uninvested user side could be larger than that for
 invested user side.
Journal: International Journal of Production Research 
Pages: 3808-3821 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1148275 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1148275 
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Template-Type: ReDIF-Article 1.0
Author-Name: Florian Sahling 
Author-X-Name-First: Florian 
Author-X-Name-Last: Sahling 
Title: Integration of vendor selection into production and remanufacturing planning subject to emission constraints 
Abstract:
 This paper presents a new model formulation that incorporates vendor
 selection into production and remanufacturing planning subject to emission
 constraints. The objective is to determine a feasible production and
 remanufacturing plan at minimal cost. In each period, the given external
 demand must be satisfied for both new and remanufactured products.
 Remanufactured products can be substituted by new products, but not vice
 versa. When a product is (re)manufactured, the appropriate machine must be
 set up, which entails set-up costs and/or set-up time. The procurement of
 raw material that is offered by several vendors at different prices is
 integrated into this planning problem. To solve this integrated production
 and remanufacturing planning problem, we apply two solution approaches
 based on mathematical programming: first, a combination of column
 generation and a period-oriented fix-and-relax heuristic and second, an
 adapted fix-and-optimise heuristic. The results of our numerical
 investigation demonstrate the high solution quality of both solution
 approaches.
Journal: International Journal of Production Research 
Pages: 3822-3836 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1148276 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1148276 
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Template-Type: ReDIF-Article 1.0
Author-Name: Yu-Chung Tsao 
Author-X-Name-First: Yu-Chung 
Author-X-Name-Last: Tsao 
Title: Designing a supply chain network for deteriorating inventory under preservation effort and trade credits 
Abstract:
 When designing a perishable goods supply chain network under trade credit
 arrangements, distribution companies must contend with deteriorating
 inventory and product preservation efforts to maximise profits. Key
 decisions include locating distribution centres (DCs), assigning retail
 stores to DCs, joint replenishment cycle time and investing in
 preservation technology. This paper addresses these factors from the
 position that as preservation effort increases, preservation technology
 cost increases and deterioration rate decreases. An algorithm based on
 piecewise nonlinear optimisation is provided for solving supply chain
 network design problems efficiently. In contrast to other studies that
 have used the approximation approach, the proposed approach solves the
 original problem accurately and efficiently. Numerical studies are
 conducted to demonstrate the solutions procedures and determine the
 effects of the parameters on decisions and profits. The results of this
 study and the proposed modelling approach are useful references for
 managerial decisions in designing a supply chain network the context of
 trade credit and inventory deterioration.
Journal: International Journal of Production Research 
Pages: 3837-3851 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1157272 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1157272 
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Template-Type: ReDIF-Article 1.0
Author-Name: A. Negahban 
Author-X-Name-First: A. 
Author-X-Name-Last: Negahban 
Author-Name: J.S. Smith 
Author-X-Name-First: J.S. 
Author-X-Name-Last: Smith 
Title: The effect of supply and demand uncertainties on the optimal production and sales plans for new products 
Abstract:
 When introducing a new product, firms face a hierarchy of decisions at the
 strategic and operational levels including capacity sizing, time to market
 or starting sales, initial inventory required by the product&#x2019;s
 release time and production management in response to changes in the
 demand (hereafter referred to as production-sales policies). The goal of
 this paper was to show the importance of considering both supply and
 demand uncertainties in the determination of the production-sales policy
 which has been overlooked in the existing literature. More specifically,
 we test two main hypotheses: (1) ignoring supply and demand uncertainties
 may lead to potentially incorrect decisions; and, (2) the decision could
 be different if risk is used as the primary performance measure instead of
 the commonly used expected (mean) profit. We perform extensive
 experimentation with a Monte Carlo simulation model of the stochastic
 supply-restricted new product diffusion and use different statistical
 procedures, namely, the Welch&#x2019;s <italic>t</italic>-test and a
 nonparametric double-bootstrap method to compare the average and
 percentiles of the profit for different policies, respectively. The
 results indicate that the correctness of the two hypotheses depends on the
 diffusion speed, consumers&#x2019; backlogging behaviour, production
 capacity, price and variable production and inventory costs. The findings
 also have important implications for managers regarding market entry time,
 parameter estimation, production strategy and the implementation of the
 proposed model.
Journal: International Journal of Production Research 
Pages: 3852-3869 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1157274 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1157274 
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Template-Type: ReDIF-Article 1.0
Author-Name: Baofeng Huo 
Author-X-Name-First: Baofeng 
Author-X-Name-Last: Huo 
Author-Name: Qiang Wang 
Author-X-Name-First: Qiang 
Author-X-Name-Last: Wang 
Author-Name: Xiande Zhao 
Author-X-Name-First: Xiande 
Author-X-Name-Last: Zhao 
Author-Name: Sebastian Schuh 
Author-X-Name-First: Sebastian 
Author-X-Name-Last: Schuh 
Title: Threats and benefits of power discrepancies between organisations: a supply chain perspective 
Abstract:
 The discrepancy of power between organisations has raised concerns over
 the abuse of power in inter-organisational relationships, especially in
 the supply chain where parties often have different power positions. In
 this study, we develop and test a model that explains how the less
 powerful party may react to different forms of power exercised by the
 power source. Nowadays, customers are typically more powerful than
 manufacturers in supply chains. Specifically, based on data from 617
 manufacturers representing various organisational sizes and industries, we
 examine the impact of customer coercive and expert power on the
 manufacturer&#x2019;s information sharing behaviours (information systems
 and content) as well as the performance implications for both the
 manufacturer and the customer. Structural equation modelling reveals that
 customer expert power positively predicts the establishment of information
 systems and the extent to which information is actively shared. In
 contrast, customer coercive power is negatively associated with the
 establishment of information systems, while it is positively related to
 information content. Information systems, in turn, predict the extent to
 which information is effectively exchanged, which ultimately relates
 positively to flexibility and delivery performance. Flexibility
 performance is positively related to financial performance, while delivery
 performance is not. Taken together, these findings enrich our
 understanding of inter-organisational power dynamics by offering important
 insights into differential reactions that the power target may choose to
 counter power imbalances.
Journal: International Journal of Production Research 
Pages: 3870-3884 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1159744 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1159744 
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Template-Type: ReDIF-Article 1.0
Author-Name: Ehsan Ardjmand 
Author-X-Name-First: Ehsan 
Author-X-Name-Last: Ardjmand 
Author-Name: Gary R. Weckman 
Author-X-Name-First: Gary R. 
Author-X-Name-Last: Weckman 
Author-Name: William A. Young 
Author-X-Name-First: William A. 
Author-X-Name-Last: Young 
Author-Name: Omid  Sanei Bajgiran 
Author-X-Name-First: Omid 
Author-X-Name-Last:  Sanei Bajgiran 
Author-Name: Bizhan Aminipour 
Author-X-Name-First: Bizhan 
Author-X-Name-Last: Aminipour 
Title: A robust optimisation model for production planning and pricing under demand uncertainty 
Abstract:
 The profitability of every manufacturing plant is dependent on its pricing
 strategy and a production plan to support the customers&#x2019; demand. In
 this paper, a new robust multi-product and multi-period model for planning
 and pricing is proposed. The demand is considered to be uncertain and
 price-dependent. Thus, for each price, a range of demands is possible. The
 unsatisfied demand is considered to be lost and hence, no backlogging is
 allowed. The objective is to maximise the profit over the planning
 horizon, which consists of a finite number of periods. To solve the
 proposed model, a modified unconscious search (US) algorithm is
 introduced. Several artificial test problems along with a real case
 implementation of the model in a textile manufacturing plant are used to
 show the applicability of the model and effectiveness of the US for
 tackling this problem. The results show that the proposed model can
 improve the profitability of the plant and the US is able to find high
 quality solutions in a very short time compared to exact methods.
Journal: International Journal of Production Research 
Pages: 3885-3905 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1161251 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1161251 
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Template-Type: ReDIF-Article 1.0
Author-Name: Florian Klug 
Author-X-Name-First: Florian 
Author-X-Name-Last: Klug 
Title: Analysing bullwhip and backlash effects in supply chains with phase space trajectories 
Abstract:
 We will investigate demand and supply variations in supply chains commonly
 known as bullwhip and backlash effects. The main goal of this paper is to
 detect bullwhip and backlash effects and its interactions by measuring
 only a few supply chain variables. To do so, we consider a multistage
 supply chain and analyse it with the aid of phase space trajectories. An
 examination of the geometrical structures of trajectories can reveal the
 dynamics of the bullwhip and backlash behaviour in supply chains.
 Therefore, we use a physical analogy to wave theory and describe order and
 delivery oscillations as a process of wave reflection. The proposed
 methodology systematically provides the basis for analysing a number of
 dynamic and transient behaviours that supplement the traditional analysis.
 These behaviour patterns include supply chain stability, compactness and
 bullwhip/backlash trade-offs, which have important consequences for the
 design, operation and control of supply chains.
Journal: International Journal of Production Research 
Pages: 3906-3926 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1162342 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1162342 
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Template-Type: ReDIF-Article 1.0
Author-Name: Po-Chen Lin 
Author-X-Name-First: Po-Chen 
Author-X-Name-Last: Lin 
Author-Name: Reha Uzsoy 
Author-X-Name-First: Reha 
Author-X-Name-Last: Uzsoy 
Title: Chance-constrained formulations in rolling horizon production planning: an experimental study 
Abstract:
 Rolling horizon procedures, where an infinite horizon problem is
 approximated by the solution to a sequence of finite horizon problems, are
 common in production planning practice and research. However, these
 procedures also lead to frequent changes in planned release and production
 quantities, a phenomenon referred to as nervousness. We examine the
 performance of two chance-constrained production planning models developed
 for systems with stochastic demand in a rolling horizon environment, and
 find that these formulations significantly reduce planned release changes
 (nervousness) while also improving cost and service-level performance.
Journal: International Journal of Production Research 
Pages: 3927-3942 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1165356 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165356 
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Template-Type: ReDIF-Article 1.0
Author-Name: Arda Yenipazarli 
Author-X-Name-First: Arda 
Author-X-Name-Last: Yenipazarli 
Author-Name: Harold P. Benson 
Author-X-Name-First: Harold P. 
Author-X-Name-Last: Benson 
Author-Name: Selcuk Erenguc 
Author-X-Name-First: Selcuk 
Author-X-Name-Last: Erenguc 
Title: A branch-and-bound algorithm for the concave cost supply problem 
Abstract:
 Effective supplier selection and allocation of order quantity among
 multiple suppliers are indispensable to the success of a manufacturing
 company. While companies have begun to turn into a comprehensive
 multi-criteria approach, most buyers still consider purchasing cost to be
 their primary concern in selecting their suppliers. In this paper, we
 consider the concave cost supply problem where a manufacturer seeks to
 select the suppliers and simultaneously procure the quantity of
 material/component required for production at the minimum total cost
 during a standard production period. We provide and validate an effective
 and efficient branch-and-bound algorithm that is finite and that finds the
 global optimal solution of the problem without any restrictions on the
 cost functions or on the set of input parameters used in the problem.
 Numerical experiments are conducted to evaluate the performance of the
 proposed algorithm.
Journal: International Journal of Production Research 
Pages: 3943-3961 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1165358 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165358 
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Template-Type: ReDIF-Article 1.0
Author-Name: I-Hsuan Hong 
Author-X-Name-First: I-Hsuan 
Author-X-Name-Last: Hong 
Author-Name: Pin-Chun Chen 
Author-X-Name-First: Pin-Chun 
Author-X-Name-Last: Chen 
Author-Name: Hsien-Ting Yu 
Author-X-Name-First: Hsien-Ting 
Author-X-Name-Last: Yu 
Title: The effects of government subsidies on decentralised reverse supply chains 
Abstract:
 This paper examines the impacts of exogenous government subsidies on
 recycled material flows in decentralised reverse supply chains where
 players behave according to their own interests. We present a four-tiered
 network equilibrium model consisting of the sources of electronic scrap
 products and the collectors, processors and demand markets. We
 mathematically transform the players&#x2019; optimality conditions
 governing players&#x2019; behaviours into a variational inequality
 formulation. We investigate the impact of alternate schemes of government
 subsidies on the equilibrium amount, subsidy effectiveness and subsidy
 elasticity. The real-world case study shows that subsidising the tier of
 processors demonstrates the superiority of the investigated performance
 measures.
Journal: International Journal of Production Research 
Pages: 3962-3977 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1167982 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1167982 
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Template-Type: ReDIF-Article 1.0
Author-Name: Devendra Choudhary 
Author-X-Name-First: Devendra 
Author-X-Name-Last: Choudhary 
Author-Name: Ravi Shankar 
Author-X-Name-First: Ravi 
Author-X-Name-Last: Shankar 
Author-Name: M.K. Tiwari 
Author-X-Name-First: M.K. 
Author-X-Name-Last: Tiwari 
Author-Name: Arun Kr. Purohit 
Author-X-Name-First: Arun Kr. 
Author-X-Name-Last: Purohit 
Title: VMI versus information sharing: an analysis under static uncertainty strategy with fill rate constraints 
Abstract:
 A vendor-managed inventory (VMI) relationship between a downstream
 retailer and an upstream vendor consists of two distinct components: (i)
 information sharing (IS) and (ii) a shift in decision-making
 responsibility. This study compares these two components of VMI in a
 two-stage serial supply chain based on the &#x2018;static
 uncertainty&#x2019; strategy under dynamic and random demand with fill
 rate constraints. Numerical experiments are conducted using analytical
 models to identify the conditions where the incremental value of VMI over
 IS is significant. The results provide guidelines relevant to academia and
 supply chain practitioners in taking VMI adoption decision above and
 beyond IS according to their specific business environment.
Journal: International Journal of Production Research 
Pages: 3978-3993 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1168943 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1168943 
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Template-Type: ReDIF-Article 1.0
Author-Name: Juan P&#xe9;rez 
Author-X-Name-First: Juan 
Author-X-Name-Last: P&#xe9;rez 
Author-Name: H&#xe9;ctor L&#xf3;pez-Ospina 
Author-X-Name-First: H&#xe9;ctor 
Author-X-Name-Last: L&#xf3;pez-Ospina 
Author-Name: Alejandro Cataldo 
Author-X-Name-First: Alejandro 
Author-X-Name-Last: Cataldo 
Author-Name: Juan-Carlos Ferrer 
Author-X-Name-First: Juan-Carlos 
Author-X-Name-Last: Ferrer 
Title: Pricing and composition of bundles with constrained multinomial logit 
Abstract:
 In this paper, we propose an extension of the problem of bundling with
 multinomial logit, making an explicit inclusion of the consumers&#x2019;
 maximum willingness to pay (MWTP) by means of the constrained multinomial
 logit (CMNL). In the bundling problem, we determine the price and the
 composition of bundles offered for a single segment of consumers by a
 firm, which is competing with others in the market, and we compare this
 result to a base case in which the consumers&#x2019; MWTP is not
 considered. We assume these consumers as rational since they choose the
 bundle that maximise their utility and the bundle price is within their
 MWTP. The resulting model is a non-linear mixed integer programme which is
 solved in two steps: (i) pricing is the first step; the prices are
 numerically determined in a fixed point equations system and (ii) in the
 second step the composition of the bundle is determined by explicit
 enumeration. The results show that the price obtained is less than the one
 got in the case without CMNL (and bigger than the costs), and the
 composition of the offered bundle is different as well. It is possible to
 conclude that not considering the consumers&#x2019; MWTP in the context of
 the problem of bundling will imply an overestimation of the firm&#x2019;s
 profit. We have analysed as well the results for a Chilean
 telecommunications company. These results show the importance of including
 the MWTP in the pricing and composition process.
Journal: International Journal of Production Research 
Pages: 3994-4007 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1170905 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1170905 
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Template-Type: ReDIF-Article 1.0
Author-Name: Hai Li 
Author-X-Name-First: Hai 
Author-X-Name-Last: Li 
Author-Name: Stuart X. Zhu 
Author-X-Name-First: Stuart X. 
Author-X-Name-Last: Zhu 
Author-Name: Nanfang Cui 
Author-X-Name-First: Nanfang 
Author-X-Name-Last: Cui 
Author-Name: Jianbin Li 
Author-X-Name-First: Jianbin 
Author-X-Name-Last: Li 
Title: Analysis of gray markets in differentiated duopoly 
Abstract:
 In recent years, gray markets have become a significant phenomenon in the
 business practice. This paper investigates the gray markets issues in
 differentiated duopoly case by considering quantity competition among
 firms. We develop a game-theoretic model and provide equilibrium results
 for three scenarios, i.e. the benchmark scenario &#x2018;no gray
 market&#x2019;, the scenario &#x2018;parallel imports act as a buffer
 against a follower&#x2019;s product&#x2019; and the scenario &#x2018;gray
 markets stimulate the competition&#x2019;. By the analysis of the
 equilibrium results, some important managerial insights are obtained.
 Finally, by comparison of the equilibrium results among different
 scenarios, we study the impact of gray markets on manufacturers&#x2019;
 optimal strategies and profits in differentiated duopoly.
Journal: International Journal of Production Research 
Pages: 4008-4027 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1170906 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1170906 
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Template-Type: ReDIF-Article 1.0
Author-Name: Congjun Rao 
Author-X-Name-First: Congjun 
Author-X-Name-Last: Rao 
Author-Name: Yong Zhao 
Author-X-Name-First: Yong 
Author-X-Name-Last: Zhao 
Author-Name: Junjun Zheng 
Author-X-Name-First: Junjun 
Author-X-Name-Last: Zheng 
Author-Name: Cheng Wang 
Author-X-Name-First: Cheng 
Author-X-Name-Last: Wang 
Author-Name: Zhongwen Chen 
Author-X-Name-First: Zhongwen 
Author-X-Name-Last: Chen 
Title: An extended uniform-price auction mechanism of homogeneous divisible goods: supply optimisation and non-strategic bidding 
Abstract:
 In an extended uniform-price auction mechanism of homogeneous divisible
 goods, strategic buyers and non-strategic buyers are allowed to
 participate in the auction simultaneously, and the optimal supply to
 strategic buyers is determined by a seller after having observed the bids.
 For both nonlinear bids and linear bids given by symmetric buyers, pure
 strategy symmetric Nash equilibriums are analysed, and then the dominant
 relationship is discussed deeply between the two kinds of equilibrium
 bids. Some conclusions are drawn about this extended uniform-price auction
 mechanism, i.e. nonlinear equilibrium bids dominate linear ones, and the
 supply optimisation can effectively reduce the buyers&#x2019; market power
 and thus eliminate many underpricing equilibriums. Moreover, several
 suggestions are given on how to choose optimal bidding strategies for
 buyers and how to design an optimal mechanism for a seller.
Journal: International Journal of Production Research 
Pages: 4028-4042 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1171417 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1171417 
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Template-Type: ReDIF-Article 1.0
Author-Name: Nengmin Wang 
Author-X-Name-First: Nengmin 
Author-X-Name-Last: Wang 
Author-Name: Jizhou Lu 
Author-X-Name-First: Jizhou 
Author-X-Name-Last: Lu 
Author-Name: Gengzhong Feng 
Author-X-Name-First: Gengzhong 
Author-X-Name-Last: Feng 
Author-Name: Yungao Ma 
Author-X-Name-First: Yungao 
Author-X-Name-Last: Ma 
Author-Name: Huigang Liang 
Author-X-Name-First: Huigang 
Author-X-Name-Last: Liang 
Title: The bullwhip effect on inventory under different information sharing settings based on price-sensitive demand 
Abstract:
 Information sharing (IS) is proved to be a valid method to counter demand
 variability amplification along the supply chain, or bullwhip effect
 (BWE). Different from the traditional way of measuring the BWE based on
 order quantity, we measure the BWE on inventory in different IS settings
 and try to find the best IS approach. In this paper, the retailer will
 face the market demand which is price-sensitive, and the price follows a
 first-order autoregressive process. This demand model includes some
 indexes that can provide more useful managerial insights than previously
 studied parameters. Our study identifies the best IS setting under any
 conditions, and clarifies that the benefits of IS will be evident when the
 overall market product pricing process is highly correlated over time, the
 demand shocks to the retailer are high, the price sensitivity coefficient
 is small, the overall market shocks are low, the retailer&#x2019;s
 lead-time is long and the manufacturer&#x2019;s lead-time is short.
Journal: International Journal of Production Research 
Pages: 4043-4064 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1171418 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1171418 
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Template-Type: ReDIF-Article 1.0
Author-Name: Scott R. Swenseth 
Author-X-Name-First: Scott R. 
Author-X-Name-Last: Swenseth 
Author-Name: David L. Olson 
Author-X-Name-First: David L. 
Author-X-Name-Last: Olson 
Title: Trade-offs in lean vs. outsourced supply chains 
Abstract:
 Lean supply chain management is well established, effective in improving
 inventory control as well as leading to greater quality. Continuous
 improvement obtained from lean implementation is expected to lead to
 better learning, yielding added profitability over time. However, the
 growth of global supply chains lead to increased complexity and
 variability, which may not always favour the lean management style. Impact
 on total cost is often difficult to precisely estimate, in part due to
 high levels of uncertainty with respect to disaster and catastrophe,
 changing governmental regulation around the world, and in part due to
 increased variability from longer supply lines. We examine some of the
 cost impacts of lean systems vs. outsourcing policies with assumed
 purchasing cost advantages through simulation of a global supply chain
 with detailed inventory factors, and compare relative profit impact. These
 results are used to argue that in some circumstances strategic
 considerations such as lower purchasing cost can override short-term
 inventory savings obtained from lean systems.
Journal: International Journal of Production Research 
Pages: 4065-4080 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1173251 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173251 
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Template-Type: ReDIF-Article 1.0
Author-Name: Chuanxu Wang 
Author-X-Name-First: Chuanxu 
Author-X-Name-Last: Wang 
Author-Name: Rongbing Huang 
Author-X-Name-First: Rongbing 
Author-X-Name-Last: Huang 
Title: Comments on &#x2018;vendor-managed inventory with consignment stock agreement for single vendor--single buyer under the emission-trading scheme&#x2019; 
Abstract:
 Zanoni, Mazzoldi, and Jaber [Zanoni, S., L. Mazzoldi, and M. Y., Jaber.
 2014. Vendor-managed inventory with consignment stock agreement for single
 vendor--single buyer under the emission-trading scheme.
 <italic>International Journal of Production Research</italic> 52 (1):
 20--31] consider a joint economic lot size problem under the
 vendor-managed inventory with consignment stock agreement and an
 emission-trading scheme. They show that the total cost of the system is a
 jointly convex function by simply showing that every element of the
 Hessian is positive. Noticing this mistake, we analyse the same problem in
 this technical note. We first provide a closed-form solution when the
 production rate is given. In order to avoid a complete search over all
 possible production rates, we then develop an efficient continuous
 approximation algorithm. Computational experiment shows that the
 approximation algorithm is effective and efficient.
Journal: International Journal of Production Research 
Pages: 4081-4086 
Issue: 13 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1106610 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106610 
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Template-Type: ReDIF-Article 1.0
Author-Name: Saravanan Venkatachalam 
Author-X-Name-First: Saravanan 
Author-X-Name-Last: Venkatachalam 
Author-Name: Arunachalam Narayanan 
Author-X-Name-First: Arunachalam 
Author-X-Name-Last: Narayanan 
Title: Efficient formulation and heuristics for multi-item single source ordering problem with transportation cost 
Abstract:
 Integrated inventory and transportation decisions are critical in the
 supply chain, providing significant gains for all parties. In this paper,
 we present a mathematical formulation for the dynamic demand multi-item
 single source replenishment problem with a piecewise linear transportation
 cost. Through an extensive experimental study, we find that the new
 formulation provides a tighter LP relaxation of the problem, while
 requiring fewer computational resources to optimally solve the problem
 when compared with existing model in the literature. We also present a new
 metaheuristic for this general class of coordinated capacitated
 replenishment problems. On average, the solutions from heuristics are
 within 1.23% of the optimal solution for the comprehensive set of test
 problems.
Journal: International Journal of Production Research 
Pages: 4087-4103 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1088666 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1088666 
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Template-Type: ReDIF-Article 1.0
Author-Name: Gokula Vijaykumar Annamalai Vasantha 
Author-X-Name-First: Gokula Vijaykumar 
Author-X-Name-Last: Annamalai Vasantha 
Author-Name: Ananda Prasanna Jagadeesan 
Author-X-Name-First: Ananda Prasanna 
Author-X-Name-Last: Jagadeesan 
Author-Name: Jonathan Roy Corney 
Author-X-Name-First: Jonathan Roy 
Author-X-Name-Last: Corney 
Author-Name: Andrew Lynn 
Author-X-Name-First: Andrew 
Author-X-Name-Last: Lynn 
Author-Name: Anupam Agrawal 
Author-X-Name-First: Anupam 
Author-X-Name-Last: Agrawal 
Title: Crowdsourcing solutions to 2D irregular strip packing problems from Internet workers 
Abstract:
 Many industrial processes require the nesting of 2D profiles prior to the
 cutting, or stamping, of components from raw sheet material. Despite
 decades of sustained academic effort, algorithmic solutions are still
 sub-optimal and produce results that can frequently be improved by manual
 inspection. However, the Internet offers the prospect of novel
 &#x2018;human-in-the-loop&#x2019; approaches to nesting problems that uses
 online workers to produce packing efficiencies beyond the reach of current
 CAM packages. To investigate the feasibility of such an approach, this
 paper reports on the speed and efficiency of online workers engaged in the
 interactive nesting of six standard benchmark data-sets. To ensure the
 results accurately characterise the diverse educational and social
 backgrounds of the many different labour forces available online, the
 study has been conducted with subjects based in both Indian IT service
 (i.e. Rural BPOs) centres and a network of homeworkers in Northern
 Scotland. The results (i.e. time and packing efficiency) of the human
 workers are contrasted with both the baseline performance of a commercial
 CAM package and recent research results. The paper concludes that online
 workers could consistently achieve packing efficiencies roughly 4% higher
 than the commercial based-line established by the project. Beyond
 characterising the abilities of online workers to nest components, the
 results also make a contribution to the development of algorithmic
 solutions by reporting new solutions to the benchmark problems and
 demonstrating methods for assessing the packing strategy employed by the
 best workers.
Journal: International Journal of Production Research 
Pages: 4104-4125 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1102355 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1102355 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xianhao Xu 
Author-X-Name-First: Xianhao 
Author-X-Name-Last: Xu 
Author-Name: Bipan Zou 
Author-X-Name-First: Bipan 
Author-X-Name-Last: Zou 
Author-Name: Guwen Shen 
Author-X-Name-First: Guwen 
Author-X-Name-Last: Shen 
Author-Name: Yeming (Yale) Gong 
Author-X-Name-First: Yeming (Yale) 
Author-X-Name-Last: Gong 
Title: Travel-time models and fill-grade factor analysis for double-deep multi-aisle AS/RSs 
Abstract:
 Double-deep multi-aisle automated storage/retrieval systems are
 increasingly applied for storing and retrieving unit loads, with
 advantages of increased space utilisation, reduced number of aisles and
 improved efficiency of storage rack (S/R) machines. In such systems, the
 retrieval process may consist of the rearrangement of blocking loads,
 based on the assumptions of uniformly distributed storage locations and
 random storage policy. We formulate analytical travel-time models of both
 single- and dual-command cycles under three rearrangement rules. We
 validate the analytical travel-time models by simulation and conduct
 numerical experiments to analyse the effect of the number of aisles an S/R
 machine serves, the fill-grade factor and the command cycles on the
 expected travel time of the S/R machine. The results show that the
 expected travel time of the S/R machine is increasing with the increase in
 the number of aisles an S/R machine serves and the increase in the
 fill-grade factor, and dual command cycle outperforms single-command cycle
 in terms of cycle time. To deal with the trade-off between the storage
 space cost and the operational cost of the S/R machine, we develop a
 decision model for finding an optimal fill-grade factor to minimise the
 total cost. We find the condition when an optimal fill-grade factor exists
 and show how to calculate it. Based on the decision model, we compare the
 performance of double-deep multi-aisle automated storage/retrieval system
 (AS/RSs) and single-deep single-aisle AS/RSs. The results show that
 double-deep multi-aisle AS/RSs outperform single-deep single-aisle AS/RSs
 in terms of total cost, although double-deep multi-aisle AS/RSs need more
 storage locations.
Journal: International Journal of Production Research 
Pages: 4126-4144 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1106604 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106604 
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Template-Type: ReDIF-Article 1.0
Author-Name: Mirja Meyer 
Author-X-Name-First: Mirja 
Author-X-Name-Last: Meyer 
Author-Name: Marc-Thorsten H&#xfc;tt 
Author-X-Name-First: Marc-Thorsten 
Author-X-Name-Last: H&#xfc;tt 
Author-Name: Julia Bendul 
Author-X-Name-First: Julia 
Author-X-Name-Last: Bendul 
Title: The elementary flux modes of a manufacturing system: a novel approach to explore the relationship of network structure and function 
Abstract:
 Elementary flux modes (EFMs) are a concept from Systems Biology, where
 they serve as an indicator of component relevance in metabolic networks.
 An elementary flux mode is a functionally relevant, non-decomposable path
 through a given network. In this paper, we apply elementary flux mode
 analysis to manufacturing systems, with the aim of using the number of
 EFMs as a predictor for resource significance in the manufacturing system.
 For this, we formulate a network representation of a manufacturing
 process, which allows us to define the manufacturing equivalent of a
 stoichiometric matrix to draw an analogy between metabolic and
 manufacturing systems. This, in turn, allows the computation of EFMs,
 which we conduct in a case-study for a real manufacturing system. We
 further show that the change of EFMs under resource breakdown is a good
 indicator of the average order lateness in the manufacturing system. In
 this way, EFMs provide insight into the relationship of network structure
 and function in manufacturing.
Journal: International Journal of Production Research 
Pages: 4145-4160 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1106612 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106612 
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Template-Type: ReDIF-Article 1.0
Author-Name: Kaibo Wang 
Author-X-Name-First: Kaibo 
Author-X-Name-Last: Wang 
Author-Name: Wei Jiang 
Author-X-Name-First: Wei 
Author-X-Name-Last: Jiang 
Author-Name: Bo Li 
Author-X-Name-First: Bo 
Author-X-Name-Last: Li 
Title: A spatial variable selection method for monitoring product surface 
Abstract:
 Two-dimensional (2-D) data maps are generated in certain advanced
 manufacturing processes. Such maps contain rich information about process
 variation and product quality status. As a proven effective quality
 control technique, statistical process control (SPC) has been widely used
 in different processes for shift detection and assignable cause
 identification. However, charting algorithms for 2-D data maps are still
 vacant. This paper proposes a variable selection-based SPC method for
 monitoring 2-D wafer surface. The fused LASSO algorithm is firstly
 employed to identify potentially shifted sites on the surface; a charting
 statistic is then developed to detect statistically significant shifts. As
 the variable selection algorithm can nicely preserve shift patterns in
 spatial clusters, the newly proposed chart is proved to be both effective
 in detecting shifts and capable of providing diagnostic information for
 process improvement. Extensive Monte Carlo simulations and a real example
 have been used to demonstrate the effectiveness and usage of the proposed
 method.
Journal: International Journal of Production Research 
Pages: 4161-4181 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1109723 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1109723 
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Template-Type: ReDIF-Article 1.0
Author-Name: Saurabh Pratap 
Author-X-Name-First: Saurabh 
Author-X-Name-Last: Pratap 
Author-Name: Manoj Kumar B 
Author-X-Name-First: Manoj 
Author-X-Name-Last: Kumar B 
Author-Name: Divyanshu Saxena 
Author-X-Name-First: Divyanshu 
Author-X-Name-Last: Saxena 
Author-Name: M.K. Tiwari 
Author-X-Name-First: M.K. 
Author-X-Name-Last: Tiwari 
Title: Integrated scheduling of rake and stockyard management with ship berthing: a block based evolutionary algorithm 
Abstract:
 An integrated problem of optimising the operations at a commercial bulk
 material port terminal is studied in this paper. We simultaneously
 optimise the stockyard operations and rake schedule for outbound cargo, in
 conjunction with the arriving vessels and the status of the stockyards at
 the port. A mixed integer linear programming model for the problem is
 developed while incorporating the inherent complexities of the integrated
 model. To solve the real-life instances, two heuristic methods are
 proposed specifically for the considered problem. Firstly, genetic
 algorithm coupled with a greedy heuristic and later, block-based
 evolutionary algorithm (BBEA) is employed. After applying both techniques,
 we obtain the optimised schedule for loading of rakes and allotment of
 stockyard space for vessels as well as rakes at the terminal. Finally, we
 test the results of both models in three traffic scenarios between
 themselves and with real-life data from a port situated along the Eastern
 coast of India. The study resulted in significant reduction of turnaround
 time for rakes at the port terminal, which in turn lead to monetary
 savings. The model also automates the day to day operational
 decision-making at the port.
Journal: International Journal of Production Research 
Pages: 4182-4204 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1111535 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1111535 
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Template-Type: ReDIF-Article 1.0
Author-Name: Maksim Barketau 
Author-X-Name-First: Maksim 
Author-X-Name-Last: Barketau 
Author-Name: Erwin Pesch 
Author-X-Name-First: Erwin 
Author-X-Name-Last: Pesch 
Title: An approximation algorithm for a special case of the asymmetric travelling salesman problem 
Abstract:
 We consider the following optimisation problem that we encountered during
 the consolidation process of trains in a container transhipment terminal
 as well as in the intermediate storage of containers in sea ports in order
 to accelerate the loading and unloading of the vessels. There are
 <italic>n</italic> ordered pairs of points in the
 <italic>m</italic>-dimensional metric space: <inline-formula
 id="ILM0001"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1113327_ilm0001.gif"/></inline-formula>. The problem is
 to find a permutation <inline-formula id="ILM0002"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1113327_ilm0002.gif"/></inline-formula> of numbers
 <inline-formula id="ILM0003"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1113327_ilm0003.gif"/></inline-formula> minimising the
 function <inline-formula id="ILM0004"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1113327_ilm0004.gif"/></inline-formula> where
 <inline-formula id="ILM0005"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1113327_ilm0005.gif"/></inline-formula> is the metric
 of the space. The problem can be considered as a special case of the
 asymmetric travelling salesman problem. As for Euclidean, Manhattan and
 Chebyshev metric the problem is NP-hard (as a generalisation of the
 well-known TSP problem) we propose the simple approximation algorithm with
 the approximation guarantee equal to 3. The approximation guarantee is
 tight as will be shown by a sequence of instances for which the
 approximation ratio converges to 3.
Journal: International Journal of Production Research 
Pages: 4205-4212 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1113327 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1113327 
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Template-Type: ReDIF-Article 1.0
Author-Name: S.R. Patterson 
Author-X-Name-First: S.R. 
Author-X-Name-Last: Patterson 
Author-Name: E. Kozan 
Author-X-Name-First: E. 
Author-X-Name-Last: Kozan 
Author-Name: P. Hyland 
Author-X-Name-First: P. 
Author-X-Name-Last: Hyland 
Title: An integrated model of an open-pit coal mine: improving energy efficiency decisions 
Abstract:
 This article contributes an original integrated model of an open-pit coal
 mine for supporting energy-efficient decisions. Mixed integer linear
 programming is used to formulate a general integrated model of the
 operational energy consumption of four common open-pit coal mining
 subsystems: excavation and haulage, stockpiles, processing plants and belt
 conveyors. Mines are represented as connected instances of the four
 subsystems, in a flow sheet manner, which are then fitted to data provided
 by the mine operators. Solving the integrated model ensures the
 subsystems&#x2019; operations are synchronised and whole-of-mine energy
 efficiency is encouraged. An investigation on a case study of an open-pit
 coal mine is conducted to validate the proposed methodology. Opportunities
 are presented for using the model to aid energy-efficient decision-making
 at various levels of a mine, and future work to improve the approach is
 described.
Journal: International Journal of Production Research 
Pages: 4213-4227 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1117150 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1117150 
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Template-Type: ReDIF-Article 1.0
Author-Name: Francesco Lolli 
Author-X-Name-First: Francesco 
Author-X-Name-Last: Lolli 
Author-Name: Rita Gamberini 
Author-X-Name-First: Rita 
Author-X-Name-Last: Gamberini 
Author-Name: Claudio Giberti 
Author-X-Name-First: Claudio 
Author-X-Name-Last: Giberti 
Author-Name: Bianca Rimini 
Author-X-Name-First: Bianca 
Author-X-Name-Last: Rimini 
Author-Name: Federica Bondi 
Author-X-Name-First: Federica 
Author-X-Name-Last: Bondi 
Title: A simulative approach for evaluating alternative feeding scenarios in a kanban system 
Abstract:
 In accordance with the lean production philosophy, an assembly line may be
 supplied by means of a kanban system, which regulates and simplifies the
 flow of materials between the lines and the warehouses. This paper focuses
 on evaluation of feeding policies that differ from each other in term of
 the number of kanbans managed per feeding tour. A pure cost-based approach
 is thus proposed, which considers both inline inventories along with
 handling costs proportionate to the number of operators involved in the
 parts-feeding process. A multi-scenario simulative approach is applied in
 order to establish the number of operators required to avoid inline
 shortages. The scenario minimising total cost is then selected. The
 innovation introduced is a model for describing kanban arrivals and their
 requests for feeding, improving the potential of the simulation to
 describe real-life environments. Lastly, a case study from the automotive
 industry is presented in order to highlight the applicability of the
 proposed approach as well and the effects of alternative feeding policies
 on the total cost incurred.
Journal: International Journal of Production Research 
Pages: 4228-4239 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1117675 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1117675 
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Template-Type: ReDIF-Article 1.0
Author-Name: Chenjie Wang 
Author-X-Name-First: Chenjie 
Author-X-Name-Last: Wang 
Author-Name: Ningxuan Kang 
Author-X-Name-First: Ningxuan 
Author-X-Name-Last: Kang 
Author-Name: Li Zheng 
Author-X-Name-First: Li 
Author-X-Name-Last: Zheng 
Title: A factory-level dynamic operator allocation policy: the bubble allocation 
Abstract:
 In this paper, we propose a factory-level dynamic operator allocation
 policy called the bubble allocation policy. This policy is commonly
 implemented in labour-intensive industries in the presence of different
 operator speeds, high labour turnover, and learning effects. We prove the
 optimality of bubble allocation in several typical scenarios under
 deterministic and exponential processing time and different operator speed
 assumptions. When labour turnover and learning effects were considered,
 the effects of the bubble allocation were verified through simulation.
 Bubble allocation had a more significant positive effect on system
 throughput than the passive operator allocation policy. The positive
 effects of bubble allocation are enhanced with a larger production system
 scale (more parallel lines and more stations), higher turnover rate and
 slower learning process. Compared with active allocation policies such as
 work-sharing policy, bubble allocation policy has no requirements for
 additional cross-training and is not sensitive to the switching time of
 tasks. The bubble allocation policy stands out when the system is large
 and the flow line is designed in a balanced way.
Journal: International Journal of Production Research 
Pages: 4240-4255 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2015.1134841 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1134841 
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Moshref-Javadi 
Author-X-Name-First: Mohammad 
Author-X-Name-Last: Moshref-Javadi 
Author-Name: Mark R. Lehto 
Author-X-Name-First: Mark R. 
Author-X-Name-Last: Lehto 
Title: Material handling improvement in warehouses by parts clustering 
Abstract:
 A major part of warehouse operations is related to the collection of parts
 from the warehouse which is called the Order Picking Problem. To improve
 order picking operations, the total travel distance and generally picking
 time must be reduced. In this paper, a two-level approach is proposed that
 determines the locations of parts in the warehouse. The first step
 clusters parts into part families. Four different clustering methods based
 on principal component analysis, singular value decomposition and Two-Step
 Cluster Component are applied. In the second step, four different
 heuristics are proposed to determine the locations of parts. In addition
 to the minimisation of travel distance, we also consider the minimisation
 of the total congestion in aisles due to multiple workers. The proposed
 algorithms also consider the interactions between part families to
 minimise intergroup movements. As a result of the implementation, we
 achieved more than 40% reduction in material handling compared to the
 current set-up of the warehouse. The applied algorithms can easily be
 modified to be used for warehouses with different configurations. The
 algorithms utilised in this case study can be helpful to researchers to
 become familiar with new heuristics, as well as practitioners to design
 improved warehouses.
Journal: International Journal of Production Research 
Pages: 4256-4271 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1140916 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1140916 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: X.Q. Zuo 
Author-X-Name-First: X.Q. 
Author-X-Name-Last: Zuo 
Author-Name: C.C. Murray 
Author-X-Name-First: C.C. 
Author-X-Name-Last: Murray 
Author-Name: A.E. Smith 
Author-X-Name-First: A.E. 
Author-X-Name-Last: Smith 
Title: Sharing clearances to improve machine layout 
Abstract:
 This paper considers a double-row layout problem with shared clearances in
 the context of semiconductor manufacturing. By sharing some clearances,
 reductions in both layout area and material handling cost of approximately
 7--10% are achieved. Along with minimal clearances for separating adjacent
 machines, clearances that can be shared by adjacent machines are
 considered. The shared clearances may be located on either or both sides
 of machines. A mixed integer linear programming formulation of this
 problem is established, with the objective to minimise both material flow
 cost and layout area. A hybrid approach combining multi-objective tabu
 search and heuristic rules is proposed to solve it. Computational results
 show that the hybrid approach is very effective for this problem and finds
 machine layouts with reduced areas and handling costs by exploiting shared
 clearances.
Journal: International Journal of Production Research 
Pages: 4272-4285 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1142134 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1142134 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Riccardo Manzini 
Author-X-Name-First: Riccardo 
Author-X-Name-Last: Manzini 
Author-Name: Riccardo Accorsi 
Author-X-Name-First: Riccardo 
Author-X-Name-Last: Accorsi 
Author-Name: Giulia Baruffaldi 
Author-X-Name-First: Giulia 
Author-X-Name-Last: Baruffaldi 
Author-Name: Teresa Cennerazzo 
Author-X-Name-First: Teresa 
Author-X-Name-Last: Cennerazzo 
Author-Name: Mauro Gamberi 
Author-X-Name-First: Mauro 
Author-X-Name-Last: Gamberi 
Title: Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS) 
Abstract:
 Autonomous vehicle storage and retrieval systems use vehicles that move
 horizontally along rails within the storage racks, while vertical
 movements are provided by lifts. The solution proposed in this paper
 addresses a particular system configuration that works with multiple deep
 storage lanes that are widely used in the food and beverage industry,
 characterised by large volumes of products of limited variety. The generic
 deep lane is single item, i.e. one stock keeping unit, and single batch,
 i.e. one production lot, thereby affecting the performance of the system
 in terms of storage capacity utilisation and throughput. Determining the
 number and depth of the lanes is crucial to aid the design and control of
 such a storage system. The aim of this paper was to support the design of
 AVS/RSs though a set of original analytic models for the determination of
 the travelled distance and time for single-command and dual-command cycles
 given alternative layout configurations. The models are validated by
 simulation and exemplified with a real-warehousing case study. The paper
 presents useful guidelines for the configuration of the system layout
 including the determination of the optimal shape ratio and the length of
 the lanes.
Journal: International Journal of Production Research 
Pages: 4286-4304 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1144241 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1144241 
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Template-Type: ReDIF-Article 1.0
Author-Name: Rakesh Venkitasubramony 
Author-X-Name-First: Rakesh 
Author-X-Name-Last: Venkitasubramony 
Author-Name: Gajendra K. Adil 
Author-X-Name-First: Gajendra K. 
Author-X-Name-Last: Adil 
Title: Analytical models for pick distances in fishbone warehouse based on exact distance contour 
Abstract:
 The pick distance models for a unit load warehouse employing fishbone
 layout conventionally use semicircular approximation for distance contour
 which can result in significant error. This paper develops discrete and
 continuous pick distance models for fishbone layout under random, full
 turnover, and class-based storage policies based on exact polygonal
 distance contour. Class-based storage policy with three classes was found
 to give pick distance comparable to full turnover policy over a range of
 demand skews and warehouse shapes studied. The discrete and continuous
 models are compared considering finite storage space, aisle width and
 discontinues in the ABC curve for a real life data. The sensitivity of
 warehouse performance over a range of warehouse parameters is studied. We
 also outline a methodology for class-based storage design where class
 partitions can be derived for a warehouse of any dimension from the
 results of a unit area warehouse.
Journal: International Journal of Production Research 
Pages: 4305-4326 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1148277 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1148277 
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Template-Type: ReDIF-Article 1.0
Author-Name: Byung-In Kim 
Author-X-Name-First: Byung-In 
Author-X-Name-Last: Kim 
Author-Name: Youngmin Ki 
Author-X-Name-First: Youngmin 
Author-X-Name-Last: Ki 
Author-Name: Donghee Son 
Author-X-Name-First: Donghee 
Author-X-Name-Last: Son 
Author-Name: Byungjoo Bae 
Author-X-Name-First: Byungjoo 
Author-X-Name-Last: Bae 
Author-Name: Jun-Seo Park 
Author-X-Name-First: Jun-Seo 
Author-X-Name-Last: Park 
Title: An algorithm for a cutting problem in window frame production 
Abstract:
 This research discusses the cutting problem encountered by a real-life
 window frame manufacturer. In the problem, four types of bars (upper,
 bottom, left and right) should be cut from raw material aluminium profiles
 for each window frame order. These bars must be cut such that trim loss is
 minimised. Moreover, the bars should be assigned to the same raw material
 profile if possible to increase productivity; otherwise, they should be
 assigned to neighbouring raw material profiles. Furthermore, the numbers
 of bar types as derived from a raw material profile should not be
 unbalanced because this scenario induces subsequent machine load
 imbalance. In this study, we develop a mixed integer programming model and
 a knapsack-based heuristic approach that minimises the weighted sum of
 trim loss, bar type imbalance and the degree of order spreading. The
 results of computational experiments demonstrate the effectiveness of the
 proposed algorithm, and the proposed approach outperforms the legacy
 system of the company. Thus, this method is currently being used by the
 firm in question.
Journal: International Journal of Production Research 
Pages: 4327-4339 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1148279 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1148279 
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Template-Type: ReDIF-Article 1.0
Author-Name: M. &#xc7;elik 
Author-X-Name-First: M. 
Author-X-Name-Last: &#xc7;elik 
Author-Name: H. S&#xfc;ral 
Author-X-Name-First: H. 
Author-X-Name-Last: S&#xfc;ral 
Title: Order picking in a parallel-aisle warehouse with turn penalties 
Abstract:
 In many real-life routing problems, incorporating the negative effects of
 turns is an important, but often overlooked aspect. This is especially
 true for order picking in warehouses, where making the turns not only
 decreases the picking efficiency by reducing the speed of the vehicle, but
 it also results in other unquantifiable effects such as vehicle tipovers,
 increased congestion and increased risk of collision with pedestrians or
 other vehicles. In this paper, we consider the order picking problem in a
 parallel-aisle warehouse by taking into account the number and effect of
 the turns. In particular, we show that the problem of minimising the
 number of turns, minimising travel time under turn penalties, the
 biobjective problem that involves turn and travel time minimisation as
 separate objectives, and the triobjective problem with U-turn minimisation
 as a third objective can all be solved in polynomial time. Our
 computational results show that the algorithms we develop can generate the
 corresponding Pareto front very quickly, and significantly outperform
 heuristic approaches used in practice.
Journal: International Journal of Production Research 
Pages: 4340-4355 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1154624 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154624 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Barry R. Cobb 
Author-X-Name-First: Barry R. 
Author-X-Name-Last: Cobb 
Title: Estimating cycle time and return rate distributions for returnable transport items 
Abstract:
 A return rate distribution for returnable transport items (RTI) is
 estimated from radio frequency identification (RFID) data. The technique
 is dependent on estimating a probability density function for backward
 fill-to-fill cycle times for the returnable containers. The cycle time
 distribution yields an estimate of a time period where most containers
 will return to the manufacturer. To obtain return rate observations, the
 number of returns in a production lot is observed by tracking the fill and
 return of uniquely tagged containers over this time period, adjusting for
 containers with long cycle times. The process also gives an estimate of
 the percentage of RTI tagged in the population or fleet of containers. The
 effects of estimation errors due to a partial RFID-tagging of the fleet
 are examined, and satisfactory results can be obtained when not all
 containers are tagged. The use of the cycle time and return rate
 distributions for creating a forecast of container returns is illustrated,
 and implementation of cycle time and return rate as indicators of supply
 chain performance is discussed.
Journal: International Journal of Production Research 
Pages: 4356-4367 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1162920 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1162920 
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Template-Type: ReDIF-Article 1.0
Author-Name: J.H. Ruan 
Author-X-Name-First: J.H. 
Author-X-Name-Last: Ruan 
Author-Name: X.P. Wang 
Author-X-Name-First: X.P. 
Author-X-Name-Last: Wang 
Author-Name: F.T.S. Chan 
Author-X-Name-First: F.T.S. 
Author-X-Name-Last: Chan 
Author-Name: Y. Shi 
Author-X-Name-First: Y. 
Author-X-Name-Last: Shi 
Title: Optimizing the intermodal transportation of emergency medical supplies using balanced fuzzy clustering 
Abstract:
 In this paper, we are concerned with the problem of the
 &#x2018;helicopters and vehicles&#x2019; intermodal transportation of
 medical supplies in response to large-scale disasters. To deal with the
 disadvantages of the use of classic Fuzzy C-Means (FCM) in the intermodal
 transportation optimization, two balanced FCM methods, i.e. FCM with
 capacity constraints and FCM with number constraints, are formulated to
 select emergency distribution centers (EDCs) and assign medical aid
 points, which could construct balanced &#x2018;helicopters and
 vehicles&#x2019; intermodal transportation network. Then, considering
 helicopter travel time, transfer time and vehicle delivery time, a
 clustering-based intermodal routes optimization model is presented to
 produce intermodal transportation routes. Numerical experiments are
 presented to show the effectiveness and advantage of the developed
 approach, and observe the impact of number of EDCs and transfer efficiency
 at EDCs on the performance of intermodal transportation. This paper could
 provide methodological and operational supports for the
 &#x2018;helicopters and vehicles&#x2019; intermodal transportation of
 medical supplies in response to large-scale disasters.
Journal: International Journal of Production Research 
Pages: 4368-4386 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1174344 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1174344 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Liangliang Jin 
Author-X-Name-First: Liangliang 
Author-X-Name-Last: Jin 
Author-Name: Qiuhua Tang 
Author-X-Name-First: Qiuhua 
Author-X-Name-Last: Tang 
Author-Name: Chaoyong Zhang 
Author-X-Name-First: Chaoyong 
Author-X-Name-Last: Zhang 
Author-Name: Xinyu Shao 
Author-X-Name-First: Xinyu 
Author-X-Name-Last: Shao 
Author-Name: Guangdong Tian 
Author-X-Name-First: Guangdong 
Author-X-Name-Last: Tian 
Title: More MILP models for integrated process planning and scheduling 
Abstract:
 The integration of process planning and scheduling is important for an
 efficient utilisation of manufacturing resources. In general, there are
 two types of models for this problem. Although some MILP models have been
 reported, most existing models belong to the first type and they cannot
 realise a true integration of process planning and scheduling. Especially,
 they are completely powerless to deal with the cases where jobs are
 expressed by network graphs because generating all the process plans from
 a network graph is difficult and inefficient. The network graph-specific
 models belong to the other type, and they have seldom been deliberated on.
 In this research, some novel MILP models for integrated process planning
 and scheduling in a job shop flexible manufacturing system are developed.
 By introducing some network graph-oriented constraints to accommodate
 different operation permutations, the proposed models are able to express
 and utilise flexibilities contained in network graphs, and hence have the
 power to solve network graph-based instances. The established models have
 been tested on typical test bed instances to verify their correctness.
 Computational results show that this research achieves the anticipant
 purpose: the proposed models are capable of solving network graph-based
 instances.
Journal: International Journal of Production Research 
Pages: 4387-4402 
Issue: 14 
Volume: 54 
Year: 2016 
Month: 7 
X-DOI: 10.1080/00207543.2016.1140917 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1140917 
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Template-Type: ReDIF-Article 1.0
Author-Name: J.R.S. Dias 
Author-X-Name-First: J.R.S. 
Author-X-Name-Last: Dias 
Author-Name: C.A. Maia 
Author-X-Name-First: C.A. 
Author-X-Name-Last: Maia 
Author-Name: V.F. Lucena 
Author-X-Name-First: V.F. 
Author-X-Name-Last: Lucena 
Title: Synchronising operations on productive systems modelled by timed event graphs 
Abstract:
 This study considers the synchronisation of events modelled by graphs of
 timed event systems. The start and finish points of events are indicated
 by the firing of transitions in the system. Synchronising the firing of
 these transitions control events, which are activities within a
 manufacturing system. Synchronisation is achieved by controlling the
 inflow of raw materials into the system. A feedback controller is proposed
 to control the flow of incoming feedstock. The controller parameters are
 calculated. Delays are applied to the input supply and the production rate
 is established when the control of the synchronisation constraints is
 satisfied. The proposed method ensures that the system control operates
 according to the control strategy of &#x2018;just-in-time&#x2019;
 production planning.
Journal: International Journal of Production Research 
Pages: 4403-4417 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1041573 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1041573 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Vahab Moradinaftchali 
Author-X-Name-First: Vahab 
Author-X-Name-Last: Moradinaftchali 
Author-Name: Xiaoguang Wang 
Author-X-Name-First: Xiaoguang 
Author-X-Name-Last: Wang 
Author-Name: Lixin Song 
Author-X-Name-First: Lixin 
Author-X-Name-Last: Song 
Title: Enhancement in quality and productivity: a riskless approach based on optimum selection of tolerance and improvement strategies 
Abstract:
 The need of higher quality products from the customers and the tendency of
 industries to quality improvement for maintaining their competitive
 position over the long run are the main motives of using improvement
 methodologies. However, any use of improvement methodology besides its
 additional costs will also change the total variability of the process.
 Changes in total variability will affect the optimal value of tolerance as
 well as the quality of the product. Therefore, one of the main concerns of
 the producers is to find an effective way to manufacture their goods in a
 manner that reduces the production costs and gains customers&#x2019;
 satisfaction. To meet these goals, this study introduces an algorithm to
 propose a riskless approach of improvement that results in the maximum
 amount of net savings. It is shown that using appropriate improvement
 strategies simultaneous with a proper selection of tolerance have an
 important impact to enhance productivity and quality.
Journal: International Journal of Production Research 
Pages: 4418-4429 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1055346 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055346 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Nur Ainunnazli Binti Aminuddin 
Author-X-Name-First: Nur Ainunnazli 
Author-X-Name-Last: Binti Aminuddin 
Author-Name: Jose Arturo Garza-Reyes 
Author-X-Name-First: Jose Arturo 
Author-X-Name-Last: Garza-Reyes 
Author-Name: Vikas Kumar 
Author-X-Name-First: Vikas 
Author-X-Name-Last: Kumar 
Author-Name: Jiju Antony 
Author-X-Name-First: Jiju 
Author-X-Name-Last: Antony 
Author-Name: Luis Rocha-Lona 
Author-X-Name-First: Luis 
Author-X-Name-Last: Rocha-Lona 
Title: An analysis of managerial factors affecting the implementation and use of overall equipment effectiveness 
Abstract:
 To ensure manufacturing organisations remain competitive, most of them are
 turning to total productive maintenance (TPM) and lean manufacturing to
 ensure seamless operations. Overall equipment effectiveness (OEE) is the
 foundation of these two business improvement strategies as it tackles the
 underlying losses that impede equipment efficiency. This study presents
 the prevalence of managerial issues related to the implementation and use
 of OEE in the manufacturing industry. To do this, five hypotheses and four
 research questions were formulated and tested using a combination of
 descriptive statistics and cross-tabulation, chi-square, analysis of
 variance, Tukey&#x2019;s pairwise comparison, <italic>Z</italic>-test and
 correlation tests. Data were collected through a survey questionnaire
 responded by 139 manufacturing organisations worldwide. The results
 establish, among other &#x2018;soft&#x2019; aspects, the linkage of the
 OEE implementation with that of TPM and lean manufacturing, and the
 drivers, most critical factors, barriers and the role of management in its
 implementation. The study also identifies how manufacturing organisations
 employ the information provided by OEE and how the data for its
 computation are collected. This study supports the very limited empirical
 research on the implementation and use of OEE. Thus, this research
 provides organisations, and their managers, with a better understanding of
 different factors that affect the successful deployment and management of
 this highly used measure in industry.
Journal: International Journal of Production Research 
Pages: 4430-4447 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1055849 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055849 
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Bo Zhou 
Author-X-Name-First: Bo 
Author-X-Name-Last: Zhou 
Author-Name: Jibin Zhao 
Author-X-Name-First: Jibin 
Author-X-Name-Last: Zhao 
Author-Name: Lun Li 
Author-X-Name-First: Lun 
Author-X-Name-Last: Li 
Author-Name: Renbo Xia 
Author-X-Name-First: Renbo 
Author-X-Name-Last: Xia 
Title: NURBS curve interpolation algorithm based on tool radius compensation method 
Abstract:
 This paper focuses on developing an algorithm that can generate toolpaths
 in NURBS form for smooth, high speed and accurate machining. The initial
 toolpaths are obtained by tool radius compensation method which is based
 on the workpiece boundary offsetting. According to different lengths and
 the continuous short block (CSB) criterion, these offset linear segments
 can be regarded as CSBs or long straight segments. Junctions are located
 where the curvature value is greater than the preset curvature threshold
 value or where it changes abruptly, or at the two end points of any long
 straight segment. During machining, the NURBS fitting module first looks
 ahead several CSBs and converts them into parametric curves in real time.
 During the conversion, continuities of the position, slope or even
 curvature at the transition of the parametric curves and unfitted line
 segments can be guaranteed. Then the acceleration/deceleration
 feedrate-planning scheme is proposed to determine the transition feedrate
 at the junction between the fitted curves and unfitted long straight
 segments, and the corner feedrate within the fitted curve. Simulations and
 experiments show that the proposed algorithm can significantly improve
 machining accuracy and reduce cutting time to satisfy today&#x2019;s
 high-speed and high-accurate machining requirements.
Journal: International Journal of Production Research 
Pages: 4448-4474 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1062933 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1062933 
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Template-Type: ReDIF-Article 1.0
Author-Name: Giulio Barbato 
Author-X-Name-First: Giulio 
Author-X-Name-Last: Barbato 
Author-Name: Paolo Chiabert 
Author-X-Name-First: Paolo 
Author-X-Name-Last: Chiabert 
Author-Name: Gianluca D&#x2019;Antonio 
Author-X-Name-First: Gianluca 
Author-X-Name-Last: D&#x2019;Antonio 
Author-Name: Manuela De Maddis 
Author-X-Name-First: Manuela 
Author-X-Name-Last: De Maddis 
Author-Name: Franco Lombardi 
Author-X-Name-First: Franco 
Author-X-Name-Last: Lombardi 
Author-Name: Suela Ruffa 
Author-X-Name-First: Suela 
Author-X-Name-Last: Ruffa 
Title: Method for automatic alignment recovery of a spur gear 
Abstract:
 This paper deals with the development of an online methodology for the
 automatic control and alignment of spur gears. The proposed methodology
 works on a set of points acquired on the workpiece surfaces by means of a
 manufacturing machine equipped with a set of sensors for dimensional
 measurements. A mathematical algorithm is developed to correct the
 position of the gear; it constitutes the main part of the developed
 monitoring and control system: it is able to real-time analyse the
 collected data of each measure and provide the orientation parameters that
 minimise the residual positioning errors. The methodology is first tested
 on simulated data-sets and the final workpiece configuration exhibits a
 good reproducibility. The tests executed on real data, acquired both
 through a coordinate measuring machine and the sensor system integrated
 into the manufacturing machine, confirm this result. The employment of
 this automation system allows to shorten the time necessary for the
 alignment process and improves the precision of the final positioning,
 leading to enhanced quality of the products and higher process
 flexibility, compared to the currently employed manual operation.
Journal: International Journal of Production Research 
Pages: 4475-4486 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1064180 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064180 
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Template-Type: ReDIF-Article 1.0
Author-Name: Seung-Jun Shin 
Author-X-Name-First: Seung-Jun 
Author-X-Name-Last: Shin 
Author-Name: Jungyub Woo 
Author-X-Name-First: Jungyub 
Author-X-Name-Last: Woo 
Author-Name: Duck Bong Kim 
Author-X-Name-First: Duck Bong 
Author-X-Name-Last: Kim 
Author-Name: Senthilkumaran Kumaraguru 
Author-X-Name-First: Senthilkumaran 
Author-X-Name-Last: Kumaraguru 
Author-Name: Sudarsan Rachuri 
Author-X-Name-First: Sudarsan 
Author-X-Name-Last: Rachuri 
Title: Developing a virtual machining model to generate MTConnect machine-monitoring data from STEP-NC 
Abstract:
 The ability to predict performance of manufacturing equipment during early
 stages of process planning is vital for improving efficiency of
 manufacturing processes. In the metal cutting industry, measurement of
 machining performance is usually carried out by collecting
 machine-monitoring data that record the machine tool&#x2019;s actions
 (e.g. coordinates of axis location and power consumption). Understanding
 the impacts of process planning decisions is central to the enhancement of
 the machining performance. However, current methodologies lack the
 necessary models and tools to predict impacts of process planning
 decisions on the machining performance. This paper presents the
 development of a virtual machining model (called <italic>STEP2M</italic>
 model) that generates machine-monitoring data from process planning data.
 The <italic>STEP2M</italic> model builds upon a physical model-based
 analysis for the sources of energy on a machine tool, and adopts STEP-NC
 and MTConnect standardised interfaces to represent process planning and
 machine-monitoring data. We have developed a prototype system for 2-axis
 turning operation and validated the system by conducting an experiment
 using a Computer Numerical Control lathe. The virtual machining model
 presented in this paper enables process planners to analyse machining
 performance through virtual measurement and to perform interoperable data
 communication through standardised interfaces.
Journal: International Journal of Production Research 
Pages: 4487-4505 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1064182 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064182 
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Template-Type: ReDIF-Article 1.0
Author-Name: Thawani Mpatama Sanjika 
Author-X-Name-First: Thawani Mpatama 
Author-X-Name-Last: Sanjika 
Author-Name: Carel Nicoolas Bezuidenhout 
Author-X-Name-First: Carel Nicoolas 
Author-X-Name-Last: Bezuidenhout 
Title: A primary influence vertex approach to identify driving factors in complex integrated agri-industrial systems -- an example from sugarcane supply and processing systems 
Abstract:
 Integrated agri-industrial systems (IAISs), such as sugarcane supply and
 processing systems, are complex systems and hence generally difficult to
 understand and manage. The large number factors in IAISs coupled with the
 complex interrelationships among the factors make it challenging to
 identify the points of intervention for improving their overall
 performance. Several approaches, such as the network theory and the Theory
 of Constraints have been used to identify important factors in systems
 with variations in success. This paper demonstrates a primary influence
 vertex approach for identifying and ranking the factors that drive the
 performance of IAISs. The approach is based on comprehensive causal
 network analyses and was tested in four relatively diverse large-scale
 sugarcane milling operations in South Africa. Results from the analyses
 were found to be consistent with the literature and external knowledge of
 the milling areas as at the time of the study. It is concluded that the
 approach can proffer a sound basis from which deeper rooted problems in
 systems can be identified on an ongoing basis. It is, however, recommended
 that the approach should be systematically compared with other relevant
 methods that are used to analyse complex systems.
Journal: International Journal of Production Research 
Pages: 4506-4519 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1064552 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064552 
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Template-Type: ReDIF-Article 1.0
Author-Name: Satish Tyagi 
Author-X-Name-First: Satish 
Author-X-Name-Last: Tyagi 
Title: An improved fuzzy-AHP (IFAHP) approach to compare SECI modes 
Abstract:
 Mental models and knowledge base of an employee are two key resources of
 an organisation that are imperative to develop innovative products.
 Effective utilisation of socialisation (S), externalisation (E),
 combination (C) and internalisation (I) modes within any product
 development (PD) phase plays an important role in creating new knowledge
 and updating the mental models. In order to investigate the influence of
 SECI modes on a specific PD phase, an improved fuzzy analytical hierarchy
 process approach is presented. In simple fuzzy analytical hierarchy
 process, the numbers are either normalised or a zero value is assigned to
 the degree of possibility when two triangles are not intersecting with
 each other. This approach calculates distorted values of degree of
 possibility and thus very likely produces false ranking of alternatives.
 The article proposes to extend the triangle edges about
 <italic>x</italic>-axis until they intersect when the pessimistic value of
 one triangle is more than the optimistic value of other triangle. It
 allows developing a mathematical formulation to estimate the true values
 of degree of possibility instead of zero. An example of conceptual design
 phase is discussed to illustrate the applicability and usefulness of
 proposed framework. In order to evaluate the performance of underlying
 phase in terms of knowledge creation, five criteria are selected based on
 the literature search and discussion with subject matter experts from
 strategic decision areas. After stringent analysis and exhaustive
 experimentation, it is found that internalisation mode highly influences
 the conceptual design phase.
Journal: International Journal of Production Research 
Pages: 4520-4536 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1067378 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1067378 
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Template-Type: ReDIF-Article 1.0
Author-Name: YaoAn Lu 
Author-X-Name-First: YaoAn 
Author-X-Name-Last: Lu 
Author-Name: Ye Ding 
Author-X-Name-First: Ye 
Author-X-Name-Last: Ding 
Author-Name: LiMin Zhu 
Author-X-Name-First: LiMin 
Author-X-Name-Last: Zhu 
Title: Simultaneous optimization of the feed direction and tool orientation in five-axis flat-end milling 
Abstract:
 The two additional rotational motions of five-axis machining make the
 determination of the optimal feed direction and tool orientation a
 challenging task. A new model to find the optimal feed direction and tool
 orientation maximising the machining width and avoiding local gouging at a
 cutter contact (CC) point with a flat-end cutter considering the tool path
 smoothness requirement is developed in this paper. The machining error is
 characterised by a signed distance function defined from a point on the
 bottom tool circle of the cutter to the design surface. With the help of
 the differential evolution approach, the optimisation model can be
 resolved to determine the optimal tool orientation and feed direction at a
 given CC point, and generate the smooth tool paths following the optimal
 feed direction. Simulation examples demonstrate the developed techniques
 can improve the tool orientation and feed direction at a CC point to
 increase the machining width, improving the efficiency of freeform surface
 machining.
Journal: International Journal of Production Research 
Pages: 4537-4546 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1070973 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1070973 
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Template-Type: ReDIF-Article 1.0
Author-Name: Paulo Sergio Gon&#xe7;alves de Oliveira 
Author-X-Name-First: Paulo Sergio Gon&#xe7;alves de 
Author-X-Name-Last: Oliveira 
Author-Name: Dirceu da Silva 
Author-X-Name-First: Dirceu da 
Author-X-Name-Last: Silva 
Author-Name: Luciano Ferreira da Silva 
Author-X-Name-First: Luciano Ferreira da 
Author-X-Name-Last: Silva 
Author-Name: Meire dos Santos Lopes 
Author-X-Name-First: Meire dos Santos 
Author-X-Name-Last: Lopes 
Author-Name: Andr&#xe9;Luis Helleno 
Author-X-Name-First: Andr&#xe9;Luis 
Author-X-Name-Last: Helleno 
Title: Factors that influence product life cycle management to develop greener products in the mechanical industry 
Abstract:
 Our aim was to discover the most important factors that influence the
 development of greener products in the mechanical industry, emphasising
 green design in product creation based on current environmental issues and
 considering product development as one important aspect of product life
 cycle management. This model is important to the mechanical industry
 because this sector relies heavily on raw materials, and recycling
 products is one way to improve environmental conditions. We used
 exploratory factor analyses to assess new product development,
 communication in change management, concurrent engineering, green products
 design worries and supplier involvement risks perception. The factor
 analyses initially found 10 constructs, but the 10th was eliminated
 because it had only one variable, and 5 were eliminated because they
 yielded Cronbach&#x2019;s alpha values less than 0.6. To develop this
 model, we sent questionnaires to 2000 professionals in the Brazilian
 mechanical industry through LinkedIn discussion groups, mostly to
 professionals who participated in product development and was received 405
 answered questionnaires which 394 was considered valid. The results show
 the importance of consistently managing product development throughout the
 entire product life cycle. This includes aspects such as product
 recycling, green products and using materials that are easy to recycle,
 from the very beginning of product design.
Journal: International Journal of Production Research 
Pages: 4547-4567 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1071893 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1071893 
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Manikas 
Author-X-Name-First: Andrew 
Author-X-Name-Last: Manikas 
Author-Name: James Kroes 
Author-X-Name-First: James 
Author-X-Name-Last: Kroes 
Title: Improved forward buying of commodity materials 
Abstract:
 This research presents the Enhanced Commodity Forward Buy (ECFB)
 heuristic, a new method for commodity purchasing, which allows strategic
 forward buying of commodities for products that include commodity
 components or materials. The ECFB addresses limitations of existing
 methods by considering stochastic demand and stochastic commodity prices
 for products that contain both commodity and non-commodity materials. We
 conduct a simulation test of the new heuristic on 10 commodity indices
 using actual historical market prices, over a range of holding costs,
 markup margins, commodity percentages of the product&#x2019;s cost of
 goods sold and demand distributions. The results of the simulation show
 that compared with five other buying methods, the ECFB heuristic&#x2019;s
 ability to adapt to variations in both demand and commodity prices allows
 it to generate higher profits when demand is uncertain and commodity
 prices are volatile.
Journal: International Journal of Production Research 
Pages: 4568-4583 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1083627 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1083627 
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Template-Type: ReDIF-Article 1.0
Author-Name: A. Sanz-Lobera 
Author-X-Name-First: A. 
Author-X-Name-Last: Sanz-Lobera 
Author-Name: Emilio G&#xf3;mez 
Author-X-Name-First: Emilio 
Author-X-Name-Last: G&#xf3;mez 
Author-Name: Jes&#xfa;s P&#xe9;rez 
Author-X-Name-First: Jes&#xfa;s 
Author-X-Name-Last: P&#xe9;rez 
Author-Name: Lorenzo Sevilla 
Author-X-Name-First: Lorenzo 
Author-X-Name-Last: Sevilla 
Title: A proposal of cost-tolerance models directly collected from the manufacturing process 
Abstract:
 In this paper, the concept of cost-tolerance functions based on data
 directly obtained from the manufacturing process is proposed. Traditional
 models used in manufacturing field define cost-tolerance relationships
 from mathematical functions whose relationship with the process is not
 usually set in a clear way. In this work, proposed models allow to obtain
 cost-tolerance functions directly from parameters measured on
 manufacturing process. The paper defines some of these functions using
 statistical distributions derived from the population of manufactured
 parts. A general methodology to reach a cost-tolerance function from any
 distribution of the manufactured parts is proposed. Once functions are
 defined, an application example is presented. Finally, the main criteria
 for suitable appropriateness use of models are established.
Journal: International Journal of Production Research 
Pages: 4584-4598 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1086036 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1086036 
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Template-Type: ReDIF-Article 1.0
Author-Name: Ren-Zi Yang 
Author-X-Name-First: Ren-Zi 
Author-X-Name-Last: Yang 
Author-Name: Hong-Sen Yan 
Author-X-Name-First: Hong-Sen 
Author-X-Name-Last: Yan 
Author-Name: Li-Li Zhu 
Author-X-Name-First: Li-Li 
Author-X-Name-Last: Zhu 
Title: The retrieval method of KMS knowledge meshes by complexity analysis 
Abstract:
 Knowledgeable manufacturing system (KMS) transforms all types of advanced
 manufacturing modes into corresponding knowledge meshes (KMs) and selects
 the best combination of KMs to satisfy enterprise requirements.
 Efficiently retrieving and reconfiguring KMs can reduce the complexity of
 new KMs gained by self-reconfiguration operations and enhance its
 practicability. This paper presents the method for measuring the KM
 complexity based on entropy and that for fuzzily classifying and
 retrieving for KMs based on granularity. Utilising the intrinsic
 information of KM, knowledge capacity function based on entropy is
 introduced to measure the KM complexity, and proved to be a monotone
 function of the number, measure, coefficient and weight of elements in KM.
 Properties of the KM operations are kept. Taking quality, quantity and
 complexity into account, the similarity function is defined. As revealed
 by our analysis, this function is of similarity both in the sense of
 matching, and in the mode of gaining KM. Then, the KMs in the KM base are
 fuzzily clustered. The number of classes is not fixed in advance, but can
 be dynamically adjusted. Each clustering centre is the best state
 corresponding to certain demands and has the minimum complexity degree. KM
 features are quantised in importance using the weight vectors. The search
 space is determined by centring at the clustering, which converts the
 problem from fine-grained space to coarse-grained space. Our tests and
 software package developed have proved the method to be quite effective.
Journal: International Journal of Production Research 
Pages: 4599-4616 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1090641 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1090641 
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Template-Type: ReDIF-Article 1.0
Author-Name: L.S. Dharmasena 
Author-X-Name-First: L.S. 
Author-X-Name-Last: Dharmasena 
Author-Name: P. Zeephongsekul 
Author-X-Name-First: P. 
Author-X-Name-Last: Zeephongsekul 
Title: A new process capability index for multiple quality characteristics based on principal components 
Abstract:
 This paper presents a new multivariate process capability index (MPCI)
 which is based on the principal component analysis (PCA) and is dependent
 on a parameter <inline-formula id="ILM0001"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1091520_ilm0001.gif"/></inline-formula> which can take
 on any real number. This MPCI generalises some existing multivariate
 indices based on PCA proposed by several authors when <inline-formula
 id="ILM0002"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1091520_ilm0002.gif"/></inline-formula> or
 <inline-formula id="ILM0003"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1091520_ilm0003.gif"/></inline-formula>. One of the key
 contributions of this paper is to show that there is a direct
 correspondence between this MPCI and process yield for a unique value of
 <inline-formula id="ILM0004"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1091520_ilm0004.gif"/></inline-formula>. This result is
 used to establish a relationship between the capability status of the
 process and to show that under some mild conditions, the estimators of
 this MPCI is consistent and converge to a normal distribution. This is
 then applied to perform tests of statistical hypotheses and in determining
 sample sizes. Several numerical examples are presented with the objective
 of illustrating the procedures and demonstrating how they can be applied
 to determine the viability and capacity of different manufacturing
 processes.
Journal: International Journal of Production Research 
Pages: 4617-4633 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1091520 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1091520 
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Template-Type: ReDIF-Article 1.0
Author-Name: Murat Uzam 
Author-X-Name-First: Murat 
Author-X-Name-Last: Uzam 
Author-Name: Zhiwu Li 
Author-X-Name-First: Zhiwu 
Author-X-Name-Last: Li 
Author-Name: Umar Suleiman Abubakar 
Author-X-Name-First: Umar Suleiman 
Author-X-Name-Last: Abubakar 
Title: Think globally act locally approach for the synthesis of a liveness-enforcing supervisor of FMSs based on Petri nets 
Abstract:
 This paper, by using Petri nets (PNs), reports a general approach, called
 a think globally, act locally (TGAL) method, to compute liveness-enforcing
 supervisors (LES) for flexible manufacturing systems (FMSs) prone to
 deadlocks. A place called global sink/source place (GP) is introduced
 provisionally help us to decide a set of monitors such that deadlock
 states can be removed. The TGAL method proceeds with liveness enforcement
 by an iterative way in which a complete state enumeration is computed at
 each step. The resulting LES is generally maximally permissive or
 suboptimal, without solving intractable integer linear programming (ILP)
 problems. Given a system, a sufficient condition is developed to decide
 whether the TGAL method can find maximally permissive, that is, optimal
 supervisors. Several typical FMSs popularly studied in the literature are
 used as the examples to demonstrate the proposed method.
Journal: International Journal of Production Research 
Pages: 4634-4657 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1098785 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1098785 
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Template-Type: ReDIF-Article 1.0
Author-Name: Youli Wang 
Author-X-Name-First: Youli 
Author-X-Name-Last: Wang 
Author-Name: Xiaohui Wang 
Author-X-Name-First: Xiaohui 
Author-X-Name-Last: Wang 
Author-Name: Xueliang Zhang 
Author-X-Name-First: Xueliang 
Author-X-Name-Last: Zhang 
Author-Name: Liming Dai 
Author-X-Name-First: Liming 
Author-X-Name-Last: Dai 
Title: Establishment and application of a process dimension tree 
Abstract:
 Process planning, dimensions and tolerance greatly influence the quality
 and cost of a part in machining processes. In this paper, English letters
 with subscripts are used denote each surface of a part in machining
 processes, and directed line segments are used to represent process
 dimensions. A process dimension tree and a complete dimension model are
 also established. The process dimension tree expresses the machining
 sequences of each surface and the process datum of each process dimension.
 The tree also intuitively and completely reflects the relations of all
 dimensions. The established process dimension tree simplifies the change
 or optimisation of process route and indicates the influence of the
 dimensioning datum of a blank on rough machining allowances and
 dimensional accuracy. This simple and efficient approach may be used to
 establish dimension models, improve process route and optimise blank
 dimensioning.
Journal: International Journal of Production Research 
Pages: 4658-4668 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1098788 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1098788 
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Template-Type: ReDIF-Article 1.0
Author-Name: Alvaro Gil 
Author-X-Name-First: Alvaro 
Author-X-Name-Last: Gil 
Author-Name: Jean-Marc Frayret 
Author-X-Name-First: Jean-Marc 
Author-X-Name-Last: Frayret 
Title: Log classification in the hardwood timber industry: method and value analysis 
Abstract:
 Natural resources industries, such as the forest product industry, must
 deal with variable input material, which affects their efficiency and
 their ability to accurately predict output yields. In order to address
 this, the industry can use technologies that adapt to variable input, or
 plan its operations taking variability into account. In the Canadian
 softwood lumber industry, the first approach is used with the adoption of
 advanced technologies that adapt sawing patterns to logs&#x2019; and
 work-in-process characteristic using scanners technology. Another approach
 to deal with material variability is input material classification.
 Specific characteristics can be measured to classify input material and
 reduce variability within each class. However, whether the process
 involves logs, mining ores or recycled papers, material classification has
 both a value and a cost. This paper first proposes a method based on
 classification tree analysis to classify hardwood logs. Next, using
 agent-based simulation, it analyses the value of different classification
 strategies, from detailed, to no classification at all. Results show in
 the context of the Qu&#xe9;bec hardwood lumber industry that the benefit
 of detailed classification is offset by its cost, while a relatively
 simple classification strategy dramatically improves output yield at
 relatively low cost.
Journal: International Journal of Production Research 
Pages: 4669-4688 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1106607 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106607 
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhiqiao Wu 
Author-X-Name-First: Zhiqiao 
Author-X-Name-Last: Wu 
Author-Name: C.K. Kwong 
Author-X-Name-First: C.K. 
Author-X-Name-Last: Kwong 
Author-Name: C.K.M. Lee 
Author-X-Name-First: C.K.M. 
Author-X-Name-Last: Lee 
Author-Name: Jiafu Tang 
Author-X-Name-First: Jiafu 
Author-X-Name-Last: Tang 
Title: Joint decision of product configuration and remanufacturing for product family design 
Abstract:
 Product family design (PFD) is a popular method for increasing product
 variety to satisfy the needs of diversified markets. With the increasing
 concern for environmental friendliness in society, more and more companies
 develop launching remanufactured products and include them in their
 product families. Therefore, PFD should be considered in a broad decision
 space where configuration of product variants and remanufacturing are
 considered simultaneously. However, this issue was not addressed properly
 in previous research. In this paper, a methodology for joint decision of
 product configuration and remanufacturing is proposed in which a
 bi-objective mixed integer programming model is formulated to determine
 the configurations of both new and remanufactured products for minimising
 product cost, maximising total market share, and satisfying reliability
 requirements. Then, Non-dominated Sorting Genetic Algorithm II (NSGAII) is
 adopted to solve the optimization problem. Computational experiments were
 conducted and their results show that NSGAII is convergent to the model
 well. A case study is presented to illustrate the applicability and
 effectiveness of the proposed methodology.
Journal: International Journal of Production Research 
Pages: 4689-4702 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1109154 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1109154 
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Template-Type: ReDIF-Article 1.0
Author-Name: Wen-An Yang 
Author-X-Name-First: Wen-An 
Author-X-Name-Last: Yang 
Author-Name: Qiang Zhou 
Author-X-Name-First: Qiang 
Author-X-Name-Last: Zhou 
Author-Name: Kwok-Leung Tsui 
Author-X-Name-First: Kwok-Leung 
Author-X-Name-Last: Tsui 
Title: Differential evolution-based feature selection and parameter optimisation for extreme learning machine in tool wear estimation 
Abstract:
 Cutting tool wear degrades the product quality in manufacturing processes.
 Hence, real-time online estimation of tool wear is important for
 suggesting a tool replacement before the wear limit is reached, in order
 to protect the workpiece and the CNC machine from damage and breakdown. In
 this study, using both statistical features and wavelet features extracted
 from sensor signals, an adaptive evolutionary extreme learning machine
 (ELM) learning paradigm is developed for tool wear estimation in
 high-speed milling&#xa0;process. In the proposed method, a discrete
 differential evolution (DE) algorithm is used to select input features for
 the ELM, and a continuous DE algorithm is used for parameter optimisation
 of the mixed kernel function for the ELM. The experimental results
 indicate that the proposed adaptive evolutionary ELM-based tool wear
 estimation model can effectively estimate the tool wear in high-speed
 milling process. Empirical comparisons show that the proposed model
 performs better than existing approaches in estimating the tool wear.
Journal: International Journal of Production Research 
Pages: 4703-4721 
Issue: 15 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1111534 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1111534 
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Template-Type: ReDIF-Article 1.0
Author-Name: Len Vandenheede 
Author-X-Name-First: Len 
Author-X-Name-Last: Vandenheede 
Author-Name: Mario Vanhoucke 
Author-X-Name-First: Mario 
Author-X-Name-Last: Vanhoucke 
Author-Name: Broos Maenhout 
Author-X-Name-First: Broos 
Author-X-Name-Last: Maenhout 
Title: A scatter search for the extended resource renting problem 
Abstract:
 In this paper, the extended Resource Renting Problem (RRP/extended) is
 presented. The RRP/extended is a time-constrained project scheduling
 problem, in which the total project cost is minimised. In the
 RRP/extended, this total project cost is determined by a number of extra
 costs, which are defined in this paper. These costs are based on the costs
 that are used in the traditional Resource Renting Problem and the Total
 Adjustment Cost Problem. Therefore, the RRP/extended represents a union of
 these two problems. To solve the RRP/extended, a scatter search is
 developed. The building blocks of this scatter search are specifically
 designed for the RRP/extended. We introduce two crossovers and an
 improvement method. The efficiency of these building blocks will be shown
 in the paper. Furthermore, a sensitivity analysis is presented in which
 the five costs have diverse values.
Journal: International Journal of Production Research 
Pages: 4723-4743 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1064177 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064177 
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhenyuan Liu 
Author-X-Name-First: Zhenyuan 
Author-X-Name-Last: Liu 
Author-Name: Lei Xiao 
Author-X-Name-First: Lei 
Author-X-Name-Last: Xiao 
Author-Name: Jing Tian 
Author-X-Name-First: Jing 
Author-X-Name-Last: Tian 
Title: An activity-list-based nested partitions algorithm for resource-constrained project scheduling 
Abstract:
 The resource-constrained project scheduling problem (RCPSP) has received
 wide attention. In this paper, an activity-list-based nested partitions
 algorithm (ALNP) is developed for solving the RCPSP and a P-ALNP is
 proposed to improve ALNP with local adjustment. In the algorithms, to
 improve the search efficiency, a partial double justification is employed
 as local search mechanism. The computational experiments on the PSPLIB and
 analysis on robustness of the algorithms show that ALNP outperforms the
 traditional serial scheduling scheme for solving the large-scale, complex
 RCPSPs, and P-ALNP can improve ALNP and obtain better results. P-ALNP is a
 competitive algorithm for solving the RCPSP.
Journal: International Journal of Production Research 
Pages: 4744-4758 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1065353 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1065353 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian-Ya Ding 
Author-X-Name-First: Jian-Ya 
Author-X-Name-Last: Ding 
Author-Name: Shiji Song 
Author-X-Name-First: Shiji 
Author-X-Name-Last: Song 
Author-Name: Jatinder N.D. Gupta 
Author-X-Name-First: Jatinder N.D. 
Author-X-Name-Last: Gupta 
Author-Name: Cheng Wang 
Author-X-Name-First: Cheng 
Author-X-Name-Last: Wang 
Author-Name: Rui Zhang 
Author-X-Name-First: Rui 
Author-X-Name-Last: Zhang 
Author-Name: Cheng Wu 
Author-X-Name-First: Cheng 
Author-X-Name-Last: Wu 
Title: New block properties for flowshop scheduling with blocking and their application in an iterated greedy algorithm 
Abstract:
 This paper proposes new block properties for the flowshop scheduling
 problem with blocking to minimise makespan. A pruning procedure based on
 these proposed properties is used in the construction phase of an iterated
 greedy algorithm to decrease the total number of solutions to be examined
 to find an optimal schedule. Computational results using Taillard&#x2019;s
 benchmark problem instances show that the new block properties help to
 eliminate more &#x2018;unpromising&#x2019; solutions than the classic
 properties. In addition, the effectiveness of the proposed algorithm is
 verified by comparison with some high-performing algorithms for the
 considered problem.
Journal: International Journal of Production Research 
Pages: 4759-4772 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1076941 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076941 
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Template-Type: ReDIF-Article 1.0
Author-Name: Olatunde T. Baruwa 
Author-X-Name-First: Olatunde T. 
Author-X-Name-Last: Baruwa 
Author-Name: Miquel A. Piera 
Author-X-Name-First: Miquel A. 
Author-X-Name-Last: Piera 
Title: A coloured Petri net-based hybrid heuristic search approach to simultaneous scheduling of machines and automated guided vehicles 
Abstract:
 To achieve a significant improvement in the overall performance of a
 flexible manufacturing system, the scheduling process must consider the
 interdependencies that exist between the machining and transport systems.
 However, most works have addressed the scheduling problem as two
 independent decision making problems, assuming sufficient capacity in the
 transport system. In this paper, we study the simultaneous scheduling (SS)
 problem of machines and automated guided vehicles using a timed coloured
 Petri net (TCPN) approach under two performance objectives; makespan and
 exit time of the last job. The modelling approach allows the evaluation of
 all the feasible vehicle assignments as opposed to the traditional
 dispatching rules and demonstrates the benefits of vehicle-controlled
 assignments over machine-controlled for certain production scenarios. In
 contrast with the hierarchical decomposition technique of existing
 approaches, TCPN is capable of describing the dynamics and evaluating the
 performance of the SS problem in a single model. Based on TCPN modelling,
 SS is performed using a hybrid heuristic search algorithm to find optimal
 or near-optimal schedules by searching through the reachability graph of
 the TCPN with heuristic functions. Large-sized instances are solved in
 relatively short computation times, which were a priori unsolvable with
 conventional search algorithms. The algorithm&#x2019;s performance is
 evaluated on a benchmark of 82 test problems. Experimental results
 indicate that the proposed algorithm performs better than the conventional
 ones and compares favourably with other approaches.
Journal: International Journal of Production Research 
Pages: 4773-4792 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1087656 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1087656 
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Template-Type: ReDIF-Article 1.0
Author-Name: Deming Lei 
Author-X-Name-First: Deming 
Author-X-Name-Last: Lei 
Author-Name: Xiuping Guo 
Author-X-Name-First: Xiuping 
Author-X-Name-Last: Guo 
Title: A shuffled frog-leaping algorithm for job shop scheduling with outsourcing options 
Abstract:
 In this paper, job shop scheduling problem with outsourcing options is
 considered and a novel shuffled frog-leaping algorithm (SFLA) is presented
 to minimise total tardiness under condition that total outsourcing cost
 does not exceed a given upper bound. In SFLA, a tournament selection-based
 method is used to decompose the whole population into some memeplexes, the
 search process in each memeplex is done on the best solution of the
 memeplex and composed of the global search step and the multiple
 neighbourhood search step. SFLA is tested on a number of instances and
 compared with some methods from the literature. Computational results
 validate the promising performance of SFLA on the considered problem.
Journal: International Journal of Production Research 
Pages: 4793-4804 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1088970 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1088970 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian Lin 
Author-X-Name-First: Jian 
Author-X-Name-Last: Lin 
Title: A hybrid discrete biogeography-based optimization for the permutation flow&#xa0;shop scheduling problem 
Abstract:
 The permutation flow shop scheduling problem (PFSP) which is known to be
 NP-hard has been widely investigated in recent years. In this paper, an
 effective hybrid discrete biogeography-based optimization (HDBBO)
 algorithm is proposed for solving the PFSP with the objective to minimise
 the makespan. Opposition-based learning method and the NEH heuristic are
 utilised in the HDBBO to generate an initial population with certain
 quality and diversity. Moreover, a novel variable local search strategy is
 presented and incorporated within the biogeography-based optimization
 framework to improve the exploitation ability. Computational results on
 two typical benchmark suits and comparisons with some state-of-the-art
 algorithms are presented to show the effectiveness of the HDBBO scheme.
Journal: International Journal of Production Research 
Pages: 4805-4814 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1094584 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1094584 
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Template-Type: ReDIF-Article 1.0
Author-Name: Sicheng Zhang 
Author-X-Name-First: Sicheng 
Author-X-Name-Last: Zhang 
Author-Name: T.N. Wong 
Author-X-Name-First: T.N. 
Author-X-Name-Last: Wong 
Title: Studying the impact of sequence-dependent set-up times in integrated process planning and scheduling with E-ACO heuristic 
Abstract:
 In job-shop scheduling, the importance of set-up issues is well known and
 has been considered in many solution approaches. However, in integrated
 process planning and scheduling (IPPS) involving flexible process plans,
 the set-up times are often ignored, or absorbed into processing times in
 IPPS domain, with the purpose to reduce the complexity. This is based on
 the assumption that set-up times are sequence-independent, or short enough
 to be ignored compared to processing times. However, it is not uncommon to
 encounter sequence-dependent set-up times (SDSTs) in practical production.
 This paper conducts a detailed investigation on the impact of SDSTs on the
 practical performance of the schedule: a comparative study is made for
 different cases where set-up times are (1) separately considered, (2)
 absorbed into processing times, or (3) totally ignored. An enhanced
 version of ant colony optimisation (E-ACO) algorithm is used to solve the
 IPPS problem, with the objective to minimise the total makespan. The
 following four types of set-up issues are considered: part
 loading/unloading, fixture preparation, tool switching and material
 transportation. Situations with various set-up time lengths have been
 studied and compared. A special case of IPPS problem involving a large
 number of identical jobs has been specifically studied and discussed. The
 results have shown that, set-up times should be carefully dealt with under
 different circumstances.
Journal: International Journal of Production Research 
Pages: 4815-4838 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1098786 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1098786 
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Template-Type: ReDIF-Article 1.0
Author-Name: Ching-Jong Liao 
Author-X-Name-First: Ching-Jong 
Author-X-Name-Last: Liao 
Author-Name: Cheng-Hsiung Lee 
Author-X-Name-First: Cheng-Hsiung 
Author-X-Name-Last: Lee 
Author-Name: Hsing-Tzu Tsai 
Author-X-Name-First: Hsing-Tzu 
Author-X-Name-Last: Tsai 
Title: Scheduling with multi-attribute set-up times on unrelated parallel machines 
Abstract:
 This paper studies a problem in the knitting process of the textile
 industry. In such a production system, each job has a number of attributes
 and each attribute has one or more levels. Because there is at least one
 different attribute level between two adjacent jobs, it is necessary to
 make a set-up adjustment whenever there is a switch to a different job.
 The problem can be formulated as a scheduling problem with multi-attribute
 set-up times on unrelated parallel machines. The objective of the problem
 is to assign jobs to different machines to minimise the makespan. A
 constructive heuristic is developed to obtain a qualified solution. To
 improve the solution further, a meta-heuristic that uses a genetic
 algorithm with a new crossover operator and three local searches are
 proposed. The computational experiments show that the proposed
 constructive heuristic outperforms two existed heuristics and the current
 scheduling method used by the case textile plant.
Journal: International Journal of Production Research 
Pages: 4839-4853 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1118574 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1118574 
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Template-Type: ReDIF-Article 1.0
Author-Name: Guillermo Campos Ciro 
Author-X-Name-First: Guillermo 
Author-X-Name-Last: Campos Ciro 
Author-Name: Fr&#xe9;d&#xe9;ric Dugardin 
Author-X-Name-First: Fr&#xe9;d&#xe9;ric 
Author-X-Name-Last: Dugardin 
Author-Name: Farouk Yalaoui 
Author-X-Name-First: Farouk 
Author-X-Name-Last: Yalaoui 
Author-Name: Russell Kelly 
Author-X-Name-First: Russell 
Author-X-Name-Last: Kelly 
Title: Open shop scheduling problem with a multi-skills resource constraint: a genetic algorithm and an ant colony optimisation approach 
Abstract:
 The continuous evolution of manufacturing environments leads to a more
 efficient production process that controls an increasing number of
 parameters. Production resources usually represent an important constraint
 in a manufacturing activity, specially talking about the management of
 human resources and their skills. In order to study the impact of this
 subject, this paper considers an open shop scheduling problem based on a
 mechanical production workshop to minimise the total flow time including a
 multi-skill resource constraint. Then, we count with a number of workers
 that have a versatility to carry out different tasks, and according to
 their assignment a schedule is generated. In that way, we have formulated
 the problem as a linear as and a non-linear mathematical model which
 applies the classic scheduling constraints, adding some different
 resources constraints related to personnel staff competences and their
 availability to execute one task. In addition, we introduce a genetic
 algorithm and an ant colony optimisation (ACO) method to solve large size
 problems. Finally, the best method (ACO) has been used to solve a real
 industrial case that is presented at the end.
Journal: International Journal of Production Research 
Pages: 4854-4881 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1126371 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1126371 
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Template-Type: ReDIF-Article 1.0
Author-Name: Shen-Tsu Wang 
Author-X-Name-First: Shen-Tsu 
Author-X-Name-Last: Wang 
Title: Integrating grey sequencing with the genetic algorithm--immune algorithm to optimise touch panel cover glass polishing process parameter design 
Abstract:
 The touch panel cover glass is one of the important parts and components
 that determine touch panel quality. The quality requirement of touch panel
 cover glass emphasises the stability of glass thickness. As this factor
 directly influences the induction effect and touch of the touch panel, the
 parameter conditions for the cover glass polishing process have
 significant impact. This study integrated grey sequencing with the Genetic
 algorithm--Immune algorithm to optimise the parameter design for the touch
 panel cover glass polishing process. The experimental measurement value
 was the thickness value of the processed glass, and the uniformity of
 glass thickness after processing was discussed. The optimum processing
 combination influencing the process conditions is as follows: the ambient
 temperature is 22 (&#xb0;C), the processing pressure is 0.04 (Mpa), the
 processing time is 30 (min), the machine speed is 70 (rpm), the polishing
 solution concentration is 1.4 (g/cm-super-3), the central particle size of
 polishing powder is 1.4 (um) and the process capability
 <italic>C</italic><sub><italic>pk</italic></sub> is 1.75, which is better
 than the process capability of
 <italic>C</italic><sub><italic>pk</italic></sub> 1.41 of the response
 surface methodology and the process capability of
 <italic>C</italic><sub><italic>pk</italic></sub> 1.37 of the Taguchi
 experimental design.
Journal: International Journal of Production Research 
Pages: 4882-4893 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1130278 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1130278 
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiae Zhang 
Author-X-Name-First: Jiae 
Author-X-Name-Last: Zhang 
Author-Name: Jianjun Yang 
Author-X-Name-First: Jianjun 
Author-X-Name-Last: Yang 
Title: Flexible job-shop scheduling with flexible workdays, preemption, overlapping in operations and satisfaction criteria: an industrial application 
Abstract:
 This paper addresses a real scheduling problem, namely, a complex flexible
 job-shop scheduling problem (FJSP) with special characteristics (flexible
 workdays, preemption and overlapping in operations), where the objective
 is to maximise a satisfaction criterion defined through goal programming.
 To allow for flexible workdays, the solution representation of the
 classical FJSP is extended to consider overtime decisions and a sequence
 of time-cell states, which is used to model resource capability. A new
 temporal-constraint-handling method is proposed to solve the problem of
 overlapping in operations in a flexible-workday environment. Three
 solution methods are proposed to solve this scheduling problem: a
 heuristic method based on priority rules, a goal-guided tabu search (GGTS)
 and an extended genetic algorithm (EGA). In the GGTS, the neighbourhood
 functions are defined based on elimination approaches, and five possible
 neighbourhood functions
 (<italic>N</italic>0&#x2009;&#x2287;&#x2009;<italic>N</italic>1&#x2009;&#x
 2287;&#x2009;<italic>N</italic>2&#x2009;&#x2287;&#x2009;<italic>N</italic>
 3&#x2009;&#x2287;&#x2009;<italic>N</italic>4) are presented. The
 effectiveness and efficiency of the three solution methods are verified
 using dedicated benchmark instances. Computational simulations and
 comparisons indicate that the proposed <italic>N</italic>4-based GGTS
 demonstrates performance competitive with that of the EGA and the GGTSs
 based on the other neighbourhood functions (<italic>N</italic>0,
 <italic>N</italic>1, <italic>N</italic>2 and <italic>N</italic>3) for
 solving the scheduling problem.
Journal: International Journal of Production Research 
Pages: 4894-4918 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2015.1134839 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1134839 
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Template-Type: ReDIF-Article 1.0
Author-Name: Shengchao Zhou 
Author-X-Name-First: Shengchao 
Author-X-Name-Last: Zhou 
Author-Name: Xueping Li 
Author-X-Name-First: Xueping 
Author-X-Name-Last: Li 
Author-Name: Huaping Chen 
Author-X-Name-First: Huaping 
Author-X-Name-Last: Chen 
Author-Name: Cong Guo 
Author-X-Name-First: Cong 
Author-X-Name-Last: Guo 
Title: Minimizing makespan in a no-wait flowshop with two batch processing machines using estimation of distribution algorithm 
Abstract:
 This paper studies the problem of minimising makespan in a no-wait
 flowshop with two batch processing machines (comprised of a parallel batch
 processing machine and a serial batch processing machine), non-identical
 job sizes and unequal ready times. We propose a population-based
 evolutionary method named estimation of distribution algorithm (EDA).
 Firstly, the individuals in the population are coded into job sequences.
 Then, a probabilistic model is built to generate new population and an
 incremental learning method is developed to update the probabilistic
 model. Thirdly, the best-fit heuristic is used to group jobs into batches
 and a least idle/waiting time approach is proposed to sequence the batches
 on batch processing machines. In addition, some problem-dependent local
 search heuristics are incorporated into the EDA to further improve the
 searching quality. Computational simulation and comparisons with some
 existing algorithms demonstrate the effectiveness and robustness of the
 proposed algorithm. Furthermore, the effectiveness of embedding the local
 search method in the EDA is also evaluated.
Journal: International Journal of Production Research 
Pages: 4919-4937 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2016.1140920 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1140920 
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Template-Type: ReDIF-Article 1.0
Author-Name: Dimitris C. Paraskevopoulos 
Author-X-Name-First: Dimitris C. 
Author-X-Name-Last: Paraskevopoulos 
Author-Name: Christos D. Tarantilis 
Author-X-Name-First: Christos D. 
Author-X-Name-Last: Tarantilis 
Author-Name: George Ioannou 
Author-X-Name-First: George 
Author-X-Name-Last: Ioannou 
Title: An adaptive memory programming framework for the resource-constrained project scheduling problem 
Abstract:
 The Resource-Constrained Project Scheduling Problem (RCPSP) is one of the
 most intractable combinatorial optimisation problems that combines a set
 of constraints and objectives met in a vast variety of applications and
 industries. Its solution raises major theoretical challenges due to its
 complexity, yet presenting numerous practical dimensions. Adaptive memory
 programming (AMP) is one of the most successful frameworks for solving
 hard combinatorial optimisation problems (e.g. vehicle routing and
 scheduling). Its success stems from the use of learning mechanisms that
 capture favourable solution elements found in high-quality solutions. This
 paper challenges the efficiency of AMP for solving the RCPSP, to our
 knowledge, for the first time in the literature. Computational experiments
 on well-known benchmark RCPSP instances show that the proposed AMP
 consistently produces high-quality solutions in reasonable computational
 times.
Journal: International Journal of Production Research 
Pages: 4938-4956 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2016.1145814 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1145814 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xuemei Qi 
Author-X-Name-First: Xuemei 
Author-X-Name-Last: Qi 
Author-Name: Hongtao Wang 
Author-X-Name-First: Hongtao 
Author-X-Name-Last: Wang 
Author-Name: Haihong Zhu 
Author-X-Name-First: Haihong 
Author-X-Name-Last: Zhu 
Author-Name: Ji Zhang 
Author-X-Name-First: Ji 
Author-X-Name-Last: Zhang 
Author-Name: Fulong Chen 
Author-X-Name-First: Fulong 
Author-X-Name-Last: Chen 
Author-Name: Jie Yang 
Author-X-Name-First: Jie 
Author-X-Name-Last: Yang 
Title: Fast local neighborhood search algorithm for the no-wait flow shop scheduling with total flow time minimization 
Abstract:
 A fast local neighbourhood search (FLNS) algorithm is proposed in this
 paper to minimise the total flow time in the no-wait flow shop scheduling
 problem, which is known to be NP-hard for more than two machines. In this
 work, an unscheduled job sequence is constructed firstly according to the
 total processing time and standard deviation of jobs on the machines. This
 job sequence is undergone an initial optimisation using basic
 neighbourhood search algorithm. Then, an innovative local neighbourhood
 search scheme is designed to search for the partial neighbourhood in each
 iterative processing and calculate the neighbourhood solution with an
 objective increment method. This not only improves the solution quality
 significantly, but also speeds up the convergence of the solution of the
 algorithm. Moreover, a probabilistic acceptance criterion is adopted to
 help our method escape from the local optima. Based on Taillard&#x2019;s
 benchmarks, the experimental results show that the proposed FLNS algorithm
 is superior to major existing algorithms (IHA, IBH<sub>LS</sub>, GA-VNS
 and DHS) in terms of both quality and robustness, and can provide best
 upper bounds. The in-depth statistical analysis demonstrates that the
 promising performance of our proposed algorithm is also statistically
 significant.
Journal: International Journal of Production Research 
Pages: 4957-4972 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2016.1150615 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1150615 
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Template-Type: ReDIF-Article 1.0
Author-Name: Alcides Santander-Mercado 
Author-X-Name-First: Alcides 
Author-X-Name-Last: Santander-Mercado 
Author-Name: Maria Jubiz-Diaz 
Author-X-Name-First: Maria 
Author-X-Name-Last: Jubiz-Diaz 
Title: The economic lot scheduling problem: a survey 
Abstract:
 This paper aims to present a literature review and an analysis of research
 works in the field of economic lot scheduling problem (ELSP) based on the
 related articles published since 1958. Because of ELSP complexity, there
 are a noticeable number of studies that use algorithms based on different
 approaches in order to deliver a feasible solution. Therefore, the
 contribution of this paper is to introduce a taxonomic classification
 based on scheduling policies and solving methodologies proposed by
 authors. Also, a simple data analysis is carried out to understand the
 evolution of ELSP and to identify potential research areas for further
 studies. The results show that there is an increasing trend in this topic
 but there are still much needs from industrial manufacturing systems. This
 study is expected to provide a comprehensive list of references for other
 researchers, who are interested in ELSP research.
Journal: International Journal of Production Research 
Pages: 4973-4992 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2016.1154214 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154214 
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Template-Type: ReDIF-Article 1.0
Author-Name: Michele Ciavotta 
Author-X-Name-First: Michele 
Author-X-Name-Last: Ciavotta 
Author-Name: Carlo Meloni 
Author-X-Name-First: Carlo 
Author-X-Name-Last: Meloni 
Author-Name: Marco Pranzo 
Author-X-Name-First: Marco 
Author-X-Name-Last: Pranzo 
Title: Speeding up a Rollout algorithm for complex parallel machine scheduling 
Abstract:
 Rollout methodology is a constructive metaheuristic algorithm and its main
 characteristics are its modularity, the adaptability to different
 objectives and constraints and the easiness of implementation.
 Multi-heuristic Rollout extends the Rollout by incorporating several
 constructive heuristics in the Rollout framework and it is able to easily
 incorporate human experience inside its research patterns to fulfil
 complex requirements dictated by the application at hand. However, a
 drawback for both Rollout and multi-heuristic Rollout is often represented
 by the required computation time. This paper proposes some alternatives of
 the full multi-heuristic Rollout algorithm aimed at improving the
 efficiency by reducing the computational effort while preserving the
 effectiveness. Namely, we propose dynamic heuristics pruning and
 candidates reduction strategies. As illustrative case studies, we analyse
 complex deterministic identical parallel machine scheduling problems
 showing how Rollout procedures can be used to tackle several additional
 constraints arising in real contexts. More specifically, we considered
 both standard (batch production, family set-ups, release, due dates, etc.)
 and non-standard (machine unavailabilities, maximum campaign size)
 scheduling constraints. An extensive campaign of computational experiments
 shows the behaviour of the multi-heuristic Rollout approach and the
 effectiveness of the different proposed speed-up methods.
Journal: International Journal of Production Research 
Pages: 4993-5009 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2016.1157276 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1157276 
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Template-Type: ReDIF-Article 1.0
Author-Name: Nima Kazemi 
Author-X-Name-First: Nima 
Author-X-Name-Last: Kazemi 
Author-Name: Salwa Hanim Abdul-Rashid 
Author-X-Name-First: Salwa Hanim 
Author-X-Name-Last: Abdul-Rashid 
Author-Name: Ehsan Shekarian 
Author-X-Name-First: Ehsan 
Author-X-Name-Last: Shekarian 
Author-Name: Eleonora Bottani 
Author-X-Name-First: Eleonora 
Author-X-Name-Last: Bottani 
Author-Name: Roberto Montanari 
Author-X-Name-First: Roberto 
Author-X-Name-Last: Montanari 
Title: A fuzzy lot-sizing problem with two-stage composite human learning 
Abstract:
 Due to the repetitive nature of inventory planning over the planning
 horizon, the operator in charge has to perform planning tasks
 repetitively, and consequently s/he becomes more familiar with the tasks
 over time. Familiarity with the tasks suggests that learning takes place
 in inventory planning. Even though the operator&#x2019;s learning over
 time might improve his/her efficiency, prior research on fuzzy lot-sizing
 problems mostly overlooked the effect of human learning in their models
 and its impact on the operator&#x2019;s performance. To close the research
 gap in this area, this paper models the operator's learning in a fuzzy
 economic order quantity model with backorders. The paper models a
 situation where the operator applies the acquired knowledge over the
 cycles in setting the fuzzy parameters at the beginning of every planning
 cycle, where his/her learning ability includes the cognitive and motor
 capabilities of a human being. Subsequently, a mathematical model which
 takes account of a two-stage human learning over the planning cycles is
 developed, which is then analytically investigated using sample data-sets.
 The results indicate that both operator&#x2019;s capabilities, cognitive
 and motor, affect the efficiency of the fuzzy lot-sizing inventory model,
 but the influence of the cognitive capability is more profound, which in
 turn suggests the importance of training programmes for the workforces.
 The results of the sensitivity analysis also draw some managerial insights
 for the case that some model parameters vary over the planning horizon.
Journal: International Journal of Production Research 
Pages: 5010-5025 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2016.1165874 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165874 
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Template-Type: ReDIF-Article 1.0
Author-Name: Albert Corominas 
Author-X-Name-First: Albert 
Author-X-Name-Last: Corominas 
Title: A note on &#x2018;A bit-wise mutation algorithm for mixed-model sequencing in JIT production systems&#x2019; (Nazar & Pillai, 2015, IJPR, 53:19, 5931-5947) 
Abstract:
 This note discusses three points about the problem of sequencing units on
 a mixed-model assembly line in &#x2018;A bit-wise mutation algorithm for
 mixed-model sequencing in JIT production systems&#x2019; (Nazar & Pillai,
 2015, IJPR, 53:19, 5931-5947). Specifically, the mixed-integer quadratic
 model, the bit-wise mutation algorithm and the bi-objective problem to
 optimise both product rate variation and makespan. The conclusion of the
 discussion is that the three alleged contributions are not valid or are
 outperformed by those presented in some previously published papers.
Journal: International Journal of Production Research 
Pages: 5026-5027 
Issue: 16 
Volume: 54 
Year: 2016 
Month: 8 
X-DOI: 10.1080/00207543.2016.1146420 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1146420 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xu Guan 
Author-X-Name-First: Xu 
Author-X-Name-Last: Guan 
Author-Name: Guo Li 
Author-X-Name-First: Guo 
Author-X-Name-Last: Li 
Author-Name: Suresh Pal Sethi 
Author-X-Name-First: Suresh Pal 
Author-X-Name-Last: Sethi 
Title: The implication of vendor inventory liability period in a decentralised assembly system 
Abstract:
 This paper investigates a decentralised assembly system that consists of
 one manufacturer and multiple suppliers who produce the complementary
 components. In a single selling season, the manufacturer initially sets a
 vendor inventory liability period (VILP) to control the suppliers&#x2019;
 delivery times, and the suppliers simultaneously determine when to deliver
 their components. Given the firms&#x2019; equilibrium strategies, we find
 that it is not wise for the manufacturer to set an overly long VILP, since
 having no inventory is not always beneficial to the manufacturer. A
 supplier may choose to postpone his delivery when the length of the VILP
 increases or the other suppliers&#x2019; deliveries are delayed, and
 either of these conditions is detrimental to the supplier&#x2019;s
 profitability. We also examine the impact of VILP under different
 situations and find that having VILPs customised for different suppliers
 can reduce the manufacturer&#x2019;s cost as well as improve the supply
 chain&#x2019;s overall efficiency.
Journal: International Journal of Production Research 
Pages: 5029-5044 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2015.1067374 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1067374 
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Template-Type: ReDIF-Article 1.0
Author-Name: Wook-Yeon Hwang 
Author-X-Name-First: Wook-Yeon 
Author-X-Name-Last: Hwang 
Title: Cluster-based artificial contrasts for inhomogeneously distributed data with an indicator variable 
Abstract:
 Multivariate statistical process control is used for simultaneously
 monitoring several process variables. The original artificial contrasts
 (AC) are very useful for monitoring inhomogeneously distributed data with
 an indicator variable. The cluster-based AC improve it by considering
 separated clusters, respectively. Then the artificial data used for the AC
 overlap each cluster. Numerical experiments show that our method
 outperforms existing methods in terms of Type-II error rate.
Journal: International Journal of Production Research 
Pages: 5045-5055 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2015.1075667 
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1075667 
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Template-Type: ReDIF-Article 1.0
Author-Name: Shuihua Han 
Author-X-Name-First: Shuihua 
Author-X-Name-Last: Han 
Author-Name: Weina Ma 
Author-X-Name-First: Weina 
Author-X-Name-Last: Ma 
Author-Name: Ling Zhao 
Author-X-Name-First: Ling 
Author-X-Name-Last: Zhao 
Author-Name: Xuelian Zhang 
Author-X-Name-First: Xuelian 
Author-X-Name-Last: Zhang 
Author-Name: Ming K. Lim 
Author-X-Name-First: Ming K. 
Author-X-Name-Last: Lim 
Author-Name: Shuangyuan Yang 
Author-X-Name-First: Shuangyuan 
Author-X-Name-Last: Yang 
Author-Name: Stephen Leung 
Author-X-Name-First: Stephen 
Author-X-Name-Last: Leung 
Title: A robust optimisation model for hybrid remanufacturing and manufacturing systems under uncertain return quality and market demand 
Abstract:
 In remanufacturing research, most researchers predominantly emphasised on
 the recovery of whole product (core) rather than at the component level
 due to its complexity. In contrast, this paper addresses the challenges to
 focus on remanufacturing through component recovery, so as to solve
 production planning problems of hybrid remanufacturing and manufacturing
 systems. To deal with the uncertainties of quality and quantity of product
 returns, the processing time of remanufacturing, remanufacturing costs, as
 well as market demands, a robust optimisation model was developed in this
 research and a case study was used to evaluate its effectiveness and
 efficiency. To strengthen this research, a sensitivity analysis of the
 uncertain parameters and the original equipment manufacturer&#x2019;s
 (OEM&#x2019;s) pricing strategy was also conducted. The research finding
 shows that the market demand volatility leads to a significant increase in
 the under fulfilment and a reduction in OEM&#x2019;s profit. On the other
 hand, recovery cost reduction, as endogenous cost saving, encourages the
 OEM to produce more remanufactured products with the increase in market
 demand. Furthermore, the OEM may risk profit loss if they raise the price
 of new products, and inversely, they could gain more if the price of
 remanufactured products is raised.
Journal: International Journal of Production Research 
Pages: 5056-5072 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1145815 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1145815 
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Template-Type: ReDIF-Article 1.0
Author-Name: H.W. You 
Author-X-Name-First: H.W. 
Author-X-Name-Last: You 
Author-Name: Michael B.C. Khoo 
Author-X-Name-First: Michael B.C. 
Author-X-Name-Last: Khoo 
Author-Name: P. Castagliola 
Author-X-Name-First: P. 
Author-X-Name-Last: Castagliola 
Author-Name: Liang Qu 
Author-X-Name-First: Liang 
Author-X-Name-Last: Qu 
Title: Optimal exponentially weighted moving average <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" content-type="black-white" xlink:href="tprs_a_1145820_ilg0001_b.eps"/> charts with estimated parameters based on median run length and expected median run length 
Abstract:
 This paper examines the exponentially weighted moving average (EWMA)
 <inline-formula id="ILM0001"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1145820_ilm0001.gif"/></inline-formula> chart with
 estimated process parameters. As the run length distribution is skewed
 when the process is in-control or slightly out-of-control, the average run
 length (ARL) provides less meaningful interpretation of a chart&#x2019;s
 performance. Therefore, in this paper, the median run length (MRL) and
 expected MRL (EMRL) are used as alternative performance criteria.
 Additionally, the methodology for computing the EMRL of the EWMA
 <inline-formula id="ILM0002"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1145820_ilm0002.gif"/></inline-formula> chart with
 known process parameters is presented. Since the performance of the EWMA
 <inline-formula id="ILM0003"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1145820_ilm0003.gif"/></inline-formula> chart is
 affected by estimation error, a study on the minimum number of Phase-I
 samples required so that the chart with estimated parameters has a desired
 performance is conducted. As this study reveals that a large number of
 Phase-I samples are needed, optimal design procedures for minimising the
 out-of-control MRL and EMRL of the EWMA <inline-formula
 id="ILM0004"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1145820_ilm0004.gif"/></inline-formula> chart with
 estimated process parameters are suggested. By using these proposed
 procedures, the EWMA <inline-formula id="ILM0005"><inline-graphic
 xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1145820_ilm0005.gif"/></inline-formula> chart with
 estimated parameters will have a closer performance to its known
 parameters counterpart, even with a reasonable number of Phase-I samples.
 The construction of the MRL based EWMA <inline-formula
 id="ILM0006"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1145820_ilm0006.gif"/></inline-formula> chart with
 estimated parameters is illustrated using real data and compared with the
 corresponding chart based on ARL.
Journal: International Journal of Production Research 
Pages: 5073-5094 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1145820 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1145820 
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Template-Type: ReDIF-Article 1.0
Author-Name: A. Ben Mabrouk 
Author-X-Name-First: A. 
Author-X-Name-Last: Ben Mabrouk 
Author-Name: A. Chelbi 
Author-X-Name-First: A. 
Author-X-Name-Last: Chelbi 
Author-Name: M. Radhoui 
Author-X-Name-First: M. 
Author-X-Name-Last: Radhoui 
Title: Optimal imperfect preventive maintenance policy for equipment leased during successive periods 
Abstract:
 In this paper, we consider randomly failing equipment leased several times
 during their life cycle with a given warranty period. A mathematical model
 is developed to determine the optimal efficiency levels of preventive
 maintenance (PM) to be performed on the equipment between successive lease
 periods, maximising the expected total profit of the lessor over the
 equipment life cycle. The model considers the expected leasing revenue as
 well as the equipment acquisition cost and the average PM and repair
 costs. PM actions allow reducing the age of the equipment to a certain
 extent with a corresponding cost depending on the PM level adopted. The
 efficiency of the PM is determinant of the expected revenue during the
 next lease period. Given a set of <italic>K</italic> possible PM levels
 and the number of lease periods <italic>n</italic> over the equipment life
 cycle, <italic>K</italic>-super-<italic>n</italic>&#x2212;1 PM strategies
 are possible. A genetic algorithm is proposed in order to obtain nearly
 optimal policies in situations where the number of possibilities
 <italic>K</italic>-super-<italic>n</italic>&#x2212;1 is very high.
 Obtained numerical results are discussed. Small- and big-size instances of
 the problem are considered in the case of a service company in the oil and
 gas industry specialised in leasing specific equipment such as separators,
 to oil companies for production activities with a limited duration of
 several months like well testing or short production tests.
Journal: International Journal of Production Research 
Pages: 5095-5110 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1146417 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1146417 
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Template-Type: ReDIF-Article 1.0
Author-Name: J. MacGregor Smith 
Author-X-Name-First: J. 
Author-X-Name-Last: MacGregor Smith 
Title: Joint optimisation of buffers and network population for closed finite queueing systems 
Abstract:
 The buffer allocation problem for closed finite queueing networks is a
 nonlinear integer programming problem which is <inline-formula
 id="ILM0001"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
 xlink:href="tprs_a_1154213_ilm0001.gif"/></inline-formula>-Hard. A
 queueing network decomposition methodology based upon a mean value
 analysis algorithm is coupled with a nonlinear sequential quadratic
 programming algorithm to compute the simultaneous optimal buffer
 allocations and network population via a branch-and-bound scheme for
 various network topologies. The joint optimisation problem is essentially
 multi-objective where the decision variable on the population will be
 treated as a constraint linking the buffer allocation and the throughput
 which is to be maximised. The fact that the optimisation problem is a
 concave programming problem assists in the search for an optimal solution.
 The material handling or transportation system for transferring the finite
 customer population between the nodes in the network is also examined.
 Extensive numerical results demonstrate the efficacy of the optimisation
 methodology.
Journal: International Journal of Production Research 
Pages: 5111-5135 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1154213 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154213 
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Th&#xfc;rer 
Author-X-Name-First: Matthias 
Author-X-Name-Last: Th&#xfc;rer 
Author-Name: Mark Stevenson 
Author-X-Name-First: Mark 
Author-X-Name-Last: Stevenson 
Title: Workload control in job shops with re-entrant flows: an assessment by simulation 
Abstract:
 One of the key functions of Workload Control is order release. Jobs are
 not released immediately onto the shop floor -- they are withheld and
 selectively released to create a mix of jobs that keeps work-in-process
 within limits and meet due dates. A recent implementation of Workload
 Control&#x2019;s release method highlighted an important issue thus far
 overlooked by research: How to accommodate re-entrant flows, whereby a
 station is visited multiple times by the same job? We present the first
 study to compare the performance of Workload Control both with and without
 re-entrant flows. Simulation results from a job shop model highlight two
 important aspects: (i) re-entrant flows increase variability in the work
 arriving at a station, leading to a direct detrimental effect on
 performance; (ii) re-entrant flows affect the release decision-making
 process since the load contribution of all visits by a job to a station
 has to fit within the norm. Both aspects have implications for practice
 and our interpretation of previous research since: (i) parameters given
 for work arriving may significantly differ from those realised; (ii)
 increased workload contributions at release mean that prior simulations
 may have been unstable, leading to some jobs never being released.
Journal: International Journal of Production Research 
Pages: 5136-5150 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1156182 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1156182 
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Template-Type: ReDIF-Article 1.0
Author-Name: Giovanny Arbelaez Garces 
Author-X-Name-First: Giovanny 
Author-X-Name-Last: Arbelaez Garces 
Author-Name: Auguste Rakotondranaivo 
Author-X-Name-First: Auguste 
Author-X-Name-Last: Rakotondranaivo 
Author-Name: Eric Bonjour 
Author-X-Name-First: Eric 
Author-X-Name-Last: Bonjour 
Title: Improving users&#x2019; product acceptability: an approach based on Bayesian networks and a simulated annealing algorithm 
Abstract:
 Developing products that are properly suited to users&#x2019; needs and
 preferences in order to be accepted is one of the main challenges
 designers and engineers face constantly. Evaluating and improving
 users&#x2019; product acceptability has become an important research
 question. Many approaches leave the acceptability evaluation question for
 the last phases of the New Product Development process (NPD), when an
 almost finished prototype is available and when there is no time left for
 important modifications. In the early phase of the NPD process, the
 project managers need models and methods to evaluate the potential
 acceptability of the new concept and if required, to define actions to
 improve this concept. In this paper, a method with two main goals is
 proposed to tackle this problem. Its first goal consists in evaluating an
 index of users&#x2019; product acceptability. When this index is too low,
 the second goal concerns the optimal selection of the most appropriate
 actions (improvement scenario) to increase this previously assessed index
 and to optimise the supplementary cost. As information collected from
 users in the early phase is subject to uncertainty, the proposed method
 exploits the inference properties of Bayesian networks making it possible
 to make useful estimations of the acceptability index. Furthermore, the
 improvement scenarios are composed of actions that make it possible to
 improve different criteria composing the users&#x2019; acceptability
 index. The improvement problem is formulated as an optimisation problem to
 be solved by a simulated annealing algorithm. In order to illustrate its
 interest, the proposed method is applied to a real case concerning the
 design of a medical-stocking threading device.
Journal: International Journal of Production Research 
Pages: 5151-5168 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1156183 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1156183 
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Template-Type: ReDIF-Article 1.0
Author-Name: Chih-Hsuan Wang 
Author-X-Name-First: Chih-Hsuan 
Author-X-Name-Last: Wang 
Author-Name: Yu-Wei Chien 
Author-X-Name-First: Yu-Wei 
Author-X-Name-Last: Chien 
Title: Combining balanced scorecard with data envelopment analysis to conduct performance diagnosis for Taiwanese LED manufacturers 
Abstract:
 Light emitting diode (LED) is a popular component to replace the
 traditional lighting source or advertising sign display. In 2014,
 high-brightness LED has a strong growth in backlight display, mobile
 appliances, automotive devices and outdoor illumination. However, emerging
 technologies in compound materials, epitaxying, packaging and new entrants
 result in a scale-based economy and intensively competitive environment.
 Inspired by the concept of business analytics, this paper proposes a novel
 framework to conduct corporate diagnosis for Taiwanese LED manufacturers:
 (1) balanced scorecard is fused with data envelopment analysis to address
 the impact of operational efficiency on performance outcomes, (2)
 financial and non-financial indicators are incorporated into the process
 of performance measurement, (3) the intricate causalities between key
 performance indicators (KPIs) and multiple outcomes (i.e. earnings per
 share and return on equity) are captured and (4) managerial insights are
 provided to indicate adaptive adjustment on significant KPIs. More
 importantly, a data-set comprising representative Taiwanese LED companies
 spanned from 2010 to 2014 is used to justify the validity of the proposed
 framework.
Journal: International Journal of Production Research 
Pages: 5169-5181 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1156780 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1156780 
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Template-Type: ReDIF-Article 1.0
Author-Name: Sebastian Steinker 
Author-X-Name-First: Sebastian 
Author-X-Name-Last: Steinker 
Author-Name: Mario Pesch 
Author-X-Name-First: Mario 
Author-X-Name-Last: Pesch 
Author-Name: Kai Hoberg 
Author-X-Name-First: Kai 
Author-X-Name-Last: Hoberg 
Title: Inventory management under financial distress: an empirical analysis 
Abstract:
 This study analyses inventory reductions as a means of short-term
 financing of firms under financial distress. We use quarterly panel data
 of U.S. manufacturing firms for the period from 1995 to 2007. We identify
 a sample of 198 distressed firms for which we analyse changes in relative
 inventory. Approximately 70% of distressed firms reduce their inventories
 until the end of their individual distress periods. This decrease
 corresponds to a mean reduction of 18.7 inventory days or 9.4%. Additional
 regression analyses show that differences in inventory adjustments depend
 on pre-distress inventory performance, firm size, and turnaround strategy.
 We also compile a sample of 142 firms that defaulted to analyse inventory
 actions of unsuccessful turnarounds. Our findings indicate that defaulting
 firms also reduce their inventories but that the reductions are lower than
 those of firms that resolve their financial distress. We conclude that
 distressed firms use short-term inventory adjustments to free up cash and
 to achieve long-term efficiency gains from inventory optimisation. Our
 findings suggest that inventory optimisation is an essential part of a
 complete and successful turnaround strategy and financially distressed
 firms should always consider this action as a means to prevent bankruptcy.
Journal: International Journal of Production Research 
Pages: 5182-5207 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1157273 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1157273 
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Template-Type: ReDIF-Article 1.0
Author-Name: Mu-Chen Chen 
Author-X-Name-First: Mu-Chen 
Author-X-Name-Last: Chen 
Author-Name: Chun-Chin Hsu 
Author-X-Name-First: Chun-Chin 
Author-X-Name-Last: Hsu 
Author-Name: Bharat Malhotra 
Author-X-Name-First: Bharat 
Author-X-Name-Last: Malhotra 
Author-Name: Manoj Kumar Tiwari 
Author-X-Name-First: Manoj Kumar 
Author-X-Name-Last: Tiwari 
Title: An efficient ICA-DW-SVDD fault detection and diagnosis method for non-Gaussian processes 
Abstract:
 Independent Component Analysis (ICA) has been extensively used for
 detecting faults in industrial processes. While applying ICA to process
 monitoring, the inability of identifying the important components affect
 the fault diagnosis ability. For further improving the competence of ICA,
 this paper proposes an approach integrating ICA, Durbin Watson (DW)
 criterion and Support Vector Data Description (SVDD) to monitor
 non-Gaussian process for detecting faults. In the proposed approach,
 namely ICA--DW--SVDD, ICA is a non-Gaussian information extractor from
 original variables, DW identifies dominating ICs, and SVDD plays the role
 of fault detector. This paper also discusses the retracing method to
 detect original variables causing disturbance in the process. One
 simulation case and the Tennessee Eastman Process are used to demonstrate
 the effectiveness of our proposed approach.
Journal: International Journal of Production Research 
Pages: 5208-5218 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1161250 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1161250 
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Template-Type: ReDIF-Article 1.0
Author-Name: Vitor G. Azevedo 
Author-X-Name-First: Vitor G. 
Author-X-Name-Last: Azevedo 
Author-Name: Lucila M.S. Campos 
Author-X-Name-First: Lucila M.S. 
Author-X-Name-Last: Campos 
Title: Combination of forecasts for the price of crude oil on the spot market 
Abstract:
 In this paper, we present a combination of three forecast models, ARIMA,
 exponential smoothing and dynamic regression, in order to predict the West
 Texas Intermediate (WTI) crude oil spot price and the Brent North Sea
 (Brent) crude oil spot price. Using samples from the period between
 January 1994 and June 2012 (in-sample), we identify the parameters and
 estimate the models. The validated models are combined to perform a
 forecast out-of-sample between July 2012 and June 2013. The results
 demonstrate that among the three models tested in-sample with Brent
 Prices, based on the MAPE measurement error, the ARIMA (2,1,8) model
 produced the best result, and the dynamic regression model was the best
 in-sample model for the WTI price. In the validation phase, the dynamic
 regression models did not prove to be valid, and therefore the
 combinations are performed only with the ARIMA and exponential smoothing
 models. For both proxies of oil prices, the combination of forecasts using
 ARIMA and exponential smoothing (out-of-sample) performed better than
 individual ARIMA and exponential models and also better than our benchmark
 models (naive forecast and Neural Network model). Based on the results, it
 can be inferred that using to a combination of forecasts to predict WTI
 and Brent spot prices is promising. We also point out that the selected
 model is easily replicable in spreadsheets and forecasting software and is
 based only on the past or lagged WTI or Brent values for future
 predictions.
Journal: International Journal of Production Research 
Pages: 5219-5235 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1162340 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1162340 
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Template-Type: ReDIF-Article 1.0
Author-Name: Alain Bensoussan 
Author-X-Name-First: Alain 
Author-X-Name-Last: Bensoussan 
Author-Name: Qi Feng 
Author-X-Name-First: Qi 
Author-X-Name-Last: Feng 
Author-Name: Sirong Luo 
Author-X-Name-First: Sirong 
Author-X-Name-Last: Luo 
Author-Name: Suresh P. Sethi 
Author-X-Name-First: Suresh P. 
Author-X-Name-Last: Sethi 
Title: Evaluating long-term service performance under short-term forecast updates 
Abstract:
 Managing product availability in a cost-effective way has always been a
 major challenge faced by inventory managers. We study the problem of a
 firm selling a perishable product with short-term demand patterns and a
 long-term service target using the newsvendor framework. The newsvendor
 determines his long-term order at the first stage, and revises the order
 according to a short-term forecast update at the second stage. He also
 evaluates a long-term service target for his overall performance on
 product availability across all possible forecast updates. We characterise
 his optimal inventory policy that minimises the expected inventory cost
 while meeting the long-term service target. Both in-stock rate and fill
 rate targets are examined.
Journal: International Journal of Production Research 
Pages: 5236-5249 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1165357 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165357 
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Template-Type: ReDIF-Article 1.0
Author-Name: Lihao Lu 
Author-X-Name-First: Lihao 
Author-X-Name-Last: Lu 
Author-Name: Qinglong Gou 
Author-X-Name-First: Qinglong 
Author-X-Name-Last: Gou 
Author-Name: Wansheng Tang 
Author-X-Name-First: Wansheng 
Author-X-Name-Last: Tang 
Author-Name: Jianxiong Zhang 
Author-X-Name-First: Jianxiong 
Author-X-Name-Last: Zhang 
Title: Joint pricing and advertising strategy with reference price effect 
Abstract:
 Consumers are susceptible to reference price effects when they make
 purchase decisions for a certain product. Meanwhile, the sales price and
 advertisement are the determinable factors that have impact on
 consumers&#x2019; reference price which are also fundamental marketing
 strategies. Therefore, how to determine an appropriate sales price and
 advertising effort level to maximise firms&#x2019; profits is an essential
 task. A joint pricing and advertising problem for a monopolistic firm with
 consideration of reference price effect is investigated, where consumer
 demand rate is price-sensitivity and depends on the gap between the sales
 price and the reference price in consumers&#x2019; mind. An optimisation
 model is established to maximise the firm&#x2019;s total profit by making
 a joint pricing and advertising strategy. The static and dynamic joint
 strategies are obtained by applying Pontryagin&#x2019;s maximum principle.
 Results show that the dynamic strategies dominate the static ones.
 Furthermore, the dynamic pricing and dynamic advertising strategies are
 strategic complements. Additionally, the length of the sales period plays
 a key role in determining the superiority of the two dynamic strategies.
 Specifically, a relatively short sales period highlights the value of the
 dynamic advertising while a long sales period strengthens the function of
 the dynamic pricing.
Journal: International Journal of Production Research 
Pages: 5250-5270 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1165878 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165878 
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Template-Type: ReDIF-Article 1.0
Author-Name: Xun Wang 
Author-X-Name-First: Xun 
Author-X-Name-Last: Wang 
Author-Name: Fotios Petropoulos 
Author-X-Name-First: Fotios 
Author-X-Name-Last: Petropoulos 
Title: To select or to combine? The inventory performance of model and expert forecasts 
Abstract:
 Demand forecasting is a crucial input of any inventory system. The quality
 of the forecasts should be evaluated not only in terms of forecast
 accuracy or bias but also with regards to their inventory implications,
 which include the impact on the total inventory cost, the achieved service
 levels and the variance of orders and inventory. Forecast selection and
 combination are two very widely applied forecasting strategies that have
 shown repeatedly to increase the forecasting performance. However, the
 inventory performance of these strategies remains unexplored. We
 empirically examine the effects of forecast selection and combination on
 inventory when two sources of forecasts are available. We employ a large
 data-set that contains demands and (statistical and judgmental) forecasts
 for multiple pharmaceutical stock keeping units. We show that forecast
 selection and simple combination increase simultaneously the forecasting
 and inventory performance.
Journal: International Journal of Production Research 
Pages: 5271-5282 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1167983 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1167983 
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Template-Type: ReDIF-Article 1.0
Author-Name: Kyoung-Kuk Kim 
Author-X-Name-First: Kyoung-Kuk 
Author-X-Name-Last: Kim 
Author-Name: Chi-Guhn Lee 
Author-X-Name-First: Chi-Guhn 
Author-X-Name-Last: Lee 
Author-Name: Sunggyun Park 
Author-X-Name-First: Sunggyun 
Author-X-Name-Last: Park 
Title: Dynamic pricing with &#x2018;BOGO&#x2019; promotion in revenue management 
Abstract:
 We consider a dynamic pricing problem when a seller, facing uncertain
 demands, sells a single product in a finite horizon. The seller actively
 adopts dynamic pricing and quantity discount schemes. The proposed model
 is based on the assumption that each customer has random reservation
 prices and the purchase size depends on the posted price and discount. We
 particularly focus on the widely adopted promotional schemes &#x2018;buy
 one get one free&#x2019; and &#x2018;50% off&#x2019; and study the optimal
 strategic choices of the seller. Analytical results together with
 numerical experiments are presented to help us obtain managerial insights.
 Additional numerical results for a generalised model are provided so as to
 examine the effectiveness of promotional schemes.
Journal: International Journal of Production Research 
Pages: 5283-5302 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1173250 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173250 
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Template-Type: ReDIF-Article 1.0
Author-Name: R. Ahmadi 
Author-X-Name-First: R. 
Author-X-Name-Last: Ahmadi 
Title: An optimal replacement policy for complex multi-component systems 
Abstract:
 Given a reward structure, this paper addresses an optimal replacement
 problem for complex multi-component systems. To maintain revenue stream
 resulting from system, the system is inspected according to a homogeneous
 Poisson process and certain actions are carried out in response to the
 system state. Decisions are based on a performance measure described by a
 Squared Bessel process. Given some assumption, we explore the inherent
 relation between the Squared Bessel process and an extended Gamma (EG)
 process. Since there are some flow of income and increasing costs due to
 inspections, the problem is to optimally stop processing the system and
 carrying out a renewal to maximize the reward functional. To this end,
 using the local characteristics of the EG process as a stopping criterion
 and the expected total discounted reward as a measure of policy, this
 paper aims at determining an optimal operating (stopping) time which truly
 balances both income and cost and so maximizes the expected discounted
 reward over a cycle. In support of the model a numerical example is
 provided to show feasibility of this programme in real application.
 Attention is restricted to perfect repair and inspection, but the paper
 provides the structure so that different scenarios can be explored.
Journal: International Journal of Production Research 
Pages: 5303-5316 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1173252 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173252 
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Template-Type: ReDIF-Article 1.0
Author-Name: Salma Karray 
Author-X-Name-First: Salma 
Author-X-Name-Last: Karray 
Author-Name: Chirag Surti 
Author-X-Name-First: Chirag 
Author-X-Name-Last: Surti 
Title: Channel coordination with quantity discounts and/or cooperative advertising 
Abstract:
 We assess the interactive effects of two commonly used channel
 coordination mechanisms (quantity discounts (QDs) and cooperative
 advertising (CA)). We use a game-theoretic model and solve four
 non-cooperative games. In the first game, neither QDs nor CA is
 implemented. Cooperative advertising alone is offered in the second game,
 while quantity discounts alone are offered in the third game. In the
 fourth game, both QDs and CA are implemented. We obtain analytical
 solutions and compare equilibrium results across games to assess the
 effectiveness of CA (QDs) when implemented alone or jointly with QDs (CA).
 The main findings suggest that the profitability of each of these
 mechanisms is affected by whether the other is implemented or not in the
 channel. For example, while CA benefits the manufacturer when implemented
 alone, it can increase or decrease the manufacturer&#x2019;s profit when
 added to QDs. Looking at which coordination mechanism is most effective
 when used alone, we find that both the manufacturer and the supply chain
 prefer QDs to CA. Finally, the retailer may not benefit from either one or
 both of these coordination mechanisms, especially if marketing efforts are
 not highly effective.
Journal: International Journal of Production Research 
Pages: 5317-5335 
Issue: 17 
Volume: 54 
Year: 2016 
Month: 9 
X-DOI: 10.1080/00207543.2016.1173253 
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173253 
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Template-Type: ReDIF-Article 1.0
Author-Name: He Huang
Author-X-Name-First: He
Author-X-Name-Last: Huang
Author-Name: Qiuling Meng
Author-X-Name-First: Qiuling
Author-X-Name-Last: Meng
Author-Name: Hongyan Xu
Author-X-Name-First: Hongyan
Author-X-Name-Last: Xu
Author-Name: Yu Zhou
Author-X-Name-First: Yu
Author-X-Name-Last: Zhou
Title: Cost information sharing under competition in remanufacturing
Abstract: 
 Third-party remanufacturers (TPRs) enter the market and compete with original equipment manufacturers (OEMs). Because of multiple uncertainty of the remanufacturing process, the variable remanufacturing cost is random and its true value cannot be observed by OEMs. In this paper, we consider the competition between one TPR and one OEM, and then investigate incentives of cost information sharing. The remanufactured product quantity is constrained by the new product quantity. If the new production cost is low enough such that the optimal remanufactured product quantity is less than the optimal new product quantity, the TPR should always share cost information with the OEM so that their quantity decisions in equilibrium are more responsive to market conditions to avoid overproduction or underproduction. However, if the quantity constraint is binding, the TPR should not always share cost information; in this case, cost information sharing can allow the OEM to adjust the new product quantity to limit remanufacturing and hence be detrimental to the TPR. When the TPR does not voluntarily share cost information, we further examine the impacts of private information on the society and the environment, and then suggest the government to promote information sharing and subsidise the TPR under certain conditions.
Journal: International Journal of Production Research
Pages: 6579-6592
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1567952
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1567952
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Template-Type: ReDIF-Article 1.0
Author-Name: Behnam Bahrami
Author-X-Name-First: Behnam
Author-X-Name-Last: Bahrami
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Author-Name: Veronique Limère
Author-X-Name-First: Veronique
Author-X-Name-Last: Limère
Title: Enhancing the order picking process through a new storage assignment strategy in forward-reserve area
Abstract: 
 This paper reexamines the order picking process in a warehouse facing the challenges that e-commerce brings about and which are characterised by a very large number of small sized orders and returns. Implementing effective storage assignment strategies combined with efficient batching, in this context, is very fundamental to keep the warehouse’s responsiveness and order completion times up to the standards. This paper investigates a new storage assignment strategy, initially implemented by a large shoes and footwear wholesaler, to enhance the performance of the order picking process in its warehouses. The impact of this new storage assignment strategy on the performance of the order picking process is analysed via simulation. The performance of the system, measured in terms of total picking time as well as order lead time while taking congestion into account, is compared to the cases where conventional storage assignment strategies are implemented. A full factorial design is set up and the simulation output is statistically analysed. The results of this analysis are reported and thoroughly discussed. Attending to the results, the proposed strategy presents a remarkable potential to shorten total picking travel distances and order completion time and consequently customer satisfaction.
Journal: International Journal of Production Research
Pages: 6593-6614
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1567953
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1567953
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Template-Type: ReDIF-Article 1.0
Author-Name: Hu Yu
Author-X-Name-First: Hu
Author-X-Name-Last: Yu
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Title: Optimising two dwell point policies for AS/RSs with input and output point at opposite ends of the aisle
Abstract: 
 Automated storage and retrieval systems (AS/RSs) are widely used for storing and retrieving products in all types of warehouses. Dwell point policy is a vital control policy that can greatly affect the performance of AS/RSs. In this paper, we study dwell point policies in AS/RSs with input and output stations at opposite ends of the aisle. We first propose two dwell point policies. We find that five existing dwell point policies in the literature are special cases of exactly one of our policies. We then develop expected travel time models for the proposed policies, solve these models with the objective of minimising expected travel time, and obtain closed-form solutions for the optimal dwell location(s). We prove that one proposed policy dominates the other in terms of expected travel time. Numerical experiments are performed to quantify the percentage gap of expected travel time between the proposed policies and policies in the literature. We find that, in some situations, the better proposed policy can achieve up to 8%–10% reduction in expected travel time in comparison with the best literature policy. A real-data case study validates that these situations arise with high probability in typical daily warehouse operations.
Journal: International Journal of Production Research
Pages: 6615-6633
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1570377
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1570377
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Template-Type: ReDIF-Article 1.0
Author-Name: Chin-Chia Wu
Author-X-Name-First: Chin-Chia
Author-X-Name-Last: Wu
Author-Name: Ameni Azzouz
Author-X-Name-First: Ameni
Author-X-Name-Last: Azzouz
Author-Name: I-Hong Chung
Author-X-Name-First: I-Hong
Author-X-Name-Last: Chung
Author-Name: Win-Chin Lin
Author-X-Name-First: Win-Chin
Author-X-Name-Last: Lin
Author-Name: Lamjed Ben Said
Author-X-Name-First: Lamjed
Author-X-Name-Last: Ben Said
Title: A two-stage three-machine assembly scheduling problem with deterioration effect
Abstract: 
 The two-stage assembly scheduling problem has received growing attention in the research community. Furthermore, in many two-stage assembly scheduling problems, the job processing times are commonly assumed as a constant over time. However, it is at odds with real production situations some times. In fact, the dynamic nature of processing time may occur when machines lose their performance during their execution times. In this case, the job that is processed later consumes more time than another one processed earlier. In view of these observations, we address the two-stage assembly linear deterioration scheduling problem in which there are two machines at the first stage and an assembly machine at the second stage. The objective is to complete all jobs as soon as possible (or to minimise the makespan, implies that the system can yield a better and efficient task planning to limited resources). Given the fact that this problem is NP-hard, we then derive some dominance relations and a lower bound used in the branch-and-bound method for finding the optimal solution. We also propose three metaheuristics, including dynamic differential evolution (DDE), simulated annealing (SA) algorithm, and cloud theory-based simulated annealing (CSA) algorithm for find near-optimal solutions. The performances of the proposed algorithms are reported as well.
Journal: International Journal of Production Research
Pages: 6634-6647
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1570378
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1570378
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Template-Type: ReDIF-Article 1.0
Author-Name: Ezra Wari
Author-X-Name-First: Ezra
Author-X-Name-Last: Wari
Author-Name: Weihang Zhu
Author-X-Name-First: Weihang
Author-X-Name-Last: Zhu
Title: A Constraint Programming model for food processing industry: a case for an ice cream processing facility
Abstract: 
 This paper presents a Constraint Programming (CP) scheduling model for an ice cream processing facility. CP is a mathematical optimisation tool for solving problems either for optimality (for small-size problems) or good quality solutions (for large-size problems). For practical scheduling problems, a single CP solution model can be used to optimise daily production or production horizon extending for months. The proposed model minimises a makespan objective and consists of various processing interval and sequence variables and a number of production constraints for a case from a food processing industry. Its performance was compared to a Mixed Integer Linear Programming (MILP) model from the literature for optimality, speed, and competence using the partial capacity of the production facility of the case study. Furthermore, the model was tested using different product demand sizes for the full capacity of the facility. The results demonstrate both the effectiveness, flexibility, and speed of the CP models, especially for large-scale models. As an alternative to MILP, CP models can provide a reasonable balance between optimality and computation speed for large problems.
Journal: International Journal of Production Research
Pages: 6648-6664
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1571250
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1571250
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Template-Type: ReDIF-Article 1.0
Author-Name: Behnaz Hosseini
Author-X-Name-First: Behnaz
Author-X-Name-Last: Hosseini
Author-Name: Barış Tan
Author-X-Name-First: Barış
Author-X-Name-Last: Tan
Title: Modelling and analysis of a cooperative production network
Abstract: 
 In this study, we examine the cooperative production business model for a group of producers serving their own customers and also have access to external customers who can make an agreement to buy products at a lower price if a desired service level can be guaranteed. When the producers cannot meet the desired service level requirement of the external customers at the offered price on their own, they participate in a cooperative network. The network consolidates the external customers for its members and routes an arriving external customer to one of the participants. We determine the optimal production and rationing policies for each participating manufacturer as well as the optimal routing policy for the network. We also propose an accurate approximate method to analyse a network with a high number of homogeneous producers using a single queue approximation method. We show that, based on the parameters of the producers and the external market, the network can provide the desired service level for the external customers at the offered price and makes all the members increase their profit by better utilising their capacity and serving more external customers.
Journal: International Journal of Production Research
Pages: 6665-6686
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1571254
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1571254
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Template-Type: ReDIF-Article 1.0
Author-Name: Mei-Fang Wu
Author-X-Name-First: Mei-Fang
Author-X-Name-Last: Wu
Author-Name: Hsuan-Yu Chen
Author-X-Name-First: Hsuan-Yu
Author-X-Name-Last: Chen
Author-Name: Tsang-Chuan Chang
Author-X-Name-First: Tsang-Chuan
Author-X-Name-Last: Chang
Author-Name: Chih-Feng Wu
Author-X-Name-First: Chih-Feng
Author-X-Name-Last: Wu
Title: Quality evaluation of internal cylindrical grinding process with multiple quality characteristics for gear products
Abstract: 
 Gears are among the most crucial components in the transmission systems of machine tools. Gear manufacturing includes a number of processing procedures. The grinding process is an important procedure involving high precision and fairly small grinding surfaces. For this reason, this study aimed at developing a quality assessment model for the internal cylindrical grinding process of gears. The Six Sigma quality indices (SSQIs) were used to directly assess the quality of the internal cylindrical grinding process due to their ability to directly reflect quality level and process yield. Since the process may include nominal-the-best (NTB), larger-the-better (LTB) and smaller-the-better (STB) quality characteristics, so we used the variable transformation method to normalise the specifications of each quality characteristic for the convenient and effective management and analysis of process performance for multiple quality characteristics. We then constructed a multi-characteristic process quality analysis chart (MPQAC) to simultaneously assess the quality levels of various quality characteristics. Furthermore, the MPQAC can provide references for process improvement. This ensures the quality of internal cylindrical grinding and enhances the quality of gear and machine tool products. Finally, a real-world application and numerical experiments demonstrate the effectiveness and practical applicability of the proposed method.
Journal: International Journal of Production Research
Pages: 6687-6701
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1567951
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1567951
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Template-Type: ReDIF-Article 1.0
Author-Name: David L. Olson
Author-X-Name-First: David L.
Author-X-Name-Last: Olson
Author-Name: Desheng Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Wu
Author-Name: Yang Shanlin
Author-X-Name-First: Yang
Author-X-Name-Last: Shanlin
Author-Name: James H. Lambert
Author-X-Name-First: James H.
Author-X-Name-Last: Lambert
Title: Complex product manufacturing in the intelligence-connected era
Journal: International Journal of Production Research
Pages: 6702-6704
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1645442
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1645442
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Template-Type: ReDIF-Article 1.0
Author-Name: Sirikarn Chansombat
Author-X-Name-First: Sirikarn
Author-X-Name-Last: Chansombat
Author-Name: Ponnapa Musikapun
Author-X-Name-First: Ponnapa
Author-X-Name-Last: Musikapun
Author-Name: Pupong Pongcharoen
Author-X-Name-First: Pupong
Author-X-Name-Last: Pongcharoen
Author-Name: Christian Hicks
Author-X-Name-First: Christian
Author-X-Name-Last: Hicks
Title: A Hybrid Discrete Bat Algorithm with Krill Herd-based advanced planning and scheduling tool for the capital goods industry
Abstract: 
 Capital goods companies produce high value products such as power plant or ships, which have deep and complex product structures, with components having long process routings. Contracts usually include substantial penalties for late delivery. The high value of items can lead to substantial holding costs. Efficient schedules minimise earliness and tardiness costs and need to satisfy assembly and operation precedence constraints as well as finite capacity. This paper presents the first advanced planning and scheduling (APS) tool for the capital goods industry that uses a Discrete Bat Algorithm (DBA), modified DBA (MDBA) and hybrid DBA with Krill Herd algorithm (HDBK) to optimise schedules. The tool was validated using four data-sets obtained from a collaborating capital goods company. A sequential experimental strategy was adopted. The first experiment identified appropriate parameter settings for the DBA. The second experiment evaluated and compared the performance of the proposed HDBK algorithm with an Artificial Bee Colony, Krill Herd (KH), Modified KH, DBA and MDBA metaheuristics. The experimental results revealed that the HDBK performed best in terms of the minimum penalty cost for all problem sizes and achieved up to a 47.837% reduction in mean total penalty costs of extra-large problem size.
Journal: International Journal of Production Research
Pages: 6705-6726
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2018.1471240
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471240
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Template-Type: ReDIF-Article 1.0
Author-Name: Sebastian Poeschl
Author-X-Name-First: Sebastian
Author-X-Name-Last: Poeschl
Author-Name: Frank Wirth
Author-X-Name-First: Frank
Author-X-Name-Last: Wirth
Author-Name: Thomas Bauernhansl
Author-X-Name-First: Thomas
Author-X-Name-Last: Bauernhansl
Title: Strategic process planning for commissioning processes in mechanical engineering
Abstract: 
 Planning in mechanical engineering is a key factor for a successful product development process. Especially, when it comes to producing machines, planning drastically reduces the risk of failures in either processes or parts. The commissioning process is mainly focusing on adjusting and testing. Thus, commissioning is the process where most of the failures are detected. On the one hand, in literature, the planning of processes has mainly focused on the optimisation of the planned duration of a production process. Durations of errors in processes and possible effects on other processes have not been considered in the literature. On the other hand, risk analyses mainly focus on the minimisation of errors in either processes or products. The goal of this paper is to develop an applicable methodology for the combination of an optimisation of the risk and the duration of a commissioning process in mechanical engineering. The focus is to analyse the planning of a commissioning process and combine it with a methodology to optimise risks and durations. Furthermore, the method is designed to be applicable in all areas of mechanical engineering. The method is validated at the commissioning of special machinery and during ramp-up processes and has shown a possible time reduction of about 40% without increasing the risks of failures.
Journal: International Journal of Production Research
Pages: 6727-6739
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2018.1556408
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1556408
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Template-Type: ReDIF-Article 1.0
Author-Name: Ling Li
Author-X-Name-First: Ling
Author-X-Name-Last: Li
Author-Name: Min Liu
Author-X-Name-First: Min
Author-X-Name-Last: Liu
Author-Name: Weiming Shen
Author-X-Name-First: Weiming
Author-X-Name-Last: Shen
Author-Name: Guoqing Cheng
Author-X-Name-First: Guoqing
Author-X-Name-Last: Cheng
Title: A novel performance evaluation model for MRO management indicators of high-end equipment
Abstract: 
 High-end equipment oriented maintenance, repair and operation (MRO) management is crucial for asset intensive industries. The existing works mainly focus on providing the best possible joint optimisation for production and maintenance management without aiming at the complicated relationships among them. In the intelligence-connected era, the rapid development of Internet of things and big data technologies enables us to access, collect, and store the industrial big data, which is especially necessary for MRO management indicator evaluation, and so we try to apply big data analysis to visualise the system structure of complicated relationships among MRO indicators at different management levels. In this paper, the decision-making trial and evaluation laboratory (DEMATEL) and improved analytical network process (ANP) are applied to build the performance evaluation model for MRO management indicators, in which DEMATEL is utilised to quantify the system structure of different management levels, and the improved ANP is introduced to calculate relative weights of corresponding indicators. The results point out to managers which indicators should deserve more attention in MRO management decision-making as well as joint optimisation for production and maintenance management. A case study illustrates the feasibility and practicality of the proposed model.
Journal: International Journal of Production Research
Pages: 6740-6757
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1566654
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566654
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Template-Type: ReDIF-Article 1.0
Author-Name: Qiang Zhang
Author-X-Name-First: Qiang
Author-X-Name-Last: Zhang
Author-Name: Xiaonong Lu
Author-X-Name-First: Xiaonong
Author-X-Name-Last: Lu
Author-Name: Zhanglin Peng
Author-X-Name-First: Zhanglin
Author-X-Name-Last: Peng
Author-Name: Minglun Ren
Author-X-Name-First: Minglun
Author-X-Name-Last: Ren
Title: Perspective: a review of lifecycle management research on complex products in smart-connected environments
Abstract: 
 Smart-connected technologies, such as the Internet of things and cloud computing, are transforming how industries and enterprises do business by improving the lifecycle management of their product. Therefore, to study the lifecycle management of complex products under smart-connected environment, many studies have been published outlining new methods for smart development, intelligent manufacturing, and data-driven services. This paper first proposes the concept and architecture of smart-connected products and then systematically reviews the current research about new paradigms of product development, manufacturing and services. The paper also summarises the conceptual framework, research issues and opportunities of each phase of the product lifecycle management.
Journal: International Journal of Production Research
Pages: 6758-6779
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1587186
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1587186
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Template-Type: ReDIF-Article 1.0
Author-Name: Sara Markworth Johnsen
Author-X-Name-First: Sara Markworth
Author-X-Name-Last: Johnsen
Author-Name: Lars Hvam
Author-X-Name-First: Lars
Author-X-Name-Last: Hvam
Title: Understanding the impact of non-standard customisations in an engineer-to-order context: A case study
Abstract: 
 Companies operating with an engineer-to-order (ETO) manufacturing strategy produce customised solutions for their customers. While they may be able to build on a base of existing sub-solutions, e.g. standard product structures, modules or parts when engineering a customer-specific solution, they often have to create something completely new to satisfy customers’ requirements. However, it is not always clear to ETO companies what the costs associated with making customer specific solutions are, or which product or project characteristics drive costs and in what business processes. Therefore, it is not clear to companies if it is actually profitable for them to fulfil all of their customers’ requirements. Hence, making it relevant to understand how creating non-standard customisations impact project profitability. This paper presents a framework for how ETO companies can quantify the impact of the complexity associated with non-standard customisations when cost data is only available at the project level. The framework is theoretically founded; it is based on statistical regression and a definition of a complexity index for non-standard customisations. The framework is validated in the context of an ETO case company and empirical data is presented.
Journal: International Journal of Production Research
Pages: 6780-6794
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2018.1471239
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471239
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Template-Type: ReDIF-Article 1.0
Author-Name: Hao Wang
Author-X-Name-First: Hao
Author-X-Name-Last: Wang
Author-Name: Shuai Ding
Author-X-Name-First: Shuai
Author-X-Name-Last: Ding
Author-Name: Desheng Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Wu
Author-Name: Youtao Zhang
Author-X-Name-First: Youtao
Author-X-Name-Last: Zhang
Author-Name: Shanlin Yang
Author-X-Name-First: Shanlin
Author-X-Name-Last: Yang
Title: Smart connected electronic gastroscope system for gastric cancer screening using multi-column convolutional neural networks
Abstract: 
 Gastroscopy is a widely adopted method for gastric cancer screening and early diagnosis. Clinical studies show that it can effectively prolong patient life and maximise therapeutic effect. However, it is difficult for doctors to identify and detect lesions in real time, which manifests as the major challenge in gastroscopy. In this paper, we propose SCEG, a smart connected electronic gastroscopy system that performs dynamic cancer screening in gastroscopy. By integrating electronic gastroscopy with cloud-based medical image analysis service, we develop an AdaBoost-based multi-column convolutional neural network (MCNN) for enhancing gastric cancer screening. Experimental results show that the proposed MCNN approach significantly outperforms other competing approaches.
Journal: International Journal of Production Research
Pages: 6795-6806
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2018.1464232
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1464232
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Template-Type: ReDIF-Article 1.0
Author-Name: Juan Liu
Author-X-Name-First: Juan
Author-X-Name-Last: Liu
Author-Name: Fei Qiao
Author-X-Name-First: Fei
Author-X-Name-Last: Qiao
Author-Name: Weichang Kong
Author-X-Name-First: Weichang
Author-X-Name-Last: Kong
Title: Scenario-based multi-objective robust scheduling for a semiconductor production line
Abstract: 
 Scheduling problems of semiconductor manufacturing systems (SMS) with the goal of optimising some classical performance indices (NP-hard), tend to be increasingly complicated due to stochastic uncertainties. This paper targets the robust scheduling problem of an SMS with uncertain processing times. A three-stage multi-objective robust optimisation (MORO) approach is proposed, that can collaboratively optimise the performance indices and their robustness measures. In the first stage, this paper studies the scheduling problem in the deterministic environment and obtains feasible scheduling strategies that perform well in four performance indices (the average cycle time (CT), the on-time delivery rate (ODR), the throughput (TP), and the total movement amount of wafers (MOV)). Then, in the second stage, the uncertainties are introduced into the production system. In the third stage, this paper proposes a hybrid method consisting of scenario planning, discrete simulation, and multi-objective optimisation to obtain an approximately and more robust optimal solution from the feasible scheduling strategy set. The proposed MORO approach is tested in a semiconductor experiment production line and makes a full analysis to illustrate the effectiveness of our method. The results show that our MORO is superior concerning the total robustness with multi-objective.
Journal: International Journal of Production Research
Pages: 6807-6826
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1641234
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641234
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Template-Type: ReDIF-Article 1.0
Author-Name: Salman Kimiagari
Author-X-Name-First: Salman
Author-X-Name-Last: Kimiagari
Author-Name: Samira Keivanpour
Author-X-Name-First: Samira
Author-X-Name-Last: Keivanpour
Title: An interactive risk visualisation tool for large-scale and complex engineering and construction projects under uncertainty and interdependence
Abstract: 
 Implementation of the megaprojects with large-scale engineering and construction projects are risky in nature and evaluating the associated risks of those large projects is a critical success factor. The systematic approaches and empirical studies related to the visualisation and communicating risks of these projects remain missing. This paper aims to develop a systematic approach to managing and visualising the risk of these mega-projects using joint application of fuzzy group decision-making, analytic network process and mapping the resulting network of dependencies together with proximity information, graph theory, and mutual information theory. We have applied the model in a real case study of megaprojects in the oil and gas industry. The methodology proposed in this study could be used in the other large-scale engineering and construction projects considering the contracts features and the contextual factors.
Journal: International Journal of Production Research
Pages: 6827-6855
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2018.1503426
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1503426
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Template-Type: ReDIF-Article 1.0
Author-Name: Iain Reid
Author-X-Name-First: Iain
Author-X-Name-Last: Reid
Author-Name: David Bamford
Author-X-Name-First: David
Author-X-Name-Last: Bamford
Author-Name: Hossam Ismail
Author-X-Name-First: Hossam
Author-X-Name-Last: Ismail
Title: Reconciling engineer-to-order uncertainty by supporting front-end decision-making
Abstract: 
 This paper presents the dynamics of engineer-to-order (ETO) practice through Integration Definition for Function Modelling (IDEF) practice. The paper describes and defines how an ETO manufacturer utilised IDEF-QA in order to manage project uncertainties within the tendering process. The research is conceptualised through an empirical action research approach, involving an active role in the assessment of the ETO process. The paper revisits the use of IDEF, showcasing an assessment of output quality. It also suggests a road map for resource uncertainty within ETO, specifically when scoping the supply chain for ETO projects. The paper then presents an IDEF Quality Assessment model for improving the tendering process of ETO, and it examines the importance of evaluating project behaviour for supporting new future projects. The principal contribution is in how a structured approach provides IDEF with a quality assessment of resources, thereby consolidating and establishing a relationship for highlighting the uncertainties experienced by ETO manufacturers within the decision-making process.
Journal: International Journal of Production Research
Pages: 6856-6874
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2018.1552370
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1552370
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Template-Type: ReDIF-Article 1.0
Author-Name: Dexiang Wu
Author-X-Name-First: Dexiang
Author-X-Name-Last: Wu
Author-Name: Desheng Dash Wu
Author-X-Name-First: Desheng Dash
Author-X-Name-Last: Wu
Author-Name: Roy H. Kwon
Author-X-Name-First: Roy H.
Author-X-Name-Last: Kwon
Title: Optimising data-driven network under limited resource: a partial diversification approach
Abstract: 
 This paper describes a cardinality constrained network flow structure whose special characteristics are used to analyse different risk aspects under an environment of uncertainty. The network structure developed is a suitable alternative to support financial planning and many other decision-making problems with limited resources. By setting a diversification level, we can manage systematic and non-systematic risks under a stochastic mixed integer linear programming framework. A dual decomposition method, Progressive Hedging (PH), is applied to more efficiently accommodate instances with large numbers of scenarios. We studied the impact of the level of the diversification on transaction costs and considered different factors that influence the performance of the algorithm. In particular, a Lagrangian bound is embedded to enhance the capacity of the method. Numerical results show the effectiveness of the proposed decision support approach.
Journal: International Journal of Production Research
Pages: 6875-6892
Issue: 21
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2018.1508901
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1508901
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Template-Type: ReDIF-Article 1.0
Author-Name: Jia Huang
Author-X-Name-First: Jia
Author-X-Name-Last: Huang
Author-Name: Xiao-Yue You
Author-X-Name-First: Xiao-Yue
Author-X-Name-Last: You
Author-Name: Hu-Chen Liu
Author-X-Name-First: Hu-Chen
Author-X-Name-Last: Liu
Author-Name: Sheng-Li Si
Author-X-Name-First: Sheng-Li
Author-X-Name-Last: Si
Title: New approach for quality function deployment based on proportional hesitant fuzzy linguistic term sets and prospect theory
Abstract: 
 As a powerful instrument to fulfil customer needs, quality function deployment (QFD) is capable of converting customer requirements (CRs) into appropriate engineering characteristics (ECs) in the product design and development. Nevertheless, the inherent defects of the conventional QFD, such as the description of experts’ opinions with crisp numbers and the non-robust ranking of ECs, confine its efficiency and potential applications. In this study, a novel QFD approach using proportional hesitant fuzzy linguistic term sets (PHFLTSs) and prospect theory is proposed to overcome the insufficiencies of the traditional QFD. Specifically, the relationships between CRs and ECs are represented by PHFLTSs and the weights of CRs are derived with the best-worst method (BWM). An extended prospect theory is employed for the prioritisation of the ECs that have been identified. Finally, two application examples are provided to examine the applicability and advantages of our proposed QFD approach.
Journal: International Journal of Production Research
Pages: 1283-1299
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1470343
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1470343
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Template-Type: ReDIF-Article 1.0
Author-Name: Yaoan A. Lu
Author-X-Name-First: Yaoan A.
Author-X-Name-Last: Lu
Author-Name: Ye Ding
Author-X-Name-First: Ye
Author-X-Name-Last: Ding
Author-Name: Chengyong Wang
Author-X-Name-First: Chengyong
Author-X-Name-Last: Wang
Author-Name: Limin Zhu
Author-X-Name-First: Limin
Author-X-Name-Last: Zhu
Title: Tool path generation for five-axis machining of blisks with barrel cutters
Abstract: 
 A barrel cutter has a cutting segment with a large radius on its profile, and this arc segment allows the cutter to tilt away from the part surface, avoiding the collisions of the tool with the part. Therefore, barrel cutters are suitable for five-axis blisk machining. However, the barrel cutters are more challenging for CAM software to generate paths. A method of generating collision-free and large-machining width flank milling paths with smooth axes movements for blisk machining with barrel cutters is proposed. Local gouge between the tool flute surface and the blade to be machined is considered, and the collisions of the blisk with the non-cutting parts of the tool, i.e. tool shank and holder, are also detected. The machined part geometry is the complement of the cutter’s swept envelope from the stock. Accordingly, the swept profile of the cutter at each cutter contact point is employed to evaluate the machining width naturally. Thereafter, a multi-criteria tool path generation model is established, and it is converted into a single-objective optimization with the weighted sum method. An algorithm based on the Differential Evolution algorithm is developed to solve this model. The numerical example illustrates the effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 1300-1314
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1470344
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1470344
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Template-Type: ReDIF-Article 1.0
Author-Name: Simon Emde
Author-X-Name-First: Simon
Author-X-Name-Last: Emde
Author-Name: Shohre Zehtabian
Author-X-Name-First: Shohre
Author-X-Name-Last: Zehtabian
Title: Scheduling direct deliveries with time windows to minimise truck fleet size and customer waiting times
Abstract: 
 This paper tackles the operational problem of scheduling direct deliveries from a single source (e.g. a distribution centre) to multiple customers (e.g. assembly plants). The problem consists of scheduling a set of given round trips such that each trip is processed exactly once within its time window and the employed truck fleet is as small as possible. Moreover, as a secondary objective, customer waiting times should be minimal. Such planning problems arise in many industries like, for instance, the automotive industry, where just-in-time parts are often shipped via direct delivery to OEMs. We propose two different mixed-integer programming models for this problem, discuss similarities to classic routing and scheduling problems from the literature, identify a subproblem that is solvable in polynomial time and propose suitable heuristics. In a computational study, the proposed procedures are shown to perform well both on newly generated instances as well as those from the literature. We also show that minimising waiting times is an adequate measure to make schedules more robust in the face of unforeseen disturbances.
Journal: International Journal of Production Research
Pages: 1315-1330
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1470696
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1470696
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Template-Type: ReDIF-Article 1.0
Author-Name: Arash Geramian
Author-X-Name-First: Arash
Author-X-Name-Last: Geramian
Author-Name: Ajith Abraham
Author-X-Name-First: Ajith
Author-X-Name-Last: Abraham
Author-Name: Mojtaba Ahmadi Nozari
Author-X-Name-First: Mojtaba
Author-X-Name-Last: Ahmadi Nozari
Title: Fuzzy logic-based FMEA robust design: a quantitative approach for robustness against groupthink in group/team decision-making
Abstract: 
 Group/team decision-making is an integral part of almost all failure mode and effects analysis (FMEA) projects. A dysfunctional aspect of this decision-making fashion in fuzzy FMEA is that group/team members’ designs for membership functions and IF-THEN rules may be overshadowed by a member’s design. This problem is caused by groupthink, a pitfall known by the Organisational Behaviour science. This study aims to develop a fuzzy FMEA approach which is robust to the problem. We applied the Taguchi’s robust parameter design and investigated the effects of various control parameters namely Defuzzification, Aggregation, And and Implication operators for the fuzzy inference system (FIS). Our experiments illustrate that the control parameters, in the above-mentioned order, have the most effect on the signal-to-noise ratio (SNR). These factors’ optimal setting consists of the Centroid, Sum, Minimum and Minimum levels, respectively.
Journal: International Journal of Production Research
Pages: 1331-1344
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1471236
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471236
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:5:p:1331-1344




Template-Type: ReDIF-Article 1.0
Author-Name: Rakesh Venkitasubramony
Author-X-Name-First: Rakesh
Author-X-Name-Last: Venkitasubramony
Author-Name: Gajendra K. Adil
Author-X-Name-First: Gajendra K.
Author-X-Name-Last: Adil
Title: Designing a block stacked warehouse for dynamic and stochastic product flow: a scenario-based robust approach
Abstract: 
 The problem considered in this paper is motivated from a real life case. Conventional models in designing block stacked warehouse assume uniform and deterministic inflow and outflow of products in specific quantities and time intervals. These assumptions would lead to underestimation of space requirement for the case. Also, the possibility of leasing additional warehouse space during seasonal spikes was found to be unexplored in block stacking design literature. In this study, we develop a scenario-based model to address the decisions of warehouse size, lane depth and hiring of temporary additional warehouse capacity when flow of products is stochastic and dynamic in nature. A sequential decision model is presented with future operating scenarios assumed to branch out in the form of a tree. On comparison with conventional block stacking design methods, the model is found to provide robust solution in stochastic and dynamic environments in terms of risk reduction and infeasibility avoidance. Further, the model gives additional flexibility to the designer to trade-off model and solution robustness with predicted cost.
Journal: International Journal of Production Research
Pages: 1345-1365
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1472402
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1472402
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Template-Type: ReDIF-Article 1.0
Author-Name: W.L. Pearn
Author-X-Name-First: W.L.
Author-X-Name-Last: Pearn
Author-Name: Chen-ju Lin
Author-X-Name-First: Chen-ju
Author-X-Name-Last: Lin
Author-Name: Y.H. Chen
Author-X-Name-First: Y.H.
Author-X-Name-Last: Chen
Author-Name: J.Y. Huang
Author-X-Name-First: J.Y.
Author-X-Name-Last: Huang
Title: A note on Group Selection with multiple quality characteristics: power comparison of two methods
Abstract: 
 The Group Selection problem is an essential problem in the supplier selection process. The objective of the problem is to select a subset of suppliers containing the best among multiple candidate suppliers. Manufacturers should procure parts from the selected suppliers to produce high-quality products. Lin, C.J., W.L. Pearn, J.Y. Huang, and Y.H. Chen [2017. “Group Selection for Processes with Multiple Quality Characteristics.” Communications in Statistics – Theory and Methods. doi:10.1080/03610926.2017.1364392] considered the problem under multiple quality characteristics, and proposed the Modified Bonferroni method and the Multiple Comparisons with the Best (MCB) method to tackle the problem. The two methods, however, may select different subset containing the best depending on the magnitude of the differences among the k estimated $C_{\,pk}^T$CpkT index values. In this paper, we derive the power function for the Modified Bonferroni method, and compare the power of the two methods with extensive simulations. The results show that the MCB method is more powerful than the Modified Bonferroni method when the actual number of the best process is one. On the other hand, the Modified Bonferroni method significantly outperforms the MCB method when the actual number of the best process is greater than one. The results provide practitioners with useful reference about the properties of the two methods for supplier selection.
Journal: International Journal of Production Research
Pages: 1366-1370
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1476788
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1476788
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Template-Type: ReDIF-Article 1.0
Author-Name: Christina Arampantzi
Author-X-Name-First: Christina
Author-X-Name-Last: Arampantzi
Author-Name: Ioannis Minis
Author-X-Name-First: Ioannis
Author-X-Name-Last: Minis
Author-Name: Georgios Dikas
Author-X-Name-First: Georgios
Author-X-Name-Last: Dikas
Title: A strategic model for exact supply chain network design and its application to a global manufacturer
Abstract: 
 This paper presents a comprehensive model that captures significant strategic decisions involved in designing or redesigning high-performance supply chains from the perspective of the manufacturer. The problem considers deterministic demand by multiple clients, for multiple products, over the periods of a long-term horizon. The design decisions involve selection of suppliers, establishment or resizing of production facilities and distribution centres, possible subcontracting of related activities, and selection of transportation modes and routes. The problem is formulated by a Mixed Integer Linear Programming model. Its objective is to minimise the overall costs associated with procurement, production, inventory, warehousing, and transportation over the design horizon. Appropriate constraints model the complex relationships among the links of the supply chain. The proposed model has been applied to a large case study of a global manufacturing firm, providing valuable insights into the transformation of the firm’s current supply chain network, as well as into the potential of the proposed approach.
Journal: International Journal of Production Research
Pages: 1371-1397
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1489155
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1489155
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Template-Type: ReDIF-Article 1.0
Author-Name: JianChao Luo
Author-X-Name-First: JianChao
Author-X-Name-Last: Luo
Author-Name: ZhiQiang Liu
Author-X-Name-First: ZhiQiang
Author-X-Name-Last: Liu
Author-Name: KeYi Xing
Author-X-Name-First: KeYi
Author-X-Name-Last: Xing
Title: Hybrid branch and bound algorithms for the two-stage assembly scheduling problem with separated setup times
Abstract: 
 This article proposes hybrid branch and bound algorithms to minimise the makespan for the two-stage assembly scheduling problem with separated setup times. In the studied problem, there are multiple machines at the first stage, each of which produces a component of a job. When all components are available, a single assembly machine at the second stage completes the job. Existing algorithms are based on the state space search and hence suffer from the state space explosion problem. In order to reduce the search space, lower and upper bounds for a partial schedule are proposed. Also, a heuristic function and a dominance rule are developed to guide the search process. Moreover, accelerated factors are introduced to increase the speed of the search. Experimental results indicate that our algorithms outperform an existing method, and can find the optimal or near-optimal schedules in a short time for all tested problems with up to ten thousand jobs and nine first-stage machines.
Journal: International Journal of Production Research
Pages: 1398-1412
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1489156
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1489156
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Template-Type: ReDIF-Article 1.0
Author-Name: Horst Tempelmeier
Author-X-Name-First: Horst
Author-X-Name-Last: Tempelmeier
Author-Name: Lars Fischer
Author-X-Name-First: Lars
Author-X-Name-Last: Fischer
Title: A procedure for the approximation of the waiting time distribution in a discrete-time (r, S) inventory system
Abstract: 
 We study a single-item periodic review $\lpar r\comma \;S\rpar $(r,S) inventory policy. Demands arrive on a discrete (e.g. daily) time axis. This is the time model underlying the Advanced Planning Software systems used for supply chain management in industrial practice. We present a procedure for the calculation of the probability distribution of the customer waiting time. We discuss optimisation problems which can be solved on the basis of the probability distribution of the waiting time.
Journal: International Journal of Production Research
Pages: 1413-1426
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1489157
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1489157
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Template-Type: ReDIF-Article 1.0
Author-Name: Mourad Benttaleb
Author-X-Name-First: Mourad
Author-X-Name-Last: Benttaleb
Author-Name: Faicel Hnaien
Author-X-Name-First: Faicel
Author-X-Name-Last: Hnaien
Author-Name: Farouk Yalaoui
Author-X-Name-First: Farouk
Author-X-Name-Last: Yalaoui
Title: Minimising the makespan in the two-machine job shop problem under availability constraints
Abstract: 
 Classical scheduling problem assumes that machines are available during the scheduling horizon. This assumption may be justified in some situations but it does not apply if maintenance requirements, machine breakdowns or other availability constraints have to be considered. In this paper, we treat a two-machine job shop scheduling problem with one availability constraint on each machine to minimise the maximum completion time (makespan). The unavailability periods are known in advance and the processing of an operation cannot be interrupted by an unavailability period (non-preemptive case). We present in our approach properties dealing with permutation dominance and the optimality of Jackson's rule under availability constraints. In order to evaluate the effectiveness of the proposed approach, we develop two mixed integer linear programming models and two schemes for a branch and bound method to solve the tackled problem. Computational results validate the proposed approach and prove the efficiency of the developed methods.
Journal: International Journal of Production Research
Pages: 1427-1457
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1489160
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1489160
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Template-Type: ReDIF-Article 1.0
Author-Name: Fu Gu
Author-X-Name-First: Fu
Author-X-Name-Last: Gu
Author-Name: Jianfeng Guo
Author-X-Name-First: Jianfeng
Author-X-Name-Last: Guo
Author-Name: Philip Hall
Author-X-Name-First: Philip
Author-X-Name-Last: Hall
Author-Name: Xinjian Gu
Author-X-Name-First: Xinjian
Author-X-Name-Last: Gu
Title: An integrated architecture for implementing extended producer responsibility in the context of Industry 4.0
Abstract: 
 Extended producer responsibility (EPR) is a regulatory measure to enforce the life cycle management of electrical and electronic equipment, however, the implementation of EPR programmes is not as effective as expected. In the face of the fourth industrial revolution that commonly labelled as ‘Industry 4.0,’ this paper proposes an integrated architecture to achieve effective and efficient EPR from the manufacturer perspective, and attention is specifically paid on promoting information sharing. On the basis of the selected case study, a smart refrigerator plant of Haier, the architecture integrates information systems and facilitates life cycle management. Particularly, eco-design and end-of-life disposal, the two lasting problems in the current practises of implementing EPR, can be enforced based on product modularisation and high level of information availability that provided by the architecture. The outcomes of this study provide a valuable reference for other sectors that involve EPR or product life cycle management.
Journal: International Journal of Production Research
Pages: 1458-1477
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1489161
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1489161
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Template-Type: ReDIF-Article 1.0
Author-Name: Atanu Chaudhuri
Author-X-Name-First: Atanu
Author-X-Name-Last: Chaudhuri
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Title: A socio-technical view of performance impact of integrated quality and sustainability strategies
Abstract: 
 This research seeks to examine the direct effects of social and technical integration on deployment of quality and sustainability management programmes and the indirect effect of those on quality and sustainability performance. We also seek to test the spillover effects of quality and sustainability management programmes on sustainability and quality performance, respectively. Socio-technical systems (STSs) theory is used to test the role of social and technical integration on quality and sustainability management programmes. The framework of integrated management system, as supported by both STSs and complementarity theory, is used to test the direct and spillover effects of quality and sustainability management programmes. A large multi-country sample is used to empirically test our theory-induced hypotheses. The findings support that social and technical integration are indeed significant enablers for the positive relationships that quality and sustainability programmes have on quality performance and sustainability performance. Specifically, the results show that while social integration has both direct and indirect effects on quality and sustainability performance, technical integration impacts quality and sustainability performance only through the mediation effect of the respective programmes. The results do not support the spillover effects of quality and sustainability management programmes on sustainability and quality performance. Implications of the findings on academic knowledge and managerial practice are offered.
Journal: International Journal of Production Research
Pages: 1478-1496
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1492162
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1492162
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehrdad Mohammadi
Author-X-Name-First: Mehrdad
Author-X-Name-Last: Mohammadi
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Claude Yugma
Author-X-Name-First: Claude
Author-X-Name-Last: Yugma
Title: Performance evaluation of single and multi-class production systems using an approximating queuing network
Abstract: 
 Performance evaluation, and in particular cycle time estimation, is critical to optimise production plans in high-tech manufacturing industries. This paper develops a new aggregation model based on queuing network, so-called queue-based aggregation (QAG) model, to estimate the cycle time in a production system. Multiple workstations in serial and job-shop configurations are aggregated into a single-step workstation. The parameters of the aggregated workstation are approximated based on the parameters of the original workstations. Numerical experiments indicate that the proposed QAG model is computationally efficient and yields fairly accurate results when compared to other aggregation approaches in the literature.
Journal: International Journal of Production Research
Pages: 1497-1523
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1492163
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1492163
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Template-Type: ReDIF-Article 1.0
Author-Name: Mengdi Zhang
Author-X-Name-First: Mengdi
Author-X-Name-Last: Zhang
Author-Name: Yufang Fu
Author-X-Name-First: Yufang
Author-X-Name-Last: Fu
Author-Name: Zhiheng Zhao
Author-X-Name-First: Zhiheng
Author-X-Name-Last: Zhao
Author-Name: Saurabh Pratap
Author-X-Name-First: Saurabh
Author-X-Name-Last: Pratap
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Game theoretic analysis of horizontal carrier coordination with revenue sharing in E-commerce logistics
Abstract: 
 This paper proposes comparisons among two different competitive power structures with and without horizontal coordination. We conduct a game theoretic analysis on the situation where two logistics service providers compete in an e-commerce logistics market with respect to the order quantity and service level decision on a particular logistics service product. Under a consumer utility-based demand, we acquire the equilibrium order quantity decisions and optimal profits under the centralised setting and decentralised setting. An analytical model is established to examine the existence of the Nash equilibrium in the service game. We then prove that the logistics service demand depends on different competitive power structures with the establishment of Cournot game and Stackelberg game model. The analytical results and the equilibrium analysis of the e-commerce logistics system are investigated. After that, we compare the equilibrium results among the centralised system, Cournot game, and Stackelberg game. To empower the horizontal carrier coordination, we design a revenue sharing contract for the decentralised model. A numerical study illustrates the impact of parameters on the optimal decision variables. In this paper, we prove the effectiveness of horizontal carrier collaboration and explicate the reason for the lower marginal profit in logistics theoretically.
Journal: International Journal of Production Research
Pages: 1524-1551
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1492754
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1492754
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Template-Type: ReDIF-Article 1.0
Author-Name: Ana Esteso
Author-X-Name-First: Ana
Author-X-Name-Last: Esteso
Author-Name: Josefa Mula
Author-X-Name-First: Josefa
Author-X-Name-Last: Mula
Author-Name: Francisco Campuzano-Bolarín
Author-X-Name-First: Francisco
Author-X-Name-Last: Campuzano-Bolarín
Author-Name: MME Alemany Diaz
Author-X-Name-First: MME Alemany
Author-X-Name-Last: Diaz
Author-Name: Angel Ortiz
Author-X-Name-First: Angel
Author-X-Name-Last: Ortiz
Title: Simulation to reallocate supply to committed orders under shortage
Abstract: 
 This article aims to deal with the reallocating supply problem in both its real and planned contexts, to orders that result from the order promising process under shortage. To this end, we propose a system dynamics-based simulation model to facilitate modelling for order managers, and to provide a graphic support tool to understand the process and to make decisions. The basis of the simulation model’s structure is a mixed-integer linear programming approach that intends to maximise profits by considering the possibility of making partial and delayed deliveries. To illustrate this, we consider a real-world problem from the ceramic sector that contemplates 35 orders. We obtained a solution by a mathematical programming model and a simulation model. The results show the simulation model’s capacity to obtain near-optimum results, and to provide a simulated history of the system.
Journal: International Journal of Production Research
Pages: 1552-1570
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1493239
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1493239
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcos Paulo Valadares de Oliveira
Author-X-Name-First: Marcos Paulo Valadares de
Author-X-Name-Last: Oliveira
Author-Name: Robert Handfield
Author-X-Name-First: Robert
Author-X-Name-Last: Handfield
Title: Analytical foundations for development of real-time supply chain capabilities
Abstract: 
 The emergence of real-time supply chain visibility technologies has raised challenges for organisations in developing the required management capabilities required to exploit enhanced visibility. The convergence of cloud computing, mobile technology, distributed computing, and data integration technologies has enabled managers for the first time to have real-time visibility of material flows in end to end supply chains, enhancing their ability to identify bottlenecks and disruptions of material flows anywhere in their network. To effectively harness these technologies, a new set of managerial decision-making capabilities as well as enhanced data governance disciplines will be required. In this research, we employ organisational information processing theory to explore the relationship of analytical capabilities, data quality, reporting quality, and real-time data capabilities on supply chain performance. Our research model suggests that the benefits of real-time information technologies are dependent on quality reporting and managerial analytical strengths to derive supply chain benefits. The implications for managerial applications and research are further described based on these findings.
Journal: International Journal of Production Research
Pages: 1571-1589
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1493240
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1493240
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Template-Type: ReDIF-Article 1.0
Author-Name: Arnaud Stimec
Author-X-Name-First: Arnaud
Author-X-Name-Last: Stimec
Author-Name: François Grima
Author-X-Name-First: François
Author-X-Name-Last: Grima
Title: The impact of implementing continuous improvement upon stress within a Lean production framework
Abstract: 
 The purpose of this research is to understand the impact of implementing continuous improvement upon the occupational stress of employees within the framework of Lean management. The outcomes of empirical research mobilising a mixed methodology prove that continuous improvement can help attenuate stress levels, whilst achieving or surpassing economic performance objectives, if its implementation means an effective and satisfactory participation by both employees as well as by management. Conversely, when there is no continuous improvement or it is ill-suited, Lean results in greater stress. These findings confirm the interest in furthering insight into Lean management by moving from a global approach to an approach integrating the effects of its various pillars, especially continuous improvement.
Journal: International Journal of Production Research
Pages: 1590-1605
Issue: 5
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1494391
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1494391
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Template-Type: ReDIF-Article 1.0
Author-Name: Yeu-Shiang Huang
Author-X-Name-First: Yeu-Shiang
Author-X-Name-Last: Huang
Author-Name: Rong-Shuan Ho
Author-X-Name-First: Rong-Shuan
Author-X-Name-Last: Ho
Author-Name: Chih-Chiang Fang
Author-X-Name-First: Chih-Chiang
Author-X-Name-Last: Fang
Title: Quantity discount coordination for allocation of purchase orders in supply chains with multiple suppliers
Abstract: 
 Studies about supply chain coordination have emphasised maximising the profit of the overall supply chain, but the profit changes of individual members in the supply chain have often been overlooked. It has been shown that profit increment of the whole supply chain may not be beneficial for every individual member. Therefore, the use of quantity discounts to achieve the coordination of a supply chain is discussed in this article. A two-echelon selling system with a single buyer and multiple suppliers is considered to enhance profitability for both sides at the same time. An acceptable quantity discount condition for both the buyer and the suppliers to determine an appropriate order quantity allocation to produce more profits in the supply chain is proposed. Furthermore, the profit distribution between the buyer and each supplier is studied. Finally, the results of the numerical application show that the buyer should focus on managing the procurement costs to decrease the acquiring costs, and the suppliers should focus on the fixed costs of management to reduce the production costs in machine operations.
Journal: International Journal of Production Research
Pages: 6653-6671
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1055345
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055345
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Template-Type: ReDIF-Article 1.0
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Xiaoya Han
Author-X-Name-First: Xiaoya
Author-X-Name-Last: Han
Author-Name: Jie Liu
Author-X-Name-First: Jie
Author-X-Name-Last: Liu
Author-Name: Qin Cheng
Author-X-Name-First: Qin
Author-X-Name-Last: Cheng
Title: Supply chain equilibrium among companies with offline and online selling channels
Abstract: 
 This study proposes a supply chain system model containing Nash game companies that compete in a common market. Each company adopts a vertical integration strategy and runs offline and online selling channels. To maximise profits, the companies determine optimal production quantities and prices. Using theory of finite-dimensional variational inequality, we prove the existence and uniqueness of the equilibrium pattern and develop a converged algorithm. Numerically, we compute the equilibrium production quantities and prices, and subsequently generate three findings through sensitivity analyses. By changing the transportation cost, we demonstrate that the offline price is conditionally higher than the online price with different transportation and processing costs. All equilibrium prices and profits decrease when substitution intensity is increased, and thus companies should differentiate their products. Altering consumer preference for online purchasing shows that consumer preference significantly influences the production quantities and profits. Online selling is not positively affected by consumer preference for online purchasing but is affected by the complex relationship between consumer preference and its variable cost.
Journal: International Journal of Production Research
Pages: 6672-6688
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1055350
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055350
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Template-Type: ReDIF-Article 1.0
Author-Name: Kingsley Gnanendran
Author-X-Name-First: Kingsley
Author-X-Name-Last: Gnanendran
Author-Name: Kathleen Iacocca
Author-X-Name-First: Kathleen
Author-X-Name-Last: Iacocca
Title: The point of purchase decision in a supply chain with value-added reselling
Abstract: 
 We explore a stylised decision model in order to better understand the trade-offs inherent in locating the point of purchase on a supply chain. In simple terms, a supply chain can be visualised as a series of value-adding production stages where the end product becomes increasingly differentiated as it travels downstream. The manufacturer is responsible for all processing up to the point of purchase, whereas the buyer (a value-added reseller) is responsible for further processing up to the end of product completion. Product demand becomes more and more uncertain with each downstream stage resulting in ever larger errors in matching demand with supply. Our paper proposes an approach and a model for finding the best location for the interface between the manufacturer and buyer so that the buyer’s expected total profit is maximised, and explores how product characteristics such as configurability and lead time sensitivity of demand might impact the results.
Journal: International Journal of Production Research
Pages: 6689-6700
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1055845
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055845
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:22:p:6689-6700




Template-Type: ReDIF-Article 1.0
Author-Name: Wenjun Ni
Author-X-Name-First: Wenjun
Author-X-Name-Last: Ni
Author-Name: Jia Shu
Author-X-Name-First: Jia
Author-X-Name-Last: Shu
Title: Trade-off between service time and carbon emissions for safety stock placement in multi-echelon supply chains
Abstract: 
 With the low-carbon revolution, many firms face the continuous challenge for reducing carbon emissions in their supply chain activities. Built upon the strategic safety stock placement model, in this paper, we model the carbon emissions for each stage of a multi-echelon supply chain as a function of the service time guaranteed by this stage to its immediate downstream stages. We establish that there is a negative correlation between service time and carbon emissions at each stage. Based on this, we develop two models to study the trade-off between service time and carbon emissions for safety stock placement in multi-echelon supply chains by considering carbon cap and carbon tax, respectively. Both of them are solved using iterative piecewise linear approximations. We implement these two models to study how carbon cap, carbon emission cost rate and guaranteed service time affect the optimal safety stock placement using a real chain.
Journal: International Journal of Production Research
Pages: 6701-6718
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1056319
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056319
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Template-Type: ReDIF-Article 1.0
Author-Name: Ping Cao
Author-X-Name-First: Ping
Author-X-Name-Last: Cao
Author-Name: Mengmeng Fan
Author-X-Name-First: Mengmeng
Author-X-Name-Last: Fan
Author-Name: Ke Liu
Author-X-Name-First: Ke
Author-X-Name-Last: Liu
Title: Optimal dynamic pricing problem considering patient and impatient customers’ purchasing behaviour
Abstract: 
 We divide customers into two types according to their purchasing behaviour: one is impatient and the other is patient. An impatient customer will be immediately lost if his reservation price of the product is below the current price, while a patient customer will wait until the price drops below his reservation price and buy one item. The seller’s objective is to maximise his expected discounted overall revenue by dynamically pricing. We prove that the optimal pricing policy has a control limit structure, examine the impact of the proportion parameter on the seller’s expected discounted overall revenue and show that the limiting behaviour of the optimal pricing policy when there are little patient customers is the same as the optimal static pricing policy. We also show that the seller will make more profit if he partially knows the number of waiting customers by providing subscription service to customers. A set of numerical results illustrates the value of dynamic pricing and information with respect to problem parameters such as the arriving probability and the subscription probability.
Journal: International Journal of Production Research
Pages: 6719-6735
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1056320
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056320
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Template-Type: ReDIF-Article 1.0
Author-Name: Albert Munoz
Author-X-Name-First: Albert
Author-X-Name-Last: Munoz
Author-Name: Michelle Dunbar
Author-X-Name-First: Michelle
Author-X-Name-Last: Dunbar
Title: On the quantification of operational supply chain resilience
Abstract: 
 Operational disruptions impact a supply chain’s ability to match supply and demand. To remain competitive, supply chains need to be resilient and thus capable of rapidly and effectively recovering from operational disruptions. Supply chain resilience is inherently multidimensional, as it spans across multiple tiers, and thus is difficult to quantify. Extant research has measured the transient response through a single-dimension or single-organisation as a proxy for operational resilience. Whilst this greatly simplifies the analysis, it is also potentially misleading, as an erroneous selection of metric(s) may lead to an inaccurate evaluation of the transient response. This research extends the understanding of operational resilience via quantitative evaluation of multiple transient response measures across multiple tiers; the objective being to construct a multidimensional, multi-echelon operational supply chain resilience metric. The study utilises disruptions as experimental inputs for a serial supply chain simulation model; results are obtained for individual measurements of the transient response across multiple supply chain tiers. Analysis indicates that individual dimensions of resilience can adequately explain the transient response at the single-firm level, whilst aggregation of multiple resilience dimensions across multiple tiers has greater capacity to holistically capture the performance response to supply chain disruptions.
Journal: International Journal of Production Research
Pages: 6736-6751
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1057296
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1057296
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Template-Type: ReDIF-Article 1.0
Author-Name: Kanchan Das
Author-X-Name-First: Kanchan
Author-X-Name-Last: Das
Author-Name: Reza S. Lashkari
Author-X-Name-First: Reza S.
Author-X-Name-Last: Lashkari
Title: Risk readiness and resiliency planning for a supply chain
Abstract: 
 This paper proposes supply chain (SC) risk readiness and resiliency measures and formulates a model for planning and controlling select internal business factors to create desired risk resiliency in order to avert potential risks and mitigate their after-effect. SCs may be exposed to events that affect their business operations, and primarily impact the production processes (i.e. production-related risks), or events (such as natural calamities or terrorism) that affect the way the business interacts with the market, and primarily impact the transportation and distribution processes (i.e. market-related risks). Although a business cannot control such disasters as natural calamities or terrorism, it is possible to identify and control the factors that are responsible for production-related risks and that influence several market-related risks or disasters. The proposed model and the measures will guide SCs through the process of identification, planning and controlling the internal factors that make the chain resilient to these various risks. The resiliency measures and the mixed integer programming model will also enable SCs to conduct what-if analyses of cost and performance trade-off options. A numerical example illustrates the planning in typical scenarios.
Journal: International Journal of Production Research
Pages: 6752-6771
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1057624
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1057624
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuheng Cao
Author-X-Name-First: Yuheng
Author-X-Name-Last: Cao
Author-Name: Aaron L. Nsakanda
Author-X-Name-First: Aaron L.
Author-X-Name-Last: Nsakanda
Author-Name: Moustapha Diaby
Author-X-Name-First: Moustapha
Author-X-Name-Last: Diaby
Author-Name: Michael J. Armstrong
Author-X-Name-First: Michael J.
Author-X-Name-Last: Armstrong
Title: Rewards-supply planning under option contracts in managing coalition loyalty programmes
Abstract: 
 We examine the problem of planning the supply of rewards in coalition loyalty programmes considering that the buyer–supplier relationships with commercial partners are governed by option contracts rather than wholesale price contracts similar to what is commonly used in practice. We develop a two-stage stochastic linear programme model with simple recourse which considers uncertain demand requirements, limited reward purchasing budgets, multiple programme partners of various sizes, point-liability control targets and overall profitability. A sampling average approximation scheme is used to solve the model. Numerical experiments show that option contracts perform better than wholesale price contracts when redemption demand uncertainty is high and the number of redemption partners is large. The results also suggest that the common practice of increasing redemption capacities is not the most effective way to cope with demand uncertainties. Programmes that reduce redemption demand variability and/or create better contracting structures are more promising in improving points-liability, redemption budget spending and overall profitability than traditional approaches.
Journal: International Journal of Production Research
Pages: 6772-6786
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1059519
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1059519
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Template-Type: ReDIF-Article 1.0
Author-Name: Deming Zhou
Author-X-Name-First: Deming
Author-X-Name-Last: Zhou
Author-Name: Uday S. Karmarkar
Author-X-Name-First: Uday S.
Author-X-Name-Last: Karmarkar
Author-Name: Bo Jiang
Author-X-Name-First: Bo
Author-X-Name-Last: Jiang
Title: Competition in multi-echelon distributive supply chains with linear demand
Abstract: 
 We studied competition in multi-echelon supply chains with a distributive structure. Firms in the supply chain are grouped into homogeneous sectors that contain identical firms with identical production capabilities that all produce exactly one undifferentiated product. Each sector may distribute its product to several different downstream sectors, and each sector is only supplied by a single upstream sector. The demand curves in final markets are assumed to be linear, as are the variable costs of production in all sectors. Competition is modelled via the successive Cournot model in which firms choose production quantities for their downstream market so as to maximise their own profits, given prices for the input. Under these assumptions, equilibrium prices, quantities and firm-level profits for any multi-echelon distributive network can be derived. We discuss the network transformation properties, and using these properties, we examine the effect of demand parameter changes and cost changes on any firm’s equilibrium price, quantity and profit. We also explore the effects of entry on the equilibrium solution. While the effects of upstream entry on downstream sectors are as expected, the effect of downstream entry on upstream sectors, and therefore on sectors in parallel (lateral) paths, can be quite counter-intuitive.
Journal: International Journal of Production Research
Pages: 6787-6807
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1061223
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1061223
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 6808-6808
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1092300
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1092300
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Template-Type: ReDIF-Article 1.0
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Nachiappan Subramanian
Author-X-Name-First: Nachiappan
Author-X-Name-Last: Subramanian
Author-Name: Shams Rahman
Author-X-Name-First: Shams
Author-X-Name-Last: Rahman
Title: Supply chain resilience: role of complexities and strategies
Abstract: 
 This article introduces the relationship between complexities and proactive management practices in supply chain resilience, particularly due to global sourcing (GS) strategies. The main objectives of this paper are as follows: (i) explain the various aspects of GS rather than reporting the trends and implications described in the literature, (ii) view GS in terms of complexity theory and (iii) investigate the resilience of supply chain due to GS complexity and suggest strategies to overcome complexities. We propose a GS resilience framework for future researchers to analyse the impact of GS complexity factors on supply chain resilience with respect to three outcomes: (i) risk and innovation, (ii) benefit in terms of sales promotion and (iii) challenges and responsiveness. Based on the framework, this introductory article summarises the papers appear in this special issue. This article would be useful to researchers and practitioners to further explore the role of complexities, proactive management strategies on GS resilience.
Journal: International Journal of Production Research
Pages: 6809-6819
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1093667
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1093667
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Template-Type: ReDIF-Article 1.0
Author-Name: Alex Alblas
Author-X-Name-First: Alex
Author-X-Name-Last: Alblas
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Title: Design resilience in the fuzzy front end (FFE) context: an empirical examination
Abstract: 
 This study provides a detailed understanding of the flexibilities that affect performance of innovation projects in the fuzzy front end (FFE) stage. We use the ambidextrous theory approach along with theories on flexibility to propose key drivers of design resilience in innovation projects. A set of six in-depth case studies across a variety of contextual settings is used to investigate important sources of flexibilities that contribute to design resilience. The effects of different design flexibility on the firms’ design resilience are examined. Specifically, an in-depth examination of ‘within case’ trends suggested key design flexibilities to be further examined in the ‘across case’ analyses. Our findings provide valuable insights about the enabling design flexibilities and contextual effects of design resilience in the FFE stage of innovation projects. Based on the findings from the case studies, four sources of design flexibility emerged that vary in terms of their influence on design resilience: (1) iterative learning, (2) modularity, (3) engineering change management and (4) design reuse. Patterns from the ‘across case’ analyses were then used to isolate specific types of design flexibilities that are important for design resilience and organisational resilience. We also provide categorisation of these drivers of design resilience in the context of passive flexibility and active flexibility practices. One of the major contributions of the study is that it provides a detailed categorisation of design resilience in relation to organisational resilience.
Journal: International Journal of Production Research
Pages: 6820-6838
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.899718
File-URL: http://hdl.handle.net/10.1080/00207543.2014.899718
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Template-Type: ReDIF-Article 1.0
Author-Name: Dilek Yilmaz Borekci
Author-X-Name-First: Dilek
Author-X-Name-Last: Yilmaz Borekci
Author-Name: Yasin Rofcanin
Author-X-Name-First: Yasin
Author-X-Name-Last: Rofcanin
Author-Name: Hasan Gürbüz
Author-X-Name-First: Hasan
Author-X-Name-Last: Gürbüz
Title: Organisational resilience and relational dynamics in triadic networks: a multiple case analysis
Abstract: 
 This study aims to analyse resilience and relational dynamics (competitive, cooperative and co-opetitive) within a triadic buyer–supplier–supplier context. Our central goal is to show how a buyer’s supplier–supplier relational behaviour leads to and shapes resilience of this triad. We utilised a multiple-design case approach and selected eight buyers and their suppliers from the textile industry in Turkey. By analysing a triadic context from another industry, we conducted validation analyses. Our findings showed a pattern of relationship between the resilience and the relational dynamics of a triad. Built on theory and insights from the cases, we proposed three propositions. We argued that when co-opetition prevails in a triadic context of relations, the triad resilience level is highest. In competitive relational settings the triad resilience level is lowest, and when the relational dynamics are cooperative, the triad resilience level is moderate. This study is the first to introduce and discuss organisational resilience at triadic level. Furthermore, to our knowledge, our insights from cases are among the first attempts to link three types of supplier–supplier relational dynamics to triad resilience via the use of a multiple-design case approach. Therefore, our contributions are likely to extend the organisational resilience and buyer–supplier–supplier relations research.
Journal: International Journal of Production Research
Pages: 6839-6867
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.903346
File-URL: http://hdl.handle.net/10.1080/00207543.2014.903346
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Template-Type: ReDIF-Article 1.0
Author-Name: Djalma Araújo Rangel
Author-X-Name-First: Djalma Araújo
Author-X-Name-Last: Rangel
Author-Name: Taiane Kamel de Oliveira
Author-X-Name-First: Taiane Kamel
Author-X-Name-Last: de Oliveira
Author-Name: Maria Silene Alexandre Leite
Author-X-Name-First: Maria Silene Alexandre
Author-X-Name-Last: Leite
Title: Supply chain risk classification: discussion and proposal
Abstract: 
 The supply chain management philosophy has often been used by organisations to achieve a competitive advantage, but it increases the vulnerability of these supply chains (SC) to certain risks. This dialogue between competitive advantage and risk generation has increased the number of studies related to the topic of ‘supply chain risk management’. Aiming to contribute to this field of research, a literature survey was conducted on 16 risk classifications, which included 56 risk types. These risk types were sorted according to existing conceptual similarities and then related to the five management processes intrinsic in a functional SC (plan, source, make, deliver and return), which are mainly advocated by the supply chain operations reference model. This literature review also highlights the lack of consensus among the surveyed authors concerning the risk types that affect a SC, a gap which this paper seeks to close by proposing a supply chain risk classification.
Journal: International Journal of Production Research
Pages: 6868-6887
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.910620
File-URL: http://hdl.handle.net/10.1080/00207543.2014.910620
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Template-Type: ReDIF-Article 1.0
Author-Name: Eugene Levner
Author-X-Name-First: Eugene
Author-X-Name-Last: Levner
Author-Name: Alexander Ptuskin
Author-X-Name-First: Alexander
Author-X-Name-Last: Ptuskin
Title: An entropy-based approach to identifying vulnerable components in a supply chain
Abstract: 
 We consider a problem of quantifying risk factors and identifying most informative (or vulnerable) components of the supply chain in terms of the amount of information about the risks and corresponding losses. This knowledge is beneficial for the selection of risk-prevention decisions. Shannon’s entropy is shown to be a powerful tool for risk management in hierarchical supply chains. An efficient algorithm is proposed that permits to reduce the size of the supply chain model without a loss of essential information about the risks and their economic consequences. A case study is presented to demonstrate the validity of the entropy-based approach.
Journal: International Journal of Production Research
Pages: 6888-6902
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.934400
File-URL: http://hdl.handle.net/10.1080/00207543.2014.934400
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Template-Type: ReDIF-Article 1.0
Author-Name: Emma Brandon-Jones
Author-X-Name-First: Emma
Author-X-Name-Last: Brandon-Jones
Author-Name: Brian Squire
Author-X-Name-First: Brian
Author-X-Name-Last: Squire
Author-Name: Yvonne G.T. Van Rossenberg
Author-X-Name-First: Yvonne G.T.
Author-X-Name-Last: Van Rossenberg
Title: The impact of supply base complexity on disruptions and performance: the moderating effects of slack and visibility
Abstract: 
 In the face of increasing supply base complexity, organisations have to develop new ways to manage or mitigate risk. This paper investigates the impact of four dimensions of complexity on the frequency of disruptions and plant performance. We apply insights from organisational information processing theory to understand how organisations can mitigate against the impact of more frequent disruptions. We test the moderating effects of slack resources as a means to absorb the effects of disruptions and supply visibility as a means to improve the ability to handle disruptions. The model is tested with data from 264 supply chain management professionals. Our findings broadly support the original hypotheses and suggest that supply base complexity can increase the frequency of disruptions and reduce plant performance but that slack resources and visibility can help to mitigate the effects. The study offers valuable insights into the management of supply base complexity.
Journal: International Journal of Production Research
Pages: 6903-6918
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.986296
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986296
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohamad Sofitra
Author-X-Name-First: Mohamad
Author-X-Name-Last: Sofitra
Author-Name: Katsuhiko Takahashi
Author-X-Name-First: Katsuhiko
Author-X-Name-Last: Takahashi
Author-Name: Katsumi Morikawa
Author-X-Name-First: Katsumi
Author-X-Name-Last: Morikawa
Title: The coevolution of interconnected relationship strategies in supply networks
Abstract: 
 Supply network (SN) complexity is the main challenge for managers in predicting the consequences of their firm’s relationship strategy decisions. The number of relationships and their interconnectedness constitute SN complexity and moreover, a firm’s relationships inside an SN are coevolved. It is, therefore, important to investigate how a specific relationship strategy has connected and coevolved with other types of relationship strategies in the context of a specific business situation and the interaction policies of firms. What kind of attractors of interconnected relationships will emerge?To address these issues, we model firms’ interactions inside an SN using cellular automata and complex adaptive system perspectives. Several micro-rules that mimic the drivers and mechanisms of all archetypes of relationship strategies (i.e. cooperation, defection, competition and co-opetition) were programmed inside agents. Experiments using the prisoner’s dilemma game reward schemes, representing business situation factors, have been built and the results show that the coevolution of interconnected relationship strategies coevolution causes the emergence of interesting attractors.
Journal: International Journal of Production Research
Pages: 6919-6936
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.991840
File-URL: http://hdl.handle.net/10.1080/00207543.2014.991840
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Template-Type: ReDIF-Article 1.0
Author-Name: Yasemin Merzifonluoglu
Author-X-Name-First: Yasemin
Author-X-Name-Last: Merzifonluoglu
Title: Impact of risk aversion and backup supplier on sourcing decisions of a firm
Abstract: 
 This study focuses on a newsvendor problem with multiple suppliers, considering the risk-neutral and risk-averse objectives in a mean-risk optimisation model. The firm first decides order quantities from the primary (unreliable) suppliers and reserve capacity from the secondary (reliable) backup supplier. After the state of its primary suppliers and customer demand is revealed, the firm purchases from the available suppliers and uses the backup supplier subject to the reserved capacity. For the special case of normal distribution and risk-neutral objective, optimality properties were developed. A comprehensive numerical study examines the sensitivity of the sourcing strategies of firms to risk, shortage cost, demand uncertainty, salvage value, and capacity reserve options; various managerial insights are offered based on this.
Journal: International Journal of Production Research
Pages: 6937-6961
Issue: 22
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.999956
File-URL: http://hdl.handle.net/10.1080/00207543.2014.999956
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuyan Wang
Author-X-Name-First: Yuyan
Author-X-Name-Last: Wang
Author-Name: Zhaoqing Yu
Author-X-Name-First: Zhaoqing
Author-X-Name-Last: Yu
Author-Name: Liang Shen
Author-X-Name-First: Liang
Author-X-Name-Last: Shen
Title: Study on the decision-making and coordination of an e-commerce supply chain with manufacturer fairness concerns
Abstract: 
 The decision-making and coordination of an e-commerce supply chain (ECSC) with manufacturer fairness concerns by incorporating the e-commerce platform into the decision-making process is studied in this paper. An ECSC composed of a single manufacturer and a single e-commerce platform is developed, and the optimal decisions for three scenarios are investigated, namely, a decentralised decision-making model without consideration of fairness concerns, a decentralised decision-making model considering manufacturer fairness concerns, and a centralised decision-making model. Then, a comparative analysis of the optimal decisions of the different models is conducted. On this basis, a coordination mechanism for the decentralised decision-making models is further proposed, and finally, a numerical analysis is employed to verify the conclusions. The research shows that the e-commerce platform, although it is the dominant party, obtains less profit than the manufacturer due to the unique operation characteristics of the ECSC. The sales price, service level, and profit of the ECSC are maximised in the centralised decision-making model, and they are not affected by the commission rate. The sales price, service level and profit of the decentralised decision-making model that considers manufacturer fairness concerns are inferior to those for the model that considers fairness concerns, indicating that manufacturer fairness concerns reduce system efficiency. In addition, a ‘cost sharing joint commission’ contract can be used to coordinate an ECSC.
Journal: International Journal of Production Research
Pages: 2788-2808
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1500043
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1500043
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Template-Type: ReDIF-Article 1.0
Author-Name: Juliang Zhang
Author-X-Name-First: Juliang
Author-X-Name-Last: Zhang
Author-Name: Shouting Zhao
Author-X-Name-First: Shouting
Author-X-Name-Last: Zhao
Author-Name: T.C. Edwin Cheng
Author-X-Name-First: T.C. Edwin
Author-X-Name-Last: Cheng
Author-Name: Guowei Hua
Author-X-Name-First: Guowei
Author-X-Name-Last: Hua
Title: Optimisation of online retailer pricing and carrier capacity expansion during low-price promotions with coordination of a decentralised supply chain
Abstract: 
 In recent years, many online retailers in China set low prices on 11 November, which stimulates huge delivery demand and results in many problems although carriers make an effort to increase their delivery capacities temporarily. To circumvent this difficulty, we consider a supply chain consisting of an online retailer, who can set price to influence the demand, and a capacitated carrier, whose capacity can be expanded at a high cost. We derive the optimal decisions in the centralised and decentralised decision systems, and compare the performances of the two systems. We find that the optimal decisions, and which system has lower price, larger capacity increment, and more late delivered goods depends on the model parameters (the market scale, the late delivery costs, the capacity expansion cost, the delivery fee, and the demand uncertainty). Specially, we show that, contrary to the traditional channel, the online retailer in the decentralised system may set lower price and the carrier has less incentive to expand capacity in the decentralised system in some situations, which underlines the need for coordination. In addition, we propose coordination contracts to improve the overall performance of the supply chain under deterministic and random demands.
Journal: International Journal of Production Research
Pages: 2809-2827
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1516901
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1516901
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Template-Type: ReDIF-Article 1.0
Author-Name: Baozhuang Niu
Author-X-Name-First: Baozhuang
Author-X-Name-Last: Niu
Author-Name: Yaoqi Liu
Author-X-Name-First: Yaoqi
Author-X-Name-Last: Liu
Author-Name: Feng Liu
Author-X-Name-First: Feng
Author-X-Name-Last: Liu
Author-Name: Carman K.M. Lee
Author-X-Name-First: Carman K.M.
Author-X-Name-Last: Lee
Title: Transfer pricing and channel structure of a multinational firm under overseas retail disruption risk
Abstract: 
 Considering a chain-to-chain competition model, we formulate a new multinational firm's (MNF's) trade-off between global tax-planning gains (via transfer pricing) and channel decentralisation loss. In the presence of an established MNF's competition, it is optional for the new MNF to operate two divisions (one for domestic manufacturing and one for overseas retailing) or one integrated division selling products to an independent overseas retailer at a wholesale price. For the former, we characterise the new MNF's transfer pricing strategies and find that interestingly, MNFs might both keep profits in high-tax region due to the tense competition in the retailing stage. For the latter, we find that the new MNF's channel decentralisation via wholesaling can be a win–win situation for the established MNF and itself, when the new MNF's overseas retail cost is in a moderate range. We further examine the new MNF's overseas retail disruption risk and find that, this risk drives the new MNF to lower the transfer price sharply and intensifies the retail competition. We use contraction mapping argument to show the uniqueness of the system equilibrium.
Journal: International Journal of Production Research
Pages: 2901-2925
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1516902
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1516902
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanting Huang
Author-X-Name-First: Yanting
Author-X-Name-Last: Huang
Author-Name: Zongjun Wang
Author-X-Name-First: Zongjun
Author-X-Name-Last: Wang
Title: Pricing and production decisions in a closed-loop supply chain considering strategic consumers and technology licensing
Abstract: 
 This paper considers a closed-loop supply chain consisting of a manufacturer and a third party in which the manufacturer licenses the third party to undertake remanufacturing activities in the presence of strategic consumers. We analyse the impacts of strategic consumer behaviour and the third-party remanufacturing cost on three kinds of remanufacturing scenarios, namely no-remanufacturing, partial-remanufacturing and full-remanufacturing. We adopt a Stackelberg game to obtain the equilibrium strategies of each remanufacturing model and show that the demand of new products decreases and the demand of remanufactured products increases as consumers become more strategic. Considering the manufacturer’s profit decrease due to strategic consumer behaviour, the manufacturer suffers a smaller profit loss when he licenses the third party to remanufacture because he can charge a higher licensing fee from the third party to share remanufacturing revenues. Moreover, the manufacturer prefers the third-party remanufacturing mode rather than the manufacturer–remanufacturing mode if the third-party remanufacturing cost is relatively low and remanufacturing can always bring a profit increase to both the manufacturer and the third party.
Journal: International Journal of Production Research
Pages: 2847-2866
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1530470
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530470
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Template-Type: ReDIF-Article 1.0
Author-Name: Bin Shen
Author-X-Name-First: Bin
Author-X-Name-Last: Shen
Author-Name: Xiaoyan Xu
Author-X-Name-First: Xiaoyan
Author-X-Name-Last: Xu
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Title: Simplicity is beauty: pricing coordination in two-product supply chains with simplest contracts under voluntary compliance
Abstract: 
 Pricing is an important topic in supply chains. In this paper, we explore the coordination challenge with the use of simplest contracts for the case with two products. To be specific, we consider a single-manufacturer single-retailer make-to-order supply chain. In the base model, we consider the case when the product demands are independent and derive the optimal pricing decisions under a decentralised setting. Comparing with the centralised setting, we show that double marginalisation in the decentralised setting reduces the supply chain efficiency by 25%. We then find that the simpler contracts such as the three-parameter two-part tariff (3P-TT) contract and the three-parameter revenue sharing (3P-RS) contract can coordinate the two-product supply chain. We extend the analysis in two cases: (i) the case when the products are substitutable and (ii) the case when the retailer is risk averse, and show that both the 3P-TT and 3P-RS contracts can coordinate the respective supply chain. We also find that the degrees of product substitution and retailer’s risk averse significantly influence the supply chain performance.
Journal: International Journal of Production Research
Pages: 2769-2787
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1530474
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530474
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Template-Type: ReDIF-Article 1.0
Author-Name: Yan Zhang
Author-X-Name-First: Yan
Author-X-Name-Last: Zhang
Author-Name: Yanyan He
Author-X-Name-First: Yanyan
Author-X-Name-Last: He
Author-Name: Jinfeng Yue
Author-X-Name-First: Jinfeng
Author-X-Name-Last: Yue
Author-Name: Qinglong Gou
Author-X-Name-First: Qinglong
Author-X-Name-Last: Gou
Title: Pricing decisions for a supply chain with refurbished products
Abstract: 
 This paper considers a supply chain consisting of a supplier and a retailer where a fixed portion of new products sold will be returned to the retailer and then be repaired and resold as refurbished products at a lower price. Using the utility model, we formulate how consumers will make their choices when facing both new and refurbished products. Then, using the divide-and-conquer method, we derive the supplier and retailer's equilibrium decisions, including the supplier's wholesale price and the retailer's prices for both the new and refurbished products. The main findings include the following. First, refurbished products will be sold in the market only when the refurbishing cost is small. In this situation, as the refurbishing cost increases, most of the negative impact on the retailer will be transferred to the supplier. Second, in the same condition, as the refurbishing cost increases, the wholesale price and retail price of the new product will change in opposite directions. This result contrasts with the traditional pass-through effect. Third, when the repair cost is moderate, the retailer will eventually not sell refurbished products, but its profit can be significantly improved and the double marginalisation effect can be mitigated.
Journal: International Journal of Production Research
Pages: 2867-2900
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1543968
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543968
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2867-2900




Template-Type: ReDIF-Article 1.0
Author-Name: Weili Xue
Author-X-Name-First: Weili
Author-X-Name-Last: Xue
Author-Name: Yulin Hu
Author-X-Name-First: Yulin
Author-X-Name-Last: Hu
Author-Name: Zhiyuan Chen
Author-X-Name-First: Zhiyuan
Author-X-Name-Last: Chen
Title: The value of buyback contract under price competition
Abstract: 
 We investigate the value of buyback contract by analysing a supply chain with one manufacturer and two competing retailers. Three scenarios, depending on whether buyback contracts are offered to neither, one, or both of the retailers, are considered. We first study the case when the manufacturer can only determine his buyback price. We show how the demand uncertainty, the competition level and the handling cost of buyback contract influence the profits of the manufacturer, the two retailers and the whole supply chain. Interestingly, contrary to the conventional wisdom that the buyback contract may intensify competition between the retailers, we show that offering the buyback contract to two competing retailers can benefit every channel member even if the competition level is high. Next, we study the return contract, a special type of buyback contract, and show the effect of competition level and industry outlook on supply chain parties' choices on return contract. We extend Padmanabhan and Png [1997. “Manufacturer's Returns Policies And Retail Competition.” Marketing Science 16 (1): 81–94] to the case with an asymmetric contract structure, i.e. one return contract and one whole-sale contract. We show that an asymmetric contract structure may better off both the retailers and the whole supply chain.
Journal: International Journal of Production Research
Pages: 2679-2694
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1544425
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1544425
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2679-2694




Template-Type: ReDIF-Article 1.0
Author-Name: Rohit Gupta
Author-X-Name-First: Rohit
Author-X-Name-Last: Gupta
Author-Name: Indranil Biswas
Author-X-Name-First: Indranil
Author-X-Name-Last: Biswas
Author-Name: Sushil Kumar
Author-X-Name-First: Sushil
Author-X-Name-Last: Kumar
Title: Pricing decisions for three-echelon supply chain with advertising and quality effort-dependent fuzzy demand
Abstract: 
 Simultaneous influence of market power structure, advertising and quality efforts on the optimal pricing decisions and performance of a multi-echelon supply chain under uncertainty have received scant attention in the literature. We focus on this gap by examining a serial decentralised three-echelon supply chain consisting of a supplier, a manufacturer and a retailer. The uncertainty associated with customer demand, marginal production costs and effort costs is expressed as linguistic or fuzzy variables. We analyse centralised supply chain to obtain all benchmark parameters. We investigate four decentralised supply chain cases through fuzzy game theoretic approach. We compare among three Stackelberg games with various supply chain leaderships and a vertical Nash. Our key findings are as follows. First, the manufacturer puts least quality effort while retailer puts least advertising effort when they act as Stackelberg leader in a three-echelon supply chain. Second, supplier's per unit price is governed by the channel leadership in three-echelon supply chain while retail prices are less affected by the leadership. We investigate the impact of fuzzy degree of quality and advertising sensitivity on optimal profit distribution among agents. We present numerical analysis to illustrate the importance of the derived theoretical results and discuss additional managerial insights.
Journal: International Journal of Production Research
Pages: 2715-2731
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1547434
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1547434
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Template-Type: ReDIF-Article 1.0
Author-Name: Lipan Feng
Author-X-Name-First: Lipan
Author-X-Name-Last: Feng
Author-Name: Yongjian Li
Author-X-Name-First: Yongjian
Author-X-Name-Last: Li
Author-Name: Fangchao Xu
Author-X-Name-First: Fangchao
Author-X-Name-Last: Xu
Author-Name: Qianzhou Deng
Author-X-Name-First: Qianzhou
Author-X-Name-Last: Deng
Title: Optimal pricing and trade-in policies in a dual-channel supply chain when considering market segmentation
Abstract: 
 Many companies are implementing trade-in programmes through multiple channels. This may ultimately lead to fiercer channel conflict and competition. Few studies have explored firms’ optimal trade-in policies in such an environment. To fill the gap, we build a theoretical model that captures the features of a dual-channel situation in which a manufacturer implements a trade-in programme through retail and direct channels simultaneously. Compared with the case in which there is no trade-in rebate, the results show that a trade-in programme can intensify or mitigate the double marginalisation effect if the retailer can initially decide the trade-in rebate in the retail channel. This significantly relies on market segmentation. However, when the retailer cannot decide the trade-in rebate in the retail channel, the trade-in programme aggravates the double marginalisation effect. Second, the trade-in rebate offered by the retailer may be higher than the subsidy offered by the manufacturer, as long as the retailer can autonomously decide the trade-in rebate in the retail channel. Furthermore, we find that both the manufacturer and retailer prefer to obtain the right to autonomously decide the trade-in rebate in the retail channel, but the supply chain prefers that the manufacturer do it. Some numerical examples are provided to further explain these outcomes.
Journal: International Journal of Production Research
Pages: 2828-2846
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1551636
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1551636
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Template-Type: ReDIF-Article 1.0
Author-Name: Razieh Sadeghi
Author-X-Name-First: Razieh
Author-X-Name-Last: Sadeghi
Author-Name: Ata Allah Taleizadeh
Author-X-Name-First: Ata Allah
Author-X-Name-Last: Taleizadeh
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Author-Name: Jafar Heydari
Author-X-Name-First: Jafar
Author-X-Name-Last: Heydari
Title: Coordinating and pricing decisions in two competitive reverse supply chains with different channel structures
Abstract: 
 This paper addresses coordination and competition problem in two reverse supply chains each having its own exclusive retailer and manufacturer. The chains have various collecting channel structures so that one of them uses the advantages of dual channels, where the consumer can return their e-waste through direct or traditional channels, while its competitor collects obsolete products only through its traditional channel. The willingness to return in each channel is a function of self- and cross-discounts of the competitors. Four decision scenarios are investigated; the first and second chain respectively select, Decentralised-Decentralised, Centralised-Centralised, Centralised-Decentralised or Decentralised-Centralised scenario. The closed-form optimal solution of each channel is derived based on the Stackelberg game when the second chain acts as a leader. The most economical scenario is determined by using a Non-Zero-Sum game when each chain plays as a single player in the game. To coordinate the members’ decisions and to convince unsatisfied members, two coordination contracts are offered. Numerical investigations reveal that direct channel suggests more discount and obtains more share of market. The results show that Centralised-Centralised scenario is the best decision from the SCs’ perspective which proposing contracts are able to persuade members to change their strategy to a global decision.
Journal: International Journal of Production Research
Pages: 2601-2625
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1551637
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1551637
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2601-2625




Template-Type: ReDIF-Article 1.0
Author-Name: Xu Chen
Author-X-Name-First: Xu
Author-X-Name-Last: Chen
Author-Name: Shuyao Wu
Author-X-Name-First: Shuyao
Author-X-Name-Last: Wu
Author-Name: Xiaojun Wang
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Wang
Author-Name: Dong Li
Author-X-Name-First: Dong
Author-X-Name-Last: Li
Title: Optimal pricing strategy for the perishable food supply chain
Abstract: 
 This research investigates the optimal pricing strategy for the perishable food supply chain. Using the setting of a two-echelon supply chain including a supplier and a retailer, we apply the game theory approach to derive the equilibriums for both a single pricing strategy and a two-stage pricing strategy. Through a comparison of the equilibriums, we explore how the two pricing strategies affect the supply chain’s decisions and supplier’s and retailer’s performance individually and collectively. The results of the analysis show that the optimal choice of pricing strategy depends on the price markdown cost and its relationship with the two critical thresholds that are determined by a combination of factors including the potential market size, the price and quality sensitivity factors, the initial quality, the unit product cost, and the quality deterioration rate.
Journal: International Journal of Production Research
Pages: 2755-2768
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1557352
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1557352
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2755-2768




Template-Type: ReDIF-Article 1.0
Author-Name: Prakash Awasthy
Author-X-Name-First: Prakash
Author-X-Name-Last: Awasthy
Author-Name: K. V. Gopakumar
Author-X-Name-First: K. V.
Author-X-Name-Last: Gopakumar
Author-Name: Sirish Kumar Gouda
Author-X-Name-First: Sirish Kumar
Author-X-Name-Last: Gouda
Author-Name: Tanushree Haldar
Author-X-Name-First: Tanushree
Author-X-Name-Last: Haldar
Title: Trust in humanitarian operations: a content analytic approach for an Indian NGO
Abstract: 
 Trust between partners, a key element enabling coordination across supply chains, has recently started gaining attention in humanitarian operations literature. Yet, empirical examination of this concept is scant. Borrowing from extant literature on trust within organisational behaviour stream, this paper aims to empirically verify trust formation types: companion, competence and commitment, in a disaster relief supply chain using primary and secondary data from an Indian Humanitarian relief organisation (HRO). Further, we identify variations in trust formation during disaster relief activities and developmental programmes, and between upstream and downstream partners of a humanitarian relief organisation. Based on the results of our content analysis, we contend that while companion based trust is significantly more prevalent during developmental programmes, competence based trust is important during both disaster periods and otherwise. We also find that there are significant differences in the trust formation between upstream and downstream partners and the HRO. This study has significant theoretical and practical implications on identifying the role of trust in humanitarian operations.
Journal: International Journal of Production Research
Pages: 2626-2641
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1566652
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566652
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2626-2641




Template-Type: ReDIF-Article 1.0
Author-Name: Yuelin Shen
Author-X-Name-First: Yuelin
Author-X-Name-Last: Shen
Author-Name: Xiaodong Yang
Author-X-Name-First: Xiaodong
Author-X-Name-Last: Yang
Author-Name: Yue Dai
Author-X-Name-First: Yue
Author-X-Name-Last: Dai
Title: Manufacturer-retail platform interactions in the presence of a weak retailer
Abstract: 
 Motivated by the emergence of dominant retail platforms operating using a store-within-a-store strategy, we study the interaction of such a retailer's decision on the selling format and a manufacturer's decision on the channel selection. The dominant retailer may elect to operate as a traditional reseller or a retail platform where the manufacturer manages his own store and pays a slotting fee and a portion of the revenue to the platform. The manufacturer makes the channel selection decision between the dominant retailer and a weak reseller. A Stackelberg game with the dominant retailer being the leader is formulated, and five relevant channel options are presented. We solve sub-games and characterise the equilibrium solution of the full game. Numerical studies shed light on the roles of the slotting fee and the outcomes of some prevailing selling formats in business practice. In particular, it is shown that the demand substitution between the dominant retailer and the weak retailer is crucial in determining channel selection.
Journal: International Journal of Production Research
Pages: 2732-2754
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1566657
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566657
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2732-2754




Template-Type: ReDIF-Article 1.0
Author-Name: Dinh Anh Phan
Author-X-Name-First: Dinh Anh
Author-X-Name-Last: Phan
Author-Name: Thi Le Hoa Vo
Author-X-Name-First: Thi Le Hoa
Author-X-Name-Last: Vo
Author-Name: Anh Ngoc Lai
Author-X-Name-First: Anh Ngoc
Author-X-Name-Last: Lai
Title: Supply chain coordination under trade credit and retailer effort
Abstract: 
 In this paper, we study the role of trade credit in coordinating a Capital Constrained Supply Chain in the presence of retailer Effort (CCSCE), essentially because of the impact of its related default risks on the relationship between the chain’s members. We consider a CCSCE consisting of a supplier and a retailer where the retailer may exert costly promotional efforts to increase the market demand but has limited capital and no access to bank financing due to low credit rating. Conversely, the supplier has adequate funds to offer trade credit to the retailer without borrowing from external channels. We then examine whether the existing coordination contracts can still coordinate the CCSCE under trade credit. Our result shows that these contracts can achieve coordination of the supply chain when the interest rate of trade credit is competitively priced. Nevertheless, this position cannot always be reached. That’s why we propose a generalised contract based on risk compensation to coordinate the CCSCE. Using our proposed coordinating contract, the supplier perfectly coordinates the retailer’s decisions for the largest joint profit, and arbitrarily allocates the maximised joint profit among supply chain members. Finally, the numerical study allows to verify this finding. From managerial insights, our results provide the supply chain managers with novel insights on how to combine trade credit with the existing coordination contracts in order to improve the profitability of the entire supply chain as well as the individual member.
Journal: International Journal of Production Research
Pages: 2642-2655
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1567950
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1567950
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2642-2655




Template-Type: ReDIF-Article 1.0
Author-Name: Feng Tao
Author-X-Name-First: Feng
Author-X-Name-Last: Tao
Author-Name: Tijun Fan
Author-X-Name-First: Tijun
Author-X-Name-Last: Fan
Author-Name: Yao-Yu Wang
Author-X-Name-First: Yao-Yu
Author-X-Name-Last: Wang
Author-Name: Kin Keung Lai
Author-X-Name-First: Kin Keung
Author-X-Name-Last: Lai
Title: Joint pricing and inventory strategies in a supply chain subject to inventory inaccuracy
Abstract: 
 This paper focuses on pricing strategies, inventory policies for a supply chain when Radio Frequency Identification (RFID) technology is adopted to cope with inventory inaccuracy. The supply chain consists of one supplier and one retailer, in which the RFID tag price is shared between the supplier and the retailer. We present and compare the performance differences between a wholesale price contract and a consignment contract when the retailer is the Stackelberg leader and the supplier is the follower. Based on the optimal pricing and inventory decisions, an interesting observation of contract selection is that there are two critical values of inventory available rate such that when the inventory availability is less than the lower value, both the supplier and the retailer prefer a consignment contract; when the inventory availability is greater than the upper value, a wholesale price contract is their best choice; when the inventory availability is between the two values, the supplier prefers a wholesale price contract and the retailer prefers a consignment contract. Additionally, there exist threshold values of RFID tag price and sharing rate to determine the contract preference for the retailer. Furthermore, the profits of both the supplier and the retailer are independent of the RFID tag price sharing rate in a wholesale price contract, and the supplier has the incentive to invest in RFID tag cost in a consignment contract.
Journal: International Journal of Production Research
Pages: 2695-2714
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1579933
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1579933
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2695-2714




Template-Type: ReDIF-Article 1.0
Author-Name: Lijian Chen
Author-X-Name-First: Lijian
Author-X-Name-Last: Chen
Author-Name: Shanling Li
Author-X-Name-First: Shanling
Author-X-Name-Last: Li
Author-Name: Derek Wang
Author-X-Name-First: Derek
Author-X-Name-Last: Wang
Title: Designing the price controller for the dynamic pricing of self-storage
Abstract: 
 In this paper, we study the dynamic pricing practices in the self-storage industry by introducing the widely used price controller, a term borrowed from control theories, among all self-storage service providers. Most self-storage service providers adopt the price controller method because of its effectiveness, simplicity, and straightforwardness. The price controller method adjusts the price per store's rental performance over the period. With noises on both move-ins and move-outs, the price controller method is a stochastic control model to determine the pricing trajectory at a sequence of discrete time spots to maximize the expected revenue growth. We find that the price controller method may outperform the myopic pricing method by evolving the pricing decision toward its optimum. Also, we discuss several unique properties of the self-storage industry and gain significant knowledge by analyzing the necessity of issuing a rental lease incentive to new customers.
Journal: International Journal of Production Research
Pages: 2656-2674
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1587191
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1587191
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2656-2674




Template-Type: ReDIF-Article 1.0
Author-Name: Hubert Pun
Author-X-Name-First: Hubert
Author-X-Name-Last: Pun
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Author-Name: Gregory DeYong
Author-X-Name-First: Gregory
Author-X-Name-Last: DeYong
Author-Name: Yong He
Author-X-Name-First: Yong
Author-X-Name-Last: He
Title: Special issue on ‘New consideration of pricing in supply chains’
Journal: International Journal of Production Research
Pages: 2675-2678
Issue: 9
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1587252
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1587252
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:9:p:2675-2678




Template-Type: ReDIF-Article 1.0
Author-Name: Qiannong Gu
Author-X-Name-First: Qiannong
Author-X-Name-Last: Gu
Author-Name: John K. Visich
Author-X-Name-First: John K.
Author-X-Name-Last: Visich
Author-Name: Kunpeng Li
Author-X-Name-First: Kunpeng
Author-X-Name-Last: Li
Author-Name: Ziping Wang
Author-X-Name-First: Ziping
Author-X-Name-Last: Wang
Title: Exploiting timely demand information in determining production lot-sizing: an exploratory study
Abstract: 
 The emerging automatic data-capturing technology, radio frequency identification technology (RFID), has been extensively adopted in logistics process and retail operations. However, limited research has been conducted on how to exploit and integrate RFID-enabled timely demand information into production processes. The lack of sufficient evaluation on the financial benefits of RFID hinders the adoption of this technology in production processes. In this study, we propose a framework to integrate RFID-enabled timely demand information into a dynamic production lot-sizing problem. Our results show that manufacturers, distributors and retailers can benefit from the availability of timely demand information via RFID. Our research sheds new light on understanding the financial value of RFID in a production process, and fills a gap in the application of RFID along the supply chain.
Journal: International Journal of Production Research
Pages: 4531-4543
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1245452
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1245452
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:16:p:4531-4543




Template-Type: ReDIF-Article 1.0
Author-Name: Walid W. Nasr
Author-X-Name-First: Walid W.
Author-X-Name-Last: Nasr
Author-Name: Moueen Salameh
Author-X-Name-First: Moueen
Author-X-Name-Last: Salameh
Author-Name: Lama Moussawi-Haidar
Author-X-Name-First: Lama
Author-X-Name-Last: Moussawi-Haidar
Title: Economic production quantity with maintenance interruptions under random and correlated yields
Abstract: 
 This paper considers an economic production quantity with imperfect items where the quality of items produced within the same production run is correlated. Production and scheduled maintenance policies for a correlated binomial production system are investigated. We study the impact of correlation on the system performance measures and draw insights in terms of the effect of correlation on the production and maintenance policies. We also illustrate that the popular and commonly used interrupted geometric production systems can be analysed by an equivalent correlated binomial production model.
Journal: International Journal of Production Research
Pages: 4544-4556
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1265684
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1265684
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Template-Type: ReDIF-Article 1.0
Author-Name: Zied Hajej
Author-X-Name-First: Zied
Author-X-Name-Last: Hajej
Author-Name: Nidhal Rezg
Author-X-Name-First: Nidhal
Author-X-Name-Last: Rezg
Author-Name: Ali Gharbi
Author-X-Name-First: Ali
Author-X-Name-Last: Gharbi
Title: Improved preventive maintenance in the framework of forecasting problem under subcontractor constraint
Abstract: 
 The paper presents a new improved preventive maintenance strategy for a forecasting problem of production and maintenance optimisation under subcontractor constraint. In order to satisfy the customer, the manufacturing system consists of a principal machine M1 and called upon subcontractor machine Ms. Knowing that both machines are subjected to random failures, failure rate of main machine increases with time and according to production rates. An improved preventive maintenance strategy is used for control of the machine M1, whereas subcontractor machine Ms is uncontrollable from preventive maintenance point of view. An analytic formulation of problem has been proposed in order to determine the economical production plans for M1 and Ms. An improved maintenance strategy (IMS) is developed in order to minimise the total production loss, when the subcontractor machine is unavailable. It consists of determining the best time to perform preventive maintenance actions taking into account production rates, history of M1 and the state of subcontractor machine Ms. Numerical results and sensitivity analysis are presented to highlight the performance measure and the usefulness of the IMS.
Journal: International Journal of Production Research
Pages: 4557-4600
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1268276
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1268276
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Template-Type: ReDIF-Article 1.0
Author-Name: Kai Hoberg
Author-X-Name-First: Kai
Author-X-Name-Last: Hoberg
Author-Name: Florian Badorf
Author-X-Name-First: Florian
Author-X-Name-Last: Badorf
Author-Name: Lars Lapp
Author-X-Name-First: Lars
Author-X-Name-Last: Lapp
Title: The inverse hockey stick effect: an empirical investigation of the fiscal calendar’s impact on firm inventories
Abstract: 
 We empirically investigate how manufacturers’ inventory decisions relate to the fiscal calendar. Although optimal firm inventories should depend on demand and supply, we find that the artificial accounting construct of the fiscal year frequently drives inventory dynamics. In an effort to manage earnings and cash flows (CFs) towards the fiscal year-end (FYE), firms significantly reduce their inventories in the fourth fiscal quarter only to increase their inventories in the next fiscal year. Using a sample of 4877 US manufacturing firms for the period 1990–2010, we find that inventories are 3.9–6.0% lower on average in the fourth fiscal quarter. In the analysis, we control for inventory theory-related factors that have been identified in prior literature. Because this pattern is the inverse of that observed for sales, we refer to this phenomenon as the inverse hockey stick effect. The effect holds for all three individual inventory types: raw materials, work in progress and finished goods. We find that inventory reductions in the fourth fiscal quarter are particularly substantial if firms have an incentive to beat CF targets. In contrast to our expectations, we do not find evidence that financial distress links to inventory reductions at the FYE.
Journal: International Journal of Production Research
Pages: 4601-4624
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1269969
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1269969
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Template-Type: ReDIF-Article 1.0
Author-Name: Xue-Yi Ai
Author-X-Name-First: Xue-Yi
Author-X-Name-Last: Ai
Author-Name: Jin-Long Zhang
Author-X-Name-First: Jin-Long
Author-X-Name-Last: Zhang
Author-Name: Lin Wang
Author-X-Name-First: Lin
Author-X-Name-Last: Wang
Title: Optimal joint replenishment policy for multiple non-instantaneous deteriorating items
Abstract: 
 In this paper, we deal with the problem of determining the optimal economic operating policy when a number of non-instantaneous deteriorating items are jointly replenished. We establish a multi-item joint replenishment model for non-instantaneous deteriorating items under constant demand rate allowing full backlogging. This problem is challenging, in particular, the cost function is a piecewise function with exponential parts, which makes the problem more complicated. To solve this problem, an approximation method is used to simplify the objective function and a bound-based heuristic algorithm is developed to solve the model. Numerical examples illustrate the effectiveness of the proposed method and the quality of the approximation. Experimental results on a real-life case study show that the proposed model can achieve substantial cost savings compared to the individual replenishment policy for non-instantaneous deteriorating items. Furthermore, sensitivity analysis of key parameters is carried out and the implications are discussed in detail.
Journal: International Journal of Production Research
Pages: 4625-4642
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1276306
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1276306
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohamed Noomane Darghouth
Author-X-Name-First: Mohamed Noomane
Author-X-Name-Last: Darghouth
Author-Name: Anis Chelbi
Author-X-Name-First: Anis
Author-X-Name-Last: Chelbi
Author-Name: Daoud Ait-kadi
Author-X-Name-First: Daoud
Author-X-Name-Last: Ait-kadi
Title: Investigating reliability improvement of second-hand production equipment considering warranty and preventive maintenance strategies
Abstract: 
 A cost model for optimal reliability improvement of warranted second-hand production equipment is developed. The second-hand production equipment of age x is subjected to an upgrade action of a certain level u before it is sold with a Free Repair Warranty. We look at determining the optimal upgrade level when not performing and when performing periodic preventive maintenance (PM) during the warranty period. Two different PM strategies are considered: (a) periodic PM actions having the same efficiency level; (b) periodic multi-phase PM actions with a maintenance efficiency level which varies according to the phase. The proposed model aims at helping the dealer to find the optimal upgrade level to perform before selling the second-hand equipment, and to assess whether performing PM actions during the warranty period, according to a specific maintenance strategy, is worthwhile in terms of cost reduction. Numerical experimentations considering each PM scenario are performed in order to investigate how each PM strategy impacts the improvement level to be performed and the associated total expected cost. The obtained results showed that the expected total cost incurred by the dealer is governed by a sensitive trade-off between the warranty servicing cost and the costs associated with the reliability improvement, and with the PM performed during the warranty period. It is also found that the proposed new periodic multi-phase PM policy with an increasing maintenance efficiency level yields lower upgrade levels, inducing lower costs for the dealer.
Journal: International Journal of Production Research
Pages: 4643-4661
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1277277
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1277277
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Template-Type: ReDIF-Article 1.0
Author-Name: Phillip O. Kriett
Author-X-Name-First: Phillip O.
Author-X-Name-Last: Kriett
Author-Name: Sebastian Eirich
Author-X-Name-First: Sebastian
Author-X-Name-Last: Eirich
Author-Name: Martin Grunow
Author-X-Name-First: Martin
Author-X-Name-Last: Grunow
Title: Cycle time-oriented mid-term production planning for semiconductor wafer fabrication
Abstract: 
 Wafers are produced in an environment with uncertain demand and failure-prone machines. Production planners have to react to changes of both machine availability and target output, and revise plans appropriately. The scientific community mostly proposes WIP-oriented mid-term production planning to solve this problem. In such approaches, production is planned by defining targets for throughput rates and buffer levels of selected operations. In industrial practice, however, cycle time-oriented planning is often preferred over WIP-oriented planning. We therefore propose a new linear programming formulation, which facilitates cycle time-oriented mid-term production planning in wafer fabrication. This approach plans production by defining release quantities and target cycle times up to selected operations. It allows a seamless integration with the subordinate scheduling level. Here, least slack first scheduling translates target cycle times into lot priorities. We evaluate our new methodology in a comprehensive simulation study. The results suggest that cycle time-oriented mid-term production planning can both increase service level and reduce cycle time compared to WIP-oriented planning. Further, it requires less modelling effort and generates plans, which are easier to comprehend by human planners.
Journal: International Journal of Production Research
Pages: 4662-4679
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1278083
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1278083
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Template-Type: ReDIF-Article 1.0
Author-Name: Manuel Cardós
Author-X-Name-First: Manuel
Author-X-Name-Last: Cardós
Author-Name: Ester Guijarro
Author-X-Name-First: Ester
Author-X-Name-Last: Guijarro
Author-Name: Eugenia Babiloni
Author-X-Name-First: Eugenia
Author-X-Name-Last: Babiloni
Title: On the estimation of on-hand stocks for base-stock policies and lost sales systems and its impact on service measures
Abstract: 
 This paper focuses on computing on-hand stock levels at the beginning of a replenishment cycle for a lost sales inventory system with periodic reviews and discrete demand. A base-stock policy is used for replenishments. The literature provides an Exact method which requires a huge computational effort, and two closed-form approximate methods that arise from the backordering case, the Non-stockout and the Bijvank &amp; Johansen. In this paper we propose three new and closed-form approaches that explicitly consider the lost sales assumptions: the Adjusted Non-stockout, the Polar Opposite and the 1-Step methods. Existing and proposed methods are evaluated in terms of their accuracy when computing the cycle service level and the fill rate. In this sense, results show that the Bijvank &amp; Johansen and 1-Step methods provide similar performance but present different behaviours in terms of under or over estimating service measures that have different implications on the design of stock policies.
Journal: International Journal of Production Research
Pages: 4680-4694
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2017.1279759
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1279759
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Nuno O. Fernandes
Author-X-Name-First: Nuno O.
Author-X-Name-Last: Fernandes
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Author-Name: Ting Qu
Author-X-Name-First: Ting
Author-X-Name-Last: Qu
Title: On the backlog-sequencing decision for extending the applicability of ConWIP to high-variety contexts: an assessment by simulation
Abstract: 
 Constant Work-in-Process (ConWIP) is a card-based control system that was developed for simple flow shops – a lack of load-balancing capabilities hinders its application to more complex shops. In contrast, load balancing is an integral part of Workload Control, a production planning and control concept developed for high-variety environments. One means of load balancing evident in the Workload Control literature is through the use of a capacity slack-based backlog-sequencing rule. This study therefore investigates the potential of the backlog-sequencing decision to improve load balancing in the context of ConWIP, thereby making it suitable for more complex, high-variety environments. Using simulation, we demonstrate that: (i) the choice of backlog-sequencing rule significantly impacts throughput times and tardiness-related performance measures; and (ii) capacity slack-based sequencing rules achieve significant performance improvements over ‘classical’ ConWIP backlog-sequencing rules. These results significantly extend the applicability of ConWIP. Results from the Workload Control literature however do not directly translate across to ConWIP. The simplified release procedure of ConWIP makes backlog-sequencing based on planned release dates dysfunctional. This negatively impacts the performance of modified capacity slack-based sequencing rules that were recently shown to be the best choice for Workload Control.
Journal: International Journal of Production Research
Pages: 4695-4711
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2017.1281462
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1281462
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Template-Type: ReDIF-Article 1.0
Author-Name: Kai Meng
Author-X-Name-First: Kai
Author-X-Name-Last: Meng
Author-Name: Peihuang Lou
Author-X-Name-First: Peihuang
Author-X-Name-Last: Lou
Author-Name: Xianghui Peng
Author-X-Name-First: Xianghui
Author-X-Name-Last: Peng
Author-Name: Victor Prybutok
Author-X-Name-First: Victor
Author-X-Name-Last: Prybutok
Title: Quality-driven recovery decisions for used components in reverse logistics
Abstract: 
 Reverse logistics has emerged as a promising strategy for enhancing environmental sustainability through remanufacturing, reusing, or recycling used components. It is crucial to pursue quality-driven decision-making for component recovery because quality is a dominant factor for component salvage value and its recoverability. To maximise the profit from component recovery, a quality-driven decision model was proposed in this study. Remaining useful life (RUL) was utilised as a measure of quality in the proposed model, where conditional RUL distribution was predicted by utilising both the failure data and condition monitoring data based on a proportional hazard model. Under RUL uncertainty, an interval decision-making approach was developed to suggest recovery strategies for the decision-makers to identify a satisfactory solution according to their risk preferences. Compared to the existing approaches for quality-driven recovery decision-making based on RUL prediction, this work provides a more accurate and powerful approach to managing and mitigating decision risk. Numerical experiments demonstrated the effectiveness and superiority of the proposed model.
Journal: International Journal of Production Research
Pages: 4712-4728
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2017.1287971
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1287971
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Template-Type: ReDIF-Article 1.0
Author-Name: Hongtao Hu
Author-X-Name-First: Hongtao
Author-X-Name-Last: Hu
Author-Name: Ye Zhang
Author-X-Name-First: Ye
Author-X-Name-Last: Zhang
Author-Name: Lu Zhen
Author-X-Name-First: Lu
Author-X-Name-Last: Zhen
Title: A two-stage decomposition method on fresh product distribution problem
Abstract: 
 Refrigerator cars are widely used for fresh product distribution. The energy consumption of these vehicles is sensitive to the environment temperature, and changes continuously due to fluctuations of the environment temperature. As a result, the total refrigeration cost is influenced by the car’s departure time. To reduce operation costs of third-party transportation providers, the refrigerator car scheduling problem is addressed in this research. A time-dependent mixed-integer programming model is established to reduce total operation costs, including routing, time penalty, cargo damage and refrigeration costs. An adaptive heuristic method is proposed by combining the variable neighbourhood search and particle swarm optimisation. To improve the algorithm quality, a two-stage decomposition method is developed. The problem is divided into two echelon sub-problems. One is the shortest path problem, and the other is the departure time scheduling problem. A feedback strategy is utilised to avoid local optimal solutions and design of experiments methodology is adopted to derive the optimal parameter setting of the algorithm. Numerical experiments are conducted to demonstrate the effectiveness of the proposed time-dependent decision model.
Journal: International Journal of Production Research
Pages: 4729-4752
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2017.1292062
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1292062
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Template-Type: ReDIF-Article 1.0
Author-Name: Yang Li
Author-X-Name-First: Yang
Author-X-Name-Last: Li
Author-Name: Qirong Tang
Author-X-Name-First: Qirong
Author-X-Name-Last: Tang
Author-Name: Qing Chang
Author-X-Name-First: Qing
Author-X-Name-Last: Chang
Author-Name: Michael P. Brundage
Author-X-Name-First: Michael P.
Author-X-Name-Last: Brundage
Title: An event-based analysis of condition-based maintenance decision-making in multistage production systems
Abstract: 
 Condition-based maintenance (CBM) is becoming increasingly prevalent because of its capability to continuously track equipment health degradation and accurately predict unscheduled equipment failure. CBM helps to improve the business bottom line by preventing costly station failure. However, it is not uncommon that CBM needs to stop stations for maintenance during operation, which can severely impede the normal production. The objective of this paper is to develop a systematic method to predict the negative impact of CBM stoppage events on production in a multistage manufacturing system. The research helps to predict the real expense of applying CBM, which is the foundation to establish a comprehensive real-time CBM decision-making model. We start from the event-based analysis of system dynamics and develop a stochastic estimation method to predict the permanent production loss caused by a CBM stoppage event. The monotonicity property of permanent production loss is investigated. Simulation case studies are performed to illustrate the theoretical results and demonstrate their potential in facilitating CBM decision-making.
Journal: International Journal of Production Research
Pages: 4753-4764
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2017.1292063
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1292063
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiajun Zhou
Author-X-Name-First: Jiajun
Author-X-Name-Last: Zhou
Author-Name: Xifan Yao
Author-X-Name-First: Xifan
Author-X-Name-Last: Yao
Title: A hybrid approach combining modified artificial bee colony and cuckoo search algorithms for multi-objective cloud manufacturing service composition
Abstract: 
 This paper proposes a multi-objective hybrid artificial bee colony (MOHABC) algorithm for service composition and optimal selection (SCOS) in cloud manufacturing, in which both the quality of service and the energy consumption are considered from the perspectives of economy and environment that are two pillars of sustainable manufacturing. The MOHABC uses the concept of Pareto dominance to direct the searching of a bee swarm, and maintains non-dominated solution found in an external archive. In order to achieve good distribution of solutions along the Pareto front, cuckoo search with Levy flight is introduced in the employed bee search to maintain diversity of population. Furthermore, to ensure the balance of exploitation and exploration capabilities for MOHABC, the comprehensive learning strategy is designed in the onlooker search so that every bee learns from the external archive elite, itself and other onlookers. Experiments are carried out to verify the effect of the improvement strategies and parameters’ impacts on the proposed algorithm and comparative study of the MOHABC with typical multi-objective algorithms for SCOS problems are addressed. The results show that the proposed approach obtains very promising solutions that significantly surpass the other considered algorithms.
Journal: International Journal of Production Research
Pages: 4765-4784
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2017.1292064
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1292064
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Template-Type: ReDIF-Article 1.0
Author-Name: Dongjin Lee
Author-X-Name-First: Dongjin
Author-X-Name-Last: Lee
Author-Name: Rong Pan
Author-X-Name-First: Rong
Author-X-Name-Last: Pan
Title: Predictive maintenance of complex system with multi-level reliability structure
Abstract: 
 Onboard sensors, which constantly monitor the states of a system and its components, have made the predictive maintenance (PdM) of a complex system possible. To date, system reliability has been extensively studied with the assumption that systems are either single-component systems or they have a deterministic reliability structure. However, in many realistic problems, there are complex multi-component systems with uncertainties in the system reliability structure. This paper presents a PdM scheme for complex systems by employing discrete time Markov chain models for modelling multiple degradation processes of components and a Bayesian network (BN) model for predicting system reliability. The proposed method can be considered as a special type of dynamic Bayesian network because the same BN is repeatedly used over time for evaluating system reliability and the inter-time–slice connection of the same node is monitored by a sensor. This PdM scheme is able to make probabilistic inference at any system level, so PdM can be scheduled accordingly.
Journal: International Journal of Production Research
Pages: 4785-4801
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2017.1299947
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1299947
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Template-Type: ReDIF-Article 1.0
Author-Name: Oskar P. Roemeling
Author-X-Name-First: Oskar P.
Author-X-Name-Last: Roemeling
Author-Name: Martin J. Land
Author-X-Name-First: Martin J.
Author-X-Name-Last: Land
Author-Name: Kees Ahaus
Author-X-Name-First: Kees
Author-X-Name-Last: Ahaus
Author-Name: Jannes Slomp
Author-X-Name-First: Jannes
Author-X-Name-Last: Slomp
Author-Name: Wouter van den Bijllaardt
Author-X-Name-First: Wouter
Author-X-Name-Last: van den Bijllaardt
Title: Impact of lean interventions on time buffer reduction in a hospital setting
Abstract: 
 This paper focuses on performance changes stemming from a series of lean interventions in a medical laboratory. This research is one of the first to link a series of lean interventions and performance over time. In a mixed-method case study, six years of patient-related throughput data, retrieved from a laboratory computer database, are analysed. Three distinct periods with significant differences in throughput time performance can be distinguished. Semi-structured interviews were held to investigate the lean interventions preceding the performance changes. Given the long-term nature of the study, the event history calendar method was applied to enhance the respondents’ recall and reliability. A single lean intervention, among the hundreds that took place, was supposed to cause the main reduction in throughput times. It concentrated on improving process flow through the removal of batching, a source of artificial variability. A later major intervention, the introduction of flow-focused machinery, had mixed effects and initial performance gains were not sustained. The results show that ongoing series of interventions do not always lead to ongoing performance improvements in terms of throughput times but support theories emphasising the importance of variability reduction.
Journal: International Journal of Production Research
Pages: 4802-4815
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2017.1301687
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1301687
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehmood Khan
Author-X-Name-First: Mehmood
Author-X-Name-Last: Khan
Author-Name: Matloub Hussain
Author-X-Name-First: Matloub
Author-X-Name-Last: Hussain
Author-Name: Leopoldo Eduardo Cárdenas-Barrón
Author-X-Name-First: Leopoldo Eduardo
Author-X-Name-Last: Cárdenas-Barrón
Title: Learning and screening errors in an EPQ inventory model for supply chains with stochastic lead time demands
Abstract: 
 This paper investigates the role of variable lead time, learning in production and screening errors in a vendor–buyer supply chain with defective items. The vendor–buyer supply chain is modelled for supplying a single item considering that the lots from vendor may contain some defective items. It is assumed that demand during lead time follows a normal distribution. Moreover, the production time at vendor’s facility is assumed to follow learning whereas buyer’s screening for defective items is prone to errors as well. Numerical examples are presented to illustrate the impact of different variables in the model. The analysis shows that delay in transportation lead time forces the buyer to carry more inventories to avoid shortages. Further, Type I error has a major impact on this cost. It was found that learning in production keeps on reducing the total cost of the supply chain up to a threshold.
Journal: International Journal of Production Research
Pages: 4816-4832
Issue: 16
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2017.1310402
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1310402
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohsen Moghaddam
Author-X-Name-First: Mohsen
Author-X-Name-Last: Moghaddam
Author-Name: Shimon Y. Nof
Author-X-Name-First: Shimon Y.
Author-X-Name-Last: Nof
Author-Name: Ehud Menipaz
Author-X-Name-First: Ehud
Author-X-Name-Last: Menipaz
Title: Design and administration of collaborative networked headquarters
Abstract: 
 Regional headquarters (RHs) lead regionally serving subsidiaries responsible for organising geographically dispersed manufacturing and/or service operations in their respective regional subsidiaries (RSs), with certain levels of autonomy and decision-making authority. RHs have recently attracted greater attention, as a major investment of decentralised manufacturing and service operations. The goal of this work is thus to develop a comprehensive framework to enable optimal design and administration of interconnected, collaborative, and networked manufacturing and service systems. The decisions include optimal design of (1) RH networks based on multiple indicators, and (2) collaboration mechanisms between the RHs. Cyber-supported communication technologies enable the RHs to collaboratively process their electronic tasks (e-Tasks), such that the overall service level, resource utilisation and stability are improved. A bi-objective mixed integer programming model is developed for modelling the RH network design and administration problem. Data envelopment analysis is applied for combining multiple RH network design indicators into unified preference scores. Due to the computational complexity of the problem, a memetic algorithm is developed with a local search mechanism for making task sharing decisions. Several numerical experiments are conducted to illustrate, analyse and highlight the unique features and implications of the developed methodology.
Journal: International Journal of Production Research
Pages: 7074-7090
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2015.1125544
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1125544
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Template-Type: ReDIF-Article 1.0
Author-Name: Syed Imran Shafiq
Author-X-Name-First: Syed Imran
Author-X-Name-Last: Shafiq
Author-Name: Cesar Sanin
Author-X-Name-First: Cesar
Author-X-Name-Last: Sanin
Author-Name: Carlos Toro
Author-X-Name-First: Carlos
Author-X-Name-Last: Toro
Author-Name: Edward Szczerbicki
Author-X-Name-First: Edward
Author-X-Name-Last: Szczerbicki
Title: Virtual engineering process (VEP): a knowledge representation approach for building bio-inspired distributed manufacturing DNA
Abstract: 
 The objective of this research is to provide a user-friendly and effective way of representing engineering processes for distributed manufacturing systems so that they can develop, accumulate and share knowledge. The basic definition and principle of the approach is introduced first and then the prototype version of the system is developed and demonstrated with case studies, which verify the feasibility of the proposed approach. This paper proposes a novel concept of virtual engineering process (VEP), which is experience-based knowledge representation of engineering processes. VEP is an extension of our previous work on virtual engineering object (VEO). VEP model includes complete process knowledge required to manufacture a component. This knowledge is captured from three distinctive aspects related to manufacturing. First, information about the manufacturing operations involved. Second, information about the resources/machines required to perform operations and third, information about process level decisions that are taken. It also aims to combine/share experience of engineering objects, manufacturing processes, and systems. It applies bio-inspired knowledge engineering approach called decisional DNA and set of experience-based knowledge representation.
Journal: International Journal of Production Research
Pages: 7129-7142
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2015.1125545
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1125545
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Template-Type: ReDIF-Article 1.0
Author-Name: Seokgi Lee
Author-X-Name-First: Seokgi
Author-X-Name-Last: Lee
Author-Name: Yuncheol Kang
Author-X-Name-First: Yuncheol
Author-X-Name-Last: Kang
Author-Name: Vittaldas V. Prabhu
Author-X-Name-First: Vittaldas V.
Author-X-Name-Last: Prabhu
Title: Smart logistics: distributed control of green crowdsourced parcel services
Abstract: 
 This paper presents the development of an integrated decision-making framework for on-demand parcel delivery services that considers Just-In-Time delivery, fuel consumption and carbon emissions. Optimal policies based on the Markov decision process are established to allow for inclusion of parcel delivery requests. The framework’s integrated dynamic algorithm, based on a continuous variable feedback control, allows for unified processing of delivery requests and route scheduling. Computational experiments show that the integrated approach could increase revenue by 6.4% by reducing fuel and emission costs by 2.5%; however, the approach may incur more cost in terms of timeliness compared to a myopic approach.
Journal: International Journal of Production Research
Pages: 6956-6968
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2015.1132856
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1132856
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Template-Type: ReDIF-Article 1.0
Author-Name: Navin K. Dev
Author-X-Name-First: Navin K.
Author-X-Name-Last: Dev
Author-Name: Ravi Shankar
Author-X-Name-First: Ravi
Author-X-Name-Last: Shankar
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Lakshman S. Thakur
Author-X-Name-First: Lakshman S.
Author-X-Name-Last: Thakur
Title: A hybrid adaptive decision system for supply chain reconfiguration
Abstract: 
 Due to short product life cycle, it is expedient to reconfiguration an existing supply chain from time to time. Companies need to impose the standards on operational units for finding the best or the near best alternative configuration. Thus, it becomes imperative to effectively adapt various enablers in a supply chain by understanding the dynamics between them that help to reconfigure a supply chain for high levels of performance. This paper presents an integration of agent-based simulation and decision tree learning as the data mining techniques to determine adaptive decisions of operational units of a mobile phone supply chain. Agent-based simulation output is subjected to data mining analysis to understand system behaviour in terms of interactions and the factors influencing the performance. An entropy-based formulation is proposed as the basis for comparing different operational units in the supply chain. The insights obtained are then encapsulated as operational rules and guidelines supporting better decision-making.
Journal: International Journal of Production Research
Pages: 7100-7114
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2015.1134842
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1134842
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Template-Type: ReDIF-Article 1.0
Author-Name: Merve Aydin
Author-X-Name-First: Merve
Author-X-Name-Last: Aydin
Author-Name: Berna Haktanirlar Ulutas
Author-X-Name-First: Berna Haktanirlar
Author-X-Name-Last: Ulutas
Title: A new methodology to cluster derivative product modules: an application
Abstract: 
 Companies are trying several ways to offer competitive and highly differentiated products. The goal for the product platform is to share elements for common functions and to differentiate each product in the family by satisfying different requirements as much as possible. This study focuses on the product variety and short product life cycles that result from the increase and diversification in consumer needs and expectations. Proposed methodology aims to maximise the use of common product modules by considering platform-based derivative products and modular product design approaches to minimise the planning complexity in supply chain, manufacturing and service for derivative products. Functional and technical features of the products are determined in the first step. Then, design structure matrix is formed. After defining product components, similarity matrix for derivative products is formed. A clustering algorithm based on Clonal Selection is used to generate critical product modules. Data from a home appliance manufacturer are used to assess three versions of a product by also considering the production process. The grouping enabled to shorten the release time of a new derivative product to the market.
Journal: International Journal of Production Research
Pages: 7091-7099
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1143133
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1143133
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Template-Type: ReDIF-Article 1.0
Author-Name: Ashutosh Nayak
Author-X-Name-First: Ashutosh
Author-X-Name-Last: Nayak
Author-Name: Rodrigo Reyes Levalle
Author-X-Name-First: Rodrigo
Author-X-Name-Last: Reyes Levalle
Author-Name: Seokcheon Lee
Author-X-Name-First: Seokcheon
Author-X-Name-Last: Lee
Author-Name: Shimon Y. Nof
Author-X-Name-First: Shimon Y.
Author-X-Name-Last: Nof
Title: Resource sharing in cyber-physical systems: modelling framework and case studies
Abstract: 
 Cyber-physical systems (CPSs) have attracted significant research interest because of their promising applications across different domains; nonetheless, how to effectively model CPSs in real applications is still a challenge. In this article, a resource sharing-based framework (RSBF) for CPSs is developed to enable flexible modelling of a wide range of CPSs and systems of CPSs, with specific focus on resource sharing. RSBF combines elements from graph theory and social welfare to describe complex arrangements of overlapping task and resource communities in CPSs, with the objective of maximising CPS utility through decentralised control. The framework implementation is validated through three case studies: scheduling in smart factories, energy distribution in smart grids and information routing in multi-robot systems. Results show that RSBF can successfully represent the dissimilar systems under study. Furthermore, performance analysis on benchmark scheduling problems yields near-optimal results with less computational time, showing the potential of the use of social welfare functions to CPS modelling and control.
Journal: International Journal of Production Research
Pages: 6969-6983
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1146419
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1146419
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohit Goswami
Author-X-Name-First: Mohit
Author-X-Name-Last: Goswami
Author-Name: Saurabh Pratap
Author-X-Name-First: Saurabh
Author-X-Name-Last: Pratap
Author-Name: S.K. Kumar
Author-X-Name-First: S.K.
Author-X-Name-Last: Kumar
Title: An integrated Bayesian-Game theoretic approach for product portfolio planning of a multi-attributed product in a duopolistic market
Abstract: 
 The focus of this paper is to develop a Bayesian-Game theoretic framework for product portfolio planning problem thereby aiding the manufacturers operating across variety of product industries to offer the right product portfolio set. The problem is modelled for a duopolistic market and the product type considered is characterised by multiple product attributes having varying attribute levels. Initially, feasible product portfolio candidates are generated in terms of combinations of different product attributes and their attribute levels employing the attribute compatibility constraint. Different product portfolio sets thus generated function as different product offering strategies of the two manufacturers. Thereafter, employing the function-based cost-estimating framework and multi-linear regression methodology, manufacturing costs and product premiums, respectively, are estimated for different product portfolios. Utilising the Bayesian risk network, the purchase probabilities are estimated in high, medium and low-risk states for various product portfolios. The purchase probability is made a function of price and functionality. The purchase probabilities thus obtained acts as an input to the final pay-off calculation. Finally, employing these pay-off values, product offering scenarios are populated for the two manufacturers both in equilibrium and non-equilibrium state.
Journal: International Journal of Production Research
Pages: 6997-7013
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1150614
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1150614
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Template-Type: ReDIF-Article 1.0
Author-Name: Nagesh Shukla
Author-X-Name-First: Nagesh
Author-X-Name-Last: Shukla
Author-Name: Senevi Kiridena
Author-X-Name-First: Senevi
Author-X-Name-Last: Kiridena
Title: A fuzzy rough sets-based multi-agent analytics framework for dynamic supply chain configuration
Abstract: 
 Considering the need for more effective decision support in the context of distributed manufacturing, this paper develops an advanced analytics framework for configuring supply chain (SC) networks. The proposed framework utilises a distributed multi-agent system architecture to deploy fuzzy rough sets-based algorithms for knowledge elicitation and representation. A set of historical sales data, including network node-related information, is used together with the relevant details of product families to predict SC configurations capable of fulfilling desired customer orders. Multiple agents such as data retrieval agent, knowledge acquisition agent, knowledge representation agent, configuration predictor agent, evaluator agent and dispatching agent are used to help execute a broad spectrum of SC configuration decisions. The proposed framework considers multiple product variants and sourcing options at each network node, as well as multiple performance objectives. It also captures decisions that span the entire SC simultaneously and, by implication, represents multiple network links. Using an industry test case, the paper demonstrates the effectiveness of the proposed framework in terms of fulfilling customer orders with lower production and emissions costs, compared to the results generated using existing tools.
Journal: International Journal of Production Research
Pages: 6984-6996
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1151567
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1151567
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Template-Type: ReDIF-Article 1.0
Author-Name: Ajay Kumar
Author-X-Name-First: Ajay
Author-X-Name-Last: Kumar
Author-Name: Ravi Shankar
Author-X-Name-First: Ravi
Author-X-Name-Last: Shankar
Author-Name: Alok Choudhary
Author-X-Name-First: Alok
Author-X-Name-Last: Choudhary
Author-Name: Lakshman S. Thakur
Author-X-Name-First: Lakshman S.
Author-X-Name-Last: Thakur
Title: A big data MapReduce framework for fault diagnosis in cloud-based manufacturing
Abstract: 
 This research develops a MapReduce framework for automatic pattern recognition based on fault diagnosis by solving data imbalance problem in a cloud-based manufacturing (CBM). Fault diagnosis in a CBM system significantly contributes to reduce the product testing cost and enhances manufacturing quality. One of the major challenges facing the big data analytics in CBM is handling of data-sets, which are highly imbalanced in nature due to poor classification result when machine learning techniques are applied on such data-sets. The framework proposed in this research uses a hybrid approach to deal with big data-set for smarter decisions. Furthermore, we compare the performance of radial basis function-based Support Vector Machine classifier with standard techniques. Our findings suggest that the most important task in CBM is to predict the effect of data errors on quality due to highly imbalance unstructured data-set. The proposed framework is an original contribution to the body of literature, where our proposed MapReduce framework has been used for fault detection by managing data imbalance problem appropriately and relating it to firm’s profit function. The experimental results are validated using a case study of steel plate manufacturing fault diagnosis, with crucial performance matrices such as accuracy, specificity and sensitivity. A comparative study shows that the methods used in the proposed framework outperform the traditional ones.
Journal: International Journal of Production Research
Pages: 7060-7073
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1153166
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1153166
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianming Yao
Author-X-Name-First: Jianming
Author-X-Name-Last: Yao
Author-Name: Ziliang Deng
Author-X-Name-First: Ziliang
Author-X-Name-Last: Deng
Title: Dynamic resource integration optimisation of global distributed manufacturing: an embeddedness–interaction perspective
Abstract: 
 In the era of fragmented global value chain enabled by digital networks, distributed manufacturing with effective global resource integration and optimisation has become important for multinational enterprises (MNEs) to organise. However, conventional theories and methods disregard the dynamic nature of integration optimisation triggered by knowledge accumulation and spillover during resource embeddedness in the local market and interaction amongst resources. This study establishes a novel embeddedness–interaction perspective, which refers to focusing on intra-network knowledge transfer and inter-network knowledge spillover frequently observed in the resource integration of global distributed manufacturing in MNEs. This study elaborates the mechanism of resource integration optimisation of distributed manufacturing with the presence of an embeddedness–interaction nexus. On this basis, a novel, dynamic resource integration optimisation model and a corresponding algorithm for global distributed manufacturing are constructed. In particular, we designate the minimisation of the weighted Euclidean distance between scores and expected value as the most essential objective of resource integration optimisation modelling and algorithm to highlight the effect of the embeddedness–interaction nexus on dynamic resource integration optimisation. We illustrate the value of the embeddedness–interaction perspective and verify the feasibility and validity of the model and algorithm by applying this optimisation method to a two-country, two-stage, six-resource case.
Journal: International Journal of Production Research
Pages: 7143-7157
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1154622
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154622
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Boris Sokolov
Author-X-Name-First: Boris
Author-X-Name-Last: Sokolov
Author-Name: Inna Solovyeva
Author-X-Name-First: Inna
Author-X-Name-Last: Solovyeva
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Ferry Jie
Author-X-Name-First: Ferry
Author-X-Name-Last: Jie
Title: Dynamic recovery policies for time-critical supply chains under conditions of ripple effect
Abstract: 
 We consider time-critical supply chains (SCs) in the Australia dairy industry and recovery policies in the presence of the ripple effect. Ripple effect is the impact of a disruption on SC economic performance and disruption-based scope of changes needed in the supply structures and parameters to preserve the resilience. First, we describe the ripple effect in general and one example of the ripple effect in the dairy SC in Australia. Second, we present a model for reactive recovery policies in the dairy SC under conditions of the ripple effect and exemplify them on a simulation example. The results of this study can be used in future for comparing proactive and reactive approaches in tackling the ripple effect from resilience and flexibility views.
Journal: International Journal of Production Research
Pages: 7245-7258
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1161253
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1161253
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Template-Type: ReDIF-Article 1.0
Author-Name: Nishikant Mishra
Author-X-Name-First: Nishikant
Author-X-Name-Last: Mishra
Author-Name: Akshit Singh
Author-X-Name-First: Akshit
Author-X-Name-Last: Singh
Author-Name: Sushma Kumari
Author-X-Name-First: Sushma
Author-X-Name-Last: Kumari
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Syed Imran Ali
Author-X-Name-First: Syed Imran
Author-X-Name-Last: Ali
Title: Cloud-based multi-agent architecture for effective planning and scheduling of distributed manufacturing
Abstract: 
 In modern world, manufacturing processes have become very complex because of consistently fluctuating demand of customers. Numerous production facilities located at various geographical locations are being utilised to address the demands of their multiple clients. Often, the components manufactured at distinct locations are being assembled in a plant to develop the final product. In this complex scenario, manufacturing firms have to be responsive enough to cope with the fluctuating demand of customers. To accomplish it, there is a need to develop an integrated, dynamic and autonomous system. In this article, a self-reactive cloud-based multi-agent architecture for distributed manufacturing system is developed. The proposed architecture will assist manufacturing industry to establish real-time information exchange between the autonomous agents, clients, suppliers and manufacturing unit. The mechanism described in this study demonstrates how the autonomous agents interact with each other to rectify the internal discrepancies in manufacturing system. It can also address the external interferences like variations in client’s orders to maximise the profit of manufacturing firm in both short and long term. Execution process of proposed architecture is demonstrated using simulated case study.
Journal: International Journal of Production Research
Pages: 7115-7128
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1165359
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165359
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Template-Type: ReDIF-Article 1.0
Author-Name: Murugappan Elango
Author-X-Name-First: Murugappan
Author-X-Name-Last: Elango
Author-Name: Nachiappan Subramanian
Author-X-Name-First: Nachiappan
Author-X-Name-Last: Subramanian
Author-Name: Romeo Marian
Author-X-Name-First: Romeo
Author-X-Name-Last: Marian
Author-Name: Mark Goh
Author-X-Name-First: Mark
Author-X-Name-Last: Goh
Title: Distributed hybrid multiagent task allocation approach for dual-nozzle 3D printers in microfactories
Abstract: 
 This paper describes a three-dimensional (3D) printing machine with two nozzles that start from different locations and cover all task locations in a short span of time. Many studies have developed algorithms for reducing the total path distance of single-nozzle 3D printers. The present research proposes a hybrid methodology that can balance workloads by equalising task allocations and nozzle path lengths for both nozzles simultaneously. This multiagent task allocation approach can increase the productivity of microfactories that use dual-nozzle 3D printers to fabricate multilayer printed circuit boards. The robustness and solution quality of the method are evaluated using the standard very large-scale integration benchmark data-sets.
Journal: International Journal of Production Research
Pages: 7014-7026
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1171419
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1171419
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Template-Type: ReDIF-Article 1.0
Author-Name: Junliang Wang
Author-X-Name-First: Junliang
Author-X-Name-Last: Wang
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Title: Big data analytics for forecasting cycle time in semiconductor wafer fabrication system
Abstract: 
 In order to improve the prompt delivery reliability of the semiconductor wafer fabrication system, a big data analytics (BDA) is designed to predict wafer lots’ cycle time (CT), which is composed by four parts: data acquisition, data pre-processing, data analysing and data prediction. Firstly, the candidate feature set is constructed to collecting all features by analysing the material flow of wafer foundry. Subsequently, a data pre-processing technique is designed to extract, transform and load data from wafer lot transactions data-set. In addition, a conditional mutual information-based feature selection process is proposed to select key feature subset to reduce the dimension of data-set through data analysing without pre-knowledge. To handle the large volumes of data, a concurrent forecasting model is designed to predict the CT of wafer lots in parallel as well. According to the numerical analysis, the predict accuracy of the presented BDA improves clearly with the increase in data size. And, in the large-scale data-set, the BDA has higher accuracy than linear regression and back-propagation network in CT forecasting.
Journal: International Journal of Production Research
Pages: 7231-7244
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1174789
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1174789
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Template-Type: ReDIF-Article 1.0
Author-Name: Jose-Fernando Jimenez
Author-X-Name-First: Jose-Fernando
Author-X-Name-Last: Jimenez
Author-Name: Abdelghani Bekrar
Author-X-Name-First: Abdelghani
Author-X-Name-Last: Bekrar
Author-Name: Damien Trentesaux
Author-X-Name-First: Damien
Author-X-Name-Last: Trentesaux
Author-Name: Paulo Leitão
Author-X-Name-First: Paulo
Author-X-Name-Last: Leitão
Title: A switching mechanism framework for optimal coupling of predictive scheduling and reactive control in manufacturing hybrid control architectures
Abstract: 
 Nowadays, manufacturing systems are seeking control architectures that offer efficient production performance and reactivity to disruptive events. Dynamic hybrid control architectures are a promising approach as they are not only able to switch dynamically between hierarchical, heterarchical and semi-heterarchical structures, they can also switch the level of coupling between predictive scheduling and reactive control techniques. However, few approaches address an efficient switching process in terms of structure and coupling. This paper presents a switching mechanism framework in dynamic hybrid control architectures, which exploits the advantages of hierarchical manufacturing scheduling systems and heterarchical manufacturing execution systems, and also mitigates the respective reactivity and optimality drawbacks. The main feature in this framework is that it monitors the system dynamics online and shifts between different operating modes to attain the most suitable production control strategy. The experiments were carried out in an emulation of a real manufacturing system to illustrate the benefits of including a switching mechanism in simulated scenarios. The results show that the switching mechanism improves response to disruptions in a global performance indicator as it permits to select the best alternative from several operating modes.
Journal: International Journal of Production Research
Pages: 7027-7042
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1177237
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1177237
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Template-Type: ReDIF-Article 1.0
Author-Name: Jagjit Singh Srai
Author-X-Name-First: Jagjit Singh
Author-X-Name-Last: Srai
Author-Name: Mukesh Kumar
Author-X-Name-First: Mukesh
Author-X-Name-Last: Kumar
Author-Name: Gary Graham
Author-X-Name-First: Gary
Author-X-Name-Last: Graham
Author-Name: Wendy Phillips
Author-X-Name-First: Wendy
Author-X-Name-Last: Phillips
Author-Name: James Tooze
Author-X-Name-First: James
Author-X-Name-Last: Tooze
Author-Name: Simon Ford
Author-X-Name-First: Simon
Author-X-Name-Last: Ford
Author-Name: Paul Beecher
Author-X-Name-First: Paul
Author-X-Name-Last: Beecher
Author-Name: Baldev Raj
Author-X-Name-First: Baldev
Author-X-Name-Last: Raj
Author-Name: Mike Gregory
Author-X-Name-First: Mike
Author-X-Name-Last: Gregory
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Author-Name: B. Ravi
Author-X-Name-First: B.
Author-X-Name-Last: Ravi
Author-Name: Andy Neely
Author-X-Name-First: Andy
Author-X-Name-Last: Neely
Author-Name: Ravi Shankar
Author-X-Name-First: Ravi
Author-X-Name-Last: Shankar
Author-Name: Fiona Charnley
Author-X-Name-First: Fiona
Author-X-Name-Last: Charnley
Author-Name: Ashutosh Tiwari
Author-X-Name-First: Ashutosh
Author-X-Name-Last: Tiwari
Title: Distributed manufacturing: scope, challenges and opportunities
Abstract: 
 This discussion paper aims to set out the key challenges and opportunities emerging from distributed manufacturing (DM). We begin by describing the concept, available definitions and consider its evolution where recent production technology developments (such as additive and continuous production process technologies), digitisation together with infrastructural developments (in terms of IoT and big data) provide new opportunities. To further explore the evolving nature of DM, the authors, each of whom are involved in specific applications of DM research, examine through an expert panel workshop environment emerging DM applications involving new production and supporting infrastructural technologies. This paper presents these generalisable findings on DM challenges and opportunities in terms of products, enabling production technologies and the impact on the wider production and industrial system. Industry structure and location of activities are examined in terms of the democratising impact on participating network actors. The paper concludes with a discussion on the changing nature of manufacturing as a result of DM, from the traditional centralised, large-scale, long lead-time forecast-driven production operations to a new DM paradigm where manufacturing is a decentralised, autonomous near end user-driven activity. A forward research agenda is proposed that considers the impact of DM on the industrial and urban landscape.
Journal: International Journal of Production Research
Pages: 6917-6935
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1192302
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1192302
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Template-Type: ReDIF-Article 1.0
Author-Name: Jagjit Singh Srai
Author-X-Name-First: Jagjit Singh
Author-X-Name-Last: Srai
Author-Name: Camille Ané
Author-X-Name-First: Camille
Author-X-Name-Last: Ané
Title: Institutional and strategic operations perspectives on manufacturing reshoring
Abstract: 
 This research examines manufacturing reshoring from institutional, strategic and operations management perspectives. The multi-disciplinary approach is motivated by the active involvement of institutions in promoting reshoring activity, suggesting institutional factors can be significant in combination with the more traditional drivers of location decision considered in strategic and operations management. The synthesis of several literature domains enables a broader conceptualisation of the dynamics of reshoring. Anecdotal evidence of reshoring activity within industry has not been well evidenced in the extant literature. In this study, we consider emerging data-sets from the UK and France as they represent major developed-world manufacturing nations that have witnessed significant offshoring in recent decades, and where reshoring is now being actively promoted.
Journal: International Journal of Production Research
Pages: 7193-7211
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1193247
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193247
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Template-Type: ReDIF-Article 1.0
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Author-Name: Xiaoxi Wang
Author-X-Name-First: Xiaoxi
Author-X-Name-Last: Wang
Title: Multi-agent-based hierarchical collaborative scheduling in re-entrant manufacturing systems
Abstract: 
 Production scheduling problems in re-entrant manufacturing systems are complex due to their features of large-scale complexity, unbalanced workload and dynamic uncertainty. The aim of this paper is thus to develop an effective way of formulating production schedules for designing RMSs. First, a multi-agent-based hierarchical collaborative system consisting of a system layer, a machine layer, and a material handling device layer is developed to improve the efficiency of RMSs. The objective of the system layer is to maximise the total processing profit, and the objective of the machine layer is to determine the winning bid. Second, a contract net protocol scheduling algorithm is applied to solve capacity planning problems for key machine groups in the system layer. Third, a generalised partial global planning-contract net collaborative mechanism is adopted to allocate tasks to machines within each machine group in the machine layer. Finally, the performance of the proposed approach is validated through a case study, and the results demonstrate that the proposed approach outperforms the first-come first-serve rule in combination with the minimised batch size rule in terms of daily movement and machine utilisation.
Journal: International Journal of Production Research
Pages: 7043-7059
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1194535
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1194535
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Template-Type: ReDIF-Article 1.0
Author-Name: Mukesh Kumar
Author-X-Name-First: Mukesh
Author-X-Name-Last: Kumar
Author-Name: Gary Graham
Author-X-Name-First: Gary
Author-X-Name-Last: Graham
Author-Name: Patrick Hennelly
Author-X-Name-First: Patrick
Author-X-Name-Last: Hennelly
Author-Name: Jagjit Srai
Author-X-Name-First: Jagjit
Author-X-Name-Last: Srai
Title: How will smart city production systems transform supply chain design: a product-level investigation
Abstract: 
 This paper is a first step to understand the role that a smart city with a distributed production system could have in changing the nature and form of supply chain design. Since the end of the Second World War, most supply chain systems for manufactured products have been based on ‘scale economies’ and ‘bigness’; in our paper we challenge this traditional view. Our fundamental research question is: how could a smart city production system change supply chain design? In answering this question, we develop an integrative framework for understanding the interplay between smart city technological initiatives (big data analytics, the industrial Internet of things) and distributed manufacturing on supply chain design. This framework illustrates synergies between manufacturing and integrative technologies within the smart city context and links with supply chain design. Considering that smart cities are based on the collaboration between firms, end-users and local stakeholders, we advance the present knowledge on production systems through case-study findings at the product level. In the conclusion, we stress there is a need for future research to empirically develop our work further and measure (beyond the product level) the extent to which new production technologies such as distributed manufacturing are indeed democratising supply chain design and transforming manufacturing from ‘global production’ to a future ‘city-oriented’ social materiality.
Journal: International Journal of Production Research
Pages: 7181-7192
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1198057
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1198057
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Template-Type: ReDIF-Article 1.0
Author-Name: Letizia Mortara
Author-X-Name-First: Letizia
Author-X-Name-Last: Mortara
Author-Name: Nicolas Gontran Parisot
Author-X-Name-First: Nicolas Gontran
Author-X-Name-Last: Parisot
Title: Through entrepreneurs’ eyes: the Fab-spaces constellation
Abstract: 
 Fabrication spaces (Fab-spaces) provide individuals with access to numerous manufacturing equipment (including additive manufacturing), to carry out different types of projects. Although scholars are starting to speculate about the importance of these new organisational forms and their potential for future distributed innovation and production ecologies, this phenomenon is still largely unexplored. Building on existing multidisciplinary research, this paper offers the first empirical analysis of existing fab-spaces as providers of knowledge and production competencies. Amongst all the possible perspectives to derive a framework, we choose that of fab-space users who have an entrepreneurial intention. After deriving an analytical framework to position fab-spaces in the current academic discourse, the paper develops a classification, which considers the competences available to entrepreneurs, via fab-spaces, in conjunction with how these competences are provided. The resulting map reveals the complementarities amongst the different fab-spaces. It also shows that the current portfolio of fab-spaces supports mainly the distribution of innovation across locations and social groups. Several types of fab-spaces are currently well placed to support the transition from innovation to manufacturing, but their geographical distribution and range of manufacturing capabilities are not yet enough to provide a fully distributed manufacturing model. This study has practical consequences for entrepreneurs, in the better identification of the appropriate fab-spaces for their needs, and for policy-makers, to help position the different types of fab-spaces as elements for national systems of innovation and production.
Journal: International Journal of Production Research
Pages: 7158-7180
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1198505
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1198505
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: (x)-(x)
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1212521
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1212521
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Template-Type: ReDIF-Article 1.0
Author-Name: Jagjit Singh Srai
Author-X-Name-First: Jagjit Singh
Author-X-Name-Last: Srai
Author-Name: Tomás Seosamh Harrington
Author-X-Name-First: Tomás Seosamh
Author-X-Name-Last: Harrington
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Characteristics of redistributed manufacturing systems: a comparative study of emerging industry supply networks
Abstract: 
 This paper explores the characteristics of redistributed manufacturing systems within the context of emerging industry supply networks (EI SNs), with a particular focus on their structure, operations and reconfiguration dynamics. A number of factors have resulted in the redistribution of manufacturing. Within Emerging Industries, advances in process and information technologies, have changed the physical and information characteristics of components and products, and the viable production economies of scale. Further, the emergence of new specialised companies fulfilling key research, production or service roles have changed industry structure and operations, and the conventional model of value creation. Six industrial systems are examined using an Industrial System mapping methodology providing a basis for cross-case analysis, selected on the basis of representing alternative and novel evolution paths that may provide insights into the characteristics of EI SNs within a redistributed manufacturing context. Cross-case analysis suggests several generic aspects to EI SNs, including the blurring of traditional industry boundaries and the critical requirement to manage uncertainty. Alternative forms of EI SNs are observed supporting particular EI evolution paths. Further, more adaptive SNs support increased product variety, with lower inventory models enabled by enhanced production and distribution flexibility, often located closer to demand.
Journal: International Journal of Production Research
Pages: 6936-6955
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1214765
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1214765
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Template-Type: ReDIF-Article 1.0
Author-Name: Dong Xu
Author-X-Name-First: Dong
Author-X-Name-Last: Xu
Author-Name: Sai Srinivas Nageshwaraniyer
Author-X-Name-First: Sai Srinivas
Author-X-Name-Last: Nageshwaraniyer
Author-Name: Young-Jun Son
Author-X-Name-First: Young-Jun
Author-X-Name-Last: Son
Title: A service-oriented simulation integration platform for hierarchical manufacturing planning and control
Abstract: 
 In this paper, a coherent and comprehensive distributed simulation platform is proposed to support hierarchical manufacturing planning and control. This platform enables integration of various hardware and software components within and across supply chain members, such as manufacturing equipment, physics-based process simulators, system-dynamic, agent-based and discrete-event simulators (DESs), and databases via web services technology. At the shop level, a DES model may run in a stand-alone mode, or in conjunction with other simulators (e.g. process or agent-based simulators) and/or hardware (e.g. robots and machines). At the enterprise level, multiple shop floor simulators (each representing a factory) are integrated into a geographically dispersed environment. Exemplary models simulating aircraft drill and assembly on the shop floor are developed in widely used packages, such as Arena®, Simio®, Anylogic® and ESPRIT®, and then integrated. The proposed platform with the hardware-in-the-loop capability is successfully implemented and demonstrated for an automated manufacturing cell in the Computer Integrated Manufacturing and Simulation lab at the University of Arizona. Experiments are conducted using the proposed platform to test (1) reduction in estimated variance of part cycle time given variations in order arrival rate, effectiveness of materials processers and material handlers, and (2) computational time performance of web services. The experimental results reveal that the proposed platform is viable to enable both vertical (shop simulator to equipment level process simulators and/or equipment) as well as horizontal (e.g. multiple shop level simulators) integrations.
Journal: International Journal of Production Research
Pages: 7212-7230
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1221535
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1221535
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Template-Type: ReDIF-Article 1.0
Author-Name: Baldev Raj
Author-X-Name-First: Baldev
Author-X-Name-Last: Raj
Author-Name: Sir Mike Gregory
Author-X-Name-First: Sir Mike
Author-X-Name-Last: Gregory
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Editorial note on the special issue of “Distributed Manufacturing to Enhance Productivity”
Journal: International Journal of Production Research
Pages: 6913-6916
Issue: 23
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2017.1248003
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1248003
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Template-Type: ReDIF-Article 1.0
Author-Name: Jaakko Peltokorpi
Author-X-Name-First: Jaakko
Author-X-Name-Last: Peltokorpi
Author-Name: Henri Tokola
Author-X-Name-First: Henri
Author-X-Name-Last: Tokola
Author-Name: Esko Niemi
Author-X-Name-First: Esko
Author-X-Name-Last: Niemi
Title: Worker coordination policies in parallel station systems: performance models for a set of jobs and for continuous arrival of jobs
Abstract: 
 Varying workloads and uncertain processing times in parallel assembly cause idle times for skilled, high-cost workers. This idleness can be avoided and the utilisation of the workers improved by allowing workers to move between the stations to help each other. Worker movement between assembly stations needs efficient and feasible coordination, and therefore, this paper compares four different worker coordination policies: no helping, floater, pairs and complete helping. The dynamics of the policies are modelled by studying the parallel assembly as a continuous-time Markov process. The system is studied with two different job release cases for non-identical jobs (customised products). In the first case, a given number of jobs have to be completed by the entire system. In the second case, new jobs arrive with a Poisson-distributed rate. The models assume that when one worker helps another, their collaborative inefficiency reduces the productivity. The models are used in numerical experiments to compare the performances of worker coordination policies as average job cycle times. The main conclusions from the results suggest the use of the complete helping policy in minor collaborative inefficiency conditions, especially with a given set of jobs. The pairs policy is a reasonable alternative in major inefficiency conditions with the continuous arrival of jobs.
Journal: International Journal of Production Research
Pages: 1625-1641
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.918290
File-URL: http://hdl.handle.net/10.1080/00207543.2014.918290
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Template-Type: ReDIF-Article 1.0
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Author-Name: Huizhi Ren
Author-X-Name-First: Huizhi
Author-X-Name-Last: Ren
Author-Name: Yang Yang
Author-X-Name-First: Yang
Author-X-Name-Last: Yang
Title: Reheat furnace scheduling with energy consideration
Abstract: 
 This paper focuses on the reheat furnace scheduling problem (RFSP) which is to assign the slabs to the reheat furnace, make the slab sequence for each furnace and determine the feed-in time and the residence time for each slab in order to reduce the unnecessary energy consumption reflected by minimising the objective under consideration. Differing from the traditional scheduling problem, the actual residence time of each slab in RFSP needs to be decided and it is correlated with its neighbour slabs in the reheating sequence of the same furnace. Firstly, the RFSP is formulated as a mixed integer programming model with consideration of the practical production requirements. The strong NP-hardness of the problem motivates us to develop a scatter search (SS) algorithm to solve the problem approximately. The SS algorithm is improved by constraint propagation (CP) for filtering the infeasible solutions in both the generation of the initial solutions and the improvement procedure. To verify the algorithm performance, the proposed algorithm is compared with ILOG CP Optimiser for small-scaled problems and the standard SS, genetic algorithm (GA) for large-scaled practical problems, respectively. The computational results illustrate that the proposed algorithm is relatively effective and efficient.
Journal: International Journal of Production Research
Pages: 1642-1660
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.919418
File-URL: http://hdl.handle.net/10.1080/00207543.2014.919418
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Template-Type: ReDIF-Article 1.0
Author-Name: Tarik Aouam
Author-X-Name-First: Tarik
Author-X-Name-Last: Aouam
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Title: Zero-order production planning models with stochastic demand and workload-dependent lead times
Abstract: 
 We present three different formulations of a simple production planning problem that treat workload-dependent lead times, limited capacity and stochastic demand in an integrated fashion. We compare chance-constrained models, two-stage stochastic programming and robust optimisation using computational experiments. Our results show that the robust optimisation approach is promising, but all the different models face different but challenging issues in addressing this complex problem. We also conclude that successful approximations to this difficult problem with the potential for practical implementation can be developed.
Journal: International Journal of Production Research
Pages: 1661-1679
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.935514
File-URL: http://hdl.handle.net/10.1080/00207543.2014.935514
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehdi Abedi
Author-X-Name-First: Mehdi
Author-X-Name-Last: Abedi
Author-Name: Hany Seidgar
Author-X-Name-First: Hany
Author-X-Name-Last: Seidgar
Author-Name: Hamed Fazlollahtabar
Author-X-Name-First: Hamed
Author-X-Name-Last: Fazlollahtabar
Author-Name: Rohollah Bijani
Author-X-Name-First: Rohollah
Author-X-Name-Last: Bijani
Title: Bi-objective optimisation for scheduling the identical parallel batch-processing machines with arbitrary job sizes, unequal job release times and capacity limits
Abstract: 
 This paper deals the scheduling identical parallel batch-processing machines (BPMs) that each machine can be process a group of jobs as a batch simultaneously. The paper presents a new bi-objective-mixed integer linear programming model for BPM in which arbitrary job size, unequal release time and capacity limits are considered as realistic assumptions occur in the manufacturing environments. The objectives are to minimise the makespan and the total weighted earliness and tardiness of jobs (just in time). After developing a new bi-objective model, an ɛ-constraint method is proposed to solve the problem. This problem has been known as Np-hard. Therefore, two multi-objective optimisation methods, namely, fast non-dominated sorting genetic algorithm (NSGA-II) and multi-objective imperialist competitive algorithm (MOICA) are employed to find the pareto-optimal front for large-sized problems. The parameters of the proposed algorithms are calibrated using Response surface methodology (RSM) and the performances of the proposed algorithms on the problems of various sizes are analysed and the computational results clarify that MOICA outperform than NSGA-II in quality of solutions and computational time.
Journal: International Journal of Production Research
Pages: 1680-1711
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.952795
File-URL: http://hdl.handle.net/10.1080/00207543.2014.952795
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Template-Type: ReDIF-Article 1.0
Author-Name: P. Mohapatra
Author-X-Name-First: P.
Author-X-Name-Last: Mohapatra
Author-Name: A. Nayak
Author-X-Name-First: A.
Author-X-Name-Last: Nayak
Author-Name: S.K. Kumar
Author-X-Name-First: S.K.
Author-X-Name-Last: Kumar
Author-Name: M.K. Tiwari
Author-X-Name-First: M.K.
Author-X-Name-Last: Tiwari
Title: Multi-objective process planning and scheduling using controlled elitist non-dominated sorting genetic algorithm
Abstract: 
 The integration of process planning and scheduling is considered as a critical component in manufacturing systems. In this paper, a multi-objective approach is used to solve the planning and scheduling problem. Three different objectives considered in this work are minimisation of makespan, machining cost and idle time of machines. To solve this integration problem, we propose an improved controlled elitist non-dominated sorting genetic algorithm (NSGA) to take into account the computational intractability of the problem. An illustrative example and five test cases have been taken to demonstrate the capability of the proposed model. The results confirm that the proposed multi-objective optimisation model gives optimal and robust solutions. A comparative study between proposed algorithm, controlled elitist NSGA and NSGA-II show that proposed algorithm significantly reduces scheduling objectives like makespan, cost and idle time, and is computationally more efficient.
Journal: International Journal of Production Research
Pages: 1712-1735
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.957872
File-URL: http://hdl.handle.net/10.1080/00207543.2014.957872
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Template-Type: ReDIF-Article 1.0
Author-Name: Weigang Xu
Author-X-Name-First: Weigang
Author-X-Name-Last: Xu
Author-Name: Le Cao
Author-X-Name-First: Le
Author-X-Name-Last: Cao
Title: Optimal tool replacement with product quality deterioration and random tool failure
Abstract: 
 Operating the machine with a deteriorated cutting tool often leads to poor product quality performance and high risk of tool failure. Replacing the degraded tool is an effective measure to reduce product quality loss and chance of tool failure. Excessive tool replacements, however, may increase the production capacity loss and tool replacement cost. Taking these factors into consideration, this paper presents an approach for determining the optimal tool replacement time for cutting process. It assumes that the product quality deteriorates as cutting tool wears and tool failure occurs randomly during the cutting process. A product quality failure rate model is developed to characterise the deterioration of product quality during the cutting process, and the product quality loss is estimated based on this model. Weibull distribution is employed to describe the stochastic tool life. A tool replacement model is proposed based on balancing the product quality loss, penalty cost for possible tool failure, production capacity loss and tool replacement cost. Sensitivity analysis of the optimal tool replacement decision is presented.
Journal: International Journal of Production Research
Pages: 1736-1745
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.957878
File-URL: http://hdl.handle.net/10.1080/00207543.2014.957878
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiao-Qin Wan
Author-X-Name-First: Xiao-Qin
Author-X-Name-Last: Wan
Author-Name: Hong-Sen Yan
Author-X-Name-First: Hong-Sen
Author-X-Name-Last: Yan
Title: Integrated scheduling and self-reconfiguration for assembly job shop in knowledgeable manufacturing
Abstract: 
 The problems of integrated assembly job shop (AJS) scheduling and self-reconfiguration in knowledgeable manufacturing are studied with the objective of minimising the weighted sum of completion cost of products, the earliness penalty of operations and the training cost of workers. In AJS, each workstation consists of a certain number of teams of workers. A product is assumed to have a tree structure consisting of components and subassemblies. The assembly of components, subassemblies and final products are optimised with the capacity of workstations simultaneously. A heuristic algorithm is developed to solve the problem. Dominance relations of operations are derived and applied in the development of the heuristic. A backward insertion search strategy is designed to locally optimise the operation sequence. Once the optimal schedule is acquired, the teams are reconfigured by transferring them from workstations of lower utilisation to those of higher utilisation. Effectiveness of the proposed algorithm is tested by a number of numerical experiments. The results show that the proposed algorithm promises lower total cost and desirable simultaneous self-reconfiguration in accordance with scheduling.
Journal: International Journal of Production Research
Pages: 1746-1760
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.958595
File-URL: http://hdl.handle.net/10.1080/00207543.2014.958595
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Template-Type: ReDIF-Article 1.0
Author-Name: Reginald Dewil
Author-X-Name-First: Reginald
Author-X-Name-Last: Dewil
Author-Name: Pieter Vansteenwegen
Author-X-Name-First: Pieter
Author-X-Name-Last: Vansteenwegen
Author-Name: Dirk Cattrysse
Author-X-Name-First: Dirk
Author-X-Name-Last: Cattrysse
Author-Name: Manuel Laguna
Author-X-Name-First: Manuel
Author-X-Name-Last: Laguna
Author-Name: Thomas Vossen
Author-X-Name-First: Thomas
Author-X-Name-Last: Vossen
Title: An improvement heuristic framework for the laser cutting tool path problem
Abstract: 
 This paper deals with generating cutting paths for laser cutting machines by representing a tool path in a novel way. Using the new representation, the tool path problem can be viewed as finding a partitioning of contours which minimises the sum of the costs of a rooted directed minimum spanning tree to connect the partitions and the costs of a generalised travelling salesman problem (GTSP) solutions within each partition. Using Edmond–Liu’s algorithm to solve the arborescence problem, an improved Lin–Kernighan heuristic to solve the GTSP and a heuristic-repartitioning approach, tool paths can be generated that are 4.2% faster than those generated by an existing tool path construction heuristic.
Journal: International Journal of Production Research
Pages: 1761-1776
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.959268
File-URL: http://hdl.handle.net/10.1080/00207543.2014.959268
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Template-Type: ReDIF-Article 1.0
Author-Name: Huan-yu Zheng
Author-X-Name-First: Huan-yu
Author-X-Name-Last: Zheng
Author-Name: Ling Wang
Author-X-Name-First: Ling
Author-X-Name-Last: Wang
Title: An effective teaching–learning-based optimisation algorithm for RCPSP with ordinal interval numbers
Abstract: 
 To solve the resource-constrained project-scheduling problem (RCPSP) with ordinal interval numbers, this paper presents an effective teaching–learning-based optimisation (TLBO) algorithm. Ordinal interval number is introduced as a novel tool for handling vague information to describe the RCPSP under uncertain environment. An ordinal interval-based parallel schedule generation scheme is used to generate feasible schedules. Two new phases including the self-study phase and the exam phase are incorporated into the TLBO to enhance the teaching–learning process. In the self-study phase, the population is updated by a mutation operator to prevent premature convergence and to enhance exploration search. In the exam phase, elite students are selected to enhance exploitation search. Moreover, a novel ordinal interval resource-based crossover operator (OIRBCO) is well designed for both the teacher phase and the student phase of the TLBO. Computational comparisons between the OIRBCO and the existing two-point crossover show that OIRBCO is more effective due to the utilisation of the resource information. In addition, statistical comparisons with particle swarm optimisation and simulated annealing show that the proposed TLBO is more effective in solving the RCPSP with ordinal interval numbers.
Journal: International Journal of Production Research
Pages: 1777-1790
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.961205
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961205
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Template-Type: ReDIF-Article 1.0
Author-Name: J.S. Neufeld
Author-X-Name-First: J.S.
Author-X-Name-Last: Neufeld
Author-Name: J.N.D. Gupta
Author-X-Name-First: J.N.D.
Author-X-Name-Last: Gupta
Author-Name: U. Buscher
Author-X-Name-First: U.
Author-X-Name-Last: Buscher
Title: Minimising makespan in flowshop group scheduling with sequence-dependent family set-up times using inserted idle times
Abstract: 
 This paper focuses on the permutation flowshop group scheduling problem to minimise makespan, which is typically found in flowline manufacturing cells. In contrast to classical flowshop scheduling, it is characterised by a scheduling task at two levels: on the one hand, jobs within part families and on the other hand, a number of part families have to be sequenced. Integrating sequence-dependent set-up times for every changeover of families, this problem can represent practical cases. By modelling each family as a job with time lags, some specific problem characteristics of the group scheduling problem are pointed out. It is shown that generating job sequences by minimising the sum of inserted machine idle times instead of makespan on the first level of scheduling and the use of the schedule heads on the second level can lead to significant improvements for some test problems. These findings are used for the improvement of existing constructive heuristic algorithms, whose effectiveness is assessed for several test instances with sequence-dependent family set-up times.
Journal: International Journal of Production Research
Pages: 1791-1806
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.961209
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961209
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:6:p:1791-1806




Template-Type: ReDIF-Article 1.0
Author-Name: Mohand Lounes Bentaha
Author-X-Name-First: Mohand Lounes
Author-X-Name-Last: Bentaha
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: An exact solution approach for disassembly line balancing problem under uncertainty of the task processing times
Abstract: 
 The purpose of this work is to efficiently design disassembly lines taking into account the uncertainty of task processing times. The main contribution of the paper is the development of a decision tool that allows decision-makers to choose the best disassembly alternative (process), for an End of Life product (EOL), and assign the corresponding disassembly tasks to the workstations of the line under precedence and cycle time constraints. Task times are assumed to be random variables with known normal probability distributions. The case of presence of hazardous parts is studied and cycle time constraints are to be jointly satisfied with at least a certain probability level, or service level, fixed by the decision-maker. An AND/OR graph is used to model the precedence relationships among tasks. The objective is to minimise the line cost composed of the workstation operation costs and additional costs of workstations handling hazardous parts of the EOL product. To deal with task time uncertainties, lower and upper-bounding schemes using second-order cone programming and approximations with convex piecewise linear functions are developed. The applicability of the proposed solution approach is shown by solving to optimality a set of disassembly problem instances (EOL industrial products) from the literature.
Journal: International Journal of Production Research
Pages: 1807-1818
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.961212
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961212
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Template-Type: ReDIF-Article 1.0
Author-Name: Min-Geun Kim
Author-X-Name-First: Min-Geun
Author-X-Name-Last: Kim
Author-Name: Jae-Min Yu
Author-X-Name-First: Jae-Min
Author-X-Name-Last: Yu
Author-Name: Dong-Ho Lee
Author-X-Name-First: Dong-Ho
Author-X-Name-Last: Lee
Title: Scheduling algorithms for remanufacturing systems with parallel flow-shop-type reprocessing lines
Abstract: 
 This study considers a scheduling problem for remanufacturing systems in which end-of-life products are separated into their major components at a disassembly workstation, each of them is reprocessed at its dedicated flow-shop-type reprocessing line with serial workstations, and finally, the reprocessed components, together with new components if required, are reassembled into remanufactured products at a reassembly workstation. Among various system configurations, we focus on the one with parallel flow-shop-type reprocessing lines since it is a typical remanufacturing configuration. The problem is to determine the sequence of products to be disassembled, the sequence of components to be reprocessed at each workstation of flow-shop-type reprocessing lines and the sequence of products to be reassembled for the objective of minimising the total flow time. An integer programming model is developed to represent the problem mathematically, and then, three types of heuristics, i.e. priority rule-based heuristic, Nawaz–Enscore–Ham-based heuristic and iterated greedy algorithm, are proposed due to the problem complexity. To show the performances of the heuristics, a series of computational experiments were done on various test instances, and the results are reported.
Journal: International Journal of Production Research
Pages: 1819-1831
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.962112
File-URL: http://hdl.handle.net/10.1080/00207543.2014.962112
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Template-Type: ReDIF-Article 1.0
Author-Name: Alper Türkyılmaz
Author-X-Name-First: Alper
Author-X-Name-Last: Türkyılmaz
Author-Name: Serol Bulkan
Author-X-Name-First: Serol
Author-X-Name-Last: Bulkan
Title: A hybrid algorithm for total tardiness minimisation in flexible job shop: genetic algorithm with parallel VNS execution
Abstract: 
 This paper addresses the flexible-job-shop scheduling problem (FJSP) with the objective of minimising total tardiness. FJSP is the generalisation of the classical job-shop scheduling problem. The difference is that in the FJSP problem, the operations associated with a job can be processed on any set of alternative machines. We developed a new algorithm by hybridising genetic algorithm and variable neighbourhood search (VNS). The genetic algorithm uses advanced crossover and mutation operators to adapt the chromosome structure and the characteristics of the problem. Parallel-executed VNS algorithm is used in the elitist selection phase of the GA. Local search in VNS uses assignment of operations to alternative machines and changing of the order of the selected operation on the assigned machine to increase the result quality while maintaining feasibility. The purpose of parallelisation in the VNS algorithm is to minimise execution time. The performance of the proposed method is validated by numerical experiments on several representative problems and compared with adapted constructive heuristic algorithms’ (earliest due date, critical ratio and slack time per remaining operation) results.
Journal: International Journal of Production Research
Pages: 1832-1848
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.962113
File-URL: http://hdl.handle.net/10.1080/00207543.2014.962113
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:6:p:1832-1848




Template-Type: ReDIF-Article 1.0
Author-Name: Seda Hezer
Author-X-Name-First: Seda
Author-X-Name-Last: Hezer
Author-Name: Yakup Kara
Author-X-Name-First: Yakup
Author-X-Name-Last: Kara
Title: A network-based shortest route model for parallel disassembly line balancing problem
Abstract: 
 Disassembly lines should be balanced efficiently to increase productivity of the line and to reduce disassembly costs. This problem is called disassembly line balancing problem (DLBP). The objective of the DLBP is usually to find the minimum number of disassembly workstations required. This study introduces parallel DLBP (PDLBP) with single-product and proposes a network model based on the shortest route model (SRM) for solving PDLBP. The proposed model is illustrated via numerical examples. A comprehensive experiment is also conducted to evaluate problem-specific features of disassembly lines. To the best of our knowledge, this is the first study dealing with PDLBP. This paper will present a different point of view regarding DLBP.
Journal: International Journal of Production Research
Pages: 1849-1865
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.965348
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965348
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenyou Jia
Author-X-Name-First: Wenyou
Author-X-Name-Last: Jia
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Author-Name: You Li
Author-X-Name-First: You
Author-X-Name-Last: Li
Title: Combined scheduling algorithm for re-entrant batch-processing machines in semiconductor wafer manufacturing
Abstract: 
 In this paper, a new combined scheduling algorithm is proposed to address the problem of minimising total weighted tardiness on re-entrant batch-processing machines (RBPMs) with incompatible job families in the semiconductor wafer fabrication system (SWFS). The general combined scheduling algorithm forms batches according to parameters from the real-time scheduling simulation platform (ReS2), and then sequences batches through slack-based mixed integer linear programming model (S-MILP), which is defined as batch-oriented combined scheduling algorithm. The new combined scheduling algorithm obtains families’ parameters from ReS2 and then sequences these families through modified S-MILP, which is defined as family-oriented combined scheduling algorithm. With rolling horizon control strategy, two combined scheduling algorithms can update RBPMs scheduling continually. The experiments are implemented on ReS2 of SWFS and ILOG CPLEX, respectively. The results demonstrate the effectiveness of our proposed methods.
Journal: International Journal of Production Research
Pages: 1866-1879
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.965355
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965355
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:6:p:1866-1879




Template-Type: ReDIF-Article 1.0
Author-Name: Mehran Tamjidy
Author-X-Name-First: Mehran
Author-X-Name-Last: Tamjidy
Author-Name: Shahla Paslar
Author-X-Name-First: Shahla
Author-X-Name-Last: Paslar
Author-Name: B.T. Hang Tuah Baharudin
Author-X-Name-First: B.T. Hang Tuah
Author-X-Name-Last: Baharudin
Author-Name: Tang Sai Hong
Author-X-Name-First: Tang Sai
Author-X-Name-Last: Hong
Author-Name: M.K.A. Ariffin
Author-X-Name-First: M.K.A.
Author-X-Name-Last: Ariffin
Title: Biogeography based optimization (BBO) algorithm to minimise non-productive time during hole-making process
Abstract: 
 Tool path optimization in today’s manufacturing systems is one of the crucial issues in holes-making machining. This paper presents an evolutionary optimization algorithm based on geographic distribution of biological organism to deal with hole-making process problem. The proposed approach tackles the sequencing problem when several holes must be drilled by means of different tools to reach their desired size. The aim of this study is to minimise the non-productive time, including tool travelling time and tool switching time, by employing biogeography based optimization algorithm, since the problem is considered as NP-hard. The performance of proposed algorithm is evaluated based on various test problems adopted from the literature. The obtained results demonstrate that the proposed algorithm can efficiently improve the solution quality in terms of minimising non-productive time.
Journal: International Journal of Production Research
Pages: 1880-1894
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.965356
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965356
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:6:p:1880-1894




Template-Type: ReDIF-Article 1.0
Author-Name: Sarah Hudson
Author-X-Name-First: Sarah
Author-X-Name-Last: Hudson
Author-Name: Tom McNamara
Author-X-Name-First: Tom
Author-X-Name-Last: McNamara
Author-Name: Sabry Shaaban
Author-X-Name-First: Sabry
Author-X-Name-Last: Shaaban
Title: Unbalanced lines: where are we now?
Abstract: 
 Unbalanced unpaced serial production lines have been the subject of continued interest over the last half a century. Research into these systems taking a diversity of approaches has given rise to a variety of insights which may be of increasing relevance in a context of fast-changing production and flexibility needs. By mapping the major conclusions reached in the area of unpaced asynchronous unbalanced lines over time and from diverse sources, this review identifies some possible future avenues of research that can usefully advance knowledge in this domain.
Journal: International Journal of Production Research
Pages: 1895-1911
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.965357
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965357
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:6:p:1895-1911




Template-Type: ReDIF-Article 1.0
Author-Name: Hany Seidgar
Author-X-Name-First: Hany
Author-X-Name-Last: Seidgar
Author-Name: Mehdi Abedi
Author-X-Name-First: Mehdi
Author-X-Name-Last: Abedi
Author-Name: Sahar Tadayonirad
Author-X-Name-First: Sahar
Author-X-Name-Last: Tadayonirad
Author-Name: Hamed Fazlollahtabar
Author-X-Name-First: Hamed
Author-X-Name-Last: Fazlollahtabar
Title: A hybrid particle swarm optimisation for scheduling just-in-time single machine with preemption, machine idle time and unequal release times
Abstract: 
 This paper addresses preemption in just-in-time (JIT) single–machine-scheduling problem with unequal release times and allowable unforced machine idle time as realistic assumptions occur in the manufacturing environments aiming to minimise the total weighted earliness and tardiness costs. Delay in production systems is a vital item to be focussed to counteract lost sale and back order. Thus, JIT concept is targeted including the elements required such as machine preemption, machine idle time and unequal release times. We proposed a new mathematical model and as the problem is proven to be NP-hard, three meta-heuristic approaches namely hybrid particle swarm optimisation (HPSO), genetic algorithm and imperialist competitive algorithm are employed to solve the problem in larger sizes. In HPSO, cloud theory-based simulated annealing is employed with a certain probability to avoid being trapped in a local optimum. Taguchi method is applied to calibrate the parameters of the proposed algorithms. A number of numerical examples are solved to demonstrate the effectiveness of the proposed approach. The performance of the proposed algorithms is evaluated in terms of relative percent deviation and computational time where the computational results clarify better performance of HPSO than other algorithms in quality of solutions and computational time.
Journal: International Journal of Production Research
Pages: 1912-1935
Issue: 6
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.970705
File-URL: http://hdl.handle.net/10.1080/00207543.2014.970705
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:6:p:1912-1935




Template-Type: ReDIF-Article 1.0
Author-Name: Avi Herbon
Author-X-Name-First: Avi
Author-X-Name-Last: Herbon
Title: Optimal two-level piecewise-constant price discrimination for a storable perishable product
Abstract: 
 Price differentiation over time is an additional policy that firms might consider when determining prices for perishable products. The common policy of a fixed price regardless of freshness might result in leaving some expired inventory unsold. Price differentiation can impact the demand for perishable products, which declines as the expiration date approaches. We develop an optimisation model with the goal of evaluating the monetary effectiveness of the strategy of simultaneously combining price discrimination across heterogeneous consumers with price differentiation over time for perishable inventory under separable multiplicative demand factors of price and time. Necessary optimality equations are derived, and their solutions are proved to constitute a unique global optimal solution. It is proved that an optimal pricing policy is to implement price discrimination with respect to consumers’ sensitivity to freshness, while dynamically changing the price over time, starting with a lower price at the early stages of the product’s shelf life and increasing it at a later stage. The monetary benefit that the retailer and consumer can derive from the suggested pricing policy is evaluated by comparing the model to other models in which price discrimination or dynamic pricing are not implemented. A numerical example that illustrates the significance is introduced. From the analysis of a numerical illustration of the model, it is concluded that a dynamic price discrimination policy can be approximated by an identical-to-all dynamic pricing policy in order to maximise the retailer’s profit and thus, mitigate the retailer’s risk from failing in the process of implementing price discrimination.
Journal: International Journal of Production Research
Pages: 1738-1756
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2015.1018451
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1018451
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Template-Type: ReDIF-Article 1.0
Author-Name: Bo Yan
Author-X-Name-First: Bo
Author-X-Name-Last: Yan
Author-Name: Chenxu Ke
Author-X-Name-First: Chenxu
Author-X-Name-Last: Ke
Title: Two strategies for dynamic perishable product pricing to consider in strategic consumer behaviour
Abstract: 
 The study investigates two dynamic pricing strategies, namely posterior price matching (PM) and delay posterior price matching (DPM). These strategies are used by sellers to consider consumer behaviour in a market with several types of consumers. We analyze reduction season price, purchasing equilibrium and regular selling season price using equilibrium theory and backward induction method. A comparison of these two strategies indicates that both PM and DPM enable sellers to increase price in a regular selling season. Hassle cost and valuation differences between high- and low-end consumers influence the profits and decisions of the seller. PM is the best choice when valuations of low- and high-end consumers vary significantly. When the strategic consumer delaying fraction is small, the advantages of PM are more evident than those of DPM. However, DPM is the best choice when the difference between the valuations of low- and high-end consumers is small, and the strategic consumer delaying fraction is large. An increase in hassle cost also affects the seller’s strategy choice and profits; this effect decreases as strategic consumer delaying fraction increases.
Journal: International Journal of Production Research
Pages: 1757-1772
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2015.1035814
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1035814
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuanchun Jiang
Author-X-Name-First: Yuanchun
Author-X-Name-Last: Jiang
Author-Name: Yezheng Liu
Author-X-Name-First: Yezheng
Author-X-Name-Last: Liu
Author-Name: Hai Wang
Author-X-Name-First: Hai
Author-X-Name-Last: Wang
Author-Name: Jennifer Shang
Author-X-Name-First: Jennifer
Author-X-Name-Last: Shang
Author-Name: Shuai Ding
Author-X-Name-First: Shuai
Author-X-Name-Last: Ding
Title: Online pricing with bundling and coupon discounts
Abstract: 
 We propose an online pricing strategy by utilising product bundling and coupon discounts. Given customer’s purchase behaviour and preference for bundling and coupon, we propose a nonlinear mixed-integer programming model to determine the most appropriate bundle discount and instant coupon so as to maximise e-tailer’s profit. A fast heuristic algorithm is designed to implement the proposed model online in real time. We investigate the robustness of the proposed method by examining how uncertainties in system parameters affect performance. Through collaborative optimisation, we offer important insights and managerial implications, and show how marketers can attract more purchase and maximise profit by properly integrating marketing tools such as bundling and coupon.
Journal: International Journal of Production Research
Pages: 1773-1788
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2015.1112443
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1112443
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1773-1788




Template-Type: ReDIF-Article 1.0
Author-Name: Chunqiao Tan
Author-X-Name-First: Chunqiao
Author-X-Name-Last: Tan
Author-Name: Zhaodu Liu
Author-X-Name-First: Zhaodu
Author-X-Name-Last: Liu
Author-Name: Desheng Dash Wu
Author-X-Name-First: Desheng Dash
Author-X-Name-Last: Wu
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Title: Cournot game with incomplete information based on rank-dependent utility theory under a fuzzy environment
Abstract: 
 In most existing literatures on Cournot game, game behaviour between players is based on the hypothesis that people are complete rationality. However, players’ decisions are often affected by their behavioural characteristic and psychology preference. Traditional Cournot model also doesn’t deal with ambiguous information. Based on rank-dependent utility theory, this paper develops an incomplete information Cournot game in an ambiguous decision environment, where the form of ambiguity is described by a set of fuzzy parameters, and behavioural pattern is reflected by means of emotional function in rank-dependent utility. Further, we investigate the Nash equilibrium quantity of each manufacture in this kind of fuzzy Cournot game with incomplete information. Finally, the proposed Cournot model is applied to a case study, and dynamic variation and sensitivity analysis of optimal quantity with respect to decision-maker’s behaviour pattern are discussed in detailed, which illustrates that the proposed Cournot model is more reasonable than traditional Cournot model.
Journal: International Journal of Production Research
Pages: 1789-1805
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2015.1131865
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1131865
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1789-1805




Template-Type: ReDIF-Article 1.0
Author-Name: Peng Du
Author-X-Name-First: Peng
Author-X-Name-Last: Du
Author-Name: Lei Xu
Author-X-Name-First: Lei
Author-X-Name-Last: Xu
Author-Name: Qiushuang Chen
Author-X-Name-First: Qiushuang
Author-X-Name-Last: Chen
Author-Name: Sang-Bing Tsai
Author-X-Name-First: Sang-Bing
Author-X-Name-Last: Tsai
Title: Pricing competition on innovative product between innovator and entrant imitator facing strategic customers
Abstract: 
 When an innovative product is introduced into the market, innovators always face competition from entrant imitators. Strategic customers may also anticipate this and can design their purchase plans accordingly. In this study, we develop a dynamic game model to formulate the problem associated with competitive product pricing between an innovator and an imitator for obtaining a pricing equilibrium. The influence of various factors on pricing policies, market sales and profits are analysed. We argue that when anticipating forthcoming competitors, innovators should not price too highly in the monopoly stage. The optimal monopoly price decreases with the quality ratio and forms a U shape along with the dimension of customers’ strategic level; however, the right tail of the U is mitigated when the quality ratio increases. In the duopoly phase, the markdown for the innovator and the difference in product cost performance between the innovator and imitator are investigated. We then analyse the value of demand information. The numerical analysis indicates that the value decreases with customers’ strategic level and increases with the quality ratio. The revealing behaviour of the innovator influences the imitator marginally in pricing and considerably in profit. Finally, a medium level is always preferred when the imitator chooses the product quality level.
Journal: International Journal of Production Research
Pages: 1806-1824
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2015.1134837
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1134837
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1806-1824




Template-Type: ReDIF-Article 1.0
Author-Name: Sanjeet Singh
Author-X-Name-First: Sanjeet
Author-X-Name-Last: Singh
Author-Name: Nivedita Haldar
Author-X-Name-First: Nivedita
Author-X-Name-Last: Haldar
Author-Name: Anindya Bhattacharya
Author-X-Name-First: Anindya
Author-X-Name-Last: Bhattacharya
Title: Offshore manufacturing contract design based on transfer price considering green tax: a bilevel programming approach
Abstract: 
 The problem of designing offshore manufacturing contract resulting in optimal transfer price is troubling multinational companies over the past few years. This paper proposes designing offshore manufacturing contracts based on the transfer price in the form of bilevel programming problems after considering green tax. In these contract designs, a firm in a developed country sells a single product in its market. The same product is simultaneously being manufactured by another firm in a developing country with lower manufacturing cost. After anticipating the consumer demand, the seller places an order, based on which the manufacturer manufactures the ordered quantity, and offers a transfer price which in turn maximises its net profit after paying green tax to its government. While setting the transfer price, the manufacturer considers the manufacturing cost, the export duty payable to its government and the cost of shipping the product to the developed country. After buying the product from the manufacturer at the transfer price, the seller then sets the retail price which maximises its net profit after paying the import duty to its government; the retail price, however, must not be more than the maximum retail price applicable to the market. Thus, offshore manufacturing contract results in optimal after-tax profits for both the firms. An experimental study has been carried out to discuss the practical aspects of the results developed, where a US firm is offshoring its manufacturing activity to a Chinese firm in order to draw maximum profit.
Journal: International Journal of Production Research
Pages: 1825-1849
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2016.1144940
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1144940
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Template-Type: ReDIF-Article 1.0
Author-Name: Pei Li
Author-X-Name-First: Pei
Author-X-Name-Last: Li
Author-Name: Zhangxi Lin
Author-X-Name-First: Zhangxi
Author-X-Name-Last: Lin
Author-Name: Yang Yu
Author-X-Name-First: Yang
Author-X-Name-Last: Yu
Title: Integrating the mechanism of three-part tariff pricing to the provision of intra-site search engine advertising services
Abstract: 
 Intra-site search engines (ISEs) dedicated to private electronic markets have become popular with the fast-growing electronic markets. Among several research facets regarding the advertising services of ISEs, we focus on how to optimise the ISE-based advertising market mechanism by improving the pricing model. The widely adopted pricing scheme, Flat Fee (FF), fails to differentiate ISE advertising services among subscribers. Such inefficiency results in the loss of the subscribers and the decline of the provider’s revenue. We design an advanced pricing scheme, three-part tariff pricing with performance relevant adjustments (3PT+), implemented by a two-period contract, to match the differentiated ISE service consumption among subscribers. The mathematical analyses of the advertiser’s VaR model and ISE provider’s revenue optimisation model show that the 3PT+ pricing scheme is superior to the FF pricing scheme as the former can attract more advertisers and retain most of them in the ISE services. The experimental results from the Monte Carlo simulation further support the theoretic derivation.
Journal: International Journal of Production Research
Pages: 1850-1864
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2016.1162339
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1162339
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1850-1864




Template-Type: ReDIF-Article 1.0
Author-Name: Ying-Chyi Chou
Author-X-Name-First: Ying-Chyi
Author-X-Name-Last: Chou
Author-Name: Hsin-Yi Yen
Author-X-Name-First: Hsin-Yi
Author-X-Name-Last: Yen
Author-Name: Shao-Jung Yu
Author-X-Name-First: Shao-Jung
Author-X-Name-Last: Yu
Title: Developing a temporary workforce transaction mechanism from risk sharing perspectives
Abstract: 
 In a low-profit environment, numerous firms no longer use traditional hiring practices and are forced to use a temporary workforce; these practices result in a more flexible workforce. Although outsourcing provides several benefits, it has a high level of risk. Therefore, implementing an enterprise risk management programme is crucial for using temporary labour. This study investigated the condition under which the multiperiod contract of a temporary work agency prohibits labour shortages. This investigation was performed to improve the effectiveness of dispatch contract designs. This study incorporated the concepts of labour demand forecasting and risk sharing and proposes two types of quantity flexibility contracts, period quantity adjustment and total quantity adjustment, to develop an optimal manpower dispatch contract model. An optimal manpower dispatch contract model must coordinate the interests of a temporary work agency and user firms to increase profits for both firms and must be flexible enough to allow for numerous order adjustments. To achieve this objective, this study used sensitivity analysis and an experimental design methodology to analyse the benefits of period quantity adjustment and total quantity adjustment and, accordingly, determine the factors that influence the total expected profit.
Journal: International Journal of Production Research
Pages: 1865-1881
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2016.1174341
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1174341
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1865-1881




Template-Type: ReDIF-Article 1.0
Author-Name: Jing Zhao
Author-X-Name-First: Jing
Author-X-Name-Last: Zhao
Author-Name: Jie Wei
Author-X-Name-First: Jie
Author-X-Name-Last: Wei
Author-Name: Yongjian Li
Author-X-Name-First: Yongjian
Author-X-Name-Last: Li
Title: Pricing decisions of complementary products in a two-level fuzzy supply chain
Abstract: 
 Pricing decisions of two complementary products in a two-level fuzzy supply chain with two manufacturers and one common retailer are studied in this paper. By considering the two manufacturers and one common retailer’s leader–follower relationship, the two manufacturers’ pricing strategy and the fuzzy uncertainties associated with the manufacturing costs and customer demands of the complementary products, seven pricing games are considered. The corresponding closed-form optimal pricing decisions are obtained in the seven pricing games. Through using numerical studies and sensitivity analysis of parameters’ fuzzy degree, we compare the analytical results of different games and investigate the firms’ optimal decisions facing changing pricing environments. At last, we analyse the effect of the fuzzy degree of key parameters on optimal prices, maximal expected demands and maximal expected profits of different games. Some interesting and valuable managerial insights are established.
Journal: International Journal of Production Research
Pages: 1882-1903
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2016.1234082
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1234082
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1882-1903




Template-Type: ReDIF-Article 1.0
Author-Name: Denis M. Becker
Author-X-Name-First: Denis M.
Author-X-Name-Last: Becker
Author-Name: Alexei A. Gaivoronski
Author-X-Name-First: Alexei A.
Author-X-Name-Last: Gaivoronski
Title: Optimisation approach to target costing under uncertainty with application to ICT-service
Abstract: 
 Target costing is a modern approach applied during product development that defines cost targets for products and its components. These cost targets are driven by customer requirements and achievable revenues. The intention of this paper is the integration of target costing with modern concepts of modelling uncertainty and management of risk based on optimisation. Contrary to the traditional focus of target costing on cost targets, this paper prefers a strategy for achieving a target profit. Moreover, in this paper target costing is understood as a continuous process with incremental changes of cost drivers, product and component design as well as product prices. Therefore, the change in costs and profit with respect to aforementioned control parameters is modelled by linear approximations. Hence, improved decisions concerning design and prices are derived by linear programming models. In practice, information concerning product and component costs, demand or customer preferences are not given with certainty. Therefore, we apply a stochastic programming approach to manage the risk inherent in the target costing process. After a general presentation, we apply our approach to the provision of an information and communication technology service where the level of uncertainty is considerable.
Journal: International Journal of Production Research
Pages: 1904-1917
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2016.1275870
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1275870
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Template-Type: ReDIF-Article 1.0
Author-Name: Shiming Deng
Author-X-Name-First: Shiming
Author-X-Name-Last: Deng
Author-Name: Xuan Jiang
Author-X-Name-First: Xuan
Author-X-Name-Last: Jiang
Author-Name: Yanhai Li
Author-X-Name-First: Yanhai
Author-X-Name-Last: Li
Title: Optimal price and maximum deal size on group-buying websites for sellers with finite capacity
Abstract: 
 This paper presents an analytical model for sellers with finite capacity to optimise their price and maximum deal size limit on group-buying websites. For the general demand functions that satisfy some mild regularity conditions, the optimal strategies and the corresponding deal parameters are characterised. The optimal strategies demonstrate that deep online discounts (selling products below the cost or even selling products for free) can be optimal if the maximum deal size is used strategically. Moreover, deep discounts can be beneficial even if the capacity is tight, which explains the use of deep discounts commonly observed in practice. Our results also provide the operators of group-buying websites with useful suggestions on how to induce sellers to offer deep discounts. Sensitivity analysis with regard to the minimum deal size and capacity is provided. Our analysis shows that counter-intuitively selling out capacity may not always be optimal, even if the amount of capacity cannot satisfy the unconstrained optimal sales quantity online. Finally, we extend the model to consider offline prices being sellers’ decisions and discuss the robustness of the optimal strategies when the demand is stochastic.
Journal: International Journal of Production Research
Pages: 1918-1933
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1282643
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1282643
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Template-Type: ReDIF-Article 1.0
Author-Name: Zengqiang Wang
Author-X-Name-First: Zengqiang
Author-X-Name-Last: Wang
Author-Name: Richard Y.K. Fung
Author-X-Name-First: Richard Y.K.
Author-X-Name-Last: Fung
Author-Name: Yan-Lai Li
Author-X-Name-First: Yan-Lai
Author-X-Name-Last: Li
Author-Name: Yun Pu
Author-X-Name-First: Yun
Author-X-Name-Last: Pu
Title: An integrated decision-making approach for designing and selecting product concepts based on QFD and cumulative prospect theory
Abstract: 
 In this paper, both unbalanced linguistic terms and a risk decision-making problem with developers’ bounded rationality are considered; an integrated approach of Quality Function Deployment (QFD) and Cumulative Prospect Theory (CPT) is proposed to help increase customer satisfaction and facilitate product concepts selection. Firstly, QFD is employed to provide a customer-driven tool for developers, which can be used to generate product concept alternatives. Subsequently, enhanced information entropy is utilised to prioritise competing Customer requirements (CRs) based on unbalanced linguistic terms. These terms can be directly processed without being translated into fuzzy numbers, where the risk of information loss in fuzzification can be minimised. Product concept alternatives can be generated based on the outcomes of the subsequent QFD process. Moreover, CPT can be considered as a novel method by incorporating the developers’ psychological characteristics under risk, which can help identify the most relevant product concepts. The cost prospect values of each alternative can be calculated by the function based on the cost reference point. The deficit and profit prospect values can be obtained by aggregating the values and weights of potential results, where functions from the enhanced CPT are used. The order of all alternatives can be ranked based on their overall prospect values. Finally, the proposed approach can be evaluated by a case study concerning the development of a new hydraulic breaker. The deliverables of this study are used to evaluate the relative advantages of the proposed approach over existing multi-attribute utility ones.
Journal: International Journal of Production Research
Pages: 2003-2018
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1351632
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1351632
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Template-Type: ReDIF-Article 1.0
Author-Name: Konstantin Biel
Author-X-Name-First: Konstantin
Author-X-Name-Last: Biel
Author-Name: Fu Zhao
Author-X-Name-First: Fu
Author-X-Name-Last: Zhao
Author-Name: John W. Sutherland
Author-X-Name-First: John W.
Author-X-Name-Last: Sutherland
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Title: Flow shop scheduling with grid-integrated onsite wind power using stochastic MILP
Abstract: 
 Over the last decade, manufacturing companies have identified renewable energy as a promising means to cope with time-varying energy prices and to reduce energy-related greenhouse gas emissions. As a result of this development, global installed capacity of wind power has expanded significantly. To make efficient use of onsite wind power generation facilities in manufacturing, production scheduling tools need to consider the uncertainty attached to wind power generation along with changes in the energy procurement cost and in the products’ environmental footprints. To this end, we propose a solution procedure that first generates a large number of wind power scenarios that characterise the variability in wind power over time. Subsequently, a two-stage stochastic optimisation procedure computes a production schedule and energy supply decisions for a flow shop system. In the first stage, a bi-objective mixed integer linear programme simultaneously minimises the total weighted flow time and the expected energy cost, based on the generated wind power scenarios. In the second stage, energy supply decisions are adjusted based on real-time wind power data. A numerical example is used to illustrate the ability of the developed decision support tool to handle the uncertainty attached to wind power generation and its effectiveness in realising energy-related objectives in manufacturing.
Journal: International Journal of Production Research
Pages: 2076-2098
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1351638
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1351638
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:2076-2098




Template-Type: ReDIF-Article 1.0
Author-Name: Enzo Morosini Frazzon
Author-X-Name-First: Enzo Morosini
Author-X-Name-Last: Frazzon
Author-Name: Andre Albrecht
Author-X-Name-First: Andre
Author-X-Name-Last: Albrecht
Author-Name: Matheus Pires
Author-X-Name-First: Matheus
Author-X-Name-Last: Pires
Author-Name: Eduardo Israel
Author-X-Name-First: Eduardo
Author-X-Name-Last: Israel
Author-Name: Mirko Kück
Author-X-Name-First: Mirko
Author-X-Name-Last: Kück
Author-Name: Michael Freitag
Author-X-Name-First: Michael
Author-X-Name-Last: Freitag
Title: Hybrid approach for the integrated scheduling of production and transport processes along supply chains
Abstract: 
 The rise of new information and communication technologies leads to enhanced information transparency in supply chains. In order to utilise the resulting potentials, novel scheduling approaches that are capable of processing large amounts of data and coping with dynamic disturbances of manufacturing and transport stages have to be developed. For this purpose, the paper at hand proposes a hybrid approach for the integrated scheduling of production and transport processes along supply chains. The procedure combines mixed integer linear programming, discrete event simulation and a genetic algorithm. Obtained results show a significant reduction in the number of late orders, substantiating that proper scheduling approaches combined with information visibility allow for operational improvements in manufacturing supply chains.
Journal: International Journal of Production Research
Pages: 2019-2035
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1355118
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355118
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:2019-2035




Template-Type: ReDIF-Article 1.0
Author-Name: Pamela Danese
Author-X-Name-First: Pamela
Author-X-Name-Last: Danese
Author-Name: Margherita Molinaro
Author-X-Name-First: Margherita
Author-X-Name-Last: Molinaro
Author-Name: Pietro Romano
Author-X-Name-First: Pietro
Author-X-Name-Last: Romano
Title: Managing evolutionary paths in Sales and Operations Planning: key dimensions and sequences of implementation
Abstract: 
 Sales and Operations Planning (S&amp;OP) is a key process that improves integration and communication between business functions and aligns the plans of a company into one integrated set of plans. This article focuses on the so-called S&amp;OP ‘maturity models’, which describe the successive stages in the advancement of S&amp;OP process according to a precise set of dimensions. These models are specifically thought to plan the transitions towards advanced stages, rather than to provide guidance on how to execute them. This paper aims to address this research gap by investigating how the dimensions evolve and interact during the execution of the transition between two subsequent stages. Three case studies of S&amp;OP transitions with different starting and destination maturity stages have been compared. The findings demonstrate that the degree of seriality vs. parallelism among actions on different S&amp;OP dimensions during the transition depends on the evolution stage of S&amp;OP process. The study sheds light on the dynamics among the dimensions during the different transitions and warns managers not to underestimate the criticality of the people and organisation dimension, whose importance grows as the maturity level increases.
Journal: International Journal of Production Research
Pages: 2036-2053
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1355119
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355119
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Template-Type: ReDIF-Article 1.0
Author-Name: Hongbo Li
Author-X-Name-First: Hongbo
Author-X-Name-Last: Li
Author-Name: Li Xiong
Author-X-Name-First: Li
Author-X-Name-Last: Xiong
Author-Name: Yinbin Liu
Author-X-Name-First: Yinbin
Author-X-Name-Last: Liu
Author-Name: Haitao Li
Author-X-Name-First: Haitao
Author-X-Name-Last: Li
Title: An effective genetic algorithm for the resource levelling problem with generalised precedence relations
Abstract: 
 Resource levelling aims to obtain a feasible schedule to minimise the resource usage fluctuations during project execution. It is of crucial importance in project scheduling to ensure the effective use of scarce and expensive renewable resources, and has been successfully applied to production environments, such as make-to-order and engineering-to-order systems. In real-life projects, general temporal relationships are often needed to model complex time-dependencies among activities. We develop a novel genetic algorithm (GA) for the resource levelling problem with generalised precedence relations. Our design and implementation of GA features an efficient schedule generation scheme, built upon a new encoding mechanism that combines the random key representation and the shift vector representation. A two-pass local search-based improvement procedure is devised and integrated into the GA to enhance the algorithmic performance. Our GA is able to obtain near optimal solutions with less than 2% optimality gap for small instances in fractions of a second. It outperforms or is competitive with the state-of-the-art algorithms for large benchmark instances with size up to 1000 activities.
Journal: International Journal of Production Research
Pages: 2054-2075
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1355120
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355120
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:2054-2075




Template-Type: ReDIF-Article 1.0
Author-Name: Han Zhu
Author-X-Name-First: Han
Author-X-Name-Last: Zhu
Author-Name: Youhua (Frank) Chen
Author-X-Name-First: Youhua (Frank)
Author-X-Name-Last: Chen
Author-Name: Eman Leung
Author-X-Name-First: Eman
Author-X-Name-Last: Leung
Author-Name: Xing Liu
Author-X-Name-First: Xing
Author-X-Name-Last: Liu
Title: Outpatient appointment scheduling with unpunctual patients
Abstract: 
 This study examines the design of appointment scheduling policies with considerations of not only the conventional factors, for example, the random consultation time and multiple patient types, but also of a new factor, particularly, patient unpunctuality, that is, one patient may arrive earlier or later than the appointment time. Patient unpunctuality negatively affects the appointment scheduling system, for example, such behaviour, reduces provider productivity and clinical efficiency, increases health care costs, and limits the ability of a clinic to serve its patients population by reducing the clinic’s effective capacity. In this study, while considering patient unpunctuality, we first introduce an analytical model and show the optimality of a fixed-interval policy for a simplified two-patient model. Motivated by the result, we propose an easy-to-implement heuristic policy with a simple structure using a simulation framework to improve the performance of the appointment scheduling system. The simulation result shows that our policy is overwhelmingly preponderant in current practice. We also measure the effect of patient unpunctuality and other factors. Actual data are used to add realism to the input parameters, and practical guidelines are developed for appointment scheduling.
Journal: International Journal of Production Research
Pages: 1982-2002
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1355574
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355574
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1982-2002




Template-Type: ReDIF-Article 1.0
Author-Name: Liangyan Tao
Author-X-Name-First: Liangyan
Author-X-Name-Last: Tao
Author-Name: Desheng Dash Wu
Author-X-Name-First: Desheng Dash
Author-X-Name-Last: Wu
Author-Name: Sifeng Liu
Author-X-Name-First: Sifeng
Author-X-Name-Last: Liu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Optimal due date quoting for a risk-averse decision-maker under CVaR
Abstract: 
 This study investigates a due date quoting problem for a project with stochastic duration, taking the decision-maker’s risk attitude into consideration. The project profit is defined as the difference between the price and the cost that is comprised of production cost and earliness–tardiness penalties. In this situation, the due date determination has to be modelled as a stochastic optimisation due to stochastic duration. Conditional value at risk is thus employed as a performance measure to describe the decision-maker’s risk attitude. In fixed price contract, when the unit production cost is not smaller than the unit penalty on earliness, the optimal due date increases with the increase of the degree of a decision-maker’s risk aversion, the unit penalty on delay, and the decrease of the unit penalty on earliness. Besides, when the price is proportional to the due date and the slope is no bigger than the unit penalty on tardiness, the optimal due date is smaller than the result in fixed price. This is because high price for a short due date encourages a decision-maker to quote a small due date. Further, we compare the optimal due date in different parameter setting where the penalty coefficient of earliness is negative or zero, which means there is reward or no penalty on earliness, respectively. Finally, a case study is conducted to validate the effectiveness and efficiency of the proposed model.
Journal: International Journal of Production Research
Pages: 1934-1959
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1394587
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394587
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1934-1959




Template-Type: ReDIF-Article 1.0
Author-Name: Desheng Dash Wu
Author-X-Name-First: Desheng Dash
Author-X-Name-Last: Wu
Author-Name: Anthony Ross
Author-X-Name-First: Anthony
Author-X-Name-Last: Ross
Title: Pricing optimization, channel and uncertainty
Abstract: 
 This paper conducts a state-of-the-art review for a particular emerging field of Production Research: pricing optimisation, channel and uncertainty. This is achieved by presenting a set of state-of-the-art papers accepted to this special issue, and co-word analysis to trace the development of this research field. Data for co-word analysis is based on literature search in the International Journal of Production Research, since 1961 using Web of Science with the Keywords ‘pricing optimization’, ‘channel’ or ‘uncertainty’. Pricing approaches and tools have attracted more and more attentions from multiple disciplinary such as supply-chain management and marketing. The objective of this special issue is to contribute new insights to the extant body of knowledge in pricing optimisation, channel and uncertainty, specifically for 55th anniversary of International Journal of Production Research.
Journal: International Journal of Production Research
Pages: 1733-1737
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1398433
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398433
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1733-1737




Template-Type: ReDIF-Article 1.0
Author-Name: Danqin Yang
Author-X-Name-First: Danqin
Author-X-Name-Last: Yang
Author-Name: Tiaojun Xiao
Author-X-Name-First: Tiaojun
Author-X-Name-Last: Xiao
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Title: Optimal reservation pricing strategy for a fashion supply chain with forecast update and asymmetric cost information
Abstract: 
 We address the reservation pricing problem for a two-echelon fashion supply chain in which the downstream manufacturer with private information on its operations cost (low or high type) reserves the capacity for a critical component from the upstream supplier before placing the final order. We consider the case when the demand forecast is partially updated. We find that a novel menu of reservation contracts containing the unit reservation fee with reservation quantity and final order could induce the manufacturer to reveal its operations cost information truthfully. We also show that the supplier should require less capacity reservation and charge a lower unit reservation fee if it has asymmetric information about the manufacturer’s operations cost. Finally, we analyse the effects of forecast update, and our results indicate that: (i) the supplier benefits from forecast update because the optimal reservation pricing strategy is designed to reveal the true information and meanwhile induce a higher capacity reservation; and (ii) a greater amount of forecast update decreases the supply chain deficit and increases the supplier’s agency cost.
Journal: International Journal of Production Research
Pages: 1960-1981
Issue: 5
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2014.998789
File-URL: http://hdl.handle.net/10.1080/00207543.2014.998789
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1960-1981




Template-Type: ReDIF-Article 1.0
Author-Name: Xiu Ning
Author-X-Name-First: Xiu
Author-X-Name-Last: Ning
Author-Name: Pingke Li
Author-X-Name-First: Pingke
Author-X-Name-Last: Li
Title: A cross-entropy approach to the single row facility layout problem
Abstract: 
 The single row facility layout problem is to arrange a given number of facilities along a straight line so as to minimise the total cost associated with the interactions between the facilities. In this paper, a metaheuristic algorithm based on the cross-entropy method, incorporating a local search procedure and symmetry-breaking techniques, is developed to solve this problem. The proposed algorithm has been tested on some widely used benchmark instances. The computational results show that the proposed algorithm has found the optimal or the best solutions known so far for the instances of size with up to 100 facilities and is competitive with some existing algorithms.
Journal: International Journal of Production Research
Pages: 3781-3794
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2017.1399221
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1399221
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:11:p:3781-3794




Template-Type: ReDIF-Article 1.0
Author-Name: Moustafa Gadalla
Author-X-Name-First: Moustafa
Author-X-Name-Last: Gadalla
Author-Name: Deyi Xue
Author-X-Name-First: Deyi
Author-X-Name-Last: Xue
Title: An approach to identify the optimal configurations and reconfiguration processes for design of reconfigurable machine tools
Abstract: 
 A reconfigurable machine tool (RMT) is a special machine that can deliver different machining functions through reconfiguration processes among its configurations during the machine utilisation stage. In this research, a new approach is developed to identify the optimal configurations and the reconfiguration processes for design of the RMTs. In this work, a generic design AND-OR tree is used to model different design solution candidates, their machine configurations and parameters of these configurations. A specific design solution is created from the generic design AND-OR tree through tree-based search and modelled by different machine configurations. For a reconfiguration process between two machine configurations, a generic process AND-OR graph is used to model reconfiguration operation candidates, sequential constraints among operations and operation parameters. A graph-based search is used to generate all feasible reconfiguration process candidates from the generic process AND-OR graph. The optimal design is identified by multi-level and multi-objective hybrid optimisation. A case study is developed to show how this new approach is used for the optimal design of a RMT.
Journal: International Journal of Production Research
Pages: 3880-3900
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2017.1406674
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1406674
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Template-Type: ReDIF-Article 1.0
Author-Name: Shokraneh K. Moghaddam
Author-X-Name-First: Shokraneh K.
Author-X-Name-Last: Moghaddam
Author-Name: Mahmoud Houshmand
Author-X-Name-First: Mahmoud
Author-X-Name-Last: Houshmand
Author-Name: Omid Fatahi Valilai
Author-X-Name-First: Omid
Author-X-Name-Last: Fatahi Valilai
Title: Configuration design in scalable reconfigurable manufacturing systems (RMS); a case of single-product flow line (SPFL)
Abstract: 
 The dynamic nature of today’s manufacturing industry, which is caused by the intense global competition and constant technological advancements, requires systems that are highly adaptive and responsive to demand fluctuations. Reconfigurable manufacturing systems (RMS) enable such responsiveness through their main characteristics. This paper addresses the problem of RMS configuration design, where the demand of a single product varies throughout its production life cycle, and the system configuration must change accordingly to satisfy the required demand with minimum cost. A two-phased method is developed to handle the primary system configuration design and the necessary system reconfigurations according to demand rate changes. This method takes advantage of Reconfigurable Machine Tools in RMS. In fact, by adding/removing modules to/from a specific modular reconfigurable machine, its production capability could be increased, with lower cost. A novel mixed integer linear programming formulation is presented in the second phase of the method to optimise the process of selecting the best possible transformation for the existing machine configurations. Two different cases are designed and solved by implementing the established method. The results of these cases in terms of capital cost, capacity expansion cost, unused capacity and number of transformations, are compared with two hypothetical scenarios. Analyses of the obtained results indicate the efficiency of the proposed approach and offer a promising outlook for further research.
Journal: International Journal of Production Research
Pages: 3932-3954
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2017.1412531
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412531
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Template-Type: ReDIF-Article 1.0
Author-Name: Wilfred H. Knol
Author-X-Name-First: Wilfred H.
Author-X-Name-Last: Knol
Author-Name: Jannes Slomp
Author-X-Name-First: Jannes
Author-X-Name-Last: Slomp
Author-Name: Roel L.J. Schouteten
Author-X-Name-First: Roel L.J.
Author-X-Name-Last: Schouteten
Author-Name: Kristina Lauche
Author-X-Name-First: Kristina
Author-X-Name-Last: Lauche
Title: Implementing lean practices in manufacturing SMEs: testing ‘critical success factors’ using Necessary Condition Analysis
Abstract: 
 Lean practices are known to increase operational performance. Previous research has identified critical success factors for implementing lean practices. This research aims to examine the extent to which success factors are critical for various degrees of lean practice implementation. Using multiple-respondent self-assessments from 33 Dutch manufacturing small and medium-sized enterprises (SMEs), we conducted a Necessary Condition Analysis. Our findings indicated that the criticality of success factors is progression dependent. In the initial stages of the lean journey, SMEs could improve their lean practices in a bottom-up manner through local factors such as a learning focus, improvement training and support congruence. When lean practices are more advanced, some company-wide factors must be present: top management support, a shared improvement vision and a supplier link. Our findings question the universality of success factors such as strategic involvement and indicate the need for a more dynamic model of lean implementation.
Journal: International Journal of Production Research
Pages: 3955-3973
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2017.1419583
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1419583
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Template-Type: ReDIF-Article 1.0
Author-Name: Yavuz A. Bozer
Author-X-Name-First: Yavuz A.
Author-X-Name-Last: Bozer
Author-Name: Francisco J. Aldarondo
Author-X-Name-First: Francisco J.
Author-X-Name-Last: Aldarondo
Title: A simulation-based comparison of two goods-to-person order picking systems in an online retail setting
Abstract: 
 Design and analysis of order picking systems continues to be an active topic of interest both in academia and practice, especially in light of the significant increase in online retail sales. In this paper, we examine two types of well-known, goods-to-person order picking systems, namely, a miniload system and a Kiva system. Using a simulation model, we compare the performance of the two systems on the basis of expected throughput and expected container retrieval times to process the same set of customer orders. We also discuss some of the advantages and limitations of the two systems.
Journal: International Journal of Production Research
Pages: 3838-3858
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1424364
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424364
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianping Dou
Author-X-Name-First: Jianping
Author-X-Name-Last: Dou
Author-Name: Jun Li
Author-X-Name-First: Jun
Author-X-Name-Last: Li
Author-Name: Chun Su
Author-X-Name-First: Chun
Author-X-Name-Last: Su
Title: A discrete particle swarm optimisation for operation sequencing in CAPP
Abstract: 
 Operation sequencing is one of crucial tasks for process planning in a CAPP system. In this study, a novel discrete particle swarm optimisation (DPSO) named feasible sequence oriented DPSO (FSDPSO) is proposed to solve the operation sequencing problems in CAPP. To identify the process plan with lowest machining cost efficiently, the FSDPSO only searches the feasible operation sequences (FOSs) satisfying precedence constraints. In the FSDPSO, a particle represents a FOS as a permutation directly and the crossover-based updating mechanism is developed to evolve the particles in discrete feasible solution space. Furthermore, the fragment mutation for altering FOS and the uniform and greedy mutations for changing machine, cutting tool and tool access direction for each operation, along with the adaptive mutation probability, are adopted to improve exploration ability. Case studies are used to verify the performance of the FSDPSO. For case studies, the Taguchi method is used to determine the key parameters of the FSDPSO. A comparison has been made between the result of the proposed FSDPSO and those of three existing PSOs, an existing genetic algorithm and two ant colony algorithms. The comparative results show higher performance of the FSDPSO with respect to solution quality for operation sequencing.
Journal: International Journal of Production Research
Pages: 3795-3814
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1425015
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1425015
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenbo Wu
Author-X-Name-First: Wenbo
Author-X-Name-Last: Wu
Author-Name: Zhengdong Huang
Author-X-Name-First: Zhengdong
Author-X-Name-Last: Huang
Author-Name: Qinghua Liu
Author-X-Name-First: Qinghua
Author-X-Name-Last: Liu
Author-Name: Lianhua Liu
Author-X-Name-First: Lianhua
Author-X-Name-Last: Liu
Title: A combinatorial optimisation approach for recognising interacting machining features in mill-turn parts
Abstract: 
 Feature interactions may result in many process alternatives in part machining. Traditional process planning methods only identify one of the options, which is usually not optimal in the sense of engineering. This paper presents an optimisation approach to handle the interacting feature recognition problem in mill-turn parts. The approach subdivides the material removal volume into cells first and then it combines the cells into features. Here, a two-level cell combination method is developed. On the lower level, individual features are formed by searching the combinations of cells near a given part face; on the upper level, the feature distributions are explored by rearranging the order of part faces for feature formation. In order to optimise the feature distribution, a novel optimisation model is proposed, which quantitatively distinguishes its options by considering the factors of feature numbers, tool approaching directions, cutting directions and surface roughness. The combinatorial optimisation problem is solved with the simulated annealing algorithm. Instead of searching cell combinations directly, the proposed method explores different part face sequences, which drastically reduces the search space. The case studies show that the proposed approach can effectively handle the traditional difficulty in recognising the interacting features for mill-turn parts.
Journal: International Journal of Production Research
Pages: 3757-3780
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1425016
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1425016
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Template-Type: ReDIF-Article 1.0
Author-Name: Violetta Giada Cannas
Author-X-Name-First: Violetta Giada
Author-X-Name-Last: Cannas
Author-Name: Margherita Pero
Author-X-Name-First: Margherita
Author-X-Name-Last: Pero
Author-Name: Rossella Pozzi
Author-X-Name-First: Rossella
Author-X-Name-Last: Pozzi
Author-Name: Tommaso Rossi
Author-X-Name-First: Tommaso
Author-X-Name-Last: Rossi
Title: Complexity reduction and kaizen events to balance manual assembly lines: an application in the field
Abstract: 
 Notwithstanding the existence of a broad research base on assembly line balancing (ALB), companies do not use the mathematical approaches developed in the literature to configure assembly lines. This article aims to fill the gap between research and application by presenting and testing in a real industrial context a methodology based on complexity reduction and kaizen events. First, the methodology supports reducing the complexity that affects real-life assembly systems in terms of the variety of, e.g. finished products, materials and parts. Next, the methodology proposes the conduction of kaizen events by using lean manufacturing tools, such as process analysis, time observation, waste identification, workstation standard documents and yamazumi charts. The methodology is successfully applied to a case study that describes its use in the confectionery process for a major chocolatier company along with the results of the application. The main contribution of this paper consists in presenting a method to manage the line balancing activity within everyday industrial realities, helping practitioners to improve and maintain the performance over time.
Journal: International Journal of Production Research
Pages: 3914-3931
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1427898
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1427898
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Template-Type: ReDIF-Article 1.0
Author-Name: Jordi Pereira
Author-X-Name-First: Jordi
Author-X-Name-Last: Pereira
Title: Modelling and solving a cost-oriented resource-constrained multi-model assembly line balancing problem
Abstract: 
 A line balancing problem considers the assignment of operations to workstations in an assembly line. While assembly lines are usually associated to mass production of standardised goods, their advantages have led to their widespread use whenever a product-oriented production system is applicable and the benefits of the labour division and specialisation are significant, even when some of its characteristics may deviate from classical assembly lines. In this work, we study a line balancing problem found in the textile industry in which the line must be balanced for multiple types of goods taking into account resource requirements. In order to solve the problem, a hybrid method that combines classical methods for line balancing with an Estimation of Distribution Algorithm is proposed. Computational experiments show that the new procedure improves upon the state of the art when compared using a benchmark set derived from the literature, as well as when compared using data from the manufacturer that originated this research work.
Journal: International Journal of Production Research
Pages: 3994-4016
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1427899
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1427899
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Template-Type: ReDIF-Article 1.0
Author-Name: Gianfranco Genta
Author-X-Name-First: Gianfranco
Author-X-Name-Last: Genta
Author-Name: Maurizio Galetto
Author-X-Name-First: Maurizio
Author-X-Name-Last: Galetto
Author-Name: Fiorenzo Franceschini
Author-X-Name-First: Fiorenzo
Author-X-Name-Last: Franceschini
Title: Product complexity and design of inspection strategies for assembly manufacturing processes
Abstract: 
 In the manufacturing field, the assembly process heavily affects product final quality and cost. Specific studies, concerning the causes of the assembly defects, showed that operator errors account for high percentage of the total defects. Also, models linking the assembly complexity with the operator-induced defect rate were developed. Basing on these models, the present paper proposes a new paradigm for designing inspection strategies in case of short-run productions, for which traditional approaches may not be carried out. Specifically, defect generation models are developed to get a priori predictions of the probability of occurrence of defects, which are useful for designing effective inspection procedures. The proposed methodology is applied to a case study concerning the assembly of mechanical components in the manufacturing of hardness testing machines.
Journal: International Journal of Production Research
Pages: 4056-4066
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1430907
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1430907
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Template-Type: ReDIF-Article 1.0
Author-Name: María Teresa García-Ordás
Author-X-Name-First: María Teresa
Author-X-Name-Last: García-Ordás
Author-Name: Enrique Alegre-Gutiérrez
Author-X-Name-First: Enrique
Author-X-Name-Last: Alegre-Gutiérrez
Author-Name: Víctor González-Castro 
Author-X-Name-First: Víctor
Author-X-Name-Last: González-Castro 
Author-Name: Rocío Alaiz-Rodríguez
Author-X-Name-First: Rocío
Author-X-Name-Last: Alaiz-Rodríguez
Title: Combining shape and contour features to improve tool wear monitoring in milling processes
Abstract: 
 In this paper, a new system based on combinations of a shape descriptor and a contour descriptor has been proposed for classifying inserts in milling processes according to their wear level following a computer vision based approach. To describe the wear region shape we have proposed a new descriptor called ShapeFeat and its contour has been characterized using the method BORCHIZ that, to the best of our knowledge, achieves the best performance for tool wear monitoring following a computer vision-based approach. Results show that the combination of BORCHIZ with ShapeFeat using a late fusion method improves the classification performance significantly, obtaining an accuracy of 91.44% in the binary classification (i.e. the classification of the wear as high or low) and 82.90% using three target classes (i.e. classification of the wear as high, medium or low). These results outperform the ones obtained by both descriptors used on their own, which achieve accuracies of 88.70 and 80.67% for two and three classes, respectively, using ShapeFeat and 87.06 and 80.24% with B-ORCHIZ. This study yielded encouraging results for the manufacturing community in order to classify automatically the inserts in terms of their wear for milling processes.
Journal: International Journal of Production Research
Pages: 3901-3913
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1435919
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1435919
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Template-Type: ReDIF-Article 1.0
Author-Name: Alessia Napoleone
Author-X-Name-First: Alessia
Author-X-Name-Last: Napoleone
Author-Name: Alessandro Pozzetti
Author-X-Name-First: Alessandro
Author-X-Name-Last: Pozzetti
Author-Name: Marco Macchi
Author-X-Name-First: Marco
Author-X-Name-Last: Macchi
Title: A framework to manage reconfigurability in manufacturing
Abstract: 
 Nowadays, manufacturing firms are dealing with the unpredictability of market requirements and the frequent changes induced by technological innovation. For this reason, firms are more and more addressing the need to be responsive at an affordable cost. To do so, they are required to develop a capability called reconfigurability. This paper is a review of the existing literature because the current need makes interesting to reflect on the state of the art of reconfigurability as a concept. This reflection has led to focus on reconfigurability characteristics for both their relevance and their relationships with managerial decisions in manufacturing. To this end, a framework has been proposed. It is based on system lifecycle and production levels. These two elements have been deduced from literature and identified as relevant dimensions for decision-making.
Journal: International Journal of Production Research
Pages: 3815-3837
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1437286
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1437286
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Template-Type: ReDIF-Article 1.0
Author-Name: Guang-Yu Zhu
Author-X-Name-First: Guang-Yu
Author-X-Name-Last: Zhu
Author-Name: Xue-Wei Ju
Author-X-Name-First: Xue-Wei
Author-X-Name-Last: Ju
Author-Name: Wei-Bo Zhang
Author-X-Name-First: Wei-Bo
Author-X-Name-Last: Zhang
Title: Multi-objective sequence optimization of PCB component assembly with GA based on the discrete Fréchet distance
Abstract: 
 A new mechanism，namely a combination of curve matching method based on the discrete Fréchet distance and evolutionary algorithms，is proposed to solve pick-and-place sequence optimisation problems as a multi-objective optimisation problem. The essence of the mechanism is to accomplish the comparison of objective vectors with curve matching method. The objective vector is mapped into the array of points with a binary mapping operator and the discrete Fréchet distance is utilised to measure the similarity between the reference array of points and the comparison array of points. The genetic algorithm based on the discrete Fréchet distance (FGA) is proposed. To test the new mechanism, together with FGA, three other test algorithms are selected to solve the sequence optimisation problem. The simulation results indicate that FGA outperforms other algorithms. This new mechanism is rational and feasible for multi-objective pick-and-place sequence optimisation problems.
Journal: International Journal of Production Research
Pages: 4017-4034
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1440091
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1440091
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Template-Type: ReDIF-Article 1.0
Author-Name: Yusuf Tansel Ic
Author-X-Name-First: Yusuf Tansel
Author-X-Name-Last: Ic
Author-Name: Ebru Saraloğlu Güler
Author-X-Name-First: Ebru
Author-X-Name-Last: Saraloğlu Güler
Author-Name: Ceren Cabbaroğlu
Author-X-Name-First: Ceren
Author-X-Name-Last: Cabbaroğlu
Author-Name: Ezgi Dilan Yüksel
Author-X-Name-First: Ezgi
Author-X-Name-Last: Dilan Yüksel
Author-Name: Huri Maide Sağlam
Author-X-Name-First: Huri
Author-X-Name-Last: Maide Sağlam
Title: Optimisation of cutting parameters for minimizing carbon emission and maximising cutting quality in turning process
Abstract: 
 Modern manufacturing systems are faced with the challenge of reducing the carbon emission related to manufacturing technologies. Machining centres consume large amounts of energy and as a consequence; carbon emissions are generated owing to this consumption. This paper presents a design of experiment work related to the optimisation of machining factors in the turning process of aluminium alloys. Carbon emission and surface quality were concurrently optimised. A set of experimental scenarios was set using a Box–Behnken design and the response surface methodology was applied to get the regression model for the carbon emission and surface roughness during turning process. The relationship between factors and the responses (carbon emission and surface quality) was investigated using surface plots. Furthermore, the desirability function method using the Response Optimizer tool in MINITAB and goal programming methodology was used to obtain the values of the parameters that achieved minimum surface roughness and a minimum quantity of carbon emission.
Journal: International Journal of Production Research
Pages: 4035-4055
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1442949
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1442949
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Template-Type: ReDIF-Article 1.0
Author-Name: Amir Qamar
Author-X-Name-First: Amir
Author-X-Name-Last: Qamar
Author-Name: Mark A. Hall
Author-X-Name-First: Mark A.
Author-X-Name-Last: Hall
Author-Name: Simon Collinson
Author-X-Name-First: Simon
Author-X-Name-Last: Collinson
Title: Lean versus agile production: flexibility trade-offs within the automotive supply chain
Abstract: 
 Given the recent dynamics of the automotive industry in the UK, the ability for a firm to be flexible has often taken priority over other performance indicators. Using the notion of distinct business models and trade-offs as our theoretical lens, the purpose of this study was to: (1) Distinguish lean and agile firms based upon production methods; and (2) Compare lean and agile levels of external flexibility (EF) and supply chain flexibility (SCF). Data was obtained from 140 automotive firms in the Midlands (UK) via a survey which was sent by emails. Findings supported the theoretical notion of trade-offs, as firms implementing agile production methods were found to be more flexible in comparison with firms implementing lean production methods. More importantly, the agile firms that possessed high EF levels and SCF levels were predominantly positioned at the lower end of the automotive supply chain, whereas the lean firms were largely found to be operating at the top of the supply chain. First, we provide an innovative way in which lean and agile firms can be conceptualised. Second, as flexibility levels were assessed on actual numerical values, as opposed to using opinion based Likert Scale questions, a methodological contribution is made. Third, as flexibility is in its infancy stage of theoretical development we make an empirical contribution by developing a taxonomy that distinguishes each production concept. Finally, given the supply chain position to where lean and agile firms were found, we invoked a power perspective better understand this phenomenon.
Journal: International Journal of Production Research
Pages: 3974-3993
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1463109
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1463109
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Template-Type: ReDIF-Article 1.0
Author-Name: Tone Lerher
Author-X-Name-First: Tone
Author-X-Name-Last: Lerher
Title: Aisle changing shuttle carriers in autonomous vehicle storage and retrieval systems
Abstract: 
 The objective of this study is to propose analytical travel time models for aisle changing shuttle carriers, which are capable of travelling in the horizontal and in the cross-aisle directions. The expressions for the single and dual command travel times have been determined assuming uniform distributed storage locations and the probability theory. A simulation model has been applied for the performance analysis of the proposed analytical models. The proposed models enable the calculation of the expected travel times for single and dual command cycles of the aisle changing shuttle carriers, from which the performance can be evaluated.
Journal: International Journal of Production Research
Pages: 3859-3879
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1467060
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1467060
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 4067-4067
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1487521
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1487521
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Template-Type: ReDIF-Article 1.0
Author-Name: Manjot Singh Bhatia
Author-X-Name-First: Manjot Singh
Author-X-Name-Last: Bhatia
Title: Erratum
Journal: International Journal of Production Research
Pages: 4068-4068
Issue: 11
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1487604
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1487604
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Template-Type: ReDIF-Article 1.0
Author-Name: H.J. Long
Author-X-Name-First: H.J.
Author-X-Name-Last: Long
Author-Name: L.Y. Wang
Author-X-Name-First: L.Y.
Author-X-Name-Last: Wang
Author-Name: S.X. Zhao
Author-X-Name-First: S.X.
Author-X-Name-Last: Zhao
Author-Name: Z.B. Jiang
Author-X-Name-First: Z.B.
Author-X-Name-Last: Jiang
Title: An approach to rule extraction for product service system configuration that considers customer perception
Abstract: 
 At present, manufacturers tend to bundle a product with its related services as a product service system, to meet customer needs and achieve competitive advantage. Configuring a product service system involves selecting and combining appropriate product and service components, to satisfy individual customer needs. One crucial step to rapidly configure a product service system is to develop formalised configuration rules, which show the relationships between product service components and customer needs, including those expressed as perception needs. In this study, a rough set-based approach is proposed to acquire configuration rules. First, an information table is built by combining the results of factor analysis and questionnaire survey. Then, customer segmentation is accomplished by clustering. Based on the information table and customer segmentation, a dominance-based rough set approach is used to extract the configuration rules. Finally, a weighbridge is selected for the case study to validate the proposed approach.
Journal: International Journal of Production Research
Pages: 5337-5360
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2015.1078012
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1078012
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Template-Type: ReDIF-Article 1.0
Author-Name: Rui Miao
Author-X-Name-First: Rui
Author-X-Name-Last: Miao
Author-Name: Wenjie Huang
Author-X-Name-First: Wenjie
Author-X-Name-Last: Huang
Author-Name: Donghao Pei
Author-X-Name-First: Donghao
Author-X-Name-Last: Pei
Author-Name: Xiyao Gu
Author-X-Name-First: Xiyao
Author-X-Name-Last: Gu
Author-Name: Zefeng Li
Author-X-Name-First: Zefeng
Author-X-Name-Last: Li
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Research on lease and sale of electric vehicles based on value engineering
Abstract: 
 Electric vehicles (EVs) acknowledged as potential means of transportation tools in the near future are widely accepted as the development trend of automobile industry due to its environment protection and fuel energy saving properties. As a product containing new technologies and concepts with little market experience and consumer identification, studying its life cycle operation modes will help to figure out an optimal approach to conduct EVs manufacturing and service. The two common operation modes, lease and sale of EVs, have their own advantages and weaknesses under different scenarios and consumer psychological status. Research and comparisons on the function, cost and value of two operation modes in full life cycle will simulate the rapid development of EVs forming a mature and dynamic operation mechanism. This paper utilised approaches in value engineering, putting forward customer requirements and technical elements of EV lease and sale based on quality assessment and customer-perceived value, proposing the metric method of function and cost coefficient by mathematical modelling, and conducting value coefficient analysis and comparison based on customer’s risk aversion psychology. An illustrative example raised for studying operation mode of three different kinds of EVs based on the analysis of value coefficient, providing guideline for manufacturer and servicers of EVs.
Journal: International Journal of Production Research
Pages: 5361-5380
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2015.1081709
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1081709
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Template-Type: ReDIF-Article 1.0
Author-Name: Muhammad Imran
Author-X-Name-First: Muhammad
Author-X-Name-Last: Imran
Author-Name: R.I.M. Young
Author-X-Name-First: R.I.M.
Author-X-Name-Last: Young
Title: Reference ontologies for interoperability across multiple assembly systems
Abstract: 
 The role of information and communication technologies (ICTs) is crucial for future manufacturing organisations in order to support effective collaboration and information sharing. However, the contemporary ICT-based systems lack the required ability to adequately support interoperability across multiple domain systems. The capability of such ICT-based systems to interoperate is impeded by the semantic conflicts arising from loosely defined meanings and intents of the participating system concepts. The aim of this paper is to investigate the interoperability of assembly systems at multiple levels of concept specialisations using the concept of a formal reference ontology. Formal ontologies are providing a promising way to computationally capture the domain meanings which can subsequently provide a base to support interoperability across multiple systems and in our case multiple assembly systems. This paper takes the example of manufacturing bill of materials concept and three different domain-specific interpretations to explore and demonstrate the potential of formal reference ontologies to support interoperability.
Journal: International Journal of Production Research
Pages: 5381-5403
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2015.1087654
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1087654
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Template-Type: ReDIF-Article 1.0
Author-Name: John Ni
Author-X-Name-First: John
Author-X-Name-Last: Ni
Author-Name: Barbara B. Flynn
Author-X-Name-First: Barbara B.
Author-X-Name-Last: Flynn
Author-Name: F. Robert Jacobs
Author-X-Name-First: F. Robert
Author-X-Name-Last: Jacobs
Title: The effect of a toy industry product recall announcement on shareholder wealth
Abstract: 
 The widely publicised product recalls of lead-paint tainted toys in 2007 caused serious concerns among consumers, investors and the government. The widespread practice of global outsourcing in toy industry further intensifies consumers and investors’ uncertainties about toy safety. This paper assesses the stock market reaction to recent toy recall announcements. Based upon the theoretical underpinnings from agency theory, signalling theory and prospect theory, it also develops an understanding of factors that influence the direction and magnitude of the stock market reaction. One hundred and forty-five toy recall announcements in 2000–2014 were analysed using event study and linear regression. The results show that the announcement of a toy recall was associated with a negative stock market reaction. The stock market reaction was more negative for toy product recall announcements by retailers or distributors, smaller source firms, toys with more severe hazards and source firms with higher growth potential. This paper contributes to the product harm crisis literature by extending the automotive industry-based literature to toy industries and studying their unique features. It is important that toy industry managers are aware that the stock market penalty for a product recall increases with the degree of hazard. Moreover, toy companies, retailers and distributors with high growth potential should be aware of the signal sent by following a proactive recall strategy.
Journal: International Journal of Production Research
Pages: 5404-5415
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2015.1106608
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1106608
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Template-Type: ReDIF-Article 1.0
Author-Name: Eduardo Gomes Salgado
Author-X-Name-First: Eduardo Gomes
Author-X-Name-Last: Salgado
Author-Name: Luiz Alberto Beijo
Author-X-Name-First: Luiz Alberto
Author-X-Name-Last: Beijo
Author-Name: Paulo Sampaio
Author-X-Name-First: Paulo
Author-X-Name-Last: Sampaio
Author-Name: Carlos Henrique Pereira Mello
Author-X-Name-First: Carlos Henrique Pereira
Author-X-Name-Last: Mello
Author-Name: Pedro Saraiva
Author-X-Name-First: Pedro
Author-X-Name-Last: Saraiva
Title: ISO 9001 certification in the American Continent: a statistical analysis and modelling
Abstract: 
 The ISO 9001 standard is considered as an effective tool to support a quality management system (QMS). A steady growth in the number of ISO 9001 issued certificates is observed worldwide, confirming the interest of companies in this approach. However, information regarding this behaviour over time in the American Continent is scarce. This paper presents a set of qualitative and quantitative analyses related to the ISO 9001 certification (globally and at the country level of the Americas), the use of this standard in countries that were part of the ISO Survey 2011 and modelling the ISO 9001 certification for American countries, in order to characterise through mathematical models, the evolution of the certification process and to identify factors that influence the ISO 9001 issued certificates in the various countries analysed. Based on the work developed, a positive relationship was found between the number of issued certificates in each country per 1000 inhabitants and the indicators of economic development (Gross National Income Per Capita). It is determined that the total reserves of a country is an economic variable that directly affects the number of issued certificates, a finding not observed in other forecasting models.
Journal: International Journal of Production Research
Pages: 5416-5433
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2015.1109719
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1109719
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Template-Type: ReDIF-Article 1.0
Author-Name: Borja Ramis Ferrer
Author-X-Name-First: Borja
Author-X-Name-Last: Ramis Ferrer
Author-Name: Sergii Iarovyi
Author-X-Name-First: Sergii
Author-X-Name-Last: Iarovyi
Author-Name: Luis Gonzalez
Author-X-Name-First: Luis
Author-X-Name-Last: Gonzalez
Author-Name: Andrei Lobov
Author-X-Name-First: Andrei
Author-X-Name-Last: Lobov
Author-Name: Jose L. Martinez Lastra
Author-X-Name-First: Jose L.
Author-X-Name-Last: Martinez Lastra
Title: Management of distributed knowledge encapsulated in embedded devices
Abstract: 
 Embedded electronic devices are now to be found everywhere. In general, they can be used to collect different sorts of data (e.g. on temperature, humidity, illumination and locations). In some specific domains, such as industrial automation, embedded devices are used for process control. The devices may have a programme that can respond immediately to environmental changes perceived through sensors. In the control of large sites, where there are many devices, higher level decisions are made or processed in dedicated computers far away from the sources (devices) where the initial data are collected. This article shows how it is possible to manage portions of distributed knowledge, hosted in embedded devices, making it possible for each embedded device to hold and manage its piece of knowledge. In addition, presented approach allows keeping locus of control at the embedded device level, where the embedded device can make decisions knowing the status of the rest of the world, device contributions and their effects in the overall distributed system knowledge base.
Journal: International Journal of Production Research
Pages: 5434-5451
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2015.1120902
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1120902
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Template-Type: ReDIF-Article 1.0
Author-Name: Yi-Xi Xue
Author-X-Name-First: Yi-Xi
Author-X-Name-Last: Xue
Author-Name: Jian-Xin You
Author-X-Name-First: Jian-Xin
Author-X-Name-Last: You
Author-Name: Xufeng Zhao
Author-X-Name-First: Xufeng
Author-X-Name-Last: Zhao
Author-Name: Hu-Chen Liu
Author-X-Name-First: Hu-Chen
Author-X-Name-Last: Liu
Title: An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information
Abstract: 
 Nowadays selecting the most suitable robot is a difficult task for manufacturing firms due to increase in production demands and availability of various robot models. Robot evaluation and selection can be regarded as a multiple criteria decision-making (MCDM) problem and three key issues are the assessment of robots, the determination of criteria weights and the prioritisation of alternatives. This paper aims to propose an integrated model based on hesitant 2-tuple linguistic term sets and an extended QUALIFLEX approach for handling robot selection problems with incomplete weight information. The new model can not only manage uncertain and imprecise assessment information of decision-makers with the aid of hesitant 2-tuple linguistic term sets, but also derive the important weights of criteria objectively when the weight information is incompletely known. Moreover, based on the extended QUALIFLEX algorithm, the priority orders of robots can be clearly determined and a more reasonable and credible solution can be yielded in a particular industrial application. Finally, a robot selection case study is carried out, and comparative experiments indicate the practicality and effectiveness of the proposed integrated linguistic MCDM approach.
Journal: International Journal of Production Research
Pages: 5452-5467
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1146418
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1146418
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Template-Type: ReDIF-Article 1.0
Author-Name: Pooya Daie
Author-X-Name-First: Pooya
Author-X-Name-Last: Daie
Author-Name: Simon Li
Author-X-Name-First: Simon
Author-X-Name-Last: Li
Title: Managing product variety through configuration of pre-assembled vanilla boxes using hierarchical clustering
Abstract: 
 Postponement strategy and platform-based production are common practices of mass customisation to address supply chain challenges due to the requirement of product variety. This paper focuses on implementing mass customisation through development of semi-finished forms of products (vanilla boxes) to reduce supply chain cost and facilitate the production process. The challenge is that the possible number of vanilla box configurations grows dramatically with the increase in number of product variants. In the solution approach, the basic information of product variety is captured in a matrix format, specifying the component requirements for each product variant. Then, hierarchical clustering is applied over the components with the considerations of demands. The clustering method consists of three major stages: similarity analysis, tree construction and tree-based analysis. The key stage is similarity analysis, in which problem-specific information can be incorporated in the clustering process. Two numerical examples from the literature are used to verify that the clustering approach can yield good-quality solutions.
Journal: International Journal of Production Research
Pages: 5468-5479
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1158879
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1158879
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Template-Type: ReDIF-Article 1.0
Author-Name: Mahmoud Mohammad Migdadi
Author-X-Name-First: Mahmoud Mohammad
Author-X-Name-Last: Migdadi
Author-Name: Mohammed Khair Saleem Abu Zaid
Author-X-Name-First: Mohammed Khair Saleem
Author-X-Name-Last: Abu Zaid
Title: An empirical investigation of knowledge management competence for enterprise resource planning systems success: insights from Jordan
Abstract: 
 The primary objective of the study reported herein is to empirically test the implicit, positive relationships between ERP-related Knowledge Management Competence (KM-competence; knowledge creation, knowledge retention, knowledge transfer, and knowledge application) dimensions and the extended Enterprise Resource Planning System Success construct (ERP system success; individual impact, workgroup impact, organisational impact, information quality, system quality, and vender/consultant quality). Data were collected from 173 of business and IT managers in 455 organisations in Jordan. Statistical techniques employed included confirmatory factor analysis to examine validity of the measurement model, and structural equation modelling using AMOS 16.0 is also utilised to test the hypotheses. The results of analysis show there is a positive significant impact of ERP knowledge creation on ERP success. Also, ERP knowledge retention positively and significantly affects ERP system success. Moreover, ERP knowledge transfer positively and significantly influence ERP system success. Furthermore, ERP knowledge application has positive effect on ERP system success. The results also indicate that ERP success construct is robust since all six observed variables are strongly loaded to the latent variable. Research limitations as well as implications for practice and research are discussed.
Journal: International Journal of Production Research
Pages: 5480-5498
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1161254
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1161254
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Template-Type: ReDIF-Article 1.0
Author-Name: Francesca Guerriero
Author-X-Name-First: Francesca
Author-X-Name-Last: Guerriero
Author-Name: Giovanna Miglionico
Author-X-Name-First: Giovanna
Author-X-Name-Last: Miglionico
Author-Name: Filomena Olivito
Author-X-Name-First: Filomena
Author-X-Name-Last: Olivito
Title: Managing TV commercials inventory in the Italian advertising market
Abstract: 
 This paper studies the problem of a TV broadcaster, managing its programs schedule. A TV network is considered that has to decide on accepting and scheduling requests from its advertisers. A request is formulated both in terms of people to be reached and of budget available for the advertisement campaign. Moreover, several formulations of the problem are presented and defined in such a way as to handle different aspects of the real process: compatibility among advertisements that are scheduled in the same break; compatibility between advertisements and breaks; price discrimination due to the different positions of the advertisements within a break. Since the introduced models are computationally intractable, several heuristics are presented whose performance are evaluated in an extensive computational study based on test problems defined by considering the peculiarities of the Italian advertisements market.
Journal: International Journal of Production Research
Pages: 5499-5521
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1162919
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1162919
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Template-Type: ReDIF-Article 1.0
Author-Name: Huei-Hua Hsiao
Author-X-Name-First: Huei-Hua
Author-X-Name-Last: Hsiao
Author-Name: Shih-Wen Hsiao
Author-X-Name-First: Shih-Wen
Author-X-Name-Last: Hsiao
Author-Name: Shen-Min Liang
Author-X-Name-First: Shen-Min
Author-X-Name-Last: Liang
Title: Improving product based on affordance with fuzzy theory for product development strategy
Abstract: 
 This paper presents a design strategy which combines both conceptual and mental design information to quantitative degrees of affordance using a fuzzy scale that provides user-to-designer information. The traditional communication channel has been hidden. In the past, design concepts were not a result of direct communication between designers and users. This study found that, based on users’ mental models, users can reflectively modify product characteristics to improve the convenience of usage. These insights offer a hidden communication channel for designers and are defined as generalised affordance within the context of this research. This study proposed a novel method to semi-quantify affordance using a fuzzy linguistic modelling technique to establish a fuzzy scale table that quantifies degrees of affordance. An affordance fuzzy matrix (AFM) was created to assess the effects of affordance of each task necessary to utilise each product component. The overall results of the AFM indicate the generalised affordance of a particular product. Hidden messages are the characteristic of a product improved by the user itself because of his habit, which incurs additional product features, symbols and words, and will help product designers for further design strategy and improvements. In this study, generalised affordance is applied to an electric oven as an example.
Journal: International Journal of Production Research
Pages: 5522-5533
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1164350
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1164350
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Template-Type: ReDIF-Article 1.0
Author-Name: Yongxin Liao
Author-X-Name-First: Yongxin
Author-X-Name-Last: Liao
Author-Name: Mario Lezoche
Author-X-Name-First: Mario
Author-X-Name-Last: Lezoche
Author-Name: Hervé Panetto
Author-X-Name-First: Hervé
Author-X-Name-Last: Panetto
Author-Name: Nacer Boudjlida
Author-X-Name-First: Nacer
Author-X-Name-Last: Boudjlida
Title: Semantic annotations for semantic interoperability in a product lifecycle management context
Abstract: 
 The interoperability among a variety of systems, in or across manufacturing enterprises, has been widely accepted as one of the important factors that affect the efficiency of production. Many research works, related to the interoperability at different levels, have been carried out to tackle the information exchange, transformation, discovery and reuse. One of the main challenges in these research works is to overcome the semantic heterogeneity in the exchanged information between enterprise applications along the life cycle of a product. As a possible solution to support the semantic interoperability issue, semantic annotations have gained more and more attention. This paper identifies several existing drawbacks and proposes a formal semantic annotation approach to support the semantic enrichment of models in a product lifecycle management context.
Journal: International Journal of Production Research
Pages: 5534-5553
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1165875
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165875
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiao-long Zheng
Author-X-Name-First: Xiao-long
Author-X-Name-Last: Zheng
Author-Name: Ling Wang
Author-X-Name-First: Ling
Author-X-Name-Last: Wang
Title: A knowledge-guided fruit fly optimization algorithm for dual resource constrained flexible job-shop scheduling problem
Abstract: 
 Different from the classical job shop scheduling, the dual-resource constrained flexible job-shop scheduling problem (DRCFJSP) should deal with job sequence, machine assignment and worker assignment all together. In this paper, a knowledge-guided fruit fly optimisation algorithm (KGFOA) with a new encoding scheme is proposed to solve the DRCFJSP with makespan minimisation criterion. In the KGFOA, two types of permutation-based search operators are used to perform the smell-based search for job sequence and resource (machine and worker) assignment, respectively. To enhance the search capability, a knowledge-guided search stage is incorporated into the KGFOA with two new search operators particularly designed for adjusting the operation sequence and the resource assignment, respectively. Due to the combination of the knowledge-guided search and the smell-based search, global exploration and local exploitation can be balanced. Besides, the effect of parameter setting of the KGFOA is investigated and numerical tests are carried out using two sets of instances. The comparative results show that the KGFOA is more effective than the existing algorithms in solving the DRCFJSP.
Journal: International Journal of Production Research
Pages: 5554-5566
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1170226
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1170226
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Template-Type: ReDIF-Article 1.0
Author-Name: Kai Meng
Author-X-Name-First: Kai
Author-X-Name-Last: Meng
Author-Name: Peihuang Lou
Author-X-Name-First: Peihuang
Author-X-Name-Last: Lou
Author-Name: Xianghui Peng
Author-X-Name-First: Xianghui
Author-X-Name-Last: Peng
Author-Name: Victor Prybutok
Author-X-Name-First: Victor
Author-X-Name-Last: Prybutok
Title: An improved co-evolutionary algorithm for green manufacturing by integration of recovery option selection and disassembly planning for end-of-life products
Abstract: 
 There is a strong need for recovery decision-making for end-of-life (EOL) products to satisfy sustainable manufacturing requirements. This paper develops and tests a profit maximisation model by simultaneously integrating recovery option selection and disassembly planning. The proposed model considers the quality of EOL components. This paper utilises an integrated method of multi-target reverse recursion and partial topological sorting to generate a feasible EOL solution that also reduces the complexity of genetic constraints handling. In order to determine recovery options, disassembly level and disassembly sequence simultaneously, this paper develops an improved co-evolutionary algorithm (ICA) to search for an optimal EOL solution. The proposed algorithm adopts the evolutionary mechanism of localised interaction and endosymbiotic competition. Further, an advanced local search operator is introduced to improve convergence performance, and a global disturbance strategy is also suggested to prevent premature convergence. Finally, this paper conducts a series of computational experiments under various scenarios to validate the meta-heuristic integrated decision-making model proposed and the superiority of the developed ICA. The results show that the proposed approach offers a strong and flexible decision support tool for intelligent recovery management in a ubiquitous information environment. We discuss the theoretical and practical contributions of this paper and implications for future research.
Journal: International Journal of Production Research
Pages: 5567-5593
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1176263
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1176263
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuming Mo
Author-X-Name-First: Yuming
Author-X-Name-Last: Mo
Author-Name: Ashwin Chandramouli
Author-X-Name-First: Ashwin
Author-X-Name-Last: Chandramouli
Author-Name: Nan Kong
Author-X-Name-First: Nan
Author-X-Name-Last: Kong
Title: A simulation study on the US rehabilitation service process for patients with modest-to-severe traumatic brain injury
Abstract: 
 Traumatic brain injury (TBI) is a devastating injury with severe consequences. In this paper, we conduct a simulation study on the commonly implemented care delivery process for TBI rehabilitation in the US, which covers three care categories: inpatient acute, outpatient sub-acute and general residential care. Our investigation is focused on assessing how coverage duration of publicly funded rehabilitation impacts two key system outcomes: sub-acute rehabilitation readmission and total rehabilitation spending. We develop prediction models on the above two outcomes for patients of different conditions. We introduce the notions of forceful transition and medical necessity adjustment, and embed the notions in a state-transition simulation model. Our simulation results suggest that to minimise the care spending, the duration of publicly insured outpatient sub-acute rehab be set smaller than what is currently implemented but not to the point where coverage should be completely removed. Our sensitivity analysis justifies the robustness of our results under variations on model parameters.
Journal: International Journal of Production Research
Pages: 5594-5606
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1178863
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1178863
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Template-Type: ReDIF-Article 1.0
Author-Name: Harri Laihonen
Author-X-Name-First: Harri
Author-X-Name-Last: Laihonen
Author-Name: Sanna Pekkola
Author-X-Name-First: Sanna
Author-X-Name-Last: Pekkola
Title: Impacts of using a performance measurement system in supply chain management: a case study
Abstract: 
 The study examines how the utilisation of a new performance measurement system (PMS) influences supply chain management (SCM) and what kind of impacts the new system has on the performance of the supply chain. The paper utilises a longitudinal research setting where the data was gathered in two semi-structured interview studies after an action research project in which a new measurement system was designed and developed. The findings show how a PMS serves as a catalyst of inter-organisational knowledge transfer and promotes shared learning. The results also show how knowledge transfer and shared learning led to improved performance of the supply chain. The paper contributes by opening up the practical mechanisms through which performance measurement provides value for SCM and by showing how inter-organisational transfer of performance information catalyses learning and performance improvement. The paper looks beyond the design of performance measures and provides a view on the practice of supply chain performance management. The paper illustrates how sharing performance information amongst supply chain companies improves managers’ awareness of shared targets and the status of network operations. This also resulted in improved performance in the studied case network. Overall, the results encourage organisations to engage in network-level performance measurement and share performance information with their network partners.
Journal: International Journal of Production Research
Pages: 5607-5617
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1181810
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1181810
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Template-Type: ReDIF-Article 1.0
Author-Name: Jie Wu
Author-X-Name-First: Jie
Author-X-Name-Last: Wu
Author-Name: Qingyuan Zhu
Author-X-Name-First: Qingyuan
Author-X-Name-Last: Zhu
Author-Name: Junfei Chu
Author-X-Name-First: Junfei
Author-X-Name-Last: Chu
Author-Name: Qingxian An
Author-X-Name-First: Qingxian
Author-X-Name-Last: An
Author-Name: Liang Liang
Author-X-Name-First: Liang
Author-X-Name-Last: Liang
Title: A DEA-based approach for allocation of emission reduction tasks
Abstract: 
 Rapid economic growth has led to increasing pollution emission, leading governments to require emission reductions by specific amounts. The allocation of specific emission reduction tasks has become a significant issue and has drawn the attention of academia. Data envelopment analysis (DEA) has been extended to construct the allocation of emission reduction tasks model. These previous DEA-based approaches have strong assumptions about individual enterprise production. In this paper, we propose a new method to accurately assess the production, using each enterprise’s previously observed production to construct its own production technology plan. With emission permits decreased, the enterprise can have new production strategy based on its own technology. Assuming emission permits can be freely bought and sold, we show how each enterprise can determine the optimal amount of emission allowance that should be used for production, which may leave some allowance to be sold for extra profit or may require the purchase of permits from other firms. Considering the limitation on the total allowance from emission permits, we introduce the concept of satisfaction degree and use it in maximising the minimum enterprise satisfaction degree. Last, a numerical example is presented and an empirical application is given to verify the proposed approach.
Journal: International Journal of Production Research
Pages: 5618-5633
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1194537
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1194537
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Template-Type: ReDIF-Article 1.0
Author-Name: Clément Chatras
Author-X-Name-First: Clément
Author-X-Name-Last: Chatras
Author-Name: Vincent Giard
Author-X-Name-First: Vincent
Author-X-Name-Last: Giard
Author-Name: Mustapha Sali
Author-X-Name-First: Mustapha
Author-X-Name-Last: Sali
Title: Mass customisation impact on bill of materials structure and master production schedule development
Abstract: 
 The customisation of a vehicle on a production line results from the assembly of several hundreds of alternative components. Bills of Material (BOM) are usually made for operational purposes (to define the list of components to be assembled on a vehicle), for planning (to anticipate component procurement needs) and for commercial needs (guide customer choice and prepare sales forecasts). In the automotive industry, the diversity of end products which results from this combinatorial process (several millions) is such as no solution proposed in the literature allows to easily list the BOMs for all these vehicles. In our paper, we describe and theorise a solution used for many years by several carmakers, which consists in introducing a commercial description of the products in addition to their common organic representation. We show that this solution is an extension of the generic and modular BOM theory, recognised to be the most advanced solutions proposed in the literature. While fully meeting commercial and production control needs, this product description paradigm has limitations when it comes to determining the Master Production Schedules (MPS) at end product level beyond the frozen horizon, as performed by several automakers. An alternative approach defining MPSs at alternative component level is proposed in the literature. However, this approach also has several drawbacks that we point out. To overcome these issues, we propose a number of possible strategic and organisational tracks of improvement.
Journal: International Journal of Production Research
Pages: 5634-5650
Issue: 18
Volume: 54
Year: 2016
Month: 9
X-DOI: 10.1080/00207543.2016.1194539
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1194539
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Template-Type: ReDIF-Article 1.0
Author-Name: Shichang Du
Author-X-Name-First: Shichang
Author-X-Name-Last: Du
Author-Name: Xufeng Yao
Author-X-Name-First: Xufeng
Author-X-Name-Last: Yao
Author-Name: Delin Huang
Author-X-Name-First: Delin
Author-X-Name-Last: Huang
Title: Engineering model-based Bayesian monitoring of ramp-up phase of multistage manufacturing process
Abstract: 
 Process monitoring of full mass production phase of multistage manufacturing processes (MMPs) has been successfully implemented in many applications; however, monitoring of ramp-up phase of MMPs is often more difficult to conduct due to the limited information to establish valid process control parameters (such as mean and variance). This paper focuses on the estimation of the process control parameters used for monitoring scheme design of ramp-up phase of MMPs. An engineering model of variation propagation of an MMP is developed and reconstructed to a linear model, establishing a relationship between the error sources and the variation of product characteristics. Based on the developed linear model, a two-step Bayesian method is proposed to estimate the process control parameters. The performance of the proposed Bayesian method is validated with simulation data and real-world data, and the results demonstrate that the proposed method can effectively estimate process parameters during ramp-up phase of MMP.
Journal: International Journal of Production Research
Pages: 4594-4613
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1005247
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:15:p:4594-4613




Template-Type: ReDIF-Article 1.0
Author-Name: Shey-Huei Sheu
Author-X-Name-First: Shey-Huei
Author-X-Name-Last: Sheu
Author-Name: Tzu-Hsin Liu
Author-X-Name-First: Tzu-Hsin
Author-X-Name-Last: Liu
Author-Name: Zhe George Zhang
Author-X-Name-First: Zhe George
Author-X-Name-Last: Zhang
Author-Name: Jau-Chuan Ke
Author-X-Name-First: Jau-Chuan
Author-X-Name-Last: Ke
Title: Extended preventive replacement policy for a two-unit system subject to damage shocks
Abstract: 
 We consider a system consisting of two units (A and B), which is subject to two types of shocks (I and II) that occur according to a non-homogeneous Poisson process. The probabilities of these two shock types are age-dependent. Each type-I shock causes a minor failure of unit A, which can be corrected by a minimal repair. Meanwhile, this type of shock results in a certain amount of damage to unit B. These damages to unit B are accumulated to trigger a preventive replacement (PM) or a corrective replacement (CM) action. In addition, a minor failure for unit B with the cumulative damage of z will occur with probability πz$ \pi \left( z \right) $ at a type-I shock instant. Type-II shock is a major one that causes system replacement. We consider a two-dimensional PM policy, which prescribes that the system is preventively replaced at age T, or at the time when the total damage to unit B exceeds a prespecified level Z (but less than the failure level K where K &gt; Z) or is replaced correctively at first type-II shock or when the total damage to unit B exceeds a failure level K, whichever occurs first. Thus, both PM and CM actions may be performed in our model. To minimise the expected cost per unit time, the optimal policy (T∗$ {T^*} $, Z∗$ {Z^*} $) is derived analytically and determined numerically. We also show that our model is a generalisation of many previous maintenance models in the literature.
Journal: International Journal of Production Research
Pages: 4614-4628
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1005250
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Template-Type: ReDIF-Article 1.0
Author-Name: Sven Knoth
Author-X-Name-First: Sven
Author-X-Name-Last: Knoth
Title: Run length quantiles of EWMA control charts monitoring normal mean or/and variance
Abstract: 
 Exponentially weighted moving average (EWMA) control charts are well-established devices for monitoring process stability. Typically, control charts are evaluated by considering their Average Run Length (ARL), that is the expected number of observations or samples until the chart signals. Because of the limitations of an average, various papers also dealt with the run length distribution and quantiles. Going beyond these papers, we develop algorithms for and evaluate the quantile performance of EWMA control charts with variance adjusted control limits and with fast initial response features, of EWMA charts based on the sample variance, and of EWMA charts simultaneously monitoring mean and variance. Additionally, for the mean charts we consider medium, late and very late process changes and their impact on appropriately conditioned run length quantiles. It is demonstrated that considering run length quantiles can protect from constructing distorted EWMA designs while optimising their zero-state ARL performance. The implementation of all the considered measures in the R package ‘spc’ allows any control chart user to consider EWMA schemes from the run length quantile prospective in an easy way.
Journal: International Journal of Production Research
Pages: 4629-4647
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1005253
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005253
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Template-Type: ReDIF-Article 1.0
Author-Name: Huizhu Wang
Author-X-Name-First: Huizhu
Author-X-Name-Last: Wang
Author-Name: Seong-Hee Kim
Author-X-Name-First: Seong-Hee
Author-X-Name-Last: Kim
Author-Name: Xiaoming Huo
Author-X-Name-First: Xiaoming
Author-X-Name-Last: Huo
Author-Name: Youngmi Hur
Author-X-Name-First: Youngmi
Author-X-Name-Last: Hur
Author-Name: James R. Wilson
Author-X-Name-First: James R.
Author-X-Name-Last: Wilson
Title: Monitoring nonlinear profiles adaptively with a wavelet-based distribution-free CUSUM chart
Abstract: 
 A wavelet-based distribution-free tabular CUSUM chart based on adaptive thresholding, WDFTCa$ \text{ WDFTC}_a $ is designed for rapidly detecting shifts in the mean of a high-dimensional profile whose noise components have a continuous nonsingular multivariate distribution. First computing a discrete wavelet transform of the noise vectors for randomly sampled Phase I (in-control) profiles, WDFTCa$ \text{ WDFTC}_a $ uses a matrix-regularization method to estimate the covariance matrix of the wavelet-transformed noise vectors; then, those vectors are aggregated (batched) so that the non-overlapping batch means of the wavelet-transformed noise vectors have manageable covariances. Lower and upper in-control thresholds are computed for the resulting batch means of the wavelet-transformed noise vectors using the associated marginal Cornish–Fisher expansions that have been suitably adjusted for between-component correlations. From the thresholded batch means of the wavelet-transformed noise vectors, Hotelling’s T2$ T^2 $-type statistics are computed to set the parameters of a CUSUM procedure. To monitor shifts in the mean profile during Phase II (regular) operation, WDFTCa$ \text{ WDFTC}_a $ computes a similar Hotelling’s T2$ T^2 $-type statistic from successive thresholded batch means of the wavelet-transformed noise vectors using the in-control thresholds; then WDFTCa$ \text{ WDFTC}_a $ applies the CUSUM procedure to the resulting T2$ T^2 $-type statistics. Experimentation with several normal and non-normal test processes revealed that WDFTCa$ \text{ WDFTC}_a $ outperformed existing non-adaptive profile-monitoring schemes.
Journal: International Journal of Production Research
Pages: 4648-4667
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1029085
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Template-Type: ReDIF-Article 1.0
Author-Name: M. Assid
Author-X-Name-First: M.
Author-X-Name-Last: Assid
Author-Name: A. Gharbi
Author-X-Name-First: A.
Author-X-Name-Last: Gharbi
Author-Name: A. Hajji
Author-X-Name-First: A.
Author-X-Name-Last: Hajji
Title: Joint production, setup and preventive maintenance policies of unreliable two-product manufacturing systems
Abstract: 
 This article addresses the problem of joint optimisation of production, setup and maintenance activities of unreliable manufacturing system producing two products. Given the complexity of the problem in a dynamic and stochastic environment, the literature has treated the problem separately by considering each axis individually (setup, production and maintenance) or by combining two axes simultaneously (production-setup, production-maintenance). Following the trend of scientific research advances that supports the fact that an integrated control leads to best performances, the main objective of this paper is to provide a control policy that will simultaneously combine the production, the setup and the preventive maintenance activities. To tackle the problem, an experimental resolution approach using combined continuous/discrete event simulation models is considered. The aim is to accurately imitate the production system behaviour, and to optimise the control policy parameters which minimise the total cost incurred. An in-depth study of the effects of the system parameter variation on the performance of the studied policies is performed in order to draw meaningful conclusions and to illustrate the robustness of the proposed resolution approach.
Journal: International Journal of Production Research
Pages: 4668-4683
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1030468
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Template-Type: ReDIF-Article 1.0
Author-Name: Muhammad Aslam
Author-X-Name-First: Muhammad
Author-X-Name-Last: Aslam
Author-Name: Muhammad Azam
Author-X-Name-First: Muhammad
Author-X-Name-Last: Azam
Author-Name: Nasrullah Khan
Author-X-Name-First: Nasrullah
Author-X-Name-Last: Khan
Author-Name: Chi-Hyuck Jun
Author-X-Name-First: Chi-Hyuck
Author-X-Name-Last: Jun
Title: A mixed control chart to monitor the process
Abstract: 
 In this paper, we propose a mixed control chart to monitor the process quality using attribute data combined with variable data. The proposed control chart proceeds like an np control chart based on the number of nonconforming parts but requires variable data only when the decision is indeterminate. The control coefficients are determined by considering the in-control and the out-of-control average run lengths for various specified parameters. The extensive tables are provided for the industrial use. The advantages of the proposed control chart are discussed over the traditional np control chart.
Journal: International Journal of Production Research
Pages: 4684-4693
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1031354
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1031354
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Template-Type: ReDIF-Article 1.0
Author-Name: Zied Hajej
Author-X-Name-First: Zied
Author-X-Name-Last: Hajej
Author-Name: Sadok Turki
Author-X-Name-First: Sadok
Author-X-Name-Last: Turki
Author-Name: Nidhal Rezg
Author-X-Name-First: Nidhal
Author-X-Name-Last: Rezg
Title: Modelling and analysis for sequentially optimising production, maintenance and delivery activities taking into account product returns
Abstract: 
 This paper develops and analyses a stochastic optimisation problem with a service level constraint for generating a sequentially optimal plan of production, maintenance and delivery activities in a deteriorating manufacturing system. Stochastic demand along with product returns are both assumed the latter of which allows for restocking products returned by the customer which are still new and thus in saleable condition. A constrained production/maintenance/delivery problem with service level, stochastic demand, delivery time, failure rate and product returned is formulated based on quadratic model. This quadratic formulation is adapted to provide an inventory, delivery, production and maintenance policies. The objective of this paper is to study the delivery time influence on the planning of the production, maintenance and delivery activities. Finally, we present simulation results to illustrate the exploitation of the proposed approach.
Journal: International Journal of Production Research
Pages: 4694-4719
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1041569
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Template-Type: ReDIF-Article 1.0
Author-Name: Mou-Yuan Liao
Author-X-Name-First: Mou-Yuan
Author-X-Name-Last: Liao
Author-Name: W.L. Pearn
Author-X-Name-First: W.L.
Author-X-Name-Last: Pearn
Author-Name: Yen-Lun Liu
Author-X-Name-First: Yen-Lun
Author-X-Name-Last: Liu
Title: Assessing the actual Gamma process quality – a curve-fitting approach for modifying the non-normal flexible index
Abstract: 
 Process capability indices (PCIs) have been widely adopted for quality assurance activities. By analysing PCIs, a production department can trace and improve a poor process to enhance product quality level and satisfy customer requirements. Among these indices, Cpk remains the most prevalent for facilitating managerial decisions because it can provide bounds on the process yield for normally distributed processes. However, processes are often non-normal in practice, and Cpk may quite likely misrepresent the actual product quality. Hence, the flexible index Cjkp, which considers possible differences in the variability above and below the target value, has been developed for practical use. However, Cjkp continues to suffer from serious bias in assessing actual capability, especially when the process distribution is highly skewed. In this paper, we modify Cjkp for assessing the actual process quality of a Gamma process. A correction factor is obtained by the curve-fitting method. The results show that our proposed method can significantly reduce the bias for calculation of actual nonconformities. Moreover, we introduce a sample estimator for our modified index. The ratio of this estimator’s average value and the modified index is approximately 1. This implies that our proposed estimator can provide an appropriate estimation for assessing the actual Gamma process quality.
Journal: International Journal of Production Research
Pages: 4720-4734
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1041572
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1041572
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Template-Type: ReDIF-Article 1.0
Author-Name: Michael B.C. Khoo
Author-X-Name-First: Michael B.C.
Author-X-Name-Last: Khoo
Author-Name: Eng Keng Tan
Author-X-Name-First: Eng Keng
Author-X-Name-Last: Tan
Author-Name: Zhi Lin Chong
Author-X-Name-First: Zhi Lin
Author-X-Name-Last: Chong
Author-Name: Salah Haridy
Author-X-Name-First: Salah
Author-X-Name-Last: Haridy
Title: Side-sensitive group runs double sampling (SSGRDS) chart for detecting mean shifts
Abstract: 
 This paper proposes a side-sensitive group runs double sampling (SSGRDS) chart to detect shifts in the process mean. It improves the side-sensitive group runs chart proposed by Gadre and Rattihalli. The implementation of the SSGRDS chart is explained. The newly developed SSGRDS chart is compared with the synthetic, double sampling, synthetic double sampling, side-sensitive group runs and exponentially weighted moving average charts, in terms of the zero-state and steady-state average number of observations to signal (ANOS) and expected average number of observations to signal (EANOS). The zero-state and steady-state ANOS (ssANOS) and EANOS results reveal that the optimal SSGRDS chart generally performs well for detecting small and large mean shifts, from an overall perspective, compared with the optimal versions of other competing charts. This article provides tables of optimal charting parameters to facilitate the design of the SSGRDS chart. From these tables, the user can directly determine the optimal charting parameters for (i) minimising the standardised mean shift δopt$ \left( {\delta _{{{\text{opt}}}} } \right) $, based on different combinations of in-control ANOS ANOS0$ \left( {ANOS_{0} } \right) $ and in-control average sample size ASS0$ \left( {ASS_{0} } \right) $, or (ii) minimising an overall range of shifts δmin,δmax$ \left( {\delta _{{\min }} ,\delta _{{\max }} } \right) $, based on different in-control EANOS EANOS0$ \left( {EANOS_{0} } \right) $ and ASS0 combinations.
Journal: International Journal of Production Research
Pages: 4735-4753
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1043033
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1043033
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Template-Type: ReDIF-Article 1.0
Author-Name: He Huang
Author-X-Name-First: He
Author-X-Name-Last: Huang
Author-Name: Ting Xie
Author-X-Name-First: Ting
Author-X-Name-Last: Xie
Title: Reliability improvement and production decision under Cournot competition
Abstract: 
 We consider two competing manufacturers who are unreliable and exert effort endogenously to improve their reliability within a dynamic decision framework. The manufacturers first decide the optimal level of effort and then input quantities after observing improvement outcomes. We explore the relationship between optimal input quantity and realised reliability, and find that the balance between two effects – price reduction effect and cost reduction effect – plays an important role. When market potential is low, the cost reduction effect dominates the price reduction effect, resulting in that the optimal input quantity increases in the realised reliability. The opposite situation is true when the market potential is high. By further examining the interaction between competition and reliability improvement, we find that the competition reduces the effort level of reliability improvement and this impact increases in the probability of the improvement success. In terms of expected input quantity, the reliability improvement intensifies competition with lower market potential but weakens competition with higher market potential. While in terms of expected output quantity to the market, the improvement behaviour of each competitor always intensifies competition by reducing the output inefficiency caused by random yield.
Journal: International Journal of Production Research
Pages: 4754-4768
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1043402
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1043402
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Template-Type: ReDIF-Article 1.0
Author-Name: Afrooz Moatari-Kazerouni
Author-X-Name-First: Afrooz
Author-X-Name-Last: Moatari-Kazerouni
Author-Name: Yuvin Chinniah
Author-X-Name-First: Yuvin
Author-X-Name-Last: Chinniah
Author-Name: Bruno Agard
Author-X-Name-First: Bruno
Author-X-Name-Last: Agard
Title: A proposed occupational health and safety risk estimation tool for manufacturing systems
Abstract: 
 There are numerous hazards to be found in almost any workplace. Annually, millions of workers die, are injured or become ill as a result of these occupational hazards. Industrial machines are often involved in these occupational accidents. Because of the demands of regulatory compliance, and the potentially high cost in terms of human suffering and lost production, businesses should place particular emphasis on safety measures. Risk is defined as a combination of the probability of harm and the severity of its consequences. Generally, risk estimation involves examining the hazards associated with a situation or with the use of a machine. A large number of techniques have been proposed for risk estimation, and recent studies have revealed that some of them have serious flaws. The main objective of this paper is to develop a proposed risk assessment tool based on the findings of an earlier study. Our research results constitute a first step towards the integration of occupational health and safety (OHS) concerns into facility planning models which traditionally do not consider OHS. The proposed risk estimation tool is developed based on the characteristics, strengths and weaknesses of 31 existing risk estimation tools, and is then applied to 20 scenarios representing different hazardous situations. To evaluate the performance of the proposed tool, the results were compared with those of other risk estimation tools and confirmed its proposed ability to estimate risk relative to other risk estimation tools.
Journal: International Journal of Production Research
Pages: 4459-4475
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.942005
File-URL: http://hdl.handle.net/10.1080/00207543.2014.942005
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuwei Lu
Author-X-Name-First: Yuwei
Author-X-Name-Last: Lu
Author-Name: Xiaolan Xie
Author-X-Name-First: Xiaolan
Author-X-Name-Last: Xie
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Performance evaluation of elective inpatient admission with delay announcement
Abstract: 
 This paper investigates the improvement of the hospitalisation admission process of elective inpatients by delay announcement to free patients from blind and long wait, a phenomenon often observed in top Chinese hospitals. We propose a formal simulation model in which relevant resource requirements during the hospitalisation of a patient are represented by an original ‘multistage treatment model’. Other key components of the formal model include impatience of patients, resource capacities and key performance indicators such as the original concept of waiting time visibility. Through sensitivity analysis of the simulation model, we demonstrate the benefits of delay announcement and the value of our ‘multistage treatment model’.
Journal: International Journal of Production Research
Pages: 4476-4491
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.944628
File-URL: http://hdl.handle.net/10.1080/00207543.2014.944628
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:15:p:4476-4491




Template-Type: ReDIF-Article 1.0
Author-Name: Daniel Yuh Chao
Author-X-Name-First: Daniel Yuh
Author-X-Name-Last: Chao
Title: Revision on ‘Maximally permissive deadlock prevention via an Invariant Controlled Method’
Abstract: 
 All current design approaches of maximally permissive supervisors assume that forbidden and legal markings are linearly separable. Based on that implicit assumption, Liu et al. propose a novel method of optimal control of a problematic siphon to synthesise maximally permissive controllers. However, there are counter examples for which we could not produce optimal solutions. This occurs when forbidden and legal markings are not linearly separable even though it rarely happens. Verifying linear separability involves solving a large set of linear inequalities and is quite time consuming. This paper aims to relieve this problem via enhancing our critical-siphon approach. Specifically, we propose to: (1) find an efficient method to detect linear inseparability; (2) construct best suboptimal control models; (3) find all lost legal markings; and (4) identify the linear equations that violate linear separability. Each above contribution is unique and pioneering.
Journal: International Journal of Production Research
Pages: 4492-4498
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.949897
File-URL: http://hdl.handle.net/10.1080/00207543.2014.949897
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Template-Type: ReDIF-Article 1.0
Author-Name: Jinkun Lee
Author-X-Name-First: Jinkun
Author-X-Name-Last: Lee
Author-Name: Vittal Prabhu
Author-X-Name-First: Vittal
Author-X-Name-Last: Prabhu
Title: Optimal search of distributed arrival time control
Abstract: 
 Distributed arrival time control (DATC) is a heuristic feedback control algorithm for scheduling which has been developed for a real-time distributed scheduling of heterarchical systems. It has been renowned not only for its fast solution searching algorithm but also for its flexibility to changing environment. However, the optimality of this heuristic method has not been analytically explained until recently because it has been designed to discover a near optimal solution instead of the true optimum. In this paper, we provide a novel optimal search method for the DATC scheduling problem by introducing a scalar cost function over the vector space of time and show the existence and location of true optima for the DATC scheduling problem through geometric approach. This geometrical interpretation enables us to find the true optimal by direct projection without iterations like previous DATC approaches. Based on the true optimum found, we evaluate the optimality of DATC algorithms by examining their dependency on initial conditions and explain their intrinsic causality mechanism for the discrepancy with true optimum. The implication of this study is on the new viewpoint over the vector space of DATC, which not only solves the optimality issue of DATC but also provides a new direction of direct search approach like projection method for the true optimum.
Journal: International Journal of Production Research
Pages: 4499-4510
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.952794
File-URL: http://hdl.handle.net/10.1080/00207543.2014.952794
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhaoqiang Wang
Author-X-Name-First: Zhaoqiang
Author-X-Name-Last: Wang
Author-Name: Changhua Hu
Author-X-Name-First: Changhua
Author-X-Name-Last: Hu
Author-Name: Wenbin Wang
Author-X-Name-First: Wenbin
Author-X-Name-Last: Wang
Author-Name: Xiangyu Kong
Author-X-Name-First: Xiangyu
Author-X-Name-Last: Kong
Author-Name: Wei Zhang
Author-X-Name-First: Wei
Author-X-Name-Last: Zhang
Title: A prognostics-based spare part ordering and system replacement policy for a deteriorating system subjected to a random lead time
Abstract: 
 Prognostics-based spare part ordering and system replacement (PSOSR) policies are at the forefront of the prevalent prognostics and health management discipline. However, almost all of the existing researches in this domain ignore the stochasticity of the lead time. With this in mind, this paper proposes a PSOSR policy based on the real-time health condition of a deteriorating system subjected to a random lead time. In doing so, the degradation path of the interested system is modelled by a Wiener process, and the associated life distributions can be predicted recursively according to the real-time health condition of the system. In turn, the proposed policy can also be updated dynamically based on these real-time obtained life distributions. The policy, which – in addition to incorporating the stochasticity of the lead time – integrates the decision-making issues of both spare part ordering and system replacement – is finally applied to a case study of an inertial navigation system served in a type of aircraft. The experimental results validate the policy’s effectiveness and superiority.
Journal: International Journal of Production Research
Pages: 4511-4527
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.988892
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988892
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaojun Zhou
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Zhou
Author-Name: Yanting Li
Author-X-Name-First: Yanting
Author-X-Name-Last: Li
Author-Name: Lifeng Xi
Author-X-Name-First: Lifeng
Author-X-Name-Last: Xi
Author-Name: Jay Lee
Author-X-Name-First: Jay
Author-X-Name-Last: Lee
Title: Multi-phase preventive maintenance policy for leased equipment
Abstract: 
 This paper proposes a multi-phase preventive maintenance (PM) policy for leased equipment by combining the advantages of both periodic PM and sequential PM. The lease period of the equipment is divided into multiple PM phases. The PM activities within each phase are performed periodically with the convenience of implementation, while the frequency of PM for each phase is different and it gives a gradual increase because of the imperfect effect of PM. A multi-phase PM model is built up based on the age reduction method for imperfect PM with the penalty for equipment failures and overtime of repair involved. The optimal PM intervals for every PM phases are achieved by minimising the cumulative maintenance cost throughout the lease period from the perspective of the lessor. Numerical example shows that the cumulative maintenance cost under the proposed multi-phase PM policy is lower than that under periodic PM policy.
Journal: International Journal of Production Research
Pages: 4528-4537
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.990116
File-URL: http://hdl.handle.net/10.1080/00207543.2014.990116
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian Zhou
Author-X-Name-First: Jian
Author-X-Name-Last: Zhou
Author-Name: Zheyu Tang
Author-X-Name-First: Zheyu
Author-X-Name-Last: Tang
Author-Name: Deming Zhou
Author-X-Name-First: Deming
Author-X-Name-Last: Zhou
Author-Name: Ting Fang
Author-X-Name-First: Ting
Author-X-Name-Last: Fang
Title: A study on capacity allocation scheme with seasonal demand
Abstract: 
 This paper studies a game-theoretical capacity allocation problem in a two-echelon supply chain comprised of one supplier and N retailers. With demand fluctuating seasonally and significantly, supply is sufficient in low-demand periods but is insufficient in high-demand periods, especially when the supplier’s capacity decreases in high-demand periods. Retailers compete for the supplier’s capacity in high-demand periods, but do not want to absorb the supplier’s redundant capacity in low-demand periods. A turn-and-earn allocation scheme is proposed to encourage retailers to increase their order quantity in low-demand periods. Under the turn-and-earn allocation scheme, in high-demand periods, the supplier is willing to offer a guaranteed portion of supply capacity for the primary retailer. The remaining capacity in high-demand periods is allocated based on orders retailers placed in low-demand periods. In response, the retailers will decide how much they should order in low-demand periods. Then, a competitive game based on Nash equilibrium among the supplier and her retailers is analysed. In order to solve the problem of unreasonable distribution of interest caused by competition, a contract is designed to make it possible for subsidy to be transferred from the supplier to the retailers. Usually, the supplier and her primary retailer can both be better off under turn-and-earn allocation compared with fixed allocation, and the system efficiency in Nash solution is close to it in optimal solution. A numerical study is also conducted to discuss the parties’ sensitivity to different demand level and guaranteed allocation portion of capacity.
Journal: International Journal of Production Research
Pages: 4538-4552
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.991457
File-URL: http://hdl.handle.net/10.1080/00207543.2014.991457
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Template-Type: ReDIF-Article 1.0
Author-Name: Ata Allah Taleizadeh
Author-X-Name-First: Ata Allah
Author-X-Name-Last: Taleizadeh
Author-Name: Mahsa Noori-daryan
Author-X-Name-First: Mahsa
Author-X-Name-Last: Noori-daryan
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: Pricing and ordering decisions in a supply chain with imperfect quality items and inspection under buyback of defective items
Abstract: 
 In this article, the economic production and inventory model in a three-layer supply chain including one distributor, one manufacturer and one retailer for a single-product and general demand functions under three scenarios is developed. We assume that during the production process, both healthy and defective items are generated. As the first scenario, we develop the first model, in which the defective items are not reworked and all considered as scrape, while in the second model, we assume that the defective items are reworked and are sold as perfect item. In the second scenario, we assume that defective item can be sold with lower price than the selling price. Moreover, raw materials with imperfect quality are sent back from a distributor to outside supplier under a lower price. Determining the order quantity of the distributor and the selling prices of the distributor and the manufacturer as well as the retailer was the goal of this article such that the total profit of each member is maximised. In order to solve the models, the Stackelberg approach is employed between the members, and the concavity of the profit functions is proved using several theorems. Then, closed form solutions are derived for the decision variables and a solution algorithm is proposed to determine the optimal solutions. Finally, a numerical example is presented to illustrate the applicability of the model.
Journal: International Journal of Production Research
Pages: 4553-4582
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.997399
File-URL: http://hdl.handle.net/10.1080/00207543.2014.997399
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Template-Type: ReDIF-Article 1.0
Author-Name: S. Khalili
Author-X-Name-First: S.
Author-X-Name-Last: Khalili
Author-Name: H. Hosseini Nasab
Author-X-Name-First: H.
Author-X-Name-Last: Hosseini Nasab
Author-Name: F. Moobed
Author-X-Name-First: F.
Author-X-Name-Last: Moobed
Title: Optimal assignment of human resources for maintenance departments using fuzzy queuing systems
Abstract: 
 Maintenance-related costs are one of the main components of overhead costs and constitute an important part of a product’s actual cost. Therefore, making proper efforts to reduce and optimise maintenance costs could be one way of gaining competitive advantages. A major part of maintenance-related costs is the salaries paid to the workforce in the maintenance department. This paper seeks the optimal assignment of human resources to the maintenance department to reduce the related costs. First, we model the maintenance department using fuzzy queue models. Then, a cost function is proposed which includes the costs of workforce shortage and workforce overload. The optimal size of workforce is obtained by considering different numbers and choosing the one which minimises the total costs. Some parameters are fuzzy outputs of the queue models, which make fuzzy results of the cost function. In order to find the minimum fuzzy cost function, we use Lee and Li fuzzy ranking method. Finally, our model is tested in a spiral-tube company and a sensitivity analysis is performed.
Journal: International Journal of Production Research
Pages: 4583-4593
Issue: 15
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.998791
File-URL: http://hdl.handle.net/10.1080/00207543.2014.998791
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Template-Type: ReDIF-Article 1.0
Author-Name: Lei Xu
Author-X-Name-First: Lei
Author-X-Name-Last: Xu
Author-Name: Qian Wang
Author-X-Name-First: Qian
Author-X-Name-Last: Wang
Author-Name: Simin Huang
Author-X-Name-First: Simin
Author-X-Name-Last: Huang
Title: Dynamic order acceptance and scheduling problem with sequence-dependent setup time
Abstract: 
 This paper studies the order acceptance and scheduling problem under a single machine environment when the orders come stochastically during the planning horizon and a sequence-dependent setup time is required between the processing of different types of orders. The objective is to maximise the expected revenue subject to the due date constraints. The problem is formulated as a stochastic dynamic programming model. A rule based on the opportunity cost of the remaining system capacity for the current system state is proposed to make the order acceptance decisions. The remaining system capacity is estimated by a heuristic which generates a good schedule for the accepted orders. Its opportunity cost is estimated by both mathematical programme and greedy heuristic. Computational experiments show that the profit generated by the integrated dynamic programming decision model is much higher than the widely used first-come-first-accept policy in industries and the benefit increases with the length of planning horizon, the arrival rate and the length of lead time. Acceptance decision based on mathematical programming outperforms greedy heuristic by about 7% and its computational time is short. It also shows that the quality of the solutions generated by the opportunity cost based order acceptance rule is satisfactory.
Journal: International Journal of Production Research
Pages: 5797-5808
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1005768
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005768
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Template-Type: ReDIF-Article 1.0
Author-Name: Jordi Pereira
Author-X-Name-First: Jordi
Author-X-Name-Last: Pereira
Author-Name: Mariona Vilà
Author-X-Name-First: Mariona
Author-X-Name-Last: Vilà
Title: An exact algorithm for the mixed-model level scheduling problem
Abstract: 
 The Monden Problem, also known as the Output Rate Variation Problem, is one of the original formulations for mixed-model assembly line-level scheduling problems in a just-in-time system. In this paper, we develop a new branch-and-bound procedure for the problem that uses several new and previously proposed lower and upper bounds. The algorithm also includes several dominance rules that leverage the symmetry in the problem as well as a new labelling procedure that avoids repeated exploration of previously examined partial solutions. The branching strategy exploits the capabilities of current multiprocessor computers by exploring the search tree in a parallel fashion. The algorithm has been tested on several sets of instances from the literature and is able to optimally solve problems that are double the size of those addressed by other procedures previously reported in the literature.
Journal: International Journal of Production Research
Pages: 5809-5825
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1005771
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005771
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Template-Type: ReDIF-Article 1.0
Author-Name: Ji-Bo Wang
Author-X-Name-First: Ji-Bo
Author-X-Name-Last: Wang
Author-Name: Jian-Jun Wang
Author-X-Name-First: Jian-Jun
Author-X-Name-Last: Wang
Title: Research on scheduling with job-dependent learning effect and convex resource-dependent processing times
Abstract: 
 We study resource allocation scheduling with job-dependent learning effect on a single machine with or without due date assignment considerations. For a convex resource processing time function, we provide a polynomial time algorithm to find the optimal job sequence, and resource allocations that minimise the schedule criterion (the total compression cost) subject to the constraint that the total compression cost (the schedule criterion) is less than or equal to a fixed amount.
Journal: International Journal of Production Research
Pages: 5826-5836
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1010746
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1010746
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Template-Type: ReDIF-Article 1.0
Author-Name: Durk-Jouke van der Zee
Author-X-Name-First: Durk-Jouke
Author-X-Name-Last: van der Zee
Title: Family-based dispatching with parallel machines
Abstract: 
 Family-based dispatching heuristics seek to lower set-up frequencies by grouping similar types of jobs for joint processing. Hence, job flow times may be improved as less time is spent on set-ups. So far, family-based dispatching with parallel machines received little attention in literature. We address the perceived gap by proposing extensions to existing family-based dispatching heuristics. Main extensions concern improved rules for family priority settings and for coordinating the number of machines in use by a single family. Extended heuristics are tested by an extensive simulation study. Significant performance gains for extended heuristics vs. existing heuristics are found. Performance gains are largest for high set-up to run-time ratios.
Journal: International Journal of Production Research
Pages: 5837-5856
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1011289
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1011289
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Template-Type: ReDIF-Article 1.0
Author-Name: Kai Li
Author-X-Name-First: Kai
Author-X-Name-Last: Li
Author-Name: Shan-lin Yang
Author-X-Name-First: Shan-lin
Author-X-Name-Last: Yang
Author-Name: Joseph Y.-T. Leung
Author-X-Name-First: Joseph Y.-T.
Author-X-Name-Last: Leung
Author-Name: Ba-yi Cheng
Author-X-Name-First: Ba-yi
Author-X-Name-Last: Cheng
Title: Effective meta-heuristics for scheduling on uniform machines with resource-dependent release dates
Abstract: 
 This paper considers a uniform machine scheduling problem in which the release date of a job can be compressed by additional resources. The objective is to minimise the total resource usage, subject to the constraint that the makespan does not exceed a given deadline. The problem is known to be strongly NP-hard. We define two types of job moves - the right move and the left move - and analyse their effect on the resource usage. We discuss the calculation of total resource usage for two types of neighbourhood generation methods - the insertion method and exchange method. A variable neighbourhood search algorithm and a simulated annealing algorithm are developed as heuristics. To evaluate the performance of the heuristics, we develop a lower bound by relaxing the original problem to an assignment problem, which can be solved in O(n3)$ O(n^3) $ time. Finally, we generate a large number of random data, and test the performance and efficiency of the proposed heuristics. Our results indicate that the heuristics are reasonably efficient and perform very well compared with the lower bound.
Journal: International Journal of Production Research
Pages: 5857-5872
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1012303
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1012303
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Template-Type: ReDIF-Article 1.0
Author-Name: Jean-Philippe Gagliardi
Author-X-Name-First: Jean-Philippe
Author-X-Name-Last: Gagliardi
Author-Name: Jacques Renaud
Author-X-Name-First: Jacques
Author-X-Name-Last: Renaud
Author-Name: Angel Ruiz
Author-X-Name-First: Angel
Author-X-Name-Last: Ruiz
Title: Sequencing approaches for multiple-aisle automated storage and retrieval systems
Abstract: 
 Automated storage and retrieval systems (AS/RS) are used in high velocity distribution centres to provide accurate and fast order processing. While almost every industrial system is comprised of many aisles, most of the academic research on the operational aspects of AS/RS is devoted to single-aisle systems, probably due to the broadly accepted hypothesis proposing that an m aisles system can be modelled as m 1-aisle independent systems. In this article, we present two multi-aisles sequencing approaches and evaluate their performance when all the aisles are managed independently first, and then in a global manner. Computational experiments conducted on a multi-aisle AS/RS simulation model clearly demonstrate that a multi-aisle system cannot be accurately represented by multiple single-aisle systems. The numerical results demonstrate that, when dealing with random storage, globally sequencing multi-aisle AS/RS leads to makespan reductions ranging from 14 to 29% for 2- and 3-aisle systems, respectively.
Journal: International Journal of Production Research
Pages: 5873-5883
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1012600
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1012600
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanyan Wang
Author-X-Name-First: Yanyan
Author-X-Name-Last: Wang
Author-Name: Shandong Mou
Author-X-Name-First: Shandong
Author-X-Name-Last: Mou
Author-Name: Yaohua Wu
Author-X-Name-First: Yaohua
Author-X-Name-Last: Wu
Title: Task scheduling for multi-tier shuttle warehousing systems
Abstract: 
 Multi-tier shuttle warehousing systems are increasingly popular because of their high flexibility and robustness. These systems consist of a multi-tier shuttle sub-system that controls horizontal movement and a lift sub-system that manages vertical movement. The combination of shuttles and lifts undertakes inbound/outbound tasks instead of the stacker crane in conventional automated storage and retrieval systems. Scheduling different devices to reduce expected cycle time is an important concern. Thus, we propose a time sequence mathematical model of task operation on the basis of the movement characteristics of shuttles and lifts. The task scheduling problem between shuttles and lifts is converted into an assembly line parallel job problem by analysing the mathematical model, which generates the scheduling task queue model in the specified time window. In addition, a Pareto optimal based on an elitist non-dominated sorting genetic algorithm is adopted to solve the multi-objective optimisation function in the task scheduling problem. Finally, we illustrate the findings of the study through a practical example. Results show that the optimisation scheduling solution can reduce the total lift idle time and the total shuttle waiting time. Furthermore, it can improve warehousing efficiency and lower operation costs.
Journal: International Journal of Production Research
Pages: 5884-5895
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1012604
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1012604
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Template-Type: ReDIF-Article 1.0
Author-Name: Kai Zhou Gao
Author-X-Name-First: Kai Zhou
Author-X-Name-Last: Gao
Author-Name: Ponnuthurai Nagaratnam Suganthan
Author-X-Name-First: Ponnuthurai Nagaratnam
Author-X-Name-Last: Suganthan
Author-Name: Quan Ke Pan
Author-X-Name-First: Quan Ke
Author-X-Name-Last: Pan
Author-Name: Mehmet Fatih Tasgetiren
Author-X-Name-First: Mehmet Fatih
Author-X-Name-Last: Tasgetiren
Title: An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time
Abstract: 
 This study addresses flexible job shop scheduling problem (FJSP) with fuzzy processing time. The fuzzy or uncertainty of processing time is one of seven characteristics in remanufacturing. A discrete harmony search (DHS) algorithm is proposed for FJSP with fuzzy processing time. The objective is to minimise maximum fuzzy completion time. A simple and effective heuristic rule is proposed to initialise harmony population. Extensive computational experiments are carried out using five benchmark cases with eight instances from remanufacturing. The proposed heuristic rule is evaluated using five benchmark cases. The proposed DHS algorithm is compared to six metaheuristics. The results and comparisons show the effectiveness and efficiency of DHS for solving FJSP with fuzzy processing time.
Journal: International Journal of Production Research
Pages: 5896-5911
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1020174
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1020174
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Template-Type: ReDIF-Article 1.0
Author-Name: Martin Steinrücke
Author-X-Name-First: Martin
Author-X-Name-Last: Steinrücke
Title: Integrated production, distribution and scheduling in the aluminium industry: a continuous-time MILP model and decomposition method
Abstract: 
 This article deals with the multi-stage production–shipping and distribution–scheduling problem in the aluminium industry. Related processes take place in worldwide operating networks with multiple sites in each stage. The aim is to coordinate production activities and material flows worldwide months in advance and exactly to the day, so that temporary storage of intermediate products is reduced network wide or even set to zero. This paper includes a further development of the multi-stage production-shipping and distribution-scheduling problem including in-time supplies of all production sites (MSPSDS-IS). However, the in-time supplies at the sites often result in network-wide temporary storage before and/or after site production. In contrast, it should be possible that either stock-free material flows within the entire network or site-specific storage times are prescribed. The previous modelling is not able to meet these aforementioned requirements as it can be considered as special case of the generalised approach developed in the following. Therefore, a substantially extended continuous-time MILP model is presented. Furthermore, extensive computational experiments with a high-performance computer indicate that a modified version of the relax-and-fix heuristic, which was applicable to the MSPSDS-IS, also results in high-quality solutions and remarkable reductions in computation times.
Journal: International Journal of Production Research
Pages: 5912-5930
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1023401
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1023401
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Template-Type: ReDIF-Article 1.0
Author-Name: K.P. Abdul Nazar
Author-X-Name-First: K.P.
Author-X-Name-Last: Abdul Nazar
Author-Name: V. Madhusudanan Pillai
Author-X-Name-First: V.
Author-X-Name-Last: Madhusudanan Pillai
Title: A bit-wise mutation algorithm for mixed-model sequencing in JIT production systems
Abstract: 
 Product sequencing in a mixed-model production system is an operational level problem and is computationally hard. This necessitates the use of non-traditional optimisation methods to solve it in a short time. In the first phase, this study addresses the mixed-model sequencing problem with the objective of minimising production rates variation (PRV) which is a just-in-time objective. We formulated a mixed integer quadratic assignment model for this problem. LINGO 14.0 solver could solve this model for small- and medium-size problems. The study presents a bit-wise mutation algorithm to solve the sequencing problem with the same objective. This algorithm uses a single unary operator which makes it simpler and faster. Computational results show that the algorithm succeeds in solving large-size PRV problems in a reasonable time, for which the algorithms reported in the literature could only get near-optimal solutions. In the second phase, we consider both PRV and one of the system performance measures, makespan as objectives for the mixed-model sequencing problem. A mathematical description of the underlying model is provided. The bit-wise mutation algorithm is modified to generate a set of non-dominated solutions which provide the decision-maker with the opportunity to trade-off between the two objectives.
Journal: International Journal of Production Research
Pages: 5931-5947
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1032438
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1032438
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Template-Type: ReDIF-Article 1.0
Author-Name: E. Cunha Neto
Author-X-Name-First: E.
Author-X-Name-Last: Cunha Neto
Author-Name: V.J.M. Ferreira Filho
Author-X-Name-First: V.J.M.
Author-X-Name-Last: Ferreira Filho
Author-Name: E.F. Arruda
Author-X-Name-First: E.F.
Author-X-Name-Last: Arruda
Title: Stochastic economic lot sizing and scheduling problem with pitch interval, reorder points and flexible sequence
Abstract: 
 This paper presents a solution for a class of the stochastic economic lot sizing scheduling problem that is typical of the replenishment pull system proposed by the lean manufacturing approach. In this class, lots of any product are produced in fixed intervals called pitch. The proposed solution uses flexible production sequences and reorder points that are compatible with the concepts of supermarket and level production. It adopts the queuing discipline obtained from a fluid model that approximates the stochastic process of arrival and production orders. Given the queuing discipline, an iterative algorithm returns a near-optimal solution for the system. The proposed approach allows us possible to differentiate inventory cost and service levels by product, and the stock required is lower than that required by the discipline ‘first stock out, first out’. The algorithm is fast and stable, allowing its frequent use in real-world instances.
Journal: International Journal of Production Research
Pages: 5948-5961
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1033031
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1033031
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Template-Type: ReDIF-Article 1.0
Author-Name: Homa Amirian
Author-X-Name-First: Homa
Author-X-Name-Last: Amirian
Author-Name: Rashed Sahraeian
Author-X-Name-First: Rashed
Author-X-Name-Last: Sahraeian
Title: Augmented ε-constraint method in multi-objective flowshop problem with past sequence set-up times and a modified learning effect
Abstract: 
 This article addresses a general tri-objective non-permutation flowshop problem to minimise the makespan, the sum of flow time and maximum tardiness simultaneously. In order to enhance the applicability of the model, some practical assumptions are included. These are release dates, past sequence-dependent set-up times, a truncated generalisation of Dejong’s learning effect and predetermined machine availability constraints. First, the problem is formulated as a mixed-integer linear programming model. Second, the true Pareto front is achieved with augmented ε-constraint method for small-sized problems. Third, due to the high complexity of the model and the impractical computational times of larger instances, a heuristic algorithm based on the ε-constraint method is also proposed. Finally, the algorithms are tested to gauge their effectiveness, and the results are compared with other methods.
Journal: International Journal of Production Research
Pages: 5962-5976
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1033033
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1033033
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Template-Type: ReDIF-Article 1.0
Author-Name: R. M’Hallah
Author-X-Name-First: R.
Author-X-Name-Last: M’Hallah
Author-Name: T. Al-Khamis
Author-X-Name-First: T.
Author-X-Name-Last: Al-Khamis
Title: A Benders decomposition approach to the weighted number of tardy jobs scheduling problem on unrelated parallel machines with production costs
Abstract: 
 This paper addresses the problem of scheduling on-time jobs on unrelated parallel machines with machine production costs. The objective is to maximise the net profit which is the sum of the weights of on-time jobs and the cost of using the machines. This scheduling problem is very important and frequent in industrial settings. It is herein solved using an exact approach that applies Benders decomposition to obtain tight upper and lower bounds and uses the bounds within a branch and bound. The computational investigation shows the efficacy of the approach in solving large instances. Most importantly, the proposed approach provides a new venue for solving large-scale scheduling problems.
Journal: International Journal of Production Research
Pages: 5977-5987
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1033501
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1033501
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Template-Type: ReDIF-Article 1.0
Author-Name: Amir Ahmadi-Javid
Author-X-Name-First: Amir
Author-X-Name-Last: Ahmadi-Javid
Author-Name: Pedram Hooshangi-Tabrizi
Author-X-Name-First: Pedram
Author-X-Name-Last: Hooshangi-Tabrizi
Title: A mathematical formulation and anarchic society optimisation algorithms for integrated scheduling of processing and transportation operations in a flow-shop environment
Abstract: 
 This paper addresses a permutation flow-shop scheduling problem where there are a finite number of transporters to carry jobs from each machine to its subsequent machine. The problem is first formulated as a mixed-integer linear programme, and then two anarchic society optimisation (ASO) algorithms are developed to solve large-sized instances of the problem. The numerical experience shows that the ASO algorithms are considerably effective and efficient. Finally, a sensitivity analysis is carried out to study the performance of the manufacturing system versus the transportation times and the number of transporters.
Journal: International Journal of Production Research
Pages: 5988-6006
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1035812
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1035812
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Template-Type: ReDIF-Article 1.0
Author-Name: Jun-Ho Lee
Author-X-Name-First: Jun-Ho
Author-X-Name-Last: Lee
Author-Name: Hyun-Jung Kim
Author-X-Name-First: Hyun-Jung
Author-X-Name-Last: Kim
Author-Name: Tae-Eog Lee
Author-X-Name-First: Tae-Eog
Author-X-Name-Last: Lee
Title: Scheduling cluster tools for concurrent processing of two wafer types with PM sharing
Abstract: 
 We examine cyclic scheduling of single-armed and dual-armed cluster tools that concurrently process two wafer types by sharing a process module (PM). Because a PM is shared by two different wafers, the backward and swap sequences, which are prevalently used for single-armed and dual-armed tools without such complexity, respectively, are not effective. We therefore propose new sequences, called alternating backward and alternating swap sequences, for steady cycles of single-armed and dual-armed tools, respectively. We then develop optimality conditions for which the proposed sequences achieve the minimum cycle times in a fundamental cycle, and show that the optimality conditions hold for most practical cases. We also develop a condition for which a shared PM becomes the bottleneck and hence the PM sharing increases the cycle time. For general cycles, we propose heuristic scheduling methods that combine both the alternating backward (or swap) sequence and the conventional backward (or swap) sequence. Finally, we experimentally verify the efficiency and effectiveness of the proposed algorithm for dual-armed cluster tools.
Journal: International Journal of Production Research
Pages: 6007-6022
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1035813
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1035813
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Template-Type: ReDIF-Article 1.0
Author-Name: Yoav Ben-Yehoshua
Author-X-Name-First: Yoav
Author-X-Name-Last: Ben-Yehoshua
Author-Name: Eyal Hariri
Author-X-Name-First: Eyal
Author-X-Name-Last: Hariri
Author-Name: Gur Mosheiov
Author-X-Name-First: Gur
Author-X-Name-Last: Mosheiov
Title: A note on minimising total absolute deviation of job completion times on a two-machine no-wait proportionate flowshop
Abstract: 
 A popular measure used in service systems is that of total absolute deviation of job completion times (TADC). It is relevant to settings where the objective is to balance the level of service provided to different customers. During the last decade, TADC has been studied in various machine settings, and under various assumptions on the job processing times. In this note, we study TADC on a two-machine no-wait proportionate flow shop, i.e. a flow shop with machine-independent processing times, and with no buffer between the machines. A very surprising and unique result is introduced: a simple index policy (the well-known largest processing time (LPT) first sequence) is shown to be optimal for instances of no more than seven jobs. This property does not hold for larger instances. We show that for instances of eight and nine jobs, there are exactly two schedules which are candidates for optimality. For the 10-job instance, the number of candidates increases. This uncommon behaviour of the optimal solution and, consequently, the complexity of the problem studied here, remain open questions, and are challenging topics for future research.
Journal: International Journal of Production Research
Pages: 5717-5724
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2014.991843
File-URL: http://hdl.handle.net/10.1080/00207543.2014.991843
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Template-Type: ReDIF-Article 1.0
Author-Name: Dilupa Nakandala
Author-X-Name-First: Dilupa
Author-X-Name-Last: Nakandala
Author-Name: H.C.W. Lau
Author-X-Name-First: H.C.W.
Author-X-Name-Last: Lau
Author-Name: Li Zhao
Author-X-Name-First: Li
Author-X-Name-Last: Zhao
Title: A hybrid optimisation model for pallet loading
Abstract: 
 This study adopts a hybrid approach that integrates the genetic algorithm (GA) and fuzzy logic in order to assist in the generation of an optimal pallet loading plan. The proposed model enables the maximisation of profits for freight forwarders through the most efficient use of space and weight in pallet loading. The model uses fuzzy controllers to determine the numbers and size of cargo units on a pallet as well as the mutation rate in the GA approach within the optimisation process and enables the capture of tacit knowledge vested in industry practitioners. The pragmatic use of the model is illustrated using a freight-forwarding scenario that demonstrates the inherent limitations of the standard GA method, followed by the application of the proposed fuzzy GA model. To further demonstrate the benefits of the hybrid model, simulated annealing and Tabu search are used to benchmark the results achieved using various approaches; the proposed hybrid model is demonstrated to exceed these other approaches in overall performance. The application of the proposed hybrid approach across a range of scenarios is also discussed.
Journal: International Journal of Production Research
Pages: 5725-5741
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2014.993044
File-URL: http://hdl.handle.net/10.1080/00207543.2014.993044
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Template-Type: ReDIF-Article 1.0
Author-Name: Paz Perez-Gonzalez
Author-X-Name-First: Paz
Author-X-Name-Last: Perez-Gonzalez
Author-Name: Jose M. Framinan
Author-X-Name-First: Jose M.
Author-X-Name-Last: Framinan
Title: Assessing scheduling policies in a permutation flowshop with common due dates
Abstract: 
 This paper focuses onto a situation arising in most real-life manufacturing environments when scheduling has to be performed periodically. In such a scenario, different scheduling policies can be adopted, being perhaps the most common to assume that, once a set of jobs has been scheduled, their schedule cannot be modified (‘frozen’ schedule). This implies that, when the next set of jobs is to be scheduled, the resources may not be fully available. Another option is assuming that the schedule of the previously scheduled jobs can be modified as long as it does not violate their due date, which has been already possibly committed to the customer. This policy leads to a so-called multi-agent scheduling problem. The goal of this paper is to discern when each policy is more suitable for the case of a permutation flowshop with common due dates. To do so, we carry out an extensive computational study in a test bed specifically designed to control the main factors affecting the policies, so we analyse the solution space of the underlying scheduling problems. The results indicate that, when the due date of the committed jobs is tight, the multi-agent approach does not pay off in view of the difficulty of finding feasible solutions. Moreover, in such cases, the policy of ‘freezing’ the schedule of the jobs leads to a very simple scheduling problem with many good/acceptable solutions. In contrast, when the due date has a medium/high slack, the multi-agent approach is substantially better. Nevertheless, in this latter case, in order to perceive the full advantage of this policy, powerful solution procedures have to be designed, as the structure of the solution space of the latter problem makes extremely hard to find optimal/good solutions.
Journal: International Journal of Production Research
Pages: 5742-5754
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2014.994077
File-URL: http://hdl.handle.net/10.1080/00207543.2014.994077
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Template-Type: ReDIF-Article 1.0
Author-Name: Li-Lan Liu
Author-X-Name-First: Li-Lan
Author-X-Name-Last: Liu
Author-Name: Rong-Song Hu
Author-X-Name-First: Rong-Song
Author-X-Name-Last: Hu
Author-Name: Xiang-Ping Hu
Author-X-Name-First: Xiang-Ping
Author-X-Name-Last: Hu
Author-Name: Gai-Ping Zhao
Author-X-Name-First: Gai-Ping
Author-X-Name-Last: Zhao
Author-Name: Sen Wang
Author-X-Name-First: Sen
Author-X-Name-Last: Wang
Title: A hybrid PSO-GA algorithm for job shop scheduling in machine tool production
Abstract: 
 In our previous research applied to the job shop scheduling problem (JSSP) for machine tool production, the multi-objective optimisation model based on the particle swarm optimization (PSO) research had an imbalance performance between the convergence rate and the convergence precision. In this article, a new hybrid algorithm using PSO and generic algorithm (GA) is proposed to solve this particular problem. In this new algorithm, named hybrid PSO-GA algorithm (HPGA), the PSO algorithm is redefined and modified by introducing genetic operators, i.e. the crossover operator and the mutation operator, to update the particles in the population. The HPGA is then applied in heavy machinery company with minimising machines’ makespan and minimising jobs’ tardiness as the two optimal objectives. The comparisons with actual application report have illustrated that the proposed HPGA can obtain higher quality of schedule solution for machine tool production. Furthermore, with solution quality and convergence rate as the two estimation measurements metrics, some comparisons are performed in order to illustrate that the HPGA has superiority over the PSO, GA and simulated annealing algorithm (SA). Results have indicated that, with the combination of the merits of PSO and GA, the proposed HPGA approach can achieve not only better solution quality but also faster convergence rate than the PSO, GA and SA, within a reasonable computation time for high dimensions JSSP.
Journal: International Journal of Production Research
Pages: 5755-5781
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2014.994714
File-URL: http://hdl.handle.net/10.1080/00207543.2014.994714
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Template-Type: ReDIF-Article 1.0
Author-Name: Christopher Daniel Rose
Author-X-Name-First: Christopher Daniel
Author-X-Name-Last: Rose
Author-Name: Jenny M.G. Coenen
Author-X-Name-First: Jenny M.G.
Author-X-Name-Last: Coenen
Title: Comparing four metaheuristics for solving a constraint satisfaction problem for ship outfitting scheduling
Abstract: 
 This study compares the performance of four different metaheuristics for solving a constraint satisfaction scheduling problem of the outfitting process of shipbuilding. The ship outfitting process is often unorganised and chaotic due to the complex interactions between the stakeholders and the overall lack of sufficiently detailed planning. The examined methods are genetic algorithms (GA), simulated annealing (SA), genetic simulated annealing (GSA) and discrete particle swarm optimisation (PSO). Each of these methods relies on a list scheduling heuristic to transform the solution space into feasible schedules. Although the SA had the best performance for a medium-sized superstructure section, the GSA created the best schedules for engine room double-bottom sections, the most complex sections in terms of outfitting. The GA provided the best scalability in terms of computational time while only marginally sacrificing solution quality. The solution quality of the PSO was very poor in comparison with the other methods. All methods generated schedules with sufficiently high resource utilisation, approximately 95%. The findings from this work will be incorporated into a larger project with the aim of creating a tool which can automatically generate an outfitting planning for a vessel.
Journal: International Journal of Production Research
Pages: 5782-5796
Issue: 19
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2014.998786
File-URL: http://hdl.handle.net/10.1080/00207543.2014.998786
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Template-Type: ReDIF-Article 1.0
Author-Name: Shahab Derhami
Author-X-Name-First: Shahab
Author-X-Name-Last: Derhami
Author-Name: Jeffrey S. Smith
Author-X-Name-First: Jeffrey S.
Author-X-Name-Last: Smith
Author-Name: Kevin R. Gue
Author-X-Name-First: Kevin R.
Author-X-Name-Last: Gue
Title: Optimising space utilisation in block stacking warehouses
Abstract: 
 Block stacking storage is an inexpensive storage system widely used in manufacturing systems where pallets of stock keeping units (SKUs) are stored in a warehouse at the finite production rates. However, determining the optimal lane depth that maximises space utilisation under a finite production rate constraint has not been adequately addressed in the literature and is an open problem. In this research, we propose mathematical models to obtain the optimal lane depth for single and multiple SKUs where the pallet production rates are finite. A simulation model is used to evaluate performance of the proposed models under stochastic uncertainty in the major production parameters and the demand.
Journal: International Journal of Production Research
Pages: 6436-6452
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1154216
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154216
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Template-Type: ReDIF-Article 1.0
Author-Name: José Antonio Larco
Author-X-Name-First: José Antonio
Author-X-Name-Last: Larco
Author-Name: René de Koster
Author-X-Name-First: René
Author-X-Name-Last: de Koster
Author-Name: Kees Jan Roodbergen
Author-X-Name-First: Kees Jan
Author-X-Name-Last: Roodbergen
Author-Name: Jan Dul
Author-X-Name-First: Jan
Author-X-Name-Last: Dul
Title: Managing warehouse efficiency and worker discomfort through enhanced storage assignment decisions
Abstract: 
 Humans are at the heart of crucial processes in warehouses. Besides the common economic goal of minimising cycle times, we therefore add in this paper the human well-being goal of minimising workers’ discomfort in the context of order picking. We propose a methodology for identifying the most suitable storage location solutions with respect to both goals. The first step in our methodology is to build data-driven empirical models for estimating cycle times and workers’ discomfort. The second step of the methodology entails the use of these empirically grounded models to formulate a bi-objective assignment problem for assigning products to storage locations. The developed methodology is subsequently tested on two actual warehouses. The results of these practical tests show that clear trade-offs exist and that optimising only for discomfort can be costly in terms of cycle time. Based on the results, we provide practical guidelines for taking storage assignment decisions that simultaneously address discomfort and travel distance considerations.
Journal: International Journal of Production Research
Pages: 6407-6422
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1165880
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165880
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Template-Type: ReDIF-Article 1.0
Author-Name: Banu Yetkin Ekren
Author-X-Name-First: Banu
Author-X-Name-Last: Yetkin Ekren
Title: Graph-based solution for performance evaluation of shuttle-based storage and retrieval system
Abstract: 
 The aim of this study is to provide a graph-based solution for performance evaluation of a new autonomous vehicle-based storage and retrieval system, shuttle-based storage and retrieval system (SBS/RS), under various design concepts. By the graph-based solution, it is aimed the decision-maker (i.e. warehouse manager) evaluates a pre-defined system’s performance promptly and decides on the correct design concept based on his/her requirements from thousands of alternative design scenarios of SBS/RS. The design concepts include number of bays (NoB), aisles (NoA) and tiers (NoT) for the rack design and arrival rate of storage/retrieval (S/R) transactions to an aisle of the warehouse (AR). The performance of the system is evaluated in terms of average utilisation of lifts and average cycle time of S/R transactions. Simulation is utilised for the modelling purpose. Seven NoT, seven NoB and six AR scenarios are considered in the experiments. Hence, 294 experiments are completed to obtain the graphs. By this study, to the best of our knowledge it is the first time a graph-based solution including comprehensive design concepts of SBS/RS is presented.
Journal: International Journal of Production Research
Pages: 6516-6526
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1203076
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1203076
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Template-Type: ReDIF-Article 1.0
Author-Name: Albert H. Schrotenboer
Author-X-Name-First: Albert H.
Author-X-Name-Last: Schrotenboer
Author-Name: Susanne Wruck
Author-X-Name-First: Susanne
Author-X-Name-Last: Wruck
Author-Name: Kees Jan Roodbergen
Author-X-Name-First: Kees Jan
Author-X-Name-Last: Roodbergen
Author-Name: Marjolein Veenstra
Author-X-Name-First: Marjolein
Author-X-Name-Last: Veenstra
Author-Name: Arjan S. Dijkstra
Author-X-Name-First: Arjan S.
Author-X-Name-Last: Dijkstra
Title: Order picker routing with product returns and interaction delays
Abstract: 
 E-commerce companies often use manual order-picking systems in their warehouses since these systems can provide the required flexibility and scalability. Manual systems have been widely studied, but the operating policies may require significant changes for e-commerce settings. First, to maintain consumers’ loyalty, it is important to maintain delivery reliability even on the busiest days. When the number of order pickers in an area increases, however, more delays due to interactions may occur. For example, travel speed may need to be lowered when order pickers pass each other in narrow aisles. Second, many products sold through e-commerce are returned by consumers. Before these returned products can be sold again, they must be reintegrated in the stock. This paper presents hybrid genetic algorithms to determine routes for simultaneous pickup of products in response to consumers’ orders and delivery of returned products to storage locations. Furthermore, interactions between the order pickers are considered in the routing decisions. The developed algorithms use specific warehouse problem characteristics. We identify the mix of pickups and deliveries to realise the highest savings in practice. It is shown that order-picker interactions can be a significant cause for delay and should be accounted for in the routing.
Journal: International Journal of Production Research
Pages: 6394-6406
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1206982
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1206982
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Template-Type: ReDIF-Article 1.0
Author-Name: Susanne Wruck
Author-X-Name-First: Susanne
Author-X-Name-Last: Wruck
Author-Name: Iris F.A. Vis
Author-X-Name-First: Iris F.A.
Author-X-Name-Last: Vis
Author-Name: Jaap Boter
Author-X-Name-First: Jaap
Author-X-Name-Last: Boter
Title: Risk control for staff planning in e-commerce warehouses
Abstract: 
 Internet sale supply chains often need to fulfil quickly small orders for many customers. The resulting high demand and planning uncertainties pose new challenges for e-commerce warehouse operations. Here, we develop a decision support tool to assist managers in selecting appropriate risk policies and making staff planning decisions in uncertain conditions. Multistage stochastic modelling has been used to analyse risk optimisation approaches and expected value-based optimisation. Exhaustive numerical and practical validations have been performed to test the tool’s applicability. We demonstrate, using a Dutch e-commerce warehouse, that the multi-period conditional value at risk appears to be most applicable.
Journal: International Journal of Production Research
Pages: 6453-6469
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1207816
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1207816
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Template-Type: ReDIF-Article 1.0
Author-Name: Jörg M. Ries
Author-X-Name-First: Jörg M.
Author-X-Name-Last: Ries
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: Johannes Fichtinger
Author-X-Name-First: Johannes
Author-X-Name-Last: Fichtinger
Title: Environmental impact of warehousing: a scenario analysis for the United States
Abstract: 
 In recent years, there has been observed a continued growth of global carbon dioxide emissions, which are considered as a crucial factor for the greenhouse effect and associated with substantial environmental damages. Amongst others, logistic activities in global supply chains have become a major cause of industrial emissions and the progressing environmental pollution. Although a significant amount of logistic-related carbon dioxide emissions is caused by storage and material handling processes in warehouses, prior research mostly focused on the transport elements. The environmental impact of warehousing has received only little attention by research so far. Operating large and highly technological warehouses, however, causes a significant amount of energy consumption due to lighting, heating, cooling and air condition as well as fixed and mobile material handling equipment which induces considerable carbon dioxide emissions. The aim of this paper is to summarise preliminary studies of warehouse-related emissions and to discuss an integrated classification scheme enabling researchers and practitioners to systematically assess the carbon footprint of warehouse operations. Based on the systematic assessment approach containing emissions determinants and aggregates, overall warehouse emissions as well as several strategies for reducing the carbon footprint will be studied at the country level using empirical data of the United States. In addition, a factorial analysis of the warehouse-related carbon dioxide emissions in the United States enables the estimation of future developments and facilitates valuable insights for identifying effective mitigation strategies.
Journal: International Journal of Production Research
Pages: 6485-6499
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1211342
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1211342
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Template-Type: ReDIF-Article 1.0
Author-Name: Teun van Gils
Author-X-Name-First: Teun
Author-X-Name-Last: van Gils
Author-Name: Katrien Ramaekers
Author-X-Name-First: Katrien
Author-X-Name-Last: Ramaekers
Author-Name: An Caris
Author-X-Name-First: An
Author-X-Name-Last: Caris
Author-Name: Mario Cools
Author-X-Name-First: Mario
Author-X-Name-Last: Cools
Title: The use of time series forecasting in zone order picking systems to predict order pickers’ workload
Abstract: 
 In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. This paper introduces workload forecasting in a warehouse context, in particular a zone picking warehouse. Improved workforce planning can contribute to an effective and efficient order picking process. Most order picking publications treat demand as known in advance. As warehouses accept late orders, the assumption of a constant given demand is questioned in this paper. The objective of this study is to present time series forecasting models that perform well in a zone picking warehouse. A real-life case study demonstrates the value of applying time series forecasting models to forecast the daily number of order lines. The forecast of order lines, along with order pickers’ productivity, can be used by warehouse supervisors to determine the daily required number of order pickers, as well as the allocation of order pickers across warehouse zones. Time series are applied on an aggregated level, as well as on a disaggregated zone level. Both bottom-up and top-down approaches are evaluated in order to find the best-performing forecasting method.
Journal: International Journal of Production Research
Pages: 6380-6393
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1216659
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1216659
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Template-Type: ReDIF-Article 1.0
Author-Name: Timothy Sprock
Author-X-Name-First: Timothy
Author-X-Name-Last: Sprock
Author-Name: Anike Murrenhoff
Author-X-Name-First: Anike
Author-X-Name-Last: Murrenhoff
Author-Name: Leon F. McGinnis
Author-X-Name-First: Leon F.
Author-X-Name-Last: McGinnis
Title: A hierarchical approach to warehouse design
Abstract: 
 The design of large complex systems, such as warehouses, requires multiple experts and analyses as well as methods to organise and integrate their knowledge. While there are many models for optimising individual aspects of warehouses, there is not, today, a comprehensive design methodology that incorporates and supports all of the design decisions and provides a method to effectively integrate the solutions to these subproblems into a complete warehouse system specification. In this research, we propose a hierarchical design decision support methodology based on decomposing the design problem into a set of subproblems and using a formal model of the system to integrate the solutions to these subproblems. The methodology enables a thorough search of the design space and the identification of many candidate designs for consideration by the design decision maker. The hierarchical design methodology is demonstrated with an example of designing a forward pick area.
Journal: International Journal of Production Research
Pages: 6331-6343
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1241447
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1241447
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Template-Type: ReDIF-Article 1.0
Author-Name: Bradley Guthrie
Author-X-Name-First: Bradley
Author-X-Name-Last: Guthrie
Author-Name: Pratik J. Parikh
Author-X-Name-First: Pratik J.
Author-X-Name-Last: Parikh
Author-Name: Nan Kong
Author-X-Name-First: Nan
Author-X-Name-Last: Kong
Title: Evaluating warehouse strategies for two-product class distribution planning
Abstract: 
 Distribution networks often manage products with varying life cycles, where demand for some products is relatively stable throughout the year (basic) and the demand for others is short-lived (fashion). Beyond the coordination of inventory and transportation decisions, decisions at the warehouse must be considered as its resources are frequently shared by both product classes simultaneously. For this two-product class distribution planning problem, we focus on characterising three real-world distribution strategies observed in industry and evaluating them based on total distribution cost and warehouse measures (e.g. workforce plan and workload variation) against a benchmark ILS-based heuristic. Experimental results suggest that there are in fact strategies in industry that under specific system configurations may provide competitive solutions compared to the benchmark heuristic on large problem instances (e.g. 200 stores, 1000 products, and 28 days). Several managerial insights are derived to compare such distinct warehouse strategies and the corresponding impact on the network.
Journal: International Journal of Production Research
Pages: 6470-6484
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1249429
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1249429
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Template-Type: ReDIF-Article 1.0
Author-Name: Thomas Chabot
Author-X-Name-First: Thomas
Author-X-Name-Last: Chabot
Author-Name: Rahma Lahyani
Author-X-Name-First: Rahma
Author-X-Name-Last: Lahyani
Author-Name: Leandro C. Coelho
Author-X-Name-First: Leandro C.
Author-X-Name-Last: Coelho
Author-Name: Jacques Renaud
Author-X-Name-First: Jacques
Author-X-Name-Last: Renaud
Title: Order picking problems under weight, fragility and category constraints
Abstract: 
 Warehouse order picking activities are among the ones that impact the most the bottom lines of warehouses. They are known to often account for more than half of the total warehousing costs. New practices and innovations generate new challenges for managers and open new research avenues. Many practical constraints arising in real-life have often been neglected in the scientific literature. We introduce, model and solve a rich order picking problem under weight, fragility and category constraints, motivated by our observation of a real-life application arising in the grocery retail industry. This difficult warehousing problem combines complex picking and routing decisions under the objective of minimising the distance travelled. We first provide a full description of the warehouse design which enables us to algebraically compute the distances between all pairs of products. We then propose two distinct mathematical models to formulate the problem. We develop five heuristic methods, including extensions of the classical largest gap, mid-point, S-shape and combined heuristics. The fifth one is an implementation of the powerful adaptive large neighbourhood search algorithm specifically designed for the problem at hand. We then implement a branch-and-cut algorithm and cutting planes to solve the two formulations. The performance of the proposed solution methods is assessed on a newly generated and realistic test bed containing up to 100 pickups and 7 aisles. We compare the bounds provided by the two formulations. Our in-depth analysis shows which formulation tends to perform better. Extensive computational experiments confirm the efficiency of the ALNS metaheuristic and derive some important insights for managing order picking in this kind of warehouses.
Journal: International Journal of Production Research
Pages: 6361-6379
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1251625
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1251625
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Template-Type: ReDIF-Article 1.0
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: Ralf M. Elbert
Author-X-Name-First: Ralf M.
Author-X-Name-Last: Elbert
Author-Name: Torsten Franzke
Author-X-Name-First: Torsten
Author-X-Name-Last: Franzke
Title: Maverick picking: the impact of modifications in work schedules on manual order picking processes
Abstract: 
 Order picking, the process of retrieving items from their storage locations to fulfil customer orders, ranks among the most labour- and time-intensive processes in warehousing. Prior research in this area had a strong focus on the development of operating policies that increase the efficiency of manual order picking, for example by calculating optimal routes for the order pickers or by assigning products to storage locations. One aspect that poses a major challenge to many warehouse managers in practice has, curiously enough, remained largely unexplored by academic research: modifications in workflows (i.e. workplace deviance in a positive or negative sense) in order picking, which we define as ‘maverick picking’. The purpose of this paper is to characterise maverick picking and to study its causes, its forms of appearance and its potential impact on order picking performance. To gain insights into maverick picking, we first survey the literature to illustrate the state-of-knowledge of maverick picking. Subsequently, we report the results of a multi-case study on maverick picking and deduct a related content framework. The results of our case study support the proposition that maverick picking is highly relevant in practice and that it is a major determinant of order picking performance.
Journal: International Journal of Production Research
Pages: 6344-6360
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1252862
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1252862
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Template-Type: ReDIF-Article 1.0
Author-Name: Amir Hossein Gharehgozli
Author-X-Name-First: Amir Hossein
Author-X-Name-Last: Gharehgozli
Author-Name: René de Koster
Author-X-Name-First: René
Author-X-Name-Last: de Koster
Author-Name: Rick Jansen
Author-X-Name-First: Rick
Author-X-Name-Last: Jansen
Title: Collaborative solutions for inter terminal transport
Abstract: 
 Major ports contain multiple container terminals, sea terminals, train, truck and barge terminal, and empty container depots, operated by different companies. Port authorities try to streamline inter terminal container transport (ITT) within congested port areas by offering expensive common road and rail infrastructure. Alternatively, individual stakeholders can set up private or collaborative container transport systems. This paper develops a framework to analyse and determine feasibility conditions of a common ITT system in a port area, depending on total transport volumes. First, we develop a simulation model to evaluate the costs of transporting containers using different modes of transport including trucks, automated guided vehicles, and multi trailer systems. Next, the required number of vehicles per mode is determined for a given throughput and waiting time. The results of the simulation are used in a game-theoretic setting to determine the cost savings per stakeholder operating in a coalition. By comparing cost savings for all possible coalitions, it is possible to determine, for each stakeholder, the attractiveness of using a common system. We find the coalitions that result in the highest savings and compare them with the infrastructure cost required to realise them. We apply the method to determine the feasibility of a common ITT system for terminals in the Port of Rotterdam and show that it only pays off in case of high demand for container transports.
Journal: International Journal of Production Research
Pages: 6527-6546
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1262564
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1262564
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Template-Type: ReDIF-Article 1.0
Author-Name: Yingying Wu
Author-X-Name-First: Yingying
Author-X-Name-Last: Wu
Author-Name: Chen Zhou
Author-X-Name-First: Chen
Author-X-Name-Last: Zhou
Author-Name: Yaohua Wu
Author-X-Name-First: Yaohua
Author-X-Name-Last: Wu
Author-Name: Xiang T. R. Kong
Author-X-Name-First: Xiang T. R.
Author-X-Name-Last: Kong
Title: Zone merge sequencing in an automated order picking system
Abstract: 
 This paper considers the zone automated order fulfilment systems with a number of zones linked by a main conveyor. Each zone has a number of dispensers and a buffer. Each dispenser holds one type of item and dispenses the items for an order into a buffer before the items are merged to the main conveyor. Due to variability of the mix of item types and number of items for each type in successive orders, idle time or open space on the conveyor can occur if the buffers merge the items to the conveyor sequentially. The idle time prolongs the order fulfilment duration. This paper aims to provide a solution to reduce the idle time or open space by optimising the merging sequences among zones. A model is developed to find merging sequences with minimum order fulfilment time. However, the model is strongly NP-hard. A greedy heuristic-based solution approach is thus developed. Experiment performance shows that the presented solution can reduce the order fulfilment time approximately 5% with both empirical data and simulation data. Moreover, the sensitivity analysis is conducted to measure the effect of the solution under the variation of zone numbers and order structures. Although the idle time reduction can be achieved with any number of zones and order structures, it was most significant in certain range of zone numbers and appropriate order structures.
Journal: International Journal of Production Research
Pages: 6500-6515
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2016.1264641
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1264641
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Template-Type: ReDIF-Article 1.0
Author-Name: Masoud Mirzaei
Author-X-Name-First: Masoud
Author-X-Name-Last: Mirzaei
Author-Name: René B.M. De Koster
Author-X-Name-First: René B.M.
Author-X-Name-Last: De Koster
Author-Name: Nima Zaerpour
Author-X-Name-First: Nima
Author-X-Name-Last: Zaerpour
Title: Modelling load retrievals in puzzle-based storage systems
Abstract: 
 Puzzle-based storage systems are a new type of automated storage systems that allow storage of unit loads (e.g. cars, pallets, boxes) in a rack on a very small footprint with individual accessibility of all loads. They resemble the famous 15-sliding tile puzzle. Current models for such systems study retrieving loads one at a time. However, much time can be saved by considering multiple retrieval loads simultaneously. We develop an optimal method to do this for two loads and heuristics for three or more loads. Optimal retrieval paths are constructed for multiple load retrieval, which consists of moving multiple loads first to an intermediary ‘joining location’. We find that, compared to individual retrieval, optimal dual load retrieval saves on average 17% move time, and savings from the heuristic is almost the same. For three loads, savings are 23% on average. A limitation of our method is that it is valid only for systems with a very high space utilisation, i.e. only one empty location is available. Future research should investigate retrieving multiple loads for systems with multiple empty slots.
Journal: International Journal of Production Research
Pages: 6423-6435
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1304660
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1304660
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Template-Type: ReDIF-Article 1.0
Author-Name: Rong Chen
Author-X-Name-First: Rong
Author-X-Name-Last: Chen
Author-Name: Changyong Liang
Author-X-Name-First: Changyong
Author-X-Name-Last: Liang
Author-Name: Dongxiao Gu
Author-X-Name-First: Dongxiao
Author-X-Name-Last: Gu
Author-Name: Joseph Y-T. Leung
Author-X-Name-First: Joseph Y-T.
Author-X-Name-Last: Leung
Title: A multi-objective model for multi-project scheduling and multi-skilled staff assignment for IT product development considering competency evolution
Abstract: 
 We address a multi-skill project scheduling problem for IT product development in this article. The goal is for product development managers to be able to generate an initial schedule at an early stage of development activities. Due to the complexity of the product structure and functionality, an IT product development effort is divided into multiple projects. Each project includes several tasks, and each task must be completed by an employee who has mastered a certain skill to complete it. A pool of multi-skilled employees is available, and the employees’ skill efficiencies are influenced by both learning and forgetting phenomena. Based on the real-world demands of product development managers, three objectives are simultaneously considered: skill efficiency gain, product development cycle time and costs. To solve this problem, we propose a multi-objective non-linear mixed integer programming model. The Non-dominated Sorting Genetic Algorithm II (NSGA-II)is designed to generate an approximation to the optimal Pareto front of this NP-hard multi-objective optimisation problem. The algorithm produces feasible schedules for all the development projects using the serial schedule generation scheme. We adopt penalty values and individual employee adjustments to address resource conflicts and constraint violations. A weighted ideal point method is used to select the final solution from the approximate Pareto solution set. An application case of a new electrical energy saving product implementation in a leading electrical device company in China is used to illustrate the proposed model and algorithm.
Journal: International Journal of Production Research
Pages: 6207-6234
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1326641
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1326641
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Template-Type: ReDIF-Article 1.0
Author-Name: Yassine Qamsane
Author-X-Name-First: Yassine
Author-X-Name-Last: Qamsane
Author-Name: Abdelouahed Tajer
Author-X-Name-First: Abdelouahed
Author-X-Name-Last: Tajer
Author-Name: Alexandre Philippot
Author-X-Name-First: Alexandre
Author-X-Name-Last: Philippot
Title: Towards an approach of synthesis, validation and implementation of distributed control for AMS by using events ordering relations
Abstract: 
 We study distributed control synthesis and validation for automated manufacturing systems (AMS) in the framework of supervisory control theory. To reduce the size of the control problem, we view an AMS as comprised of asynchronous subsystems which are coupled through imposed logical Boolean specifications. The principle of the distributed control approach is the decomposition of the global monolithic control action into local coordinated control strategies for the individual subsystems. Owing to its importance in a distributed scheme, the order in which events occur arouses interest. By extending our previous results, we develop a set of rules of events precedence ordering, under which the control strategy via decomposition promises the subsystems synchronisation and coordination. We show how these rules contribute to reduce the size of the controller models used in the verification/validation and implementation steps. The effectiveness of the proposed approach is demonstrated by means of an industrial AMS example.
Journal: International Journal of Production Research
Pages: 6235-6253
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1333648
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1333648
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Template-Type: ReDIF-Article 1.0
Author-Name: Nicholas M. Putman
Author-X-Name-First: Nicholas M.
Author-X-Name-Last: Putman
Author-Name: Francisco Maturana
Author-X-Name-First: Francisco
Author-X-Name-Last: Maturana
Author-Name: Kira Barton
Author-X-Name-First: Kira
Author-X-Name-Last: Barton
Author-Name: Dawn M. Tilbury
Author-X-Name-First: Dawn M.
Author-X-Name-Last: Tilbury
Title: Virtual fusion: a hybrid environment for improved commissioning in manufacturing systems
Abstract: 
 Efficiency and quality are major factors contributing to profits in manufacturing systems. Production downtime occurs during commissioning of a new system, adoption of new processes, system faults, or (un)planned maintenance; all of which result in reduced production and profit loss. Current techniques for evaluating change to a manufacturing system rely on simulation and modeling to verify processes, but ignore the physical interactions of the work parts on the system. Implementation techniques to evaluate commissioning focus on identifying issues with the cyber interfaces, ignoring the physical interfaces. To validate the cyber and physical interfaces simultaneously, physical work are sent through the system, resulting in significant costs from scrapped work parts and loss of production time. This research proposes a virtual fusion environment where the physical interfaces between a virtual work part and a manufacturing system can be investigated in real-time, on the physical system, without the expenses associated with physical work parts. The virtual environment includes a virtual fusion filter to monitor discrepancies between the physical and virtual systems, and generate a hybrid virtual-physical input signal to the system level controller for virtualisation of a work part onto a physical system. Experimental demonstrations validate the feasibility of the proposed approach.
Journal: International Journal of Production Research
Pages: 6254-6265
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1334974
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1334974
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Template-Type: ReDIF-Article 1.0
Author-Name: Saeedeh Anvari
Author-X-Name-First: Saeedeh
Author-X-Name-Last: Anvari
Author-Name: Metin Turkay
Author-X-Name-First: Metin
Author-X-Name-Last: Turkay
Title: The facility location problem from the perspective of triple bottom line accounting of sustainability
Abstract: 
 Design of facilities network, allocation of customers to be served from the facilities and their operations have strong economic, environmental and social impacts. Although the decisions in the facility location problem may have varying effects on these impacts, simultaneous consideration of these effects in the early stages of decision-making for facility location selection and network plan has attracted limited attention in the facility location decision literature. Specifically, the social dimension and mathematical modelling are rarely used. In this paper, we present a decision support framework for the facility location problem that incorporates the triple bottom line accounting of sustainability. The framework is a valuable integration of mathematical modelling embedding the criteria with proper measurement indicators in a multi-objective model, perspectives of the related stakeholders, any thresholds and assumption, model analysis, and the decision-maker strategy to find the best-fit alternative. We demonstrate our methodological approach to establish a supply network for digital products in Turkey using real data. The results indicate that the method can balance the economic, environmental and social pillars, based on limitations of the three pillars and strategic perspective of the decision-maker. The decision-maker can interpret the interactions among the three pillars of sustainability and can make his decision by analysing the balance between them.
Journal: International Journal of Production Research
Pages: 6266-6287
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1341064
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1341064
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Template-Type: ReDIF-Article 1.0
Author-Name: Raphael Kramer
Author-X-Name-First: Raphael
Author-X-Name-Last: Kramer
Author-Name: Mauro Dell’Amico
Author-X-Name-First: Mauro
Author-X-Name-Last: Dell’Amico
Author-Name: Manuel Iori
Author-X-Name-First: Manuel
Author-X-Name-Last: Iori
Title: A batching-move iterated local search algorithm for the bin packing problem with generalized precedence constraints
Abstract: 
 In this paper, we propose a generalisation of the bin packing problem, obtained by adding precedences between items that can assume heterogeneous non-negative integer values. Such generalisation also models the well-known Simple Assembly Line Balancing Problem of type I. To solve the problem, we propose a simple and effective iterated local search algorithm that integrates in an innovative way of constructive procedures and neighbourhood structures to guide the search to local optimal solutions. Moreover, we apply some preprocessing procedures and adapt classical lower bounds from the literature. Extensive computational experiments on benchmark instances suggest that the developed algorithm is able to generate good quality solutions in a reasonable computational time.
Journal: International Journal of Production Research
Pages: 6288-6304
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1341065
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1341065
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Template-Type: ReDIF-Article 1.0
Author-Name: Karim Aroui
Author-X-Name-First: Karim
Author-X-Name-Last: Aroui
Author-Name: Gülgün Alpan
Author-X-Name-First: Gülgün
Author-X-Name-Last: Alpan
Author-Name: Yannick Frein
Author-X-Name-First: Yannick
Author-X-Name-Last: Frein
Title: Minimising work overload in mixed-model assembly lines with different types of operators: a case study from the truck industry
Abstract: 
 This paper considers the problem of sequencing mixed-model assembly lines (MMALs). Our goal is to determine the sequence of products to minimise work overload. This problem is known as the MMAL sequencing problem with work overload minimisation: we explicitly use task operation times to find the product sequence. This paper is based on an industrial case study of a truck assembly line. In this industrial context, as a reaction to work overloads, operators at the workstations finish their tasks before the product reaches the next workstation, but at the expense of fatigue. Furthermore, there are different types of operators, each with different task responsibilities. The originality of this work is to model this new way of reacting against work overloads, to integrate three operator types in the sequencing model and to apply the developed methods in a real industrial context. To solve this problem, we propose three meta-heuristic procedures: genetic algorithm, simulated annealing and a combination of these two meta-heuristics. All the methods proposed are tested on industrial data and compared to the solutions obtained using a mixed-integer linear programme. The results show that the proposed methods considerably improve the results of the current procedure used in the case study.
Journal: International Journal of Production Research
Pages: 6305-6326
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1346313
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346313
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Template-Type: ReDIF-Article 1.0
Author-Name: René B. M. De Koster
Author-X-Name-First: René B. M.
Author-X-Name-Last: De Koster
Author-Name: Andrew L. Johnson
Author-X-Name-First: Andrew L.
Author-X-Name-Last: Johnson
Author-Name: Debjit Roy
Author-X-Name-First: Debjit
Author-X-Name-Last: Roy
Title: Warehouse design and management
Abstract: 
 Warehouse design and operations have undergone major changes over the past decades. In particular, with the onset of e-commerce, the complexity of warehouse operations has increased multi-fold with the storage of large SKU assortment in small quantities, volatile demand patterns and primarily single-line customer orders. They have grown in size due to consolidation, new and fast identification and communication technologies have found their way into the warehouse and process automation technologies have progressed improving speed and operational efficiencies. In line with these developments, this special issue pays attention to new technologies and methods and how they impact warehouse design and management.
Journal: International Journal of Production Research
Pages: 6327-6330
Issue: 21
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1371856
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1371856
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Template-Type: ReDIF-Article 1.0
Author-Name: Shlomo Karhi
Author-X-Name-First: Shlomo
Author-X-Name-Last: Karhi
Author-Name: Dvir Shabtay
Author-X-Name-First: Dvir
Author-X-Name-Last: Shabtay
Title: Single machine scheduling to minimise resource consumption cost with a bound on scheduling plus due date assignment penalties
Abstract: 
 We study a single-machine scheduling problem in a flexible framework, where both job processing times and due dates are decision variables to be determined by the scheduler. We consider the case where each of the job processing times is a convex decreasing function of the amount of non-renewable resource that is allocated to the corresponding processing operation. Moreover, we consider two of the more common due-date assignment methods. For each of the methods, our objective is to find a solution minimising the total resource consumption cost, given an upper bound on the value of the weighted number of tardy jobs plus due date assignment costs. Since the problem is known to be NP$ \mathcal NP $-hard, we focus on designing approximation algorithms.
Journal: International Journal of Production Research
Pages: 3080-3096
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1400708
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1400708
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3080-3096




Template-Type: ReDIF-Article 1.0
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Author-Name: Zhanguo Zhu
Author-X-Name-First: Zhanguo
Author-X-Name-Last: Zhu
Author-Name: Kan Fang
Author-X-Name-First: Kan
Author-X-Name-Last: Fang
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Scheduling on a two-machine permutation flow shop under time-of-use electricity tariffs
Abstract: 
 We consider a two-machine permutation flow shop scheduling problem to minimise the total electricity cost of processing jobs under time-of-use electricity tariffs. We formulate the problem as a mixed integer linear programming, then we design two heuristic algorithms based on Johnson’s rule and dynamic programming method, respectively. In particular, we show how to find an optimal schedule using dynamic programming when the processing sequence is fixed. In addition, we propose an iterated local search algorithm to solve the problem with problem-tailored procedures and move operators, and test the computational performance of these methods on randomly generated instances.
Journal: International Journal of Production Research
Pages: 3173-3187
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1401236
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401236
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Template-Type: ReDIF-Article 1.0
Author-Name: Shi Qiang Liu
Author-X-Name-First: Shi Qiang
Author-X-Name-Last: Liu
Author-Name: Erhan Kozan
Author-X-Name-First: Erhan
Author-X-Name-Last: Kozan
Author-Name: Mahmoud Masoud
Author-X-Name-First: Mahmoud
Author-X-Name-Last: Masoud
Author-Name: Yu Zhang
Author-X-Name-First: Yu
Author-X-Name-Last: Zhang
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Title: Job shop scheduling with a combination of four buffering constraints
Abstract: 
 In this paper, a new scheduling problem is investigated in order to optimise a more generalised Job Shop Scheduling system with a Combination of four Buffering constraints (i.e. no-wait, no-buffer, limited-buffer and infinite-buffer) called CBJSS. In practice, the CBJSS is significant in modelling and analysing many real-world scheduling systems in chemical, food, manufacturing, railway, health care and aviation industries. Critical problem properties are thoroughly analysed in terms of the Gantt charts. Based on these properties, an applicable mixed integer programming model is formulated and an efficient heuristic algorithm is developed. Computational experiments show that the proposed heuristic algorithm is satisfactory for solving the CBJSS in real time.
Journal: International Journal of Production Research
Pages: 3274-3293
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1401240
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401240
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3274-3293




Template-Type: ReDIF-Article 1.0
Author-Name: Guanghui Zhang
Author-X-Name-First: Guanghui
Author-X-Name-Last: Zhang
Author-Name: Keyi Xing
Author-X-Name-First: Keyi
Author-X-Name-Last: Xing
Author-Name: Feng Cao
Author-X-Name-First: Feng
Author-X-Name-Last: Cao
Title: Scheduling distributed flowshops with flexible assembly and set-up time to minimise makespan
Abstract: 
 The scheduling problems under distributed production or flexible assembly settings have achieved increasing attention in recent years. This paper considers scheduling the integration of these two environments and proposes an original distributed flowshop scheduling problem with flexible assembly and set-up time. Distributed production stage is deployed several homogeneous flowshop factories that process the jobs to be assembled into final products in the flexible assembly stage. The objective is to find a schedule, including a production subschedule for jobs and an assembly subschedule for products, to minimise the makespan. Such a scheduling problem involves four successive decisions: assigning jobs to production factories, sequencing jobs at every factory, designating an assembly machine for each product and sequencing products on each assembly machine. The computational model is first established, and then a constructive heuristic (TPHS) and two hybrid metaheuristics (HVNS and HPSO) are proposed. Numerical experiments have been carried out and results validate the algorithmic feasibility and effectiveness. TPHS can obtain reasonable solutions in a shorter time, while metaheuristics can report better solutions using more yet acceptable time. HPSO is statistically comparable yet less robust compared with HVNS for small-scale instances. For the large-scale case, HPSO outperforms HVNS on both effectiveness and robustness.
Journal: International Journal of Production Research
Pages: 3226-3244
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1401241
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401241
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3226-3244




Template-Type: ReDIF-Article 1.0
Author-Name: Ramon Companys
Author-X-Name-First: Ramon
Author-X-Name-Last: Companys
Author-Name: Imma Ribas
Author-X-Name-First: Imma
Author-X-Name-Last: Ribas
Title: A note on the paper ‘Demonstrating Johnson’s algorithm via resource constrained scheduling’
Abstract: 
 In this paper, we demonstrate that the relation between two jobs defined by min{ai, bj} ≤ min{bi, aj}, used in Johnson’s theorem, is not transitive. However, both the theorem and Johnson’s algorithm are correct.
Journal: International Journal of Production Research
Pages: 3097-3098
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1401242
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401242
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Template-Type: ReDIF-Article 1.0
Author-Name: Chin-Chia Wu
Author-X-Name-First: Chin-Chia
Author-X-Name-Last: Wu
Author-Name: Du-Juan Wang
Author-X-Name-First: Du-Juan
Author-X-Name-Last: Wang
Author-Name: Shuenn-Ren Cheng
Author-X-Name-First: Shuenn-Ren
Author-X-Name-Last: Cheng
Author-Name: I-Hong Chung
Author-X-Name-First: I-Hong
Author-X-Name-Last: Chung
Author-Name: Win-Chin Lin
Author-X-Name-First: Win-Chin
Author-X-Name-Last: Lin
Title: A two-stage three-machine assembly scheduling problem with a position-based learning effect
Abstract: 
 The two-stage assembly scheduling problem has attracted increasing research attention. In many such problems, job processing times are commonly assumed to be fixed. However, this assumption does not hold in many real production situations. In fact, processing times usually decrease steadily when the same task is performed repeatedly. Therefore, in this study, we investigated a two-stage assembly position-based learning scheduling problem with two machines in the first stage and an assembly machine in the second stage. The objective was to complete all jobs as soon as possible (or to minimise the makespan, implying that the system can perform better and efficient task planning with limited resources). Because this problem is NP-hard, we derived some dominance relations and a lower bound for the branch-and-bound method for finding the optimal solution. We also propose three heuristics, three versions of the simulated annealing (SA) algorithm, and three versions of cloud theory-based simulated annealing algorithm for determining near-optimal solutions. Finally, we report the performance levels of the proposed algorithms.
Journal: International Journal of Production Research
Pages: 3064-3079
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1401243
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401243
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Title: On the beat of the drum: improving the flow shop performance of the Drum–Buffer–Rope scheduling mechanism
Abstract: 
 One of the main elements of the theory of constraints is its Drum–Buffer–Rope (DBR) scheduling (or release) mechanism that controls the release of jobs to the system. Jobs are not released directly to the shop floor – they are withheld in a backlog and released in accordance with the output rate of the bottleneck (i.e. the drum). The sequence in which jobs are considered for release from the backlog is determined by the schedule of the drum, which also determines in which order jobs are processed or dispatched on the shop floor. In the DBR literature, the focus is on the urgency of jobs and the same procedure is used both for backlog sequencing and dispatching. In this study, we explore the potential of using different combinations of rules for sequencing and dispatching to improve DBR performance. Based on controlled simulation experiments in a pure and general flow shop we demonstrate that, although the original procedure works well in a pure flow shop, it becomes dysfunctional in a general flow shop where job routings vary. Performance can be significantly enhanced by switching from a focus on urgency to a focus on the shortest bottleneck processing time during periods of high load.
Journal: International Journal of Production Research
Pages: 3294-3305
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1401245
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401245
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3294-3305




Template-Type: ReDIF-Article 1.0
Author-Name: Yan Ge
Author-X-Name-First: Yan
Author-X-Name-Last: Ge
Author-Name: Aimin Wang
Author-X-Name-First: Aimin
Author-X-Name-Last: Wang
Title: Spatial scheduling strategy for irregular curved blocks based on the modified genetic ant colony algorithm (MGACA) in shipbuilding
Abstract: 
 This paper proposes a scheduling strategy for irregular curved blocks to address the complex spatiotemporal coupling scheduling problem related to the entered time, the entered sequence, the setting positions and the rotated angles for the curved blocks in a shipbuilding yard. The strategy presents a makespan-based curved blocks – classification and selection rule to fulfil the programming time for the entry of the curved blocks into the workplace and realises the suppression on the delay. Useless stepping search of curved blocks in occupied workplace is avoided by combining the lowest centre-of-gravity rule with the calculation method of the remained workplace proposed in this paper. A modified genetic ant colony algorithm was proposed, which apply the ease to premature characteristics of GA and the excellent local optimisation ability of ACO, to let and promote the algorithm falls into local optimum. Then the large-scale and full-range mutation will be implemented to make the algorithm jump out of the original local optimisation to search more local optimal solutions so that the global optimal solution can be achieved. Finally, a software system for algorithm verification was developed which conducts the comparative analysis of the algorithms and verifies the validity of the algorithm proposed.
Journal: International Journal of Production Research
Pages: 3099-3115
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1402135
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1402135
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3099-3115




Template-Type: ReDIF-Article 1.0
Author-Name: Yahui Zhang
Author-X-Name-First: Yahui
Author-X-Name-Last: Zhang
Author-Name: Xiaofeng Hu
Author-X-Name-First: Xiaofeng
Author-X-Name-Last: Hu
Author-Name: Chuanxun Wu
Author-X-Name-First: Chuanxun
Author-X-Name-Last: Wu
Title: A modified multi-objective genetic algorithm for two-sided assembly line re-balancing problem of a shovel loader
Abstract: 
 This article deals with a real-life multi-objective two-sided assembly line rebalancing problem (MTALRBP) with modifications of production demand, line’s structure and production process in a Chinese construction machinery manufacturing firm. The objectives are minimising the cycle time and rebalancing cost, considering some specific constraints associated with the inevitable wait time, such as novel cycle time, idle time and balanced constraints. A modified non-dominated sorting genetic algorithm II (MNSGA-II) is proposed to solve this problem. MNSGA-II employs some problem-specific designs for encoding and decoding, initial population, crossover operator, mutation operator and selection operator. The great performance of MNSGA-II is demonstrated from two aspects: one is through the comparison between the representative results and current situation in the production system in terms of some ALs’ performance evaluation index, the other is utilising the comparison between the proposed MNSGA-II and two versions of initial NSGA-II in terms of ratio, convergence and spread.
Journal: International Journal of Production Research
Pages: 3043-3063
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1402136
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1402136
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Template-Type: ReDIF-Article 1.0
Author-Name: Javad Seif
Author-X-Name-First: Javad
Author-X-Name-Last: Seif
Author-Name: Andrew Junfang Yu
Author-X-Name-First: Andrew Junfang
Author-X-Name-Last: Yu
Author-Name: Fahimeh Rahmanniyay
Author-X-Name-First: Fahimeh
Author-X-Name-Last: Rahmanniyay
Title: Modelling and optimization of a bi-objective flow shop scheduling with diverse maintenance requirements
Abstract: 
 In real-world problems, machines cannot continuously operate and have to stop for maintenance before they fail. Lack of maintenance can also affect the performance of machines in processing jobs. In this paper, a permutation flow shop scheduling problem with multiple age-based maintenance requirements is modelled as a novel mixed-integer linear program in which the objectives are conflicting. In modelling the problem, we assume that infrequent maintenance can prolong job processing times. One of the objectives is to minimise the total maintenance cost by planning as few maintenance activities as possible to only meet the minimum requirements, and the other objective tries to minimise the total tardiness by sequencing the jobs and planning the maintenance activities in such a way that the processing times are not prolonged and unnecessary maintenance times are avoided. Because of this conflict, an interactive fuzzy, bi-objective model is introduced. Application of the model is illustrated through a case study for operations and maintenance scheduling of heavy construction machinery. An effective and efficient solution methodology is developed based on the structure of the problem and tested against commercial solvers and a standard GA. Computational results have verified the efficiency of the proposed solution methodology and show that unlike the proposed method, a generic metaheuristic that does not consider the unique structure of the problem can become ineffective for real-world problem sizes.
Journal: International Journal of Production Research
Pages: 3204-3225
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1403660
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1403660
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Template-Type: ReDIF-Article 1.0
Author-Name: Murat Güngör
Author-X-Name-First: Murat
Author-X-Name-Last: Güngör
Author-Name: Ali Tamer Ünal
Author-X-Name-First: Ali Tamer
Author-X-Name-Last: Ünal
Author-Name: Z. Caner Taşkın
Author-X-Name-First: Z. Caner
Author-X-Name-Last: Taşkın
Title: A parallel machine lot-sizing and scheduling problem with a secondary resource and cumulative demand
Abstract: 
 We investigate a parallel machine multi-item lot-sizing and scheduling problem with a secondary resource, in which demands are given for the entire planning horizon rather than for every single period. All-or-nothing assumption of the discrete lot-sizing and scheduling problem is valid so that a machine is either idle or works at full capacity in a period. The objective is to minimise the number of setups and teardowns. We prove that the problem is NP-hard and present two equivalent formulations. We show some properties of the optimal objective value, give optimality conditions and suggest a heuristic algorithm. We discuss and formulate two possible extensions related to real-life applications. Finally, we carry out computational experiments to compare the two formulations, to determine the effect of our proposed modeling improvements on solution performance, and to test the quality of our heuristic.
Journal: International Journal of Production Research
Pages: 3344-3357
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1406675
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1406675
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3344-3357




Template-Type: ReDIF-Article 1.0
Author-Name: Shin Woong Sung
Author-X-Name-First: Shin Woong
Author-X-Name-Last: Sung
Author-Name: Young Jae Jang
Author-X-Name-First: Young Jae
Author-X-Name-Last: Jang
Title: Heuristic for the assort-packing and distribution problem in the fashion apparel industry
Abstract: 
 We model and derive an algorithm for the assort-packing and distribution problem (APDP) in the fashion apparel industry. Assort-packing is a common method used to reduce the distribution lead time between manufacturers and retailers, wherein different items are packed together in one box according to the retailers’ demands. Specifically, in the fashion industry, multiple box types are configured by varying the size distribution of the same apparel product. In this study, we propose an optimisation model to quantitatively solve the APDP with respect to how many box types should be configured, how to configure the size distribution in each box, and how many of each type of box should be sent to stores. In particular, the modelling and algorithm development focus on the size-assorted homogeneous-article configuration in the APDP, a widely used assort-packing method in the fashion industry. We show that the APDP is NP-hard, and propose a heuristic algorithm in which a pre-processing step significantly reduces the search space. Numerical studies of the industry scale are conducted and show that the algorithm outperforms the benchmarking algorithms.
Journal: International Journal of Production Research
Pages: 3116-3133
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1412525
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412525
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3116-3133




Template-Type: ReDIF-Article 1.0
Author-Name: Jiayi Liu
Author-X-Name-First: Jiayi
Author-X-Name-Last: Liu
Author-Name: Zude Zhou
Author-X-Name-First: Zude
Author-X-Name-Last: Zhou
Author-Name: Duc Truong Pham
Author-X-Name-First: Duc Truong
Author-X-Name-Last: Pham
Author-Name: Wenjun Xu
Author-X-Name-First: Wenjun
Author-X-Name-Last: Xu
Author-Name: Chunqian Ji
Author-X-Name-First: Chunqian
Author-X-Name-Last: Ji
Author-Name: Quan Liu
Author-X-Name-First: Quan
Author-X-Name-Last: Liu
Title: Robotic disassembly sequence planning using enhanced discrete bees algorithm in remanufacturing
Abstract: 
 Increasing attention is being paid to remanufacturing due to environmental protection and resource saving. Disassembly, as an essential step of remanufacturing, is always manually finished which is time-consuming while robotic disassembly can improve disassembly efficiency. Before the execution of disassembly, generating optimal disassembly sequence plays a vital role in improving disassembly efficiency. In this paper, to minimise the total disassembly time, an enhanced discrete Bees algorithm (EDBA) is proposed to solve robotic disassembly sequence planning (RDSP) problem. Firstly, the modified feasible solution generation (MFSG) method is used to build the disassembly model. After that, the evaluation criterions for RDSP are proposed to describe the total disassembly time of a disassembly sequence. Then, with the help of mutation operator, EDBA is proposed to determine the optimal disassembly sequence of RDSP. Finally, case studies based on two gear pumps are used to verify the effectiveness of the proposed method. The performance of EDBA is analysed under different parameters and compared with existing optimisation algorithms used in disassembly sequence planning (DSP). The result shows the proposed method is more suitable for robotic disassembly than the traditional method and EDBA generates better quality of solutions compared with the other optimisation algorithms.
Journal: International Journal of Production Research
Pages: 3134-3151
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1412527
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412527
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Template-Type: ReDIF-Article 1.0
Author-Name: Jobish Vallikavungal Devassia
Author-X-Name-First: Jobish
Author-X-Name-Last: Vallikavungal Devassia
Author-Name: M. Angélica Salazar-Aguilar
Author-X-Name-First: M. Angélica
Author-X-Name-Last: Salazar-Aguilar
Author-Name: Vincent Boyer
Author-X-Name-First: Vincent
Author-X-Name-Last: Boyer
Title: Flexible job-shop scheduling problem with resource recovery constraints
Abstract: 
 In this work, we introduce a Flexible Job-shop Scheduling Problem with Resource Recovery Constraints (FRRC). In the FRRC, besides the constraints of the classical Flexible Job-shop Scheduling Problem (FJSP), operations may require resources to be processed. The resources are available in batches and a recovery time is required between each batch. This problem is inspired by a real situation faced by a brewing company where different yeasts are available in a limited quantity and are recovered only once they have been completely used. The objective is to schedule the operations such that the makespan is minimised. A mathematical model and a metaheuristic based on a General Variable Neighborhood Search is proposed for the solution of the FRRC. Computational results over a large set of instances, adapted from the FJSP literature, are presented.
Journal: International Journal of Production Research
Pages: 3326-3343
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1420262
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1420262
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3326-3343




Template-Type: ReDIF-Article 1.0
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Author-Name: Jörgen Winkel
Author-X-Name-First: Jörgen
Author-X-Name-Last: Winkel
Author-Name: Gunnar Palmerud
Author-X-Name-First: Gunnar
Author-X-Name-Last: Palmerud
Author-Name: Mikael Forsman
Author-X-Name-First: Mikael
Author-X-Name-Last: Forsman
Title: Innovation and employee injury risk in automotive disassembly operations
Abstract: 
 Engineering innovations in car disassembly systems are studied for affects on system operators’ risk of repetitive strain injury (RSI). Objective instrumented measures of injury risk factors with synchronised video-based task analyses were used to examine changes in operators’ RSI risk during two cases of engineering innovation: (1) a shift in industrial model from traditional extracting saleable parts to line-based full material recovery, and (2) the prospective effects of a simulated ‘Lean’-inspired process improvement in the line system. Both cases of innovation showed significantly increased movement speeds and reduced muscular recovery opportunities, implying increased RSI risk. This case study reveals a mechanism by which innovation may increase RSI risks for operators. Managers responsible for engineering innovation should ensure their teams have the tools and mandate necessary to control injury hazards as part of the development and design process. These cases suggest how failure to manage RSI hazards in the innovation process may allow increases of injury risks that can compromise operational performance. This ‘innovation pitfall’ has implications for operator health and organisational sustainability. Alternative pathways are discussed.
Journal: International Journal of Production Research
Pages: 3188-3203
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2018.1432910
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1432910
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3188-3203




Template-Type: ReDIF-Article 1.0
Author-Name: Cong He
Author-X-Name-First: Cong
Author-X-Name-Last: He
Author-Name: Zailin Guan
Author-X-Name-First: Zailin
Author-X-Name-Last: Guan
Author-Name: Lei Yue
Author-X-Name-First: Lei
Author-X-Name-Last: Yue
Author-Name: Saif Ullah
Author-X-Name-First: Saif
Author-X-Name-Last: Ullah
Title: Set-partitioning-based heuristic for balancing and configuration of automated flexible machining line
Abstract: 
 Flexible machining lines are used in a wide range of industries due to their ability of reconfiguration to meet high variety of customer demands. A novel problem is proposed in the current research to consider automated flexible machining line (AFML) with automated machining using computer numerical control machines and automated auxiliary operations using robots. A mixed-integer programming model for the current novel problem is developed. Moreover, a novel method named set-partitioning-based heuristic (SPH) is proposed to solve this new flexible machining line balancing problem to minimise the cycle time of the line and the performance is compared with both exact algorithm and random search algorithm. A set of benchmark instances based on different size of problems against different system parameters is made. Furthermore, sensitivity analysis of the system parameter in AFML is performed to know, how the number of machines and processing time can influence the cycle time and the utilisation of AFML. Computational experiments are performed to show the performance of the proposed method SPH against other methods and the results indicate that SPH performs best among all test methods in terms of solution quality and computation on both the proposed benchmark instances.
Journal: International Journal of Production Research
Pages: 3152-3172
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2018.1436785
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1436785
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3152-3172




Template-Type: ReDIF-Article 1.0
Author-Name: Daniel Tonke
Author-X-Name-First: Daniel
Author-X-Name-Last: Tonke
Author-Name: Martin Grunow
Author-X-Name-First: Martin
Author-X-Name-Last: Grunow
Title: Maintenance, shutdown and production scheduling in semiconductor robotic cells
Abstract: 
 Our approach is the first to study simultaneous scheduling of preventive maintenance, shutdowns and production for robotic cells in semiconductor manufacturing. It hereby exploits the frequent periods of overcapacity in semiconductor manufacturing to reduce wear and tear. In contrast to existing approaches, our scheduling approach is able to deal with different preventive-maintenance types. We borrow the Resource Task Network representation from the process-industry domain to represent our problem and facilitate its formulation as a mathematical model. In addition, we develop efficiency-improving constraints based on the characteristics of the preventive-maintenance activities. In numerical tests based on industry data, we show that the model generates high-quality schedules even without applying the inequalities, although the optimality gap is reduced only when including inequalities. We furthermore assess the trade-off between shutdowns and batch lead times. We compare our model’s schedule quality to (i) the simple industry practice of shutting down chambers permanently to reduce wear and tear and (ii) an approach that schedules maintenance and production sequentially. The numerical tests yield the following managerial insights. First, integrating maintenance and production scheduling has substantial advantages. Second, the practice of shutting equipment down permanently diminishes scheduling flexibility and solution quality. Third, shutdowns scheduling must also consider the impact on batch waiting times.
Journal: International Journal of Production Research
Pages: 3306-3325
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2018.1444809
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1444809
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Template-Type: ReDIF-Article 1.0
Author-Name: Irina E. Utkina
Author-X-Name-First: Irina E.
Author-X-Name-Last: Utkina
Author-Name: Mikhail V. Batsyn
Author-X-Name-First: Mikhail V.
Author-X-Name-Last: Batsyn
Author-Name: Ekaterina K. Batsyna
Author-X-Name-First: Ekaterina K.
Author-X-Name-Last: Batsyna
Title: A branch-and-bound algorithm for the cell formation problem
Abstract: 
 The Cell Formation Problem (CFP) is an important optimisation problem in manufacturing. It has been introduced in the Group Technology (GT) and its goal is to group machines and parts processed on them into production cells minimising the movement of parts to other cells for processing and maximising for each cell the loading of its machines with operations on its parts. We consider one of the computationally hardest formulations of this problem – the CFP with a variable number of cells and the grouping efficacy objective, which is a fractional function. The CFP literature contains many heuristic algorithms, but only a small number of exact approaches especially for this formulation. In the current paper, we present an exact branch-and-bound algorithm for the same hard CFP formulation. To linearise the fractional objective function, we apply the Dinkelbach approach. We have been able to solve 24 of the 35 instances from the well known GT benchmark. For the remaining 11 instances, the difference in the grouping efficacy with the best known solutions is less than 2.6%.
Journal: International Journal of Production Research
Pages: 3262-3273
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2018.1444811
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1444811
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3262-3273




Template-Type: ReDIF-Article 1.0
Author-Name: Biao Yuan
Author-X-Name-First: Biao
Author-X-Name-Last: Yuan
Author-Name: Ran Liu
Author-X-Name-First: Ran
Author-X-Name-Last: Liu
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Daily scheduling of caregivers with stochastic times
Abstract: 
 This paper addresses a daily caregiver scheduling and routing problem arising in home health care or home care service providers. The problem is quite challenging due to its uncertainties in terms of travel and service times derived from changes in road traffic conditions and customer health status in practice. We first model the problem as a stochastic programme with recourse, where the recourse action is to skip customers without services if the caregiver arrives later than their latest starting service time (i.e. hard time window requirements). Then, we formulate the problem as a set partitioning model and solve it with a branch-and-price (B&amp;P) algorithm. Specifically, we devise an effective discrete approximation method to calculate the arrival time distribution of caregivers, incorporate it into a problem-specific label algorithm, and use a removal-and-insertion-based heuristic and the decremental state-space relaxation technique to accelerate the pricing process. Finally, we conduct numerical experiments on randomly generated instances to validate the effectiveness of the discrete approximation method and the proposed B&amp;P algorithm.
Journal: International Journal of Production Research
Pages: 3245-3261
Issue: 9
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2018.1445879
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1445879
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:9:p:3245-3261




Template-Type: ReDIF-Article 1.0
Author-Name: Maria Jubiz-Diaz
Author-X-Name-First: Maria
Author-X-Name-Last: Jubiz-Diaz
Author-Name: Alcides Santander-Mercado
Author-X-Name-First: Alcides
Author-X-Name-Last: Santander-Mercado
Author-Name: John E. Candelo-Becerra
Author-X-Name-First: John E.
Author-X-Name-Last: Candelo-Becerra
Title: A multi-item multi-packaging model to minimise cost of lost units, unpacking cost and CO2 emissions
Abstract: 
 This paper presents two multi-objective models that integrate packaging size and production scheduling problems for a flexible flow shop system. The main objective is to find the packaging size of finished product per item and the production schedule that would minimise cost of lost units, unpacking cost, inventory cost, earliness/tardiness penalties and kilograms of carbon dioxide emitted by resources operation. Since the complexity of the proposed models, a Pareto-based hybrid genetic algorithm (HGA) is also developed. A case study was developed to analyse the performance of both models using different instances. Numerical results indicate that the outperformance of one model over the other depends on the demand and the packaging size.
Journal: International Journal of Production Research
Pages: 6246-6263
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566650
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566650
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Template-Type: ReDIF-Article 1.0
Author-Name: Finbarr Murphy
Author-X-Name-First: Finbarr
Author-X-Name-Last: Murphy
Author-Name: Fabian Pütz
Author-X-Name-First: Fabian
Author-X-Name-Last: Pütz
Author-Name: Martin Mullins
Author-X-Name-First: Martin
Author-X-Name-Last: Mullins
Author-Name: Torsten Rohlfs
Author-X-Name-First: Torsten
Author-X-Name-Last: Rohlfs
Author-Name: Dennis Wrana
Author-X-Name-First: Dennis
Author-X-Name-Last: Wrana
Author-Name: Michael Biermann
Author-X-Name-First: Michael
Author-X-Name-Last: Biermann
Title: The impact of autonomous vehicle technologies on product recall risk
Abstract: 
 Complex Advanced Driving Assistance Systems (ADAS) and Autonomous Vehicle (AV) technology are increasing the number of vehicle recalls. At the same time, financial risks resulting from extensive product recall events can severely affect vehicle manufacturers and their suppliers, exposing the automotive supply chain to business continuity, legal and reputational risk. However, these risk implications are under-appreciated by large segments of the supply chain. This study shows that product recall events are increasing in general but recall events associated with ADAS/AV technology form an increasingly large percentage of these recall events. Based on this analysis, we describe ADAS/AV-specific aspects of risk mitigation and present a multidimensional approach, combining production-centric risk mitigation avenues in the automotive supply chain with the transfer of residual financial risks via insurance. We find that this comprehensive risk mitigation approach benefits in higher transparency of total production costs and increased resilience of the automotive supply chain. Against the background of an increasing product recall risk resulting from the increasing automation and interconnectedness of modern vehicles, we therefore suggest a closer, more strategic cooperation between insurance companies, car manufacturers and automotive suppliers for the benefit of all parties.
Journal: International Journal of Production Research
Pages: 6264-6277
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566651
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566651
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Template-Type: ReDIF-Article 1.0
Author-Name: Guofang Nan
Author-X-Name-First: Guofang
Author-X-Name-Last: Nan
Author-Name: Zan Zhang
Author-X-Name-First: Zan
Author-X-Name-Last: Zhang
Author-Name: Minqiang Li
Author-X-Name-First: Minqiang
Author-X-Name-Last: Li
Title: Optimal pricing for cloud service providers in a competitive setting
Abstract: 
 Cloud services are transforming business and government at an ever-increasing rate. As a form of cloud service, software as a service (SaaS) is one of the fast growing segments of the information technology and has become an attractive alternative to the on-premises software. In this paper, we study the optimal pricing strategies of a cloud service provider in an incumbent-entrant setting under user upgrade cost and switching cost. Our results show that in equilibrium the market structure is not unique. The specific market segmentation depends on the incumbent’s pricing strategy whether to provide discounted price to its old customers and the levels of user upgrade cost and switching cost. When faced with customers who are heterogeneous in the sensitivity to the related costs, the incumbent firm may need to offer a discount to the new customers rather than to those who have purchased from it. This implies that the entry of a SaaS firm into the market is a potential threat to the incumbent on-premises software firm, especially in capturing new customers from the untapped market.
Journal: International Journal of Production Research
Pages: 6278-6291
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566655
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566655
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianjun Wang
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wang
Author-Name: Yizhong Ma
Author-X-Name-First: Yizhong
Author-X-Name-Last: Ma
Author-Name: Fugee Tsung
Author-X-Name-First: Fugee
Author-X-Name-Last: Tsung
Author-Name: Gang Chang
Author-X-Name-First: Gang
Author-X-Name-Last: Chang
Author-Name: Yiliu Tu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Tu
Title: Economic parameter design for ultra-fast laser micro-drilling process
Abstract: 
 The basic requirement in this type of micro-drilling process is to achieve high product quality with the minimum machining cost, which can be realised through parameter design. In this paper, we propose a new economic parameter design under the framework of Bayesian modelling and optimisation. First of all, the Bayesian seemingly unrelated regression (SUR) models are utilised to develop the relationship models between input factors and output responses in the laser micro-drilling process. After that, simulated response values which reflect the real laser micro-drilling process are obtained by using the Gibbs sampling procedure. Moreover, a novel rejection cost function and a quality loss function are constructed based on the simulated responses. Finally, an optimisation scheme integrating the rejection cost (i.e. rework cost and scrap cost) function and the quality loss function is implemented by using multi-objective genetic algorithm to find feasible economic parameter settings for laser micro-drilling process.
Journal: International Journal of Production Research
Pages: 6292-6314
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566660
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566660
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Template-Type: ReDIF-Article 1.0
Author-Name: Kai Ding
Author-X-Name-First: Kai
Author-X-Name-Last: Ding
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: Xudong Zhang
Author-X-Name-First: Xudong
Author-X-Name-Last: Zhang
Author-Name: Guanghui Zhou
Author-X-Name-First: Guanghui
Author-X-Name-Last: Zhou
Author-Name: Fuqiang Zhang
Author-X-Name-First: Fuqiang
Author-X-Name-Last: Zhang
Title: Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors
Abstract: 
 Smart manufacturing is the core idea of the fourth industrial evolution. For a smart manufacturing shop floor, real-time monitoring, simulation and prediction of manufacturing operations are vital to improve the production efficiency and flexibility. In this paper, the Cyber-Physical System (CPS) and Digital Twin technologies are introduced to build the interconnection and interoperability of a physical shop floor and corresponding cybershop floor. A Digital Twin-based Cyber-Physical Production System (DT-CPPS) is further established, and the configuring mechanism, operating mechanism and real-time data-driven operations control of DT-CPPS are discussed in detail. It is expected that DT-CPPS will provide the basis for shop floors to march towards smart manufacturing.
Journal: International Journal of Production Research
Pages: 6315-6334
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566661
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566661
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuanzhu Zhan
Author-X-Name-First: Yuanzhu
Author-X-Name-Last: Zhan
Author-Name: Kim Hua Tan
Author-X-Name-First: Kim Hua
Author-X-Name-Last: Tan
Author-Name: Baofeng Huo
Author-X-Name-First: Baofeng
Author-X-Name-Last: Huo
Title: Bridging customer knowledge to innovative product development: a data mining approach
Abstract: 
 In the big data era, firms are inundated with customer data, which are valuable in improving services, developing new products, and identifying new markets. However, it is not clear how companies apply data-driven methods to facilitate customer knowledge management when developing innovative new products. Studies have investigated the specific benefits of applying data-driven methods in customer knowledge management, but failed to systematically investigate the specific mechanics of how firms realised these benefits. Accordingly, this study proposes a systematic approach to link customer knowledge with innovative product development in a data-driven environment. To mine customer needs, this study adopts the Apriori algorithm and C5.0 in addition to the association rule and decision tree methodologies for data mining. It provides a systematic and effective method for managers to extract knowledge ‘from’ and ‘about’ customers to identify their preferences, enabling firms to develop the right products and gain competitive advantages. The findings indicate that the knowledge-based approach is effective, and the knowledge extracted is shown as a set of rules that can be used to identify useful patterns for both innovative product development and marketing strategies.
Journal: International Journal of Production Research
Pages: 6335-6350
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566662
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Template-Type: ReDIF-Article 1.0
Author-Name: Chun-Ming Yang
Author-X-Name-First: Chun-Ming
Author-X-Name-Last: Yang
Author-Name: Kuen-Suan Chen
Author-X-Name-First: Kuen-Suan
Author-X-Name-Last: Chen
Title: Two-phase selection framework that considers production costs of suppliers and quality requirements of buyers
Abstract: 
 Buyers are faced with selecting the optimal supplier, while suppliers are left to consider production costs. In this study, we developed a two-phase selection framework that allows buyers to evaluate the performance of suppliers while taking production costs into account for value maximisation. This scheme is a win-win solution capable of promoting long-term relationships between buyers and suppliers. Under the assumption of normality, the first phase involves constructing a new Six Sigma quality capability analysis chart (SSQCAC) which takes production costs into account. The objective is to evaluate all potential suppliers using the 100 × (1–α)% upper confidence limit (UCL) of an integrated Six Sigma quality index (SSQI) QPIh when dealing with products with smaller-the-better (STB), larger-the-better (LTB), or nominal-the-best (NTB) quality characteristics. According to interval estimation theory, this method can have a significant impact on the consumption of resources; i.e. the production costs of the supplier can be decreased by reducing the production quality to below that required by the buyer. The proposed method also filters out unsuitable suppliers in order to simplify the decision problem and reduce computational demands and operational risks/costs without compromising the quality of the final product. In the second phase, a detailed analysis is conducted using Euclidean distance measure to select the optimal supplier from among the remaining candidates. We conducted a real-world case study to evaluate the efficacy of the proposed method. We also conducted comparisons with existing methods to demonstrate the advantages of the proposed method and its managerial implications. Suggestions for future study are also provided.
Journal: International Journal of Production Research
Pages: 6351-6368
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566663
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566663
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Template-Type: ReDIF-Article 1.0
Author-Name: Yang Yang
Author-X-Name-First: Yang
Author-X-Name-Last: Yang
Author-Name: Lujie Chen
Author-X-Name-First: Lujie
Author-X-Name-Last: Chen
Author-Name: Fu Jia
Author-X-Name-First: Fu
Author-X-Name-Last: Jia
Author-Name: Zhiduan Xu
Author-X-Name-First: Zhiduan
Author-X-Name-Last: Xu
Title: Complementarity of circular economy practices: an empirical analysis of Chinese manufacturers
Abstract: 
 In recent years, circular economy (CE) is receiving increasing attention worldwide and is intended to integrate economic activity and environmental wellbeing in a sustainable way. The CE mainly focuses on both the front (eco-design, ECO) and back ends (reverse activities, RA) of operations and production at the firm level. However, what is missing in the literature are the synergistic effects between the two practices on corporate social responsibility (CSR) performance. Drawing on systems theory, this paper used panel data of Chinese manufacturing firms over the period from 2013 to 2015 that was collected from Chinese Research Data Services Platform (CNRDS) and Rankins CSR Ratings (RKS) databases and performed a series of regression tests to see whether complementarity exists between them and their effects on CSR performance. The results show significant complementarity between ECO and RA in improving CSR performance. Furthermore, building on systems theory, three kinds of enablers are identified as essential for promoting the interaction of subsystems and the complementarity of ECO and RA, including CSR vision as an internal enabler within the system, an environmental management system as a system regulation, and supply chain cooperation as an external enabler from the environment.
Journal: International Journal of Production Research
Pages: 6369-6384
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566664
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566664
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:20:p:6369-6384




Template-Type: ReDIF-Article 1.0
Author-Name: Wen Jun Tan
Author-X-Name-First: Wen Jun
Author-X-Name-Last: Tan
Author-Name: Allan N. Zhang
Author-X-Name-First: Allan N.
Author-X-Name-Last: Zhang
Author-Name: Wentong Cai
Author-X-Name-First: Wentong
Author-X-Name-Last: Cai
Title: A graph-based model to measure structural redundancy for supply chain resilience
Abstract: 
 Globalisation and lean initiatives increase the vulnerabilities of the supply chains (SC), where disruptions in any plant in a supply chain network (SCN) can propagate throughout the whole SCN. Redundancy is part of the SC re-engineering to improve supply chain resilience (SCRES). This paper presents a conceptual model of an SCN using graph theory, considering the relationships between plants and materials. Based on the model, the structural redundancy of the SCN is measured, which is used to assess SCRES. This assessment approach focuses on the resilience of the SCN against disruptions. Case studies are discussed to illustrate the applicability of this model and show that increasing structural redundancy of the SCN improves SCRES against disruptions.
Journal: International Journal of Production Research
Pages: 6385-6404
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566666
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566666
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Template-Type: ReDIF-Article 1.0
Author-Name: S. Moons
Author-X-Name-First: S.
Author-X-Name-Last: Moons
Author-Name: K. Braekers
Author-X-Name-First: K.
Author-X-Name-Last: Braekers
Author-Name: K. Ramaekers
Author-X-Name-First: K.
Author-X-Name-Last: Ramaekers
Author-Name: A. Caris
Author-X-Name-First: A.
Author-X-Name-Last: Caris
Author-Name: Y. Arda
Author-X-Name-First: Y.
Author-X-Name-Last: Arda
Title: The value of integrating order picking and vehicle routing decisions in a B2C e-commerce environment
Abstract: 
 In B2C e-commerce sales, customers expect a fast and low-cost delivery. To be able to fulfil these customer expectations, both warehouse and distribution operations have to be performed in an efficient and effective way. Ideally, these two supply chain functions should be considered simultaneously in an integrated problem since they are interrelated. In this paper, a record-to-record travel algorithm is proposed to solve the integrated order picking-vehicle routing problem (I-OP-VRP). Experiments with both small-size and large-size instances are conducted. Furthermore, the integrated approach is compared with an approach in which both problems are solved sequentially. Results show that integration leads to increased service levels, i.e. it allows to shorten the time between placing an order and receiving the goods. On top, the integrated approach leads to costs savings of on average 1.8%. Thus, integration is indispensable for a fast and cost-efficient delivery of goods.
Journal: International Journal of Production Research
Pages: 6405-6423
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566668
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566668
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Template-Type: ReDIF-Article 1.0
Author-Name: Junyi Lin
Author-X-Name-First: Junyi
Author-X-Name-Last: Lin
Author-Name: Mohamed M. Naim
Author-X-Name-First: Mohamed M.
Author-X-Name-Last: Naim
Title: Why do nonlinearities matter? The repercussions of linear assumptions on the dynamic behaviour of assemble-to-order systems
Abstract: 
 The hybrid assembly-to-order (ATO) supply chain, combining make-to-stock and make-to-order (MTS-MTO) production, separated by a customer order decoupling point (CODP), is well recognised in many sectors. Based on the well-established Inventory and Order Based Production Control Systems (the IOBPCS family), we develop a hybrid ATO system dynamics model and analytically study the impact of nonlinearities on its dynamic performance. Nonlinearities play an important, sometimes even a dominant, role in influencing the dynamic performance of supply chain systems. However, most IOBPCS based analytical studies assume supply chain systems are completely linear and thereby greatly limit the applicability of published results, making it difficult to fully explain and describe oscillations caused by internal factors. We address this gap by analytically exploring the non-negative order and capacity constraint nonlinearities present in an ATO system. By adopting nonlinear control engineering and simulation approaches, we reveal that, depending on the mean and amplitude of the demand, the non-negative order and capacity constraints in the ATO system may occur and their significant impact on system dynamics performance should be carefully considered. Failing to monitor non-negative order constraints may underestimate the mean level of inventory and overestimate the inventory recovery speed. Sub-assemblers may suffer increased inventory cost (i.e. the consequence of varying inventory levels and recovery speed) if capacity and non-negative order constraints are not considered at their production site. Future research should consider the optimal trade-off design between CODP inventory and capacity and the exploration of delivery lead-time dynamics.
Journal: International Journal of Production Research
Pages: 6424-6451
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566669
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566669
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming-Chuan Chiu
Author-X-Name-First: Ming-Chuan
Author-X-Name-Last: Chiu
Author-Name: Chih-Yuan Chu
Author-X-Name-First: Chih-Yuan
Author-X-Name-Last: Chu
Author-Name: Tsai Chi Kuo
Author-X-Name-First: Tsai Chi
Author-X-Name-Last: Kuo
Title: Product service system transition method: building firm’s core competence of enterprise
Abstract: 
 Product service system (PSS), applicable in numerous fields, is an innovative business model integrating products, services, and supporting infrastructure. It has been known as a promising approach to realise sustainable development of both enterprises and environment. However, only a few studies were addressed to support the PSS transition of enterprises. Thus the aim of this study is to develop a PSS transition methodology, comprising a quantitative PSS classification framework and transformation procedures. In order to classify PSS typology, rough set theory is applied, and as a result, a set of classification rules is derived from the analysis of 40 contemporary PSS service providers based on their attributes and the decision rules. In addition, this study also proposes a PSS transformation process that considers firms’ core competencies and current PSS types. Moreover, the result also demonstrates the discovery of a new PSS type, platform-oriented PSS. The discovery and definition of this new type extend the current PSS typology. Finally, the proposed transition methodology is applied to an automotive company as a case study, illustrating the advantages and possibilities of this research.
Journal: International Journal of Production Research
Pages: 6452-6472
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566670
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566670
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:20:p:6452-6472




Template-Type: ReDIF-Article 1.0
Author-Name: Oladipupo Olaitan
Author-X-Name-First: Oladipupo
Author-X-Name-Last: Olaitan
Author-Name: Erlend Alfnes
Author-X-Name-First: Erlend
Author-X-Name-Last: Alfnes
Author-Name: Jørn Vatn
Author-X-Name-First: Jørn
Author-X-Name-Last: Vatn
Author-Name: Jan Ola Strandhagen
Author-X-Name-First: Jan Ola
Author-X-Name-Last: Strandhagen
Title: CONWIP implementation in a system with cross-trained teams
Abstract: 
 Although a significant amount of research exists on the implementation of the CONstant Work In Process (CONWIP) production control strategy in different types of manufacturing environments, the challenge posed by the complex flow of multiple products through the case manufacturing system of this work necessitates defining a unique type of item release rule to operate with the CONWIP control. The case system is a chair cover production line, which has sets of cross-trained teams that can process its different product models with different levels of efficiency. This work focusses on the CONWIP control strategy, but with the introduction of a new item release rule for prioritising items for release into the system. Results from simulation experiments show that operating CONWIP with an item release rule that is synchronised with the work rate of each of the system's cross-trained teams improves its performance. In comparison with a First in First out (FIFO) rule, this item release rule shortens the system throughput time. It also increases the chances of items being processed by the team most suitable for them, thereby minimising the quality and efficiency issues that might occur in systems that consist of teams with varying levels of proficiency for processing the different product models. Irrespective of the item release rule that is applied, CONWIP achieves a better distribution of workload amongst the teams than a Push control achieves.
Journal: International Journal of Production Research
Pages: 6473-6486
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566671
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566671
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:20:p:6473-6486




Template-Type: ReDIF-Article 1.0
Author-Name: Murat Şahin
Author-X-Name-First: Murat
Author-X-Name-Last: Şahin
Author-Name: Talip Kellegöz
Author-X-Name-First: Talip
Author-X-Name-Last: Kellegöz
Title: Balancing Multi-Manned Assembly Lines With Walking Workers: Problem Definition, Mathematical Formulation, and an Electromagnetic Field Optimisation Algorithm
Abstract: 
 Assembly lines are widely used in industrial environments that produce standardised products in high volumes. Multi-manned assembly line is a special version of them that allows simultaneous operation of more than one worker at the same workstation. These lines are widely used in large-sized product manufacturing since they have many advantages over the simple one. This article has dealt with multi-manned assembly line balancing problem with walking workers for minimising the number of workers and workstations as the first and second objectives, respectively. A linear mixed-integer programming formulation of the problem has been firstly addressed after the problem definition is given. Besides that, a metaheuristic based on electromagnetic field optimisation algorithm has been improved. In addition to the classical electromagnetic field optimisation algorithm, a regeneration strategy has been applied to enhance diversification. A particle swarm optimisation algorithm from assembly line balancing literature has been modified to compare with the proposed algorithm. A group of test instances from many precedence diagrams were generated for evaluating the performances of all solution methods. Deviations from lower bound values of the number of workers/workstations and the number of optimal solutions obtained by these methods are concerned as performance criteria. The results obtained by the proposed programming formulations have been also compared with the solutions obtained by the traditional mathematical model of the multi-manned assembly line. Through the experimental results, the performance of the metaheuristic has been found very satisfactory according to the number of obtained optimal solutions and deviations from lower bound values.
Journal: International Journal of Production Research
Pages: 6487-6505
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566672
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566672
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Template-Type: ReDIF-Article 1.0
Author-Name: Chao Guan
Author-X-Name-First: Chao
Author-X-Name-Last: Guan
Author-Name: Zeqiang Zhang
Author-X-Name-First: Zeqiang
Author-X-Name-Last: Zhang
Author-Name: Yunpeng Li
Author-X-Name-First: Yunpeng
Author-X-Name-Last: Li
Title: A flower pollination algorithm for the double-floor corridor allocation problem
Abstract: 
 This research explores the double-floor corridor allocation problem (DFCAP), which deals with the optimal arrangement of departments over two floors and then place them along both sides against a corridor. This problem is a natural extension of the corridor allocation problem (CAP) to additional floors; the layout of each floor can be regarded as an approximately independent CAP. The DFCAP is commonly observed in manufacturing and service buildings. In this study, a mixed-integer programming formulation for the DFCAP is developed, and it is able to reduce to the classical CAP model. Then a novel flower pollination algorithm is provided, which is discretised using swap pair set approach to solve the considered DFCAP. In addition, to ameliorate the algorithm, three constructive heuristic rules are developed to produce a reasonably good initial population; meanwhile, a variable neighbourhood search structure is presented to prevent prematurity in arrival at a poor local solution. Finally, several instances for the DFCAP with a size of 9 ≤ n ≤ 80 are employed in the algorithms, as well as in mixed-integer non-linear programming (MINLP) formulations, which are solved with GUROBI 7.0.1. Moreover, the above-mentioned instances are utilized to show that the proposed algorithm performs better in comparison to the state-of-the-art optimization algorithms.
Journal: International Journal of Production Research
Pages: 6506-6527
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566673
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566673
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Template-Type: ReDIF-Article 1.0
Author-Name: K.H. Leung
Author-X-Name-First: K.H.
Author-X-Name-Last: Leung
Author-Name: C.C. Luk
Author-X-Name-First: C.C.
Author-X-Name-Last: Luk
Author-Name: K.L. Choy
Author-X-Name-First: K.L.
Author-X-Name-Last: Choy
Author-Name: H.Y. Lam
Author-X-Name-First: H.Y.
Author-X-Name-Last: Lam
Author-Name: Carman K.M. Lee
Author-X-Name-First: Carman K.M.
Author-X-Name-Last: Lee
Title: A B2B flexible pricing decision support system for managing the request for quotation process under e-commerce business environment
Abstract: 
 In the era of digitalisation, e-commerce retail sites have become decisive channels for reaching millions of potential customers worldwide. Digital marketing strategies are formulated by the marketing teams in order to increase the traffic on their e-commerce sites, thereby boosting the sales of the products. With the massive amount of data available from the cloud, which were conventionally made with a high degree of intuition based on decision makers’ knowledge and experience, can now be supported with the application of artificial intelligence techniques. This paper introduces a novel approach in applying the fuzzy association rule mining approach and the fuzzy logic technique, for discovering the factors influencing the pricing decision of products launched in e-commerce retail site, and in formulating flexible, dynamic pricing strategies for each product launched in an e-commerce site. A pricing decision support system for B2B e-commerce retail businesses, namely Smart-Quo, is developed and implemented in a Hong Kong-based B2B e-commerce retail company. A six-month pilot run reveals a significant improvement in terms of the efficiency and effectiveness in making pricing decisions on each product. The case study demonstrates the feasibility and potential benefits of applying artificial intelligence techniques in marketing management in today’s digital age.
Journal: International Journal of Production Research
Pages: 6528-6551
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1566674
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566674
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Template-Type: ReDIF-Article 1.0
Author-Name: Henokh Yernias Fibrianto
Author-X-Name-First: Henokh Yernias
Author-X-Name-Last: Fibrianto
Author-Name: Soondo Hong
Author-X-Name-First: Soondo
Author-X-Name-Last: Hong
Title: Dynamic order batching in bucket brigade order picking systems with consecutive batch windows and non-identical pickers
Abstract: 
 The blocking mitigation mechanism contained in a batching and sequencing model improves order picking performance in bucket brigade order picking systems by adjusting the batch formation in a given batch window. The batch formation of a given batch window affects the transition to the next batch window and limits the batch formation’s structure in the next window. In addition, imbalance in picker capability increases the variation of batch formation while mitigating blocking delay. Our paper proposes a dynamic indexed batching model to smooth the transition between consecutive batch windows and give a better approximation of non-identical pickers’ capability. We develop a mixed integer programming solution for a dynamic indexed batching model in a bucket brigade order picking system (DIBMB). Simulation experiments show that the DIBMB smooths the transition between batch windows as measured in the delay experienced by the first batch in each batch window. Comparisons to the available batching models show that under DIBMB, the blocking delay gradually increases throughout the sequence of batches.
Journal: International Journal of Production Research
Pages: 6552-6568
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1567948
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1567948
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Template-Type: ReDIF-Article 1.0
Author-Name: David Tchoffa
Author-X-Name-First: David
Author-X-Name-Last: Tchoffa
Author-Name: Nicolas Figay
Author-X-Name-First: Nicolas
Author-X-Name-Last: Figay
Author-Name: Parisa Ghodous
Author-X-Name-First: Parisa
Author-X-Name-Last: Ghodous
Author-Name: Ernesto Exposito
Author-X-Name-First: Ernesto
Author-X-Name-Last: Exposito
Author-Name: Kouami Seli Apedome
Author-X-Name-First: Kouami Seli
Author-X-Name-Last: Apedome
Author-Name: Abderrahaman El Mhamedi
Author-X-Name-First: Abderrahaman
Author-X-Name-Last: El Mhamedi
Title: Dynamic manufacturing network – from flat semantic graphs to composite models
Abstract: 
 During last years, the federated interoperability framework (FIF) has been developed by Airbus Group Innovation (AGI) for establishing sustainable Product and Process data interoperability. FIF combines usage of open standards for Manufacturing, Information Systems (IS) and Information & Communication Technologies (ICT). FIF evolvability was demonstrated by addressing successively Concurrent Engineering and Collaborative Product design in Virtual Enterprises. Due to the considered complex systems, FIF uses Enterprise Modelling (EM) and Model Driven Approach (MDAp) for preparing and building operational interoperability. Interconnected enterprise platforms behaviour and data flows are derived from business logic models. When exchanging data, FIF prevents data loss and semantic inconsistency relying on ontology: a semantic hyper-graph is produced per collaboration. Equivalent constructs of all the languages used in the MDAp are mapped for conceptualisation, design, development and realisation. But it requires more when addressing the complexity of the considered systems. Using semantic graphs and descriptive logic is not suited when dealing with multi-scale models and the various breakdowns with different granularity. This paper describes an innovative approach for extending the FIF, relying on modelling over UML2/SysML and introduces mereotopology. Usage is illustrated with a comprehensive use case combining Manufacturing 4.0 and PLM (Product Lifecycle Management) of the future.
Journal: International Journal of Production Research
Pages: 6569-6578
Issue: 20
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1570375
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1570375
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Template-Type: ReDIF-Article 1.0
Author-Name: Yunsoo Ha
Author-X-Name-First: Yunsoo
Author-X-Name-Last: Ha
Author-Name: Junjae Chae
Author-X-Name-First: Junjae
Author-X-Name-Last: Chae
Title: A decision model to determine the number of shuttles in a tier-to-tier SBS/RS
Abstract: 
 Shuttle-based storage and retrieval systems (SBS/RSs), which are designed to increase throughput capacity and flexibility, are a type of automated storage and retrieval system used for lightweight loads. SBS/RSs can increase throughput capacity by using multiple shuttles and elevators as storage and retrieval machines (SRMs). They can also facilitate improvements in flexibility since they are able to adjust the number of SRMs according to transaction demands. Thus, determining the number of shuttles is an important issue in tier-to-tier SBS/RSs. In this paper, a decision model to determine the number of shuttles is proposed. The model is based on the travel time model, and it considers parameters such as the physical configuration, velocity profile and the probability that the shuttle operates a dual command. Finally, the throughput capacity from the travel time model is compared with that from a simulation-based approach in order to verify the effects of the model. In addition, a critical discussion regarding the characteristics of the tier-to-tier system is provided.
Journal: International Journal of Production Research
Pages: 963-984
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1476787
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1476787
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Template-Type: ReDIF-Article 1.0
Author-Name: Salvatore Cannella
Author-X-Name-First: Salvatore
Author-X-Name-Last: Cannella
Author-Name: Carmela Di Mauro
Author-X-Name-First: Carmela
Author-X-Name-Last: Di Mauro
Author-Name: Roberto Dominguez
Author-X-Name-First: Roberto
Author-X-Name-Last: Dominguez
Author-Name: Alessandro Ancarani
Author-X-Name-First: Alessandro
Author-X-Name-Last: Ancarani
Author-Name: Florian Schupp
Author-X-Name-First: Florian
Author-X-Name-Last: Schupp
Title: An exploratory study of risk aversion in supply chain dynamics via human experiment and agent-based simulation
Abstract: 
 The literature on the impact of risk aversion on supply chains (SCs) is relatively limited and, in particular, there is a dearth of theory and a lack of empirical evidence concerning: (1) the impact of individual risk aversion on the generation and dynamics of the order policy (e.g. order patterns and inventory holding costs); (2) the impact of several combinations of risk-averse members in each stage of a multi-echelon SC. We explore these gaps through a multi-method approach (i.e. human experiments and agent-based simulation), thus using both empirical and simulated data. Specifically, based on results from a human experiment, we develop the conjecture that risk aversion is positively correlated to the desired stock level and consequently to the safety stock factor of inventory order policies. Building on this finding, we perform a simulation study to infer the impact of individual risk aversion in a multi-echelon SC. Results show that alternative compositions of the SC in terms of risk aversion levels of the echelons significantly influence inventory holdings and SC dynamics. The study implies that a company facing problems of high inventory days-on-hand should favour low-risk aversion managers, as instrumental to lowering stock and improving net working capital.
Journal: International Journal of Production Research
Pages: 985-999
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1497817
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1497817
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Template-Type: ReDIF-Article 1.0
Author-Name: Shou-feng Ji
Author-X-Name-First: Shou-feng
Author-X-Name-Last: Ji
Author-Name: Xiao-shuai Peng
Author-X-Name-First: Xiao-shuai
Author-X-Name-Last: Peng
Author-Name: Rong-juan Luo
Author-X-Name-First: Rong-juan
Author-X-Name-Last: Luo
Title: An integrated model for the production-inventory-distribution problem in the Physical Internet
Abstract: 
 In contrast to traditional supply chain networks, Physical Internet (PI) is an interconnected open global logistics network based on open PI hubs and standard PI-containers that has the potential to achieve ground-breaking improvements in integrated production-inventory-distribution management. In this paper, to quantify the advantages of PI from a cost performance perspective, we propose a mixed-integer linear programming (MILP) formulation for addressing the problem that combines an integrated production-inventory-distribution decision with PI, which has been addressed separately in the existing literature. The results of computational experiments show that while achieving a comparable or better service level, PI can achieve significant cost savings compared to a traditional supply chain network with a dynamic configuration and a hybrid configuration. Moreover, we investigate the impact of several problem parameter changes on the total costs under each network setting, and managerial insights are derived.
Journal: International Journal of Production Research
Pages: 1000-1017
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1497818
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1497818
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Template-Type: ReDIF-Article 1.0
Author-Name: Nicolas Brulard
Author-X-Name-First: Nicolas
Author-X-Name-Last: Brulard
Author-Name: Van-Dat Cung
Author-X-Name-First: Van-Dat
Author-X-Name-Last: Cung
Author-Name: Nicolas Catusse
Author-X-Name-First: Nicolas
Author-X-Name-Last: Catusse
Author-Name: Cyril Dutrieux
Author-X-Name-First: Cyril
Author-X-Name-Last: Dutrieux
Title: An integrated sizing and planning problem in designing diverse vegetable farming systems
Abstract: 
 To support the short food supply chain development in cities, we propose a diverse vegetable farm design model to maximise the farm revenue in response to clients' daily demands in local fresh fruits and vegetables. The model supports decision in creating or adapting farms within or around cities with viable business models. To the best of our knowledge, our model is a first attempt to integrate strategic and tactical decisions on multi-techniques, multi-products and multi-clients production systems. Integrating strategic and tactical decisions, we obtain new solutions that could not be obtained by separating the two decision levels, due to product short-time perishability constraints: on-plot and cold-room storage, loss functions and price reduction. We define a specific formulation of the production methods in the model to consider both cultivation and harvest tasks that compete for limited and expensive labour resource. This paper presents the mixed integer linear programme we develop, as well as graphical and computational results. We have been able to find relevant solutions on a real farm case study that demonstrates the interest of using short time-paces for the strategic sizing of a farm growing fresh perishable products.
Journal: International Journal of Production Research
Pages: 1018-1036
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1498985
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1498985
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Template-Type: ReDIF-Article 1.0
Author-Name: Chunguang Bai
Author-X-Name-First: Chunguang
Author-X-Name-Last: Bai
Author-Name: Ahmet Satir
Author-X-Name-First: Ahmet
Author-X-Name-Last: Satir
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: Investing in lean manufacturing practices: an environmental and operational perspective
Abstract: 
 Lean manufacturing practices (LMPs) and corporate environmental sustainability are becoming inextricably linked. Throughout the lean and green debate, many organisations have recognised that LMPs have implications for their sustainable development and competitive positioning. Not only LMPs are complex on their own, but when perceived from an environmental sustainability perspective, the decision to implement an LMP can become even more intricate. Although general tools exist, the lack of effective decision-making tools to help in the implementation of LMPs with an environmental sustainability dimension is palpable. Thus, this study tackles the aforementioned decision problem by incorporating environmental and operational performance outcome expectations as these expectations are viewed in light of the ease of implementation of various LMPs. A novel multi-criteria decision-making (MCDM) model for evaluation of LMPs is developed in this respect. The model integrates a three-parameter interval grey number with rough set theory and the TODIM method. The model is run using empirical data from six manufacturing organisations. The findings facilitate the identification of a ‘locus of investments’ for a better selection of LMPs. The robustness of the decision support model developed is assessed through sensitivity analysis.
Journal: International Journal of Production Research
Pages: 1037-1051
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1498986
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1498986
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Template-Type: ReDIF-Article 1.0
Author-Name: Neven Hadžić
Author-X-Name-First: Neven
Author-X-Name-Last: Hadžić
Title: Analytical Solution of the serial Bernoulli production line steady-state performance and its application in the shipbuilding process
Abstract: 
 The modern shipbuilding industry is faced with numerous challenges urging abiding improvement of the shipbuilding process and its management. Such a demanding problem is usually approached using complex production management models involving large data basis handling. The same problem can be solved using simpler, intuitive and mathematically transparent models developed within production system engineering. For these purposes, the analytical solution of the serial Bernoulli production line steady-state performance involving an arbitrary number of machines and buffers of arbitrary occupancy is developed based on Markov chain approach and eigenvalue problem including formulation of the generalised transition matrix as a key novelty. Performance measures in case of general serial Bernoulli production line are developed and the theory is validated using serial Bernoulli lines composed of two, three, four and five machines. The obtained results are compared to those determined using a semi-analytical approach. In order to further demonstrate the applicability of the developed theory, performance measure analysis is performed in cases of longer lines composed of 6, 7, 8, 9 and 10 machines with non-equal buffer capacities. Application of the developed procedure in the analysis of the shipbuilding process is illustrated in a case of the plate prefabrication line usually placed in each shipyard.
Journal: International Journal of Production Research
Pages: 1052-1065
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1500042
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1500042
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Template-Type: ReDIF-Article 1.0
Author-Name: Kunpeng Li
Author-X-Name-First: Kunpeng
Author-X-Name-Last: Li
Author-Name: Yang Li
Author-X-Name-First: Yang
Author-X-Name-Last: Li
Author-Name: Qiannong Gu
Author-X-Name-First: Qiannong
Author-X-Name-Last: Gu
Author-Name: Alicia Ingersoll
Author-X-Name-First: Alicia
Author-X-Name-Last: Ingersoll
Title: Joint effects of remanufacturing channel design and after-sales service pricing: an analytical study
Abstract: 
 We conduct an analytical study on remanufacturing channel design and after-sales service pricing, which jointly affect the sustainability and profitability of the supply chain. We model a supply chain with one manufacturer and one independent retailer. The manufacturer, as the Stackelberg game leader, engages in remanufacturing to take advantage of production cost savings. The collection of the used products can be carried out by either the manufacturer or the retailer. After-sales service, for example, extended warranty, is offered with the product and is sold separately. The service provider can be either the manufacturer or the retailer. We use game theoretic models to answer an important research question: How do remanufacturing and after-sales service jointly affect channel selection decisions? We explore the benefits of joint decision making in terms of remanufacturing efficiency and after-sales service performance. We find that it is most efficient for the retailer to collect the used product for remanufacturing and to offer after-sales service, because the retailer simultaneously makes decisions regarding remanufacturing and after-sales service and thus reduces double marginalisation in the supply chain. We also demonstrate numerically how the costs of collecting used products and providing after-sales service impact channel selection decisions.
Journal: International Journal of Production Research
Pages: 1066-1081
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1500722
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1500722
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1066-1081




Template-Type: ReDIF-Article 1.0
Author-Name: M.A. Darwish
Author-X-Name-First: M.A.
Author-X-Name-Last: Darwish
Author-Name: M. Alkhedher
Author-X-Name-First: M.
Author-X-Name-Last: Alkhedher
Author-Name: Abdulrahman Alenezi
Author-X-Name-First: Abdulrahman
Author-X-Name-Last: Alenezi
Title: Reducing the effects of demand uncertainty in single-newsvendor multi-retailer supply chains
Abstract: 
 Due to fierce competition in today’s global market, businesses are forced to provide customers with high service levels. Typically, vendors produce or order sufficient quantities at the beginning of a selling season to ensure reasonable service levels for the whole season. However, due to the probabilistic nature of demand, high service levels at the beginning of a selling season does not guarantee appropriate service levels during the course of consuming the item. Thus, revision of service levels during a selling season is important and ignoring such revision may lead to serious consequences for businesses like profit loss due to cancelled orders and reduction of the market share of the company. In this paper, we propose a model for a newsvendor supply chain with single vendor and multiple retailers where the vendor has two-ordering opportunities. At the beginning of a selling season, the retailer orders from a vendor a quantity such that a predetermined service level is achieved. At the second-ordering instant, the retailer learns more about the demand pattern and uses the new available demand data to update the coming demand using Bayesian approach. Based on the updated demand, the retailer evaluates the new service level for the remaining portion of the selling season. If this service level is lower than a specific value, a second batch is ordered. We develop the model for general demand distribution and determine the optimal quantities at the beginning of the selling season and at the second-ordering opportunity.
Journal: International Journal of Production Research
Pages: 1082-1102
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1501164
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1501164
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Template-Type: ReDIF-Article 1.0
Author-Name: Qingying Li
Author-X-Name-First: Qingying
Author-X-Name-Last: Li
Author-Name: Jianheng Zhou
Author-X-Name-First: Jianheng
Author-X-Name-Last: Zhou
Title: A horizontal capacity reservation game under asymmetric information
Abstract: 
 We investigate a common horizontal dual-sourcing model in the semiconductor industry. The supply chain consists of an integrated device manufacturer (IDM) and a pure-play foundry. The IDM can make internal production and source from the foundry, and only the IDM sells the products to the market. Both the IDM and the foundry must invest in production capacity before making production. We consider stochastic one-period demand, which can either be a high type or a low type. We assume that the true demand type is private information to the IDM such that the IDM and the foundry engage in a signalling game. We identify the unique separating equilibrium in this asymmetrical information setting. We find that information asymmetry may mitigate or aggravate the double marginalisation effect, and that it may also affect the capacity allocation between the IDM and the foundry. Furthermore, we conduct a numerical study to investigate the sensitivity of the equilibrium and the information rent.
Journal: International Journal of Production Research
Pages: 1103-1118
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1501165
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1501165
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1103-1118




Template-Type: ReDIF-Article 1.0
Author-Name: Leilei Meng
Author-X-Name-First: Leilei
Author-X-Name-Last: Meng
Author-Name: Chaoyong Zhang
Author-X-Name-First: Chaoyong
Author-X-Name-Last: Zhang
Author-Name: Xinyu Shao
Author-X-Name-First: Xinyu
Author-X-Name-Last: Shao
Author-Name: Yaping Ren
Author-X-Name-First: Yaping
Author-X-Name-Last: Ren
Author-Name: Caile Ren
Author-X-Name-First: Caile
Author-X-Name-Last: Ren
Title: Mathematical modelling and optimisation of energy-conscious hybrid flow shop scheduling problem with unrelated parallel machines
Abstract: 
 This paper investigates an energy-conscious hybrid flow shop scheduling problem with unrelated parallel machines (HFSP-UPM) with the energy-saving strategy of turning off and on. We first analyse the energy consumption of HFSP-UPM and formulate five mixed integer linear programming (MILP) models based on two different modelling ideas namely idle time and idle energy. All the models are compared both in size and computational complexities. The results show that MILP models based on different modelling ideas vary dramatically in both size and computational complexities. HFSP-UPM is NP-Hard, thus, an improved genetic algorithm (IGA) is proposed. Specifically, a new energy-conscious decoding method is designed in IGA. To evaluate the proposed IGA, comparative experiments of different-sized instances are conducted. The results demonstrate that the IGA is more effective than the genetic algorithm (GA), simulating annealing algorithm (SA) and migrating birds optimisation algorithm (MBO). Compared with the best MILP model, the IGA can get the solution that is close to an optimal solution with the gap of no more than 2.17% for small-scale instances. For large-scale instances, the IGA can get a better solution than the best MILP model within no more than 10% of the running time of the best MILP model.
Journal: International Journal of Production Research
Pages: 1119-1145
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1501166
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1501166
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Template-Type: ReDIF-Article 1.0
Author-Name: Xingyu Jiang
Author-X-Name-First: Xingyu
Author-X-Name-Last: Jiang
Author-Name: Boxue Song
Author-X-Name-First: Boxue
Author-X-Name-Last: Song
Author-Name: Li Li
Author-X-Name-First: Li
Author-X-Name-Last: Li
Author-Name: Mingming Dai
Author-X-Name-First: Mingming
Author-X-Name-Last: Dai
Author-Name: Haoyin Zhang
Author-X-Name-First: Haoyin
Author-X-Name-Last: Zhang
Title: The customer satisfaction-oriented planning method for redesign parameters of used machine tools
Abstract: 
 Performance recovery is the main emphasis in most remanufactured machine tools, rather than the effective combination of customer requirements (CRs) and redesign processes. Because of this, remanufactured machine tools do not reach their potential competitiveness, highly restricting the implementations to recover used machine tools. To help remedy this, fuzzy nonlinear regression is applied to the fuzzy relationships between CRs and redesign parameters, and the fuzzy correlations among redesign parameters are analysed by fully considering the uncertainties between CRs and redesign parameters. Improved planning equations based on fuzzy nonlinear regression are proposed by injecting fuzziness into the original planning equations. The redesign process of a machine tool is taken as an example to implement the proposed method. The results show that the improved planning equations can obtain higher customer satisfaction compared to the unimproved planning equations. This can provide new thinking to effectively combine CRs and redesign processes.
Journal: International Journal of Production Research
Pages: 1146-1160
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1502483
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1502483
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1146-1160




Template-Type: ReDIF-Article 1.0
Author-Name: Stanko Dimitrov
Author-X-Name-First: Stanko
Author-X-Name-Last: Dimitrov
Author-Name: Oben Ceryan
Author-X-Name-First: Oben
Author-X-Name-Last: Ceryan
Title: Optimal inventory decisions when offering layaway
Abstract: 
 This paper presents an inventory management policy for a retailer offering a layaway programme. Layaway is a service provided by retailers that allows budget constrained consumers who have sufficiently high valuations to pay for a product in several instalments rather than at once and obtain the product that has been reserved for them at the end of the payment period. If a consumer defaults on payments, then the reserved item is released back into store inventory. In this paper, we first determine the retailer's optimal order decisions when layaway is offered. We find that the order quantity under a layaway programme decreases with the likelihood of consumers not finishing their layaway plans and that it is not always profitable for a retailer to offer a layaway programme. We then identify the market conditions under which the retailer would benefit from a layaway programme. Lastly, we consider an extension to capture the influence of the timing of consumer defaults.
Journal: International Journal of Production Research
Pages: 1161-1175
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1502484
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1502484
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1161-1175




Template-Type: ReDIF-Article 1.0
Author-Name: Chen Yang
Author-X-Name-First: Chen
Author-X-Name-Last: Yang
Author-Name: Shulin Lan
Author-X-Name-First: Shulin
Author-X-Name-Last: Lan
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Title: Research on coordinated development between metropolitan economy and logistics using big data and Haken model
Abstract: 
 To quantitatively study the relationship and mutual effects between metropolitan economy and logistics is an important, yet pending issue, which can scientifically guide the urban planning and investment. Through the identified evaluation indexes of metropolitan logistics and economic development, this paper first builds up an evaluation process model of metropolitan economic and logistics development, based on big data analytics (BDA), the entropy evaluation method, and the maximum deviation method. BDA can help extract the exact data about the indicators of metropolitan economy and logistics. Then a Haken model is adopted to ravel out the dynamic co-evolutionary law of economy and logistics in five Chinese cities, which complements the above static evaluation. The results show that the economic development is an order parameter and plays a key role in the coordinated development of metropolitan logistics and economy. However, from 2013 to 2014, these five cities had not established an orderly evolved positive-feedback mechanism through which economic development promotes the coordinated development of metropolitan logistics and economic development.
Journal: International Journal of Production Research
Pages: 1176-1189
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1503427
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1503427
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian Wang
Author-X-Name-First: Jian
Author-X-Name-Last: Wang
Author-Name: Huimin Miao
Author-X-Name-First: Huimin
Author-X-Name-Last: Miao
Author-Name: Mingzhu Yu
Author-X-Name-First: Mingzhu
Author-X-Name-Last: Yu
Title: Interdependent order allocation in the two-echelon competitive and cooperative supply chain
Abstract: 
 In this paper, we consider an order allocation problem in a two-echelon supply chain with multiple suppliers and multiple demanders. The orders from the demanders are interdependent in terms of execution sequence. We consider both the competition and cooperation relationships between the suppliers and demanders. We provide formal definition for the order allocation problem and propose a negotiation mechanism which includes a two-stage negotiation protocol and two heuristic negotiation algorithms. Different negotiation strategies are proposed for the demanders and suppliers to resolve the order interdependency and competition conflict. An automated negotiation approach is introduced to implement the negotiation mechanism. The computational experiments show that orders under different supply chain contexts can be allocated with high success rate. We also numerically compare the influence of different negotiation strategies and investigate the interaction of conflict resolutions.
Journal: International Journal of Production Research
Pages: 1190-1213
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1504171
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504171
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Template-Type: ReDIF-Article 1.0
Author-Name: Sujeet Kumar Singh
Author-X-Name-First: Sujeet Kumar
Author-X-Name-Last: Singh
Author-Name: Mark Goh
Author-X-Name-First: Mark
Author-X-Name-Last: Goh
Title: Multi-objective mixed integer programming and an application in a pharmaceutical supply chain
Abstract: 
 Multi-objective integer linear and/or mixed integer linear programming (MOILP/MOMILP) are very useful for many areas of application as any model that incorporates discrete phenomena requires the consideration of integer variables. However, the research on the methods for the general multi-objective integer/mixed integer model has been scant when compared to multi-objective linear programming with continuous variables. In this paper, an MOMILP is proposed, which integrates various conflicting objectives. We give importance to the imprecise nature of some of the critical factors used in the modelling that can influence the effectiveness of the model. The uncertainty and the hesitation arising from estimating such imprecise parameters are represented by intuitionistic fuzzy numbers. The MOMILP model with intuitionistic fuzzy parameters is first converted into a crisp MOMILP model, using appropriate defuzzification strategies. Thereafter, the MOMILP is transformed into a single objective problem to yield a compromise solution with an acceptable degree of satisfaction, using suitable scalarisation techniques such as the gamma-connective technique and the minimum bounded sum operator technique. The proposed solution method is applied to several test problems and a multi-objective pharmaceutical supply chain management model with self generated random data.
Journal: International Journal of Production Research
Pages: 1214-1237
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1504172
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504172
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Template-Type: ReDIF-Article 1.0
Author-Name: Florian Lücker
Author-X-Name-First: Florian
Author-X-Name-Last: Lücker
Author-Name: Ralf W. Seifert
Author-X-Name-First: Ralf W.
Author-X-Name-Last: Seifert
Author-Name: Işık Biçer
Author-X-Name-First: Işık
Author-X-Name-Last: Biçer
Title: Roles of inventory and reserve capacity in mitigating supply chain disruption risk
Abstract: 
 This research focuses on managing disruption risk in supply chains using inventory and reserve capacity under stochastic demand. While inventory can be considered as a speculative risk mitigation lever, reserve capacity can be used in a reactive fashion when a disruption occurs. We determine optimal inventory levels and reserve capacity production rates for a firm that is exposed to supply chain disruption risk. We fully characterise four main risk mitigation strategies: inventory strategy, reserve capacity strategy, mixed strategy and passive acceptance. We illustrate how the optimal risk mitigation strategy depends on product characteristics (functional versus innovative) and supply chain characteristics (agile versus efficient). This work is inspired from a risk management problem of a leading pharmaceutical company.
Journal: International Journal of Production Research
Pages: 1238-1249
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1504173
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504173
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Template-Type: ReDIF-Article 1.0
Author-Name: Mervegül Kırcı
Author-X-Name-First: Mervegül
Author-X-Name-Last: Kırcı
Author-Name: Işık Biçer
Author-X-Name-First: Işık
Author-X-Name-Last: Biçer
Author-Name: Ralf W. Seifert
Author-X-Name-First: Ralf W.
Author-X-Name-Last: Seifert
Title: Optimal replenishment cycle for perishable items facing demand uncertainty in a two-echelon inventory system
Abstract: 
 We consider a two-echelon supply chain with an upstream manufacturer and a downstream retailer for a single perishable product. The manufacturer processes raw materials into finished products, which are purchased by the retailer in each replenishment cycle. The raw materials of the manufacturer are highly perishable (i.e. perishing within hours or days), and the finished goods at the retailer face demand uncertainty and obsolescence. We model the manufacturer–retailer relationship as a Stackelberg game where the retailer is the leader and decides the replenishment cycle that minimises its mismatch cost between supply and uncertain demand. The manufacturer is the follower and decides its processing rate to minimise its unit cost for finished goods. Our results show that the raw material and finished goods lifetimes, which are interrelated through the duration of the replenishment cycle, have a significant impact on supply chain costs. Although raw material spoilage cost by itself is low, we show that short raw material lifetimes have a significant impact on the costs of both parties. Additionally, we find that while high manufacturer markups increase retailer costs, they reduce the manufacturer's costs due to large production batches.
Journal: International Journal of Production Research
Pages: 1250-1264
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1504244
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504244
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1250-1264




Template-Type: ReDIF-Article 1.0
Author-Name: Morteza Davari
Author-X-Name-First: Morteza
Author-X-Name-Last: Davari
Author-Name: Erik Demeulemeester
Author-X-Name-First: Erik
Author-X-Name-Last: Demeulemeester
Title: A novel branch-and-bound algorithm for the chance-constrained resource-constrained project scheduling problem
Abstract: 
 The resource-constrained project scheduling problem (RCPSP) has been widely studied during the last few decades. In real-world projects, however, not all information is known in advance and uncertainty is an inevitable part of these projects. The chance-constrained resource-constrained project scheduling problem (CC-RCPSP) has been recently introduced to deal with uncertainty in the RCPSP. In this paper, we propose a branch-and-bound (B&B) algorithm and a mixed integer linear programming (MILP) formulation that solve a sample average approximation of the CC-RCPSP. We introduce two different branching schemes and eight different priority rules for the proposed B&B algorithm. The computational results suggest that the proposed B&B procedure clearly outperforms both a proposed MILP formulation and a branch-and-cut algorithm from the literature.
Journal: International Journal of Production Research
Pages: 1265-1282
Issue: 4
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1504245
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504245
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Template-Type: ReDIF-Article 1.0
Author-Name: Foivos Psarommatis
Author-X-Name-First: Foivos
Author-X-Name-Last: Psarommatis
Author-Name: Gökan May
Author-X-Name-First: Gökan
Author-X-Name-Last: May
Author-Name: Paul-Arthur Dreyfus
Author-X-Name-First: Paul-Arthur
Author-X-Name-Last: Dreyfus
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Zero defect manufacturing: state-of-the-art review, shortcomings and future directions in research
Abstract: 
 This paper provides a literature review on zero defect manufacturing based on the content analysis performed for 280 research articles published from 1987 to 2018 in a variety of academic journals and conference proceedings. The review summarises the state-of-the-art, highlights shortcomings and further directions in research. Accordingly, we investigated how zero defect manufacturing was implemented and evaluated the main research patterns in the sample by analysing key factors. Based on the extensive review of the zero defect manufacturing literature, we identified and highlighted four distinctive strategies based on overarching themes for zero defect manufacturing, i.e. detection, repair, prediction, and prevention. Evaluation of current research and descriptive analysis highlighted six major shortcomings of current research in zero defect manufacturing: (i) focus on a single strategy instead of a holistic approach for global optima; (ii) certain industries are under-researched; (iii) full potential of industry-academia collaboration is not achieved; (iv) not enough focus on the beginning of manufacturing lifecycle; (v) cost–benefit comparative analysis is not evident; (vi) standard and clear definition of terms are missing. Finally, we presented four further directions in which an advance of the topic would stimulate scholarly and practical needs: (i) shift from local to global solutions; (ii) investigate pros and cons; (iii) role of people and human activities in manufacturing; (iv) new business models for zero defect manufacturing.
Journal: International Journal of Production Research
Pages: 1-17
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1605228
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1605228
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Template-Type: ReDIF-Article 1.0
Author-Name: Sven Winkelhaus
Author-X-Name-First: Sven
Author-X-Name-Last: Winkelhaus
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Title: Logistics 4.0: a systematic review towards a new logistics system
Abstract: 
 Enterprises are confronted with new customer requirements and challenged by global competition leading to fundamental changes of today’s industry. Against this background, at present Industry 4.0 is the main concept of dealing with these challenges in manufacturing. Lacking a comparable covering concept in logistics, this study aims to stringently unify diverse approaches in research to a Logistics 4.0-framework in order to generate a new picture of the state of logistics research. In this article, a comprehensive framework of Logistics 4.0 is developed. First, the term Logistics 4.0 is defined, and then a systematic literature review of 114 articles on Logistics 4.0 is performed. The resulting framework combines external triggers, main technological innovations, impacts of human interactions and logistics tasks. Existing solutions that support Logistics 4.0 are summarised according to the technologies: internet of things, cyber-physical systems, Big Data, cloud computing, mobile-based systems, social media-based systems and further technologies. Managerial implications are outlined and open research issues are examined. For researchers, this review offers the possibility to unify and expand existing solutions and to identify links and interfaces that are still needed. As for managerial implications, this framework can be used to identify future strategies and technologies to fulfil certain logistics tasks, but also to develop new technological solutions for current and future demands.
Journal: International Journal of Production Research
Pages: 18-43
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1612964
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1612964
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Template-Type: ReDIF-Article 1.0
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Hendrik Wurtmann
Author-X-Name-First: Hendrik
Author-X-Name-Last: Wurtmann
Author-Name: Stefan Seuring
Author-X-Name-First: Stefan
Author-X-Name-Last: Seuring
Title: Managing climate change risks in global supply chains: a review and research agenda
Abstract: 
 Climate change is forcing governments and businesses to explore mitigation strategies to avoid future catastrophe. There is an urgent need to manage climate change risks in global supply chains. Following a systematic literature review and text mining approach, 90 interdisciplinary articles between the years 2005 and 2018 were studied. Thematic and descriptive analysis identifies sources, consequences and control mechanisms for the climate change risks. It is found that climate change driven by extreme weather conditions significantly impacts food production, natural resources and transportation worldwide. This direct impact on food, mining and logistics sectors cascades into other interlinked global supply chain network. Climate change and supply chains are found to be mutually influencing each other through natural disasters and greenhouse gas (GHG) emissions respectively. A systems theory driven, novel supply chain risk management framework for managing climate change risks is proposed. The study contributes to supply chain risk management literature by capturing the nexus between climate change and supply chain management.
Journal: International Journal of Production Research
Pages: 44-64
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1629670
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629670
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Template-Type: ReDIF-Article 1.0
Author-Name: Sachin S. Kamble
Author-X-Name-First: Sachin S.
Author-X-Name-Last: Kamble
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Title: Big data-driven supply chain performance measurement system: a review and framework for implementation
Abstract: 
 Performance measures and metrics (PMM) is identified to be an essential aspect of managing diverse supply chains. The PMM improves the firm’s performance by providing open and transparent communication between the various stakeholders of an organisation. The literature suggests that big data analytics has a positive impact on the supply chain and firm performance. Presently, the literature lack studies that recognise the PMM relevant to big data-driven supply chain (BDDSC). The present study is based on a comprehensive review of 66 papers published with the primary objective to identify the various PMMs used to evaluate the BDDSC. The findings suggest that the PMMs applicable to BDDSC can be classified into two non-mutually exclusive categories. The first category represents 24 performance measures used to evaluate the performance of the big data analytics capability and the second category represents 130 measures used for assessing the performance of BDDSC processes. The study also reports the emergence of new performance measures based on increasing use of predictive and social analytics in BDDSC. Based on the results of the study a framework on BDDSC performance measurement system is proposed which will guide the managers to have a robust performance measurement system in their organisation.
Journal: International Journal of Production Research
Pages: 65-86
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1630770
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630770
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Template-Type: ReDIF-Article 1.0
Author-Name: Ainhoa Goienetxea Uriarte
Author-X-Name-First: Ainhoa
Author-X-Name-Last: Goienetxea Uriarte
Author-Name: Amos H.C. Ng
Author-X-Name-First: Amos H.C.
Author-X-Name-Last: Ng
Author-Name: Matías Urenda Moris
Author-X-Name-First: Matías
Author-X-Name-Last: Urenda Moris
Title: Bringing together Lean and simulation: a comprehensive review
Abstract: 
 Lean is and will still be one of the most popular management philosophies in the Industry 4.0 context and simulation is one of its key technologies. Many authors discuss about the benefits of combining Lean and simulation to better support decision makers in system design and improvement. However, there is a lack of reviews in the domain. Therefore, this paper presents a four-stage comprehensive review and analysis of existing literature on their combination. The aim is to identify the state of the art, existing methods and frameworks for combining Lean and simulation, while also identifying key research perspectives and challenges. The main trends identified are the increased interest in the combination of Lean and simulation in the Industry 4.0 context and in their combination with optimisation, Six Sigma, as well as sustainability. The number of articles in these areas is likely to continue to grow. On the other hand, we highlight six gaps found in the literature regarding the combination of Lean and simulation, which may induce new research opportunities. Existing technical, organisational, as well as people and culture related challenges on the combination of Lean and simulation are also discussed.
Journal: International Journal of Production Research
Pages: 87-117
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1643512
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1643512
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Template-Type: ReDIF-Article 1.0
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Ata Allah Taleizadeh
Author-X-Name-First: Ata Allah
Author-X-Name-Last: Taleizadeh
Author-Name: Xiaohang Yue
Author-X-Name-First: Xiaohang
Author-X-Name-Last: Yue
Title: Game theory applications in production research in the sharing and circular economy era
Abstract: 
 In recent years, topics such as sharing economy and circular supply chains have emerged in production research and operations management. To explore them and tackle the associated challenges, we need to acquire a full understanding of decision-makers’ strategic behaviours as well as the deployment of sophisticated analytical methods such as game theory. In this article, we concisely examine the meanings of sharing economy and circular supply chains in production research. We then introduce the featured papers of the special issue and highlight the major insights developed. Future research directions are discussed.
Journal: International Journal of Production Research
Pages: 118-127
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1681137
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1681137
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Template-Type: ReDIF-Article 1.0
Author-Name: Ting Ji
Author-X-Name-First: Ting
Author-X-Name-Last: Ji
Author-Name: Xiaoping Xu
Author-X-Name-First: Xiaoping
Author-X-Name-Last: Xu
Author-Name: Xiaoming Yan
Author-X-Name-First: Xiaoming
Author-X-Name-Last: Yan
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Title: The production decisions and cap setting with wholesale price and revenue sharing contracts under cap-and-trade regulation
Abstract: 
 After consideration of a supply chain consisting of a manufacturer and a retailer, this paper uses a two-stage Stackelberg game to explore the production decision as well as the government cap setting with wholesale price and revenue sharing contracts under cap-and-trade regulation. We also compare the total carbon emission and social welfare with the two contracts. We list some main conclusions. Firstly, we find that the government's over-allocated carbon credits may damage the manufacturer's profit with wholesale price or revenue sharing contract, which can increase the difficulty of implementing cap-and-trade regulation. Secondly, we detect that the optimal cap under the two contracts is decreasing or constant in the environmental concern parameter, which means that the government should keep the optimal cap unchanged under the low or high environmental concern parameter, and decrease the cap when the middle environmental concern parameter increases. Thirdly, we show that using green technology may increase the total carbon emission. Finally, we discover that the social welfare with wholesale price contract is less (larger) than that with revenue sharing contract under low (high) value of the environmental concern parameter, and the social welfare with the two contracts is equal to each other under middle value of the environmental concern parameter.
Journal: International Journal of Production Research
Pages: 128-147
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1641239
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641239
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Template-Type: ReDIF-Article 1.0
Author-Name: Bin Shen
Author-X-Name-First: Bin
Author-X-Name-Last: Shen
Author-Name: Yifan Cao
Author-X-Name-First: Yifan
Author-X-Name-Last: Cao
Author-Name: Xiaoyan Xu
Author-X-Name-First: Xiaoyan
Author-X-Name-Last: Xu
Title: Product line design and quality differentiation for green and non-green products in a supply chain
Abstract: 
 Motivated by the real practices in the circular economy, this paper aims to identify optimal product line design for green and non-green products in terms of quality differentiation. We develop a price and quality driven consumer choice model in a two-echelon supply chain through using a game-theoretical approach. Our study shows that no matter how high or low the product quality difference is, when the consumers’ willingness to pay (WTP) for responsibility is relatively low, a single product line strategy will be prioritised over a two-product line strategy; whereas when the consumers’ WTP for responsibility is relatively high, a two-product line strategy is more desirable. Moreover, we find that enhancing product quality could increase consumer welfare and reduce environmental impact. Only when green and non-green product quality difference is large enough, designing and selling green products is beneficial to consumers, brings the slightest pressure on the environment, and generates the highest social welfare. Furthermore, we extend the model by introducing a simplified contract and find that a simplified contract is not able to increase the manufacturer's profit, but may increase the retailer's profit and consumer surplus as well as generate better performance in environmental protection and social welfare.
Journal: International Journal of Production Research
Pages: 148-164
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1656843
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656843
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Template-Type: ReDIF-Article 1.0
Author-Name: Qingying Li
Author-X-Name-First: Qingying
Author-X-Name-Last: Li
Author-Name: Xiaotong Guan
Author-X-Name-First: Xiaotong
Author-X-Name-Last: Guan
Author-Name: Tianqin Shi
Author-X-Name-First: Tianqin
Author-X-Name-Last: Shi
Author-Name: Wen Jiao
Author-X-Name-First: Wen
Author-X-Name-Last: Jiao
Title: Green product design with competition and fairness concerns in the circular economy era
Abstract: 
 In this paper, we consider green product design in a supply chain consisting of one manufacturer and two retailers, where retailer 1 aims at monetary profit maximisation, and retailer 2 has fairness concern. We consider two kinds of green products: a marginal-intensive green product (MIGP) and a development-intensive green product (DIGP). For the former, the green investment cost depends on the green level and the production quantity; while for the latter, the green investment cost depends on the green level solely. In each case, we investigate the impact of the retailer’s fairness concern by comparing the optimal solutions and supply chain performance with those in the basic models in which all the supply chain members aim at profit maximisation. We find that retailer 2 will set a higher retailing price and earn a smaller market share. Such inferiority increases as retailer 2’s inequity aversion increases or as the substitutability degree of the products offered by the two retailers increases. We also find that retailer 2’s fairness concern will always harm the manufacturer. If an equity outcome is achieved, the supply chain may achieve a better performance; however, if an inequity outcome is attained, the supply chain always performs worse.
Journal: International Journal of Production Research
Pages: 165-179
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1657249
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1657249
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Template-Type: ReDIF-Article 1.0
Author-Name: Kaiying Cao
Author-X-Name-First: Kaiying
Author-X-Name-Last: Cao
Author-Name: Bing Xu
Author-X-Name-First: Bing
Author-X-Name-Last: Xu
Author-Name: Jia Wang
Author-X-Name-First: Jia
Author-X-Name-Last: Wang
Title: Optimal trade-in and warranty period strategies for new and remanufactured products under carbon tax policy
Abstract: 
 In the context of remanufactured products with low production and carbon emission costs, manufacturing firms that produce and sell new and remanufactured products need to choose whether or not to offer trade-in service only for remanufactured products. To address this challenge, this paper investigates the optimal trade-in and warranty period strategies of a firm subject to carbon tax and trade-in subsidies policies. According to the firm’s trade-in choices, we develop two theoretical models: model TIA (Trade-in services are offered for all products) and model TIR (Trade-in service is only available to remanufactured products). The results offer some managerial insights. TIA and TIR may be a firm’s optimal trade-in choice under certain conditions; furthermore, the optimal trade-in service choice is not always benefit consumers. The results show that trade-in strategies have no effect on warranty period strategies, while a firm does not take warranty periods into consideration is more likely to choose TIR rather than TIA. A firm in TIR can curb carbon emissions more effectively. Interestingly, trade-in subsidies are not necessarily conducive to curbing total carbon emissions. We also present several quantitative examples, and find that consumers’ increased acceptance of the remanufactured product does not always benefit the firm.
Journal: International Journal of Production Research
Pages: 180-199
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1617448
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1617448
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Template-Type: ReDIF-Article 1.0
Author-Name: Juanjuan Qin
Author-X-Name-First: Juanjuan
Author-X-Name-Last: Qin
Author-Name: Yuqing Han
Author-X-Name-First: Yuqing
Author-X-Name-Last: Han
Author-Name: Guangming Wei
Author-X-Name-First: Guangming
Author-X-Name-Last: Wei
Author-Name: Liangjie Xia
Author-X-Name-First: Liangjie
Author-X-Name-Last: Xia
Title: The value of advance payment financing to carbon emission reduction and production in a supply chain with game theory analysis
Abstract: 
 This paper investigates the value of advance payment financing to carbon emission reduction and production in a supply chain. We discuss two models, namely, (1) a supply chain model with a manufacturer that is not capital-constrained, under the conditions of being with and without advance payment financing, and (2) a supply chain model with a capital-constrained manufacturer, under the conditions of using bank financing and mixed financing. We characterize and compare the optimal solutions in the two supply chain models and then extend the models with cap-and-trade regulation and general stochastic demand. We find that in the supply chain model without a capital-constrained manufacturer, advance payment financing with a low-price discount can increase the supply chain partners’ profits. However, in the supply chain model with a capital-constrained manufacturer, when the manufacturer’s production cost is high, mixed financing with a low-price discount can improve both partners’ profits. Furthermore, in the model with a capital-constrained manufacturer, when the manufacturer’s carbon emission reduction efficiency is high, the use of mixed financing can encourage the manufacturer to increase carbon emission reductions. The results help the manufacturer and the retailer to decide whether to join in advance payment financing.
Journal: International Journal of Production Research
Pages: 200-219
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1671626
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1671626
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhiying Tao
Author-X-Name-First: Zhiying
Author-X-Name-Last: Tao
Author-Name: Qinglong Gou
Author-X-Name-First: Qinglong
Author-X-Name-Last: Gou
Author-Name: Juzhi Zhang
Author-X-Name-First: Juzhi
Author-X-Name-Last: Zhang
Title: A local seller's app channel strategy concerning delivery
Abstract: 
 When a local seller launches an app channel, it can either deliver online orders itself or use a third party service. Given this background, an interesting problem is whether and how a local seller's channel strategy will be affected by these delivery options. To investigate this problem, we focus on a local seller facing these two delivery options. For each option, besides setting the online and offline prices, the seller also determines its delivery service coverage. Assuming that consumers are evenly located along an infinite Hotelling line, we propose a joint pricing and delivery distance decision model and derive the local seller's optimal decisions in two subcases, i.e. the seller is a price taker or a price setter. By analyzing and comparing the seller's optimal decisions in these situations, we find that (i) the local seller's channel strategy will be changed dramatically by the delivery option – the seller will abandon the offline channel when it delivers itself; (ii) whether the seller is a price taker or price setter will also influence the seller's channel strategy; and (iii) unexpectedly, the highly developed just-in-time logistics is an important factor that helps the offline channel and app channel coexist in the Internet era.
Journal: International Journal of Production Research
Pages: 220-255
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2018.1535725
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1535725
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Template-Type: ReDIF-Article 1.0
Author-Name: Ningning Wang
Author-X-Name-First: Ningning
Author-X-Name-Last: Wang
Author-Name: Ting Zhang
Author-X-Name-First: Ting
Author-X-Name-Last: Zhang
Author-Name: Xiaojun Fan
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Fan
Author-Name: Xiaoxuan Zhu
Author-X-Name-First: Xiaoxuan
Author-X-Name-Last: Zhu
Title: Game theoretic analysis for advertising models in dual-channel supply chains
Abstract: 
 In the sharing economy, it is trendy that companies share advertising resources or investments. This paper develops game-theoretic models to discuss three advertising schemes in a dual-channel supply chain consisting of a manufacturer and two competing retailers. The first is brand advertising, i.e. the manufacturer advertises solely for its branded product. The second is emerging joint advertising, i.e. the manufacturer jointly advertises for the product and the online retailer, and the online retailer shares a part of the advertising costs. We propose a third model, the cost-sharing of brand advertising, i.e. the manufacturer advertises solely for the product, and the offline retailer shares a part of the advertising costs. The valuation enhancement effect of brand advertising, and the valuation enhancement and demand shifting effects of joint advertising are recognised and examined. The results show that whether retailers should cooperate with the manufacturer on advertising depends on the consumer initial preference for channels, and the potential scale and cost-efficiency of advertising. We find that joint advertising benefits participants at the expense of harming the offline retailer due to demand shifting effect, while the cost-sharing of brand advertising may benefit all due to the valuation enhancement effect.
Journal: International Journal of Production Research
Pages: 256-270
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2018.1540894
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1540894
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Template-Type: ReDIF-Article 1.0
Author-Name: Yi He
Author-X-Name-First: Yi
Author-X-Name-Last: He
Author-Name: Qingyun Xu
Author-X-Name-First: Qingyun
Author-X-Name-Last: Xu
Author-Name: Pengkun Wu
Author-X-Name-First: Pengkun
Author-X-Name-Last: Wu
Title: Omnichannel retail operations with refurbished consumer returns
Abstract: 
 Online consumers being allowed to return unsatisfied products to any store prevails in the omnichannel retailing context. Retailers increasingly implement a store return option to offer consumers a seamless shopping experience. This paper develops a newsvendor model of a retailer selling its products to consumers through both online and offline channels. Consumers can return unsatisfied products to the retailer for a full refund, and the returned items can be resold as refurbished products in the circular economy era. Utilising the game theory, the retailer’s optimal ordering and pricing decisions are obtained under the benchmark scenario and omnichannel strategy. From the analytical results and numerical analysis, we examine the effects of implementing a store return option on the retailer under omnichannel retailing. The main results show that after implementing store return, (i) the optimal price of the new product remains unchanged, while the price of refurbished items may decrease in a certain condition; (ii) the optimal order quantity of the online channel increases, while that of the store decreases; (iii) in most conditions, store return strategy can achieve a win-win outcome. Specifically, consumers can enjoy more services without paying extra costs and retailer makes higher profit by implementing this strategy.
Journal: International Journal of Production Research
Pages: 271-290
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1629672
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629672
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Template-Type: ReDIF-Article 1.0
Author-Name: Varun Gupta
Author-X-Name-First: Varun
Author-X-Name-Last: Gupta
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: Dual sourcing under supply disruption with risk-averse suppliers in the sharing economy
Abstract: 
 Giant retailers sell their store brands and (re)sell substitute national brands for manufacturers (suppliers) simultaneously, which becomes an important sourcing and selling supply chain strategy in the sharing economy era. In this paper, we develop a game-theoretic model to examine the impact of risk-averse suppliers on dual sourcing decisions under supply disruption when two substitute products are sold in a common market. We examine the impact of risk-aversion, demand volatility, and supply disruption on the supply chain profitability and pricing policies. We hypothesise and then analytically derive several propositions on the dependencies of the profitability and risk-aversion, demand volatility and pricing, and risk-aversion and pricing. We also conduct numerical analysis to explore the impact of disruption. We offer insights for managers and researchers alike by uncovering the role of supplier risk-aversion for decision-making settings with substitute products and dual sourcing when product supply may be disrupted.
Journal: International Journal of Production Research
Pages: 291-307
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1686189
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1686189
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:1:p:291-307




Template-Type: ReDIF-Article 1.0
Author-Name: Qingning Cao
Author-X-Name-First: Qingning
Author-X-Name-Last: Cao
Author-Name: Jianqiang Zhang
Author-X-Name-First: Jianqiang
Author-X-Name-Last: Zhang
Title: Gray market's product quality in the circular economy era
Abstract: 
 Gray market occurs when a product is diverted from a market to another without the authorisation of the manufacturer. Conventional wisdom believes that (a) the manufacturer should increase product quality as consumer valuation increases, (b) gray market dilutes the manufacturer's incentive to invest in quality, (c) gray products flow from a low-value market to a high-value one, and (d) the manufacturer can decrease product differentiation across regions to curb gray diversion. This paper provides another look by analysing a game-theoretic model wherein one manufacturer sells a product in two markets, a high-value market and a low-value one, each of which contains one single authorised retailer. Using a game-theoretic approach, we find that (a) in the absence of a gray market, the manufacturer may decrease product quality as consumer valuation increases, (b) a unilateral gray market, which diverts products from the low- to the high-value market, can motivate the manufacturer to improve quality, (c) there may exist two gray markets simultaneously: one diverts products from the low- to the high-value market, and the other occurs along the reverse direction, and (d) when quality can be differentiated across markets, the manufacturer might increase quality differentiation in order to manage gray market.
Journal: International Journal of Production Research
Pages: 308-331
Issue: 1
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1638980
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1638980
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Template-Type: ReDIF-Article 1.0
Author-Name: Dong Li
Author-X-Name-First: Dong
Author-X-Name-Last: Li
Author-Name: Xiaojun Wang
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Wang
Title: Dynamic supply chain decisions based on networked sensor data: an application in the chilled food retail chain
Abstract: 
 With large volume of product flows and complex supply chain processes, more data than ever before is being generated and collected in supply chains through various tracking and sensory technologies. The purpose of this study is to show a potential scenario of using a prototype tracking tool that facilitate the utilisation of sensor data, which is often unstructured and enormous in nature, to support supply chain decisions. The research investigates the potential benefits of the chilled food chain management innovation through sensor data driven pricing decisions. Data generated and recorded through the sensor network are used to predict the remaining shelf-life of perishable foods. Numerical analysis is conducted to examine the benefit of proposed approach under various operational situations and product features. The research findings demonstrate a way of modelling pricing and potential of performance improvement in chilled food chains to provide a vision of smooth transfer and implementation of the sensor data driven supply chain management. The research finding would encourage firms in the food industry to explore innovation opportunities from big data and develop proper data driven strategies to improve their competitiveness.
Journal: International Journal of Production Research
Pages: 5127-5141
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1047976
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047976
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Template-Type: ReDIF-Article 1.0
Author-Name: Hing Kai Chan
Author-X-Name-First: Hing Kai
Author-X-Name-Last: Chan
Author-Name: Ewelina Lacka
Author-X-Name-First: Ewelina
Author-X-Name-Last: Lacka
Author-Name: Rachel W.Y. Yee
Author-X-Name-First: Rachel W.Y.
Author-X-Name-Last: Yee
Author-Name: Ming K. Lim
Author-X-Name-First: Ming K.
Author-X-Name-Last: Lim
Title: The role of social media data in operations and production management
Abstract: 
 Social media data contain rich information in posts or comments written by customers. If those data can be extracted and analysed properly, companies can fully utilise this rich source of information. They can then convert the data to useful information or knowledge, which can help to formulate their business strategy. This cannot only facilitate marketing research in view of customer behaviour, but can also aid other management disciplines. Operations management (OM) research and practice with the objective to make decisions on product and process design is a fine example. Nevertheless, this line of thought is under-researched. In this connection, this paper explores the role of social media data in OM research. A structured approach is proposed, which involves the analysis of social media comments and a statistical cluster analysis to identify the interrelationships amongst important factors. A real-life example is employed to demonstrate the concept.
Journal: International Journal of Production Research
Pages: 5027-5036
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1053998
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1053998
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Template-Type: ReDIF-Article 1.0
Author-Name: Jing Wu
Author-X-Name-First: Jing
Author-X-Name-Last: Wu
Author-Name: He Li
Author-X-Name-First: He
Author-X-Name-Last: Li
Author-Name: Zhangxi Lin
Author-X-Name-First: Zhangxi
Author-X-Name-Last: Lin
Author-Name: Khim-Yong Goh
Author-X-Name-First: Khim-Yong
Author-X-Name-Last: Goh
Title: How big data and analytics reshape the wearable device market – the context of e-health
Abstract: 
 The wearable device can be a key link between health care and big data and analytics (BDA). The benefits of BDA in health care have been widely acknowledged, but the uncertainty of the implementation of BDA has led some firms to hesitate in adopting this technology. In this research, we are keen to answer the key questions of whether the wearable device firms would adopt the BDA strategy, and how much effort they would put into it. We propose a competition model between the wearable device firms with and without BDA strategies, and consider the consumer’s preference towards BDA and network effects. Our model demonstrates that the investment on BDA directly affects the firm’s equilibrium price, market share and profit and at the same time, this strategy also affects the rival’s performances. When the firm with BDA strategy adopts different competition strategy: conservative or expansive, the outcomes of market are different. We also find that different market structures, fully covered and partially covered, have different impacts on the firms’ competition when the consumers have heterogeneous preference on BDA strategy.
Journal: International Journal of Production Research
Pages: 5168-5182
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1059521
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1059521
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Template-Type: ReDIF-Article 1.0
Author-Name: Erik Hofmann
Author-X-Name-First: Erik
Author-X-Name-Last: Hofmann
Title: Big data and supply chain decisions: the impact of volume, variety and velocity properties on the bullwhip effect
Abstract: 
 The bullwhip effect is causing inefficiencies in today’s supply chains. This study deals with the potential of big data on the improvement of the various supply chain processes. The aim of this paper is to elaborate which characteristic of big data (lever) has the greatest potential to mitigate the bullwhip effect. From previous research, starting points for big data applications are derived. By using an existing system dynamics model, the big data levers ‘velocity’, ‘volume’ and ‘variety’ are transferred into a simulation. Overall, positive impacts of all the big data levers are elaborated. Findings suggest that the data property ‘velocity’ relatively bears the greatest potential to enhance performance. The results of this research will help in justifying the application of big data in supply chain management. The paper contributes to the literature by operationalising big data in the control engineering analyses.
Journal: International Journal of Production Research
Pages: 5108-5126
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1061222
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1061222
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:17:p:5108-5126




Template-Type: ReDIF-Article 1.0
Author-Name: Sjoerd van der Spoel
Author-X-Name-First: Sjoerd
Author-X-Name-Last: van der Spoel
Author-Name: Chintan Amrit
Author-X-Name-First: Chintan
Author-X-Name-Last: Amrit
Author-Name: Jos van Hillegersberg
Author-X-Name-First: Jos
Author-X-Name-Last: van Hillegersberg
Title: Predictive analytics for truck arrival time estimation: a field study at a European distribution centre
Abstract: 
 Distribution centres (DCs) are the hubs connecting transport streams in the supply chain. The synchronisation of coming and going cargo at a DC requires reliable arrival times. To achieve this, a reliable method to predict arrival times is needed. A literature review was performed to find the factors that are reported to predict arrival time: congestion, weather, time of day and incidents. While travel time receives considerable attention, there is a gap in literature concerning arrival vs. travel/journey time prediction. None of the reviewed papers investigate arrival time: all the papers found investigate travel time. Arrival time is the consequence of travel time in combination with departure time, so though the travel time literature is applicable, the human factor involved in planning the time of departure can affect the arrival time (especially for truck drivers who have travelled the same route before). To validate the factors that influence arrival time, the authors conducted a detailed case study that includes a survey of 230 truckers, a data analysis and a data mining experiment, using real traffic and weather data. These show that although a ‘big data’ approach delivers valuable insights, the predictive power is not as high as expected; other factors, such as human or organisational factors, could influence arrival time, and it is concluded that such organisational factors should be considered in future predictive models.
Journal: International Journal of Production Research
Pages: 5062-5078
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1064183
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064183
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Template-Type: ReDIF-Article 1.0
Author-Name: Alain Yee Loong Chong
Author-X-Name-First: Alain Yee Loong
Author-X-Name-Last: Chong
Author-Name: Eugene Ch’ng
Author-X-Name-First: Eugene
Author-X-Name-Last: Ch’ng
Author-Name: Martin J. Liu
Author-X-Name-First: Martin J.
Author-X-Name-Last: Liu
Author-Name: Boying Li
Author-X-Name-First: Boying
Author-X-Name-Last: Li
Title: Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews
Abstract: 
 This study aims to investigate the contributions of online promotional marketing and online reviews as predictors of consumer product demands. Using electronic data from Amazon.com, we attempt to predict if online review variables such as valence and volume of reviews, the number of positive and negative reviews, and online promotional marketing variables such as discounts and free deliveries, can influence the demand of electronic products in Amazon.com. A Big Data architecture was developed and Node.JS agents were deployed for scraping the Amazon.com pages using asynchronous Input/Output calls. The completed Web crawling and scraping data-sets were then preprocessed for Neural Network analysis. Our results showed that variables from both online reviews and promotional marketing strategies are important predictors of product demands. Variables in online reviews in general were better predictors as compared to online marketing promotional variables. This study provides important implications for practitioners as they can better understand how online reviews and online promotional marketing can influence product demands. Our empirical contributions include the design of a Big Data architecture that incorporate Neural Network analysis which can used as a platform for future researchers to investigate how Big Data can be used to understand and predict online consumer product demands.
Journal: International Journal of Production Research
Pages: 5142-5156
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1066519
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1066519
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Template-Type: ReDIF-Article 1.0
Author-Name: J.M. Yao
Author-X-Name-First: J.M.
Author-X-Name-Last: Yao
Title: Supply chain resources integration optimisation in B2C online shopping
Abstract: 
 B2C online shopping companies must optimise their supply chain resources integration (SCRI) to provide service capacities, improve the experiences of their customers and introduce satisfactory customised services. These companies need to determine how to achieve an effective SCRI according to different customised service modes, improve their utilisation of resources and solve special problems in online shopping. This study discusses the dynamic equilibrium between the supply and demand service capacities by analysing the characteristics and service modes of SCRI in B2C. A discussion of these capacities must not only consider the traditional optimisation objectives, but also evaluate the suitability of resources from the angles of general service, emergent service and strategic potential capacities to achieve an effective SCRI. Therefore, this study considers the capacity target orientation consistency of the resource (cooperator) as an important optimisation objective and evaluates such consistency by identifying the capacity characteristic factors and introducing them into SCRI. An optimisation model and an improved ant algorithm are proposed to solve the SCRI process. The feasibility and validity of this model and algorithm are verified by demonstrating their application and illustrating their research value.
Journal: International Journal of Production Research
Pages: 5079-5094
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1074298
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1074298
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:17:p:5079-5094




Template-Type: ReDIF-Article 1.0
Author-Name: Laor Boongasame
Author-X-Name-First: Laor
Author-X-Name-Last: Boongasame
Author-Name: Punnarumol Temdee
Author-X-Name-First: Punnarumol
Author-X-Name-Last: Temdee
Author-Name: Farhad Daneshgar
Author-X-Name-First: Farhad
Author-X-Name-Last: Daneshgar
Title: A group signature based buyer coalition scheme with trustable third party
Abstract: 
 Despite the large number of existing buyer coalition schemes and increasing need for trusting relationship in buyer coalitions, no current buyer coalition scheme explicitly addresses trust issues within these schemes in a formalised manner. Without establishing a trusting relationships among various roles, many buyers may not be willing to join the coalitions. This study proposes a solution, in the form of an algorithmic design, as a response to the above need. Specific features of the proposed solution are: (i) the use of ‘group signature’ in order to guarantees anonymity within a group that results in trustfulness of the relationships and (ii) introducing a new role called ‘authority’ to maintain and implement anonymity. In addition, the proposed scheme is capable of maintaining ‘correctness’ and ‘accountability’ by both identifying misbehaved buyers as well as implementing various punishment methods.Knowledge domain of the study is the common space between three overlapping fields including Electronic Commerce, Communication Technologies and Information Systems.
Journal: International Journal of Production Research
Pages: 5050-5061
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1076946
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1076946
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen-Fu Chien
Author-X-Name-First: Chen-Fu
Author-X-Name-Last: Chien
Author-Name: Chiao-Wen Liu
Author-X-Name-First: Chiao-Wen
Author-X-Name-Last: Liu
Author-Name: Shih-Chung Chuang
Author-X-Name-First: Shih-Chung
Author-X-Name-Last: Chuang
Title: Analysing semiconductor manufacturing big data for root cause detection of excursion for yield enhancement
Abstract: 
 With the shrinking feature size of integrated circuits driven by continuous technology migrations for wafer fabrication, the control of tightening critical dimensions is critical for yield enhancement, while physical failure analysis is increasingly difficult. In particular, the yield ramp up stage for implementing new technology node involves new production processes, unstable machine configurations, big data with multiple co-linearity and high dimensionality that can hardly rely on previous experience for detecting root causes. This research aims to propose a novel data-driven approach for Analysing semiconductor manufacturing big data for low yield (namely, excursions) diagnosis to detect process root causes for yield enhancement. The proposed approach has shown practical viability to efficiently detect possible root causes of excursion to reduce the trouble shooting time and improve the production yield effectively.
Journal: International Journal of Production Research
Pages: 5095-5107
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1109153
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1109153
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:17:p:5095-5107




Template-Type: ReDIF-Article 1.0
Author-Name: Feng-Ming Tsai
Author-X-Name-First: Feng-Ming
Author-X-Name-Last: Tsai
Author-Name: Linda J.W. Huang
Author-X-Name-First: Linda J.W.
Author-X-Name-Last: Huang
Title: Using artificial neural networks to predict container flows between the major ports of Asia
Abstract: 
 Container flow information is a critical issue for port operators and liners to support their strategic planning and decision-making. This study uses artificial neural networks (ANNs) to predict container flows by considering GDP, interest rates, the value of export and import trade, the numbers of export and import containers and the number of quay cranes. ANNs are developed for data mining purposes, and the developed model can simultaneously predict container flows between the major ports of Asia. The forecasting results indicate that the prediction errors are relatively small in most selected ports, and thus shipping companies can use the container flow prediction model to make decisions concerning operations. The results can be further applied to the trend analysis of container flows among the major ports of Asia, and a community analysis of the containers was conducted for the purpose of supply chain management.
Journal: International Journal of Production Research
Pages: 5001-5010
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2015.1112046
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1112046
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:17:p:5001-5010




Template-Type: ReDIF-Article 1.0
Author-Name: Steven Ji-fan Ren
Author-X-Name-First: Steven
Author-X-Name-Last: Ji-fan Ren
Author-Name: Samuel Fosso Wamba
Author-X-Name-First: Samuel
Author-X-Name-Last: Fosso Wamba
Author-Name: Shahriar Akter
Author-X-Name-First: Shahriar
Author-X-Name-Last: Akter
Author-Name: Rameshwar Dubey
Author-X-Name-First: Rameshwar
Author-X-Name-Last: Dubey
Author-Name: Stephen J. Childe
Author-X-Name-First: Stephen J.
Author-X-Name-Last: Childe
Title: Modelling quality dynamics, business value and firm performance in a big data analytics environment
Abstract: 
 Big data analytics have become an increasingly important component for firms across advanced economies. This paper examines the quality dynamics in big data environment that are linked with enhancing business value and firm performance (FPER). The study identifies that system quality (i.e. system reliability, accessibility, adaptability, integration, response time and privacy) and information quality (i.e. completeness, accuracy, format and currency) are key to enhance business value and FPER in a big data environment. The study also proposes that the relationship between quality and FPER is mediated by business value of big data. Drawing on the resource-based theory and the information systems success literature, this study extends knowledge in this domain by linking system quality, information quality, business value and FPER.
Journal: International Journal of Production Research
Pages: 5011-5026
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1154209
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154209
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Template-Type: ReDIF-Article 1.0
Author-Name: Wen-Yu Chiang
Author-X-Name-First: Wen-Yu
Author-X-Name-Last: Chiang
Title: Discovering customer value for marketing systems: an empirical case study
Abstract: 
 Data mining technologies have been employed in a variety of business managements for discovering useful commercial knowledge or marketing model for many years. Hence, the major marketing issue for airlines is to identify and analyse valuable air travellers recently, so that airlines can attract them for enhancing the profits and growth rates. However, growth rates are always an important issue for airline industries. An empirical case of air travellers’ markets in Taiwan is implemented in this research. This research proposes a model (FSLC model, RFM model based) via the data mining technologies to discover valuable travellers for airlines. This study partitions the market of air travellers in Taiwan, and the paper generates useful association rules to find an optimised target market for dynamic marketing or CRM systems. Nevertheless, the results of this research can be applied on marketing or CRM systems of the airline industry for identifying valuable travellers. Finally, the purpose of this research is to find high-value markets for marketing or CRM systems of airlines in Taiwan, and the framework can be applied to other industries as well.
Journal: International Journal of Production Research
Pages: 5157-5167
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1231429
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1231429
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Template-Type: ReDIF-Article 1.0
Author-Name: Yoomin Ahn
Author-X-Name-First: Yoomin
Author-X-Name-Last: Ahn
Author-Name: Seoung Hwan Lee
Author-X-Name-First: Seoung Hwan
Author-X-Name-Last: Lee
Title: Classification and prediction of burr formation in micro drilling of ductile metals
Abstract: 
 In the micro drilling of precision miniature holes, the formation of exit burrs is a topic of interest, especially for ductile materials. Because such burrs are difficult to remove, it is important to be able to predict various burr types and to employ burr minimisation schemes that consider burrs’ micro-scale characteristics. In the present work, an artificial neural network (ANN) was used to predict the formation of burrs in the micro drilling of copper and brass, along with burr formation/optimisation analysis specialised for micro drills. The influence of cutting conditions, including cutting speed, feed and drill diameter, upon exit micro burr characteristics such as burr size and type was observed, analysed and classified. Based on the results, an empirical equation to predict micro burr height is proposed herein. The classification results were compared with conventional burr cases using burr control charts. Then, micro burr types were predicted by means of an ANN, using the influential parameters as input vectors. The usefulness of the proposed scheme was demonstrated by comparing the experimental and prediction/analysis results.
Journal: International Journal of Production Research
Pages: 4833-4846
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1254355
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1254355
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Template-Type: ReDIF-Article 1.0
Author-Name: Dongliang Cui
Author-X-Name-First: Dongliang
Author-X-Name-Last: Cui
Author-Name: Guoqi Feng
Author-X-Name-First: Guoqi
Author-X-Name-Last: Feng
Author-Name: Ping Zhou
Author-X-Name-First: Ping
Author-X-Name-Last: Zhou
Author-Name: Yajun Zhang
Author-X-Name-First: Yajun
Author-X-Name-Last: Zhang
Title: Parametric design-based multi-objective optimisation for high-pressure turbine disc
Abstract: 
 Mass and radial deformation are of great importance for a high-pressure turbine disc (HPTD). However, computational cost of computer-aided engineering (CAE) is too high to optimise the mutually restricted objectives. A parameterisation-based method is proposed to speed the optimisation process of HPTD: ‘body-flange’-based parametric template is used to generate CAE samples; noise-based virtual samples are implemented to enlarge the training set, a cost-effective neural network is used as fitness function of non-dominated sorting genetic algorithm-II for optimisation whose initial population is the combination of different sample sets. Experiment results show that the proposed data-driven framework reduces the engineering difficulty of multi-objective optimisation, and it has high popularisation value for optimisation of other complex products.
Journal: International Journal of Production Research
Pages: 4847-4861
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1259669
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1259669
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Template-Type: ReDIF-Article 1.0
Author-Name: A. Mousavi
Author-X-Name-First: A.
Author-X-Name-Last: Mousavi
Author-Name: H.R.A. Siervo
Author-X-Name-First: H.R.A.
Author-X-Name-Last: Siervo
Title: Automatic translation of plant data into management performance metrics: a case for real-time and predictive production control
Abstract: 
 A scalable and repeatable solution for linking shop-floor control system to a discrete event simulation (DES) model is presented. The key objective is to automatically translate the real-time data from the control system (e.g. supervisory control and data acquisition, SCADA) into KPI transfer functions of the production process. Such a seamless translation allows for the integration of engineering data emitted at plant level to higher level information system for decision-making. The solution provides a platform for researchers and practitioners to utilise the capabilities of real-time DAQ and control with that of discrete event simulation to accurately measure the key manufacturing systems performance metrics. In addition to the real-time capabilities, the predictive capabilities of the solution provide the managers to look ahead and to conduct What-if scenarios. Such capability enables line management to optimise performance and predict destabilising factors in the system ahead of time. A fully operational version of the designed solution has been deployed in a brewery’s live production system for the first time. The brewhouse production line model measures the utilisation of resources, Overall Equipment Effectiveness, and Overall Line Effectiveness in real-time and fast-forward mode simulation. The results of the predictive models (What-if-Scenarios) have been validated and verified by statistical means and direct observations. The accuracy of the estimated parameters is highly satisfactory.
Journal: International Journal of Production Research
Pages: 4862-4877
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1265682
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1265682
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Template-Type: ReDIF-Article 1.0
Author-Name: Gabriele Arcidiacono
Author-X-Name-First: Gabriele
Author-X-Name-Last: Arcidiacono
Author-Name: Rossella Berni
Author-X-Name-First: Rossella
Author-X-Name-Last: Berni
Author-Name: Luciano Cantone
Author-X-Name-First: Luciano
Author-X-Name-Last: Cantone
Author-Name: Pierpaolo Placidoli
Author-X-Name-First: Pierpaolo
Author-X-Name-Last: Placidoli
Title: Kriging models for payload distribution optimisation of freight trains
Abstract: 
 This paper deals with Kriging models applied to optimise braking performances for freight trains. More precisely, it is focused on mass distribution optimisation aimed at reducing the effects of in-train forces among vehicles, e.g. compression and tensile forces, in-train emergency braking. To this end, Kriging models are applied with covariance structure based on the Matérn function, introducing specific input parameters to better outline the payload distribution on the train, also evaluating the shape of the payload distribution. The different shapes, related to the payload distributions, have been implemented into a model through a Python routine, which has been used to ‘assemble’ the simulated trains. The analysed train carries 80% of its maximum payload capacity during an emergency braking from the speed of 30 km/h. Satisfactory results have been obtained considering compression forces, tensile forces and their sum, also considering residuals and diagnositc measures.
Journal: International Journal of Production Research
Pages: 4878-4890
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1268275
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1268275
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Template-Type: ReDIF-Article 1.0
Author-Name: Moacir Godinho Filho
Author-X-Name-First: Moacir
Author-X-Name-Last: Godinho Filho
Author-Name: Antonio Gilberto Marchesini
Author-X-Name-First: Antonio Gilberto
Author-X-Name-Last: Marchesini
Author-Name: Jan Riezebos
Author-X-Name-First: Jan
Author-X-Name-Last: Riezebos
Author-Name: Nico Vandaele
Author-X-Name-First: Nico
Author-X-Name-Last: Vandaele
Author-Name: Gilberto Miller Devós Ganga
Author-X-Name-First: Gilberto Miller Devós
Author-X-Name-Last: Ganga
Title: The extent of knowledge of Quick Response Manufacturing principles: an exploratory transnational study
Abstract: 
 The main goal of this research is to identify whether companies that have implemented the Quick Response Manufacturing (QRM) approach have full knowledge of the QRM principles or have merely applied the elements (principles and tools) that have a close relationship with Lean Manufacturing. Based on a review of the literature regarding the QRM principles, an exploratory survey was conducted for over 20 manufacturing companies from Brazil, Europe and the USA that operate in an Engineer or Make to Order environment system and explicitly have conducted QRM journeys. The results of the present study show that (i) the surveyed companies have difficulty knowing and applying some of the exclusive elements of this approach, even if they started implementing QRM several years ago; (ii) the surveyed companies’ knowledge degree over QRM exclusive elements is apparently higher among US-based companies due to better trained employees and better dissemination and awareness of the QRM exclusive elements; and (iii) a mentality based on productivity, low costs and due date delivery was identified as the main barrier for companies to achieve a higher knowledge degree regarding QRM.
Journal: International Journal of Production Research
Pages: 4891-4911
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1268729
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1268729
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Template-Type: ReDIF-Article 1.0
Author-Name: Jung Young Lee
Author-X-Name-First: Jung Young
Author-X-Name-Last: Lee
Author-Name: Morgan Swink
Author-X-Name-First: Morgan
Author-X-Name-Last: Swink
Author-Name: Temyos Pandejpong
Author-X-Name-First: Temyos
Author-X-Name-Last: Pandejpong
Title: Team diversity and manufacturing process innovation performance: the moderating role of technology maturity
Abstract: 
 This research studies how technological maturity in manufacturing process innovation (MPI) projects moderates the impacts of different types of team diversity on technical success. While researchers consider the variety aspect of team diversity to be beneficial as a rich source of information, they consider disparity and separation to be detrimental as sources of social barriers to information processing. However, demographic manifestations of diversity involve a combination of these aspects. We therefore posit that technology maturity is an important moderator which may raise or lower the influence of one diversity aspect over another. Specifically, we examine five manifestations of project team diversity, including three types of variety (functional variety, full-time/part-time variety, location tenure variety) and two types of disparity (education level disparity, experience level disparity). Results from 183 MPI projects in US companies indicate that technology maturity negatively moderates the relationship between functional variety and MPI technical performance. It positively moderates the relationships between experience level disparity and MPI technical performance, and between location tenure variety and MPI technical performance. The impacts of education level disparity and full-time/part-time variety do not appear to be moderated by technology maturity.
Journal: International Journal of Production Research
Pages: 4912-4930
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1272765
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1272765
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Template-Type: ReDIF-Article 1.0
Author-Name: Satya S. Chakravorty
Author-X-Name-First: Satya S.
Author-X-Name-Last: Chakravorty
Author-Name: Douglas N. Hales
Author-X-Name-First: Douglas N.
Author-X-Name-Last: Hales
Title: Sustainability of process improvements: an application of the experiential learning model (ELM)
Abstract: 
 Despite the pervasiveness of process improvement (Lean or Six Sigma) programmes, there is a rising concern regarding the sustainability of these programmes. Several studies point out that initial operational efficiency gains as a result of these programmes simply disappear over time. Using process improvement implementation experiences in an aircraft manufacturing and distribution operation, we studied long-term sustainability of process improvement events. We found that process owners of successful improvement events applied experiential learning model (ELM). The ELM is a cycle of – (1) concrete experience, (2) reflective observations, and (3) abstract conceptualizations, and (4) active experimentation. This study finds that when the ELM cycle is repeated many times over an extended period to continuously improve, and documented using A3 reports, that the improvement is sustained.
Journal: International Journal of Production Research
Pages: 4931-4947
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1277278
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1277278
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Template-Type: ReDIF-Article 1.0
Author-Name: Nadeera Gnan Tilshan Gunaratne
Author-X-Name-First: Nadeera Gnan Tilshan
Author-X-Name-Last: Gunaratne
Author-Name: Malihe Akhavan Abdollahian
Author-X-Name-First: Malihe Akhavan
Author-X-Name-Last: Abdollahian
Author-Name: Shamsul Huda
Author-X-Name-First: Shamsul
Author-X-Name-Last: Huda
Author-Name: John Yearwood
Author-X-Name-First: John
Author-X-Name-Last: Yearwood
Title: Exponentially weighted control charts to monitor multivariate process variability for high dimensions
Abstract: 
 Multivariate monitoring of industrial or clinical procedures often involves more than three correlated quality characteristics and the status of the process is judged using a sample of size one. Majority of existing control charts for monitoring process variability for individual observations are capable of monitoring up to three characteristics. One of the hurdles in designing optimal control charts for large dimension data is the enormous computing resources and time that is required by simulation algorithm to estimate the charts parameters. This paper proposes a novel algorithm based on Parallelised Monte Carlo simulation to improve the ability of the Multivariate Exponentially Weighted Mean Squared Deviation and Multivariate Exponentially Weighted Moving Variance charts to monitor process variability for high dimensions in a computationally efficient way. Different techniques have been deployed to reduce computing space and execution time. The optimal control limits (L) to detect small, medium and large shifts in the covariance matrix of up to 15 characteristics are provided. Furthermore, utilising the large number of optimal L values generated by the algorithm enabled authors to develop exponential decay functions to predict L values. This eliminates the need for further execution of the parallelised Monte Carlo simulation.
Journal: International Journal of Production Research
Pages: 4948-4962
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1278081
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1278081
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Template-Type: ReDIF-Article 1.0
Author-Name: Kuen-Suan Chen
Author-X-Name-First: Kuen-Suan
Author-X-Name-Last: Chen
Author-Name: Kung-Jeng Wang
Author-X-Name-First: Kung-Jeng
Author-X-Name-Last: Wang
Author-Name: Tsang-Chuan Chang
Author-X-Name-First: Tsang-Chuan
Author-X-Name-Last: Chang
Title: A novel approach to deriving the lower confidence limit of indices , , and  in assessing process capability
Abstract: 
 Process capability indices (PCIs) are widely used as a measure of process potential and process performance. Unfortunately, the use of sample data to estimate PCIs means that any error in the sampling can introduce considerable uncertainty into the assessment of process capability. This necessitates the use of the lower confidence limit (LCL) in the estimation of minimum process capability. Furthermore, the complexity of sampling distributions of the PCIs greatly hinders interval estimation, such that only an approximate or asymptotic LCL can be achieved. This paper proposes a novel approach to deriving the 1001-α%$100\left( {1 - \alpha } \right)\%$ LCL of indices Cpu, Cpl and Cpk using Boole’s inequality and DeMorgan’s theorem. This approach is based on subsample data collected from a stable process. Hypothesis testing is also used to determine whether the process is capable of satisfying the quality requirements of customers. We calculated the critical values of the PCIs for various significance levels, capability requirements and sample sizes. Finally, we present analysis of two cases to demonstrate the applicability of the proposed approach.
Journal: International Journal of Production Research
Pages: 4963-4981
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1282644
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1282644
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Template-Type: ReDIF-Article 1.0
Author-Name: Kyoung-jae Kim
Author-X-Name-First: Kyoung-jae
Author-X-Name-Last: Kim
Author-Name: Hyunchul Ahn
Author-X-Name-First: Hyunchul
Author-X-Name-Last: Ahn
Title: Recommender systems using cluster-indexing collaborative filtering and social data analytics
Abstract: 
 As a result of the extensive variety of products available in e-commerce settings during the last decade, recommender systems have been highlighted as a means of mitigating the problem of information overload. Collaborative filtering (CF) is the most widely used algorithm to build such systems, and improving the predictive accuracy of CF-based recommender systems has been a major research challenge. This research aims to improve the prediction accuracy of CF by incorporating social network analysis (SNA) and clustering techniques. Our proposed model identifies the most influential people in an online social network by SNA and then conducts clustering analysis using these people as initial centroids (cluster centres). Finally, the model makes recommendations using cluster-indexing CF based on the clustering outcomes. In this step, our model adjusts the effect of neighbours in the same cluster as the target user to improve prediction accuracy by reflecting hidden information about his or her social community. The experimental results indicate that the proposed model outperforms other comparison models, including conventional CF, with statistical significance.
Journal: International Journal of Production Research
Pages: 5037-5049
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1287443
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1287443
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Template-Type: ReDIF-Article 1.0
Author-Name: Feng Li
Author-X-Name-First: Feng
Author-X-Name-Last: Li
Author-Name: Jian Song
Author-X-Name-First: Jian
Author-X-Name-Last: Song
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Liang Liang
Author-X-Name-First: Liang
Author-X-Name-Last: Liang
Title: Using common weights and efficiency invariance principles for resource allocation and target setting
Abstract: 
 Data envelopment analysis (DEA) has proven to be a useful technique for evaluating the relative performance of comparable and homogeneous decision-making units (DMUs). In recent years, DEA-based resource allocation and target setting approaches have gained more and more attention from both practitioners and academic researchers. In this paper, we propose a new mechanism to simultaneously adopt the principles of common weights and efficiency invariance in allocating multiple resources and setting multiple targets among DMUs. To obtain the final plan, we minimise the deviation between the possible plan based on common weights and another feasible plan emphasising efficiency invariance. If the minimum deviation equals zero, one optimal plan will be determined. In general situations, however, the proposed approach will present two plans that have a non-zero deviation. One is generated using a common set of weights for all DMUs in such a way that the change of efficiencies is minimised, while the other is generated by strictly keeping efficiency scores unchanged yet having similar or even identical weights on input–output measures for each DMU to the utmost extent. The efficacy and usefulness of the proposed approach are demonstrated using a numerical example from previous literature and an empirical application to an urban bus company in China.
Journal: International Journal of Production Research
Pages: 4982-4997
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1287450
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1287450
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 5183-5183
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1322671
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1322671
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Template-Type: ReDIF-Article 1.0
Author-Name: Kim Hua Tan
Author-X-Name-First: Kim Hua
Author-X-Name-Last: Tan
Author-Name: Guojun Ji
Author-X-Name-First: Guojun
Author-X-Name-Last: Ji
Author-Name: Chee Peng Lim
Author-X-Name-First: Chee Peng
Author-X-Name-Last: Lim
Author-Name: Ming-Lang Tseng
Author-X-Name-First: Ming-Lang
Author-X-Name-Last: Tseng
Title: Using big data to make better decisions in the digital economy
Abstract: 
 The question this special issue would like to address is how to harvest big data to help decision-makers to deliver better fact-based decisions aimed at improving performance or to create better strategy? This special issue focuses on the big data applications in supporting operations decisions, including advanced research on decision models and tools for the digital economy. Responds to this special issue was great and we have included many high-quality papers. We are pleased to present 13 of the best papers. The techniques presented include data mining, simulation and expert system with applications span across online reviews, food retail chain to e-health.
Journal: International Journal of Production Research
Pages: 4998-5000
Issue: 17
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1331051
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1331051
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhiyang Jia
Author-X-Name-First: Zhiyang
Author-X-Name-Last: Jia
Author-Name: Liang Zhang
Author-X-Name-First: Liang
Author-X-Name-Last: Zhang
Title: Serial production lines with geometric machines and finite production runs: performance analysis and system-theoretic properties
Abstract: 
 A production run is typically referred to as a group of identical goods that is produced by a particular manufacturing process. In many discrete manufacturing practices, the manufacturing activity is carried out by deploying a series of production runs of different products according to customer orders. If the volume of a production run is relatively small and process changeovers are necessary, the production system operates partially (or entirely) in the transient regime, especially at the beginning and near the end of a production run. In this case, the traditional steady-state analysis approach may become inapplicable. In this paper, we consider finite production run-based manufacturing in serial lines with machines obeying the geometric reliability model and buffers having finite capacity. Exact Markovian analysis is first used to derive the closed-form formulae to calculate the transient performance of the production line during a production run as well as the distribution, mean, and standard deviation of its completion time in one- and two-machine lines. For multi-machine lines, an aggregation-based approach is proposed to approximate the system performance measures with high accuracy and computational efficiency. In addition, system-theoretic properties of production run completion time with respect to machine and buffer parameters are discussed.
Journal: International Journal of Production Research
Pages: 2247-2262
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1513658
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1513658
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Template-Type: ReDIF-Article 1.0
Author-Name: Cheng Zhang
Author-X-Name-First: Cheng
Author-X-Name-Last: Zhang
Author-Name: Haihong Huang
Author-X-Name-First: Haihong
Author-X-Name-Last: Huang
Author-Name: Lei Zhang
Author-X-Name-First: Lei
Author-X-Name-Last: Zhang
Author-Name: Zhifeng Liu
Author-X-Name-First: Zhifeng
Author-X-Name-Last: Liu
Title: Semi-quantitative method for task planning in product eco-design
Abstract: 
 Ensuring the environmental sustainability of products is challenging because it involves all the stages and processes throughout product life cycle. Product eco-design is essential to achieve it. In the proposed methodology, product eco-design is implemented based on five eco-design elements, namely, function, material, geometric structure, connection relationship and manufacturing process. However, because of the fragmentation of existing eco-design tools, the gap between eco-design evaluation and eco-design optimisation requires a new mechanism to seamlessly integrate them for efficient industrial applications. A new checklist tool called Checklist of Product Eco-design Optimisation Potential (CPEOP) is developed to assess product eco-design optimisation potential. Based on the new tool, optimisation effect of product eco-design can be quantitatively assessed. Furthermore, a novel semi-quantitative method for task planning in product eco-design is proposed, which involves evaluating the product with CPEOP, screening candidates for eco-design and determining the candidates’ optimisation directions. The uncertainties arising from CPEOP and enterprise design status quo are further analysed. Subsequently, a case study on a refrigerator is conducted to elucidate the process of the method and reveal its potential. The proposed method is then discussed through a comparison with two mainstream eco-design tools.
Journal: International Journal of Production Research
Pages: 2263-2280
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1514474
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1514474
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenliang Chen
Author-X-Name-First: Wenliang
Author-X-Name-Last: Chen
Author-Name: Zheng Wang
Author-X-Name-First: Zheng
Author-X-Name-Last: Wang
Title: Analysis of the steady state probability distribution of a manufacturing system under the prioritised hedging point control policy
Abstract: 
 In order to evaluate the average production cost of a multi-product-type, multi-stage and multi-parallel-machine manufacturing system (denoted as mP/mS/mM), one of the effective ways is to obtain its steady-state probability distribution. Because the two-product-type and multi-parallel-machine system that demand backlog is not allowed can be considered as a basic building block of the mP/mS/mM system, we begin by investigating the method of obtaining its steady-state probability distribution under the prioritised hedging point control policy. Although the shape of the distribution domains of the work-in-process (WIP) levels influences the steady-state probability balance equations, we develop a unified form of the marginal probability balance equations for all the possible shapes of distribution domains, which can be used to calculate the marginal probability distribution for each product type for the two-product-type and multi-parallel-machine system. Furthermore, we extend this analysis method to both the multiple-product-type, multi-parallel-machine, and single-stage system and the more complex mP/mS/mM system, and propose a method to obtain their approximate marginal probability distributions of the WIP levels. Finally, numerical experiments are conducted to verify the accuracy of the proposed method of analysing the steady-state probability distribution of an mP/mS/mM system.
Journal: International Journal of Production Research
Pages: 2281-2303
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1514475
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1514475
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2281-2303




Template-Type: ReDIF-Article 1.0
Author-Name: Vinay Gonela
Author-X-Name-First: Vinay
Author-X-Name-Last: Gonela
Author-Name: Dalila Salazar
Author-X-Name-First: Dalila
Author-X-Name-Last: Salazar
Author-Name: Jun Zhang
Author-X-Name-First: Jun
Author-X-Name-Last: Zhang
Author-Name: Atif Osmani
Author-X-Name-First: Atif
Author-X-Name-Last: Osmani
Author-Name: Iddrisu Awudu
Author-X-Name-First: Iddrisu
Author-X-Name-Last: Awudu
Author-Name: Barbara Altman
Author-X-Name-First: Barbara
Author-X-Name-Last: Altman
Title: Designing a sustainable stochastic electricity generation network with hybrid production strategies
Abstract: 
 This paper aims to design a sustainable stochastic electricity production network where fossil fuels-based, biomass-based, and co-firing-based production strategies are simultaneously considered in order to take advantage of all the three production strategies. A multi-objective stochastic mixed integer linear programming model is proposed to achieve economic feasibility, as well as environmental and social benefits under multiple uncertainties. The model is solved by using the improved augmented epsilon constraint method. A case study is used to illustrate the effectiveness of the proposed model. Pareto optimal analysis is conducted to understand the trade-off between economic, environmental, and social aspects of sustainability.
Journal: International Journal of Production Research
Pages: 2304-2326
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1516900
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1516900
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Template-Type: ReDIF-Article 1.0
Author-Name: Zelin Zhang
Author-X-Name-First: Zelin
Author-X-Name-Last: Zhang
Author-Name: Jianghua Wu
Author-X-Name-First: Jianghua
Author-X-Name-Last: Wu
Author-Name: Feiqiong Wei
Author-X-Name-First: Feiqiong
Author-X-Name-Last: Wei
Title: Refurbishment or quality recovery: joint quality and pricing decisions for new product development
Abstract: 
 Refurbishment and quality recovery, as two important strategies of reverse logistics, have been widely used for consumer durables, especially consumer electronics. This trend is driven by manufacturers’ profit-seeking behaviours and the increasing environmental concerns of society. This study investigates and compares the optimal emergence of these two strategies when product quality is endogenous. Model analyses provide several notable insights. First, we find that the refurbishment strategy dominates the quality recovery strategy when the fraction of the recoverable quality-inducing components in the defective product is low enough. Moreover, when the refurbishment strategy emerges as the optimum, the quality and price of the new product as well as the total realised sales of both new and refurbished products are consistently higher than those with the quality recovery strategy. In addition, when either the refurbishment or quality recovery strategy emerges as the optimum, the overall consumer surplus is also enhanced. Finally, in the model generalisation, we show that a synthetic strategy with which some of the returned defective products are refurbished and others are remanufactured through quality recovery can certainly increase the manufacturers’ profit compared to either one of them when the fraction of the recoverable quality-inducing components in the defective product is moderate.
Journal: International Journal of Production Research
Pages: 2327-2343
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1516904
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1516904
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Template-Type: ReDIF-Article 1.0
Author-Name: Sue E. Stankus
Author-X-Name-First: Sue E.
Author-X-Name-Last: Stankus
Author-Name: Krystel K. Castillo-Villar
Author-X-Name-First: Krystel K.
Author-X-Name-Last: Castillo-Villar
Title: An Improved multivariate generalised likelihood ratio control chart for the monitoring of point clouds from 3D laser scanners
Abstract: 
 Statistical quality control techniques are crucial for manufacturing companies with tight tolerances but high-volume data generated from laser scanners has pushed the limits of traditional control charts. In a previous work, multivariate generalised likelihood ratio control (MGLR) chart was used to identify process shifts and locate defects on artefacts by converting 3D point cloud data to a 2D image. This paper presents a 3D MGLR control chart that retains the 3D nature of the point cloud data and uses a Fourier transform of the point errors. The average run length (ARL1) of the proposed 3D MGLR was tested using a designed experiment with ten replications and varying the number of past scans and number of Regions of Interest (ROIs). The designed experiment was repeated using three defects: incorrect surface curvature, surface scratch, and surface dent. The proposed methodology identified the dent while the prior methodology never identified it. In addition, the proposed methodology had a significantly shorter ARL1 than the prior methodology for the scratch and no significant difference in the ARL1 for the incorrect surface curvature. The proposed 3D MGLR control chart enabled the usage of 3D data without needing to convert it to a 2D image.
Journal: International Journal of Production Research
Pages: 2344-2355
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1518600
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518600
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Template-Type: ReDIF-Article 1.0
Author-Name: Cinthia de Azevêdo Faustino
Author-X-Name-First: Cinthia de Azevêdo
Author-X-Name-Last: Faustino
Author-Name: Cláudia Fabiana Gohr
Author-X-Name-First: Cláudia Fabiana
Author-X-Name-Last: Gohr
Author-Name: Luciano Costa Santos
Author-X-Name-First: Luciano Costa
Author-X-Name-Last: Santos
Title: An approach for evaluating collaboration attributes in cluster-based companies
Abstract: 
 This paper presents an approach for evaluating collaboration attributes in companies operating in industrial clusters. From the literature review, we identified governance, geographic proximity, and trust as the main collaboration attributes in industrial clusters. For each of them, there is a set of related sub-attributes that composed the evaluation model. For developing the model, we used the graph theoretic approach (GTA), a methodology for multi-attribute assessment that considers interdependencies among elements of a system to provide an overall evaluation. We applied the model to five companies of a furniture cluster. The results showed the model allows for systematizing relationship management because it highlights the collaboration attributes that need to be improved. Furthermore, the application of the model may contribute to encouraging companies to develop collaborative practices.
Journal: International Journal of Production Research
Pages: 2356-2371
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1518604
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518604
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2356-2371




Template-Type: ReDIF-Article 1.0
Author-Name: Sihan Huang
Author-X-Name-First: Sihan
Author-X-Name-Last: Huang
Author-Name: Guoxin Wang
Author-X-Name-First: Guoxin
Author-X-Name-Last: Wang
Author-Name: Yan Yan
Author-X-Name-First: Yan
Author-X-Name-Last: Yan
Title: Delayed reconfigurable manufacturing system
Abstract: 
 Reconfigurable manufacturing systems (RMS) is a new manufacturing paradigm aiming at providing exactly functionality and capacity needed and exactly when needed. Reconfiguration is the main method to achieve this goal. But, the reconfiguration is an interruption to production activities causing production loss and system ramp-up problem and the ‘exact functionality’ may increase the reconfiguration efforts and aggravate the production loss and the ramp-up time. Therefore, a special RMS – delayed reconfigurable manufacturing system (D-RMS) is proposed to promote the practicality of RMS. Starting from the RMS built around part family with the characteristic of delayed differentiation, whose reconfiguration activities mainly occur in the latter stages of manufacturing system and the former stages have the potential to maintain partial production activities to reduce production loss during reconfiguration. Inspired from this, the basic structure of RMS is divided into two subsystems, subsystem 1 is capable of maintain partial production with a certain more functionality than needed, subsystem 2 reconfigure to provide exactly functionality and capacity of a specific part exactly when needed. And then, the benefits of D-RMS are analysed from inventory and ramp-up time aspects. Finally, a case study is presented to show the implementation process of D-RMS and validates the practicability of D-RMS.
Journal: International Journal of Production Research
Pages: 2372-2391
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1518605
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518605
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Template-Type: ReDIF-Article 1.0
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Title: An integrated storage assignment method for manual order picking warehouses considering cost, workload and posture
Abstract: 
 This paper presents an integrated storage assignment method for low-level picker-to-parts order picking warehouses taking into account economic and ergonomic objectives. Three different pallet rack layouts are studied in this paper, namely (a) picking from full pallets on the floor, (b) picking from half-pallets on the floor, and (c) picking from half-pallets on the upper rank of the shelf. First, cost functions are developed to assess the total order picking performance impact of these different pallet rack layouts. Second, with regard to workload, the metabolic cost and energy expenditure rates for picking from the different rack layouts under study are derived. Third, for assessing the working posture during order picking, the Ovako Working Posture Analysing System index is used where the required data is collected using a motion capturing system. The developed models are combined to propose a heuristic storage assignment procedure that supports the decision of which item to store on which pallet. The developed storage assignment method is then applied to an industrial case study. The results of the paper support warehouse managers in assessing the order picking storage assignment from an ergonomics viewpoint and in estimating its impact on financial order picking performance.
Journal: International Journal of Production Research
Pages: 2392-2408
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1518609
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518609
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Template-Type: ReDIF-Article 1.0
Author-Name: Muh. Khoirul Khakim Habibi
Author-X-Name-First: Muh. Khoirul Khakim
Author-X-Name-Last: Habibi
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Author-Name: Van-Dat Cung
Author-X-Name-First: Van-Dat
Author-X-Name-Last: Cung
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Sample average approximation for multi-vehicle collection–disassembly problem under uncertainty
Abstract: 
 The implementation of the circular economy is increasingly supported by many governments. It is performed by integrating the activities of reverse supply chain (RSC) into those of forward supply chain. However, many companies that traditionally focus on the activities of forward supply chain have decided to collaborate with third-party reverse logistics providers to manage the RSC. This collaboration motivates the work presented in this paper to propose better decisions for decision makers in the providers under the fact that integrating decisions of the collection of End-of-Life products and their disassembly process proposes a RSC with better performance. In this paper, an integrated problem concerning those decisions is presented and formalised. It also deals with the uncertainty of the quality and the quantity of products as well as the demands of the associated components. Two approximate methods are developed to provide the solutions.
Journal: International Journal of Production Research
Pages: 2409-2428
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1519262
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1519262
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2409-2428




Template-Type: ReDIF-Article 1.0
Author-Name: Fansen Kong
Author-X-Name-First: Fansen
Author-X-Name-Last: Kong
Title: Development of metric method and framework model of integrated complexity evaluations of production process for ergonomics workstations
Abstract: 
 Staff in manufacturing sites not only need certain physical requirements for their allotted tasks but also utilise a large amount of information processing in the looming industrial age 4.0. This work established the Principles of Information Processing Economy in the production process and proposed a framework model of integrated complexity evaluation method for the production process, which combines both physical and cognitive loads while accounting for the effect of time stress. The method proposed in this study can be used for ergonomics evaluation of workstations. Compared with traditional evaluation methods, this method has good flexibility to account for the changes in labour loads in the industrial 4.0 eras and the role of various intelligent auxiliary systems. The proposed operational framework model can provide useful information for task assignment, operator selection and training, work organisation, and performance prediction.
Journal: International Journal of Production Research
Pages: 2429-2445
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1519266
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1519266
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Template-Type: ReDIF-Article 1.0
Author-Name: Zouhour Guiras
Author-X-Name-First: Zouhour
Author-X-Name-Last: Guiras
Author-Name: Sadok Turki
Author-X-Name-First: Sadok
Author-X-Name-Last: Turki
Author-Name: Nidhal Rezg
Author-X-Name-First: Nidhal
Author-X-Name-Last: Rezg
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Optimal maintenance plan for two-level assembly system and risk study of machine failure
Abstract: 
 This paper deals with the optimisation of two-levels assembly system planning. This system is composed of a single machine, inventories at levels 1 and 2 for stock keeping components to assembly and final assembled product. It assumed that the machine processes all assembly operations and is subject to random failure. A mathematical model is developed to incorporate a supply planning for two-level assembly systems under stochastic lead times and breakdowns machine. A preventive maintenance plan is carried out to reduce the frequency of the corrective maintenance actions. This work has double goals. The first one is to find the optimal order release dates for the different components at level 2 and the optimal preventive maintenance plan. The second one is to quantify the risk due to machine failures which have an impact on the lead-time of the finished product. To consider the maintenance actions, preventive maintenance actions are perfectly performed to restore the machine to state “as good as new”, minimal repair is considered at failure. The model minimises the total cost, which is the sum of inventory holding cost for components at levels 1 and 2, backlogging and inventory holding cost for the finished products and maintenance costs. To illustrate the effectiveness of the proposed model, different meta-heuristics are applied; the genetic algorithm shows the most suited to our analytical model, the optimal release date founded by this algorithm allows finding the optimal preventive maintenance plan. The obtained optimal maintenance planning is used in the risk assessment in order to find the threshold repair period that avoids lost profit.
Journal: International Journal of Production Research
Pages: 2446-2463
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1521017
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521017
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2446-2463




Template-Type: ReDIF-Article 1.0
Author-Name: Lei Zhang
Author-X-Name-First: Lei
Author-X-Name-Last: Zhang
Author-Name: Xuening Chu
Author-X-Name-First: Xuening
Author-X-Name-Last: Chu
Author-Name: Deyi Xue
Author-X-Name-First: Deyi
Author-X-Name-Last: Xue
Title: Identification of the to-be-improved product features based on online reviews for product redesign
Abstract: 
 Acquisition of customer needs usually serves as the basis for the identification of to-be-improved features for the product redesign process. However, the customer's true needs tend to be non-obvious and are difficult to extract from the data source like interviews or market survey. In the era of Big Data, with the advances in e-commerce, the customer's online review has become one of the most important data source to reveal the insight of customer's preference. In this paper, an online-review-based approach is introduced to identify the to-be-improved product features. The product features and corresponding opinions are extracted and reduced based on the semantic similarity. A structured preference model based on the semantic orientation analysis is constructed. A redesign index is subsequently introduced to measure the priority of redesign for each feature, and a target feature selection model is created to identify the to-be-improved features from candidate features considering engineering cost, redesign lead time and technical risk. A case study for smartphones is developed to demonstrate the effectiveness of the developed approach. In the future study, the online reviews may be combined with the traditional survey data to provide a more effective and reliable identification on the to-be-improved product features.
Journal: International Journal of Production Research
Pages: 2464-2479
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1521019
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521019
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Template-Type: ReDIF-Article 1.0
Author-Name: Abdelhakim Khatab
Author-X-Name-First: Abdelhakim
Author-X-Name-Last: Khatab
Author-Name: Claver Diallo
Author-X-Name-First: Claver
Author-X-Name-Last: Diallo
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Author-Name: Uday Venkatadri
Author-X-Name-First: Uday
Author-X-Name-Last: Venkatadri
Title: Integrated production quality and condition-based maintenance optimisation for a stochastically deteriorating manufacturing system
Abstract: 
 This paper investigates the problem of optimally integrating production quality and condition-based maintenance in a stochastically deteriorating single- product, single-machine production system. Inspections are periodically performed on the system to assess its actual degradation status. The system is considered to be in ‘fail mode’ whenever its degradation level exceeds a predetermined threshold. The proportion of non-conforming items, those that are produced during the time interval where the degradation is beyond the specification threshold, are replaced either via overtime production or spot market purchases. To optimise preventive maintenance costs and at the same time reduce production of non-conforming items, the degradation of the system must be optimally monitored so that preventive maintenance is carried out at appropriate time intervals. In this paper, an integrated optimisation model is developed to determine the optimal inspection cycle and the degradation threshold level, beyond which preventive maintenance should be carried out, while minimising the sum of inspection and maintenance costs, in addition to the production of non-conforming items and inventory costs. An expression for the total expected cost rate over an infinite time horizon is developed and solution method for the resulting model is discussed. Numerical experiments are provided to illustrate the proposed approach.
Journal: International Journal of Production Research
Pages: 2480-2497
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1521021
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521021
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2480-2497




Template-Type: ReDIF-Article 1.0
Author-Name: Qiang Zhang
Author-X-Name-First: Qiang
Author-X-Name-Last: Zhang
Author-Name: Ping Liu
Author-X-Name-First: Ping
Author-X-Name-Last: Liu
Author-Name: Jürgen Pannek
Author-X-Name-First: Jürgen
Author-X-Name-Last: Pannek
Title: Combining MPC and integer operators for capacity adjustment in job-shop systems with RMTs
Abstract: 
 With today's worldwide competition, manufacturing companies are faced with challenges to respond to volatile market demands quickly and flexibly while maintaining a cost-effective level of production. Capacity adjustment is one of the major approaches to cope with such uncertain fluctuations, balance capacity and load and improve the effectiveness of manufacturing control. Instead of flexible staffs, working time and outsourcing, in this paper, we consider a machinery-based capacity adjustment via Reconfigurable Machine Tools (RMTs) to compensate for unpredictable events. To include these tools effectively on the operational and tactical layer, we propose a complementing feedback approach using model predictive control (MPC) to identify the potential of RMTs for a better compliance with logistics objectives and a sustainable demand oriented capacity allocation. To this end, we formulate a reconfiguration rule for the determination of the triggered RMTs and propose three strategies for resolving the integer assignment of RMTs: floor operator, genetic algorithm as well as branch and bound. Utilising simulation, we demonstrate the effectiveness of the proposed method for a four-workstation job-shop system.
Journal: International Journal of Production Research
Pages: 2498-2513
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1521022
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521022
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Ma
Author-X-Name-First: Andrew
Author-X-Name-Last: Ma
Author-Name: Aydin Nassehi
Author-X-Name-First: Aydin
Author-X-Name-Last: Nassehi
Author-Name: Chris Snider
Author-X-Name-First: Chris
Author-X-Name-Last: Snider
Title: Anarchic manufacturing
Abstract: 
 This paper introduces anarchic manufacturing, an extremely distributed planning and control philosophy, as the methodology for planning and controlling future smart factories. Anarchic manufacturing delegates decision-making authority and autonomy to the lowest level of entities in system elements with no centralised control or oversight. It is often postulated that traditional hierarchical structures may not be well suited to manage the state-of-the-art hyper-connected smart factories due to their reliance on communication between management layers. Distributed systems, on the other hand, are commonly perceived to be inherently more flexible, robust and adaptable than hierarchical systems due to their structure. This paper characterises distributed systems by evaluating the relative flexibility of a representative hierarchical system against an anarchic system in a job shop scenario. Multi-agent-based simulation is used to model both hierarchical and anarchic systems, which are tested for flexibility following the Taguchi method and compared against Taillard's benchmark job shop problems for overall performance. The results show that the anarchic system performs as well as the hierarchical system when subjected to unforeseen disruption, refuting the argument that hierarchical systems are too rigid and distributed systems are inherently more flexible. However, anarchic manufacturing systems, which show adaptability and self-optimising traits, provide a platform to potentially enable the emerging digital manufacturing paradigm through the free market structure especially when bandwidth for communications is limited.
Journal: International Journal of Production Research
Pages: 2514-2530
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1521534
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521534
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Template-Type: ReDIF-Article 1.0
Author-Name: Faycal A. Touzout
Author-X-Name-First: Faycal A.
Author-X-Name-Last: Touzout
Author-Name: Lyes Benyoucef
Author-X-Name-First: Lyes
Author-X-Name-Last: Benyoucef
Title: Multi-objective sustainable process plan generation in a reconfigurable manufacturing environment: exact and adapted evolutionary approaches
Abstract: 
 Achieving competitiveness in nowadays manufacturing market goes through being cost and time-efficient as well as environmentally harmless. Reconfigurable manufacturing system (RMS) is a paradigm that is able to meet these challenges due to its scalability and integrability. In this paper, we aim to solve the multi-objective sustainable process plan generation problem in a reconfigurable environment. In addition to the total production cost and the completion time, we use the amount of greenhouse gases (GHG) emitted during the manufacturing process as a sustainability criterion. We propose an iterative multi-objective integer linear programming (I-MOILP) approach and its comparison with adapted versions of the two well-known evolutionary algorithms, respectively, the Archived Multi-Objective Simulated Annealing (AMOSA) and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Moreover, we study the influence of the probabilities of genetic operators on the convergence of the adapted NSGA-II. To illustrate the applicability of the three approaches, an example is presented and obtained numerical results analysed.
Journal: International Journal of Production Research
Pages: 2531-2547
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1522006
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1522006
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2531-2547




Template-Type: ReDIF-Article 1.0
Author-Name: Nadia Bahria
Author-X-Name-First: Nadia
Author-X-Name-Last: Bahria
Author-Name: Anis Chelbi
Author-X-Name-First: Anis
Author-X-Name-Last: Chelbi
Author-Name: Hanen Bouchriha
Author-X-Name-First: Hanen
Author-X-Name-Last: Bouchriha
Author-Name: Imen Harbaoui Dridi
Author-X-Name-First: Imen Harbaoui
Author-X-Name-Last: Dridi
Title: Integrated production, statistical process control, and maintenance policy for unreliable manufacturing systems
Abstract: 
 The objective of this paper is to develop an integrated approach for the joint control of production, maintenance and quality for batch manufacturing systems. We consider such systems that are subject to degradation which is at the origin of the production of defective units. The quality control of lots produced is performed using an ‘x-bar’ control chart. This graphical tool will allow estimating the quality of the batch being produced and possibly undertake perfect preventive or corrective maintenance actions on the production system. A buffer stock is built to maintain continuity of supply during maintenance actions. The incurred total cost includes setup cost, inventory costs, the cost of unused products, maintenance costs and quality costs. Decision variables include the buffer stock size, the sample size, the sampling interval, the surveillance and the control limits of the control chart. Numerical experiments and sensitivity analyses are provided to evaluate the effectiveness of the proposed control policy and the robustness of the solving approach.
Journal: International Journal of Production Research
Pages: 2548-2570
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1530472
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530472
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Template-Type: ReDIF-Article 1.0
Author-Name: Pai Zheng
Author-X-Name-First: Pai
Author-X-Name-Last: Zheng
Author-Name: Yuan Lin
Author-X-Name-First: Yuan
Author-X-Name-Last: Lin
Author-Name: Chun-Hsien Chen
Author-X-Name-First: Chun-Hsien
Author-X-Name-Last: Chen
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Title: Smart, connected open architecture product: an IT-driven co-creation paradigm with lifecycle personalization concerns
Abstract: 
 Nowadays, the emphasis on manufacturing has shifted from a manufacturer-dominating to a customer-centric manner by actively involving users into the co-creation process to realise individual satisfaction. In such era, the rapid development of information and communication technology (e.g. wireless sensor network, and cyber-physical systems) enables a promising market of IT-driven product, i.e. smart, connected product, and also changes the way of user–manufacturer interaction in the product development process. However, to the best of authors’ knowledge, co-creation manner in such context is scarcely reported. Meanwhile, there is a lack of any paradigms given to enable such product open innovation along the lifecycle for personalisation concerns. Aiming to fill this gap, this paper, as an explorative research, proposes a new product development paradigm, i.e. smart, connected open architecture product (SCOAP). It follows the adaptable design principles for product extendibility and lifecycle consideration. Moreover, it enlarges the scope of existing open architecture product by involving IT-driven innovation consideration as well. Hence, the definitions, characteristics, evaluation criteria, development method, and lifecycle co-creation context of SCOAP are presented in details. To make it more concrete, a demo project of a smart, connected open architecture bicycle is given at last.
Journal: International Journal of Production Research
Pages: 2571-2584
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1530475
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530475
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Template-Type: ReDIF-Article 1.0
Author-Name: Prodromos D. Chatzoglou
Author-X-Name-First: Prodromos D.
Author-X-Name-Last: Chatzoglou
Author-Name: Vassiliki N. Michailidou
Author-X-Name-First: Vassiliki N.
Author-X-Name-Last: Michailidou
Title: A survey on the 3D printing technology readiness to use
Abstract: 
 3D printing technology redesigns the production chain and contributes to the production of customised products, or products with specific characteristics. The evolution of this production technology and its various applications improve our daily life and lead to important changes in economic and social level. The aim of this dissertation is to examine the attitude of people towards 3D printing technological innovation and their intention to use it at their workplace. A new conceptual model has been designed and empirically tested using primary data collected using a structured questionnaire. The sample consists of 258 respondents from a number of European countries. The findings highlight the importance of perceived usefulness, output usability, compatibility and attitude towards understanding respondents’ intention to use 3D printing technology.
Journal: International Journal of Production Research
Pages: 2585-2599
Issue: 8
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2019.1572934
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1572934
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Template-Type: ReDIF-Article 1.0
Author-Name: R.M. Thirupathi
Author-X-Name-First: R.M.
Author-X-Name-Last: Thirupathi
Author-Name: S. Vinodh
Author-X-Name-First: S.
Author-X-Name-Last: Vinodh
Title: Application of interpretive structural modelling and structural equation modelling for analysis of sustainable manufacturing factors in Indian automotive component sector
Abstract: 
 Sustainable manufacturing practices are essential for automotive component manufacturing organisations to ensure competitive advantage. The interrelation between sustainability enablers' namely economic prosperity, environment well-being, social well-being, performance management and research and development need to be analysed for deriving practical insights. Theoretical model development of enablers using interpretive structural modelling (ISM) has been statistically verified using measurement models and structural model of partial least square, structural equation modelling (SEM). In this context, this article presents a combined ISM and SEM approach for building the models with the help of experts for automotive component manufacturing organisation. The measurement and structural model are constructed based on survey among 70 practitioners from automotive component manufacturing organisations in Southern India. The research hypotheses have been formulated to verify the relationship and are analysed. The results of the study indicated that the usage of ISM is very powerful to establish structural relationship between sustainable manufacturing enablers and there exist structural relationship between the enablers.
Journal: International Journal of Production Research
Pages: 6661-6682
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2015.1126372
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1126372
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Template-Type: ReDIF-Article 1.0
Author-Name: José Moyano-Fuentes
Author-X-Name-First: José
Author-X-Name-Last: Moyano-Fuentes
Author-Name: Pedro-José Martínez-Jurado
Author-X-Name-First: Pedro-José
Author-X-Name-Last: Martínez-Jurado
Title: The influence of competitive pressure on manufacturer internal information integration
Abstract: 
 Research on competitive pressure plays an important part in understanding a firm’s behaviour in its changing environment. This paper provides an empirical contribution to the knowledge of the relationship between competitive pressure and internal information integration in this area by focusing on manufacturer internal information integration. The findings show that the degree of manufacturer internal information can be explained by the competitive strength of the largest firm in the industry. From a management perspective, the results indicate the need to regard the competitive landscape as an additional lever of manufacturer internal information sharing.
Journal: International Journal of Production Research
Pages: 6683-6692
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2015.1131866
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1131866
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Template-Type: ReDIF-Article 1.0
Author-Name: Yingfeng Zhang
Author-X-Name-First: Yingfeng
Author-X-Name-Last: Zhang
Author-Name: Sichao Liu
Author-X-Name-First: Sichao
Author-X-Name-Last: Liu
Author-Name: Yang Liu
Author-X-Name-First: Yang
Author-X-Name-Last: Liu
Author-Name: Rui Li
Author-X-Name-First: Rui
Author-X-Name-Last: Li
Title: Smart box-enabled product–service system for cloud logistics
Abstract: 
 Modern logistics takes significant progress and rapid developments with the prosperity of E-commerce, particularly in China. Typical challenges that logistics industry is facing now are composed by a lack of sharing, standard, cost-effective and environmental package and efficient optimisation method for logistics tasks distribution. As a result, it is difficult to implement green, sustainable logistics services. Three important technologies, Physical Internet (PI), product–service system (PSS) and cloud computing (CC), are adopted and developed to address the above issues. PI is extended to design a world-standard green recyclable smart box that is used to encapsulate goods. Smart box-enabled PSS is constructed to provide an innovative sustainable green logistics service, and high-quality packaging, as well as reduce logistics cost and environmental pollution. A real-time information-driven logistics tasks optimisation method is constructed by designing a cloud logistics platform based on CC. On this platform, a hierarchical tree-structure network for customer orders (COs) is built up to achieve the order-box matching of function. Then, a distance clustering analysis algorithm is presented to group and form the optimal clustering results for all COs, and a real-time information-driven optimisation method for logistics orders is proposed to minimise the unused volume of containers. Finally, a case study is simulated to demonstrate the efficiency and feasibility of proposed cloud logistics optimisation method.
Journal: International Journal of Production Research
Pages: 6693-6706
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2015.1134840
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1134840
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Template-Type: ReDIF-Article 1.0
Author-Name: Maryam Darvish
Author-X-Name-First: Maryam
Author-X-Name-Last: Darvish
Author-Name: Homero Larrain
Author-X-Name-First: Homero
Author-X-Name-Last: Larrain
Author-Name: Leandro C. Coelho
Author-X-Name-First: Leandro C.
Author-X-Name-Last: Coelho
Title: A dynamic multi-plant lot-sizing and distribution problem
Abstract: 
 In this paper, we investigate a multi-plant, production planning and distribution problem for the simultaneous optimisation of production, inventory control, demand allocation and distribution decisions. The objective of this rich problem is to satisfy the dynamic demand of customers while minimising the total cost of production, inventory and distribution. By solving the problem, we determine when the production needs to occur, how much has to be produced in each of the plants, how much has to be stored in each of the warehouses and how much needs to be delivered to each customer in each period. On a large real data-set inspired by a case obtained from an industrial partner, we show that the proposed integration is highly effective. Moreover, we study several trade-offs in a detailed sensitivity analysis. Our analyses indicate that the proposed scenarios give the company competitive advantage in terms of reduced total logistics cost, and also highlight more possibilities that become available taking advantage of an integrated approach towards logistics planning. These abundant opportunities are to be synergised and exploited in an interconnected open global logistics system.
Journal: International Journal of Production Research
Pages: 6707-6717
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1154623
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154623
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Template-Type: ReDIF-Article 1.0
Author-Name: Yu-Wei An
Author-X-Name-First: Yu-Wei
Author-X-Name-Last: An
Author-Name: Hong-Sen Yan
Author-X-Name-First: Hong-Sen
Author-X-Name-Last: Yan
Title: Lagrangean relaxation approach to joint optimization for production planning and scheduling of synchronous assembly lines
Abstract: 
 This paper focuses on simultaneous optimisation of production planning and scheduling problem over a time period for synchronous assembly lines. Differing from traditional top-down approaches, a mixed integer programming model which jointly considers production planning and detailed scheduling constraints is formulated, and a Lagrangian relaxation method is developed for the proposed model, whereby the integrated problem is decomposed into planning, batch sequencing, tardiness and earliness sub-problems. The scheduling sub-problem is modelled as a time-dependent travelling salesman problem, which is solved using a dynasearch algorithm. A proposition of Lagrangian multipliers is established to accelerate the convergence speed of the proposed algorithm. The average direction strategy is employed to solve the Lagrangian dual problem. Test results demonstrate that the proposed model and algorithm are effective and efficient.
Journal: International Journal of Production Research
Pages: 6718-6735
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1157271
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1157271
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Template-Type: ReDIF-Article 1.0
Author-Name: Yumin He
Author-X-Name-First: Yumin
Author-X-Name-Last: He
Author-Name: Kathryn E. Stecke
Author-X-Name-First: Kathryn E.
Author-X-Name-Last: Stecke
Author-Name: Milton L. Smith
Author-X-Name-First: Milton L.
Author-X-Name-Last: Smith
Title: Robot and machine scheduling with state-dependent part input sequencing in flexible manufacturing systems
Abstract: 
 In competitive global markets, it is important to meet customer demands on multiple priorities such as price, quality, customisation and quick delivery. This paper investigates the problems of part input sequencing and scheduling in flexible manufacturing systems in a mass customisation/mass personalisation (MC/MP) environment. Both robot and machine scheduling rules using a state-dependent part input sequencing algorithm are investigated. Simulation experiments and statistical analyses are carried out. Effective rules are identified. The results show interactions between robot scheduling and machine scheduling in the MC/MP environment. Further research suggestions are provided.
Journal: International Journal of Production Research
Pages: 6736-6746
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1161252
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1161252
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Template-Type: ReDIF-Article 1.0
Author-Name: Jürgen Strohhecker
Author-X-Name-First: Jürgen
Author-X-Name-Last: Strohhecker
Author-Name: Michael Hamann
Author-X-Name-First: Michael
Author-X-Name-Last: Hamann
Author-Name: Jörn-Henrik Thun
Author-X-Name-First: Jörn-Henrik
Author-X-Name-Last: Thun
Title: Loading and sequencing heuristics for job scheduling on two unrelated parallel machines with long, sequence-dependent set-up times
Abstract: 
 The purpose of this paper is to develop and test intelligible heuristics for the scheduling of production orders that can easily be used in practice. Grounded in a case study, this paper examines the combined effects of assignment and sequencing heuristics on commonly used performance indicators. Discrete event simulation is used in the analysis to adequately capture the complexity found in the case study: production orders differing in many aspects, two unrelated parallel machines with varying and product-specific speed, and set-up times that depend on the (dis)similarity of successive orders. Evaluating 108 strategy–scenario combinations including the base case derived from the case study, it is found that a loading heuristic based on order quantity and scheduled capacity in combination with the shortest set-up heuristic performs best. When compared to the heuristic approach used by the case company, this strategy saves about 13.9% of total machine busy time and increases service level by 10.2%. In addition, using a reduced set of 40 production orders we are able to demonstrate that the best heuristic strategies comes close to results generated in a two-stage optimisation. The gap to optimality is only 3.1% in total busy time on average over all scenarios.
Journal: International Journal of Production Research
Pages: 6747-6767
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1173248
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173248
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Template-Type: ReDIF-Article 1.0
Author-Name: Yujun Yang
Author-X-Name-First: Yujun
Author-X-Name-Last: Yang
Author-Name: Ye Chen
Author-X-Name-First: Ye
Author-X-Name-Last: Chen
Author-Name: Chuanze Long
Author-X-Name-First: Chuanze
Author-X-Name-Last: Long
Title: Flexible robotic manufacturing cell scheduling problem with multiple robots
Abstract: 
 By considering the loaded and empty moving tie of robots moving among loading station, machines and unloading station, the flexible robotic manufacturing cell scheduling problem with multiple robots is studied. An improved discrete particle swarm optimisation with genetic operator and random-heuristic initialisation method is created to minimise the makespan. In addition, a multi-robot scheduling strategy is proposed to minimise the displacement operation when inserting the transportation tasks. By exchanging the positions of critical operations, the neighbourhood structure is established to enhance the capacity of the algorithm to local search. After detailed algorithm design and description, we report the results of a computational study that provides evidence that the proposed optimisation-based approach delivers high-quality solutions against the well-known algorithms.
Journal: International Journal of Production Research
Pages: 6768-6781
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1176267
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1176267
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuyan Han
Author-X-Name-First: Yuyan
Author-X-Name-Last: Han
Author-Name: Dunwei Gong
Author-X-Name-First: Dunwei
Author-X-Name-Last: Gong
Author-Name: Junqing Li
Author-X-Name-First: Junqing
Author-X-Name-Last: Li
Author-Name: Yong Zhang
Author-X-Name-First: Yong
Author-X-Name-Last: Zhang
Title: Solving the blocking flow shop scheduling problem with makespan using a modified fruit fly optimisation algorithm
Abstract: 
 The flow shop scheduling problem with blocking has important applications in a variety of industrial systems but is under-represented in the research literature. In this paper, a modified fruit fly optimisation (MFFO) algorithm is proposed to solve the above scheduling problem for makespan minimisation. The MFFO algorithm mainly contains three key operators. One is related to the initialisation scheme in which a problem-specific heuristic is adopted to generate an initial fruit fly swarm location with high quality. The second is concerned with the smell-based search in which a neighbourhood strategy is designed to generate a new location. To further enhance the exploitation of the proposed algorithm considered, a speed-up insert-neighbourhood-based local search is applied with a probability. Finally, the last is for the vision-based search in which an update criterion is proposed to induce the fruit fly into a better searching space. The simulation experimental results demonstrated the efficiency of the proposed algorithm, in spite of its simple structure, in comparison with a state-of-the-art algorithm. Moreover, new best solutions for Taillard’s instances are reported for this problem, which can be used as a basis of comparison in future studies.
Journal: International Journal of Production Research
Pages: 6782-6797
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1177671
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1177671
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Title: Card-based delivery date promising in pure flow shops with order release control
Abstract: 
 Card-based systems are simple, effective means of controlling production. Yet most systems concentrate on controlling the shop floor. They neglect other planning tasks, like estimating short, feasible due dates during customer enquiry management. A card-based version of the workload control concept for job shops – COBACABANA (COntrol of BAlance by CArd-BAsed Navigation) – was proposed in the literature to overcome this shortcoming. COBACABANA uses cards for due date setting and order release, making it a potentially important solution for small shops with limited resources. But many such firms operate as flow shops rather than job shops. Research demonstrated that COBACABANA’s release mechanism must be adapted if applied to a pure flow shop, but its approach to due date setting has not been evaluated in such an environment. We show COBACABANA has the potential to improve pure flow shop performance, but its due date setting procedure should be adapted compared to job shops. In a flow shop, due date estimation can also be further simplified by considering the load awaiting release to the first (gateway) station only while maintaining most performance benefits. The results are important for all card-based systems that aim to stabilise work-in-process, including kanban and ConWIP (Constant Work-in-Process).
Journal: International Journal of Production Research
Pages: 6798-6811
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1177672
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1177672
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Template-Type: ReDIF-Article 1.0
Author-Name: Jens Heger
Author-X-Name-First: Jens
Author-X-Name-Last: Heger
Author-Name: Jürgen Branke
Author-X-Name-First: Jürgen
Author-X-Name-Last: Branke
Author-Name: Torsten Hildebrandt
Author-X-Name-First: Torsten
Author-X-Name-Last: Hildebrandt
Author-Name: Bernd Scholz-Reiter
Author-X-Name-First: Bernd
Author-X-Name-Last: Scholz-Reiter
Title: Dynamic adjustment of dispatching rule parameters in flow shops with sequence-dependent set-up times
Abstract: 
 Decentralised scheduling with dispatching rules is applied in many fields of production and logistics, especially in highly complex manufacturing systems. Since dispatching rules are restricted to their local information horizon, there is no rule that outperforms other rules across various objectives, scenarios and system conditions. In this paper, we present an approach to dynamically adjust the parameters of a dispatching rule depending on the current system conditions. The influence of different parameter settings of the chosen rule on the system performance is estimated by a machine learning method, whose learning data is generated by preliminary simulation runs. Using a dynamic flow shop scenario with sequence-dependent set-up times, we demonstrate that our approach is capable of significantly reducing the mean tardiness of jobs.
Journal: International Journal of Production Research
Pages: 6812-6824
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1178406
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1178406
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Template-Type: ReDIF-Article 1.0
Author-Name: Ali Azadeh
Author-X-Name-First: Ali
Author-X-Name-Last: Azadeh
Author-Name: Shima Pashapour
Author-X-Name-First: Shima
Author-X-Name-Last: Pashapour
Author-Name: Saeed Abdolhossein Zadeh
Author-X-Name-First: Saeed
Author-X-Name-Last: Abdolhossein Zadeh
Title: Designing a cellular manufacturing system considering decision style, skill and job security by NSGA-II and response surface methodology
Abstract: 
 Cell formation is a traditional problem in cellular manufacturing systems that concerns the allocation of parts, operators and machines to the cells. This paper presents a new mathematical programming model for cell formation in which operators’ personality and decision-making styles, skill in working with machines, and also job security are incorporated simultaneously. The model involves the following five objectives: (1) minimising costs of adding new machines to and removing machines from the cells at the beginning of each period, (2) minimising total cost of material handling, (3) maximising job security, (4) minimising inconsistency of operators’ decision styles in cells and (5) minimising cost of suitable skill. On account of the NP-hard nature of the proposed model, NSGA-II as a powerful meta-heuristic approach is used for solving large-sized problems. Furthermore, response surface methodology (RSM) is used for tuning the parameters. Lastly, MOPSO and two scalarization methods are employed for validation of the results obtained. To the best of our knowledge, this is the first study that presents a multi-objective mathematical model for cell formation problem considering operators’ personality and skill, addition and removal of machines and job security.
Journal: International Journal of Production Research
Pages: 6825-6847
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1178407
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1178407
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Template-Type: ReDIF-Article 1.0
Author-Name: C.D. Rose
Author-X-Name-First: C.D.
Author-X-Name-Last: Rose
Author-Name: J.M.G. Coenen
Author-X-Name-First: J.M.G.
Author-X-Name-Last: Coenen
Title: Automatic generation of a section building planning for constructing complex ships in European shipyards
Abstract: 
 Efficient planning of the section building process is important for European shipyards since delays in this process can disrupt the on-time delivery of a ship. Automatically generating production schedules of the section building process can result in higher quality schedules compared to those created manually. Recently, the production processes of European shipyards have shifted to focus heavily on outsourcing and outfitting, yet existing automatic planning methods for section building fail to sufficiently consider these factors. This paper develops a mathematical model of the section building process which includes the effects of outfitting and outsourcing. The objective of this model is to simultaneously minimise the fluctuations in workload and the number of outsourced man-hours. The mathematical model was solved by implementing the non-dominated sorting generic algorithm-II (NSGA-II) using a custom heuristic as the fitness function. Due to the multi-objective nature of the problem definition and solution approach, a Pareto front of optimal solutions is created instead of a single, best solution. A test case showed that gains in both objectives are achievable compared to the planning developed manually. Implementing the Section Building Planning methodology developed in this paper could potentially improve the efficiency and controllability of the overall shipbuilding process.
Journal: International Journal of Production Research
Pages: 6848-6859
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1182655
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1182655
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Template-Type: ReDIF-Article 1.0
Author-Name: Alkın Yurtkuran
Author-X-Name-First: Alkın
Author-X-Name-Last: Yurtkuran
Author-Name: Erdal Emel
Author-X-Name-First: Erdal
Author-X-Name-Last: Emel
Title: A discrete artificial bee colony algorithm for single machine scheduling problems
Abstract: 
 This paper presents a discrete artificial bee colony algorithm for a single machine earliness–tardiness scheduling problem. The objective of single machine earliness–tardiness scheduling problems is to find a job sequence that minimises the total sum of earliness–tardiness penalties. Artificial bee colony (ABC) algorithm is a swarm-based meta-heuristic, which mimics the foraging behaviour of honey bee swarms. In this study, several modifications to the original ABC algorithm are proposed for adapting the algorithm to efficiently solve combinatorial optimisation problems like single machine scheduling. In proposed study, instead of using a single search operator to generate neighbour solutions, random selection from an operator pool is employed. Moreover, novel crossover operators are presented and employed with several parent sets with different characteristics to enhance both exploration and exploitation behaviour of the proposed algorithm. The performance of the presented meta-heuristic is evaluated on several benchmark problems in detail and compared with the state-of-the-art algorithms. Computational results indicate that the algorithm can produce better solutions in terms of solution quality, robustness and computational time when compared to other algorithms.
Journal: International Journal of Production Research
Pages: 6860-6878
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1185550
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1185550
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Template-Type: ReDIF-Article 1.0
Author-Name: Shih-Wei Lin
Author-X-Name-First: Shih-Wei
Author-X-Name-Last: Lin
Author-Name: Kuo-Ching Ying
Author-X-Name-First: Kuo-Ching
Author-X-Name-Last: Ying
Author-Name: Yen-I Chiang
Author-X-Name-First: Yen-I
Author-X-Name-Last: Chiang
Author-Name: Wen-Jie Wu
Author-X-Name-First: Wen-Jie
Author-X-Name-Last: Wu
Title: Minimising total weighted earliness and tardiness penalties on identical parallel machines using a fast ruin-and-recreate algorithm
Abstract: 
 This paper studies the scheduling problem of minimising total weighted earliness and tardiness penalties on identical parallel machines against a restrictive common due date. This problem is NP-hard in the strong sense and arises in many just-in-time production environments. A fast ruin-and-recreate (FR&amp;R) algorithm is proposed to obtain high-quality solutions to this complex problem. The proposed FR&amp;R algorithm is tested on a well-known set of benchmark test problems that are taken from the literature. Computational results provide evidence of the efficiency of FR&amp;R, which consistently outperform existing algorithms when applied to benchmark instances. This work provides a viable alternative approach for efficiently solving this practical but complex scheduling problem.
Journal: International Journal of Production Research
Pages: 6879-6890
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1190041
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1190041
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Template-Type: ReDIF-Article 1.0
Author-Name: K. Wang
Author-X-Name-First: K.
Author-X-Name-Last: Wang
Author-Name: W.Q. Ma
Author-X-Name-First: W.Q.
Author-X-Name-Last: Ma
Author-Name: H. Luo
Author-X-Name-First: H.
Author-X-Name-Last: Luo
Author-Name: H. Qin
Author-X-Name-First: H.
Author-X-Name-Last: Qin
Title: Coordinated scheduling of production and transportation in a two-stage assembly flowshop
Abstract: 
 To enhance the overall performance of supply chains, coordination among production and distribution stages has recently received an increasing interest. This paper considers the coordinated scheduling of production and transportation in a two-stage assembly flowshop environment. In this problem, product components are first produced and assembled in a two-stage assembly flowshop, and then completed final products are delivered to a customer in batches. Considering the NP-hard nature of this scheduling problem, two fast heuristics (SPT-based heuristic and LPT-based heuristic) and a new hybrid meta-heuristic (HGA-OVNS) are presented to minimise the weighted sum of average arrival time at the customer and total delivery cost. To guide the search process to more promising areas, the proposed HGA-OVNS integrates genetic algorithm with variable neighbourhood search (VNS) to generate the offspring individuals. Furthermore, to enhance the effectiveness of VNS, the opposition-based learning (OBL) is applied to establish some novel opposite neighbourhood structures. The proposed algorithms are validated on a set of randomly generated instances, and the computation results indicate the superiority of HGA-OVNS in quality of solutions.
Journal: International Journal of Production Research
Pages: 6891-6911
Issue: 22
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1193246
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193246
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Template-Type: ReDIF-Article 1.0
Author-Name: Qingxian An
Author-X-Name-First: Qingxian
Author-X-Name-Last: An
Author-Name: Zongrun Wang
Author-X-Name-First: Zongrun
Author-X-Name-Last: Wang
Author-Name: Ali Emrouznejad
Author-X-Name-First: Ali
Author-X-Name-Last: Emrouznejad
Author-Name: Qingyuan Zhu
Author-X-Name-First: Qingyuan
Author-X-Name-Last: Zhu
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Title: Efficiency evaluation of parallel interdependent processes systems: an application to Chinese 985 Project universities
Abstract: 
 Data envelopment analysis (DEA) has been widely applied in measuring the efficiency of homogeneous decision-making units. Network DEA, as an important branch of DEA, was built to examine the internal structure of a system, whereas traditional DEA models regard a system as a ‘black box’. However, only a few previous studies on parallel systems have considered the interdependent relationship between system components. In recent years, parallel interdependent processes systems commonly exist in production systems because of serious competition among organisations. Thus, an approach to measure the efficiency of such systems should be proposed. This paper builds an additive DEA model to measure a parallel interdependent processes system with two components which have an interdependent relationship. Then, the model is applied to analyse the ‘985 Project’ universities in China, and certain policy implications are explained.
Journal: International Journal of Production Research
Pages: 5387-5399
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1521531
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521531
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Template-Type: ReDIF-Article 1.0
Author-Name: Tsang-Chuan Chang
Author-X-Name-First: Tsang-Chuan
Author-X-Name-Last: Chang
Author-Name: Kuen-Suan Chen
Author-X-Name-First: Kuen-Suan
Author-X-Name-Last: Chen
Title: Testing process quality of wire bonding with multiple gold wires from viewpoint of producers
Abstract: 
 Wire bonding involves welding multiple gold wires to connect integrated circuits (ICs) to external circuits for power and signal transmission. Poor-quality wire bonding can prevent the IC and the electronic product from functioning effectively. In view of this, we developed a model to assess and control the quality of wire bonding with multiple gold wires from the viewpoints of both process and producers. We first analysed the consistency of wire bonding process performance. The Six Sigma quality index was then used to directly assess the quality of the wire bonding process and thereby examine its relationship with process yield. Furthermore, we derived the upper confidence limit of index  $ {Q_{PLl}} $ QPLl by statistical inference, and used it to develop a testing model to ensure rigorous quality assessment. A real-world application in an IC packaging factory located in the Taichung Science Park, Taiwan, demonstrates the effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 5400-5413
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1524164
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1524164
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaopeng Li
Author-X-Name-First: Xiaopeng
Author-X-Name-Last: Li
Author-Name: Zixian Liu
Author-X-Name-First: Zixian
Author-X-Name-Last: Liu
Author-Name: Yukun Wang
Author-X-Name-First: Yukun
Author-X-Name-Last: Wang
Author-Name: Mei Li
Author-X-Name-First: Mei
Author-X-Name-Last: Li
Title: Optimal burn-in strategy for two-dimensional warranted products considering preventive maintenance
Abstract: 
 Burn-in and preventive maintenance (PM) are effective approaches to reduce the number of warranty claims and warranty cost during post-sale support. With harsher burn-in settings, early product defects can be removed, but at the same time product degradation is accelerated and more wear-out failures may be introduced. PM actions within warranty alleviate these negative effects. This paper proposes an optimal burn-in strategy for repairable products sold with a two-dimensional base warranty (BW) and an optional extended warranty (EW). Both performance-based and cost-based models incorporating PMs are developed to obtain optimal burn-in settings, including the burn-in duration and the burn-in usage rate, so as to minimise the expected number of warranty claims and total cost respectively. The impacts of different accelerated coefficients and PM degrees on the optimal burn-in strategy are analysed. In view of the performance and cost structures, we conduct numerical examples to illustrate the applicability of the proposed models. Practical implications from a sensitivity analysis for key parameters are also elaborated.
Journal: International Journal of Production Research
Pages: 5414-5431
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1526419
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1526419
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Template-Type: ReDIF-Article 1.0
Author-Name: Junhai Ma
Author-X-Name-First: Junhai
Author-X-Name-Last: Ma
Author-Name: Wandong Lou
Author-X-Name-First: Wandong
Author-X-Name-Last: Lou
Author-Name: Yi Tian
Author-X-Name-First: Yi
Author-X-Name-Last: Tian
Title: Bullwhip effect and complexity analysis in a multi-channel supply chain considering price game with discount sensitivity
Abstract: 
 This paper constructs a multi-channel supply chain that includes a manufacturer, a dual-channel retailer and an online retailer. The dual-channel retailer has a traditional channel and an online channel, while the manufacturer cooperates with the retailers and opens a direct channel simultaneously. The horizontal and historical price discount sensitivities are taken into account to establish the price-sensitive demand functions. A price game model with the heterogeneous expectations is proposed and analysed with the methods of the stability domain, the bifurcation diagram and the maximum Lyapunov exponent. The complexity and bullwhip effect of each channel are investigated with respect to the price adjustment speed and historical price discount sensitivity. The results show that a moderate or low price discount sensitivity keeps the system stable and a high price discount sensitivity brings the system into the twofold cycle state or chaotic state. It is interesting that if both online channels increase the adjustment speeds with similar strategy the system will enter chaos through the Neimark–Sacker bifurcation. The bullwhip effect is affected by the price adjustment speed and the price discount sensitivity, especially in the double-period or chaotic state, where the bullwhip of the overall supply chain is increased significantly. The results show that controlling price discount sensitivity is useful for supply chain node companies.
Journal: International Journal of Production Research
Pages: 5432-5452
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1526420
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1526420
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaohua Cao
Author-X-Name-First: Xiaohua
Author-X-Name-Last: Cao
Author-Name: Tiffany Li
Author-X-Name-First: Tiffany
Author-X-Name-Last: Li
Author-Name: Qiang Wang
Author-X-Name-First: Qiang
Author-X-Name-Last: Wang
Title: RFID-based multi-attribute logistics information processing and anomaly mining in production logistics
Abstract: 
 Timely collecting logistics information and finding anomalies of material supply plays a critical role in modern manufacturing systems. The problem is how to obtain multi-attribute logistics information of production logistics and build an effective approach for mining anomalies from the huge number of RFID data. The multi-attribute, randomness and various measure units of logistics states further aggravate the problem. In this paper, a novel RFID-based logistics information processing approach is proposed. Firstly, the state features of production logistics is discussed from multi-attribute perspectives including time, location, quantities, sequence and path, and a set of calculating models is set up to process RFID data for getting multi-attribute state data. Furthermore, in case of the randomness and various measure units of state data, a similarity model is presented to unify measure units of state data, and a clustering approach is proposed to divide the huge number of RFID data into different clusters with high close degree for finding out anomalies. Lastly, the experimental results show that the proposed approach can efficiently find out more than 90% of anomalies among production logistics.
Journal: International Journal of Production Research
Pages: 5453-5466
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1526421
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1526421
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Template-Type: ReDIF-Article 1.0
Author-Name: Burak Erkayman
Author-X-Name-First: Burak
Author-X-Name-Last: Erkayman
Title: Transition to a JIT production system through ERP implementation: a case from the automotive industry
Abstract: 
 ERP systems provide important benefits to institutions, such as improved processes, improved data, supplier–customer integration, better planning and control, as well as real-time insight and just-in-time (JIT) management that can put a business organisation in front of the competition. In this study, the change and transformation experienced by establishing an ERP system are explained for an automotive supplier that was not using an integrated ERP system for a real-world problem. The pre-implementation situation, the problems of the existing system, the necessary reasons for such an application, the determined deficiencies of the installed system and the post-implementation situation are explained in detail. Thanks to the real-time information and integrated data generated by the reports, along with a more sophisticated business understanding, the risk to employees was lowered. As a result of a changeover to real-time Materials Requirement Planning, the decrease in inventory levels, stabilisation in delivery time and efficiency of control over the production processes were increased in addition to real-time tracking and reporting advantages. As a result of this work, the production processes were transformed into JIT. The inventory level was reduced to zero and a formerly used warehouse was no longer required.
Journal: International Journal of Production Research
Pages: 5467-5477
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1527048
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1527048
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Template-Type: ReDIF-Article 1.0
Author-Name: Nikolaos A. Fountas
Author-X-Name-First: Nikolaos A.
Author-X-Name-Last: Fountas
Author-Name: Nikolaos M. Vaxevanidis
Author-X-Name-First: Nikolaos M.
Author-X-Name-Last: Vaxevanidis
Author-Name: Constantinos I. Stergiou
Author-X-Name-First: Constantinos I.
Author-X-Name-Last: Stergiou
Author-Name: Redha Benhadj-Djilali
Author-X-Name-First: Redha
Author-X-Name-Last: Benhadj-Djilali
Title: Globally optimal tool paths for sculptured surfaces with emphasis to machining error and cutting posture smoothness
Abstract: 
 Global optimisation for manufacturing problems is mandatory for obtaining versatile benefits to facilitate modern industry. This paper deals with an original approach of globally optimising tool paths to CNC-machine sculptured surfaces. The approach entails the development of a fully automated manufacturing software interface integrated by a non-conventional genetic/evolutionary algorithm to enable intelligent machining. These attributes have been built using already existing practical machining modelling tools such as CAM systems so as to deliver a truly viable computer-aided manufacturing solution. Since global optimisation is heavily based on the formulation of the problem, emphasis has been given to the definition of optimisation criteria as crucial elements for representing performance. The criteria involve the machining error as a combined effect of chord error and scallop height, the tool path smoothness and productivity. Experiments have been designed considering several benchmark sculptured surfaces as well as tool path parameters to validate the aforementioned criteria. The new approach was implemented to another sculptured surface which has been extensively tested by previous research works. Results were compared to those available in the literature and it was found that the proposed approach can indeed constitute a promising and trustworthy technique for the global optimisation of sculptured surface CNC tool paths.
Journal: International Journal of Production Research
Pages: 5478-5498
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1530468
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530468
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Template-Type: ReDIF-Article 1.0
Author-Name: Vladimir Polotski
Author-X-Name-First: Vladimir
Author-X-Name-Last: Polotski
Author-Name: Yvan Beauregard
Author-X-Name-First: Yvan
Author-X-Name-Last: Beauregard
Author-Name: Arthur Franzoni
Author-X-Name-First: Arthur
Author-X-Name-Last: Franzoni
Title: Combining predetermined and measured assembly time techniques: Parameter estimation, regression and case study of fenestration industry
Abstract: 
 Time estimation is an important element of the effort evaluation process, which is indispensable along many phases of business development from bidding for the competitive contract to design and production phases. In particular, the time estimates are useful in the resource planning process, especially when the precision of the provided estimates is quantitatively characterised. We propose in this work an approach that combines the techniques developed within predetermined time methods (such as MODAPTS and MINIMOST) with the statistical techniques that use the real data (collected along the stopwatch time measurements). Our approach allows to obtain not only time estimates themselves, but also the confidence intervals for them. This information helps the practitioner to decide whether provided time estimates (coupled with accuracy parameters) meet his criteria. The proposed approach can be used in time estimations for the project containing several operations of different nature, and the application of our methodology is discussed in detail for the case of fenestration industry.
Journal: International Journal of Production Research
Pages: 5499-5519
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1530469
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530469
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Template-Type: ReDIF-Article 1.0
Author-Name: Zikai Zhang
Author-X-Name-First: Zikai
Author-X-Name-Last: Zhang
Author-Name: Qiuhua Tang
Author-X-Name-First: Qiuhua
Author-X-Name-Last: Tang
Author-Name: Zixiang Li
Author-X-Name-First: Zixiang
Author-X-Name-Last: Li
Author-Name: Liping Zhang
Author-X-Name-First: Liping
Author-X-Name-Last: Zhang
Title: Modelling and optimisation of energy-efficient U-shaped robotic assembly line balancing problems
Abstract: 
 Within U-shaped assembly lines, the increase of labour costs and subsequent utilisation of robots has led to growing energy consumption, which is the current main expense of auto and electronics industries. However, there are limited researches concerning both energy consumption reduction and productivity improvement on U-shaped robotic assembly lines. This paper first develops a nonlinear multi-objective mixed-integer programming model, reformulates it into a linear form by linearising the multiplication of two binary variables, and then refines the weight of multiple objectives so as to achieve a better approximation of true Pareto frontiers. In addition, Pareto artificial bee colony algorithm (PABC) is extended to tackle this new complex problem. This algorithm stores all the non-dominated solutions into a permanent archive set to keep all the good genes, and selects one solution from this set to overcome the strong local minima. Comparative experiments based on a set of newly generated benchmarks verify the superiority of the proposed PABC over four multi-objective algorithms in terms of generation distance, maximum spread, hypervolume ratio and the ratio of non-dominated solution.
Journal: International Journal of Production Research
Pages: 5520-5537
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1530479
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530479
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen Chen
Author-X-Name-First: Chen
Author-X-Name-Last: Chen
Author-Name: Lee Kong Tiong
Author-X-Name-First: Lee Kong
Author-X-Name-Last: Tiong
Title: Using queuing theory and simulated annealing to design the facility layout in an AGV-based modular manufacturing system
Abstract: 
 An automated guided vehicle-based flow production system is used for manufacturing prefabricated bathroom units. One unit can occupy a space of more than 10 m2. Due to large time deviations in sequential processes, queues are formed and greater plant space is needed. Reducing work-in-progress helps to save plant space but renders manufacture less efficient. The research explores better workstation arrangements. An open queuing network (OQN) model was used to approximate the flow production system. Since the problem of workstation arrangement is a combinatorial optimisation problem, simulated annealing (SA) was applied to search for a good solution. The combination of an OQN model and SA provides a powerful tool to solve the facility layout problem for a stochastic flow production system. The experimental results show that the proposed approach has the potential to guide industrial layout design and practice.
Journal: International Journal of Production Research
Pages: 5538-5555
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1533654
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1533654
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Template-Type: ReDIF-Article 1.0
Author-Name: Christos Zikopoulos
Author-X-Name-First: Christos
Author-X-Name-Last: Zikopoulos
Title: Determination of freight rates under stochastic demand and freight consolidation savings
Abstract: 
 Following the trend for increased agility, flexibility, responsiveness and customer support of the modern supply chains, latest business practice indicates a preference to smaller transportation quantities as the percentage of truckload shipments is declining. Therefore, transportation rates determination that takes into account freight consolidation becomes more important for firms and logistics managers. We present a decision process for the configuration of a transportation pricing scheme, which ensures that total transportation charges to customers are equal in expectation to transportation expense of the shipper. It also succeeds in returning to the customers the savings in transportation cost because of freight consolidation in a fair manner, keeping its development and implementation quite simple. The proposed decision process consists of two steps, one dealing with the average, long-term transportation expenses estimation, and a second dedicated to the evaluation of the pricing scheme parameters. Our work provides a novel, accurate yet relatively simple method for addressing the issue of transportation cost accounting and pricing when demand for outbound transportation services is stochastic and there are opportunities to obtain savings because of freight consolidation. An interesting feature is that it combines some popular tools for transportation and distribution planning under a relatively new context.
Journal: International Journal of Production Research
Pages: 5556-5573
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1552033
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1552033
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Template-Type: ReDIF-Article 1.0
Author-Name: Stefan Kurpjuweit
Author-X-Name-First: Stefan
Author-X-Name-Last: Kurpjuweit
Author-Name: Dagmar Reinerth
Author-X-Name-First: Dagmar
Author-X-Name-Last: Reinerth
Author-Name: Christoph G. Schmidt
Author-X-Name-First: Christoph G.
Author-X-Name-Last: Schmidt
Author-Name: Stephan M. Wagner
Author-X-Name-First: Stephan M.
Author-X-Name-Last: Wagner
Title: Implementing visual management for continuous improvement: barriers, success factors and best practices
Abstract: 
 Visual management (VM) has become an important lean management practice for continuous improvement and has gained increasing attention from academics and practitioners. While operations management scholars have studied its benefits and functions, the factors that enable or hinder VM implementation have not been systematically investigated. Against this background, our study analyses qualitative case study data from Swiss manufacturing firms to reveal important barriers and success factors that are relevant for the implementation of VM. Moreover, for each success factor, we present several best practices observed in the case companies to overcome the associated barriers. The results contribute to the emerging field of VM within the lean management literature and provide insights for practitioners how to implement VM more effectively.
Journal: International Journal of Production Research
Pages: 5574-5588
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1553315
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1553315
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:17:p:5574-5588




Template-Type: ReDIF-Article 1.0
Author-Name: Cong Li
Author-X-Name-First: Cong
Author-X-Name-Last: Li
Author-Name: Dehui Wang
Author-X-Name-First: Dehui
Author-X-Name-Last: Wang
Author-Name: Fukang Zhu
Author-X-Name-First: Fukang
Author-X-Name-Last: Zhu
Title: Detecting mean increases in zero truncated INAR(1) processes
Abstract: 
 Count data with zero truncation are common in the production process. It's essential to monitor these data during production flow, production quality control and market management. Most of the previous studies were based on the independent observations assumption. In fact, serial dependence of count data which significantly affects the performance of the control charts exists extensively in practice. Motivated by this, several important first-order integer-valued autoregressive time series processes are used to model the autocorrelated count data with zero truncation. We investigate the effectiveness of three following charts, the combined jumps chart, the exponentially weighted moving average chart and the cumulative sum chart, to detect the upward shifts of the process mean based on these models. A bivariate Markov chain approach could be used to obtain the average run length of these charts. Design recommendations for achieving robustness are provided based on the computation study. An application to product quality complaints data is presented to demonstrate good performances of the charts.
Journal: International Journal of Production Research
Pages: 5589-5603
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1554274
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1554274
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenchao Wei
Author-X-Name-First: Wenchao
Author-X-Name-Last: Wei
Author-Name: Pedro Amorim
Author-X-Name-First: Pedro
Author-X-Name-Last: Amorim
Author-Name: Luis Guimarães
Author-X-Name-First: Luis
Author-X-Name-Last: Guimarães
Author-Name: Bernardo Almada-Lobo
Author-X-Name-First: Bernardo
Author-X-Name-Last: Almada-Lobo
Title: Tackling perishability in multi-level process industries
Abstract: 
 The classical multi-level lot-sizing and scheduling problem formulations for process industries rarely address perishability issues, such as limited shelf lives of intermediate products. In some industries, ignoring this specificity may result in severe losses. In this paper, we start by extending a classical multi-level lot-sizing and scheduling problem formulation (MLGLSP) to incorporate perishability issues. We further demonstrate that with the objective of minimising the total costs (purchasing, inventory and setup), the production plans generated by classical models are often infeasible under a setting with perishable products. The model distinguishes different perishability characteristics of raw materials, intermediates and end products according to various industries. Finally, we provide quantitative insights on the importance of considering perishability for different production settings when solving integrated production planning and scheduling problems.
Journal: International Journal of Production Research
Pages: 5604-5623
Issue: 17
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1554916
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1554916
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Template-Type: ReDIF-Article 1.0
Author-Name: X.L. Hu
Author-X-Name-First: X.L.
Author-X-Name-Last: Hu
Author-Name: P. Castagliola
Author-X-Name-First: P.
Author-X-Name-Last: Castagliola
Author-Name: J.S. Sun
Author-X-Name-First: J.S.
Author-X-Name-Last: Sun
Author-Name: M.B.C. Khoo
Author-X-Name-First: M.B.C.
Author-X-Name-Last: Khoo
Title: Economic design of the upper-sided synthetic  chart with measurement errors
Abstract: 
 Considering a quadratic Taguchi loss function for poor quality products, as well as measurement errors in the process characteristic, this paper proposes an economic model for the upper-sided synthetic S2$ S^2 $ chart allowing multiple measurements for each sample item. The steady-state ARL of this chart is computed using a Markov chain method and the optimal number of measurements are obtained through the minimisation of the total cost model. For the proposed economic and economic statistical model, numerical examples are presented to evaluate the effect of measurement errors on the upper-sided synthetic S2$ S^2 $ chart. Finally, the sensitivity analyses of the optimal chart parameters and the cost of the upper-sided synthetic S2$ S^2 $ chart are also investigated using different input parameter values. All the above results are verified through a wide range of the input parameter values. Two illustrative examples are also provided.
Journal: International Journal of Production Research
Pages: 5651-5670
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1109721
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1109721
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Template-Type: ReDIF-Article 1.0
Author-Name: Won K. Ham
Author-X-Name-First: Won K.
Author-X-Name-Last: Ham
Author-Name: Sangchul Park
Author-X-Name-First: Sangchul
Author-X-Name-Last: Park
Title: Simulation-based scanning of a structured light system for objects without overhangs
Abstract: 
 This paper proposes an automated scanning process of a structured light system for objects without overhangs. The processes for scanning those objects need to plan scanning directions that minimise the missing area on a three-dimensional surface during the scanning process. Thus, the processes require an approach that finds the next scanning direction efficiently in terms of computational costs. This paper develops a scanning simulation approach to meet this requirement. In order to apply the developed approach, the proposed process generates a solution space for candidate-scanning directions, and represents an intermediate 3D model. The developed approach traverses the solution space in a virtual environment and executes virtual scanning for the intermediate 3D model. The virtual scanning result of each candidate-scanning direction is analysed in order to evaluate the contribution for filling missing area. The proposed process defines key scanning directions in the solution space through the iterative execution of the developed approach. The proposed process has been implemented, and applied to the scanning experiments of dental impressions.
Journal: International Journal of Production Research
Pages: 5671-5685
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1109722
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1109722
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Template-Type: ReDIF-Article 1.0
Author-Name: Young H. Chun
Author-X-Name-First: Young H.
Author-X-Name-Last: Chun
Title: Improved method of estimating the product quality after multiple inspections
Abstract: 
 A complex product is often inspected more than once in a sequential manner to ensure the product’s quality. Based on the number of defects discovered during each round of inspection process, we can estimate the number of defects still remaining in the product. For each defect, the probability that the defect will be detected during each inspection cycle is usually assumed to be a known ‘constant’. However, in many practical situations, some defects are easily detected, while others are much more difficult to identify. In this paper, we propose a ‘beta-geometric’ inspection model in which the heterogeneity in detection probability is described by a beta distribution. In a numerical study, we show that our more realistic inspection model clearly outperforms traditional estimation methods that are based on the assumption of a constant detection probability.
Journal: International Journal of Production Research
Pages: 5686-5696
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1128128
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1128128
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Template-Type: ReDIF-Article 1.0
Author-Name: Francesco Lolli
Author-X-Name-First: Francesco
Author-X-Name-Last: Lolli
Author-Name: Rita Gamberini
Author-X-Name-First: Rita
Author-X-Name-Last: Gamberini
Author-Name: Claudio Giberti
Author-X-Name-First: Claudio
Author-X-Name-Last: Giberti
Author-Name: Mauro Gamberi
Author-X-Name-First: Mauro
Author-X-Name-Last: Gamberi
Author-Name: Marco Bortolini
Author-X-Name-First: Marco
Author-X-Name-Last: Bortolini
Author-Name: Emanuele Bruini
Author-X-Name-First: Emanuele
Author-X-Name-Last: Bruini
Title: A learning model for the allocation of training hours in a multistage setting
Abstract: 
 In line with the continuous improvement theory, the learning phenomenon is often incorporated into models for predicting the evolution of the unitary quality costs. In this paper, the quality metric predicted is the rate of supplied non-conforming units through a learning process with autonomous and induced sources of experience. The former is simply learning by doing, i.e. supplying, whilst the latter is driven by the allocation of training hours to suppliers. A revised learning model with time-varying learning rates is proposed for embracing both these effects into a multistage assembly/production setting. A single-period prevention–appraisal–failure cost function is achieved, and the sample inspection rates adopted among suppliers are also considered in order to evaluate their effect. If these sample rates are given, the goal of allocating the training hours among suppliers is pursued by means of integer linear programming. Otherwise, a mixed-integer quadratic problem arises for the concurrent allocation of training hours and inspection sample rates among suppliers. A case study is finally carried out for demonstrating the applicability of the model, as well as for providing managerial insights.
Journal: International Journal of Production Research
Pages: 5697-5707
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1129466
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1129466
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Template-Type: ReDIF-Article 1.0
Author-Name: Junkang Guo
Author-X-Name-First: Junkang
Author-X-Name-Last: Guo
Author-Name: Baotong Li
Author-X-Name-First: Baotong
Author-X-Name-Last: Li
Author-Name: Zhigang Liu
Author-X-Name-First: Zhigang
Author-X-Name-Last: Liu
Author-Name: Jun Hong
Author-X-Name-First: Jun
Author-X-Name-Last: Hong
Author-Name: Xiaopan Wu
Author-X-Name-First: Xiaopan
Author-X-Name-Last: Wu
Title: Integration of geometric variation and part deformation into variation propagation of 3-D assemblies
Abstract: 
 This paper introduces a novel modelling method for variation propagation calculation of 3-D assemblies taking into account geometric variation and part deformation, which are neglected in most models in tolerance analysis. Initially, numerical studies are carried out in order to illustrate the characteristics of strain distribution in components and contact forces on the mating surfaces of a 3-D assembly. According to these characteristics, a linear equivalent model using springs to represent the elastic mating surfaces with geometric variation was presented. Then, the equilibrium criterions corresponding to actual contact situations and iterative searching algorithm of the equilibrium status of contacting were developed. The proposed modelling and calculation method were finally applied to the assembly of two machined parts, on which finite-element analyses and experimental tests were conducted to validate the effectiveness and accuracy. This linear contact model also shows an important advantage on modelling and calculating efficiency, which enable the practical application to variation propagation calculation in both tolerance design and assembly process.
Journal: International Journal of Production Research
Pages: 5708-5721
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1158881
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1158881
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Template-Type: ReDIF-Article 1.0
Author-Name: Clément Chatras
Author-X-Name-First: Clément
Author-X-Name-Last: Chatras
Author-Name: Vincent Giard
Author-X-Name-First: Vincent
Author-X-Name-Last: Giard
Title: Simultaneous standardisation of modules and their components: a global economic perspective
Abstract: 
 This paper deals with the problem of simultaneous standardisation of a set of modules and of several sets of components that may be combined in these modules. The aim is to minimise future costs of production and procurement. We introduce a multilevel standardisation that permits to link the level of forecasts used in manufacturing companies with the modules. This formulation determines the composition of the module i.e. their Bill of Material instead of using a predetermined one. The model takes into account coupling restrictions between components and also permits to modelise the possibility of lifting some of them through ‘junction components’. Our model proposes an efficient approach to deal with temporal dimension in the standardisation process. This approach is illustrated with a real case from the automotive industry and some of the related implementation problems are discussed.
Journal: International Journal of Production Research
Pages: 5722-5741
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1159352
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1159352
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 5964-5964
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1171058
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1171058
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Template-Type: ReDIF-Article 1.0
Author-Name: Ryosuke Tomohiro
Author-X-Name-First: Ryosuke
Author-X-Name-Last: Tomohiro
Author-Name: Ikuo Arizono
Author-X-Name-First: Ikuo
Author-X-Name-Last: Arizono
Author-Name: Yasuhiko Takemoto
Author-X-Name-First: Yasuhiko
Author-X-Name-Last: Takemoto
Title: Proposal of variable sequential sampling plan having desired operating characteristics indexed by quality loss
Abstract: 
 The proportion of non-conforming items has been traditionally utilised as an evaluation criterion for quality of items. However, the proportion of non-conforming items is not necessarily useful as a proper evaluation criterion for controlling high-quality manufacturing in recent years. Accordingly, in order to achieve further quality improvement and innovation, more careful quality evaluation has been required newly. Then, a concept of quality loss in the Taguchi methods has been devised as a severe criterion of quality evaluation. Hereby, a variable single sampling plan having desired operating characteristics (OCs) indexed by quality loss has been proposed in the area of statistical quality control. By the way, the most economical sampling inspection in the average sample number (ASN) is the sequential sampling plan based on the Wald’s sequential probability ratio test. Then, from the viewpoint of cost reduction, we discuss a variable sequential sampling plan having desired OC indexed by quality loss with the aim of expansion of the utility of variable sampling plan for quality loss. As the result, the design procedure of the sequential sampling plan for satisfying some required design conditions indexed by quality loss is provided. In addition, the effectiveness of the proposed sequential sampling plan is verified through some numerical examples.
Journal: International Journal of Production Research
Pages: 5742-5760
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1173249
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173249
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Template-Type: ReDIF-Article 1.0
Author-Name: Sandile Charles Shongwe
Author-X-Name-First: Sandile Charles
Author-X-Name-Last: Shongwe
Author-Name: Marien Alet Graham
Author-X-Name-First: Marien Alet
Author-X-Name-Last: Graham
Title: Short note explaining the error in ‘Machado M.A.G. and Costa A.F.B. (2014) “A side-sensitive synthetic chart combined with an  chart.”  52 (11): 3404–3416’
Journal: International Journal of Production Research
Pages: 5963-5963
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1175678
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1175678
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehmet Pınarbaşı
Author-X-Name-First: Mehmet
Author-X-Name-Last: Pınarbaşı
Author-Name: Mustafa Yüzükırmızı
Author-X-Name-First: Mustafa
Author-X-Name-Last: Yüzükırmızı
Author-Name: Bilal Toklu
Author-X-Name-First: Bilal
Author-X-Name-Last: Toklu
Title: Variability modelling and balancing of stochastic assembly lines
Abstract: 
 In a production flow line with stochastic environment, variability affects the system performance. These stochastic nature of real-world processes have been classified in three types: arrival, service and departure process variability. So far, only service process – or task time – variation has been considered in assembly line (AL) balancing studies. In this study, both service and flow process variations are modelled along with AL balancing problem. The best task assignment to stations is sought to achieve the maximal production. A novel approach which consists of queueing networks and constraint programming (CP) has been developed. Initially, the theoretical base for the usage of queueing models in the evaluation of AL performance has been established. In this context, a diffusion approximation is utilised to evaluate the performance of the line and to model the variability relations between the work stations. Subsequently, CP approach is employed to obtain the optimal task assignments to the stations. To assess the effectiveness of the proposed procedure, the results are compared to simulation. Results show that, the procedure is an effective solution method to measure the performance of stochastic ALs and achieve the optimal balance.
Journal: International Journal of Production Research
Pages: 5761-5782
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1177236
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1177236
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Template-Type: ReDIF-Article 1.0
Author-Name: Sheng Hu
Author-X-Name-First: Sheng
Author-X-Name-Last: Hu
Author-Name: Liping Zhao
Author-X-Name-First: Liping
Author-X-Name-Last: Zhao
Author-Name: Yiyong Yao
Author-X-Name-First: Yiyong
Author-X-Name-Last: Yao
Author-Name: Rushan Dou
Author-X-Name-First: Rushan
Author-X-Name-Last: Dou
Title: A variance change point estimation method based on intelligent ensemble model for quality fluctuation analysis
Abstract: 
 For multivariable production process, knowing the first time of process really changes (change point) will help to accelerate the location of assignable causes and make measures for process adjustment. So effective estimating the change point is an important way to analyse the quality fluctuation of process. In the present study, an intelligent ensemble model for quality fluctuation analysis is proposed to estimate the variance change point in multivariable process. With the method, the process is decomposed based on moving window analysis, then different types of kernel functions are combined together to form the multi-kernel support vector machine model, which has combined the feature mapping capability of each basic kernel in the new feature space. The particle swarm optimisation is considered to search the optimised multi-kernel parameters. After that, each sub-characteristic is regarded as a pattern to be recognised to determine the change point by using the optimised intelligent ensemble model. Finally, a case study is conducted to evaluate the performance of proposed approach. It reveals that the method could estimate the time of variance change point in continuous production process accurately.
Journal: International Journal of Production Research
Pages: 5783-5797
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1178862
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1178862
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Tsadikovich
Author-X-Name-First: Dmitry
Author-X-Name-Last: Tsadikovich
Author-Name: Eugene Levner
Author-X-Name-First: Eugene
Author-X-Name-Last: Levner
Author-Name: Hanan Tell
Author-X-Name-First: Hanan
Author-X-Name-Last: Tell
Author-Name: Frank Werner
Author-X-Name-First: Frank
Author-X-Name-Last: Werner
Title: Integrated demand-responsive scheduling of maintenance and transportation operations in military supply chains
Abstract: 
 The management of a military supply chain (SC) involves the integration of production, packaging, warehousing, repair, maintenance and transportation of army supplies. In this paper, we focus on the integrated demand-responsive scheduling of maintenance and transportation operations within the SC. We consider a modular representation of a SC, in which the maintenance and transportation operations constitute the corresponding modules. An efficient integration of these operations is carried out by an additional controlling (commanding) module. We describe and analyse the optimisation problems arising in each module. The main contribution of the paper is that the analysis and optimisation of the controlling module permit to enhance the performance of the entire SC. Computational experiments prove the validity and effectiveness of the suggested models.
Journal: International Journal of Production Research
Pages: 5798-5810
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1178864
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1178864
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaohuan Wang
Author-X-Name-First: Xiaohuan
Author-X-Name-Last: Wang
Author-Name: Zhi-Ping Fan
Author-X-Name-First: Zhi-Ping
Author-X-Name-Last: Fan
Author-Name: Zheng Liu
Author-X-Name-First: Zheng
Author-X-Name-Last: Liu
Title: Optimal markdown policy of perishable food under the consumer price fairness perception
Abstract: 
 Markdown policies are widely used by retailers to sell perishable food. Consumers purchase food at different prices during different sales periods. Some consumers may compare their experience with others who purchase the same items. Price unfairness or inequity is perceived when different prices are quoted without reasonable explanations. This study develops an optimal markdown model for perishable food pricing to optimise the food retailer revenue and enable a maximum aggregated consumer utility considering individuals’ price fairness perception. The model serves as the first step in evaluating trade-offs between food retailer revenue and consumer utility. In addition, it enables consumer utility to be depicted through perceived price fairness by including the effects of food perishability and scarcity. Another innovative feature is the equalisation of the consumer average aggregated utility during different sales periods as a condition of intertemporal price fairness perception. The proposed model is compared with two benchmark models to justify the effectiveness and advantages in the example. Finally, a sensitive analysis based on the food deterioration rate, consumer food desire rate and consumer average reservation price is conducted to justify the manner in which these factors influence the optimal pricing policy, and managerial insights are suggested for food retailers.
Journal: International Journal of Production Research
Pages: 5811-5828
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1179810
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1179810
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Template-Type: ReDIF-Article 1.0
Author-Name: Linmiao Zhang
Author-X-Name-First: Linmiao
Author-X-Name-Last: Zhang
Author-Name: Yong Lei
Author-X-Name-First: Yong
Author-X-Name-Last: Lei
Author-Name: Houcai Shen
Author-X-Name-First: Houcai
Author-X-Name-Last: Shen
Title: How heterogeneity influences condition-based maintenance for gamma degradation process
Abstract: 
 In many applications, units from the same population exhibit heterogeneity that they degrade with different rates due to random factors. This article studies how this heterogeneity in degradation influences condition-based maintenance (CBM) policy. Many CBM polices are developed based on gamma process because it is popularly used to characterise monotone degradation processes. In this study, we also model the unit’s degradation by gamma process. To account for the heterogeneity among units’ degradation, we incorporate a random effect parameter in the gamma process. Then the optimal policy for CBM is obtained through Markov decision process. We show that when heterogeneity exists, the transition probability of degradation state depends on both unit’s age and observed degradation level. And consequently, the optimal maintenance policy is a monotone control limit policy. We conduct extensive numerical experiments to validate and demonstrate our findings in depth.
Journal: International Journal of Production Research
Pages: 5829-5841
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1181282
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1181282
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Template-Type: ReDIF-Article 1.0
Author-Name: Cleber D. Rocco
Author-X-Name-First: Cleber D.
Author-X-Name-Last: Rocco
Author-Name: Reinaldo Morabito
Author-X-Name-First: Reinaldo
Author-X-Name-Last: Morabito
Title: Robust optimisation approach applied to the analysis of production / logistics and crop planning in the tomato processing industry
Abstract: 
 The soluble solids content in the tomato fruit, also known as ‘brix’, and the crop yield are the most relevant uncertain parameters to determine technical and economic performance in the tomato processing industry. This paper presents a linear programming model and three robust optimisation models to deal with data uncertainty in the analysis of crop, logistics and industrial tactical planning in this industry. We focused the analysis on the production and logistics costs due to the impacts of unfavourable disturbances on the amount of soluble solids and the quantity of tomatoes processed in the system. A typical industry in this sector collaborated with this study by providing real data of its production, logistics and crop plans and with in-depth discussions. From the results, some general conclusions were outlined and we discuss the benefits of adopting the robust optimisation approach instead of a deterministic one. The robust approach proved to be a powerful tool for elaborating scenarios for uncertainty analysis in medium-term decisions, as described in this study, and clearly has potential to be employed in real contexts.
Journal: International Journal of Production Research
Pages: 5842-5861
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1181284
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1181284
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Template-Type: ReDIF-Article 1.0
Author-Name: Houssein Abdo
Author-X-Name-First: Houssein
Author-X-Name-Last: Abdo
Author-Name: Jean-Marie Flaus
Author-X-Name-First: Jean-Marie
Author-X-Name-Last: Flaus
Title: Uncertainty quantification in dynamic system risk assessment: a new approach with randomness and fuzzy theory
Abstract: 
 Quantifying uncertainty during risk analysis has become an important part of effective decision-making and health risk assessment. However, most risk assessment studies struggle with uncertainty analysis and yet uncertainty with respect to model parameter values is of primary importance. Capturing uncertainty in risk assessment is vital in order to perform a sound risk analysis. In this paper, an approach to uncertainty analysis based on the fuzzy set theory and the Monte Carlo simulation is proposed. The question then arises as to how these two modes of representation of uncertainty can be combined for the purpose of estimating risk. The proposed method is applied to a propylene oxide polymerisation reactor. It takes into account both stochastic and epistemic uncertainties in the risk calculation. This study explores areas where random and fuzzy logic models may be applied to improve risk assessment in industrial plants with a dynamic system (change over time). It discusses the methodology and the process involved when using random and fuzzy logic systems for risk management.
Journal: International Journal of Production Research
Pages: 5862-5885
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1184348
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1184348
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Template-Type: ReDIF-Article 1.0
Author-Name: G. Celano
Author-X-Name-First: G.
Author-X-Name-Last: Celano
Author-Name: P. Castagliola
Author-X-Name-First: P.
Author-X-Name-Last: Castagliola
Author-Name: S. Chakraborti
Author-X-Name-First: S.
Author-X-Name-Last: Chakraborti
Author-Name: G. Nenes
Author-X-Name-First: G.
Author-X-Name-Last: Nenes
Title: On the implementation of the Shewhart sign control chart for low-volume production
Abstract: 
 Today, many companies use job production to produce small batches of work output according to customised specifications required by customers. With job production, the quantity of parts to be produced is finite and can be limited to a few thousands or hundreds (low-volume production). Usually, job production requires high-quality standards. When 100% sampling is not possible, online monitoring is a viable solution to immediately start process quality control. However, knowledge about the process distribution is frequently unavailable. Recently, it has been shown that the distribution-free Shewhart sign control chart is an efficient means to monitor processes performing high-volume production within a finite production horizon. In this paper, we reconsider the definition of the Shewhart sign chart statistic when the population size is small and we propose an approach that extends its implementation to finite batch sizes of work to be produced. Tables presenting the statistical properties of the Shewhart sign control chart for low-volume production are shown and commented. An illustrative example is discussed on a simulated data-set.
Journal: International Journal of Production Research
Pages: 5886-5900
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1186297
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1186297
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaolin Wang
Author-X-Name-First: Xiaolin
Author-X-Name-Last: Wang
Author-Name: Chun Su
Author-X-Name-First: Chun
Author-X-Name-Last: Su
Title: A two-dimensional preventive maintenance strategy for items sold with warranty
Abstract: 
 Conventional preventive maintenance (PM) strategies under two-dimensional (2D) warranties are usually age-based or usage-based, which means that the implementation of PM activities is based solely on item age or usage. In this paper, a new PM strategy, called 2D PM strategy, is proposed for items sold with a 2D warranty. Under this strategy, the item is preventively maintained every K units of age or L units of usage, whichever occurs first. The marginal approach is used to describe the effect of age and usage on item reliability by treating usage as a random function of age. Besides, the effect of PM is characterised by the reduction of virtual age. The objective of this study is to identify the optimal 2D PM strategy under fixed warranty terms so as to minimise the total expected warranty servicing cost from the manufacturer’s perspective. A numerical example is provided to demonstrate the effectiveness of the proposed PM strategy. It is shown that the 2D PM strategy contains the age-based and usage-based strategies as special cases, and outperforms them in terms of warranty servicing cost. Finally, how to implement the proposed PM strategy in practice is discussed with an illustrative case.
Journal: International Journal of Production Research
Pages: 5901-5915
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1187314
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1187314
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Template-Type: ReDIF-Article 1.0
Author-Name: Lamia Triqui Sari
Author-X-Name-First: Lamia
Author-X-Name-Last: Triqui Sari
Author-Name: Jean-Claude Hennet
Author-X-Name-First: Jean-Claude
Author-X-Name-Last: Hennet
Title: Cooperative inventory planning in a distribution network
Abstract: 
 This study addresses the problem of optimal ordering and collaborative inventory management in a distribution network as a two-stage decision problem. In the first stage, when demand is uncertain, the retailers (sellers) order the products from a warehouse. Then, when demand becomes known with certainty, retailers may exchange their products to better match local demands. Sellers should determine their optimal order quantities for the first stage, and quantities and prices of products exchanged in the second stage. This paper proposes to build sellers’ coalitions and solve the two-stage decision problem as a cooperative game. Stability of a sellers’ coalition can be achieved only if the benefits resulting from collaboration are maximised and distributed according to an allocation policy that is both efficient and rational. The profit maximisation problem is formulated as a stochastic optimisation problem with recourse. Using the scenario method, this problem is approximated by a deterministic linear problem for which the existence of a solution is guaranteed. The proposed pricing policy guarantees the rational allocation of benefits under the scenario approximation. An industrial example supports the modelling approach and is used to evaluate the profitability of the exchange practice in the case of real data.
Journal: International Journal of Production Research
Pages: 5916-5931
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1189103
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1189103
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianlan Zhong
Author-X-Name-First: Jianlan
Author-X-Name-Last: Zhong
Author-Name: Yizhong Ma
Author-X-Name-First: Yizhong
Author-X-Name-Last: Ma
Author-Name: Y.L. Tu
Author-X-Name-First: Y.L.
Author-X-Name-Last: Tu
Title: Integration of SPC and performance maintenance for supply chain system
Abstract: 
 In this paper, a supply chain system is viewed as a maintainable system, and the economic-statistical design of a likelihood ratio control chart with a maintenance application is considered for this system. The supply chain system is described by a three-state: normal state, warning state and failure state. A likelihood ratio control chart is used to monitor the system given that only categorical observations can be obtained. When the chart signals, a full inspection is performed to determine the actual system state (normal or warning), and preventive maintenance is immediately performed in the warning state. In addition, the supply chain system must be corrected upon failure (i.e. corrective maintenance), and should be maintained in a scheduled time (i.e. planned maintenance). A mathematical model is developed for the joint optimisation of the control chart parameters and planned maintenance time based on renewal theory. An example is presented to illustrate how to determine the optimal design parameters. We also investigate the effect of coefficients and statistical constraints on the decision variables and the expected cost.
Journal: International Journal of Production Research
Pages: 5932-5945
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1189104
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1189104
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Template-Type: ReDIF-Article 1.0
Author-Name: Khaled El-Akruti
Author-X-Name-First: Khaled
Author-X-Name-Last: El-Akruti
Author-Name: Tieling Zhang
Author-X-Name-First: Tieling
Author-X-Name-Last: Zhang
Author-Name: Richard Dwight
Author-X-Name-First: Richard
Author-X-Name-Last: Dwight
Title: Developing an optimum maintenance policy by life cycle cost analysis – a case study
Abstract: 
 This paper focuses on developing maintenance policies for critical assets to improve the production performance based on life cycle cost (LCC) analysis. A general approach is adopted for conducting the LCC analysis. The investigation is based on a case study to demonstrate how an optimum maintenance policy is determined. The relevant LCC structure in the case study is defined for the decision process which involves determination of the optimum life, repair limit and selection of materials, and trade-off between repair and replacement. The LCC analysis is based on statistical data modelling which facilitates decision-making on the optimal replacement of an asset and its remaining life. Based on the optimization and remaining life criterion, the optimal maintenance policy can be made. The results obtained from this case study include selection of the best lining material for use, determination of the optimal time for refractory lining replacement, the hot repair sequence required for maintaining the optimum condition and the repair limit for doing cold repairs before replacement, for one type of electric arc furnaces used in the steel industry.
Journal: International Journal of Production Research
Pages: 5946-5962
Issue: 19
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1193244
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193244
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Template-Type: ReDIF-Article 1.0
Author-Name: Shaofu Du
Author-X-Name-First: Shaofu
Author-X-Name-Last: Du
Author-Name: Lin Wei
Author-X-Name-First: Lin
Author-X-Name-Last: Wei
Author-Name: Yangguang Zhu
Author-X-Name-First: Yangguang
Author-X-Name-Last: Zhu
Author-Name: Tengfei Nie
Author-X-Name-First: Tengfei
Author-X-Name-Last: Nie
Title: Peer-regarding fairness in supply chain
Abstract: 
 People exhibit peer-regarding fairness concern when others who are in similar circumstances are treated unfairly. The fairness concern derives from a sense of sympathy or schadenfreude. We study it in a distribution channel where a supplier deals with two retailers located at independent markets. Sympathy means the decrease of the retailer’s utility because he believes that his peer’s unfair treatment is undeserved, while schadenfreude indicates the utility increase as the unfair treatment is perceived deserved. The two retailers are offered wholesale prices sequentially and set their retail prices if they accept the offers. In our paper, the second retailer has the peer-regarding fairness concern. We show the following in regards to this idea: (i) the retailers’ profits and the distribution channel performance can be improved by the peer-regarding fairness concern for sympathy; (ii) the retailers’ profits and the channel performance can be reduced by the peer-regarding fairness concern for schadenfreude; and (iii) the peer-regarding fairness concern for sympathy is unfavourable to the supplier, and the second retailer may be punished separately if the concern is not strong enough, while the supplier benefits from the peer-regarding fairness concern for schadenfreude and may exploit the second retailer solely if the schadenfreude parameter is large.
Journal: International Journal of Production Research
Pages: 3384-3396
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2016.1257872
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1257872
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Template-Type: ReDIF-Article 1.0
Author-Name: Hau-Ling Chan
Author-X-Name-First: Hau-Ling
Author-X-Name-Last: Chan
Author-Name: Bin Shen
Author-X-Name-First: Bin
Author-X-Name-Last: Shen
Author-Name: Yajun Cai
Author-X-Name-First: Yajun
Author-X-Name-Last: Cai
Title: Quick response strategy with cleaner technology in a supply chain: coordination and win-win situation analysis
Abstract: 
 Quick response strategy (QRS) has been widely adopted in a supply chain where members collect timely market information for better forecasting, and then respond promptly to the market changes by adjusting initial inventory decision. After adopting the QRS, sustainability issues such as greenhouse gas emission and energy waste may be more serious as production lead time is shorter. In this study, due to this dilemma, we develop a two-stage quick response supply chain with cleaner technology, where the manufacturer determines the cleaner technology investment and afterwards the retailer decides the ordering quantity. Based on Bayesian theory, we depict an information updating process for the QRS with cleaner technology. First, we find that the inventory service level significantly affects both manufacturer’s and retailer’s performance under the QRS with cleaner technology. Moreover, our analytical results indicate that the performance of centralised supply chain system is always better than the decentralised one. As a result, we propose two supply chain contracts, minimum ordering quantity (MOQ) and MOQ with buyback (MOQ-BB) to achieve supply chain coordination. Comparing with the MOQ, the MOQ-BB is more flexible to allow better allocation of the ‘additional’ expected profit between the channel members through the buyback price negotiation.
Journal: International Journal of Production Research
Pages: 3397-3408
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2016.1278283
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1278283
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Template-Type: ReDIF-Article 1.0
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Shu Guo
Author-X-Name-First: Shu
Author-X-Name-Last: Guo
Title: Responsive supply in fashion mass customisation systems with consumer returns
Abstract: 
 Mass customisation systems have been well-established in the fashion industry. Some fashion brands offer the mass customisation system for their selected seasonal products, and allow unconditional returns and full refund for any unsatisfied customers. Motivated by the above mentioned observed industrial practice and based on the growing importance of responsive supply, we explore in this paper the value of quick response supply in fashion mass customisation systems with consumer returns. We focus on investigating how the consumer returns rate affects (i) the optimal inventory decision of the fashion brand, (ii) the achievability of Pareto improvement in implementing quick response supply, (iii) the respective values of quick response for the fashion brand, the fashion supplier and also the fashion supply chain, and (iv) the impact of quick response supply on the environment. We interestingly find that consumer returns enhance the value of quick response supply to the fashion supplier. Quick response supply is also found to be helpful in reducing the environmental cost under the fashion mass customisation system with consumer returns.
Journal: International Journal of Production Research
Pages: 3409-3422
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1292065
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1292065
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Template-Type: ReDIF-Article 1.0
Author-Name: Meng Li
Author-X-Name-First: Meng
Author-X-Name-Last: Li
Author-Name: Tao Li
Author-X-Name-First: Tao
Author-X-Name-Last: Li
Title: Consumer search, transshipment, and bargaining power in a supply chain
Abstract: 
 We study a decentralised supply chain with one manufacturer and two symmetric retailers who could transship their excess inventory between each other. Without transshipment, the retailer’s unsatisfied customers search and buy the product at the other retailer with some probability. With transshipment, the retailer can transship the other retailer’s excess inventory to fulfil its own unmet demand. However, a transshipment price is often charged by one retailer for transshipping goods to another. We show the retailer’s profit is unimodal in the transshipment price, and the manufacturer’s profit increases in the customer search probability. Although the retailer’s preference over transshipment depends on the magnitude of search probability and transshipment price, the retailer may always prefer the transshipment no matter their magnitude. We then study the effect of bargaining power over the transshipment decision (whether to transship between retailers and at what transshipment price). Our analysis suggests that the manufacturer always prefers to control the transshipment price rather than to control whether to transship, while the retailer can prefer both. We also find that increasing bargaining power always benefits the manufacturer but could hurt the retailer. We finally check the robustness of our results by investigating the case with asymmetric retailers
Journal: International Journal of Production Research
Pages: 3423-3438
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1326644
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1326644
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Template-Type: ReDIF-Article 1.0
Author-Name: Konstantin Biel
Author-X-Name-First: Konstantin
Author-X-Name-Last: Biel
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Title: Governing the dynamics of multi-stage production systems subject to learning and forgetting effects: A simulation study
Abstract: 
 Managing production systems where production rates change over time due to learning and forgetting effects poses a major challenge to researchers and practitioners alike. This task becomes especially difficult if learning and forgetting effects interact across different stages in multi-stage production systems as rigid production management rules are unable to capture the dynamic character of constantly changing production rates. In a comprehensive simulation study, this paper first investigates to which extent typical key performance indicators (KPIs), such as the number of setups, in-process inventory, or cycle time, are affected by learning and forgetting effects in serial multi-stage production systems. The paper then analyses which parameters of such production systems are the main drivers of these KPIs when learning and forgetting occur. Lastly, it evaluates how flexible production control based on Goldratt’s Optimised Production Technology can maximise the benefits learning offers in such systems. The results of the paper indicate that learning and forgetting only have a minor influence on the number of setups in serial multi-stage production systems. The influence of learning and forgetting on in-process inventory and cycle time, in contrast, is significant, but ambiguous in case of in-process inventory. The proposed buffer management rules are shown to effectively counteract this ambiguity.
Journal: International Journal of Production Research
Pages: 3439-3461
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1338780
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1338780
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanhui Li
Author-X-Name-First: Yanhui
Author-X-Name-Last: Li
Author-Name: Hao Guo
Author-X-Name-First: Hao
Author-X-Name-Last: Guo
Author-Name: Ying Zhang
Author-X-Name-First: Ying
Author-X-Name-Last: Zhang
Title: An integrated location-inventory problem in a closed-loop supply chain with third-party logistics
Abstract: 
 Third-party logistics (3PL) is a fast growing business. Many large organisations are using 3PL services to reduce operating costs, simplify business processes, and enhance operations and supply chain flexibility. In this paper, we study location-inventory decisions jointly in a closed-loop system with 3PL. First, a  model formulation is proposed to develop mixed-integer non-linear programming (MINLP) models for the location-inventory problem under study. Then, a novel heuristics based on differential evolution and the genetic algorithm is designed to solve the MINLP  models efficiently. Last, numerical study is presented to illustrate and validate the solution approach.
Journal: International Journal of Production Research
Pages: 3462-3481
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1338781
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1338781
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Template-Type: ReDIF-Article 1.0
Author-Name: Nasim Zandi Atashbar
Author-X-Name-First: Nasim
Author-X-Name-Last: Zandi Atashbar
Author-Name: Nacima Labadie
Author-X-Name-First: Nacima
Author-X-Name-Last: Labadie
Author-Name: Christian Prins
Author-X-Name-First: Christian
Author-X-Name-Last: Prins
Title: Modelling and optimisation of biomass supply chains: a review
Abstract: 
 A growing number of researchers are attracted by the domain of bioenergies, due to the problems induced by greenhouse gas emissions and increasing energy demand. One possible way of producing biofuels in a renewable way is to use biomass, however the economic viability of a biorefinery system depends critically on the cost of its supplies. As biomass is not very expensive, logistics is responsible of an important fraction of this cost. Models and methods to optimise biomass supply chains are surveyed in this article, after introducing some technical terms and describing the main activities in these chains. This review aims to give a comprehensive overview of the research in this field with a focus on optimisation modelling issues and solution approaches. Recent advances in the current research and possible new directions are sketched.
Journal: International Journal of Production Research
Pages: 3482-3506
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1343506
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1343506
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: Revealing interfaces of supply chain resilience and sustainability: a simulation study
Abstract: 
 Dynamics of structures and processes is one of the underlying challenges in supply chain management, where multiple dimensions of economic efficiency, risk management and sustainability are interconnected. One of the substantiated issues in supply chain dynamics is resilience. Resilience has a number of intersections with supply chain sustainability. This paper aims at analysing disruption propagation in the supply chain with consideration of sustainability factors in order to design resilient supply chain structure in regard to ripple effect mitigation and sustainability increase. Ripple effect in the supply chain occurs if a disruption at a supplier cannot be localised and cascades downstream impacting supply chain performance. This simulation-based study helps to identify what sustainability factors mitigate the ripple effect in the supply chain and what sustainability factors enhance this effect. The results indicate that (i) sustainable single sourcing enhances the ripple effect; (ii) facility fortification at major employers in regions mitigates the ripple effect and enhances sustainability; and (iii) a reduction in storage facilities in the supply chain downstream of a disruption-risky facility increases sustainability but causes the ripple effect.
Journal: International Journal of Production Research
Pages: 3507-3523
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1343507
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1343507
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Template-Type: ReDIF-Article 1.0
Author-Name: G. Behzadi
Author-X-Name-First: G.
Author-X-Name-Last: Behzadi
Author-Name: M.J. O’Sullivan
Author-X-Name-First: M.J.
Author-X-Name-Last: O’Sullivan
Author-Name: T.L. Olsen
Author-X-Name-First: T.L.
Author-X-Name-Last: Olsen
Author-Name: A. Zhang
Author-X-Name-First: A.
Author-X-Name-Last: Zhang
Title: Allocation flexibility for agribusiness supply chains under market demand disruption
Abstract: 
 This paper develops a multi-commodity multi-period optimisation model to analyse market demand disruption risk in agribusiness supply chains. It investigates the role of allocation flexibility and the effectiveness of multiple risk management strategies for achieving allocation flexibility. A robust optimisation formulation is used to obtain risk-averse solutions for an objective combining expected profit and risk. Numerical results are presented for a real-life case study of Zespri’s kiwifruit supply chain. The results show that allocation flexibility is effective for mitigating market demand disruption risk. Three proposed risk management strategies, namely diversified demand market, backup demand market and flexible rerouting, improve both expected profit and risk measures. While diversified demand market and backup demand market strategies are equally important for all decision-makers, flexible rerouting is especially significant for less risk-averse decision-makers.
Journal: International Journal of Production Research
Pages: 3524-3546
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1349955
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1349955
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Template-Type: ReDIF-Article 1.0
Author-Name: Aghil Rezaei Somarin
Author-X-Name-First: Aghil
Author-X-Name-Last: Rezaei Somarin
Author-Name: Sobhan Asian
Author-X-Name-First: Sobhan
Author-X-Name-Last: Asian
Author-Name: Fariborz Jolai
Author-X-Name-First: Fariborz
Author-X-Name-Last: Jolai
Author-Name: Songlin Chen
Author-X-Name-First: Songlin
Author-X-Name-Last: Chen
Title: Flexibility in service parts supply chain: a study on emergency resupply in aviation MRO
Abstract: 
 Recent trends in the commercial aviation industry have resulted in rapidly increasing complexity and decentralisation in service parts logistics systems. As a consequence, MRO service providers tend to adopt more flexible strategies, such as service parts sourcing and demand fulfilment for customers with different service-level requirements. The MRO service providers often enter into cooperative agreements with other service providers to pool inventories, enabling them to increase their flexibility in delivering services to multiple airlines with different contractual terms. Although using cooperative strategies, such as emergency resupply, is useful to increase flexibility, the inherent complexity of optimal mechanism is a critical issue that needs to be further investigated. To this aim, we consider a repairable service parts inventory system with multi-customer classes and develop an optimal emergency resupply policy. Following this, to overcome the intractability issue of finding the optimal policy, an efficient approximation method is proposed. Numerical results indicate that the proposed approximation method is highly accurate, and leads to a significant costs reduction. This paper sheds light on the effectiveness of emergency resupply policy that improves MRO service providers’ flexibility and enables them to ensure responsive service parts inventory.
Journal: International Journal of Production Research
Pages: 3547-3562
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1351640
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1351640
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Template-Type: ReDIF-Article 1.0
Author-Name: Shailesh S. Kulkarni
Author-X-Name-First: Shailesh S.
Author-X-Name-Last: Kulkarni
Author-Name: David Francas
Author-X-Name-First: David
Author-X-Name-Last: Francas
Title: Capacity investment and the value of operational flexibility in manufacturing systems with product blending
Abstract: 
 A distinct feature of process industries such as food, chemical and consumer packaged goods is the blending of intermediates into finished goods. In the context of such manufacturing systems the levels of different inputs that can be blended to process a final good define the range of flexibility. Likewise, the cost for using (blending) different inputs defines the mobility element of flexibility. In this paper, we investigate capacity investment and the value of flexibility in the presence of such product blending constraints. We are motivated by recent case studies of food manufacturers, in particular, those manufacturers that seek to increase flexibility via blending of intermediates. We analyse stochastic programs under demand uncertainty of such manufacturing systems. We provide analytical insights into trade-offs when range and mobility are interdependent. Our analytical work gives structural insights into subtle complementarity and substitution effects between dedicated and shared resources in the presence of blending. We analytically show that there is a degradation in the cost performance of such systems with an increase in correlation. We characterise the optimal blending fraction that balances the benefits of higher range with higher costs (lower mobility). Our numerical work shows that a moderate level of blending can significantly improve flexibility and that well-known guidelines for designing limited flexibility change in the presence of blending. For example, blending, even if optimally designed, weakens the appeal of chaining configurations. Overall our work guides resource configuration in industries where product blending is an integral part of the production process.
Journal: International Journal of Production Research
Pages: 3563-3589
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1374576
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1374576
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Template-Type: ReDIF-Article 1.0
Author-Name: Gholamreza Bodaghi
Author-X-Name-First: Gholamreza
Author-X-Name-Last: Bodaghi
Author-Name: Fariborz Jolai
Author-X-Name-First: Fariborz
Author-X-Name-Last: Jolai
Author-Name: Masoud Rabbani
Author-X-Name-First: Masoud
Author-X-Name-Last: Rabbani
Title: An integrated weighted fuzzy multi-objective model for supplier selection and order scheduling in a supply chain
Abstract: 
 This paper presents a new weighted fuzzy multi-objective model to integrated supplier selection, order quantity allocation and customer order scheduling problem to prepare a responsive and order-oriented supply chain in a make-to-order manufacturing system. Total cost and quality of purchased parts as well as the reliability of on-time delivery of customer orders are regarded as the objectives of the model. On the other hand, flexible suppliers can contribute to the responsiveness and flexibility of entire supply chain in the face of uncertain customer orders. Therefore, a mathematical measure is developed for evaluating the volume flexibility of suppliers and is considered as the other objective of the model. Furthermore, by considering the effect of interdependencies between the selection criteria and to handle inconsistent and uncertain judgments, a fuzzy analytic network process method is used to identify top suppliers and consider as the last objective. In order to optimise these objectives, the decision-maker needs to decide from which supplier to purchase parts needed to assemble the customer orders, how to allocate the demand for parts between the selected suppliers, and how to schedule the customer orders for assembled products over the planning time horizon. Numerical examples are presented and computational analysis is reported.
Journal: International Journal of Production Research
Pages: 3590-3614
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1400706
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1400706
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiho Yoon
Author-X-Name-First: Jiho
Author-X-Name-Last: Yoon
Author-Name: Ram Narasimhan
Author-X-Name-First: Ram
Author-X-Name-Last: Narasimhan
Author-Name: Myung Kyo Kim
Author-X-Name-First: Myung Kyo
Author-X-Name-Last: Kim
Title: Retailer’s sourcing strategy under consumer stockpiling in anticipation of supply disruptions
Abstract: 
 We study a retailer’s sourcing strategy under consumers’ stockpiling behaviour and the factors associated with the selection of an optimal strategy in multi-tier supply chains in the presence of supply disruption risk. Stockpiling behaviour occurs when consumers attempt to mitigate the negative impact of a supply shortage. We prove that those behaviours become stronger if consumers have experienced similar problems before and weaker as more inventories are hoarded. Based on these findings, numerical analysis is carried out to compare the superiority of single sourcing versus dual sourcing from retailer’s perspective. Our results suggest that the superiority is highly dependent on factors such as supplier’s volume flexibility, retailer’s purchasing price, and supplier reliability.
Journal: International Journal of Production Research
Pages: 3615-3635
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1401748
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401748
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiho Yoon
Author-X-Name-First: Jiho
Author-X-Name-Last: Yoon
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Author-Name: Hakan Yildiz
Author-X-Name-First: Hakan
Author-X-Name-Last: Yildiz
Author-Name: William Ho
Author-X-Name-First: William
Author-X-Name-Last: Ho
Title: Models for supplier selection and risk mitigation: a holistic approach
Abstract: 
 According to a study conducted by PwC and the Business Continuity Institute in 2013, 75% of companies experience at least one major supply chain disruption a year and majority of the disruptions were caused by supply-related problems. With an increasing emphasis on upstream risk, risk management in supplier selection has become a critical issue faced by companies. Although previous studies proposed different methods and tools for effective and efficient supplier selection, only few approaches have attempted to incorporate risk mitigation strategies in supplier selection decisions. Our study aims to fill this gap by considering a wide range of quantitative and qualitative risk factors in supplier selection and evaluates the efficacy of alternative risk mitigation strategies in this context. Moreover, we suggest that both upstream and downstream strategies should be utilised simultaneously rather than relying on a single type of strategy. We further suggest that it is critical to align upstream and downstream risk mitigation strategies to reduce risk. We employ multi-objective optimization-based simulation in developing a decision model and consider data from an automotive parts manufacturer to demonstrate the application of our approach.
Journal: International Journal of Production Research
Pages: 3636-3661
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1403056
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1403056
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Template-Type: ReDIF-Article 1.0
Author-Name: Christoph Müller
Author-X-Name-First: Christoph
Author-X-Name-Last: Müller
Author-Name: Martin Grunewald
Author-X-Name-First: Martin
Author-X-Name-Last: Grunewald
Author-Name: Thomas Stefan Spengler
Author-X-Name-First: Thomas Stefan
Author-X-Name-Last: Spengler
Title: Redundant configuration of robotic assembly lines with stochastic failures
Abstract: 
 One of the main challenges in the operation of robotic assembly lines is the occurrence of failures. Due to the connection of the stations via a material handling system, failures at one station often result in throughput losses. To some extent, these throughput losses can be reduced by installing buffers between the stations. However, the installation of buffers requires considerable investments and scarce factory space. Due to the advances of manufacturing technologies that form the foundation of ‘Industry 4.0’, new solutions to reduce failure-related throughput losses open up. One solution is a redundant configuration, in which downstream (backup) stations automatically take over the operations of failed stations during repair time. The throughput loss in these situations depends on the allocation of operations and the assignment of backup stations. Existing approaches in the literature that consider redundancies in the configuration of automated lines neglect the resulting production rate. Instead, the lines’ level of redundancy is used as a surrogate measure for optimisation. We present a genetic algorithm for the redundant configuration of robotic assembly lines with stochastic failures to maximise the production rate of the line. In a numerical analysis, it is demonstrated that this approach allows for productivity improvements.
Journal: International Journal of Production Research
Pages: 3662-3682
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1406672
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1406672
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Template-Type: ReDIF-Article 1.0
Author-Name: Liang Qu
Author-X-Name-First: Liang
Author-X-Name-Last: Qu
Author-Name: Michael B.C. Khoo
Author-X-Name-First: Michael B.C.
Author-X-Name-Last: Khoo
Author-Name: Philippe Castagliola
Author-X-Name-First: Philippe
Author-X-Name-Last: Castagliola
Author-Name: Zhen He
Author-X-Name-First: Zhen
Author-X-Name-Last: He
Title: Exponential cumulative sums chart for detecting shifts in time-between-events
Abstract: 
 Time-between-events (TBE) charts use the time interval T between events to monitor process shifts (or failure rates λ). This paper presents a two-sided TBE cumulative sums (CUSUM) chart called a weighted CUSUM(WCUSUM)chart for detecting either a deterioration (decrease in T) or an improvement (increase in T) in the condition of a process. A new kind of WCUSUM chart that has an additional charting power parameter w is proposed here. A WCUSUM chart’s efficiency can be improved by using the parameter w, based on an estimated value of the mean shift. In addition, a methodology and optimal design are presented for minimising the average loss. Construction of the WCUSUM chart is illustrated by considering a random shift δ in λ (including both increasing and decreasing shifts) in the design.
Journal: International Journal of Production Research
Pages: 3683-3698
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1412523
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412523
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Template-Type: ReDIF-Article 1.0
Author-Name: Ju Myung Song
Author-X-Name-First: Ju Myung
Author-X-Name-Last: Song
Author-Name: Weiwei Chen
Author-X-Name-First: Weiwei
Author-X-Name-Last: Chen
Author-Name: Lei Lei
Author-X-Name-First: Lei
Author-X-Name-Last: Lei
Title: Supply chain flexibility and operations optimisation under demand uncertainty: a case in disaster relief
Abstract: 
 After a disaster happens, emergency response operations are critical to save humans’ lives and properties. The limited resources and time requirements call for coordinated supply chain operations. This paper studies supply chain operations for rescue kits in disaster reliefs, motivated by a real-world application. The objective is to minimise the total tardiness and peak tardiness of product delivery over the multi-period planning horizon. One major challenge is the lack of reliable prediction of customer demand in disasters. In order to cope with demand uncertainty while maintaining the tractability of the optimisation model, we decompose the demand into two components: a relatively stable base demand predicted by historical data and unpredictable demand surges. For the base demand, an optimisation model is developed to optimise the production and distribution operations, as well as the inventory replenishment policy for manufacturers and distribution centres, so as to minimise the total tardiness. For the demand surges, we propose to deploy supply chain flexibility to cope with the uncertainty. An empirical study shows the effectiveness of increasing supply chain flexibility and suggests some managerial insights on configuring such flexibility in emergency operations.
Journal: International Journal of Production Research
Pages: 3699-3713
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1416203
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1416203
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Template-Type: ReDIF-Article 1.0
Author-Name: Lei Xu
Author-X-Name-First: Lei
Author-X-Name-Last: Xu
Author-Name: Yongjian Li
Author-X-Name-First: Yongjian
Author-X-Name-Last: Li
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Xiaohang Yue
Author-X-Name-First: Xiaohang
Author-X-Name-Last: Yue
Title: Return policy and supply chain coordination with network-externality effect
Abstract: 
 The benefits of a consumer return policy have been extensively studied in extent literature. This paper explores the potentially damaging impact of a return policy on the retailer. We develop an analytical framework and examine the economic impact of consumer return among consumers, retailer and supply chain. We distinguish three network-externality (NE) cases: no network externality, fixed network-externality and variable network-externality contingent on return amount to discuss the retailer’s selling price, refund and inventory policies. Our analysis derives the optimal policies and shows that they take the form of contingence model in which the policies depend on consumer initial return and NE return. We also examine the influence of the consumer return NE effect on buy-back contracts of the supply chain and show that while the traditional buy-back contract fails to coordinate the supply chain, the NE effect does not render the differentiated buy-back contract less effective. Finally, we extend our study to a heterogeneous consumer case.
Journal: International Journal of Production Research
Pages: 3714-3732
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2017.1421786
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421786
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Template-Type: ReDIF-Article 1.0
Author-Name: Hardeep Chahal
Author-X-Name-First: Hardeep
Author-X-Name-Last: Chahal
Author-Name: Mahesh Gupta
Author-X-Name-First: Mahesh
Author-X-Name-Last: Gupta
Author-Name: Subhash Lonial
Author-X-Name-First: Subhash
Author-X-Name-Last: Lonial
Title: Operational flexibility in hospitals: Scale development and validation
Abstract: 
 The purpose of this paper is to develop and validate an operational flexibility construct that can serve as a general theory in operations management in the context of the hospital industry. The effects of management capability and competitive intensity on operational flexibility and performance relationships are also explored. We used data collected from a sample of 152 administrators of hospitals in the mid-west region of the USA and performed a systematic series of analyses. Following the transformation model, grounded in the fundamental and powerful concept of operations management, we develop a psychometrically validated, 11-item, three-dimensional (input, process, output) scale of operational flexibility (OF) construct for the hospital industry. As the degree of operational flexibility allowed in any transformation system is influenced by management capability, it is established as a complementary mediator in strengthening the OF-performance relationship in the presence of competitive intensity (i.e. moderator). The paper concludes with limitations and directions for future research.
Journal: International Journal of Production Research
Pages: 3733-3755
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2018.1442941
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1442941
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Template-Type: ReDIF-Article 1.0
Author-Name: Bo Feng
Author-X-Name-First: Bo
Author-X-Name-Last: Feng
Author-Name: Wei Liu
Author-X-Name-First: Wei
Author-X-Name-Last: Liu
Author-Name: Zhaofang Mao
Author-X-Name-First: Zhaofang
Author-X-Name-Last: Mao
Title: Use of opaque sales channels in addition to traditional channels by service providers
Abstract: 
 Motivated by the recent opaque selling trend promoted by Priceline and Hotwire, this study examines a game in which two collaborative service providers may use an opaque selling channel to satisfy demand from both leisure and business customers. Further, the service providers must make a strategic decision as to which opaque selling channel is more profitable: posted price (PP) or name your own price (NYOP). By comparing the profits from the three cases (traditional single channel, traditional and PP dual channel, and traditional and NYOP dual channel), we find some interesting results driven by the strategic interaction between two service providers and by the heterogeneity of customers. Firstly, a dual channel offers advantages over the single traditional channel, as opaque selling allows service providers to utilise customers’ heterogeneity, and thus facilitates price discrimination and customer segmentation. Secondly, choosing the traditional and NYOP mechanism enables service providers to optimise profits when the proportion and valuation of business customers, the opacity of the service, and the leisure customers’ degree of pessimism are all relatively high. Lastly, the traditional and NYOP combination outperforms the traditional and PP mechanism as a result of the relatively large pessimistic state of leisure customers.
Journal: International Journal of Production Research
Pages: 3369-3383
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2018.1449973
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1449973
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Ajay Das
Author-X-Name-First: Ajay
Author-X-Name-Last: Das
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Title: New flexibility drivers for manufacturing, supply chain and service operations
Abstract: 
 Increasing product proliferation, customisation, competition and customer expectations, as well as supply side disruptions, pose significant challenges to firm operations. Such challenges require improved efficiency and resilience in manufacturing, service and supply chain systems. New and innovative flexibility concepts and models offer a prospective route to such operational improvements. Several emerging issues in flexibility, such as risk and uncertainty management, environmental sustainability, optimal strategies under competition, optimal operations with strategic consumer behaviours are being examined in this regard. This overview provides a concise review of these critical research issues, and discusses related papers featured in this special issue. Four major flexibility drivers are classified: disruption risks, resilience and the ripple effect in the supply chain; digitalisation, smart operations and e-supply chains; sustainability and closed-loop supply chains; and supplier integration and behavioural flexibility.
Journal: International Journal of Production Research
Pages: 3359-3368
Issue: 10
Volume: 56
Year: 2018
Month: 5
X-DOI: 10.1080/00207543.2018.1457813
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1457813
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Template-Type: ReDIF-Article 1.0
Author-Name: Guanlian Xiao
Author-X-Name-First: Guanlian
Author-X-Name-Last: Xiao
Author-Name: Willem van Jaarsveld
Author-X-Name-First: Willem
Author-X-Name-Last: van Jaarsveld
Author-Name: Ming Dong
Author-X-Name-First: Ming
Author-X-Name-Last: Dong
Author-Name: Joris van de Klundert
Author-X-Name-First: Joris
Author-X-Name-Last: van de Klundert
Title: Models, algorithms and performance analysis for adaptive operating room scheduling
Abstract: 
 The complex optimisation problems arising in the scheduling of operating rooms have received considerable attention in recent scientific literature because of their impact on costs, revenues and patient health. For an important part, the complexity stems from the stochastic nature of the problem. In practice, this stochastic nature often leads to schedule adaptations on the day of schedule execution. While operating room performance is thus importantly affected by such adaptations, decision-making on adaptations is hardly addressed in scientific literature. Building on previous literature on adaptive scheduling, we develop adaptive operating room scheduling models and problems, and analyse the performance of corresponding adaptive scheduling policies. As previously proposed (fully) adaptive scheduling models and policies are infeasible in operating room scheduling practice, we extend adaptive scheduling theory by introducing the novel concept of committing. Moreover, the core of the proposed adaptive policies with committing is formed by a new, exact, pseudo-polynomial algorithm to solve a general class of stochastic knapsack problems. Using these theoretical advances, we present performance analysis on practical problems, using data from existing literature as well as real-life data from the largest academic medical centre in The Netherlands. The analysis shows that the practically feasible, basic, 1-level policy already brings substantial and statistically significant improvement over static policies. Moreover, as a rule of thumb, scheduling surgeries with large mean duration or standard deviation early appears good practice.
Journal: International Journal of Production Research
Pages: 1389-1413
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1328140
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1328140
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Template-Type: ReDIF-Article 1.0
Author-Name: Ameni Azzouz
Author-X-Name-First: Ameni
Author-X-Name-Last: Azzouz
Author-Name: Meriem Ennigrou
Author-X-Name-First: Meriem
Author-X-Name-Last: Ennigrou
Author-Name: Lamjed Ben Said
Author-X-Name-First: Lamjed
Author-X-Name-Last: Ben Said
Title: Scheduling problems under learning effects: classification and cartography
Abstract: 
 Traditionally, the processing times of jobs are assumed to be fixed and known throughout the entire process. However, recent empirical research in several industries has demonstrated that processing times decline as workers improve their skills and gain experience after doing the same task for a long time. This phenomenon is known as learning effects. Recently, several researchers have devoted a lot of effort on scheduling problems under learning effects. Although there is increase in the number of research in this topic, there are few review papers. The most recent one considers solely studies on scheduling problems with learning effects models prior to early 2007. For that, this paper focuses on reviewing the most recent advances in this field. First, we attempt to present a concise overview of some important learning models. Second, a new classification scheme for the different model of scheduling under learning effects is proposed and discussed. Next, a cartography showing the relation between some well-known models is proposed. Finally, our viewpoints and several areas for future research are provided.
Journal: International Journal of Production Research
Pages: 1642-1661
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1355576
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355576
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Template-Type: ReDIF-Article 1.0
Author-Name: Célia Paquay
Author-X-Name-First: Célia
Author-X-Name-Last: Paquay
Author-Name: Sabine Limbourg
Author-X-Name-First: Sabine
Author-X-Name-Last: Limbourg
Author-Name: Michaël Schyns
Author-X-Name-First: Michaël
Author-X-Name-Last: Schyns
Author-Name: José Fernando Oliveira
Author-X-Name-First: José Fernando
Author-X-Name-Last: Oliveira
Title: MIP-based constructive heuristics for the three-dimensional Bin Packing Problem with transportation constraints
Abstract: 
 This article is about seeking a good feasible solution in a reasonable amount of computation time to the three-dimensional Multiple Bin Size Bin Packing Problem (MBSBPP). The MBSBPP studied considers additional constraints encountered in real world air transportation situations, such as cargo stability and the particular shape of containers. This MBSBPP has already been formulated as a Mixed Integer linear Programming problem, but as yet only poor results have been achieved for even fairly small problem sizes. The goal of the work this paper describes is to develop heuristics that are able to quickly provide good initial feasible solutions for the MBSBPP. Three methodologies are considered, which are based on the decomposition of the original problem into easier subproblems: the matheuristics Relax-and-Fix, Insert-and-Fix and Fractional Relax-and-Fix. They have been parametrised on real data sets and then compared to each other. In particular, two of these techniques show promising results in reasonable computational times.
Journal: International Journal of Production Research
Pages: 1581-1592
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1355577
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355577
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Template-Type: ReDIF-Article 1.0
Author-Name: Jyh-Cheng Yu
Author-X-Name-First: Jyh-Cheng
Author-X-Name-Last: Yu
Author-Name: Chaio-Kai Chang
Author-X-Name-First: Chaio-Kai
Author-X-Name-Last: Chang
Author-Name:  Suprayitno
Author-X-Name-First: 
Author-X-Name-Last: Suprayitno
Title: Robust design optimisation via surrogate network model and soft outer array design
Abstract: 
 Robust design searches for a performance optimum with least sensitivity to variable and parameter variations. Taguchi method applies an inner array for control factors and an outer array for noise factors to estimate the Signal-to-Noise ratio (S/N). However, the cross product arrays impose serious cost concerns for expensive samplings. Also, rigorous control of noise factors to pre-set levels is impractical in industrial applications. This study presents a soft computing-based robust optimisation that merges control and noise factors into a combined experimental design to establish a surrogate using artificial neural network. Genetic algorithm is applied to search in the sub-space of control factors in the surrogate with a soft outer array to estimate the S/N served as the evolution fitness. Performance variations due to the tolerances of control and uncontrollable factors can then be estimated without conducting actual experiments. The verifications of the predicted optima become additional learning samples to refine the surrogate, and the iteration continues until convergence. The robust optimisation of a micro-accelerometer with maximised gain is used as an illustrative example. The proposed algorithm provides a superior robust optimum using a much smaller sample and less controlling cost compared with Taguchi method and a conventional response surface method.
Journal: International Journal of Production Research
Pages: 1533-1547
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1356484
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1356484
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Template-Type: ReDIF-Article 1.0
Author-Name: Adil Baykasoğlu
Author-X-Name-First: Adil
Author-X-Name-Last: Baykasoğlu
Author-Name: Fehmi Burcin Ozsoydan
Author-X-Name-First: Fehmi Burcin
Author-X-Name-Last: Ozsoydan
Title: Minimisation of non-machining times in operating automatic tool changers of machine tools under dynamic operating conditions
Abstract: 
 In many optimisation studies, it is assumed that problem related data does not change once the generated solution plan or schedule is currently in use. However, majority of real-life manufacturing problems are time-varying in their nature due to unpredictable events such as changes in lot sizes, fluctuating capacities of manufacturing constraints, changes in costs or profits. A problem, which contains at least one of these feature is referred as dynamic optimisation problem (DOP) in the related literature. The present study introduces a practical industrial application of a DOP, emerging particularly in flexible manufacturing systems (FMSs), where numerically controlled machine tools with automatic tool changers are employed. It is already known in FMSs that minimisation of non-machining times is vital for an efficient use of scarce resources. Therefore, fast response to possible changes in production is crucial in order to attain flexibility. In this context, first, a benchmarking environment is created by making use of already published problems and by introducing dynamic events. Next, effective strategies, including simulated annealing (SA) algorithm along with SA with multiple starts are developed for the introduced problem. Numerical results show that the developed SA with multiple starts is a promising approach for the introduced problem.
Journal: International Journal of Production Research
Pages: 1548-1564
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1357861
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1357861
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Template-Type: ReDIF-Article 1.0
Author-Name: Shi-Woei Lin
Author-X-Name-First: Shi-Woei
Author-X-Name-Last: Lin
Author-Name: Yi-Ting Liu
Author-X-Name-First: Yi-Ting
Author-X-Name-Last: Liu
Author-Name: Mohammad Adam Jerusalem
Author-X-Name-First: Mohammad Adam
Author-X-Name-Last: Jerusalem
Title: Bayesian reliability analysis of a products of probabilities model for parallel systems with dependent components
Abstract: 
 In a Bayesian reliability analysis of a system with dependent components, an aggregate analysis (i.e. system-level analysis) or a simplified disaggregate analysis with independence assumptions may be preferable if the estimations obtained from employing these two approaches do not deviate substantially from those derived through a disaggregate analysis, which is generally considered the most accurate method. This study was conducted to identify the key factors and their range of values that lead to estimation errors of great magnitude. In particular, a copula-based Bayesian reliability model was developed to formulate the dependence structure for a products of probabilities model of a simple parallel system. Monte Carlo simulation, regionalised sensitivity analysis and classification tree learning were employed to investigate the key factors. The resulting classification tree achieved favourable predictive accuracy. Several decision rules suggesting the optimal approach under different combinations of conditions were also extracted. This study has made a methodological contribution in laying the groundwork for investigating systems with dependent components using copula-based Bayesian reliability models. With regard to practical implications, this study also derived useful guidelines for selecting the most appropriate analysis approach under different scenarios with different magnitude of dependence.
Journal: International Journal of Production Research
Pages: 1521-1532
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1358468
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1358468
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Template-Type: ReDIF-Article 1.0
Author-Name: Salman Kimiagari
Author-X-Name-First: Salman
Author-X-Name-Last: Kimiagari
Author-Name: Benoit Montreuil
Author-X-Name-First: Benoit
Author-X-Name-Last: Montreuil
Title: Hybrid modeling approach to market deployment planning: an application to a natural disaster relief supply business venture
Abstract: 
 In today’s fast-paced global economy, entrepreneurs increasingly tend to holistically design their business ventures during the early stages of business creation. This tendency highlights the need for an efficient and systematic approach to market deployment planning due to the dynamic and complex nature of current markets and the evolving significance of global strategic positioning. Traditional market expansion planning is no longer adequate for fast-paced contexts. This paper introduces a hybrid modelling approach in order to develop a market deployment roadmap. Based on market pertinent databases, the proposed approach uses self-organising maps for market clustering and an optimisation model for market deployment road mapping within each cluster. The approach is illustrated through its application to market deployment road mapping for a business venture specialising in natural disaster supply relief. Dealing with real case studies with exploiting the vast database have not received much attention in disaster relief planning context. Hence, this study provides a novel contribution to humanitarian relief planning considering the role of the business ventures in relief operation and their business model simultaneously.
Journal: International Journal of Production Research
Pages: 1675-1707
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1359425
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1359425
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Template-Type: ReDIF-Article 1.0
Author-Name: Amir Abolhassani
Author-X-Name-First: Amir
Author-X-Name-Last: Abolhassani
Author-Name: James Harner
Author-X-Name-First: James
Author-X-Name-Last: Harner
Author-Name: Majid Jaridi
Author-X-Name-First: Majid
Author-X-Name-Last: Jaridi
Author-Name: Bhaskaran Gopalakrishnan
Author-X-Name-First: Bhaskaran
Author-X-Name-Last: Gopalakrishnan
Title: Productivity enhancement strategies in North American automotive industry
Abstract: 
 The aim of this study is to define a robust estimation model of the most dominant labour productivity measurement, Hours per Vehicle (HPV), in the auto industry. Data utilised in this study were from 10 different multinational North American carmakers from 1999 to 2007. Through a comprehensive literature review and practical consideration, 13 important variables that affect HPV were defined and developed. Several robust and advanced statistical methods were utilised to determine the best possible HPV regression equations. The MM estimator, multiple M-estimator, was defined as the best method to perform the data analysis and to derive the robust regression model to estimate HPV. Depending on the car class, the vehicle variety, model types, annual working days, car assembly utilisation and launching a new model penalise HPV; however, annual production volume, flexible manufacturing and year of production improve HPV. Moreover, Japanese plants are the benchmark regarding HPV followed by joint ventures, and American plants.
Journal: International Journal of Production Research
Pages: 1414-1431
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1359700
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1359700
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Template-Type: ReDIF-Article 1.0
Author-Name: Héctor De la Torre Gutiérrez
Author-X-Name-First: Héctor
Author-X-Name-Last: De la Torre Gutiérrez
Author-Name: Duc Truong Pham
Author-X-Name-First: Duc Truong
Author-X-Name-Last: Pham
Title: Identification of patterns in control charts for processes with statistically correlated noise
Abstract: 
 In real industrial scenarios, if the quality characteristics of a continuous or batch production process are monitored using Shewhart control charts, there could be a large number of false alarms about the process going out of control. This is because these control charts assume that the inherent noise of the monitored process is normally, independently and identically distributed, although the assumption of independence is not always correct for continuous and batch production processes. This paper presents three control chart pattern recognition systems where the inherent disturbance is assumed to be stationary. The systems use the first-order autoregressive (AR(1)), moving-average (MA(1)) and autoregressive moving-average (ARMA(1,1)) models. A special pattern generation scheme is adopted to ensure generality, randomness and comparability, as well as allowing the further categorisation of the studied patterns. Two different input representation techniques for the recognition systems were studied. These gave nearly the same performance for the MA(1) and ARMA(1,1) models, while the raw data yielded the highest accuracies when AR(1) was used. The effect of autocorrelation on the pattern recognition capabilities of the developed models was studied. It was observed that Normal and Upward Shift patterns were the most affected.
Journal: International Journal of Production Research
Pages: 1504-1520
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1360530
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1360530
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Template-Type: ReDIF-Article 1.0
Author-Name: Xianhao Xu
Author-X-Name-First: Xianhao
Author-X-Name-Last: Xu
Author-Name: Yeming (Yale) Gong
Author-X-Name-First: Yeming (Yale)
Author-X-Name-Last: Gong
Author-Name: Xiangxiang Fan
Author-X-Name-First: Xiangxiang
Author-X-Name-Last: Fan
Author-Name: Guwen Shen
Author-X-Name-First: Guwen
Author-X-Name-Last: Shen
Author-Name: Bipan Zou
Author-X-Name-First: Bipan
Author-X-Name-Last: Zou
Title: Travel-time model of dual-command cycles in a 3D compact AS/RS with lower mid-point I/O dwell point policy
Abstract: 
 Three-dimensional compact automated storage/retrieval systems (AS/RS) have been extensively applied in warehouses, with advantages of full automation, time efficiency and high space utilisation. While previous studies that use lower mid-point input/output (I/O) dwell point policy consider single-command cycles (SC), this paper builds travel-time models of dual-command cycles (DC). The S/R crane also dwells in the lower mid-point of the rack when it is idle. We validate analytical models using simulation and use analytical models to optimise system dimensions. Numerical experiments are used to compare DC with SC. The results show that DC outperform SC in terms of cycle time of one command.
Journal: International Journal of Production Research
Pages: 1620-1641
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1361049
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1361049
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Template-Type: ReDIF-Article 1.0
Author-Name: M. Mohammadi
Author-X-Name-First: M.
Author-X-Name-Last: Mohammadi
Author-Name: J.-Y. Dantan
Author-X-Name-First: J.-Y.
Author-X-Name-Last: Dantan
Author-Name: A. Siadat
Author-X-Name-First: A.
Author-X-Name-Last: Siadat
Author-Name: R. Tavakkoli-Moghaddam
Author-X-Name-First: R.
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: A bi-objective robust inspection planning model in a multi-stage serial production system
Abstract: 
 In this paper, we present a bi-objective mixed-integer linear programming (BOMILP) model for planning an inspection process used to detect nonconforming products and malfunctioning processors in a multi-stage serial production system. The model involves two inter-related decisions: (1) which quality characteristics need what kind of inspections (i.e. which-what decision) and (2) when the inspection of these characteristics should be performed (i.e. when decision). These decisions require a trade-off between the cost of manufacturing (i.e. production, inspection and scrap costs) and the customer satisfaction. Due to inevitable variations in manufacturing systems, a global robust BOMILP (RBOMILP) is developed to tackle the inherent uncertainty of the concerned parameters (i.e. production and inspection times, errors type I and II, misadjustment and dispersion of the process). In order to optimally solve the presented RBOMILP model, a meta-heuristic algorithm, namely differential evolution (DE) algorithm, is combined with the Taguchi and Monte Carlo methods. The proposed model and solution algorithm are validated through a real industrial case from a leading automotive industry in France.
Journal: International Journal of Production Research
Pages: 1432-1457
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1363425
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1363425
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Template-Type: ReDIF-Article 1.0
Author-Name: Huy Truong Quang
Author-X-Name-First: Huy
Author-X-Name-Last: Truong Quang
Author-Name: Yoshinori Hara
Author-X-Name-First: Yoshinori
Author-X-Name-Last: Hara
Title: Risks and performance in supply chain: the push effect
Abstract: 
 A risk, when it occurs, causes negative effects on outputs. Typically risks are not independent, as multiple risks occur simultaneously. These risks have links, creating a ‘push’ effect, thus increasing the severity of each and all risk(s) on outputs. This paper aims to verify the mechanism of the push effect that is a new approach in the supply chain risk management literature. In this study, two models were compared: (1) only exists in direct effects of risks on supply chain performance, i.e. the competitive model. The other, (2), contains relationships among risks that show the mechanism of the push effect, i.e. the hypothesised model. Empirical evidence found in the Vietnam construction sector proved that the hypothesised model is better suited and has greater effect on supply chain performance in terms of each and all risk(s). Comparing 55% variance of the competitive model, the hypothesised one can explain up to 73% variance of supply chain performance. These results confirm our hypotheses of the push effect. Furthermore, findings achieved from this research can be used as ‘a guideline’ for reducing the impact of this mechanism.
Journal: International Journal of Production Research
Pages: 1369-1388
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1363429
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1363429
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Template-Type: ReDIF-Article 1.0
Author-Name: Pailin Krachangphiphop
Author-X-Name-First: Pailin
Author-X-Name-Last: Krachangphiphop
Author-Name: Jessada Wannasin
Author-X-Name-First: Jessada
Author-X-Name-Last: Wannasin
Author-Name: Napisphon Meemongkol
Author-X-Name-First: Napisphon
Author-X-Name-Last: Meemongkol
Title: Process-based cost modelling for gas induced semi-solid-processed below-knee prosthesis
Abstract: 
 Below-knee prosthesis is much needed in Thailand and the world over because it serves as a close substitute for a missing body part (e.g. a device to aid people with paraplegia). Production of these components by gas-induced semi-solid process is relatively new, and investors need to be assured of success before committing themselves into a venture. Most cost models, such as the activity-based model, have flexibility limitations, and hence more input-sensitive – the process-based cost model (PBCM) – is alternatively employed in analysing more simple work process, appropriate production volume and unit cost, and was utilised in this research. An array of production volumes (5000–100,000 sets) and a number of daily work shifts (1–3) were investigated. From detailed breakdowns, analysis results suggested an optimal annual production volume in the range of 10,000–40,000 sets employing any shifts per day. Below 10,000, unit cost escalates very sharply, and beyond 40,000 it decreases only marginally. Production for export purposes is feasible since the annual domestic requirement in Thailand is only a fraction of this volume. PBCM had also proven an effective tool in this case.
Journal: International Journal of Production Research
Pages: 1361-1368
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1364441
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1364441
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:4:p:1361-1368




Template-Type: ReDIF-Article 1.0
Author-Name: Dotun Adebanjo
Author-X-Name-First: Dotun
Author-X-Name-Last: Adebanjo
Author-Name: Pei-Lee Teh
Author-X-Name-First: Pei-Lee
Author-X-Name-Last: Teh
Author-Name: Pervaiz K. Ahmed
Author-X-Name-First: Pervaiz K.
Author-X-Name-Last: Ahmed
Title: The impact of supply chain relationships and integration on innovative capabilities and manufacturing performance: the perspective of rapidly developing countries
Abstract: 
 The purpose of this research is to investigate the relationships between supply chain relationships/integration, innovative capabilities and manufacturing performance. The study adopts Institutional Theory and Resource-Based View Theory to assess relationships in 171 organisations drawn from three rapidly developing countries – Brazil, India and China. Data were collected using the International Manufacturing Strategy Survey (IMSS VI) and analysed using structural equation modelling. The study found that supply chain relationships and integration relate positively to both product and process innovative capabilities. The study also found that both product and process innovative capabilities relate positively to manufacturing performance. Furthermore, there was a positive relationship between product innovative capabilities and process innovative capabilities. The findings provide new insights into manufacturers in the three countries and show that the relationships they build with their customers have encouraged them to develop new innovative capabilities. These new capabilities, in turn, have enabled them to reap benefits of improved manufacturing performance.
Journal: International Journal of Production Research
Pages: 1708-1721
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1366083
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1366083
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:4:p:1708-1721




Template-Type: ReDIF-Article 1.0
Author-Name: Joaquim Jorge Vicente
Author-X-Name-First: Joaquim Jorge
Author-X-Name-Last: Vicente
Author-Name: Susana Relvas
Author-X-Name-First: Susana
Author-X-Name-Last: Relvas
Author-Name: Ana Paula Barbosa-Póvoa
Author-X-Name-First: Ana Paula
Author-X-Name-Last: Barbosa-Póvoa
Title: Effective bullwhip metrics for multi-echelon distribution systems under order batching policies with cyclic demand
Abstract: 
 A large number of problems in a distribution supply chain require that decisions are made in the presence of the bullwhip effect phenomenon. The impact of the order batching policies on the bullwhip effect is analysed in this paper, when cycle demand on a multi-echelon supply chain operating is considered. While investigating which bullwhip effect metrics are more adequate to measure the bullwhip effect in these type of systems, the optimal reordering plan that minimises the operation costs of the overall system is calculated. A Mixed Integer Linear Programming (MILP) model is developed that takes into account an inventory and distribution system formed by multiple warehouses and retailers with lateral transshipments. The bullwhip effect is measured through four metrics: the echelon average inventory; the echelon inventory variance ratio; the echelon average order; and the echelon order rate variance ratio. As conclusion the inventory metrics suggest that (i) using batching policy reduces instability; (ii) batching may reduce in general order variance if using larger batches and (iii) cycle demand length has no major impact in the bullwhip effect. A motivational example and a real word case study are used and tested.
Journal: International Journal of Production Research
Pages: 1593-1619
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1367105
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1367105
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Template-Type: ReDIF-Article 1.0
Author-Name: Gabriella Dellino
Author-X-Name-First: Gabriella
Author-X-Name-Last: Dellino
Author-Name: Teresa Laudadio
Author-X-Name-First: Teresa
Author-X-Name-Last: Laudadio
Author-Name: Renato Mari
Author-X-Name-First: Renato
Author-X-Name-Last: Mari
Author-Name: Nicola Mastronardi
Author-X-Name-First: Nicola
Author-X-Name-Last: Mastronardi
Author-Name: Carlo Meloni
Author-X-Name-First: Carlo
Author-X-Name-Last: Meloni
Title: A reliable decision support system for fresh food supply chain management
Abstract: 
 The paper proposes a decision support system (DSS) for the supply chain of packaged fresh and highly perishable products. The DSS combines a unique tool for sales forecasting with order planning which includes an individual model selection system equipped with ARIMA, ARIMAX and transfer function forecasting model families, the latter two accounting for the impact of prices. Forecasting model parameters are chosen via two alternative tuning algorithms: a two-step statistical analysis, and a sequential parameter optimisation framework for automatic parameter tuning. The DSS selects the model to apply according to user-defined performance criteria. Then, it considers sales forecasting as a proxy of expected demand and uses it as input for a multi-objective optimisation algorithm that defines a set of non-dominated order proposals with respect to outdating, shortage, freshness of products and residual stock. A set of real data and a benchmark – based on the methods already in use – are employed to evaluate the performance of the proposed DSS. The analysis of different configurations shows that the DSS is suitable for the problem under investigation; in particular, the DSS ensures acceptable forecasting errors and proper computational effort, providing order plans with associated satisfactory performances.
Journal: International Journal of Production Research
Pages: 1458-1485
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1367106
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1367106
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Template-Type: ReDIF-Article 1.0
Author-Name: Patricia van Loon
Author-X-Name-First: Patricia
Author-X-Name-Last: van Loon
Author-Name: Luk N. Van Wassenhove
Author-X-Name-First: Luk N.
Author-X-Name-Last: Van Wassenhove
Title: Assessing the economic and environmental impact of remanufacturing: a decision support tool for OEM suppliers
Abstract: 
 The circular economy is often presented as a solution for companies to increase the sustainability of their business. In many situations where suppliers produce subassemblies or modules for OEMs in a B2B context, dependency on their clients limits their options for profitable closed-loop supply chains. In this paper, we develop a simple tool suppliers can use to quickly assess whether remanufacturing is economic and environmentally attractive compared to producing new components. We derive optimal acquisition and reuse quantities that minimise total costs. Based on our analysis with a supplier in the automotive industry, we find that used core prices and remanufacturing yield rates have a large impact while an optimised design for remanufacturing can only marginally improve the situation. The tool is applicable to a wide variety of suppliers and industries that remanufacture their modules or subassemblies, or are exploring the option to engage in remanufacturing operations.
Journal: International Journal of Production Research
Pages: 1662-1674
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1367107
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1367107
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Template-Type: ReDIF-Article 1.0
Author-Name: Yavuz A. Bozer
Author-X-Name-First: Yavuz A.
Author-X-Name-Last: Bozer
Author-Name: Chate Eamrungroj
Author-X-Name-First: Chate
Author-X-Name-Last: Eamrungroj
Title: Throughput analysis of multi-device trip-based material handling systems operating under the modified-FCFS dispatching rule
Abstract: 
 We present an analytic model to assess the performance of a trip-based material handling system with multiple devices dispatched according to the modified-first-come-first-served rule. A key element of the model is the analytic treatment of empty trips based on whether they are device- or station-initiated. The model is evaluated against simulation results using multiple layout configurations and devices at different levels of utilisation. In developing the analytic model, we also investigate the role and impact of device-initiated dispatching vs. station-initiated dispatching, and show results that shed light on conflicting views presented in the literature on this subject. The proposed analytic model can be used to rapidly evaluate alternative handling systems and to conduct various ‘what if’ analyses; it performs reasonably well across a range of systems that were tested via simulation. In evaluating the accuracy of the model, we introduce a unique and more effective technique based on the allocation of empty trips out of each station. In addition, we propose an approximate but simple method to check for system stability.
Journal: International Journal of Production Research
Pages: 1486-1503
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1367108
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1367108
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaolin Xi
Author-X-Name-First: Xiaolin
Author-X-Name-Last: Xi
Author-Name: Yonglin Cai
Author-X-Name-First: Yonglin
Author-X-Name-Last: Cai
Author-Name: Fenglei Zhang
Author-X-Name-First: Fenglei
Author-X-Name-Last: Zhang
Author-Name: Heng Wang
Author-X-Name-First: Heng
Author-X-Name-Last: Wang
Title: An efficient algorithm for calculating the cutter location point based on projection method
Abstract: 
 Aiming at improving the efficiency of calculating the cutter location point with toroid cutter based on the projection method in NC machining for surface, a new algorithm is proposed to calculate the cutter location point directly by torus surface approximating the surface to be machined. According to the geometric information of the points on the surface, the geometrical conditions of the two tangential tori are figured out, and then the contact point is obtained by solving multivariate non-linear equations. Parameters of the tangent point on the surface to be machined are calculated in the next step. Finally, the cutter location point is calculated by a small adjustment. The proposed algorithm is applied to calculate the cutter location point with toroid cutter in surface machining and compared with the existing algorithm. The results show that the computing time of the proposed algorithm in this paper saved about 63–78%.
Journal: International Journal of Production Research
Pages: 1722-1731
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1367109
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1367109
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Template-Type: ReDIF-Article 1.0
Author-Name: Thomas Hutter
Author-X-Name-First: Thomas
Author-X-Name-Last: Hutter
Author-Name: Stefan Haeussler
Author-X-Name-First: Stefan
Author-X-Name-Last: Haeussler
Author-Name: Hubert Missbauer
Author-X-Name-First: Hubert
Author-X-Name-Last: Missbauer
Title: Successful implementation of an order release mechanism based on workload control: a case study of a make-to-stock manufacturer
Abstract: 
 This paper deals with improving the lead-time performance of a large crystal manufacturer that uses a state-of-the-art commercial Enterprise Resource Planning system. Since the company encountered some limitations of the standard production planning and control (PPC) system it sought for improvements by implementing an order release mechanism based on workload control (WLC). WLC employs certain rules for releasing orders in order to maintain a certain level of work in process to achieve a certain utilisation of the production system and thus control the flow times in order to meet the required due dates of the orders. We describe the successful implementation of an order release mechanism based on the WLC concept in this make-to-stock company. The paper describes the implemented order release mechanism, the implementation process and its impact on the company’s performance. We show that the core function of WLC – the order release mechanism – can be integrated successfully into an existing PPC system. Furthermore, this study highlights the applicability of WLC to a wider range of companies, especially to make-to-stock manufacturers.
Journal: International Journal of Production Research
Pages: 1565-1580
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1369598
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1369598
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: (i)-(i)
Issue: 4
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1373893
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1373893
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:4:p:(i)-(i)




Template-Type: ReDIF-Article 1.0
Author-Name: Yanjing Ou
Author-X-Name-First: Yanjing
Author-X-Name-Last: Ou
Author-Name: Nan Chen
Author-X-Name-First: Nan
Author-X-Name-Last: Chen
Author-Name: Michael B.C. Khoo
Author-X-Name-First: Michael B.C.
Author-X-Name-Last: Khoo
Title: An efficient multivariate control charting mechanism based on SPRT
Abstract: 
 This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling’s T2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling’s T2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme.
Journal: International Journal of Production Research
Pages: 1937-1949
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.925601
File-URL: http://hdl.handle.net/10.1080/00207543.2014.925601
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:7:p:1937-1949




Template-Type: ReDIF-Article 1.0
Author-Name: Theodor Borangiu
Author-X-Name-First: Theodor
Author-X-Name-Last: Borangiu
Author-Name: Silviu Răileanu
Author-X-Name-First: Silviu
Author-X-Name-Last: Răileanu
Author-Name: Thierry Berger
Author-X-Name-First: Thierry
Author-X-Name-Last: Berger
Author-Name: Damien Trentesaux
Author-X-Name-First: Damien
Author-X-Name-Last: Trentesaux
Title: Switching mode control strategy in manufacturing execution systems
Abstract: 
 The paper describes a semi-heterarchical control solution for mixed planning and scheduling, routing and job execution in flexible manufacturing systems based on the paradigms of holonic manufacturing and product-driven automation. The main feature of the control solution is the bidirectional switching of the operating mode (scheduling, routing) between centralised and decentralised in the presence of perturbations to ensure as long as possible both global optimisation and agility to changes in batch orders, while featuring robustness to disturbances in the production environment. At the theoretical level, the control solution is described in terms of generic structural and dynamic models. The implementation is done using a multi-agent Java Agent Development Framework framework.
Journal: International Journal of Production Research
Pages: 1950-1963
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.935825
File-URL: http://hdl.handle.net/10.1080/00207543.2014.935825
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:7:p:1950-1963




Template-Type: ReDIF-Article 1.0
Author-Name: Aamir Saghir
Author-X-Name-First: Aamir
Author-X-Name-Last: Saghir
Title: The bivariate dispersion control charts for non-normal processes
Abstract: 
 This article study the performance of the bivariate dispersion control charts, namely the S$ \left| S \right| $ and the G$ \left| G \right| $ charts, for the bivariate normal, bivariate exponential, bivariate t(5), bivariate Logistic and bivariate Laplace distributions. The asymmetrical probability limits of these charts are proposed for the distributions under study. The estimated factors and quantile points used in the construction of these two charts are provided for the bivariate non-normal distributions. The effect of improper use of constants and quantile points in the construction of the S$ \left| S \right| $ and the G$ \left| G \right| $ charts are studied in terms of the associated false alarm rates. The performances of the proposed limits of the given charts are evaluated in terms of average run length for the various bivariate distributions and compared. The performances of these control charts are also compared with their respective 3σ limits.
Journal: International Journal of Production Research
Pages: 1964-1979
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.942006
File-URL: http://hdl.handle.net/10.1080/00207543.2014.942006
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Template-Type: ReDIF-Article 1.0
Author-Name: Ping-Chen Chang
Author-X-Name-First: Ping-Chen
Author-X-Name-Last: Chang
Author-Name: Yi-Kuei Lin
Author-X-Name-First: Yi-Kuei
Author-X-Name-Last: Lin
Title: Fuzzy-based system reliability of a labour-intensive manufacturing network with repair
Abstract: 
 This paper presents a fuzzy-based assessment model to evaluate system reliability of a labour-intensive manufacturing system with repair actions. Due to the uncertainty in human performance, labour-intensive manufacturing systems must determine the capacity of each labourer in order to accurately characterise the performance of the systems. Therefore, we model such a manufacturing system as a fuzzy multi-state network in order to characterise the labourers’ influence on workstation performance. First, the workstation reliability is defined according to the loading state by three fuzzy membership functions, namely ‘under loading’, ‘normal loading’ and ‘over loading’, respectively. The system reliability is subsequently evaluated with fuzzy intersection operations in terms of these workstation reliabilities. Thus, the system reliability is defined as a fuzzy membership function to assess whether the manufacturing system performance is sufficient to satisfy the demand reliably. A case study of a footwear manufacturing system is illustrated to explain the proposed model. Furthermore, we apply the proposed model to a non-labour-intensive manufacturing network in order to validate the applicability to this class of systems.
Journal: International Journal of Production Research
Pages: 1980-1995
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.944279
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Template-Type: ReDIF-Article 1.0
Author-Name: Jaehee Kim
Author-X-Name-First: Jaehee
Author-X-Name-Last: Kim
Author-Name: Chang Ouk Kim
Author-X-Name-First: Chang Ouk
Author-X-Name-Last: Kim
Author-Name: Choonjong Kwak
Author-X-Name-First: Choonjong
Author-X-Name-Last: Kwak
Title: Analysis of timeout mechanism in a testing-repair model
Abstract: 
 With a dispatching rule collaborated, timeout is an effort to maximise system performance, by disabling the access of a job to a resource when the job keeps the resource idle too long and then by giving a waiting job the access to the resource. This paper first defines a generic testing-repair model with a single tester and proves that there exists at least one optimal solution in two extreme timeout thresholds with respect to the makespan. Experimental results are presented to support the proof. This problem is then formulated as a discrete multi-objective optimisation problem with five common performance measures of production systems. The two extreme timeout thresholds are efficient solutions in all cases, and they are even dominant in several cases. This paper explores the properties of the timeout collaboration protocol and provides useful insights into applying the timeout mechanism to production systems.
Journal: International Journal of Production Research
Pages: 1996-2010
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.944627
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Template-Type: ReDIF-Article 1.0
Author-Name: Nani Kurniati
Author-X-Name-First: Nani
Author-X-Name-Last: Kurniati
Author-Name: Ruey-Huei Yeh
Author-X-Name-First: Ruey-Huei
Author-X-Name-Last: Yeh
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Title: Designing a variables two-plan sampling system of type TNTVSS-(nT, nN; k) for controlling process fraction nonconforming with unilateral specification limit
Abstract: 
 This paper proposes a variables two-plan sampling system involving normal and tightened inspections, denoted as TNTVSS-(nT,nN;k)$ (n_{\text{T}}, \, n_{\text{N}}; \, k) $, for controlling process fraction nonconforming with a unilateral specification limit based on one-sided capability indices. The system utilises two single variables sampling plans with different sample sizes (nT,nN)$ (n_{\text{T}} , \, n_{\text{N}} ) $ and the same critical acceptance value k$ k $, where nT$ n_{\text{T}} $ and nN$ n_N $ are sample sizes required for tightened inspection and normal inspection, respectively. The tightened inspection plan is used when the quality deteriorates and the normal inspection plan is used when the quality is found to be good. The operating characteristic (OC) function of the proposed sampling system is developed based on the exact sampling distribution. The plan parameters under various settings are determined by solving two non-linear equations simultaneously, which satisfy the required quality levels and allowable risks given by the producer and the consumer. The behaviour of the proposed sampling system in terms of the OC curve and the average sample number are also examined, discussed and compared with the traditional single variables sampling plan.
Journal: International Journal of Production Research
Pages: 2011-2025
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.946159
File-URL: http://hdl.handle.net/10.1080/00207543.2014.946159
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Template-Type: ReDIF-Article 1.0
Author-Name: Cang Wu
Author-X-Name-First: Cang
Author-X-Name-Last: Wu
Author-Name: Fei Liu
Author-X-Name-First: Fei
Author-X-Name-Last: Liu
Author-Name: Bo Zhu
Author-X-Name-First: Bo
Author-X-Name-Last: Zhu
Title: Control chart pattern recognition using an integrated model based on binary-tree support vector machine
Abstract: 
 Control charts are important tools in statistical process control for determining whether a process is in control. Furthermore, effective recognition of abnormal control chart pattern (CCP) can greatly narrow the set of possible assignable causes, significantly shortening the diagnostic process. In this article, an integrated model in which binary-tree support vector machine (BTSVM) is applied for abnormal CCP recognition is proposed. The integrated model consists of three stages. In the first stage, five statistical features and eight shape features are extracted. In the second stage, a binary-class support vector machine is used to detect abnormal CCPs. In the third stage, the BTSVM is applied to classify the detected abnormal CCPs. Additionally, the Fisher Ratio method is utilised at each node of the binary tree to design the architecture of the BTSVM. Simulation experimental results show that the proposed model is able to effectively identify the type of CCPs and that the classification accuracies of the second and the third stages are up to 100% and 98.5%, respectively. A series of contrast experiments prove that the classification accuracy of BTSVM outperforms that of one against one and one against rest for abnormal CCP classification.
Journal: International Journal of Production Research
Pages: 2026-2040
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.948222
File-URL: http://hdl.handle.net/10.1080/00207543.2014.948222
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Template-Type: ReDIF-Article 1.0
Author-Name: Mou-Yuan Liao
Author-X-Name-First: Mou-Yuan
Author-X-Name-Last: Liao
Title: Assessing process incapability when collecting data from multiple batches
Abstract: 
 Process capability indices have been widely used in industry to measure the ability of firms to meet quality specifications. The Cpp$ {C_{pp}} $ index not only can directly reflect the process incapability, but also provides more information regarding process inaccuracy and imprecision than other indices. Therefore, it can help contract manufacturers to better understand their processes for improving quality performance. In real applications, the sampling data are often collected from multiple batches. Based on this condition, this study proposes an alternate method to assess the true Cpp$ {C_{pp}} $ value. The concept of generalised pivotal quantity is used, and the generalised confidence interval is derived to estimate Cpp$ {C_{pp}} $. Furthermore, we provide simulations to compare the performances of our proposed method with an existing method. The results show that the empirical confidences of the two methods are affected by the degree of process departure. Therefore, practitioners can select the appropriate one to assess the process capability, depending on the degree of process departure.
Journal: International Journal of Production Research
Pages: 2041-2054
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.952796
File-URL: http://hdl.handle.net/10.1080/00207543.2014.952796
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Template-Type: ReDIF-Article 1.0
Author-Name: Hao Tang
Author-X-Name-First: Hao
Author-X-Name-Last: Tang
Author-Name: Chao Wang
Author-X-Name-First: Chao
Author-X-Name-Last: Wang
Author-Name: Masayuki Matsui
Author-X-Name-First: Masayuki
Author-X-Name-Last: Matsui
Author-Name: Bing Liu
Author-X-Name-First: Bing
Author-X-Name-Last: Liu
Title: Hierarchical coordinated control of a multi-procedure CSPS system by learning optimisation methods
Abstract: 
 We consider the hierarchical coordinated control of a multi-procedure conveyor-serviced production station system with flexible stations deployed between adjacent procedures, which includes a dynamic intra-procedure switching control of the flexible stations for the goal of balancing different procedures and a dynamic inter-procedure production coordination of all of the stations within each procedure. It is complicated in terms of modelling and optimisation, and thus, it is difficult to find a solution using numerical methods; as a result, we refer to model-free learning optimisation methods. First, we establish a neuro-dynamic programming algorithm by utilising cerebellar model articulation controllers (CMACs) to approximate state-action values at an upper hierarchy. Second, according to the reaction-diffusion phenomenon, we combine a Wolf-PHC algorithm with a local information-interaction scheme to learn look-ahead control policies at the lower hierarchy. Simulation results show that, compared with traditional Q-learning and the backward Q-learning based Q-learning, our proposed CMAC-based learning optimisation methods have the advantages of yielding a higher processing rate and having a faster optimisation speed with a lower storage requirement.
Journal: International Journal of Production Research
Pages: 2055-2072
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.952797
File-URL: http://hdl.handle.net/10.1080/00207543.2014.952797
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Template-Type: ReDIF-Article 1.0
Author-Name: Fan-Tien Cheng
Author-X-Name-First: Fan-Tien
Author-X-Name-Last: Cheng
Author-Name: Chun-Fang Chen
Author-X-Name-First: Chun-Fang
Author-X-Name-Last: Chen
Author-Name: Yao-Sheng Hsieh
Author-X-Name-First: Yao-Sheng
Author-X-Name-Last: Hsieh
Author-Name: Hsuan-Heng Huang
Author-X-Name-First: Hsuan-Heng
Author-X-Name-Last: Huang
Author-Name: Chu-Chieh Wu
Author-X-Name-First: Chu-Chieh
Author-X-Name-Last: Wu
Title: Intelligent sampling decision scheme based on the AVM system
Abstract: 
 Wafer inspection plays a significant role in monitoring the quality of wafers production for continuous improvement. However, it requires measuring tools and additional cycle time to do real metrology, which is costly and time-consuming. Therefore, reducing sampling rate to as low as possible is a high priority to reduce production cost. Several sampling methods in the literature were proposed to achieve this goal. They utilised real sampling inspections as the representatives for the other related wafers to monitor the whole production process. Under the condition of stable manufacturing process, virtual metrology (VM) may be applied to monitor the quality of wafers, while real metrology is unavailable. Therefore, the sampling rate may further be reduced with a sampling decision scheme being designed according to reliable VM. Nevertheless, once a new production variation occurs between planned samplings and no real metrology is available during this period for updating the VM models, un-reliable VM predictions may be produced. The authors have developed the automatic virtual metrology (AVM) system for various VM applications. Therefore, this paper focuses on applying various indices of the AVM system to develop an intelligent sampling decision scheme for reducing sampling rate, while VM accuracy is still sustained.
Journal: International Journal of Production Research
Pages: 2073-2088
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.955924
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Template-Type: ReDIF-Article 1.0
Author-Name: Evangelos Psomas
Author-X-Name-First: Evangelos
Author-X-Name-Last: Psomas
Author-Name: Jiju Antony
Author-X-Name-First: Jiju
Author-X-Name-Last: Antony
Title: The effectiveness of the ISO 9001 quality management system and its influential critical factors in Greek manufacturing companies
Abstract: 
 The purpose of the study is firstly, to empirically validate the conceptual structure of the effectiveness of the ISO 9001 quality management system (QMS) in manufacturing companies and secondly, to determine the critical factors that have a significant impact on the QMS’s effectiveness. A research study was carried out through a structured questionnaire in a sample of 163 ISO 9001 certified Greek companies. Exploratory and confirmatory factor analyses are applied to extract and validate latent constructs, while their relationships are determined through structural equation modelling. The analyses confirm the conceptual factorial structure of the ISO 9001 QMS’s effectiveness which consists of three dimensions – the ISO 9001 objectives (prevention of non-conformities, continuous improvement and customer satisfaction focus). The analysis also confirms the five dimensions of the critical factors for ISO 9001 QMS effectiveness identified in the literature (internal motivation, external environment pressure, company attributes, employee attributes and quality system attributes). However, only the company internal motivation, company attributes and employee attributes have a significant impact on the ISO 9001 QMS’s effectiveness.
Journal: International Journal of Production Research
Pages: 2089-2099
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.965353
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965353
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaohong Zhang
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Zhang
Author-Name: Jianchao Zeng
Author-X-Name-First: Jianchao
Author-X-Name-Last: Zeng
Title: Deterioration state space partitioning method for opportunistic maintenance modelling of identical multi-unit systems
Abstract: 
 We propose a deterioration state space partitioning method for opportunistic maintenance modelling of identical multi-unit systems with economic dependence. The proposed method presents a common description and model for multi-unit systems with identical units based on the mutual characteristics of opportunistic maintenance models with different maintenance strategies. In the method, all possible maintenance combinations of general multi-unit systems with a known number of identical units at each maintenance decision point and their corresponding probabilities are deduced on the basis of analysis of the scenarios of multi-unit systems with one, two and three units. Further, we develop a general representation of the stationary law of unit deterioration and its numerical solution. Numerical experiments verify the correctness of our deterioration state space partitioning method and its numerical solution. The proposed method is applicable to both single-unit and multi-unit systems, and provides a new generalised modelling method for maintenance optimisation of multi-unit systems with identical units.
Journal: International Journal of Production Research
Pages: 2100-2118
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.965354
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965354
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Template-Type: ReDIF-Article 1.0
Author-Name: J.J. Ruiz-Aguilar
Author-X-Name-First: J.J.
Author-X-Name-Last: Ruiz-Aguilar
Author-Name: I.J. Turias
Author-X-Name-First: I.J.
Author-X-Name-Last: Turias
Author-Name: M.J. Jiménez-Come
Author-X-Name-First: M.J.
Author-X-Name-Last: Jiménez-Come
Title: A two-stage procedure for forecasting freight inspections at Border Inspection Posts using SOMs and support vector regression
Abstract: 
 The number of goods which passes through a border inspection post (BIP) may cause important congestion problems and delays in the port system, having an effect in the level of service of the port. Therefore, a prediction of the daily number of goods subject to inspection in BIPs seems to be a potential solution. This study proposes a two-stage procedure to better predict freight inspections. In the first stage, a Kohonen self-organising map (SOM) is employed to decompose the whole data into smaller regions which display similar statistical characteristics. In the second stage, support vector regression (SVR) is used to forecast the different homogeneous regions individually. The results obtained are compared with the single SVR technique. The experiment shows that SOM–SVR models outperform the single SVR models in the inspection forecasting. The application of the proposed technique may become a supporting tool for the prediction of the number of goods subject to inspection in BIPs of other international seaports or airports, and provides relevant information for decision-making and resource planning.
Journal: International Journal of Production Research
Pages: 2119-2130
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.965852
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965852
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Template-Type: ReDIF-Article 1.0
Author-Name: Jun Yang
Author-X-Name-First: Jun
Author-X-Name-Last: Yang
Author-Name: Huan Yu
Author-X-Name-First: Huan
Author-X-Name-Last: Yu
Author-Name: Yuan Cheng
Author-X-Name-First: Yuan
Author-X-Name-Last: Cheng
Author-Name: Min Xie
Author-X-Name-First: Min
Author-X-Name-Last: Xie
Title: Design of exponential control charts based on average time to signal using a sequential sampling scheme
Abstract: 
 Exponential charts based on time-between-events (TBE) data are widely investigated and applied in various fields. The average time to signal (ATS) is used instead of the average run length to evaluate the performance of TBE charts, since the ATS involves both the number and the time of samples inspected until a signal occurs. An ATS-unbiased exponential control chart is proposed when the in-control parameter is known. Considering the need in practice to start monitoring a production process as soon as possible, a sequential sampling scheme is adopted and the in-control parameter is estimated by an unbiased and consistent estimator. Some specific guidelines to stop updating control limits are obtained from the relationship between the phase I sample size and the actual false alarm rate. Finally, two real examples are given to illustrate the implementation and efficiency of the proposed method.
Journal: International Journal of Production Research
Pages: 2131-2145
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.974848
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974848
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Template-Type: ReDIF-Article 1.0
Author-Name: George Nenes
Author-X-Name-First: George
Author-X-Name-Last: Nenes
Author-Name: Konstantinos A. Tasias
Author-X-Name-First: Konstantinos A.
Author-X-Name-Last: Tasias
Author-Name: Giovanni Celano
Author-X-Name-First: Giovanni
Author-X-Name-Last: Celano
Title: A general model for the economic-statistical design of adaptive control charts for processes subject to multiple assignable causes
Abstract: 
 Fully adaptive control charts are efficient statistical process control means to monitor a quality characteristic affecting the outcome of a manufacturing process. Usually, the performance of these adaptive charts is investigated in processes characterised by the possibility of the occurrence of a single assignable cause. However, this assumption is frequently far from reality, because a process shift to the out-of-control condition can be the consequence of several assignable causes, which can occur at the same time or independently. In this paper, we investigate the economic-statistical design of a variable-parameter (Vp) Shewhart control chart monitoring the process mean in the presence of multiple assignable causes. We develop a Markov chain that models the occurrence of several assignable causes leading to progressive process deterioration and calling for different corrective actions. A benchmark of examples has been generated to compare the performance of the Vp control chart with other adaptive control charts and the fixed-parameter control chart. The obtained results reveal the economic superiority of the Vp control chart.
Journal: International Journal of Production Research
Pages: 2146-2164
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.974850
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974850
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Template-Type: ReDIF-Article 1.0
Author-Name: Wen-long Li
Author-X-Name-First: Wen-long
Author-X-Name-Last: Li
Author-Name: Li-ping Zhou
Author-X-Name-First: Li-ping
Author-X-Name-Last: Zhou
Author-Name: Si-Jie Yan
Author-X-Name-First: Si-Jie
Author-X-Name-Last: Yan
Title: A case study of blade inspection based on optical scanning method
Abstract: 
 Blades play an important role in aviation engine, gas turbine and jet engine. Inspecting the blade by optical method is a meaningful work in manufacturing industry. During optical inspecting process, one common problem encountered is that the scanned point cloud is large scale and noisy. In this paper, we present a systematic introduction of simplification, smoothing and parameter extraction with respect to point-sampled blades. First, the moving least square surface is applied to create a geometric deviation, which is used to subdivide and cluster the point cloud. Then, the information entropy in k-neighbourhood is defined to smooth point-sampled surface, meanwhile preserving high curvature feature. Furthermore, the computation method of single/multi section parameters is presented, and test experiments are performed in iCloud3D Blade V1.0. Experimental results demonstrate the feasibility and effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 2165-2178
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.974851
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974851
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaosong Wu
Author-X-Name-First: Xiaosong
Author-X-Name-Last: Wu
Author-Name: Rui Miao
Author-X-Name-First: Rui
Author-X-Name-Last: Miao
Author-Name: Xinyi Zhang
Author-X-Name-First: Xinyi
Author-X-Name-Last: Zhang
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Author-Name: Xuening Chu
Author-X-Name-First: Xuening
Author-X-Name-Last: Chu
Title: A conjugate Bayesian approach to control chart for multi-batch and low volume production
Abstract: 
 Control chart could effectively reflect whether a manufacturing process is currently under control or not. The calculation of control limits of the control chart has been focusing on traditional frequency approach, which requires a large sample size for an accurate estimation. A conjugate Bayesian approach is introduced to correct the calculation error of control limits with traditional frequency approach in multi-batch and low volume production. Bartlett’s test, analysis of variance test and standardisation treatment are used to construct a proper prior distribution in order to calculate the Bayes estimators of process distribution parameters for the control limits. The case study indicates that this conjugate Bayesian approach presents better performance than the traditional frequency approach when the sample size is small.
Journal: International Journal of Production Research
Pages: 2179-2185
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.975857
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975857
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Template-Type: ReDIF-Article 1.0
Author-Name: Arturo Calvo-Mora
Author-X-Name-First: Arturo
Author-X-Name-Last: Calvo-Mora
Author-Name: Araceli Picón-Berjoyo
Author-X-Name-First: Araceli
Author-X-Name-Last: Picón-Berjoyo
Author-Name: Carolina Ruiz-Moreno
Author-X-Name-First: Carolina
Author-X-Name-Last: Ruiz-Moreno
Author-Name: Lourdes Cauzo-Bottala
Author-X-Name-First: Lourdes
Author-X-Name-Last: Cauzo-Bottala
Title: Contextual and mediation analysis between TQM critical factors and organisational results in the EFQM Excellence Model framework
Abstract: 
 Following a total quality management (TQM) approach and the EFQM Model framework, this contribution aims to study the influence of TQM social factors on organisational results, by considering the TQM technical factors as a mediating variable in this relationship. Moreover, the effect of size and type of business on the implementation of TQM and results is analysed, as well as determining which TQM practices have a more important effect on the operational results. The research questions and hypotheses proposed in this research model are tested on a sample of 116 Spanish firms. The results support the reliability, validity and the high-predictive power of the EFQM Excellence Model as a framework for the implementation of TQM. Moreover, our findings indicate that TQM social factors provide a cornerstone for the success of the quality system. Similarly, TQM technical factors partially mediate the relationship between TQM social factors and results. It was also found that TQM social factors and processes management are the main predictors of operational performance. Finally, significant differences were found in TQM implementation, and in the key results of companies, based on their size; however, these differences are not significant based on the sector activity.
Journal: International Journal of Production Research
Pages: 2186-2201
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.975859
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975859
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehrdad Mohammadi
Author-X-Name-First: Mehrdad
Author-X-Name-Last: Mohammadi
Author-Name: Ali Siadat
Author-X-Name-First: Ali
Author-X-Name-Last: Siadat
Author-Name: Jean-Yves Dantan
Author-X-Name-First: Jean-Yves
Author-X-Name-Last: Dantan
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: Mathematical modelling of a robust inspection process plan: Taguchi and Monte Carlo methods
Abstract: 
 This study develops a new optimisation framework for process inspection planning of a manufacturing system with multiple quality characteristics, in which the proposed framework is based on a mixed-integer mathematical programming (MILP) model. Due to the stochastic nature of production processes and since their production processes are sensitive to manufacturing variations; a proportion of products do not conform the design specifications. A common source of these variations is maladjustment of each operation that leads to a higher number of scraps. Therefore, uncertainty in maladjustment is taken into account in this study. A twofold decision is made on the subject that which quality characteristic needs what kind of inspection, and the time this inspection should be performed. To cope with the introduced uncertainty, two robust optimisation methods are developed based on Taguchi and Monte Carlo methods. Furthermore, a genetic algorithm is applied to the problem to obtain near-optimal solutions. To validate the proposed model and solution approach, several numerical experiments are done on a real industrial case. Finally, the conclusion is provided.
Journal: International Journal of Production Research
Pages: 2202-2224
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.980460
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980460
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:7:p:2202-2224




Template-Type: ReDIF-Article 1.0
Author-Name: María Nela Pastuizaca Fernández
Author-X-Name-First: María Nela
Author-X-Name-Last: Pastuizaca Fernández
Author-Name: Andrés Carrión García
Author-X-Name-First: Andrés
Author-X-Name-Last: Carrión García
Author-Name: Omar Ruiz Barzola
Author-X-Name-First: Omar
Author-X-Name-Last: Ruiz Barzola
Title: Multivariate multinomial T2 control chart using fuzzy approach
Abstract: 
 Quality of a product is often measured through various quality characteristics generally correlated. Multivariate control charts are a response to the need for quality control in such situations. If quality characteristics are qualitative, it sometimes happens that the product quality is defined by linguistic variables – where quality levels are represented by some specific words – and product units are classified into several linguistic forms categories, depending on the degree of fulfilment of expectations, creating a situation of fuzzy classifications. This study first reviews the concepts found in the literature on the development of fuzzy multivariate control charts. We propose a method to control these fuzzy quality evaluations, with correlated multiple attributes quality characteristics, through the use of a Hotelling T2 control chart.
Journal: International Journal of Production Research
Pages: 2225-2238
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.983617
File-URL: http://hdl.handle.net/10.1080/00207543.2014.983617
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Template-Type: ReDIF-Article 1.0
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Author-Name: Tai-Hsi Wu
Author-X-Name-First: Tai-Hsi
Author-X-Name-Last: Wu
Author-Name: Tiffany Chen
Author-X-Name-First: Tiffany
Author-X-Name-Last: Chen
Title: Developing a variables repetitive group sampling scheme by considering process yield and quality loss
Abstract: 
 Acceptance sampling is a useful tool for determining whether submitted lots should be accepted or rejected. With the current increase in outsourcing production processes and the high-quality levels required, it is very desirable to have an efficient and economic sampling scheme. This paper develops a variables repetitive group sampling (RGS) plan that accounts for the process yield (meeting the manufacturing specifications) and the quality loss (variation from the target). The plan parameters are determined by solving a nonlinear optimisation problem. This implies that the plan parameters minimise the average sample number required for inspection and fulfil the classical two-point conditions on the operating characteristic (OC) curve. Besides, this paper investigates the efficiency of the proposed plan and compares it with the existing variables single sampling plan. Tables of the plan parameters for the proposed variables RGS plan are provided and an application example is presented for illustration.
Journal: International Journal of Production Research
Pages: 2239-2251
Issue: 7
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.986300
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986300
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:7:p:2239-2251




Template-Type: ReDIF-Article 1.0
Author-Name: Yacob Khojasteh
Author-X-Name-First: Yacob
Author-X-Name-Last: Khojasteh
Author-Name: Ryo Sato
Author-X-Name-First: Ryo
Author-X-Name-Last: Sato
Title: Selection of a pull production control system in multi-stage production processes
Abstract: 
 In this paper, we conduct an analytical comparison of three pull production control systems: Kanban, CONWIP and Base-stock in multi-stage production processes. First, we compare the three control systems in a multi-stage serial production process. Then, we compare them in multi-stage assembly production processes, and present guidelines that allow us to select the best system. As a result, we show which structural parameters decide the superiority of one control scheme to the others, and how they are related. A key for superiority is a configuration of parameters, such as processing times and number of cards employed in the system. We show that there is no general superiority amongst the analysed concepts. Finally, we verify the effect of variability on the system performance, and generalise the analytical results of deterministic cases by conducting numerical experiments.
Journal: International Journal of Production Research
Pages: 4363-4379
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.1001530
File-URL: http://hdl.handle.net/10.1080/00207543.2014.1001530
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Template-Type: ReDIF-Article 1.0
Author-Name: Jorick Lartigau
Author-X-Name-First: Jorick
Author-X-Name-Last: Lartigau
Author-Name: Xiaofei Xu
Author-X-Name-First: Xiaofei
Author-X-Name-Last: Xu
Author-Name: Lanshun Nie
Author-X-Name-First: Lanshun
Author-X-Name-Last: Nie
Author-Name: Dechen Zhan
Author-X-Name-First: Dechen
Author-X-Name-Last: Zhan
Title: Cloud manufacturing service composition based on QoS with geo-perspective transportation using an improved Artificial Bee Colony optimisation algorithm
Abstract: 
 Cloud Manufacturing (CMfg) ambitions to create dedicated manufacturing clouds (i.e. virtual enterprises) for complex manufacturing demands through the association of various service providers’ resources and capabilities. In order to insure a dedicated manufacturing cloud to match the level of customer’s requirements, the cloud service selection and composition appear to be a decisive process. This study takes common aspects of cloud services into consideration such as quality of service (QoS) parameters but extend the scope to the physical location of the manufacturing resources. Unlike the classic service composition, manufacturing brings additional constraints. Consequently, we propose a method based on QoS evaluation along with the geo-perspective correlation from one cloud service to another for transportation impact analysis. We also insure the veracity of the manufacturing time evaluation by resource availability overtime. Since the composition is an exhaustive process in terms of computational time consumption, the proposed method is optimised through an adapted Artificial Bee Colony (ABC) algorithm based on initialisation enhancement. Finally, the efficiency and precision of our method are discussed furthermore in the experiments chapter.
Journal: International Journal of Production Research
Pages: 4380-4404
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2015.1005765
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005765
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:14:p:4380-4404




Template-Type: ReDIF-Article 1.0
Author-Name: Alireza Faraz
Author-X-Name-First: Alireza
Author-X-Name-Last: Faraz
Author-Name: William H. Woodall
Author-X-Name-First: William H.
Author-X-Name-Last: Woodall
Author-Name: C. Heuchenne
Author-X-Name-First: C.
Author-X-Name-Last: Heuchenne
Title: Guaranteed conditional performance of the S2 control chart with estimated parameters
Abstract: 
 We evaluate the in-control performance of the S2 control chart with estimated parameters conditional on the Phase I sample. Simulation results indicate no realistic amount of Phase I data is enough to have confidence that the in-control average run length (ARL) obtained will be near the desired value. To overcome this problem, we adjust the S2 chart’s control limits such that the in-control ARL is guaranteed to be above a specified value with a certain specified probability. The required adjustment does not have too much of an adverse effect on the out-of-control performance of the chart.
Journal: International Journal of Production Research
Pages: 4405-4413
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2015.1008112
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1008112
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Template-Type: ReDIF-Article 1.0
Author-Name: Amitava Mukherjee
Author-X-Name-First: Amitava
Author-X-Name-Last: Mukherjee
Author-Name: Rudra Sen
Author-X-Name-First: Rudra
Author-X-Name-Last: Sen
Title: Comparisons of Shewhart-type rank based control charts for monitoring location parameters of univariate processes
Abstract: 
 The nonparametric (distribution-free) control charts are robust alternatives to the conventional parametric control charts when the form of underlying process distribution is unknown or complicated. In this paper, we consider two new nonparametric control charts based on the Hogg–Fisher–Randle (HFR) statistic and the Savage rank statistic. These are popular statistics for testing location shifts, especially in right-skewed densities. Nevertheless, the control charts based on these statistics are not studied in quality control literature. In the current context, we study phase-II Shewhart-type charts based on the HFR and Savage statistics. We compare these charts with the Wilcoxon rank-sum chart in terms of false alarm rate, out-of-control average run-length and other run length properties. Implementation procedures and some illustrations of these charts are also provided. Numerical results based on Monte Carlo analysis show that the new charts are superior to the Wilcoxon rank-sum chart for a class of non-normal distributions in detecting location shift. New charts also provide better control over false alarm when reference sample size is small.
Journal: International Journal of Production Research
Pages: 4414-4445
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2015.1012605
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1012605
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Template-Type: ReDIF-Article 1.0
Author-Name: Abdul Sattar Safaei
Author-X-Name-First: Abdul Sattar
Author-X-Name-Last: Safaei
Author-Name: Reza Baradaran Kazemzadeh
Author-X-Name-First: Reza Baradaran
Author-X-Name-Last: Kazemzadeh
Author-Name: Heng-Soon Gan
Author-X-Name-First: Heng-Soon
Author-X-Name-Last: Gan
Title: Robust economic-statistical design of X-bar control chart
Abstract: 
 Control charts are developed to monitor the service and production processes. The fact that many processes have uncertain parameters is a barrier to obtain the best design of the control charts. In this paper, economic statistical design (ESD) of the X-bar control chart utilising robust optimisation approach that considers interval estimates of uncertain parameters is investigated. A heuristic algorithm is developed to obtain the robust scheme of the control chart. Robust design for an industrial problem is compared with traditional ESD, and heuristic design. Numerical analyses and simulation study show that the proposed X-bar control chart offers a better approach and more reliable solutions for practitioners.
Journal: International Journal of Production Research
Pages: 4446-4458
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2015.1018449
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1018449
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Template-Type: ReDIF-Article 1.0
Author-Name: Sandra García-Bustos
Author-X-Name-First: Sandra
Author-X-Name-Last: García-Bustos
Author-Name: Francisco Aparisi
Author-X-Name-First: Francisco
Author-X-Name-Last: Aparisi
Author-Name: Eugenio K. Epprecht
Author-X-Name-First: Eugenio K.
Author-X-Name-Last: Epprecht
Title: Optimal EWMA of linear combination of Poisson variables for multivariate statistical process control
Abstract: 
 In this paper, we propose a new process control chart for monitoring correlated Poisson variables, the EWMA LCP chart. This chart is the exponentially weighted moving average (EWMA) version of the recently proposed LCP chart. The latter is a Shewhart-type control chart whose control statistic is a linear combination of the values of the different Poisson variables (elements of the Poisson vector) at each sampling time. As a Shewhart chart, it is effective at signalling large process shifts but is slow to signal smaller shifts. EWMA charts are known to be more sensitive to small and moderate shifts than their Shewhart-type counterparts, so the motivation of the present development is to enhance the performance of the LCP chart by the incorporation of the EWMA procedure to it. To ease the design of the EWMA LCP chart for the end user, we developed a user-friendly programme that runs on Windows© and finds the optimal design of the chart, that is, the coefficients of the linear combination as well as the EWMA smoothing constant and chart control limits that together minimise the out-of-control ARL under a constraint on the in-control ARL. The optimization is carried out by genetic algorithms where the ARLs are calculated through a Markov chain model. We used this programme to evaluate the performance of the new chart. As expected, the incorporation of the EWMA scheme greatly improves the performance of the LCP chart.
Journal: International Journal of Production Research
Pages: 4141-4159
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.975863
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975863
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Template-Type: ReDIF-Article 1.0
Author-Name: Guodong Huang
Author-X-Name-First: Guodong
Author-X-Name-Last: Huang
Author-Name: Jie Chen
Author-X-Name-First: Jie
Author-X-Name-Last: Chen
Author-Name: Xiuli Wang
Author-X-Name-First: Xiuli
Author-X-Name-Last: Wang
Author-Name: Yiqun Shi
Author-X-Name-First: Yiqun
Author-X-Name-Last: Shi
Title: A simulation study of CONWIP assembly with multi-loop in mass production, multi-products and low volume and OKP environments
Abstract: 
 This paper studies the performance of constant work-in-process (CONWIP) assembly system with multi-loop in mass production, multi-products and low volume and one-of-a-kind production (OKP) environments using simulation. We propose five basic design patterns of CONWIP loop and develop eight control policies of CONWIP loop based on the design pattern for standard assembly system. The performance of developed loop policies is evaluated in three production environments. In particular, control policies of CONWIP loop in OKP environment provide a valuable reference for OKP shop floor controlling. A heuristic algorithm of searching work-in-process (WIP) upper bound, the deadlock phenomenon in CONWIP assembly system and suggestion are introduced specifically. The summary of CONWIP installation guidelines in the mixed assembly system can apply CONWIP theory to practise.
Journal: International Journal of Production Research
Pages: 4160-4175
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.980458
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980458
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhuxi Chen
Author-X-Name-First: Zhuxi
Author-X-Name-Last: Chen
Author-Name: Xiaoping Li
Author-X-Name-First: Xiaoping
Author-X-Name-Last: Li
Author-Name: Jatinder N.D. Gupta
Author-X-Name-First: Jatinder N.D.
Author-X-Name-Last: Gupta
Title: A bi-directional flow-rack automated storage and retrieval system for unit-load warehouses
Abstract: 
 Flow-rack is a multi-deep rack containing multi-row and multi-column slope bins. Traditionally, bins slope in the same direction in a flow-rack to make unit-loads slide from the storage face to the retrieval face driven by gravity, which cause unit-loads are stored to the storage face and retrieved from the retrieval face. In this paper, a bi-directional flow-rack (BFR) is designed, in which bins in adjacent columns slope to opposite directions. In each side of a BFR, unit-loads are stored in half of the bins and retrieved from the other half. Therefore, dual-command (DC) operations could be simultaneously performed on both faces and blocking unit-loads are re-stored to available bins on the same face directly. We develop a travel time model for BFR systems, which provides the throughput baseline for different configurations of BFR. A DC operation generation method is introduced for BFR systems. Simulation experiments are conducted to evaluate the effectiveness of the BFR travel time model, to compare the throughput performance between BFR and SFR systems and to evaluate the performance of the proposed DC operation generation method.
Journal: International Journal of Production Research
Pages: 4176-4188
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.980459
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980459
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Template-Type: ReDIF-Article 1.0
Author-Name: Debiao Li
Author-X-Name-First: Debiao
Author-X-Name-Last: Li
Author-Name: Sang Won Yoon
Author-X-Name-First: Sang Won
Author-X-Name-Last: Yoon
Title: A novel fill-time window minimisation problem and adaptive parallel tabu search algorithm in mail-order pharmacy automation system
Abstract: 
 This paper presents a novel fill-time window (FTW) problem in a mail-order pharmacy automation (MOPA) system. The MOPA system uses a batch process to fulfil and distribute tens of thousands of highly customised prescription orders. It has been utilised to accommodate an increasing prescription volume and pharmacy dispensing productivity. Since the majority of prescription orders consist of multiple medications, the long medications’ waiting time in the collation process will increase the makespan or even cause a production deadlock in extreme cases. To minimise the collation time of multiple medication orders, the FTW is defined as the time difference between the first and last dispensed medications within a prescription order and the FTW problem is introduced as a flexible order scheduling problem by considering makespan as a constraint. To minimise the FTW, an integer mathematical model has been developed to find an optimal production schedule. To solve this NP-hard order scheduling problem efficiently, an adaptive parallel tabu search (APTS) algorithm is proposed. The performance of the proposed algorithm has been experimented with different system parameters. Based on the experimental results, the APTS algorithm yields 90-99%$ 90-99\% $ less FTW than LPT, and 13-33%$ 13-33\% $ less FTW than TS.
Journal: International Journal of Production Research
Pages: 4189-4205
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.985392
File-URL: http://hdl.handle.net/10.1080/00207543.2014.985392
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:14:p:4189-4205




Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Manikas
Author-X-Name-First: Andrew
Author-X-Name-Last: Manikas
Author-Name: Mahesh Gupta
Author-X-Name-First: Mahesh
Author-X-Name-Last: Gupta
Author-Name: Lynn Boyd
Author-X-Name-First: Lynn
Author-X-Name-Last: Boyd
Title: Experiential exercises with four production planning and control systems
Abstract: 
 In the authors’ experience, students have difficulty in understanding the differences between production planning and control techniques. Presumably, current business managers, although they have heard about these systems, may also lack clarity on the differences between them. We outline manual games for simulating production runs in four systems (Materials Requirements Planning, Just-In-Time, Theory of Constraints and CONWIP) to give managers and students’ insight into the mechanics of different production planning control techniques. We then provide excel-based simulation tools to allow users to vary parameters for each system and see the impact on inventory and throughput. We believe that the combination of manual and excel-based games significantly enhances understanding of the systems as well as their differences.
Journal: International Journal of Production Research
Pages: 4206-4217
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.985393
File-URL: http://hdl.handle.net/10.1080/00207543.2014.985393
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:14:p:4206-4217




Template-Type: ReDIF-Article 1.0
Author-Name: Asghar Seif
Author-X-Name-First: Asghar
Author-X-Name-Last: Seif
Author-Name: Alireza Faraz
Author-X-Name-First: Alireza
Author-X-Name-Last: Faraz
Author-Name: Erwin Saniga
Author-X-Name-First: Erwin
Author-X-Name-Last: Saniga
Title: Economic statistical design of the VP  control charts for monitoring a process under non-normality
Abstract: 
 Recent studies proved that variable parameters (VP) X¯$ {\bar{X}} $ control charts not only detect process mean shifts quicker than the classical X¯$ {\bar{X}} $ control chart but also have better economic properties. While most papers in control chart design assume that process data are normally distributed this may not be true in practice. In this paper, we investigate the economic statistical design of the VP X¯$ {\bar{X}} $ control chart when the underlying process distribution is non-normal. Here, we use the Burr distribution as a model of the process quality variable distribution because of its flexibility in terms of being able to model many distributions including the normal. We illustrate the design procedure and perform a sensitivity analysis on the process and cost parameters based upon the degrees of skewness and kurtosis of the population using an industrial application.
Journal: International Journal of Production Research
Pages: 4218-4230
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.986298
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986298
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Template-Type: ReDIF-Article 1.0
Author-Name: Bruno Chaves Franco
Author-X-Name-First: Bruno Chaves
Author-X-Name-Last: Franco
Author-Name: Giovanni Celano
Author-X-Name-First: Giovanni
Author-X-Name-Last: Celano
Author-Name: Philippe Castagliola
Author-X-Name-First: Philippe
Author-X-Name-Last: Castagliola
Author-Name: Antonio Fernando Branco Costa
Author-X-Name-First: Antonio Fernando Branco
Author-X-Name-Last: Costa
Author-Name: Marcela Aparecida Guerreiro Machado
Author-X-Name-First: Marcela Aparecida Guerreiro
Author-X-Name-Last: Machado
Title: A new sampling strategy for the Shewhart control chart monitoring a process with wandering mean
Abstract: 
 In many processes, such as in chemical and process industries, the observations of a quality characteristic to be monitored may be correlated, if sampling intervals are short. Correlation can be modelled by considering the process mean as a random variable wandering according to an autoregressive AR1$ AR\left( 1 \right) $ model and the observations from the process modelled as the mean plus a random error due to short-term variability or measurement error. The sensitivity of the Shewhart X¯$ {\bar {X}} $ control chart in the detection of a special cause is negatively affected by presence of correlation among observations. To overcome this problem, a new sampling strategy, denoted as ESSI (Equally Spaced Samples Items), is proposed to implement the Shewhart X¯$ {\bar {X}} $ control chart as opposed to the traditional rational subgrouping approach. The ESSI sampling strategy allows observations belonging to the same sample to be collected from the process at equally spaced time intervals between two successive inspections. A numerical analysis shows that the implementation of the ESSI strategy in presence of a process wandering mean significantly improves the statistical performance of the Shewhart X¯$ {\bar {X}} $ control chart vs. rational subgrouping for different levels of autocorrelation. Furthermore, by implementing the ESSI sampling strategy, the selection of the width of control limits for the control chart is independent of the correlation. An illustrative example shows the implementation of the proposed strategy.
Journal: International Journal of Production Research
Pages: 4231-4248
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.993774
File-URL: http://hdl.handle.net/10.1080/00207543.2014.993774
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Template-Type: ReDIF-Article 1.0
Author-Name: Seungjoo Lee
Author-X-Name-First: Seungjoo
Author-X-Name-Last: Lee
Author-Name: Seong Gu Kang
Author-X-Name-First: Seong Gu
Author-X-Name-Last: Kang
Title: A study of improving overlay accuracy by applying a new outlier handling method in FPD manufacturing
Abstract: 
 As the pixel size of display devices has been reduced, overlay accuracy between layers needs to be more improved in flat panel display (FPD) manufacturing. However, because of large substrate size and non-uniform processes in FPD manufacturing, an improvement of overlay accuracy has been a challenging work. As an effort to improve overlay accuracy, overlay error correction, which is a kind of feedback control similar to one in semiconductor manufacturing, has also been applied in the photo lithography processes for FPD. However, its characteristics and problems were not technically well investigated as much as in semiconductor manufacturing. This paper investigates one of the problems encountered in the practice of the overlay error correction: outliers in the measurement of overlay errors. Such outliers can cause undesirable effects on overlay accuracy, if used for the overlay error correction. In order to systematically cope with such outliers, a new framework is proposed for detecting and handling outliers as well as for verifying the result. In the consideration of the proposed framework, a new outlier detecting and handling method is also proposed. This method is based on a robust regression technique and is compared with others through simulation to confirm its better performance.
Journal: International Journal of Production Research
Pages: 4249-4265
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.994074
File-URL: http://hdl.handle.net/10.1080/00207543.2014.994074
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Template-Type: ReDIF-Article 1.0
Author-Name: Stephen C.H. Ng
Author-X-Name-First: Stephen C.H.
Author-X-Name-Last: Ng
Author-Name: Johnny M. Rungtusanatham
Author-X-Name-First: Johnny M.
Author-X-Name-Last: Rungtusanatham
Author-Name: Xiande Zhao
Author-X-Name-First: Xiande
Author-X-Name-Last: Zhao
Author-Name: Albena Ivanova
Author-X-Name-First: Albena
Author-X-Name-Last: Ivanova
Title: TQM and environmental uncertainty levels: profiles, fit, and firm performance
Abstract: 
 That a manufacturer should align its implementation of Total Quality Management (TQM) to the external environment it faces has been indirectly argued for long. Theoretical and empirical evidence for this argument has, unfortunately, been lacking. Our research remedies this knowledge gap. Borrowing structural contingency theory and the concept of fit, we hypothesised and report three findings. First, we found contrasting normative TQM profiles between a high vs. a low level of environmental uncertainty. Second, we identified significant detrimental impact on firm performance when a firm deviates its TQM implementation from the normative TQM profile prescribed for a specific level of environmental uncertainty. Third, we also discovered discernible differences in the deterioration in firm performance between a positive vs. a negative deviation from the normative TQM profile. These robust findings were derived from analysing secondary survey data from 330 Chinese manufacturing firms via profile deviation analysis, MANOVA, MANCOVA and OLS regression. Contrary to the literature, manufacturers operating in a volatile external environment should pursue and benefit from TQM implementation. Manufacturers should, however, not seek to implement TQM to the fullest extent nor implement TQM half-heartedly. Instead, manufacturers should benchmark best performers as to what the normative TQM profile is and pursue their own TQM implementation to minimise deviations from the normative TQM profile.
Journal: International Journal of Production Research
Pages: 4266-4286
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.994076
File-URL: http://hdl.handle.net/10.1080/00207543.2014.994076
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Template-Type: ReDIF-Article 1.0
Author-Name: Guangzhou Diao
Author-X-Name-First: Guangzhou
Author-X-Name-Last: Diao
Author-Name: Liping Zhao
Author-X-Name-First: Liping
Author-X-Name-Last: Zhao
Author-Name: Yiyong Yao
Author-X-Name-First: Yiyong
Author-X-Name-Last: Yao
Title: A dynamic quality control approach by improving dominant factors based on improved principal component analysis
Abstract: 
 Process variables in manufacturing process are critical to the final quality of product, especially in continuous process. Their abnormal fluctuations may cause many quality problems and lead to poor product quality. Against this background, this paper proposes a dynamic quality control approach by improving dominant factors (DFs) based on improved principal component analysis (iPCA). Firstly, the generation of iPCA is illustrated to identify the DFs which lead to quality problems. Then, a quality prediction model for improving DFs is proposed based on modified support vector machine (SVM). An incremental weight is introduced in SVM to improve its sparsity and increase the accuracy of quality prediction. Thus, the product quality can be guaranteed by controlling the DFs dynamically. Finally, a case study is provided to verify the feasibility and applicability of proposed method. The research is expected to provide some guidance for continuous process.
Journal: International Journal of Production Research
Pages: 4287-4303
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.997400
File-URL: http://hdl.handle.net/10.1080/00207543.2014.997400
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Template-Type: ReDIF-Article 1.0
Author-Name: Qing-Hui Wang
Author-X-Name-First: Qing-Hui
Author-X-Name-Last: Wang
Author-Name: Xiao-Ming Zhang
Author-X-Name-First: Xiao-Ming
Author-X-Name-Last: Zhang
Author-Name: Jing-Rong Li
Author-X-Name-First: Jing-Rong
Author-X-Name-Last: Li
Author-Name: Chen-Sheng Tang
Author-X-Name-First: Chen-Sheng
Author-X-Name-Last: Tang
Title: Prediction of toolpath redundancy for NC machining of free-form surfaces based on automatic recognition of steep-wall features
Abstract: 
 The degree of toolpath redundancy is a critical concern when looking for an appropriate toolpath strategy for free-form surface machining. Hence, quantitative analysis of toolpath redundancy is important to CAM applications. In this work, a novel approach for prediction of toolpath redundancy for free-form surface machining is proposed. Firstly, a general mathematical model to represent toolpath redundancy rate is proposed based on the analysis of local toolpath intervals and their difference from the optimal values. And then, taking the most widely used iso-planar machining as case study, the steep-wall features that bring in the variation of surface slope rates alone machining strips are identified as the main cause of the generation of toolpath redundancy, so a method to automatic recognising steep-wall features from free-form surface is developed. At last, based on the steep-wall feature segmentation, an algorithm is presented to quantitatively predict the toolpath redundancy rate for free-form surface machining. A comparison study is made between the predicted redundancy rates and the experimental results by a number of case studies. The results have validated that the proposed approach can effectively predict the redundancy rate for a surface machining case before the real toolpaths to be generated.
Journal: International Journal of Production Research
Pages: 4304-4316
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.997401
File-URL: http://hdl.handle.net/10.1080/00207543.2014.997401
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Template-Type: ReDIF-Article 1.0
Author-Name: Giulia Pedrielli
Author-X-Name-First: Giulia
Author-X-Name-Last: Pedrielli
Author-Name: Arianna Alfieri
Author-X-Name-First: Arianna
Author-X-Name-Last: Alfieri
Author-Name: Andrea Matta
Author-X-Name-First: Andrea
Author-X-Name-Last: Matta
Title: Integrated simulation–optimisation of pull control systems
Abstract: 
 Pull policies are considered to be among the most efficient control strategy. Setting the correct parameters to maximise their efficiency is, however, not a trivial task. Simulation–optimisation techniques have received particular attention as a means to solve this problem. Nevertheless, they require the iterative solution of an optimisation model to generate the parameter values and a discrete event simulator to evaluate the resulting system performance. In the framework of simulation-optimisation, this paper proposes a combined solution of the optimisation and simulation problems for the optimal operation of pull control systems under several control strategies. Numerical experiments were performed to evaluate the performance of the proposed technique.
Journal: International Journal of Production Research
Pages: 4317-4336
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.997404
File-URL: http://hdl.handle.net/10.1080/00207543.2014.997404
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaosong Wu
Author-X-Name-First: Xiaosong
Author-X-Name-Last: Wu
Author-Name: Rui Miao
Author-X-Name-First: Rui
Author-X-Name-Last: Miao
Author-Name: Zefeng Li
Author-X-Name-First: Zefeng
Author-X-Name-Last: Li
Author-Name: Jie Ren
Author-X-Name-First: Jie
Author-X-Name-Last: Ren
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Author-Name: Xuening Chu
Author-X-Name-First: Xuening
Author-X-Name-Last: Chu
Title: Process monitoring research with various estimator-based MEWMA control charts
Abstract: 
 Multivariate exponentially weighted moving average (MEWMA) control chart with five different estimators as population covariance matrix is rarely applied to monitor small fluctuations in the statistical process control. In this article, mathematical models of the five estimators (S1, S2, S3, S4, S5) are established, with which the relevant MEWMA control charts are obtained, respectively. Thereafter, the process monitoring performance of the five control charts is simulated. And the simulation results show that the S4 estimator-based MEWMA control chart is of the best performance both in step offset failure mode and ramp offset failure mode. Since the inline process monitoring of photovoltaic manufacturing is intended to be a problem of multivariate statistics process analysis, the feasibility and effectiveness of the proposed model are elaborated in the case study during the cell testing and sorting process control for the fabrication of multicrystalline silicon solar cells.
Journal: International Journal of Production Research
Pages: 4337-4350
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.997406
File-URL: http://hdl.handle.net/10.1080/00207543.2014.997406
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Template-Type: ReDIF-Article 1.0
Author-Name: D.R. Zanwar
Author-X-Name-First: D.R.
Author-X-Name-Last: Zanwar
Author-Name: V.S. Deshpande
Author-X-Name-First: V.S.
Author-X-Name-Last: Deshpande
Author-Name: J.P. Modak
Author-X-Name-First: J.P.
Author-X-Name-Last: Modak
Author-Name: M.M. Gupta
Author-X-Name-First: M.M.
Author-X-Name-Last: Gupta
Author-Name: K.N. Agrawal
Author-X-Name-First: K.N.
Author-X-Name-Last: Agrawal
Title: Determination of mass, damping coefficient, and stiffness of production system using convolution integral
Abstract: 
 Discrete event simulation (DES) is most widely used tool for modelling complex production systems. DES model requires skilful mapping of actual production process in a framework used for DES modelling. It also calls for extensive data collection for arriving at probability distributions followed by the time required by various activities involved in production processes and also the probability distribution of various occurrences affecting production process. System dynamics (SD) has also been used to model production system. SD model requires forming causal loop model (stock–flow diagram) showing interrelated influential variables affecting production process, their rates and mathematical relation between cause and effect. Continuous and discrete flow models had also been used for modelling production system. This work proposes a tool for simulating the production output which is simpler as compared to these two techniques. This investigation attempts to establish relationship between inputs to the production system, state of production system and number of units produced. Second-order differential equation analogizing production system with mechanical vibration system is devised and the constants of differential equation are determined. These constants signify mass, damping factor and natural frequency of mechanical vibration system. Differential equation formed for production system helps to simulate the production output in response to forces such as supply order, breakdown and preventive maintenance.
Journal: International Journal of Production Research
Pages: 4351-4362
Issue: 14
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.998787
File-URL: http://hdl.handle.net/10.1080/00207543.2014.998787
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Template-Type: ReDIF-Article 1.0
Author-Name: Filiz Cetin
Author-X-Name-First: Filiz
Author-X-Name-Last: Cetin
Author-Name: Cigdem Alabas-Uslu
Author-X-Name-First: Cigdem
Author-X-Name-Last: Alabas-Uslu
Title: Heuristic solution to the product targeting problem based on mathematical programming
Abstract: 
 Maintaining customer lifetime longevity is a crucial issue for companies. One of the strategies for dealing with this issue is to offer different promotion campaigns. Planning these campaigns creates a problem: Which targeted products in the campaign should be offered to which customers in order to maximise profit? This problem becomes vitally important under the conditions of a limited budget and a lower bound on sales target of each product. It is also remarkable from the operational research perspective because of its NP-hardness. In this study, heuristic approaches to the product targeting problem based on mathematical programming are suggested. The proposed approaches principally determine the products to be included in a campaign using heuristic rules and then distribute these products to the customers optimally. Computational results confirm that these approaches generate superior solutions to the problem in comparison with existing methods in the literature. The effectiveness and efficiency of the approaches are also shown on very large-sized test problems generated in order to verify their potential for practical applications.
Journal: International Journal of Production Research
Pages: 3-17
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2015.1112047
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1112047
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Template-Type: ReDIF-Article 1.0
Author-Name: Chunxia Yu
Author-X-Name-First: Chunxia
Author-X-Name-Last: Yu
Author-Name: T.N. Wong
Author-X-Name-First: T.N.
Author-X-Name-Last: Wong
Author-Name: Zhi Li
Author-X-Name-First: Zhi
Author-X-Name-Last: Li
Title: A hybrid multi-agent negotiation protocol supporting supplier selection for multiple products with synergy effect
Abstract: 
 Supplier selection is an important problem in supply chain management. In practice, it is common for a purchasing company to procure a bundle of products simultaneously. In this regard, synergy effect could exist between products and hence affect the final choice of suppliers. It is therefore necessary to incorporate the synergy effect between products in supplier selection process. Agent-based negotiation models are applied to automate supplier selection process. Negotiation protocol is an essential component should be considered when building an effective agent negotiation model. The objective of this research is to propose a negotiation protocol special for multi-product supplier selection problem. The negotiation protocol is a hybrid multi-agent protocol of combinatorial procurement auction protocol and multi-bilateral bargaining protocol. The negotiation protocol is able to support the purchasing company and suppliers negotiate on the concrete commitments of multiple products simultaneously, and select suppliers for multiple products. In addition, both the purchasing company and suppliers can express their preferences on the synergy effect between products in negotiation process by adopting the negotiation protocol. Simulation is conducted to demonstrate the effectiveness and efficiency of the negotiation protocol.
Journal: International Journal of Production Research
Pages: 18-37
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1189105
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1189105
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuchen Jiang
Author-X-Name-First: Yuchen
Author-X-Name-Last: Jiang
Author-Name: Juan Xu
Author-X-Name-First: Juan
Author-X-Name-Last: Xu
Author-Name: Siqian Shen
Author-X-Name-First: Siqian
Author-X-Name-Last: Shen
Author-Name: Cong Shi
Author-X-Name-First: Cong
Author-X-Name-Last: Shi
Title: Production planning problems with joint service-level guarantee: a computational study
Abstract: 
 We consider a class of single-stage multi-period production planning problems under demand uncertainty. The main feature of our paper is to incorporate a joint service-level constraint to restrict the joint probability of having backorders in any period. This is motivated by manufacturing and retailing applications, in which firms need to decide the production quantities ex ante, and also have stringent service-level agreements. The inflexibility of dynamically altering the pre-determined production schedule may be due to contractual agreement with external suppliers or other economic factors such as enormously large fixed costs and long lead time. We focus on two stochastic variants of this problem, with or without pricing decisions, both subject to a joint service-level guarantee. The demand distribution could be nonstationary and correlated across different periods. Using the sample average approximation (SAA) approach for solving chance-constrained programs, we reformulate the two variants as mixed-integer linear programs (MILPs). Via computations of diverse instances, we demonstrate the effectiveness of the SAA approach, analyse the solution feasibility and objective bounds, and conduct sensitivity analysis for the two MILPs. The approaches can be generalised to a wide variety of production planning problems, and the resulting MILPs can be efficiently computed by commercial solvers.
Journal: International Journal of Production Research
Pages: 38-58
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1193245
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193245
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Template-Type: ReDIF-Article 1.0
Author-Name: Annika Becker
Author-X-Name-First: Annika
Author-X-Name-Last: Becker
Author-Name: Raik Stolletz
Author-X-Name-First: Raik
Author-X-Name-Last: Stolletz
Author-Name: Thomas Stäblein
Author-X-Name-First: Thomas
Author-X-Name-Last: Stäblein
Title: Strategic ramp-up planning in automotive production networks
Abstract: 
 In many industries, the frequency of production ramp-ups has increased due to shorter product life cycles and increased product variety. Production often takes place at globally dispersed facilities for customers in multiple markets, for example, in the automotive industry. Therefore, ramp-up planning must be carried out for a network. The planning problem at hand is to simultaneously optimise the allocation of products of a common product platform to plants, the timing of ramp-ups and ramp-downs, ramp-up duration and shape of capacity and production and transportation volumes with respect to the net present value of the profit. We develop a hierarchical planning framework and place strategic ramp-up planning therein. We provide a mixed integer programming model for this planning problem. Following the example of a German car manufacturer in the premium segment, we conduct a numerical analysis to obtain insights into optimal ramp-up and ramp-down decisions. The results show that it could be beneficial to use both steep and flat ramp-up curves. The impact of flexibility in the choice of ramp-up slots and the number of ramp-up curves provided on the objective value is substantial. The strategic ramp-up planning model outperforms sequential planning approaches.
Journal: International Journal of Production Research
Pages: 59-78
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1193252
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193252
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Template-Type: ReDIF-Article 1.0
Author-Name: You Li
Author-X-Name-First: You
Author-X-Name-Last: Li
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Author-Name: Wenyou Jia
Author-X-Name-First: Wenyou
Author-X-Name-Last: Jia
Title: API-based two-dimensional dispatching decision-making approach for semiconductor wafer fabrication with operation due date–related objectives
Abstract: 
 This paper presents an adjacent pairwise interchanges (API)-based two-dimensional dispatching decision-making approach for semiconductor wafer fabrication with operation due date-related objectives. Each time when a machine becomes idle, the proposed dispatcher chooses a target processing job from the competing jobs and assigns it a start time. Giving the operation due date information of each competing job, we formulate this dispatcher as the mean absolute deviation problem to keep the jobs finished around their operation due dates in a proactive way. Dominance properties of this problem are established using proof by APIs. Then, a heuristic comprised of job selection within candidate set, movement of job cluster and local search is designed to solve this problem more efficiently. Numerical experiments validate the efficiency of the proposed heuristic in a single-machine environment as well as in a simulated wafer fab abstracted from practice. In comparison with four most referenced due date-related dispatching rules, the simulation study reveals the benefits brought by the two-dimensional dispatching decision with different due date tightness taken into account.
Journal: International Journal of Production Research
Pages: 79-95
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1195025
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1195025
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:1:p:79-95




Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad A.M. Abdel-Aal
Author-X-Name-First: Mohammad A.M.
Author-X-Name-Last: Abdel-Aal
Author-Name: Mujahid N. Syed
Author-X-Name-First: Mujahid N.
Author-X-Name-Last: Syed
Author-Name: Shokri Z. Selim
Author-X-Name-First: Shokri Z.
Author-X-Name-Last: Selim
Title: Multi-product selective newsvendor problem with service level constraints and market selection flexibility
Abstract: 
 We consider a multi-product multi-market newsvendor problem where the decision-maker could select some markets to serve. The considered problem involves the integration of procurement and market selection decisions. The products are procured from an external supplier. We assume that the realised demand for each product should be satisfied. In the case of shortages, the firm procures items at a higher cost. The paper considers the case where the selling prices, market entry costs, and product demand distributions are market dependent. Specifically, we discuss three cases of the Multi-Product Selective Newsvendor Problem: flexible market entry case, full market entry case and partial market entry case. The mathematical models of the above cases result in binary nonlinear programmes. We develop solution algorithms for solving the resulting combinatorial problems. Some managerial insights are provided.
Journal: International Journal of Production Research
Pages: 96-117
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1195932
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1195932
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:1:p:96-117




Template-Type: ReDIF-Article 1.0
Author-Name: Pilar I. Vidal-Carreras
Author-X-Name-First: Pilar I.
Author-X-Name-Last: Vidal-Carreras
Author-Name: Jose P. Garcia-Sabater
Author-X-Name-First: Jose P.
Author-X-Name-Last: Garcia-Sabater
Author-Name: Julio J. Garcia-Sabater
Author-X-Name-First: Julio J.
Author-X-Name-Last: Garcia-Sabater
Title: A practical model for managing inventories with unknown costs and a budget constraint
Abstract: 
 The economic production quantity method is one of the simplest models to control production and inventory. However, the assumptions on which it is based make its application difficult in practical situations. In most companies, set-up and inventory costs are unknown, or may not even exist as such, although other data are known, such as available capacity in machining hours and limits set by the financing subsystem. The present work offers a multi-item inventory model that sets reference values using known values such as inventory investment limits and production capacity. In order to confer the proposed model’s larger practical content, a spreadsheet available to be downloaded has been implemented. Finally, the model dynamics is illustrated as a numerical example obtained from a real company.
Journal: International Journal of Production Research
Pages: 118-129
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1198056
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1198056
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:1:p:118-129




Template-Type: ReDIF-Article 1.0
Author-Name: Kamil J. Mizgier
Author-X-Name-First: Kamil J.
Author-X-Name-Last: Mizgier
Title: Global sensitivity analysis and aggregation of risk in multi-product supply chain networks
Abstract: 
 Manufacturing firms manage complex supply chain networks which are exposed to a plethora of hazard events. An essential part of the risk management process is the calculation of the stand-alone risk exposures of the product-specific supply chains, but also of the entire multi-product system. In this paper, first, a global sensitivity analysis of the statistical supply chain risk model is conducted. This method helps the decision-makers to understand the risk of the model they are using. Second, a methodology for risk aggregation in multi-product supply chain networks is proposed. The real-world data is used to analyse and validate the model. Supply chain managers equipped with the proposed method will better cope with the risk in supply chains for different product configurations.
Journal: International Journal of Production Research
Pages: 130-144
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1198504
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1198504
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:1:p:130-144




Template-Type: ReDIF-Article 1.0
Author-Name: Jiaxiang Luo
Author-X-Name-First: Jiaxiang
Author-X-Name-Last: Luo
Author-Name: Jiyin Liu
Author-X-Name-First: Jiyin
Author-X-Name-Last: Liu
Author-Name: Yueming Hu
Author-X-Name-First: Yueming
Author-X-Name-Last: Hu
Title: An MILP model and a hybrid evolutionary algorithm for integrated operation optimisation of multi-head surface mounting machines in PCB assembly
Abstract: 
 This paper focuses on an operation optimisation problem for a class of multi-head surface mounting machines in printed circuit board assembly lines. The problem involves five interrelated sub-problems: assigning nozzle types as well as components to heads, assigning feeders to slots and determining component pickup and placement sequences. According to the depth of making decisions, the sub-problems are first classified into two layers. Based on the classification, a two-stage mixed-integer linear programming (MILP) is developed to describe it and a two-stage problem-solving frame with a hybrid evolutionary algorithm (HEA) is proposed. In the first stage, a constructive heuristic is developed to determine the set of nozzle types assigned to each head and the total number of assembly cycles; in the second stage, constructive heuristics, an evolutionary algorithm with two evolutionary operators and a tabu search (TS) with multiple neighbourhoods are combined to solve all the sub-problems simultaneously, where the results obtained in the first stage are taken as constraints. Computational experiments show that the HEA can obtain good near-optimal solutions for small size instances when compared with an optimal solver, Cplex, and can provide better results when compared with a TS and an EA for actual instances.
Journal: International Journal of Production Research
Pages: 145-160
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1200154
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1200154
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiangtao Wang
Author-X-Name-First: Jiangtao
Author-X-Name-Last: Wang
Author-Name: Yina Li
Author-X-Name-First: Yina
Author-X-Name-Last: Li
Author-Name: Fei Ye
Author-X-Name-First: Fei
Author-X-Name-Last: Ye
Author-Name: Quan Chen
Author-X-Name-First: Quan
Author-X-Name-Last: Chen
Title: Optimal introduction time decision for holiday products with uncertain market demand
Abstract: 
 In this paper, we investigate how retailers with different risk preferences determine the optimal introduction time and order quantity for holiday products to maximise performance in environments characterised by uncertain market demand. Specifically, both the market demand and the accuracy of sales forecasts are assumed to be affected by the timing of the introduction, which in turn affects the order quantity and subsequent performance. The results suggest that as the level of uncertainty in the market demand increases, as the retailer’s power in the industry increases and as the coefficient of elasticity of the competitive demand over introduction time is larger, the retailer prefers to set a later introduction time and to order smaller quantities, to reduce the risk of overstocking. Moreover, a risk-averse retailer will set a later introduction time and order smaller quantities than a risk-neutral retailer. Indeed, the more risk-averse the retailer is, the later will be the introduction time and the smaller the quantity ordered. The managerial implications are presented for decision-makers with different risk preferences regarding the interconnections between important factors and introduction time and inventory decisions for holiday products in environments characterised by uncertain market demand.
Journal: International Journal of Production Research
Pages: 161-175
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1200759
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1200759
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Template-Type: ReDIF-Article 1.0
Author-Name: XiaoLin Li
Author-X-Name-First: XiaoLin
Author-X-Name-Last: Li
Author-Name: YuPeng Li
Author-X-Name-First: YuPeng
Author-X-Name-Last: Li
Author-Name: Yu Wang
Author-X-Name-First: Yu
Author-X-Name-Last: Wang
Title: Minimising makespan on a batch processing machine using heuristics improved by an enumeration scheme
Abstract: 
 Batch processing machines can process several job simultaneously and are encountered in many manufacturing environments. Jobs in a batch are processed together and have the same start and end processing time. Since jobs are non-identical in job sizes and job processing times, they should be reasonably scheduled to improve the machine utilisation and processing efficiency. Two well-known heuristics, first fit longest processing time and best fit longest processing time (BFLPT), are improved in this study by considering identical job sizes and then BFLPT is further improved by an enumeration scheme proposed. Computational experiments are conducted to evaluate the performance of the improvement and the results are compared with the existing heuristics.
Journal: International Journal of Production Research
Pages: 176-186
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1200762
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1200762
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:1:p:176-186




Template-Type: ReDIF-Article 1.0
Author-Name: Ran Liu
Author-X-Name-First: Ran
Author-X-Name-Last: Liu
Author-Name: Yangyi Tao
Author-X-Name-First: Yangyi
Author-X-Name-Last: Tao
Author-Name: Qiaoyu Hu
Author-X-Name-First: Qiaoyu
Author-X-Name-Last: Hu
Author-Name: Xiaolei Xie
Author-X-Name-First: Xiaolei
Author-X-Name-Last: Xie
Title: Simulation-based optimisation approach for the stochastic two-echelon logistics problem
Abstract: 
 This work proposes a simulation-based optimisation approach for the two-echelon vehicle routing problem with stochastic demands (2E-VRPSD). In the proposed 2E-VRPSD, freight delivery from the depot to the customers is managed by shipping the freight through intermediate satellites, while each customer has a stochastic demand. The 2E-VRPSD is an extension of the famous capacitated vehicle routing problem with stochastic demands and the two-echelon vehicle routing problem (2E-VRP). A tabu search algorithm is designed to solve the 2E-VRPSD, in which Monte Carlo sampling is adopted to tackle the issue of stochastic demands. Modified two-echelon vehicle routing problem benchmark instances are used in the numerical experiments. The computational results show the advantage of the proposed simulation-based approach.
Journal: International Journal of Production Research
Pages: 187-201
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1201221
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1201221
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Template-Type: ReDIF-Article 1.0
Author-Name: Yumei Hou
Author-X-Name-First: Yumei
Author-X-Name-Last: Hou
Author-Name: Fangfang Wei
Author-X-Name-First: Fangfang
Author-X-Name-Last: Wei
Author-Name: Susan X. Li
Author-X-Name-First: Susan X.
Author-X-Name-Last: Li
Author-Name: Zhimin Huang
Author-X-Name-First: Zhimin
Author-X-Name-Last: Huang
Author-Name: Allan Ashley
Author-X-Name-First: Allan
Author-X-Name-Last: Ashley
Title: Coordination and performance analysis for a three-echelon supply chain with a revenue sharing contract
Abstract: 
 This paper focuses on a three-echelon supply chain composed of a manufacturer, a distributor and a retailer for a single selling period. Based on a revenue sharing contract, the coordination of the decentralised supply chain with the simultaneous move game or the leader–follower game is analysed. It is determined that the revenue sharing contract can coordinate the decentralised supply chain with the simultaneous move game. Our analysis reveals that the revenue sharing contract cannot coordinate the decentralised three-echelon supply chain with the leader–follower game except for a special situation. However, this result provides an opportunity to develop methodology and results that measure the potential improvement in supply chain performance that can be gained from utilising the revenue sharing contract. This is an important aspect of this paper.
Journal: International Journal of Production Research
Pages: 202-227
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1201601
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1201601
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanan Song
Author-X-Name-First: Yanan
Author-X-Name-Last: Song
Author-Name: Xiaobo Zhao
Author-X-Name-First: Xiaobo
Author-X-Name-Last: Zhao
Title: A newsvendor problem with boundedly rational strategic customers
Abstract: 
 This work considers a newsvendor system with strategic customers who are boundedly rational in terms of buying during the selling season or waiting for a discount in the savage market. The newsvendor’s decisions are to determine the selling price and order quantity. An optimisation problem is formulated with the incorporation of a game for interaction between strategic customers. We use the quantal choice framework to characterise the behaviour of strategic customers. It is shown that when the bounded rationality parameter is large, the quantal response equilibrium is unique; otherwise, multiple equilibria may exist. For the unique equilibrium case, it is not difficult to determine the optimal decisions for the newsvendor. For the multiple equilibria case, we give theoretical analyses and numerical calculations to provide implications to the newsvendor. Additionally, based on the special case (with perfectly rational strategic customers), some important results are also observed.
Journal: International Journal of Production Research
Pages: 228-243
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1201607
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1201607
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoge Zhang
Author-X-Name-First: Xiaoge
Author-X-Name-Last: Zhang
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: Andrew Adamatzky
Author-X-Name-First: Andrew
Author-X-Name-Last: Adamatzky
Author-Name: Sankaran Mahadevan
Author-X-Name-First: Sankaran
Author-X-Name-Last: Mahadevan
Author-Name: Hai Yang
Author-X-Name-First: Hai
Author-X-Name-Last: Yang
Author-Name: Zili Zhang
Author-X-Name-First: Zili
Author-X-Name-Last: Zhang
Author-Name: Yong Deng
Author-X-Name-First: Yong
Author-X-Name-Last: Deng
Title: An intelligent physarum solver for supply chain network design under profit maximization and oligopolistic competition
Abstract: 
 We propose an efficient bio-inspired algorithm for design of optimal supply chain networks in a competitive oligopoly markets. The firms compete in manufacture, storage and distribution of a product to several markets. Each firm aims at maximisation of its own profit by optimising the design capacity and product flow in the supply chain. We model the supply chain network as a multi-layer graph of manufacturing nodes, distribution nodes and storage centres. To optimise the network, we adopt the mechanisms of a foraging behaviour of slime mould Physarum polycephalym. First, we extend the original Physarum model to deal with networks with multiple sources and sinks. Second, we develop a novel method to solve the user equilibrium (UE) problem by exploiting the adaptivity of the Physarum model: we update the link costs according to the product flow. Third, we refer to an equivalent transformation between system optimum problem and UE problem to determine the optimal product flows and design capacities of a supply chain. At last, we present an approach to update the amount of product supplied by each firm. By comparing our solutions with that in Nagurney (2010b) on several numerical examples, we demonstrate the efficiency and practicality of the proposed method.
Journal: International Journal of Production Research
Pages: 244-263
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1203075
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1203075
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Template-Type: ReDIF-Article 1.0
Author-Name: Lin Chen
Author-X-Name-First: Lin
Author-X-Name-Last: Chen
Author-Name: Jin Peng
Author-X-Name-First: Jin
Author-X-Name-Last: Peng
Author-Name: Zhibing Liu
Author-X-Name-First: Zhibing
Author-X-Name-Last: Liu
Author-Name: Ruiqing Zhao
Author-X-Name-First: Ruiqing
Author-X-Name-Last: Zhao
Title: Pricing and effort decisions for a supply chain with uncertain information
Abstract: 
 This paper analyses the pricing and effort decisions of a supply chain with single manufacturer and single retailer. The manufacturer produces a kind of product and then wholesales the product to the retailer, who in turn retails it to customers over a single selling season. The retailer can influence demand through her sales effort. This research depicts the consumer demand, the manufacturing cost and the sales effort cost as uncertain variables. Considering the demand expansion effectiveness of sales effort, one centralised and three decentralised game models are built on the basis of the expected value criterion, and the equilibrium solutions are obtained. We investigate the effects of the parameters’ uncertainty degrees on the pricing and effort decisions. The results indicate that the manufacturer benefits from improvement in demand and cost uncertainties when he has at least bargaining power in the supply chain. The results also imply that the uncertainty degree of sales effort elasticity has an outstanding influence on the pricing and effort decisions, whereas the uncertainty degree of price elasticity has a modest impact on these decisions. We also study the effects of the parameters’ uncertainty degrees on the supply chain from the consumers’ perspective. The results suggest that with a power retailer, the retail price should always be on the high end. Consequently, consumers do not necessarily benefit from a power retailer. When the manufacturer and the retailer have equal bargaining power, consumers do not necessarily benefit from the supply chain, either.
Journal: International Journal of Production Research
Pages: 264-284
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1204475
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1204475
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Template-Type: ReDIF-Article 1.0
Author-Name: Karim Amrouche
Author-X-Name-First: Karim
Author-X-Name-Last: Amrouche
Author-Name: Mourad Boudhar
Author-X-Name-First: Mourad
Author-X-Name-Last: Boudhar
Author-Name: Mohamed Bendraouche
Author-X-Name-First: Mohamed
Author-X-Name-Last: Bendraouche
Author-Name: Farouk Yalaoui
Author-X-Name-First: Farouk
Author-X-Name-Last: Yalaoui
Title: Chain-reentrant shop with an exact time lag: new results
Abstract: 
 The two-machine chain-reentrant shop scheduling with the objective of minimizing the makespan, assumes that the tasks pass from the first machine to the second and return back to the first machine. In this paper, we consider the same problem in which an exact time lag between the two operations on the first machine is imposed. In Amrouche and Boudhar (2016) the authors proved that this problem is NP-hard in the strong sense in the case of identical time lags lj=L$ l_j=L $. We propose heuristic algorithms with empirical results for the latter. In addition, we establish a new NP-hardness result and some polynomial cases.
Journal: International Journal of Production Research
Pages: 285-295
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1205235
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1205235
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhanguo Zhu
Author-X-Name-First: Zhanguo
Author-X-Name-Last: Zhu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Multitasking scheduling problems with a rate-modifying activity
Abstract: 
 Motivated by the behavioral phenomena that occur while human operators are carrying out tasks, we study multitasking scheduling problems with a rate-modifying activity. In the problems, the processing of a selected task suffers from interruptions by other tasks that are available but unfinished, and the human operators regularly engage rest breaks during work shifts allowing them to recover or mitigate some of the negative effects of fatigue. The objectives are to respectively minimize: makespan, total completion time, maximum lateness, and due-date assignment related cost by determining when to schedule the rate modifying activity and the optimal task sequence in the presence of multitasking. Scheduling models and algorithms are proposed to solve the problems. The numerical examples are presented to illustrate the theorems and algorithms.
Journal: International Journal of Production Research
Pages: 296-312
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1208852
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1208852
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Template-Type: ReDIF-Article 1.0
Author-Name: Aleixandre Dolgui
Author-X-Name-First: Aleixandre
Author-X-Name-Last: Dolgui
Title: 55th anniversary of Production Research
Journal: International Journal of Production Research
Pages: 1-2
Issue: 1
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1261649
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1261649
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Template-Type: ReDIF-Article 1.0
Author-Name: Heeyoung Kim
Author-X-Name-First: Heeyoung
Author-X-Name-Last: Kim
Author-Name: Justin T. Vastola
Author-X-Name-First: Justin T.
Author-X-Name-Last: Vastola
Author-Name: Sungil Kim
Author-X-Name-First: Sungil
Author-X-Name-Last: Kim
Author-Name: Jye-Chyi Lu
Author-X-Name-First: Jye-Chyi
Author-X-Name-Last: Lu
Author-Name: Martha A. Grover
Author-X-Name-First: Martha A.
Author-X-Name-Last: Grover
Title: Incorporation of engineering knowledge into the modeling process: a local approach
Abstract: 
 Process modelling is the foundation of developing process controllers for monitoring and improving process/system health. Modelling process behaviours using a pure empirical approach might not be feasible due to limitation in collecting large amount of data. Engineering models provide valuable information about processes’ general behaviours but they might not capture distinct characteristics in the particular process studied. Many recent publications presented various ideas of using limited experimental data to adjust engineering models for making them suitable for certain applications. However, the focuses there are global adjustments, where modification of engineering models impacts the entire model-application region. In practice, some engineering models are only valid in a part of experimental data domain. Moreover, many discrepancies between engineering models and experimental data are in local regions. For example, in a chemical vapour deposition process, at high temperatures a process may be described by a diffusion limited model, while at low temperatures the process may be described by a reaction limited model. To address these problems, this article proposes two approaches for integrating engineering and data models: local model calibration and local model averaging. Through the local model calibration, the discrepancies between engineering’s first-principle models and experimental data are resolved locally based on experts’ feedbacks. To combine models adjusted locally in some regions and also models required little adjustments in other regions, a model averaging procedure based on local kernel weights is proposed. The effectiveness of the proposed method is demonstrated on simulated examples, and compared against a well-known existing global-adjustment method.
Journal: International Journal of Production Research
Pages: 5865-5880
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2016.1278082
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1278082
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Template-Type: ReDIF-Article 1.0
Author-Name: Bin Chen
Author-X-Name-First: Bin
Author-X-Name-Last: Chen
Author-Name: Youbai Xie
Author-X-Name-First: Youbai
Author-X-Name-Last: Xie
Title: A computational approach for the optimal conceptual design synthesis based on the distributed resource environment
Abstract: 
 Optimal conceptual design synthesis is the very starting and key phase in the product design. Its result is the optimal alternative in the solution space, and will be further completed and improved into the final product design scheme in the next detailed design works. With the progress of the Internet technology, a large number of design resources actually construct an increasingly growing distributed resource environment. If these rich resources can be fully introduced into the optimal conceptual design synthesis, the design efficiency and product innovation will be promoted largely. Therefore, a computational approach was proposed for the optimal conceptual design synthesis based on the distributed resource environment. In this approach, the distributed resource environment is modelled as a set of numerous functional units (FUs), and the optimal conceptual design synthesis is concluded into a process of generating the optimal objective FU chain. Here, the main workload is completed by a proposed computer algorithm. To prove the feasibility of this approach, a computer programme called Optimal Conceptual Design Synthesis System (OCDSS) was established. A garbage-powered lighting system was designed with OCDSS as an illustration.
Journal: International Journal of Production Research
Pages: 5881-5901
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1302619
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1302619
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Template-Type: ReDIF-Article 1.0
Author-Name: Sevilay Onal
Author-X-Name-First: Sevilay
Author-X-Name-Last: Onal
Author-Name: Jingran Zhang
Author-X-Name-First: Jingran
Author-X-Name-Last: Zhang
Author-Name: Sanchoy Das
Author-X-Name-First: Sanchoy
Author-X-Name-Last: Das
Title: Modelling and performance evaluation of explosive storage policies in internet fulfilment warehouses
Abstract: 
 Internet Fulfilment Warehouses (IFWs) are designed to exclusively process online retail orders. An observational study reveals that IFW operating and design attributes are significantly different from traditional warehouses in their storage and fulfilment policies. Specifically, we identify six IFW differentiators: explosive storage, very large number of beehive storage locations, bins with commingled SKUs, immediate fulfilment, short picking routes with single unit picks and high transactions with total digital control. Explosive storage of incoming bulk allows for faster fulfilment of customer orders often within a few hours. A new IFW control model is developed. This describes the associated receiving and fulfilment flows. Two decision algorithms for generating (i) a stocking list and (ii) an order picking list are presented. A simulation model was built to evaluate the fulfilment performance of the explosive policy. Experimental runs on a problem with 400 SKUs, 3240 bins and 22,000 customer orders over nine days are reported. Results show that increasing levels of explosion reduce the linear fulfilment time by as much as 16%, confirming the IFW storage policy is advantageous. The results also show that fulfilment time behaviour is convex as a function of the maximum number of stops allowed by the picking algorithm parameter.
Journal: International Journal of Production Research
Pages: 5902-5915
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1304663
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1304663
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaojie Liu
Author-X-Name-First: Xiaojie
Author-X-Name-Last: Liu
Author-Name: Gang Du
Author-X-Name-First: Gang
Author-X-Name-Last: Du
Author-Name: Roger J. Jiao
Author-X-Name-First: Roger J.
Author-X-Name-Last: Jiao
Title: Bilevel joint optimisation for product family architecting considering make-or-buy decisions
Abstract: 
 Product family architecting (PFA) aims at identification of common modules and selective modules to enable product family configuration for mass customisation. Due to nowadays manufacturers moving more towards assembly-to-order production throughout a distributed supply chain, the common practice of outsourcing of certain modules entails make-or-buy (MOB) decisions that must be taken into account in PFA. While the PFA and MOB decisions are enacted for different concerns of the manufacturer and the suppliers, it is important to deal with joint optimisation of the PFA and MOB problems. The prevailing decision models for joint optimisation are mainly originated from an ‘all-in-one’ approach that assumes both PFA and MOB decisions can be integrated into one single-level optimisation problem. Such an assumption neglects the complex trade-offs underlying two different decision-making problems and fails to reveal the inherent coupling of PFA and MOB decisions. This paper proposes to formulate joint optimisation of the PFA and MOB problems as a Stackelberg game, in which a bilevel decision mechanism model is deployed to reveal the inherent coupling and hierarchical relationships between PFA and MOB decisions. A nonlinear bilevel optimisation model is developed with the PFA problem acting as the leader and each MOB problem performing as a follower. A nested genetic algorithm is developed to solve the bilevel optimisation model. A case study of power transformer PFA subject to MOB considerations is presented to illustrate the feasibility and effectiveness of bilevel joint optimisation.
Journal: International Journal of Production Research
Pages: 5916-5941
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1304666
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1304666
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Template-Type: ReDIF-Article 1.0
Author-Name: Liang-Liang Fu
Author-X-Name-First: Liang-Liang
Author-X-Name-Last: Fu
Author-Name: Mohamed Ali Aloulou
Author-X-Name-First: Mohamed Ali
Author-X-Name-Last: Aloulou
Author-Name: Chefi Triki
Author-X-Name-First: Chefi
Author-X-Name-Last: Triki
Title: Integrated production scheduling and vehicle routing problem with job splitting and delivery time windows
Abstract: 
 In this paper, we study a production scheduling and vehicle routing problem with job splitting and delivery time windows in a company working in the metal packaging industry. In this problem, a set of jobs has to be processed on unrelated parallel machines with job splitting and sequence-dependent setup time (cost). Then the finished products are delivered in batches to several customers with heterogeneous vehicles, subject to delivery time windows. The objective of production is to minimize the total setup cost and the objective of distribution is to minimize the transportation cost. We propose mathematical models for decentralized scheduling problems, where a production schedule and a distribution plan are built consecutively. We develop a two-phase iterative heuristic to solve the integrated scheduling problem. We evaluate the benefits of coordination through numerical experiments.
Journal: International Journal of Production Research
Pages: 5942-5957
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1308572
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1308572
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:20:p:5942-5957




Template-Type: ReDIF-Article 1.0
Author-Name: Ibrahim Kucukkoc
Author-X-Name-First: Ibrahim
Author-X-Name-Last: Kucukkoc
Author-Name: David Z. Zhang
Author-X-Name-First: David Z.
Author-X-Name-Last: Zhang
Title: Balancing of mixed-model parallel U-shaped assembly lines considering model sequences
Abstract: 
 As a consequence of increasing interests in customised products, mixed-model lines have become the most significant components of today’s manufacturing systems to meet surging consumer demand. Also, U-shaped assembly lines have been shown as the intelligent way of producing homogeneous products in large quantities by reducing the workforce need thanks to the crossover workstations. As an innovative idea, we address the mixed-model parallel U-shaped assembly line design which combines the flexibility of mixed-model lines with the efficiency of U-shaped lines and parallel lines. The multi-line stations utilised in between two adjacent lines provide extra efficiency with the opportunity of assigning tasks into workstations in different combinations. The new line configuration is defined and characterised in details and its advantages are explained. A heuristic solution approach is proposed for solving the problem. The proposed approach considers the model sequences on the lines and seeks efficient balancing solutions for their different combinations. An explanatory example is also provided to show the sophisticated structure of the studied problem and explain the running mechanism of the proposed approach. The results of the experimental tests and their statistical analysis indicated that the proposed line design requires fewer number of workstations in comparison with independently balanced mixed-model U-lines.
Journal: International Journal of Production Research
Pages: 5958-5975
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1312586
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1312586
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Template-Type: ReDIF-Article 1.0
Author-Name: Moise Busogi
Author-X-Name-First: Moise
Author-X-Name-Last: Busogi
Author-Name: Kasin Ransikarbum
Author-X-Name-First: Kasin
Author-X-Name-Last: Ransikarbum
Author-Name: Yeong Gwang Oh
Author-X-Name-First: Yeong Gwang
Author-X-Name-Last: Oh
Author-Name: Namhun Kim
Author-X-Name-First: Namhun
Author-X-Name-Last: Kim
Title: Computational modelling of manufacturing choice complexity in a mixed-model assembly line
Abstract: 
 Manufacturing systems have evolved to adopt a mixed-model assembly line enabling the production of high product variety. Although the mixed-model assembly system with semi-automation (i.e. human involvement) can offer a wide range of advantages, the system becomes very complex as variety increases. Further, while the complexity from different options can worsen the system performance, there is a lack of quantifiable models for manufacturing complexity in the literature. Thus, in this paper, we propose a novel method to quantify manufacturing choice complexity for the effective management of semi-automated systems in a mixed-model assembly line. Based on the concept of information entropy, our model considers both the options mix and the similarities between options. The proposed model, along with an illustrative case study, not only serves as a tool to quantitatively assess the impact of choice complexity on total system performance, but also provides an insight into how complexity can be mitigated without affecting the overall manufacturing throughput.
Journal: International Journal of Production Research
Pages: 5976-5990
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1319088
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1319088
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:20:p:5976-5990




Template-Type: ReDIF-Article 1.0
Author-Name: Ece Sancı
Author-X-Name-First: Ece
Author-X-Name-Last: Sancı
Author-Name: Meral Azizoğlu
Author-X-Name-First: Meral
Author-X-Name-Last: Azizoğlu
Title: Rebalancing the assembly lines: exact solution approaches
Abstract: 
 In this study, we consider an assembly line rebalancing problem with disruptions caused by workstation breakdowns or shutdowns. After the disruption, we aim to find a rebalance so as to catch the trade-off between the efficiency measure of cycle time and stability measure of number of tasks assigned to different workstations in the original and new balances. Our aim is to generate all nondominated objective vectors with respect to the efficiency and stability measures. We develop two optimisation algorithms: a Mixed Integer Linear Programming-based algorithm and a Branch and Bound algorithm. The results of our experiments have shown the favourable performances of both algorithms and the superiority of the Branch and Bound algorithm.
Journal: International Journal of Production Research
Pages: 5991-6010
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1319583
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1319583
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:20:p:5991-6010




Template-Type: ReDIF-Article 1.0
Author-Name: Sylverin Kemmoe
Author-X-Name-First: Sylverin
Author-X-Name-Last: Kemmoe
Author-Name: Damien Lamy
Author-X-Name-First: Damien
Author-X-Name-Last: Lamy
Author-Name: Nikolay Tchernev
Author-X-Name-First: Nikolay
Author-X-Name-Last: Tchernev
Title: Job-shop like manufacturing system with variable power threshold and operations with power requirements
Abstract: 
 This paper addresses an important issue in manufacturing by considering the scheduling of a Job-shop like manufacturing system involving a power threshold that must not be exceeded over time. A power profile is attached to operations that must be scheduled. This power profile presents a consumption peak at the start of process in order to model most of real-world machining operations. These operations must be scheduled according to the instantly available power threshold. A mathematical formulation of the problem is proposed; its main goal is to minimise the total completion time of all operations. A set of instances is built based on classical format of instances for the Job-shop problem. As it is time-consuming to obtain exact solutions on these instances with the CPLEX solver, a Greedy Randomised Adaptive Search Procedure hybridised with an Evolutionary Local Search (GRASP × ELS) metaheuristic is designed. The GRASP × ELS is compared with two other metaheuristics: a Variable Neighbourhood Search and a Memetic Algorithm. The GRASP × ELS is also compared with several algorithms developed in the literature for the classical job-shop problem. Results show the relevancy of the metaheuristic approaches both in terms of computational time and quality of solutions.
Journal: International Journal of Production Research
Pages: 6011-6032
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1321801
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1321801
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Template-Type: ReDIF-Article 1.0
Author-Name: Hichem Haddou Benderbal
Author-X-Name-First: Hichem
Author-X-Name-Last: Haddou Benderbal
Author-Name: Mohammed Dahane
Author-X-Name-First: Mohammed
Author-X-Name-Last: Dahane
Author-Name: Lyes Benyoucef
Author-X-Name-First: Lyes
Author-X-Name-Last: Benyoucef
Title: Flexibility-based multi-objective approach for machines selection in reconfigurable manufacturing system (RMS) design under unavailability constraints
Abstract: 
 The reconfigurable manufacturing system (RMS) is a recent manufacturing paradigm driven by the high responsiveness and performance efficiencies. In such system, machines, material handling units or machines components can be added, modified, removed or interchanged as needed. Hence, the design of RMS is based on reconfigurable machines capabilities and product specification. This paper addresses the problem of machines selections for RMS design under unavailability constraints and aims to develop an approach to ensure the best process plan according to the customised flexibility required to produce all parts of a given product. More specifically, we develop a flexibility-based multi-objective approach using an adapted version of the well-known non-dominated sorting genetic algorithm to select adequate machines from a set of candidate (potential) ones, in order to ensure the best responsiveness of the designed system in case of unavailability of one of the selected machines. The responsiveness is based on the flexibility of the designed system and a generated process plan, which guarantees the management of machines unavailability. It is defined as the ability and the capacity to adapt the process plan in response to machines unavailability. Two objectives are considered, respectively, the maximisation of the flexibility index of the system and the minimisation of the total completion time. To choose the best solution in the Pareto front, a multi-objective decision-making method called technique for order of preference by similarity to ideal solution is used. To demonstrate the applicability of the proposed approach, a simple example is presented and the numerical results are analysed.
Journal: International Journal of Production Research
Pages: 6033-6051
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1321802
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1321802
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Algorithms for the joint multitasking scheduling and common due date assignment problem
Abstract: 
 In this paper, we investigate a joint multitasking scheduling and common due date assignment problem on a single machine, for which examples can be found in product delivery process in logistics. Multitasking allows the machine to perform multiple tasks. The multitasking phenomenon has been observed in various practical domains, including manufacturing and administration. In multitasking settings, each waiting job interrupts a currently in-processing job, causing an interruption time and a switching time. In common due date assignment problems, the objective is to determine the optimal value of this due date with the purpose of minimising a total penalty function, which is associated with service quality. For the problem with general interruption functions, analytical properties are obtained to reduce the search space of the optimal solutions. For the cases with linear interruption functions, we develop a polynomial-time algorithm. Numerical experiments have been conducted to validate the efficiency of our proposed algorithm. Computational results also demonstrate an interesting phenomenon that in some cases, the optimal solutions under multitasking are superior to the counterparts without multitasking. Besides, we also devise a mixed integer programme for the cases with linear interruption function.
Journal: International Journal of Production Research
Pages: 6052-6066
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1321804
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1321804
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Template-Type: ReDIF-Article 1.0
Author-Name: Hung-Chung Su
Author-X-Name-First: Hung-Chung
Author-X-Name-Last: Su
Author-Name: Yi-Su Chen
Author-X-Name-First: Yi-Su
Author-X-Name-Last: Chen
Author-Name: Young K. Ro
Author-X-Name-First: Young K.
Author-X-Name-Last: Ro
Title: Perception differences between buyer and supplier: the effect of agent negotiation styles
Abstract: 
 This study investigates the effects of individual negotiation styles on a buyer’s stated behaviour and a supplier’s anticipation of the buyer’s behaviours with regard to opportunism and compliance in a multi-echelon production network under different firm-level governance mechanisms. We design a between-subjects matched-scenario experiment to collect data from both sides of a buyer‒supplier dyad. We find that agent negotiation styles do exert influences on opportunism but not compliance. Specifically, we find that the effects of firm-level governing mechanisms dominate the effects of individual negotiation styles with regard to compliance, while individual negotiation styles have influence beyond firm-level governing mechanisms with regard to opportunism. Theoretical contributions of our findings to the current literature and managerial implications to practice are discussed.
Journal: International Journal of Production Research
Pages: 6067-6083
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1324220
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1324220
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Xuenan Yang
Author-X-Name-First: Xuenan
Author-X-Name-Last: Yang
Author-Name: Jiantong Zhang
Author-X-Name-First: Jiantong
Author-X-Name-Last: Zhang
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Scheduling a tempered glass manufacturing system: a three-stage hybrid flow shop model
Abstract: 
 Chinese tempered glass has entered a fast and stable growing era. To improve the productivity of tempered glass manufacturers, this paper investigates a scheduling problem in tempered glass production system, originated from a tempered glass manufacturer in China. This problem can be formulated as a three-stage hybrid flow shop (HFS). Single and batch processing machines coexist in this HFS. Besides, a limited buffer, between the first two stages, and machine eligibility requirement are also significant characteristics. To address this complicated scheduling problem, we first establish an integer programming model with the objective of minimising the makespan, i.e. the maximum completion time of jobs in the system. Due to the strong NP-hard nature of the problem, we then propose a constructive heuristic method, a genetic algorithm, as well as a simulated annealing algorithm, to solve practical large-scale problems. Computational results demonstrate the efficiency of the proposed approaches.
Journal: International Journal of Production Research
Pages: 6084-6107
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1324222
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1324222
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehmet Ali Ilgin
Author-X-Name-First: Mehmet Ali
Author-X-Name-Last: Ilgin
Author-Name: Hakan Akçay
Author-X-Name-First: Hakan
Author-X-Name-Last: Akçay
Author-Name: Ceyhun Araz
Author-X-Name-First: Ceyhun
Author-X-Name-Last: Araz
Title: Disassembly line balancing using linear physical programming
Abstract: 
 Disassembly is the separation of a product into its constituent parts in a systematic way. It has gained importance recently due to its vital importance in product recovery. Cost-effective implementation of disassembly operation has a direct impact on the profitability of product recovery activities (recycling, remanufacturing etc.). Although it is possible to carry out disassembly operations in a disassembly station or in a disassembly cell, the highest productivity is achieved in a disassembly line. The output of a disassembly line can be maximised only if the line is balanced. A linear physical programming-based disassembly line balancing method is proposed in this study. This method was used to balance a mixed-model disassembly line and the effectiveness of the method was illustrated by analysing the results.
Journal: International Journal of Production Research
Pages: 6108-6119
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1324225
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1324225
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Template-Type: ReDIF-Article 1.0
Author-Name: Jin Shen
Author-X-Name-First: Jin
Author-X-Name-Last: Shen
Author-Name: John Ahmet Erkoyuncu
Author-X-Name-First: John Ahmet
Author-X-Name-Last: Erkoyuncu
Author-Name: Rajkumar Roy
Author-X-Name-First: Rajkumar
Author-X-Name-Last: Roy
Author-Name: Bin Wu
Author-X-Name-First: Bin
Author-X-Name-Last: Wu
Title: A framework for cost evaluation in product service system configuration
Abstract: 
 Configuration systems are increasingly used as a means for efficient design of customised product service systems (PSS) to satisfy diverse customer needs. Cost evaluation is thereby important to assist the configuration engineers in making decisions on feasible configuration solutions. However, little research attention has been received until recently. To fill this gap, this paper contributes in developing a framework for cost evaluation in PSS configuration. A holistic view of PSS configuration, the three-dimensional PSS cost element, and a life cycle-oriented cost evaluation approach are successively proposed. The framework is thereby established with a number of parts, including the preparatory stage, the evaluation stage and the configuration stage. A pump PSS is illustrated to validate the developed framework. Four feasible configuration solutions in one configuration activity are evaluated and compared. The configuration engineers are thus assisted with the decision on selecting the one with the least cost.
Journal: International Journal of Production Research
Pages: 6120-6144
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1325528
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1325528
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Template-Type: ReDIF-Article 1.0
Author-Name: Imène Benkalai
Author-X-Name-First: Imène
Author-X-Name-Last: Benkalai
Author-Name: Djamal Rebaine
Author-X-Name-First: Djamal
Author-X-Name-Last: Rebaine
Author-Name: Caroline Gagné
Author-X-Name-First: Caroline
Author-X-Name-Last: Gagné
Author-Name: Pierre Baptiste
Author-X-Name-First: Pierre
Author-X-Name-Last: Baptiste
Title: Improving the migrating birds optimization metaheuristic for the permutation flow shop with sequence-dependent set-up times
Abstract: 
 This paper addresses the problem of scheduling a set of independent jobs with set-up times on a set of machines in a permutation flow shop environment. A metaheuristic known as the Migrating Birds Optimization (MBO) is adapted for the minimization of the makespan. Two versions of the algorithm are presented. The first is a basic MBO and the second introduces additional features. An extensive computational study is conducted to analyse the efficiency of the two methods on a benchmark of instances that can be found in Sistemas de Optimizacion Aplicada (http://soa.iti.es/problem-instances). The second version outperforms by far the first one. Moreover, the results that are produced by the latter show that it is suitable for solving real-world scheduling problems.
Journal: International Journal of Production Research
Pages: 6145-6157
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1327732
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1327732
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Boris Sokolov
Author-X-Name-First: Boris
Author-X-Name-Last: Sokolov
Author-Name: Marina Ivanova
Author-X-Name-First: Marina
Author-X-Name-Last: Ivanova
Title: Literature review on disruption recovery in the supply chain
Abstract: 
 Recent research underlines the crucial role of disruption events and recovery policies in supply chains. Despite a wealth of literature on supply chain design with disruption considerations, to the best of our knowledge there is no survey on supply chain with disruptions and recovery considerations. We analyse state-of-the-art research streams on supply chain design and planning with both disruptions and recovery considerations with the aim of relating the existing quantitative methods to empirical research. The paper structures and classifies existing research streams and application areas of different quantitative methods subject to different disruption risks and recovery measures. We identify gaps in current research and delineate future research avenues. The results of this study are twofold: operations and supply chain managers can observe which quantitative tools are available for different application areas; on the other hand, limitations and future research needs for decision-support methods in supply chain risk management domains can be identified.
Journal: International Journal of Production Research
Pages: 6158-6174
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1330572
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330572
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Template-Type: ReDIF-Article 1.0
Author-Name: Bipan Zou
Author-X-Name-First: Bipan
Author-X-Name-Last: Zou
Author-Name: Yeming (Yale) Gong
Author-X-Name-First: Yeming (Yale)
Author-X-Name-Last: Gong
Author-Name: Xianhao Xu
Author-X-Name-First: Xianhao
Author-X-Name-Last: Xu
Author-Name: Zhe Yuan
Author-X-Name-First: Zhe
Author-X-Name-Last: Yuan
Title: Assignment rules in robotic mobile fulfilment systems for online retailers
Abstract: 
 We study robotic mobile fulfilment systems for online retailers, where products are stored in movable shelves and robots transport shelves. While previous studies assume random assignment rule of workstations to robots, we propose an assignment rule based on handling speeds of workstations and design a neighbourhood search algorithm to find a near optimal assignment rule. We build semi-open queueing networks and use a two-phase approximate approach for performance estimation. We first replace workstation service processes by a composite service node and then solve the model by the matrix-geometric method. Simulations are used to validate the analytical models. Numerical experiments are conducted to compare random, handling-speeds-based, near optimal and optimal assignment rules, in terms of retrieval throughput time. The results show that the random assignment rule is not a good choice, the handling-speeds-based assignment rule significantly outperforms the random assignment rule when the workers have large handling time difference, and the neighbourhood search approach can provide an assignment rule that is very close to the optimal one, using a much shorter time. Moreover, we design the shelf blocks under the examined assignment rules, and find that the optimal width of shelf block decreases with the width to length ratio.
Journal: International Journal of Production Research
Pages: 6175-6192
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1331050
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1331050
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Template-Type: ReDIF-Article 1.0
Author-Name: Alessandro Agnetis
Author-X-Name-First: Alessandro
Author-X-Name-Last: Agnetis
Author-Name: Mohamed Ali Aloulou
Author-X-Name-First: Mohamed Ali
Author-X-Name-Last: Aloulou
Author-Name: Mikhail Y. Kovalyov
Author-X-Name-First: Mikhail Y.
Author-X-Name-Last: Kovalyov
Title: Integrated production scheduling and batch delivery with fixed departure times and inventory holding costs
Abstract: 
 In this paper, we address a model for supply chain coordination. There are m manufacturers modelled as single machines, each of which processes a specific set of jobs (products). After processing is completed, jobs are batched, and batches are shipped to a customer by means of vehicles. The problem consists in concurrently finding a production schedule of the jobs, a partition of jobs into delivery batches and an assignment of delivery batches to vehicles, so that jobs are delivered within their deadlines and total costs are minimised. We focus on a scenario characterised by fixed departure times and inventory holding costs. For each departure time there is a given number of vehicles, possibly having limited capacity. Each job incurs a cost proportional to the time from job completion to delivery departure. In this paper, we show that the problem is NP-hard even for a very restricted case, and report various polynomiality results for two scenarios, namely: (i) when the production sequence of each manufacturer is fixed in advance, and (ii) when there is a single manufacturer and processing times are all equal to 1. We also point out several open problems.
Journal: International Journal of Production Research
Pages: 6193-6206
Issue: 20
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1346323
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346323
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Template-Type: ReDIF-Article 1.0
Author-Name: A. Fleury
Author-X-Name-First: A.
Author-X-Name-Last: Fleury
Author-Name: Y. Shi
Author-X-Name-First: Y.
Author-X-Name-Last: Shi
Author-Name: S.F. Junior
Author-X-Name-First: S.F.
Author-X-Name-Last: Junior
Author-Name: J.H.D. Cordeiro
Author-X-Name-First: J.H.D.
Author-X-Name-Last: Cordeiro
Author-Name: M.T.L. Fleury
Author-X-Name-First: M.T.L.
Author-X-Name-Last: Fleury
Title: Developing an analytical framework for study of emerging country multinationals’ operations management
Abstract: 
 The rise of emerging country multinationals (EMNEs) is opening new perspectives for the study of international operations management (IOM). Research may address issues which are inexistent when the object of study is long-established developed country multinationals (DMNEs). One of the issues that may be noticed, and will be studied in this article, has to do with the design and implementation of new international operations networks. In contrast to DMNEs, internationalisation of EMNEs is strongly influenced by two further factors: country-of-origin effects and role in global production networks. Therefore, studies of EMNEs’ international operations networks must embrace two other analytical levels besides the network level: the strategic level of the headquarters and the operational level of the subsidiaries. The analytical framework in this study has been developed through the use of constructs and concepts from both IOM and international business literatures. Such framework applied to three Brazilian multinationals leads to relevant insights on the internationalisation of EMNEs as well as the design and implementation of international operations networks for such late-moving firms.
Journal: International Journal of Production Research
Pages: 5418-5436
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1005252
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005252
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Template-Type: ReDIF-Article 1.0
Author-Name: Ying Liao
Author-X-Name-First: Ying
Author-X-Name-Last: Liao
Author-Name: Erika Marsillac
Author-X-Name-First: Erika
Author-X-Name-Last: Marsillac
Title: External knowledge acquisition and innovation: the role of supply chain network-oriented flexibility and organisational awareness
Abstract: 
 In today’s dynamic business environment, building flexibility into product innovation has become increasingly important. Applying an absorptive capacity lens, this paper develops and empirically tests an integrative model linking external knowledge acquisition (EKA) with supply chain and product innovation flexibilities, and examines the moderating effect of organisational awareness (OA) (a form of individual knowledge base) on these constructs. It is one of a select few papers that explores the effect of both internal capability and external knowledge on innovation flexibility, and discusses both supply chain and human resource development implications. Results indicate that supply chain network flexibility and information spanning flexibility play a mediating role between EKA and product innovation flexibility (PIF), illustrating the importance of flexible supply chain networks and information distribution structures in facilitating the transformation of external knowledge into innovation. The study provides further evidence that strong OA allows firms to leverage external knowledge and supply chain network capability to influence PIF and performance.
Journal: International Journal of Production Research
Pages: 5437-5455
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1008106
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1008106
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Template-Type: ReDIF-Article 1.0
Author-Name: Chun-Wu Yeh
Author-X-Name-First: Chun-Wu
Author-X-Name-Last: Yeh
Author-Name: Chih-Chiang Fang
Author-X-Name-First: Chih-Chiang
Author-X-Name-Last: Fang
Title: Optimal decision for warranty with consideration of marketing and production capacity
Abstract: 
 A successful marketing strategy should be managed to integrate the decisions, such as pricing, post-sale service and production in order to maximise profits but most manufacturers did not fully consider how to integrate them into an effective one in the past. Therefore, in this study, we proposed a mathematical model and a corresponding solution algorithm to assist the decision-makers systematically to decide the synthetic decision. The decision-makers can make warranty and marketing decision according to their production capacity. Besides, the impacts on the profit, the sale, the price and the warranty when the related costs were varying are also discussed in the study, so that the decision-maker can more easily handle the possible situations. The failure times of the product in our study were drawn from a non-homogeneous Poisson process with a specific intensity function (linear, exponential or power law). A preventive maintenance programme was also considered in the warranty policy. Finally, a numerical example was given to demonstrate the effectiveness of the proposed model.
Journal: International Journal of Production Research
Pages: 5456-5471
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1010743
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1010743
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Template-Type: ReDIF-Article 1.0
Author-Name: Neda Abdolvand
Author-X-Name-First: Neda
Author-X-Name-Last: Abdolvand
Author-Name: Amir Albadvi
Author-X-Name-First: Amir
Author-X-Name-Last: Albadvi
Author-Name: Mohammad Aghdasi
Author-X-Name-First: Mohammad
Author-X-Name-Last: Aghdasi
Title: Performance management using a value-based customer-centered model
Abstract: 
 Performance management (PM) and customer management were the subjects of researchers’ attentions for several decades. This research tries to align these two approaches to provide strategic decision-making. The proposed approach suggests an integration of customer relationship management system incorporating PM system considering maximisation of customer lifetime value (CLV) metric. For this, a model is being developed to align PM and customer management. For customer management, we cluster customers based on four dimensions which are product combination, activity level, retention rate and CLV. This combination of attributes has not been used before and can bring more useful information. For example, it can reveal which product combination can pinpoint profitable, loyal and active customers. This helps for the prevention of customer migration. However, the main novelty of this research is proposing the application of CLV as a financial metric in strategic PM in an integrative approach. The research model has been applied in an Iranian commercial retail bank. In the implementation, various techniques and mathematical models including genetic K-means, analytic hierarchical processes and data envelopment analysis have been used.
Journal: International Journal of Production Research
Pages: 5472-5483
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1026613
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1026613
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Template-Type: ReDIF-Article 1.0
Author-Name: Yi-Hui Liang
Author-X-Name-First: Yi-Hui
Author-X-Name-Last: Liang
Title: Performance measurement of interorganizational information systems in the supply chain
Abstract: 
 As corporations rely on collaborations with partners to enhance their competiveness, they use interorganizational information systems (IOIS) as a powerful tool to link with their partners in the supply chain. The purpose of this study is to measure IOIS performance in the supply chain. The proposed framework considers both internal and external organisational perspectives and is based on the balanced scorecard. This study also uses experts’ pairwise comparisons in the fuzzy analytic hierarchy process approach to consider the relative weight or importance of diverse indicators of the framework. Then, this study applies the proposed framework to the Taiwanese information technology industry. The results provide references for managers and future researches when assessing IOIS performance in the supply chain. The proposed model can serve as a useful instrument for helping managers to better understand the main facets of IOIS performance, to be more capable of prioritising improvement projects, and to adopt the right solutions to enhance overall performance.
Journal: International Journal of Production Research
Pages: 5484-5499
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1026614
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1026614
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Template-Type: ReDIF-Article 1.0
Author-Name: Gilwhan Kim
Author-X-Name-First: Gilwhan
Author-X-Name-Last: Kim
Author-Name: Winston T. Lin
Author-X-Name-First: Winston T.
Author-X-Name-Last: Lin
Author-Name: N.C. Simpson
Author-X-Name-First: N.C.
Author-X-Name-Last: Simpson
Title: Evaluating the performance of US manufacturing and service operations in the presence of IT: a Bayesian stochastic production frontier approach
Abstract: 
 In this paper, we evaluate the performance of US manufacturing and service operations in the presence of information technology (IT) as measured by technical efficiency, using firm-level data from 133 companies over the period from 1999 to 2009. To gain insight into the phenomenon of the ‘IT productivity paradox’, or the history of inconsistent findings in the existing literature, we employ a Bayesian stochastic production frontier approach to model the relationship between performance and technical efficiency at the firm, industry and sector levels. Some results are indicative of a slight advantage of the manufacturing sector over the service sector in terms of technical efficiency and a significant positive contribution of IT-investment to firm output. However, other results do suggest the productivity paradox, because of a lack of any definitive association of high IT investment levels with either high- or low-technical efficiency. Indeed, the findings of this study suggest that the origin of some portion of the IT productivity paradox may exist at the industry level, in that the relationship between extreme levels of IT-investment and extreme levels of technical efficiency appear to work differently in sufficiently different industries.
Journal: International Journal of Production Research
Pages: 5500-5523
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1026616
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1026616
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Template-Type: ReDIF-Article 1.0
Author-Name: Francielly Hedler Staudt
Author-X-Name-First: Francielly Hedler
Author-X-Name-Last: Staudt
Author-Name: Gülgün Alpan
Author-X-Name-First: Gülgün
Author-X-Name-Last: Alpan
Author-Name: Maria Di Mascolo
Author-X-Name-First: Maria
Author-X-Name-Last: Di Mascolo
Author-Name: Carlos M. Taboada Rodriguez
Author-X-Name-First: Carlos M. Taboada
Author-X-Name-Last: Rodriguez
Title: Warehouse performance measurement: a literature review
Abstract: 
 As the supply chains get more complex, the variety of indicators and tools to measure warehouse performance has also increased. Furthermore, the metrics that are used for performance evaluation are assessed in different manners and hence there is not clear definition for some of these metrics. To address these issues, this literature review focuses on operational warehouse performance measurement, for which the warehouse managers need to carry out periodic analysis. Using the content analysis method, performance indicators are acquired from selected papers and are classified according to time, cost, quality and productivity dimensions. The contributions of this literature review are as follows: we present a synthesis of the literature on operational warehouse performance, we provide the definitions for the performance indicators and a framework to demonstrate their boundaries and, finally, based on the literature analysis, we also provide some discussions on current trends in warehouses and propose future research directions on warehouse performance evaluation.
Journal: International Journal of Production Research
Pages: 5524-5544
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1030466
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1030466
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Template-Type: ReDIF-Article 1.0
Author-Name: Maud Van den Broeke
Author-X-Name-First: Maud
Author-X-Name-Last: Van den Broeke
Author-Name: Robert Boute
Author-X-Name-First: Robert
Author-X-Name-Last: Boute
Author-Name: Behzad Samii
Author-X-Name-First: Behzad
Author-X-Name-Last: Samii
Title: Evaluation of product-platform decisions based on total supply chain costs
Abstract: 
 Over the past decades, several companies have introduced product platforms in the design of their products in order to produce a large product variety in a cost-efficient way. However, for some companies, the introduction of platforms ended up being more costly than expected, leading them to reconsider their platform decisions. In this paper, we develop a model to support companies in determining (1) how many platforms to develop, (2) which platforms to develop and (3) which products to derive from which platforms. The model takes into account the impact of these product-platform decisions on a company’s relevant supply chain activities and costs. The model shows how the optimal product-platform decisions depend on the trade-off between the costs of platforms versus the costs of customising these platforms to final product variants. We propose a simulated annealing algorithm to solve large problem instances within reasonable time. The practical validity of our model is shown through its application in a global technology company specialised in the development and production of medical screens.
Journal: International Journal of Production Research
Pages: 5545-5563
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1034329
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1034329
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Template-Type: ReDIF-Article 1.0
Author-Name: Fei Lv
Author-X-Name-First: Fei
Author-X-Name-Last: Lv
Author-Name: Shihua Ma
Author-X-Name-First: Shihua
Author-X-Name-Last: Ma
Author-Name: Xu Guan
Author-X-Name-First: Xu
Author-X-Name-Last: Guan
Title: The implication of capacity reservation contracts in assembly system with asymmetric demand information
Abstract: 
 This paper investigates an assembly system that consists of one assembler and two suppliers who produce complementary components. The assembler possesses some private demand information that is unobservable to the upstream suppliers, and the two suppliers have to choose their capacity reservations ahead of the selling season. To induce credible vertical information sharing, we design three capacity reservation contracts: the price-quantity contract, the price-only contract and the hybrid price-quantity and price-only contract, so as to identify how the firms’ equilibrium reservation strategies and pay-offs react under different contract schemes. The results show that the assembler obtains the highest pay-off under either the price-only contract or the hybrid contract, which is determined by whether the private demand information or the demand fluctuation is sufficiently high. The suppliers’ optimal contract types are further influenced by their decision sequence. In particular, the supplier who makes decision earlier prefers the hybrid contract, while the supplier who makes decision later prefers any of the three contracts. The supply chain generates the highest pay-off from either the price-quantity contract or the hybrid contract.
Journal: International Journal of Production Research
Pages: 5564-5591
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1036150
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1036150
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Template-Type: ReDIF-Article 1.0
Author-Name: Benjamin R. Tukamuhabwa
Author-X-Name-First: Benjamin R.
Author-X-Name-Last: Tukamuhabwa
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Author-Name: Jerry Busby
Author-X-Name-First: Jerry
Author-X-Name-Last: Busby
Author-Name: Marta Zorzini
Author-X-Name-First: Marta
Author-X-Name-Last: Zorzini
Title: Supply chain resilience: definition, review and theoretical foundations for further study
Abstract: 
 There has been considerable academic interest in recent years in supply chain resilience (SCRES). This paper presents a timely review of the available literature on SCRES based on a three-stage systematic search that identified 91 articles/sources. We provide a comprehensive definition of SCRES before strategies proposed for improving resilience are identified and the contributions to the literature are critiqued, e.g. in terms of research method and use of theory. We take stock of the field and identify the most important future research directions. A wide range of strategies for improving resilience are identified, but most attention has been on increasing flexibility, creating redundancy, forming collaborative supply chain relationships and improving supply chain agility. We also find that only limited research has been conducted into choosing and implementing an appropriate set of strategies for improving SCRES. Much of the literature is conceptual, theoretical and normative; the few available empirical studies are mainly cross-sectional and confined to a large firm, developed country context; and, there has been limited use of theory frames to improve understanding. We propose Complex Adaptive Systems (CAS) theory as an appropriate lens for studying SCRES. We demonstrate that SCRES mirrors many characteristics of a CAS – including adaptation and coevolution, non-linearity, self-organisation and emergence – with implications for the direction of both future research and practice.
Journal: International Journal of Production Research
Pages: 5592-5623
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1037934
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1037934
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Template-Type: ReDIF-Article 1.0
Author-Name: Guanghua Han
Author-X-Name-First: Guanghua
Author-X-Name-Last: Han
Author-Name: Ming Dong
Author-X-Name-First: Ming
Author-X-Name-Last: Dong
Title: Trust-embedded coordination in supply chain information sharing
Abstract: 
 This paper studies supply chain coordination with trust-embedded cost-sharing contract. In a two-tier supply chain, a retailer (she) and a supplier (he) make their private demand forecasting individually. The retailer places soft-orders, which are costless, non-verifiable and cancellable before shipping, to the supplier. After that, the supplier relies on the retailer’s ordering information to update his demand evaluation and prepare his capacity. How much the supplier relies on the retailer’s ordering information is specified by trust, which is a kind of psychological feeling and affected by multiple factors. When the supplier does not fully trust the retailer, he tends to prepare a conservative capacity to avoid over-production. To coordinate the supply chain, a two-stage coordination process is proposed. At the first stage, the supplier and retailer negotiate a cost-sharing rule to bind soft-orders. At the second stage, the retailer places a soft-order and decides whether or not to bind it referring to the cost-sharing rule. After that, the supplier determines his optimal production capacity. We show that the retailer and supplier value trust differently in the experimental studies. We also find that there is a threshold of negotiation power for the supply chain partners which means the supplier’s/retailer’s expected profit drops down if his/her negotiation power exceeds certain thresholds. The experimental studies also show that the proposed the two-stage coordination is effective.
Journal: International Journal of Production Research
Pages: 5624-5639
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1038367
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1038367
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Template-Type: ReDIF-Article 1.0
Author-Name: Faisal Aqlan
Author-X-Name-First: Faisal
Author-X-Name-Last: Aqlan
Author-Name: Sarah S. Lam
Author-X-Name-First: Sarah S.
Author-X-Name-Last: Lam
Title: Supply chain risk modelling and mitigation
Abstract: 
 In today’s global competitive environment, supply chains are more susceptible to vulnerability due to the increasing occurrence of internal and external risk events. In addition, the trend associated with lean management, which involves reducing inventory, leads to more dependency of supply chain partners on each other which exacerbates risk exposure of companies in the supply chain. This creates the need for more effective management of supply chain risks. In this research, a methodology based on Bow-Tie analysis and optimisation techniques is proposed to quantify and mitigate supply chain risks. The proposed methodology takes into consideration risk interconnections, and it identifies the best combination of mitigation strategies under budget constraints. A real case study from a high-end server manufacturing environment is presented. Results from the case study showed that the proposed methodology for risk modelling and mitigation can effectively be used to quantify the risks and achieve the required risk reduction at minimum cost while considering risk correlations.
Journal: International Journal of Production Research
Pages: 5640-5656
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1047975
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047975
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Template-Type: ReDIF-Article 1.0
Author-Name: Soumaya El Kadiri
Author-X-Name-First: Soumaya
Author-X-Name-Last: El Kadiri
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Ontologies in the context of product lifecycle management: state of the art literature review
Abstract: 
 The use of ontologies in the context of product lifecycle management (PLM) is gaining importance and popularity, while at the same time it generates a lot of controversy in discussions within scientific and engineering communities. Yet, what is ontology? What challenges have been addressed so far? What role does ontology play? Do we really need ontology? These are the core questions this paper seeks to address. We propose to conduct a comprehensive study of the concept of Ontology firstly in its domain of origin, Philosophy, and secondly in information science. Based on the understanding of this concept and an in-depth analysis of the state of the art, seven key roles of ontology are defined. These roles serve as a framework describing the general state of research on the use of ontologies in the context of PLM.
Journal: International Journal of Production Research
Pages: 5657-5668
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1052155
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1052155
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Template-Type: ReDIF-Article 1.0
Author-Name: Yash Daultani
Author-X-Name-First: Yash
Author-X-Name-Last: Daultani
Author-Name: Sushil Kumar
Author-X-Name-First: Sushil
Author-X-Name-Last: Kumar
Author-Name: Omkarprasad S. Vaidya
Author-X-Name-First: Omkarprasad S.
Author-X-Name-Last: Vaidya
Author-Name: Manoj K. Tiwari
Author-X-Name-First: Manoj K.
Author-X-Name-Last: Tiwari
Title: A supply chain network equilibrium model for operational and opportunism risk mitigation
Abstract: 
 Risk management holds a crucial role in ensuring efficiency, predictability, and coherency in supply chain operations of an enterprise. Risks are associated with every member of a supply chain network. Thus, an end-to-end risk management approach is essential to fortify the entire supply chain network. In this paper, we consider a supply chain network consisting of suppliers, manufacturers, distributors and retailers, as the representative stakeholders. In particular, we take supply chain operational, and opportunism risks into account, and investigate the roles of flexibility, and social relationship, respectively, as a mitigation approach. We develop a multi-period network equilibrium model by considering the stakeholders’ objectives of maximising profit and minimising risk. Further, the finite-dimensional variational inequality formulations are derived for the underlying network optimisation problem. An algorithm, with nice features for computations, is then applied to three simulated examples in order to illustrate the model and computational procedure as well as the types of interventions that can help the strategic decision-makers to explore quantitatively the associated profits and incurred risks in an entire supply chain network.
Journal: International Journal of Production Research
Pages: 5685-5715
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1056325
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1056325
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehdi Amini
Author-X-Name-First: Mehdi
Author-X-Name-Last: Amini
Author-Name: Haitao Li
Author-X-Name-First: Haitao
Author-X-Name-Last: Li
Title: The impact of dual-market on supply chain configuration for new products
Abstract: 
 Given a firm’s supply chain network, the key objective of supply chain configuration (SCC) is to determine a subset of supply chain partners to be involved in development, sourcing, production, distribution and support of a new product at the highest level of efficiency and expected responsiveness. Current literature on SCC realises the importance of considering the demand dynamics associated with the new product diffusion (NPD). However, these studies assume one-segment market for new products, a single homogenous consumer segment. Recent research in marketing indicates that such simplification might be fatal because a diverse and significant number of product categories may experience a dual-market structure, namely early and main markets, and generate a different demand dynamics. The objectives of this study are to: (i) develop a hybrid optimisation model, capturing both SCC decisions and the demand dynamics of dual-market NPD process; (ii) based on real-world data for a host of electronic product categories, various SCC networks and NPD demand dynamics, examine the new integrated optimisation model under one- and two-segment market; and (iii) present relevant managerial implications and guidelines for supply chain and marketing managers. Our extensive comparative computational experiment with 26 categories of consumer electronic products show that on average the relative net profit may improve significantly, when the market is considered as two-segment.
Journal: International Journal of Production Research
Pages: 5669-5684
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1058537
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1058537
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Erratum
Journal: International Journal of Production Research
Pages: (i)-(i)
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1073952
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1073952
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:18:p:(i)-(i)




Template-Type: ReDIF-Article 1.0
Author-Name: Klaus R.N. Hansen
Author-X-Name-First: Klaus R.N.
Author-X-Name-Last: Hansen
Author-Name: Martin Grunow
Author-X-Name-First: Martin
Author-X-Name-Last: Grunow
Title: Modelling ramp-up curves to reflect learning: improving capacity planning in secondary pharmaceutical production
Abstract: 
 The experience gained during production ramp-up leads to an increase of the effective production capacity over time. However, full utilisation of production capacity is not always possible during ramp-up. In such cases, the experience gained and hence the available effective capacity are overestimated. We develop a new method, which captures ramp-up as a function of the cumulative production volume to better reflect the experience gained while producing the new product. The use of the more accurate and computationally effective approach is demonstrated for the case of secondary pharmaceutical production. Due to its regulatory framework, this industry cannot fully exploit available capacities during ramp-up. We develop a capacity planning model for a new pharmaceutical drug, which determines the number and location of new production lines and the build-up of inventory such that product availability at market launch is ensured. Our MILP model is applied to a real industry case study using three empirically observed ramp-up curves to demonstrate its value as decision support tool. We demonstrate the superiority of our volume-dependent method over the traditional time-dependent ramp-up functions and derive managerial insights into the selection of ramp-up function and the value of shortening ramp-ups.
Journal: International Journal of Production Research
Pages: 5399-5417
Issue: 18
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2014.998788
File-URL: http://hdl.handle.net/10.1080/00207543.2014.998788
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Template-Type: ReDIF-Article 1.0
Author-Name: Joseph Rahme Youssef
Author-X-Name-First: Joseph Rahme
Author-X-Name-Last: Youssef
Author-Name: Gregory Zacharewicz
Author-X-Name-First: Gregory
Author-X-Name-Last: Zacharewicz
Author-Name: David Chen
Author-X-Name-First: David
Author-X-Name-Last: Chen
Author-Name: François Vernadat
Author-X-Name-First: François
Author-X-Name-Last: Vernadat
Title: EOS: enterprise operating systems
Abstract: 
 A proposal for developing an enterprise operating system (EOS) for real-time monitoring and control of enterprise operations is presented. The proposed EOS will work on top of enterprise computer operating systems to control and monitor enterprise resources instead of just computer components. A set of requirements and functionalities are first identified. Next, a survey of previous relevant works is presented and results are compared to the requirements. The architectures of the envisioned EOS are then outlined and two examples are presented to illustrate the use of the EOS. The last part draws some conclusions and gives future perspectives.
Journal: International Journal of Production Research
Pages: 2714-2732
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1378957
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1378957
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Template-Type: ReDIF-Article 1.0
Author-Name: Hongcheng Li
Author-X-Name-First: Hongcheng
Author-X-Name-Last: Li
Author-Name: Haidong Yang
Author-X-Name-First: Haidong
Author-X-Name-Last: Yang
Author-Name: Bixia Yang
Author-X-Name-First: Bixia
Author-X-Name-Last: Yang
Author-Name: Chengjiu Zhu
Author-X-Name-First: Chengjiu
Author-X-Name-Last: Zhu
Author-Name: Sihua Yin
Author-X-Name-First: Sihua
Author-X-Name-Last: Yin
Title: Modelling and simulation of energy consumption of ceramic production chains with mixed flows using hybrid Petri nets
Abstract: 
 Ceramic production chain consisting of discrete flow and continuous flow energy-intensive processes consumes substantial amounts of energy. This study aims to evaluate energy consumption performance and energy-saving potentials of the ceramic production chain. According to the energy consumption characteristics of manufacturing processes and process interaction constraints in a ceramic production chain, an approach integrating the first-order hybrid Petri net (FOHPN) model, an objective linear programming model and a sensitivity analysis is proposed. The FOHPN model will simulate the energy consumption patterns of the ceramic production chain. Meanwhile, multi-objective linear programming model and sensitivity analysis will suggest the optimal specific energy consumption (SEC) of the production chain and identify the influences of input parameters (i.e. production rate of a process) on the SEC in the optimal production scheme. Finally, a real case study from bathroom ceramic plant validates the approach. It provides a tool for modelling and simulation of energy consumption of ceramic production chains with mixed flows and helps operators to perform energy-saving actions in the ceramic enterprise.
Journal: International Journal of Production Research
Pages: 3007-3024
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1391415
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1391415
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Template-Type: ReDIF-Article 1.0
Author-Name: Claire Palmer
Author-X-Name-First: Claire
Author-X-Name-Last: Palmer
Author-Name: Zahid Usman
Author-X-Name-First: Zahid
Author-X-Name-Last: Usman
Author-Name: Osiris Canciglieri Junior
Author-X-Name-First: Osiris
Author-X-Name-Last: Canciglieri Junior
Author-Name: Andreia Malucelli
Author-X-Name-First: Andreia
Author-X-Name-Last: Malucelli
Author-Name: Robert I. M. Young
Author-X-Name-First: Robert I. M.
Author-X-Name-Last: Young
Title: Interoperable manufacturing knowledge systems
Abstract: 
 For many years now, the importance of semantic technologies, that provide a formal, logic-based route to sharing meaning, has been recognised as offering the potential to support interoperability across multiple-related applications and hence, drive manufacturing competitiveness in the digital manufacturing age. However, progress in support of manufacturing enterprise interoperability has tended to be limited to fairly narrow domains of applicability. This paper presents a progression of research and understanding, culminating in the work undertaken in the recent EU FLEXINET project, to develop a comprehensive manufacturing reference ontology that can (a) support the clarification of understanding across domains, (b) support the ability to flexibly share information across interacting software systems and (c) provide the ability to readily configure company knowledge bases to support interoperable manufacturing systems.
Journal: International Journal of Production Research
Pages: 2733-2752
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1391416
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1391416
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Template-Type: ReDIF-Article 1.0
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme Luz
Author-X-Name-Last: Tortorella
Author-Name: Diego Fettermann
Author-X-Name-First: Diego
Author-X-Name-Last: Fettermann
Title: Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies
Abstract: 
 The adoption of Industry 4.0 technologies has been deemed as a strategy to increase product quality and make manufacturing processes more efficient. However, the way that these technologies are integrated into existing production systems and which processes they can support is still under investigation. Thus, this paper aims to examine the relationship between lean production (LP) practices and the implementation of Industry 4.0 in Brazilian manufacturing companies. To achieve that we use data from a survey carried out with 110 companies of different sizes and sectors, at different stages of LP implementation. Data collected were analysed by means of multivariate analysis. Our findings indicate that LP practices are positively associated with Industry 4.0 technologies and their concurrent implementation leads to larger performance improvements. Further, the contextual variables investigated do matter to this association, although not all aspects matter to the same extent and effect.
Journal: International Journal of Production Research
Pages: 2975-2987
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1391420
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1391420
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Template-Type: ReDIF-Article 1.0
Author-Name: Rameshwar Dubey
Author-X-Name-First: Rameshwar
Author-X-Name-Last: Dubey
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Stephen J. Childe
Author-X-Name-First: Stephen J.
Author-X-Name-Last: Childe
Author-Name: Thanos Papadopoulos
Author-X-Name-First: Thanos
Author-X-Name-Last: Papadopoulos
Author-Name: Benjamin T. Hazen
Author-X-Name-First: Benjamin T.
Author-X-Name-Last: Hazen
Author-Name: David Roubaud
Author-X-Name-First: David
Author-X-Name-Last: Roubaud
Title: Examining top management commitment to TQM diffusion using institutional and upper echelon theories
Abstract: 
 Total Quality Management (TQM) is an enduring approach for enhancing firm competitiveness. Still, there is dearth of research regarding organisational diffusion (post-adoption) of TQM. To address this gap, this research proposes a theoretical model rooted in institutional and upper echelon theories that explain TQM diffusion via top management commitment. We surveyed 300 senior quality managers representing 300 auto-components manufacturers in India to collect data to test the proposed model using variance based structural equation modelling (PLS-SEM). The findings suggest that institutional pressures significantly influence top management commitment to TQM. Subsequently, top management commitment influences organisational diffusion of TQM via acceptance, routinisation and assimilation. Managers can use the findings of this research to better understand how to assimilate TQM so that anticipated benefits can be fully realised.
Journal: International Journal of Production Research
Pages: 2988-3006
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1394590
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394590
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Template-Type: ReDIF-Article 1.0
Author-Name: C.K.M. Lee
Author-X-Name-First: C.K.M.
Author-X-Name-Last: Lee
Author-Name: Yaqiong Lv
Author-X-Name-First: Yaqiong
Author-X-Name-Last: Lv
Author-Name: K.K.H. Ng
Author-X-Name-First: K.K.H.
Author-X-Name-Last: Ng
Author-Name: William Ho
Author-X-Name-First: William
Author-X-Name-Last: Ho
Author-Name: K.L. Choy
Author-X-Name-First: K.L.
Author-X-Name-Last: Choy
Title: Design and application of Internet of things-based warehouse management system for smart logistics
Abstract: 
 Warehouse operations need to change due to the increasing complexity and variety of customer orders. The demand for real-time data and contextual information is requried because of the highly customised orders, which tend to be of small batch size but with high variety. Since the orders frequently change according to customer requirements, the synchronisation of purchase orders to support production to ensure on-time order fulfilment is of high importance. However, the inefficient and inaccurate order picking process has adverse effects on the order fulfilment. The objective of this paper is to propose an Internet of things (IoT)-based warehouse management system with an advanced data analytical approach using computational intelligence techniques to enable smart logistics for Industry 4.0. Based on the data collected from a case company, the proposed IoT-based WMS shows that the warehouse productivity, picking accuracy and efficiency can be improved and it is robust to order variability.
Journal: International Journal of Production Research
Pages: 2753-2768
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1394592
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394592
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:8:p:2753-2768




Template-Type: ReDIF-Article 1.0
Author-Name: Ann-Louise Andersen
Author-X-Name-First: Ann-Louise
Author-X-Name-Last: Andersen
Author-Name: Hoda ElMaraghy
Author-X-Name-First: Hoda
Author-X-Name-Last: ElMaraghy
Author-Name: Waguih ElMaraghy
Author-X-Name-First: Waguih
Author-X-Name-Last: ElMaraghy
Author-Name: Thomas D. Brunoe
Author-X-Name-First: Thomas D.
Author-X-Name-Last: Brunoe
Author-Name: Kjeld Nielsen
Author-X-Name-First: Kjeld
Author-X-Name-Last: Nielsen
Title: A participatory systems design methodology for changeable manufacturing systems
Abstract: 
 The ability to adapt to changes in products, processes and technologies is a key competitive factor. Changeable manufacturing paradigms have emerged to address this need, but the industrial implementation remains challenging. In this paper, a participatory design methodology for changeable manufacturing systems is proposed, including requirements specification, selection of appropriate manufacturing paradigm and suitable physical and logical enablers. The methodology supports companies in determining the potential for and mechanisms of transitioning towards changeable manufacturing systems, based on knowledge of products, production, technologies and facilities. The developed methodology is applicable to both new and existing manufacturing systems. It is demonstrated in two industrial cases which highlight its applicability and differences in the appropriate recommended manufacturing systems transition towards changeability as a result of differences in manufacturing characteristics, change requirements and enablers.
Journal: International Journal of Production Research
Pages: 2769-2787
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1394594
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394594
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Template-Type: ReDIF-Article 1.0
Author-Name: Margaretha Gansterer
Author-X-Name-First: Margaretha
Author-X-Name-Last: Gansterer
Author-Name: Richard F. Hartl
Author-X-Name-First: Richard F.
Author-X-Name-Last: Hartl
Title: One- and two-sided assembly line balancing problems with real-world constraints
Abstract: 
 In this study, we consider balancing problems of one- and two-sided assembly lines with real-world constraints like task or machine incompatibilities. First, we study the one-sided assembly line balancing problem (ALBP) with a limited number of machine types per workstation. Using a genetic algorithm (GA), we find optimal results for real-world instances. A set of larger test cases is used to compare two well-established solution approaches, namely GA and tabu search (TS). Additionally, we apply a specific differential evolution algorithm (DE), which has recently been proposed for the considered ALBP. Our computational results show that DE is clearly dominated by GA. Furthermore, we show that GA outperforms TS in terms of computational time, if capacity constraints are tight. Given the algorithm’s computational performance as well as the fact that it can easily be adapted to additional constraints, we then use it to solve two-sided ALBP. Three types of constraints and two different objectives are considered. We outperform all previously published methods in terms of solution quality and computational time. Finally, we are the first to provide feasible test instances as well as benchmark results for fully constrained two-sided ALB.
Journal: International Journal of Production Research
Pages: 3025-3042
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1394599
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394599
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Template-Type: ReDIF-Article 1.0
Author-Name: Mike Bourne
Author-X-Name-First: Mike
Author-X-Name-Last: Bourne
Author-Name: Monica Franco-Santos
Author-X-Name-First: Monica
Author-X-Name-Last: Franco-Santos
Author-Name: Pietro Micheli
Author-X-Name-First: Pietro
Author-X-Name-Last: Micheli
Author-Name: Andrey Pavlov
Author-X-Name-First: Andrey
Author-X-Name-Last: Pavlov
Title: Performance measurement and management: a system of systems perspective
Abstract: 
 Despite changes in tools and practices, the conceptual foundations of performance measurement and management (PMM) are still predominantly rooted in control systems research. While PMM approaches have delivered significant organisational benefits, including creating alignment, supporting monitoring and control, and enabling prediction and optimisation of resource allocation, this paper argues that this paradigm is not capable of responding to increasingly complex and highly uncertain organisational environments. Drawing on ideas emerging in the literature on systems engineering and complex systems, we propose a novel perspective that considers PMM from a ‘system of systems’ (SoS) point of view, whose essential characteristics are autonomy, belonging, connectivity, diversity and emergence. After identifying the assumptions underpinning existing PMM approaches, we outline a SoS-based paradigm to PMM and conclude by articulating the main implications for the practice of PMM and setting out a research agenda.
Journal: International Journal of Production Research
Pages: 2788-2799
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1404159
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1404159
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Template-Type: ReDIF-Article 1.0
Author-Name: Zichang He
Author-X-Name-First: Zichang
Author-X-Name-Last: He
Author-Name: Wen Jiang
Author-X-Name-First: Wen
Author-X-Name-Last: Jiang
Title: A new belief Markov chain model and its application in inventory prediction
Abstract: 
 The Markov chain model is widely applied in many fields, especially the field of prediction. The discrete-time Markov chain (DTMC) is a common method for prediction. However, the classical DTMC model has some limitations when the system is complex with uncertain information or state space is not discrete. To address it, a new belief Markov chain (BMC) model combining Dempster-Shafer evidence theory and the DTMC is proposed. In our model, the uncertain data are allowed to be handled in the form of interval number, and the basic probability assignment is generated by an optimisation method based on the distance between interval numbers. The shortcoming of classical DTMC is overcome in the BMC model. Also, it has an efficient ability of dealing with uncertain information, including both the uncertainty of collected data and discerning states. Our model is applied to do the prediction of inventory demand and the result is close to the practical. Also, sensitivity analysis and some comparisons are accomplished to show the effectiveness and rationality of our proposed model.
Journal: International Journal of Production Research
Pages: 2800-2817
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1405166
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1405166
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:8:p:2800-2817




Template-Type: ReDIF-Article 1.0
Author-Name: Georg Weichhart
Author-X-Name-First: Georg
Author-X-Name-Last: Weichhart
Author-Name: Christian Stary
Author-X-Name-First: Christian
Author-X-Name-Last: Stary
Author-Name: François Vernadat
Author-X-Name-First: François
Author-X-Name-Last: Vernadat
Title: Enterprise modelling for interoperable and knowledge-based enterprises
Abstract: 
 The paper first takes a look at the state of the art on the overlapping areas of: Enterprise Modelling, Enterprise Integration/Interoperability, Organisational Learning and Knowledge Management. We identify requirements, characterisation and recent contributions for the interoperable and knowledge-based enterprises in the area of production of goods or services. It is then advocated that Enterprise Modelling and Knowledge Representation should combine their efforts to develop reference and reusable core manufacturing enterprise ontologies to support Enterprise Integration and Interoperability on one hand and open the door to Organisational Learning and management of active knowledge for the ‘smart’ enterprises of tomorrow on the other hand. This is illustrated by case studies from projects carried out in industry.
Journal: International Journal of Production Research
Pages: 2818-2840
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1406673
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1406673
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Template-Type: ReDIF-Article 1.0
Author-Name: Xin W. Chen
Author-X-Name-First: Xin W.
Author-X-Name-Last: Chen
Title: Knowledge-based analytics for massively distributed networks with noisy data
Abstract: 
 This article develops and implements an improving search algorithm that effectively and efficiently identifies pathways of interest using knowledge-based analytics for massively distributed networks with noisy data. The method developed in this article fundamentally changes how critical information is extracted from large data-sets. Many methods have been developed in the past to identify structures in large graphs. Most of these methods are computationally inefficient for large graphs and their outcome depends on the graph metrics and statistical measures. There has been limited research on using optimisation techniques for data mining in large networks with noisy data. The algorithm developed in this article converges to the optimal solution by traversing the interior of a feasible region. Experiments show that it identifies a pathway of interest from a network of 160,000 components in 10 hours using parallel computing. Future work will include customisation and implementation of the method to other large networks in a variety of applications.
Journal: International Journal of Production Research
Pages: 2841-2854
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1408972
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1408972
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Template-Type: ReDIF-Article 1.0
Author-Name: Damiano Arena
Author-X-Name-First: Damiano
Author-X-Name-Last: Arena
Author-Name: Apostolos Charalampos Tsolakis
Author-X-Name-First: Apostolos Charalampos
Author-X-Name-Last: Tsolakis
Author-Name: Stylianos Zikos
Author-X-Name-First: Stylianos
Author-X-Name-Last: Zikos
Author-Name: Stelios Krinidis
Author-X-Name-First: Stelios
Author-X-Name-Last: Krinidis
Author-Name: Chrysovalantou Ziogou
Author-X-Name-First: Chrysovalantou
Author-X-Name-Last: Ziogou
Author-Name: Dimosthenis Ioannidis
Author-X-Name-First: Dimosthenis
Author-X-Name-Last: Ioannidis
Author-Name: Spyros Voutetakis
Author-X-Name-First: Spyros
Author-X-Name-Last: Voutetakis
Author-Name: Dimitrios Tzovaras
Author-X-Name-First: Dimitrios
Author-X-Name-Last: Tzovaras
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Human resource optimisation through semantically enriched data
Abstract: 
 The industrial domain is experiencing a so-called fourth industrial revolution in which the evergrowing complexity of manufacturing information, the increasing amount of knowledge and the use of web-oriented techniques, represent three crucial factors that are accelerating the growth of complexity of industrial systems. On the other hand, continuous-evolving requirements in industrial environments, due to technology outbreaks and a new global marketplace, have led to an on-going evolution of human resource management through the creation and adoption of alternative business models. In the past decade, semantic models such as ontologies have been proven to be effective for many knowledge-intensive applications, since they provide formal models of domain knowledge that can be exploited in different ways. For all these reasons, an innovative human resource optimisation (HRO) engine is introduced, which employs semantically enhanced information and conditional random field (CRFs) probabilistic models with knowledge derived from industrial shop floor level, and proposes the right person for the right job in real-time shop floor operations towards optimising decisions on how to implement and schedule either repeatedly or non-occurring tasks. Industrial information data flow and semantic enrichment were ensured through the combined use of a common interface data exchange model (CIDEM) and ontologies, after which a feasibility study at a chemical plant presented interesting preliminary results.
Journal: International Journal of Production Research
Pages: 2855-2877
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1415468
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1415468
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Template-Type: ReDIF-Article 1.0
Author-Name: Bruno Vallespir
Author-X-Name-First: Bruno
Author-X-Name-Last: Vallespir
Author-Name: Yves Ducq
Author-X-Name-First: Yves
Author-X-Name-Last: Ducq
Title: Enterprise modelling: from early languages to models transformation
Abstract: 
 During the last 30 years, enterprise modelling has been recognised as an efficient tool to externalise the knowledge of companies in order to understand their operations, to analyse their running and to design new systems from several points of view: functions, processes, decisions, resources and information technology. This paper aims at describing the long evolution of enterprise modelling techniques as well as one of the future challenges of these techniques: the transformation of enterprise models. So, in a first part, the paper describes the evolution of enterprise modelling techniques from the divergence era to the convergence period. In a second time, the paper focuses on the recent advances in the use of enterprise models through model-driven approaches, interoperability problem-solving and simulation, all these advances having the same characteristic to use the transformation of enterprise models.
Journal: International Journal of Production Research
Pages: 2878-2896
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1418985
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1418985
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Template-Type: ReDIF-Article 1.0
Author-Name: Xinyu Li
Author-X-Name-First: Xinyu
Author-X-Name-Last: Li
Author-Name: Zuhua Jiang
Author-X-Name-First: Zuhua
Author-X-Name-Last: Jiang
Author-Name: Lijun Liu
Author-X-Name-First: Lijun
Author-X-Name-Last: Liu
Author-Name: Bo Song
Author-X-Name-First: Bo
Author-X-Name-Last: Song
Title: A novel approach for analysing evolutional motivation of empirical engineering knowledge
Abstract: 
 Empirical engineering knowledge (EEK), a specific technical know-how about solving engineering problems, is frequently accumulated and reused in this era of mass innovation and knowledge-driven economy. Since EEK is abidingly evolving because of the intense business competitions, continual technical renovations and wide industrial concern, it’s a new challenge both in theories and applications of knowledge management to analyse EEK evolution and its motivations. This paper proposes a novel approach to tackle this non-trivial issue. Based on the constructed domain hierarchy and EEK networks, EEK clusters are grouped and represented with populations, latent topics and distributions. Then four kinds of evolutional patterns are defined and recognised from the EEK clusters in neighbouring time intervals. The evolutional motivations of these patterns are discovered from the important evolutional events, with the proposed abductive reasoning algorithm. This paper also integrates all techniques, and implements a knowledge management system EEK-KEAS in computer-aided design (CAD), a typical engineering field. Experimental result shows that EEK-KEAS operations well in revealing the evolutional motivations of CAD EEKs, and outperforms the former approaches in feasibility and effectiveness, thereby opening up a novel way for further understanding the evolution of EEK.
Journal: International Journal of Production Research
Pages: 2897-2923
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1421785
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421785
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:8:p:2897-2923




Template-Type: ReDIF-Article 1.0
Author-Name: Sven-Vegard Buer
Author-X-Name-First: Sven-Vegard
Author-X-Name-Last: Buer
Author-Name: Jan Ola Strandhagen
Author-X-Name-First: Jan Ola
Author-X-Name-Last: Strandhagen
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Title: The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda
Abstract: 
 In recent years, Industry 4.0 has emerged as one of the most discussed concepts and has gained significant popularity in both academia and the industrial sector. Both Industry 4.0 and lean manufacturing utilise decentralised control and aim to increase productivity and flexibility. However, there have been few studies investigating the link between these two domains. This article explores this novel area and maps the current literature. This is achieved through a systematic literature review methodology, investigating literature published up to and including August 2017. This article identifies four main research streams concerning the link between Industry 4.0 and lean manufacturing, and a research agenda for future studies is proposed.
Journal: International Journal of Production Research
Pages: 2924-2940
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2018.1442945
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1442945
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:8:p:2924-2940




Template-Type: ReDIF-Article 1.0
Author-Name: Li Da Xu
Author-X-Name-First: Li Da
Author-X-Name-Last: Xu
Author-Name: Eric L. Xu
Author-X-Name-First: Eric L.
Author-X-Name-Last: Xu
Author-Name: Ling Li
Author-X-Name-First: Ling
Author-X-Name-Last: Li
Title: Industry 4.0: state of the art and future trends
Abstract: 
 Rapid advances in industrialisation and informatisation methods have spurred tremendous progress in developing the next generation of manufacturing technology. Today, we are on the cusp of the Fourth Industrial Revolution. In 2013, amongst one of 10 ‘Future Projects’ identified by the German government as part of its High-Tech Strategy 2020 Action Plan, the Industry 4.0 project is considered to be a major endeavour for Germany to establish itself as a leader of integrated industry. In 2014, China’s State Council unveiled their ten-year national plan, Made-in-China 2025, which was designed to transform China from the world’s workshop into a world manufacturing power. Made-in-China 2025 is an initiative to comprehensively upgrade China’s industry including the manufacturing sector. In Industry 4.0 and Made-in-China 2025, many applications require a combination of recently emerging new technologies, which is giving rise to the emergence of Industry 4.0. Such technologies originate from different disciplines including cyber-physical Systems, IoT, cloud computing, Industrial Integration, Enterprise Architecture, SOA, Business Process Management, Industrial Information Integration and others. At this present moment, the lack of powerful tools still poses a major obstacle for exploiting the full potential of Industry 4.0. In particular, formal methods and systems methods are crucial for realising Industry 4.0, which poses unique challenges. In this paper, we briefly survey the state of the art in the area of Industry 4.0 as it relates to industries.
Journal: International Journal of Production Research
Pages: 2941-2962
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2018.1444806
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1444806
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:8:p:2941-2962




Template-Type: ReDIF-Article 1.0
Author-Name: Shuhong Wang
Author-X-Name-First: Shuhong
Author-X-Name-Last: Wang
Author-Name: Mei Chen
Author-X-Name-First: Mei
Author-X-Name-Last: Chen
Author-Name: Malin Song
Author-X-Name-First: Malin
Author-X-Name-Last: Song
Title: Energy constraints, green technological progress and business profit ratios: evidence from big data of Chinese enterprises
Abstract: 
 This study tested the influences of energy constraints on business profit ratios based on mathematical models of energy constraints, green technological progress and business profit ratios using data of 1,039,330 qualified Chinese industrial enterprises between 2001 and 2013. Test results showed a generally non-linear relationship between energy constraints and business profit ratios. Specifically, for high-tech enterprises in East China, the relationship is U-shaped; and for low-tech enterprises in Middle and West China, the relationship is N-shaped. Proper energy policies can effectively improve business profit ratios and stimulate green technological progress in enterprises. Although China’s energy policies still have not realised relevant practical effects, proper energy policies should be implemented according to the features of different areas and enterprises. This is of great significance to green technological progress and enterprise development.
Journal: International Journal of Production Research
Pages: 2963-2974
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2018.1454613
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1454613
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:8:p:2963-2974




Template-Type: ReDIF-Article 1.0
Author-Name: F.B. Vernadat
Author-X-Name-First: F.B.
Author-X-Name-Last: Vernadat
Author-Name: F.T.S. Chan
Author-X-Name-First: F.T.S.
Author-X-Name-Last: Chan
Author-Name: A. Molina
Author-X-Name-First: A.
Author-X-Name-Last: Molina
Author-Name: S.Y. Nof
Author-X-Name-First: S.Y.
Author-X-Name-Last: Nof
Author-Name: H. Panetto
Author-X-Name-First: H.
Author-X-Name-Last: Panetto
Title: Information systems and knowledge management in industrial engineering: recent advances and new perspectives
Journal: International Journal of Production Research
Pages: 2707-2713
Issue: 8
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2018.1454615
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1454615
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:8:p:2707-2713




Template-Type: ReDIF-Article 1.0
Author-Name: Avi Herbon
Author-X-Name-First: Avi
Author-X-Name-Last: Herbon
Title: Non-cooperative game of a duopoly under asymmetric information on consumer location
Abstract: 
 We consider a single inventoried product that is sold by two competing firms (i.e. a duopoly). The two firms are located at both endpoints of a straight line. We assume the firms are unequal in their access to information on consumer locations, that is, only one of the two firms has full information about consumer location. By modelling the profit maximisation problem as a non-cooperative game, we obtain the best response function of the firm who does not have access to accurate consumer information. We show that this response function is translated into a unique, global solution. Through an extensive numerical example, we conclude that asymmetric information on consumer location has a significant effect on the profit gap between the competing firms and on the market share that each firm is able to attract. We conclude that when one firm inaccurately estimates consumer information about location, this can cause a significant deterioration in the profits of both firms and the consumers are the ones who gain from this information asymmetry. This conclusion encourages information sharing with the uninformed firm. Surprisingly, it also emerges from our computation that the higher the travelling costs the higher profits both firms obtain.
Journal: International Journal of Production Research
Pages: 5185-5201
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2016.1278482
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1278482
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:18:p:5185-5201




Template-Type: ReDIF-Article 1.0
Author-Name: Itshak Tkach
Author-X-Name-First: Itshak
Author-X-Name-Last: Tkach
Author-Name: Yael Edan
Author-X-Name-First: Yael
Author-X-Name-Last: Edan
Author-Name: Shimon Y. Nof
Author-X-Name-First: Shimon Y.
Author-X-Name-Last: Nof
Title: Multi-sensor task allocation framework for supply networks security using task administration protocols
Abstract: 
 This research proposes a multi-sensor task allocation framework for security of supply networks aimed to maximise the number of correctly detected and reported security events (defined as tasks). The framework includes a double layer system consisting of a process layer and a monitoring layer. The process layer allocates sensors to tasks using an ant colony algorithm. The monitoring layer applies four task administration protocols (TAPs) specially developed and implemented to deal with high time-consuming tasks, conflicts in task priorities and sensor failure, defined in this research as overloading, deception and tampering of sensors, respectively. A system objective function for sensor to task allocation was developed to allow computation of the expected value of system performance given the sensor and the task parameters. Sensory limitations evaluated including reliability, distance coverage and the limited number of sensors are addressed in the decision-making process. The framework enables detection of tasks as soon as they occur in every location along the supply network, based on the sensor network distribution. The dual layer system analyses reveal that TAPs increase the systems performance in the scenarios of deception, tampering and overloading by more than 64% with respect to the number of unallocated tasks in comparison to a single layer system. Overall availability was analysed using Monte Carlo simulation and the fault tolerant system yielded significantly increased number of treated tasks (by 11%, p = 0.02).
Journal: International Journal of Production Research
Pages: 5202-5224
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1286047
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1286047
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Template-Type: ReDIF-Article 1.0
Author-Name: M. Hemmati
Author-X-Name-First: M.
Author-X-Name-Last: Hemmati
Author-Name: S.M.T. Fatemi Ghomi
Author-X-Name-First: S.M.T.
Author-X-Name-Last: Fatemi Ghomi
Author-Name: Mohsen S. Sajadieh
Author-X-Name-First: Mohsen S.
Author-X-Name-Last: Sajadieh
Title: Vendor managed inventory with consignment stock for supply chain with stock- and price-dependent demand
Abstract: 
 This paper presents a single vendor–single buyer coordinated model. The vendor produces a single deteriorating item and transfers it to the buyer in equal shipments. The model is based on vendor managed inventory with consignment stock (VMI-CS) agreement in which the vendor uses the buyer’s warehouse. The buyer stocks items both on his shelf and in his warehouse. The demand is assumed to be linearly sensitive to inventory level and selling price. The objective is to determine variables that maximise the total profit. An exact solution procedure is proposed to find the optimal solution. Numerical results show that supply chain members will benefit from the advantages of economies of scale in coordinated model with VMI-CS policy.
Journal: International Journal of Production Research
Pages: 5225-5242
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1296203
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1296203
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Template-Type: ReDIF-Article 1.0
Author-Name: Kamil J. Mizgier
Author-X-Name-First: Kamil J.
Author-X-Name-Last: Mizgier
Author-Name: Joseph M. Pasia
Author-X-Name-First: Joseph M.
Author-X-Name-Last: Pasia
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Title: Multiobjective capital allocation for supplier development under risk
Abstract: 
 Supplier development is increasingly important due to the complexity of today’s supply chains and the globalisation of businesses. Since manufacturers have only limited resources, they need to make an informed decision about which suppliers to develop. Moreover, the returns from investment in supplier development are uncertain, so manufacturers have to take this risk into account when choosing their suppliers for development programmes. In this paper, we propose a multi-objective model for capital allocation for supplier development under risk. We apply it to an example of a global car manufacturer and support the decision-making process with data downloaded from the Bloomberg database. We use stock market returns and cost of capital of suppliers to assess their performance. Our model supports an informed decision, which is that tradeoffs exist between risk and cost of supplier development programme. Depending on the risk aversion of the manufacturer, we demonstrate different allocation schemes for supplier development.
Journal: International Journal of Production Research
Pages: 5243-5258
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1302618
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1302618
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Template-Type: ReDIF-Article 1.0
Author-Name: Michael Leyer
Author-X-Name-First: Michael
Author-X-Name-Last: Leyer
Author-Name: Jutta Stumpf-Wollersheim
Author-X-Name-First: Jutta
Author-X-Name-Last: Stumpf-Wollersheim
Author-Name: Francesco Pisani
Author-X-Name-First: Francesco
Author-X-Name-Last: Pisani
Title: The influence of process-oriented organisational design on operational performance and innovation: a quantitative analysis in the financial services industry
Abstract: 
 Market competition requires that organisations excel at both operational performance and innovation. Though process orientation is intended to benefit operations in general, the impact of specific elements remains unclear. The purpose of this study is to identify the specific organisational design components of process orientation that simultaneously influence operational performance and innovation. We survey employees in the financial services sector (N = 1069) regarding the influence of six process-oriented organisation design components on operational performance and innovation using PLS-SEM. The results indicate that organisational structure and process improvement encourage both operational performance and innovation. Personal autonomy is partially beneficial, while the others have no joint influence on operational performance and innovation. This study is first in providing evidence regarding the influence of a broad variety of organisational design components of process orientation on operational performance and innovation. The study contributes to theory on how process orientation improves operational performance and innovation. The findings can serve as a guideline for managers and organisations as to which organisational design components should be implemented to improve operations.
Journal: International Journal of Production Research
Pages: 5259-5270
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1304667
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1304667
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Template-Type: ReDIF-Article 1.0
Author-Name: Alberto Pliego Marugán
Author-X-Name-First: Alberto
Author-X-Name-Last: Pliego Marugán
Author-Name: Fausto Pedro García Márquez
Author-X-Name-First: Fausto Pedro
Author-X-Name-Last: García Márquez
Author-Name: Benjamin Lev
Author-X-Name-First: Benjamin
Author-X-Name-Last: Lev
Title: Optimal decision-making via binary decision diagrams for investments under a risky environment
Abstract: 
 This paper presents two methods for supporting investments and resource allocation in a constrained risky environment. These methods are based on the application of logical decision trees and binary decision diagrams as an approach that allows quantitative analysis of a qualitative study. The scenario considered in this paper is a decision-making process under risk environment, where stochastic variables are considered. The two novel procedures are introduced to facilitate the resource allocation as the objective of the decision-making process. The first procedure uses the analytic expression provided by binary decision diagrams as an objective function of a non-linear programing model. The second procedure introduces an importance measure that takes into account some external constraints, unlike the classical importance measures that only consider the topology of the tree. The first technique will optimise the outcomes and the second will provide a good approximation of the outcomes using simpler calculations.
Journal: International Journal of Production Research
Pages: 5271-5286
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1308570
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1308570
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianxin Chen
Author-X-Name-First: Jianxin
Author-X-Name-Last: Chen
Author-Name: Yong-Wu Zhou
Author-X-Name-First: Yong-Wu
Author-X-Name-Last: Zhou
Author-Name: Yuanguang Zhong
Author-X-Name-First: Yuanguang
Author-X-Name-Last: Zhong
Title: A pricing/ordering model for a dyadic supply chain with buyback guarantee financing and fairness concerns
Abstract: 
 The paper investigates pricing/ordering issues in a dyadic supply chain, in which a core supplier sells products through a budget-constrained retailer. The retailer faces stochastic demand and is fairness-concerned as well. If needed, the retailer can get financing support from bank by means of buyback guarantee financing (BGF) mode, which is often used in China. By introducing Nash bargaining solution as the fairness reference point, we formulate the retailer’s fairness-concerned utility function and develop a two-echelon pricing/ordering game model. We then study the combined impacts of fairness concerns and BGF on two members’ equilibrium strategies and supply chain performance. We also discuss the corresponding issues under no budget constraint, no financing service and bank financing. Our results show that: (1) two members’ equilibrium strategies are significantly influenced by the retailer’s fairness-concerned behaviour and initial budget; (2) as compared to no budget constraint, BGF can bring the whole supply chain more performance, which means that BGF can yield value-added; (3) When the retailer takes the risk of uncertain market solely, the retailer’s fairness concerns are beneficial for supply chain to improve the performance.
Journal: International Journal of Production Research
Pages: 5287-5304
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1308571
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1308571
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Template-Type: ReDIF-Article 1.0
Author-Name: Rihab Khemiri
Author-X-Name-First: Rihab
Author-X-Name-Last: Khemiri
Author-Name: Khaoula Elbedoui-Maktouf
Author-X-Name-First: Khaoula
Author-X-Name-Last: Elbedoui-Maktouf
Author-Name: Bernard Grabot
Author-X-Name-First: Bernard
Author-X-Name-Last: Grabot
Author-Name: Belhassen Zouari
Author-X-Name-First: Belhassen
Author-X-Name-Last: Zouari
Title: A fuzzy multi-criteria decision-making approach for managing performance and risk in integrated procurement–production planning
Abstract: 
 Nowadays in Supply Chain (SC) networks, a high level of risk comes from SC partners. An effective risk management process becomes as a consequence mandatory, especially at the tactical planning level. The aim of this article is to present a risk-oriented integrated procurement–production approach for tactical planning in a multi-echelon SC network involving multiple suppliers, multiple parallel manufacturing plants, multiple subcontractors and several customers. An originality of the work is to combine an analytical model allowing to build feasible scenarios and a multi-criteria approach for assessing these scenarios. The literature has mainly addressed the problem through cost or profit-based optimisation and seldom considers more qualitative yet important criteria linked to risk, like trust in the supplier, flexibility or resilience. Unlike the traditional approaches, we present a method evaluating each possible supply scenario through performance-based and risk-based decision criteria, involving both qualitative and quantitative factors, in order to clearly separate the performance of a scenario and the risk taken if it is adopted. Since the decision-maker often cannot provide crisp values for some critical data, fuzzy sets theory is suggested in order to model vague information based on subjective expertise. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution is used to determine both the performance and risk measures correlated to each possible tactical plan. The applicability and tractability of the proposed approach is shown on an illustrative example and a sensitivity analysis is performed to investigate the influence of criteria weights on the selection of the procurement–production plan.
Journal: International Journal of Production Research
Pages: 5305-5329
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1308575
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1308575
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Template-Type: ReDIF-Article 1.0
Author-Name: J. Behnamian
Author-X-Name-First: J.
Author-X-Name-Last: Behnamian
Author-Name: S.M.T. Fatemi Ghomi
Author-X-Name-First: S.M.T.
Author-X-Name-Last: Fatemi Ghomi
Author-Name: B. Karimi
Author-X-Name-First: B.
Author-X-Name-Last: Karimi
Author-Name: M. Fadaei Moludi
Author-X-Name-First: M.
Author-X-Name-Last: Fadaei Moludi
Title: A Markovian approach for multi-level multi-product multi-period capacitated lot-sizing problem with uncertainty in levels
Abstract: 
 This paper considers a multi-level, multi-item, multi-period capacitated lot-sizing problem with sequence-dependent family set-up times, set-up carry over and uncertainty in levels due to uncertainty in inspection, rework and scrap. In this study, we, first, determined total processing time for each product of each family. Then, expected number of times associated with visiting each level of each product as well as amount of raw materials are calculated. We developed a mixed integer linear programming model with a numerical example and sensitivity analysis.
Journal: International Journal of Production Research
Pages: 5330-5340
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1311048
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1311048
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Template-Type: ReDIF-Article 1.0
Author-Name: Dilupa Nakandala
Author-X-Name-First: Dilupa
Author-X-Name-Last: Nakandala
Author-Name: Henry Lau
Author-X-Name-First: Henry
Author-X-Name-Last: Lau
Author-Name: Paul K.C. Shum
Author-X-Name-First: Paul K.C.
Author-X-Name-Last: Shum
Title: A lateral transshipment model for perishable inventory management
Abstract: 
 Since inventory costs account for half of logistics costs, optimal inventory management to minimise total inventory costs remains a sustainable competitive advantage. Lateral transshipment (LT) is evidently a proven strategy to minimise total inventory costs. The additional LT costs are more than compensated by lowering the stock-out costs. Previous LT models have not been applied to perishable products. Our proposed LT model embodies spoilage costs in the total inventory costs function with the other cost components (purchase from a regular supplier, LT, backordering and holding), and optimises the trade-off among these five key cost components. Numerical examples from a supermarket chain case study demonstrate that, as compared against the no or lower spoilage costs scenarios, lower LT costs are required to trigger the decision point for implementing LT in the higher spoilage costs scenario. However, common to both the with and without spoilage costs scenarios, LT is still the preferred strategy to minimise total inventory costs, given the decision rules are satisfied.
Journal: International Journal of Production Research
Pages: 5341-5354
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1312587
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1312587
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Template-Type: ReDIF-Article 1.0
Author-Name: Jie Xiong
Author-X-Name-First: Jie
Author-X-Name-Last: Xiong
Author-Name: Tsan Sheng Ng
Author-X-Name-First: Tsan Sheng
Author-X-Name-Last: Ng
Author-Name: Zhou He
Author-X-Name-First: Zhou
Author-X-Name-Last: He
Author-Name: Bo Fan
Author-X-Name-First: Bo
Author-X-Name-Last: Fan
Title: Modelling and analysis of a symbiotic waste management system
Abstract: 
 A municipal solid waste management system is symbiotic when there exists physical exchange of material or by-products between different treatment units. We propose a mathematical model for studying the interactive behaviour of different waste treatment operators in a symbiotic environment. Each operator is a self-interested entity, who sets his gate fee charge to maximise his own payoff. We study the properties and gate fee strategies of the operators, and also perform sensitivity analysis on various model parameters to discuss the local operator behaviour and the effects of various intervention strategies. We also propose a numerical algorithm to solve the model, yielding the optimal equilibrium gate fee charges, payoff and market share levels of different operators. Finally, computational studies based on a two-unit scenario in a case study of organic waste recycling is performed to demonstrate the interactive and dynamic behaviours of different operators. Our results strongly suggest that, to improve new treatment technology utilisation, subsidising the operating cost of the new treatment unit is more effective in the long-run than exerting control on the gate fee upper bounds of the operators by the system regulator. Furthermore, providing residual post-treatment discounts for treatment units can benefit the service users, rather than the waste treatment operators.
Journal: International Journal of Production Research
Pages: 5355-5377
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1312588
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1312588
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Template-Type: ReDIF-Article 1.0
Author-Name: Idris Lalami
Author-X-Name-First: Idris
Author-X-Name-Last: Lalami
Author-Name: Yannick Frein
Author-X-Name-First: Yannick
Author-X-Name-Last: Frein
Author-Name: Jean-Philippe Gayon
Author-X-Name-First: Jean-Philippe
Author-X-Name-Last: Gayon
Title: Production planning in automotive powertrain plants: a case study
Abstract: 
 Based on a real case study from the automotive industry, this paper deals with production planning in powertrain plants. We present an overview of the production planning process and propose a mixed integer linear programme to determine the production quantities of each product over a planning horizon of several days. Then, using real data of an engine assembly line, we simulate the performance obtained through the proposed model within a rolling horizon planning process. We perform multiple tests in order to evaluate the impact of two parameters involved in this process: planning frequency and frozen horizon length. Furthermore, in order to illustrate the value of improving coordination between engine plants and their customers, we evaluate the impact of the quality of demand information (orders and forecasts). We analyse the simulation results and provide insights and recommendations in order to achieve a good trade-off between service level, inventory, and planning stability.
Journal: International Journal of Production Research
Pages: 5378-5393
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1315192
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1315192
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Template-Type: ReDIF-Article 1.0
Author-Name: ManWo Ng
Author-X-Name-First: ManWo
Author-X-Name-Last: Ng
Author-Name: Wayne K. Talley
Author-X-Name-First: Wayne K.
Author-X-Name-Last: Talley
Title: Chassis inventory management at U.S. container ports:modelling and case study
Abstract: 
 Recently, marine container chassis have emerged at the forefront of container port operations in the United States, after shipping lines stopped providing chassis as part of their service. With the operation and management responsibilities transferred to new parties, chassis dislocation has been a major problem across the United States. To ensure chassis availability, one response has been the creation of so-called neutral chassis pools, introducing new challenges for container port operations. This paper presents a mathematical model that can be used to objectively support the management and planning of neutral chassis pools. An empirical case study is provided to illustrate the model.
Journal: International Journal of Production Research
Pages: 5394-5404
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1315193
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1315193
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Template-Type: ReDIF-Article 1.0
Author-Name: Durk-Jouke van der Zee
Author-X-Name-First: Durk-Jouke
Author-X-Name-Last: van der Zee
Title: Coordinating batching decisions in manufacturing networks
Abstract: 
 Family-based dispatching heuristics aim for improving job flow times by reducing time spent on set-ups. They realise set-up efficiencies by batching similar types of jobs. By their intuitiveness and the simplicity of their decision logic, they may contribute to an easy to implement and viable strategy in many practical settings. Similar to common dispatching rules most existing family-based dispatching heuristics are myopic, i.e. their decision scope is restricted to a single manufacturing stage. Hence, they neglect opportunities for improving shop performance by coordinating batching decisions with other manufacturing stages. Case examples from industry underpin the need for exploring these opportunities. We do so by studying a simple two-stage flow shop, entailing a serial and a batch stage. To facilitate shop coordination we propose extensions to existing family-based dispatching heuristics. Extended heuristics seek to further increase set-up efficiencies by allowing for upstream job re-sequencing, and pro-active set-ups, i.e. set-ups that may be initiated prior to the arrival of a job. Outcomes of an extensive simulation study indicate significant performance gains for extended heuristics vs. existing heuristics. Performance gains are largest for moderate and high set-up to run-time ratios.
Journal: International Journal of Production Research
Pages: 5405-5422
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1317926
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1317926
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Template-Type: ReDIF-Article 1.0
Author-Name: Gang Li
Author-X-Name-First: Gang
Author-X-Name-Last: Li
Author-Name: Gang Yu
Author-X-Name-First: Gang
Author-X-Name-Last: Yu
Author-Name: Shouyang Wang
Author-X-Name-First: Shouyang
Author-X-Name-Last: Wang
Author-Name: Hong Yan
Author-X-Name-First: Hong
Author-X-Name-Last: Yan
Title: Bullwhip and anti-bullwhip effects in a supply chain
Abstract: 
 The anti-bullwhip effect, coined by Li et al. in 2005 based on the findings in a simulation study, is the contrary effect of the well-known bullwhip effect. Although there is ample empirical evidence that suggests both effects exist, current literature has not yet provided an integrated framework to address how the two effects are related with each other. By extending the classic work of Lee, Padmanabhan, and Whang of 1997 to a multi-stage supply chain, we derive closed-form formula to analytically describe how the two effects originate initially and then evolve over time and space in the supply chain. Our results show both the bullwhip effect and the anti-bullwhip effect can occur when facing different end-customer demands. However, the magnitude of these effects gradually decreases when moving upstream. We also show the impact of long lead-time on increasing the magnitude of information transformation at the next stage and simultaneously decreasing the magnitude at higher stages. These analytical results provide a theoretical explanation to most simulation findings of Li et al.'s 2005 work and can be used by researchers and practitioners to examine the empirical data and design innovate marketing strategies to convert the unwelcome bullwhip effect into the anti-bullwhip effect.
Journal: International Journal of Production Research
Pages: 5423-5434
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1319087
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1319087
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Template-Type: ReDIF-Article 1.0
Author-Name: Patrick J. Reilly
Author-X-Name-First: Patrick J.
Author-X-Name-Last: Reilly
Author-Name: Jennifer A. Pazour
Author-X-Name-First: Jennifer A.
Author-X-Name-Last: Pazour
Author-Name: Kellie R. Schneider
Author-X-Name-First: Kellie R.
Author-X-Name-Last: Schneider
Title: Propagation of unit location uncertainty in dense storage environments
Abstract: 
 Dense storage systems provide high-space utilisation; however, because not all units are immediately accessible, selectively offloading units can require shifting of other stored units in order to access the requested unit. Given an initial certainty in unit location, a discrete time Markov Chain is developed to quantify the growth of unit location uncertainty as a function of retrieval requests. As the first to mathematically model uncertainty propagation in dense storage operations, metrics are developed to analyse the model. A theoretical understanding of the relationship among storage density, retrieval times and unit location uncertainty is provided. Finally, a case study using inventory and load plan data from a military application illustrates how the developed models can be used by managers to evaluate selective offloading policies and layouts.
Journal: International Journal of Production Research
Pages: 5435-5449
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1319582
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1319582
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Template-Type: ReDIF-Article 1.0
Author-Name: Sanjay Jain
Author-X-Name-First: Sanjay
Author-X-Name-Last: Jain
Author-Name: Guodong Shao
Author-X-Name-First: Guodong
Author-X-Name-Last: Shao
Author-Name: Seung-Jun Shin
Author-X-Name-First: Seung-Jun
Author-X-Name-Last: Shin
Title: Manufacturing data analytics using a virtual factory representation
Abstract: 
 Large manufacturers have been using simulation to support decision-making for design and production. However, with the advancement of technologies and the emergence of big data, simulation can be utilised to perform and support data analytics for associated performance gains. This requires not only significant model development expertise, but also huge data collection and analysis efforts. This paper presents an approach within the frameworks of Design Science Research Methodology and prototyping to address the challenge of increasing the use of modelling, simulation and data analytics in manufacturing via reduction of the development effort. The use of manufacturing simulation models is presented as data analytics applications themselves and for supporting other data analytics applications by serving as data generators and as a tool for validation. The virtual factory concept is presented as the vehicle for manufacturing modelling and simulation. Virtual factory goes beyond traditional simulation models of factories to include multi-resolution modelling capabilities and thus allowing analysis at varying levels of detail. A path is proposed for implementation of the virtual factory concept that builds on developments in technologies and standards. A virtual machine prototype is provided as a demonstration of the use of a virtual representation for manufacturing data analytics.
Journal: International Journal of Production Research
Pages: 5450-5464
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1321799
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1321799
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Template-Type: ReDIF-Article 1.0
Author-Name: James B. Dai
Author-X-Name-First: James B.
Author-X-Name-Last: Dai
Author-Name: Lei Fan
Author-X-Name-First: Lei
Author-X-Name-Last: Fan
Author-Name: Neville K.S. Lee
Author-X-Name-First: Neville K.S.
Author-X-Name-Last: Lee
Author-Name: Jianbin Li
Author-X-Name-First: Jianbin
Author-X-Name-Last: Li
Title: Joint optimisation of tracking capability and price in a supply chain with endogenous pricing
Abstract: 
 Tracking systems have been widely used to resolve the issues of product recall and food safety. Thus far, few researches have been done on designing the tracking capability from the perspective of supply chain. In this paper, using the traceable unit size at the manufacturer level to measure the tracking capability, we propose a non-convex non-linear programming to jointly optimise the tracking capability and price considering the tracking cost and recall cost in a supply chain with endogenous pricing. Results show that, in both centralised and decentralised supply chains, there is a unique tracking capability and retailing/wholesale price with closed-form solutions to optimise the supply chain profit. When the cost ratio (unit tracking cost/unit recall cost) is sufficiently large and small, the optimal tracking strategy is barcode tracking and unit tracking, respectively, and otherwise, the optimal tracking strategy is batch tracking with an economic traceable unit size which depends on the cost ratio, quality inspection threshold, supply defection rate and the supplier’s tracking capability. Furthermore, in the context of large and small cost ratio, we find that improving tracking capability will enlarge and mitigate the effect of double marginalisation, respectively. In particular, we find that the strict tracking regulation policy is more robust than the subsidy policy to improve the supply chain tracking capability.
Journal: International Journal of Production Research
Pages: 5465-5484
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1321800
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1321800
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Template-Type: ReDIF-Article 1.0
Author-Name: Mengdi Zhang
Author-X-Name-First: Mengdi
Author-X-Name-Last: Zhang
Author-Name: Saurabh Pratap
Author-X-Name-First: Saurabh
Author-X-Name-Last: Pratap
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Author-Name: Zhiheng Zhao
Author-X-Name-First: Zhiheng
Author-X-Name-Last: Zhao
Title: Optimal collaborative transportation service trading in B2B e-commerce logistics
Abstract: 
 This paper investigates a less-than-truckload carrier collaboration decision-making problem in the e-commerce logistics network. E-commerce less-than-truckload carrier collaboration problem considers multiple logistics service providers (LSPs) forming a collaborative alliance in an e-commerce logistics network. They share their transportation requests and vehicle capabilities to maximise the total profit of the entire alliance, improve their vehicle utilisation and cope with fluctuations in demand. An e-commerce logistics trading system with collaborative decisions is designed. A collaborative transportation planning model is introduced to maximise the total profit without reducing the individual profit of the carriers with information sharing. A stochastic plant-pollinator algorithm is proposed for the problem and extensive computational experiments are conducted. The results show that the proposed plant-pollinated algorithm performs better than the genetic algorithm. Furthermore, the results illustrate that the higher degree of cooperation, the more benefits for carriers. Last but not least, since the increasing gasoline price leads to the decreasing margins for the small- and medium-sized LSPs. The results also show that it is critical for them to join in the alliance to survive in the competition.
Journal: International Journal of Production Research
Pages: 5485-5501
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1322731
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1322731
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Template-Type: ReDIF-Article 1.0
Author-Name: Birendra K. Mishra
Author-X-Name-First: Birendra K.
Author-X-Name-Last: Mishra
Author-Name: Ashutosh Prasad
Author-X-Name-First: Ashutosh
Author-X-Name-Last: Prasad
Author-Name: Dhinu Srinivasan
Author-X-Name-First: Dhinu
Author-X-Name-Last: Srinivasan
Author-Name: Mohsen ElHafsi
Author-X-Name-First: Mohsen
Author-X-Name-Last: ElHafsi
Title: Pricing and capacity planning for product-line expansion and reduction
Abstract: 
 We investigate optimal pricing and capacity planning decisions for product-line settings such as introducing a new product or dropping an existing one. We consider a two-product, two-period model with stochastic demands, where price and capacity decisions are made at the outset. Investment in capacity must be traded-off against the possibility of buying at higher spot market prices due to shortage in capacity or charging a higher price to manage the demand. Prior studies argue that introducing an additional product to the product-line strains capacity, resulting in an increase in the price of an existing product. In contrast, we find that introducing a new product can also result in a drop in price of an existing product, enabling strategic pricing by firms. The necessary condition for this to occur is that the demand uncertainties for the products are of similar magnitude and negatively correlated. Similar insights are obtained for the setting where an existing product is dropped from the product-line. Hence, product-market decisions and contextual factors play a role in capacity planning, capacity cost allocation and pricing.
Journal: International Journal of Production Research
Pages: 5502-5519
Issue: 18
Volume: 55
Year: 2017
Month: 9
X-DOI: 10.1080/00207543.2017.1323132
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1323132
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Template-Type: ReDIF-Article 1.0
Author-Name: Ehsan Mardan
Author-X-Name-First: Ehsan
Author-X-Name-Last: Mardan
Author-Name: Mohsen Sadegh Amalnik
Author-X-Name-First: Mohsen Sadegh
Author-X-Name-Last: Amalnik
Author-Name: Masoud Rabbani
Author-X-Name-First: Masoud
Author-X-Name-Last: Rabbani
Title: An integrated emergency ordering and production planning optimization model with demand and yield uncertainty
Abstract: 
 This paper proposes an integrated emergency ordering and production planning scheme for a multi-item, multi-product problem in which each product is composed of several ingredients. Each item can be supplied from both cheap unreliable suppliers prone to yield uncertainty and expensive reliable suppliers. A two-stage decision-making process is proposed in which orders are placed to the unreliable suppliers during the first stage and an emergency order can be placed in the second stage. In addition, a flexible backup ordering contract between the buyer and emergency supplier is proposed. A similar two-stage decision-making process is considered for production planning, where in the first stage, the main production plan is determined and in the second stage, the decision about a limited increase in the production plan is made as an emergency decision. An integrated ordering and production planning decision process is proposed for the problem. The value of emergency decisions, including the value of emergency ordering and the value of emergency production planning evaluates the effectiveness of the emergency decisions. Due to the staggering size of the problem, sample average approximation method is used to solve the problem.
Journal: International Journal of Production Research
Pages: 6023-6039
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1008109
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1008109
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Template-Type: ReDIF-Article 1.0
Author-Name: M.A.F. Belo-Filho
Author-X-Name-First: M.A.F.
Author-X-Name-Last: Belo-Filho
Author-Name: P. Amorim
Author-X-Name-First: P.
Author-X-Name-Last: Amorim
Author-Name: B. Almada-Lobo
Author-X-Name-First: B.
Author-X-Name-Last: Almada-Lobo
Title: An adaptive large neighbourhood search for the operational integrated production and distribution problem of perishable products
Abstract: 
 Production and distribution problems with perishable goods are common in many industries. For the sake of the competitiveness of the companies, the supply chain planning of products with restricted lifespan should be addressed with an integrated approach. Particularly, at the operational level, the sizing and scheduling of production lots have to be decided together with vehicle routing decisions to satisfy the customers. However, such joint decisions make the problems hard to solve for industries with a large product portfolio. This paper proposes an adaptive large neighbourhood search (ALNS) framework to tackle the problem. This metaheuristic is well known to be effective for vehicle routing problems. The proposed approach relies on mixed-integer linear programming models and tools. The ALNS outperforms traditional procedures of the literature, namely, exact methods and fix-and-optimize, in terms of quality of the solution and computational time of the algorithms. Nine in ten runs of ALNS yielded better solutions than traditional procedures, outperforming on average 12.7% over the best solutions provided by the latter methods.
Journal: International Journal of Production Research
Pages: 6040-6058
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1010744
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1010744
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Template-Type: ReDIF-Article 1.0
Author-Name: Chunxia Yu
Author-X-Name-First: Chunxia
Author-X-Name-Last: Yu
Author-Name: T.N. Wong
Author-X-Name-First: T.N.
Author-X-Name-Last: Wong
Title: A multi-agent architecture for multi-product supplier selection in consideration of the synergy between products
Abstract: 
 Supplier selection is an important task in purchasing. The performance of a supply chain depends on the selection of the right suppliers to provide the right materials or services at the right price and right time. Most of the research on supplier evaluation and selection assumes that products are procured independently. However, in reality, it is common for a purchasing company to procure a bundle of products together. In this regard, synergy could exist between products and hence affect the final choice of suppliers. It is therefore necessary for the purchasing company to incorporate the synergy between products in supplier selection. This paper presents a multi-agent system (MAS) architecture for multi-product supplier selection in consideration of the synergy between products. A three-phase supplier selection model is proposed to support multi-product procurement in consideration of the synergy between products. The three phases are, namely, product synergy determination phase, supplier pre-selection phase and negotiation-based final selection phase. The MAS is equipped with various types of autonomous function agents and different agent interaction protocols to effect the functioning of this three-phase multi-product supplier selection model.
Journal: International Journal of Production Research
Pages: 6059-6082
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1010745
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1010745
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Template-Type: ReDIF-Article 1.0
Author-Name: Robert K. Hague
Author-X-Name-First: Robert K.
Author-X-Name-Last: Hague
Author-Name: Kash Barker
Author-X-Name-First: Kash
Author-X-Name-Last: Barker
Author-Name: Jose E. Ramirez-Marquez
Author-X-Name-First: Jose E.
Author-X-Name-Last: Ramirez-Marquez
Title: Interval-valued availability framework for supplier selection based on component importance
Abstract: 
 The availability of ageing systems, particularly weapon systems within the Department of Defense, is of significant concern, as budgets tighten and system replacement is infeasible. This work addresses the selection of sole suppliers according to their ability to provide component parts that strengthen availability of the system. We extend a popular multi-criteria decision-making approach, Technique for Order Preferences by Similarity to an Ideal Solution, by (i) considering the availability of individual components as the criteria in the decision problem and (ii) weighting those criteria according to the value of component importance measures while (iii) accounting for uncertainty in underlying reliability and maintainability parameters with interval numbers. An aircraft example illustrates the approach.
Journal: International Journal of Production Research
Pages: 6083-6096
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1018454
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1018454
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Template-Type: ReDIF-Article 1.0
Author-Name: Adile Yesim Yayla
Author-X-Name-First: Adile Yesim
Author-X-Name-Last: Yayla
Author-Name: Asil Oztekin
Author-X-Name-First: Asil
Author-X-Name-Last: Oztekin
Author-Name: Alev Taskin Gumus
Author-X-Name-First: Alev Taskin
Author-X-Name-Last: Gumus
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Title: A hybrid data analytic methodology for 3PL transportation provider evaluation using fuzzy multi-criteria decision making
Abstract: 
 Third-party logistics (3PL) service provider selection for a strategic alliance is not an easy decision, and is constantly associated with uncertainty and complexity. For this reason, in this study, a hybrid fuzzy multi-criteria decision-making methodology is proposed to provide a systematic decision support tool for 3PL provider evaluation, especially for 3PL transportation provider. The proposed evaluation methodology consists of several steps. First, the strategic goal and sub-attributes are identified for 3PL service provider evaluation. After constructing the hierarchy, Buckley’s fuzzy-analytical hierarchy process (AHP) extension algorithm is used to determine the evaluation criteria weights. Then, by using fuzzy-AHP results as input weights, the fuzzy-Technique for Order Preference by Similarity to Ideal Solution technique is conducted in order to identify the most suitable third-party providers. Finally, a real-life case study in a confectionary company is presented to demonstrate the potential use of the methodology and a sensitivity analysis is performed to analyse the hybrid methodology proposed here. In the conclusion of the study, future recommendations are presented.
Journal: International Journal of Production Research
Pages: 6097-6113
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1022266
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1022266
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Template-Type: ReDIF-Article 1.0
Author-Name: Bimal Nepal
Author-X-Name-First: Bimal
Author-X-Name-Last: Nepal
Author-Name: Om Prakash Yadav
Author-X-Name-First: Om Prakash
Author-X-Name-Last: Yadav
Title: Bayesian belief network-based framework for sourcing risk analysis during supplier selection
Abstract: 
 Increasing trend in global business integration and movement of material around the world has caused supply chain system susceptible to disruption involving higher risks. This paper presents a methodology for supplier selection in a global sourcing environment by considering multiple cost and risk factors. Failure modes and effects analysis technique from reliability engineering field and Bayesian belief networks are used to quantify the risk posed by each factor. The probability and the cost of each risk are then incorporated into a decision tree model to compute the total expected costs for each supply option. The supplier selection decision is made based on the total purchasing costs including both deterministic costs (such as product and transportation costs) and the risk-associated costs. The proposed approach is demonstrated using an example of a US-based Chemical distributor. This framework provides a visual tool for supply chain managers to see how cost and risks are distributed across the different alternatives. Lastly, managers can calculate expected value of perfect information to avoid a certain risk.
Journal: International Journal of Production Research
Pages: 6114-6135
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1027011
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1027011
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Template-Type: ReDIF-Article 1.0
Author-Name: Shudong Liu
Author-X-Name-First: Shudong
Author-X-Name-Last: Liu
Author-Name: Changyong Zhang
Author-X-Name-First: Changyong
Author-X-Name-Last: Zhang
Title: An efficient inventory rationing strategy for systems with two demand classes and backordering
Abstract: 
 For systems with two customer classes and backordering, the formulae for the optimal dynamic critical levels in the literature are too complex to be extended to large values of critical levels. In this paper, an efficient method is introduced to obtain approximate closed-form expressions for the dynamic critical levels, even for large values. It is further verified by numerical results the accuracy of the approximate expressions, from which important managerial insights can be obtained.
Journal: International Journal of Production Research
Pages: 6136-6142
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1027013
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1027013
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Template-Type: ReDIF-Article 1.0
Author-Name: Fang Yu
Author-X-Name-First: Fang
Author-X-Name-Last: Yu
Author-Name: Toshiya Kaihara
Author-X-Name-First: Toshiya
Author-X-Name-Last: Kaihara
Author-Name: Nobutada Fujii
Author-X-Name-First: Nobutada
Author-X-Name-Last: Fujii
Author-Name: Changyin Sun
Author-X-Name-First: Changyin
Author-X-Name-Last: Sun
Author-Name: Wankou Yang
Author-X-Name-First: Wankou
Author-X-Name-Last: Yang
Title: A multi-attribute multi-item negotiation mechanism of supply chain networks between buyers and sellers
Abstract: 
 This article focuses on the multi-attribute multi-item negotiation between multiple manufacturer agents (MAs) and multiple material supplier agents (MSAs). A coalition formation-based negotiation protocol is proposed. The MSAs are allowed to establish coalitions when the orders of the MAs exceed their abilities. Three attributes (price, quantity and lead time) of the items are considered during the negotiation. Both the MAs and the MSAs can give concessions among the attributes in tradeoff relationships according to their own preferences. The non-cooperative game is introduced to find the equilibria of the negotiations. The final allocation scheme is determined to maximise the total profit of the supply chain networks based on the equilibria. Simulations are provided to verify the effectiveness and feasibility of the proposed protocol.
Journal: International Journal of Production Research
Pages: 6143-6160
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1034328
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1034328
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Template-Type: ReDIF-Article 1.0
Author-Name: Guangzhi Shang
Author-X-Name-First: Guangzhi
Author-X-Name-Last: Shang
Author-Name: Brooke Saladin
Author-X-Name-First: Brooke
Author-X-Name-Last: Saladin
Author-Name: Tim Fry
Author-X-Name-First: Tim
Author-X-Name-Last: Fry
Author-Name: Joan Donohue
Author-X-Name-First: Joan
Author-X-Name-Last: Donohue
Title: Twenty-six years of operations management research (1985–2010): authorship patterns and research constituents in eleven top rated journals
Abstract: 
 This paper investigates the research contributions over a 26-year time frame (1985–2010) of academic institutions and individual authors to the field of operations management (OM). We use two measures, shared articles and distributed articles, to assess the research productivity of institutions as well as individual researchers. Further we assess the contribution of institutions based on affiliated author research as well as the research of their PhD graduates. In order to accomplish this, we utilise the published OM research articles in 11 top-rated and well-known academic journals over the time period from 1985 to 2010. In addition to the research, contributions of academic institutions and individual authors, we look at several bibliometric statistics related to this body of published research. These measures indicate that the research constituency is growing as evidenced by increasing numbers of researchers and institutions represented. Lastly, the collaboration between researchers appears to be increasing as evidenced by an increasing percentage of articles with three or more authors and the average number of authors per article published.
Journal: International Journal of Production Research
Pages: 6161-6197
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1037935
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1037935
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Template-Type: ReDIF-Article 1.0
Author-Name: Dario Antonelli
Author-X-Name-First: Dario
Author-X-Name-Last: Antonelli
Author-Name: Giulia Bruno
Author-X-Name-First: Giulia
Author-X-Name-Last: Bruno
Author-Name: Teresa Taurino
Author-X-Name-First: Teresa
Author-X-Name-Last: Taurino
Author-Name: Agostino Villa
Author-X-Name-First: Agostino
Author-X-Name-Last: Villa
Title: Graph-based models to classify effective collaboration in SME networks
Abstract: 
 During the last decades, globalisation of goods’ markets and large disequilibrium amongst labour markets in different countries had a remarkable impact on small and medium enterprises – SMEs, which have been for many years the actual engine of industrial development in Europe. An ‘antidote’ to this crisis is the development of more profitable SME networks in the forms of either ‘clusters’, ‘competitiveness poles’, ‘industrial districts’ or ‘scientific parks’. A more strategic approach is needed, that builds upon existing SME aggregations and explores their main strong and weak points, such as to establish a framework for new innovative networks. The goal of this study is to offer a method to analyse the main features of existing SME networks, in order to offer to the network coordination/management committees some key parameters (KP) to evaluate the network composition and potentially to select networks modifications. The study analyses an archive of industrial networks provided by the European project CODESNET and defines different types of networks and their main KP. A further result of the analysis will be the modelling of each network type in terms of a specific graph. Graphs give a more intuitive representation of the network and an easier comprehension of its organisation. In a second stage, by a probabilistic approach, the authors propose an identification procedure to classify existing and new networks.
Journal: International Journal of Production Research
Pages: 6198-6209
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1038368
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1038368
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhixiang Chen
Author-X-Name-First: Zhixiang
Author-X-Name-Last: Chen
Author-Name: Bhaba R. Sarker
Author-X-Name-First: Bhaba R.
Author-X-Name-Last: Sarker
Title: Optimisation of multi-stage JIT production-pricing decision: centralised and decentralised models and algorithms
Abstract: 
 This research studies the optimal decision for product pricing, production lot sizing in a multi-stage serial just-in-time production system with kanban-controlled policy. A decentralised decision model and a centralised decision model of this problem are formulated as a mixed-integer nonlinear programming problem. In order to solve the models, three algorithms are developed. The first one is an approximate procedure which solves the decentralised decision model; the second one is a proximate optimal procedure using two-phase search technique that solves the centralised decision model, and the third one is an approximate method using meta-heuristic technique which is used for both decentralised and centralised models. Numerical example shows that centralised decision can obtain higher economic benefit with lower cost and higher revenue and profit. Meanwhile, when demand is more price sensitive, centralised decision can achieve significant profit enhancement. Computational results attribute to different characteristics of the problem and solution superiority.
Journal: International Journal of Production Research
Pages: 6210-6230
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1038369
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1038369
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Template-Type: ReDIF-Article 1.0
Author-Name: Junguang Zhang
Author-X-Name-First: Junguang
Author-X-Name-Last: Zhang
Author-Name: Xiwei Song
Author-X-Name-First: Xiwei
Author-X-Name-Last: Song
Author-Name: Hongyu Chen
Author-X-Name-First: Hongyu
Author-X-Name-Last: Chen
Author-Name: Ruixia (Sandy) Shi
Author-X-Name-First: Ruixia
Author-X-Name-Last: (Sandy) Shi
Title: Optimisation of critical chain sequencing based on activities’ information flow interactions
Abstract: 
 One critique for the classic critical chain sequencing methods is that only resource constraints and logical relationships between activities are considered, while interactions of information flows are ignored. However, information flow interactions exist between almost all project activities and bring about big rework risk and rework costs in project management, especially for the long-term projects tied up with big amount of money. In this paper, we propose a new approach to sequence a project’s critical chain by considering activities’ information flow. Specifically, we use the design structure matrix to measure directions and intensities of information flows between activities. The criterion for critical chain sequencing is then to minimise the total coordination cost while considering the influence of feedbacks. The simulation results show that, as opposed to the traditional critical chain sequencing methods, our approach shortens average rework time and reduces the cost.
Journal: International Journal of Production Research
Pages: 6231-6241
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1043157
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1043157
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Template-Type: ReDIF-Article 1.0
Author-Name: Birte Schaltenbrand
Author-X-Name-First: Birte
Author-X-Name-Last: Schaltenbrand
Author-Name: Kai Foerstl
Author-X-Name-First: Kai
Author-X-Name-Last: Foerstl
Author-Name: Andrew P. Kach
Author-X-Name-First: Andrew P.
Author-X-Name-Last: Kach
Author-Name: Marco J. Maier
Author-X-Name-First: Marco J.
Author-X-Name-Last: Maier
Title: Towards a deeper understanding of managerial green investment patterns – a USA–Germany comparison
Abstract: 
 Green investments are crucial mechanisms for translating green operation strategies into managerial action. We examine the impact of external pressures on green investment patterns in terms of their scope, type and time horizon across 251 German and US managers. A scenario-based experiment was conducted using a 2 × 2 × 2 factorial design in which managers were assigned to high and low consumer, community, and resource treatment groups before being asked to make green investment decisions. Our hypotheses are developed based on resource advantage theory and tested in a number of regression models. The results demonstrate that German and US managers respond differently to external pressures in their green investment decisions. Regarding the scope of green investments, German and US managers invest differently if end consumer pressure increases and partially differently if resource scarcity increases, but they act in a similar way if community pressure increases. Moreover, we detected specific variations in the type and time horizon of green investments across US and German managers. The theoretical and practical implications of these findings for green operations management research and for firms operating in multinational settings are explained.
Journal: International Journal of Production Research
Pages: 6242-6262
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1047979
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047979
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Template-Type: ReDIF-Article 1.0
Author-Name: Anand Nair
Author-X-Name-First: Anand
Author-X-Name-Last: Nair
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Author-Name: Ajay Das
Author-X-Name-First: Ajay
Author-X-Name-Last: Das
Title: Strategic purchasing participation, supplier selection, supplier evaluation and purchasing performance
Abstract: 
 In this article, we examine how purchasing’s strategic participation influences supply management activities via the choice of appropriate operational and strategic criteria. Specifically, the study focuses on supplier selection and monitoring ongoing supplier performance evaluation based on operational and strategic criteria. A combination of choosing appropriate supplier selection criteria and monitoring supplier performance ensures that the benefits of purchasing’s participation in strategic planning translate into better purchasing performance of cost, quality, delivery, flexibility and innovation. We test the hypotheses using survey data collected from manufacturing companies in the US by means of a path model. Our results provide support for the tenet that purchasing’s participation in strategic planning influences purchasing performance directly as well as through the mediating effects of supplier selection criteria and supplier performance evaluation. We discuss the theoretical and managerial implications of the findings and propose directions for further research.
Journal: International Journal of Production Research
Pages: 6263-6278
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1047983
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047983
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Template-Type: ReDIF-Article 1.0
Author-Name: Chong Wang
Author-X-Name-First: Chong
Author-X-Name-Last: Wang
Author-Name: Xu Chen
Author-X-Name-First: Xu
Author-X-Name-Last: Chen
Title: Optimal ordering policy for a price-setting newsvendor with option contracts under demand uncertainty
Abstract: 
 In this article, we investigate the newsvendor problem in a joint ordering and pricing setting in the presence of option contracts under demand uncertainty. At the beginning of a single selling season, the newsvendor who faces additive stochastic demand can obtain goods through two ways: ordering from a firm or purchasing and exercising call options. Single ordering (ordering from a firm only or purchasing and exercising call options only) and mixed ordering (ordering from a firm and purchasing and exercising call options simultaneously) cases are investigated. We find that the newsvendor’s optimal pricing and ordering strategies exist and are unique for both cases, respectively. In addition, when both cases are available, mixed ordering is the newsvendor’s optimal ordering policy. If only single ordering is available, the newsvendor prefers ordering from a firm when demand risk is low, while enjoys purchasing and exercising call options when demand risk is high. We also find that with option contracts, the newsvendor’s optimal order quantity and maximum expected profit are all decreasing in the option price and exercise price of product, while the optimal retail price in terms of option price and exercise price of product are intricate. Moreover, we show that, mixed ordering is more capable to deal with supply price volatility risk.
Journal: International Journal of Production Research
Pages: 6279-6293
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1053577
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1053577
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhiqiang Wang
Author-X-Name-First: Zhiqiang
Author-X-Name-Last: Wang
Author-Name: Baofeng Huo
Author-X-Name-First: Baofeng
Author-X-Name-Last: Huo
Author-Name: Yu Tian
Author-X-Name-First: Yu
Author-X-Name-Last: Tian
Author-Name: Zhongsheng Hua
Author-X-Name-First: Zhongsheng
Author-X-Name-Last: Hua
Title: Effects of external uncertainties and power on opportunism in supply chains: evidence from China
Abstract: 
 This study examines the determinants of opportunism in supply chain relationships in emerging markets. Drawing on transaction cost theory and resource dependence theory, we propose that external uncertainties (environmental uncertainty and legal unprotectability) influence opportunism through power (coercive and non-coercive). The results, based on 240 companies in China, indicate that environmental uncertainty enhances supplier opportunism directly and indirectly through the buyer’s use of coercive power over the supplier, while legal unprotectability enhances supplier opportunism directly, but reduces it indirectly through the buyer’s use of non-coercive power. While buyer coercive power increases supplier opportunism, buyer non-coercive power decreases it.
Journal: International Journal of Production Research
Pages: 6294-6307
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1053578
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1053578
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Template-Type: ReDIF-Article 1.0
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Author-Name: Zih-Huei Wang
Author-X-Name-First: Zih-Huei
Author-X-Name-Last: Wang
Author-Name: Ming-Hung Shu
Author-X-Name-First: Ming-Hung
Author-X-Name-Last: Shu
Title: A lots-dependent variables sampling plan considering supplier’s process loss and buyer’s stipulated specifications requirement
Abstract: 
 A well-established scheme and mechanism for deciding product acceptance is perceived as a win-win situation for the long-term supplier–buyer relationship. In this paper, we develop a lots-dependent variables sampling scheme for product acceptance determination. The dependent state is based on the sample information of the process capability index that incorporates the supplier’s process loss and the buyer’s demanded specifications requirement. This main scheme is implemented by a three-rule process that accepts or rejects a related lot conditional on the sample results of past lots. The plan-operational parameters satisfying the desired quality levels and constraining the supplier–buyer risks are determined by a non-linear optimisation model. In performance comparisons, our proposed plan demonstrated higher cost effectiveness and discriminatory power than the traditional variables single sampling plan. Finally, industrial applicability of our recommended sampling plans was investigated in a case study.
Journal: International Journal of Production Research
Pages: 6308-6319
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1053580
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1053580
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Template-Type: ReDIF-Article 1.0
Author-Name: Kamran S. Moghaddam
Author-X-Name-First: Kamran S.
Author-X-Name-Last: Moghaddam
Title: Supplier selection and order allocation in closed-loop supply chain systems using hybrid Monte Carlo simulation and goal programming
Abstract: 
 Supplier selection is an important strategic design decision in closed-loop supply chain systems. In addition, and after identifying the candidate suppliers, optimal order allocations are also considered as crucial tactical decisions. This research presents a multi-objective optimisation model to select the best suppliers and configure manufacturing and refurbishing facilities with the optimal number of parts and products in a closed-loop supply chain network. The objective functions in this research are formulated as total profit, total defective parts, total late delivered parts and economic risk factors of the candidate suppliers. The proposed multi-objective model is solved by hybrid Monte Carlo simulation integrated with three different variants of goal programming method. The effectiveness of the mathematical model and the proposed solution algorithms in obtaining Pareto-optimal solutions is demonstrated in a numerical example adopted from a real case study.
Journal: International Journal of Production Research
Pages: 6320-6338
Issue: 20
Volume: 53
Year: 2015
Month: 10
X-DOI: 10.1080/00207543.2015.1054452
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1054452
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Template-Type: ReDIF-Article 1.0
Author-Name: Kartick Dey
Author-X-Name-First: Kartick
Author-X-Name-Last: Dey
Author-Name: Sankhadip Roy
Author-X-Name-First: Sankhadip
Author-X-Name-Last: Roy
Author-Name: Subrata Saha
Author-X-Name-First: Subrata
Author-X-Name-Last: Saha
Title: The impact of strategic inventory and procurement strategies on green product design in a two-period supply chain
Abstract: 
 This study analyses the impact of power structures and strategic inventory on the development-intensive and marginal-cost-intensive green product types under three procurement strategies. The results suggest that (i) in the manufacturer-Stackelberg game, the retailer retains strategic inventory to earn higher profits. The retailer's decision improves profit for the manufacturer and greening level of the product; (ii) for the marginal-cost-intensive green product, the power structures and procurement strategies cannot make any impact on the greening level and the retailer cannot build up strategic inventory under retailer-Stackelberg game; (iii) under the Nash game, the procurement decision creates conflict between the supply chain members for marginal-cost-intensive green products; (iv) if the retailer does not maintain strategic inventory or procures product in a single lot, then the manufacturer prefers to produce marginal-cost-intensive products and retailer prefers to sale development-intensive products to receive maximum profits under manufacturer-Stackelberg game. The optimal preferences are concurrent under retailer-Stackelberg game, but not under the Nash game; (v) single-period equilibrium solutions may exhibit sub-optimal characteristics, but two-period planning can lead to exemplary outcomes in the perspective of the greening level and profits of the supply chain members.
Journal: International Journal of Production Research
Pages: 1915-1948
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1511071
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1511071
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Template-Type: ReDIF-Article 1.0
Author-Name: Yue Zhai
Author-X-Name-First: Yue
Author-X-Name-Last: Zhai
Author-Name: Yelin Fu
Author-X-Name-First: Yelin
Author-X-Name-Last: Fu
Author-Name: Gangyan Xu
Author-X-Name-First: Gangyan
Author-X-Name-Last: Xu
Author-Name: George Huang
Author-X-Name-First: George
Author-X-Name-Last: Huang
Title: Multi-period hedging and coordination in a prefabricated construction supply chain
Abstract: 
 In this paper, a multi-period buffer space hedging coordination between a building contractor (BC) and a logistics provider (LP) is investigated. In order to facilitate the application of the construction lead-time hedging (CLTH) strategy, adopted by the BC, extra buffer space needs to be reserved at LP’s intermediate warehouse for contingency usage. This strategy is defined as ‘buffer space hedging (BSH)’ and it increases the pressure of LP on involving extra storage and maintenance cost. Two coordination mechanisms are adopted for solving this BSH problem. One scheme is by introducing a cost-sharing term. A Nash game model is studied to find the individual optimal decisions. Another scheme is a cooperative game model with proper side-payments. We show that adjusting the BSH amount for each review period benefits the supply chain. Both coordination mechanisms enable a win–win outcome. Especially, if system resources are sufficient, the cooperative game outperforms the Nash game. Numerical experiments further demonstrate that the benefit of the proposed model is more significant under the case with lower unit enlarging/rearrangement cost, higher tardiness penalty and unpredictable and uncontrollable construction process-determined assembled and installed prefabs.
Journal: International Journal of Production Research
Pages: 1949-1971
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1512765
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1512765
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Template-Type: ReDIF-Article 1.0
Author-Name: Jie Wei
Author-X-Name-First: Jie
Author-X-Name-Last: Wei
Author-Name: Jing Zhao
Author-X-Name-First: Jing
Author-X-Name-Last: Zhao
Author-Name: Xiaorui Hou
Author-X-Name-First: Xiaorui
Author-X-Name-Last: Hou
Title: Integration strategies of two supply chains with complementary products
Abstract: 
 This paper studies the manufacturer's and retailer's integration strategies in a supply chain with complementary products and examines the effects of downstream, upstream and vertical integrations on supply chain members' decisions and profits and on supply chain performance. The centralised and decentralised decision models are considered as benchmarks that are compared to downstream, upstream and vertically integrated strategies. Our comparison and analysis show that the total profit of the supply chain increases with the number of integrated players and that vertical integration can be more profitable than that of upstream and downstream integrations. However, to our surprise, the upstream and downstream integration strategies do not affect the total profit.
Journal: International Journal of Production Research
Pages: 1972-1989
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1516305
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1516305
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Template-Type: ReDIF-Article 1.0
Author-Name: Simonov Kusi-Sarpong
Author-X-Name-First: Simonov
Author-X-Name-Last: Kusi-Sarpong
Author-Name: Himanshu Gupta
Author-X-Name-First: Himanshu
Author-X-Name-Last: Gupta
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: A supply chain sustainability innovation framework and evaluation methodology
Abstract: 
 Sustainability is hinged on innovation. The importance of sustainable innovation management in sustainable supply chain management (SSCM) cannot be underestimated. Studies on SSCM have emphasised the need for sustainable innovation in achieving sustainability but none provide deep insights into sustainable innovation management in SSCM implementation. This lack of research depth stimulates this study to identify and investigate criteria for sustainable supply chain management innovation advancement. This paper proposes a sustainable innovation criteria framework for investigating sustainable supply chains in manufacturing companies. To exemplify the applicability and efficiency of the proposed framework, a sample of five Indian manufacturing companies are used to evaluate and prioritise the sustainable innovation management criteria, using the ‘best–worst’ multi-criteria decision-making (BW-MCDM) model. The criteria weights for all companies from BWM are aggregated, averaged and used for ranking. The respondent managers viewed ‘financial availability for innovation’ as the most important sustainable innovation sub-criteria. The results of the study will inform industrial managers, practitioners and decision-makers on which criteria to focus on during the implementation stage, to increase sustainability in manufacturing supply chains, and further advance corporate and supply chain sustainable development. The framework may also serve as a theoretical construct for a future empirical study on sustainable supply chain innovation in the manufacturing sector. This paper sets the stage for further research in sustainable innovation practices in the manufacturing sector and its supply chains.
Journal: International Journal of Production Research
Pages: 1990-2008
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1518607
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518607
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Template-Type: ReDIF-Article 1.0
Author-Name: Sachin Kamble
Author-X-Name-First: Sachin
Author-X-Name-Last: Kamble
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Himanshu Arha
Author-X-Name-First: Himanshu
Author-X-Name-Last: Arha
Title: Understanding the Blockchain technology adoption in supply chains-Indian context
Abstract: 
 Blockchain technology (BT) is expected to bring a revolutionary paradigm shift in the manner the transactions are carried in the supply chains. BT provides better visibility and transparency by removing the disadvantages of trust related issues in a supply chain. In this paper, we advance the literature on BT and its adoption in the supply chain by developing, and statistically validating a model for understanding the user perceptions on BT adoption. The model is based on the integration of three adoption theories- technology acceptance model (TAM), technology readiness index (TRI) and the theory of planned behaviour (TPB). Based on a survey of 181 supply chain practitioners in India the proposed model was tested using structural equation modelling. The study found that the TRI constructs- Insecurity and discomfort have an insignificant effect on the perceived ease of use and usefulness. Perceived usefulness, attitude, and perceived behavioural control affect the behavioural intention. Subjective norm has a negligible impact on behavioural intention. This is one of the preliminary studies on BT adoption in supply chain and the findings imply that the supply chain practitioners perceive BT adoption free of efforts and would help them to derive maximum benefits for improving the supply chain effectiveness.
Journal: International Journal of Production Research
Pages: 2009-2033
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1518610
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518610
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Template-Type: ReDIF-Article 1.0
Author-Name: Pamela Danese
Author-X-Name-First: Pamela
Author-X-Name-Last: Danese
Author-Name: Andrea Lion
Author-X-Name-First: Andrea
Author-X-Name-Last: Lion
Author-Name: Andrea Vinelli
Author-X-Name-First: Andrea
Author-X-Name-Last: Vinelli
Title: Drivers and enablers of supplier sustainability practices: a survey-based analysis
Abstract: 
 A rich research stream investigates the drivers and enablers of supplier sustainability practices, usually classified into suppliers’ monitoring and collaboration with suppliers. Differently from previous works analysing relationships between supplier sustainability practices and drivers or enablers, this research investigates how well-defined configurations of monitoring and collaboration can be characterised in terms of drivers and enablers. In this way, it intends to advance knowledge by identifying what drivers and enablers are important and distinctive for the different configurations of supplier sustainability practices. A first result is that moving from configurations of plants which less adopt supplier sustainability practices (i.e. non-adopters) to those which invest on monitoring and/or collaboration to a limited extent (i.e. partial adopters) up to the most advanced ones (i.e. full-adopters), the pressure due to cost reduction lessens its relative importance as a driver, while the pressure due to regulations remains essential. Other relevant results are that plant size acts as a barrier for non-adopters, and the alignment between the sustainability project and plant goals results determinant especially for full-adopters. This research also enriches the debate on the opportunity of differentiating between supplier monitoring and collaboration when investigating drivers/enablers, providing evidence of the risk of oversimplifications for some enablers/drivers.
Journal: International Journal of Production Research
Pages: 2034-2056
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1519265
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1519265
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Template-Type: ReDIF-Article 1.0
Author-Name: Feng Yang
Author-X-Name-First: Feng
Author-X-Name-Last: Yang
Author-Name: Chuanya Jiao
Author-X-Name-First: Chuanya
Author-X-Name-Last: Jiao
Author-Name: Sheng Ang
Author-X-Name-First: Sheng
Author-X-Name-Last: Ang
Title: The optimal technology licensing strategy under supply disruption
Abstract: 
 We study the problem of whether and how a patent-holding firm (supplier S1) should license its technology patent to a potential rival (supplier S2). If the license is given, the two suppliers both produce a critical component for their downstream manufacturer simultaneously (sequentially) when the manufacturer adopts a dual (contingent) sourcing mode. However, both suppliers face risks of complete supply disruptions. In the study, we examine how the supply risk affects S1's technology licensing willingness and under which conditions royalty or fixed-fee licensing is its optimal strategy. The results show that when the manufacturer adopts contingent sourcing, S1 is always willing to license its technology to S2 and fixed-fee licensing is the optimal strategy. However, when dual sourcing is adopted, either royalty and fixed-fee licensing could be S1's optimal licensing strategy, depending on the reliability degree of the suppliers’ productions. Our findings extend the conclusion from previous researchers about royalty and fixed-fee licensing in a Cournot duopoly model.
Journal: International Journal of Production Research
Pages: 2057-2082
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1521535
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521535
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Template-Type: ReDIF-Article 1.0
Author-Name: Juan Manuel Maqueira
Author-X-Name-First: Juan
Author-X-Name-Last: Manuel Maqueira
Author-Name: José Moyano-Fuentes
Author-X-Name-First: José
Author-X-Name-Last: Moyano-Fuentes
Author-Name: Sebastián Bruque
Author-X-Name-First: Sebastián
Author-X-Name-Last: Bruque
Title: Drivers and consequences of an innovative technology assimilation in the supply chain: cloud computing and supply chain integration
Abstract: 
 Cloud Computing are innovative technologies that are being applied in the main business functions in the supply chain. This study aims to reveal the determinant factors (drivers and a relevant outcome) of the level of use or assimilation of Cloud Computing in the supply chain. In order to test three hypotheses we conducted an empirical study in 484 companies from sectors in an intermediate position in the supply chain. The data gathering method consisted of a telephone survey using a computerised system (CATI). We used structural equation modelling (SEM) to test the hypotheses. The empirical study reveals that Advanced Manufacturing Technologies pursuing the internal efficiency of the supply chain (Intra-organisational IT) and IT for capabilities in e-business/e-commerce seeking external connection of the supply chain with other companies (Inter-organisational IT) are drivers of Cloud Computing assimilation. Furthermore, supply chain integration is one of the major consequences of Cloud Computing assimilation in the supply chain.
Journal: International Journal of Production Research
Pages: 2083-2103
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1530473
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530473
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Template-Type: ReDIF-Article 1.0
Author-Name: I. Ribas
Author-X-Name-First: I.
Author-X-Name-Last: Ribas
Author-Name: A. Lusa
Author-X-Name-First: A.
Author-X-Name-Last: Lusa
Author-Name: A. Corominas
Author-X-Name-First: A.
Author-X-Name-Last: Corominas
Title: A framework for designing a supply chain distribution network
Abstract: 
 Based on the analysis of the pertinent literature, we propose a framework to serve as a guide in designing a distribution network as a component of a supply chain (SC). It consists of three steps that are common to goods and services SCs: position of the decoupling point, structure of the network, and product delivery. For each step, we take into account the peculiarities of both goods and services separately in order to establish a list of available options and evaluate their suitability in relation to the relevant factors that characterise the products and the markets.
Journal: International Journal of Production Research
Pages: 2104-2116
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1530477
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530477
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Template-Type: ReDIF-Article 1.0
Author-Name: Sara Saberi
Author-X-Name-First: Sara
Author-X-Name-Last: Saberi
Author-Name: Mahtab Kouhizadeh
Author-X-Name-First: Mahtab
Author-X-Name-Last: Kouhizadeh
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Author-Name: Lejia Shen
Author-X-Name-First: Lejia
Author-X-Name-Last: Shen
Title: Blockchain technology and its relationships to sustainable supply chain management
Abstract: 
 Globalisation of supply chains makes their management and control more difficult. Blockchain technology, as a distributed digital ledger technology which ensures transparency, traceability, and security, is showing promise for easing some global supply chain management problems. In this paper, blockchain technology and smart contracts are critically examined with potential application to supply chain management. Local and global government, community, and consumer pressures to meet sustainability goals prompt us to further investigate how blockchain can address and aid supply chain sustainability. Part of this critical examination is how blockchains, a potentially disruptive technology that is early in its evolution, can overcome many potential barriers. Four blockchain technology adoption barriers categories are introduced; inter-organisational, intra-organisational, technical, and external barriers. True blockchain-led transformation of business and supply chain is still in progress and in its early stages; we propose future research propositions and directions that can provide insights into overcoming barriers and adoption of blockchain technology for supply chain management.
Journal: International Journal of Production Research
Pages: 2117-2135
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1533261
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1533261
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Template-Type: ReDIF-Article 1.0
Author-Name: María del Rosario Pérez-Salazar
Author-X-Name-First: María del Rosario
Author-X-Name-Last: Pérez-Salazar
Author-Name: Alberto A. Aguilar-Lasserre
Author-X-Name-First: Alberto A.
Author-X-Name-Last: Aguilar-Lasserre
Author-Name: Miguel Gastón Cedillo-Campos
Author-X-Name-First: Miguel Gastón
Author-X-Name-Last: Cedillo-Campos
Author-Name: Ulises Juárez-Martínez
Author-X-Name-First: Ulises
Author-X-Name-Last: Juárez-Martínez
Author-Name: Rubén Posada-Gómez
Author-X-Name-First: Rubén
Author-X-Name-Last: Posada-Gómez
Title: Processes and measurement of knowledge management in supply chains: an integrative systematic literature review
Abstract: 
 During the last 10 years, important contributions about knowledge management (KM) issues in supply chain management (SCM) have been published. The current paper aims to build upon previous literature reviews focused on KM in supply chains (SCs) from an integrative perspective, particularly recognising the studies conducted by Bhosale and Kant (2016. “Metadata Analysis of Knowledge Management in Supply Chain: Investigating the Past and Predicting the Future.” Business Process Management Journal 22 (1): 140–172) and Cerchione and Esposito (2016. “A Systematic Review of Supply Chain Knowledge Management Research: State of the Art and Research Opportunities.” International Journal of Production Economics 182: 276–292) as an effort to discuss the evolution of KM in the SC field. To this end, a systematic literature review including 210 papers is conducted over the period 2008–2017 from three positions previously not addressed jointly within the supply chain (SC) context: research methods employed by the authors; KM processes applied in the business processes across the SC; and intra and inter- organisational performance metrics linked with KM initiatives. Results exhibited that: (i) ‘Survey’ and ‘Case study’ are the two research methodologies mostly employed by authors (ii) the knowledge transfer is discussed in the majority of the studies reviewed, (iii) 114 intra and inter-organisational performance metrics are reported within the SC context from an empirical data approach. Findings concerning previous identified gap analysis and future lines of research are described.
Journal: International Journal of Production Research
Pages: 2136-2159
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1521530
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521530
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Template-Type: ReDIF-Article 1.0
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Author-Name: Nathalie Perrier
Author-X-Name-First: Nathalie
Author-X-Name-Last: Perrier
Title: A review of methods, techniques and tools for project planning and control
Abstract: 
 The purpose of this article is to provide a brief review of methods and techniques developed for the most commonly studied decision-making problems in project planning and control over the last decade. These problems involve project representation, project scheduling, resource allocation, risk analysis, time and cost performance evaluation, time, cost, and cash flow forecasting, optimal timing of control points, and corrective action decision-making. We also review recent tools developed for project planning and control. The emphasis is on recent contributions, but several older yet important works are also cited. Our analysis shows an increasing attention to the stochastic nature of projects in planning and control decision and processes. Recent attention has also been put at improvements in existing project control techniques as well as developing new methods to automate data collection, process, and generate more integrated project plan. More importantly, our review highlights an important shift in the project planning and control research field, which has been largely dominated by the project scheduling literature in the past, as short term and reactive decision-making bring new challenges and opportunities to project organisations and researchers.
Journal: International Journal of Production Research
Pages: 2160-2178
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1524168
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1524168
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Template-Type: ReDIF-Article 1.0
Author-Name: George Baryannis
Author-X-Name-First: George
Author-X-Name-Last: Baryannis
Author-Name: Sahar Validi
Author-X-Name-First: Sahar
Author-X-Name-Last: Validi
Author-Name: Samir Dani
Author-X-Name-First: Samir
Author-X-Name-Last: Dani
Author-Name: Grigoris Antoniou
Author-X-Name-First: Grigoris
Author-X-Name-Last: Antoniou
Title: Supply chain risk management and artificial intelligence: state of the art and future research directions
Abstract: 
 Supply chain risk management (SCRM) encompasses a wide variety of strategies aiming to identify, assess, mitigate and monitor unexpected events or conditions which might have an impact, mostly adverse, on any part of a supply chain. SCRM strategies often depend on rapid and adaptive decision-making based on potentially large, multidimensional data sources. These characteristics make SCRM a suitable application area for artificial intelligence (AI) techniques. The aim of this paper is to provide a comprehensive review of supply chain literature that addresses problems relevant to SCRM using approaches that fall within the AI spectrum. To that end, an investigation is conducted on the various definitions and classifications of supply chain risk and related notions such as uncertainty. Then, a mapping study is performed to categorise existing literature according to the AI methodology used, ranging from mathematical programming to Machine Learning and Big Data Analytics, and the specific SCRM task they address (identification, assessment or response). Finally, a comprehensive analysis of each category is provided to identify missing aspects and unexplored areas and propose directions for future research at the confluence of SCRM and AI.
Journal: International Journal of Production Research
Pages: 2179-2202
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1530476
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530476
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:7:p:2179-2202




Template-Type: ReDIF-Article 1.0
Author-Name: Ke Ma
Author-X-Name-First: Ke
Author-X-Name-Last: Ma
Author-Name: Rudrajeet Pal
Author-X-Name-First: Rudrajeet
Author-X-Name-Last: Pal
Author-Name: Eva Gustafsson
Author-X-Name-First: Eva
Author-X-Name-Last: Gustafsson
Title: What modelling research on supply chain collaboration informs us? Identifying key themes and future directions through a literature review
Abstract: 
 Although research regarding supply chain collaboration has been increasing, studies reviewing supply chain collaboration remains limited. This review paper categorises supply chain collaboration and identifies different themes in this research field. Articles were collected based on a designed keywords list and specific subject restrictions in citation databases. Text-mining technology and conceptual criteria were used to categorise and screen articles into different categories. Finally, cluster analysis was used to group articles and identify emerging themes. From the year 1999 to 2017, a total of 678 articles regarding supply chain collaboration were found. These were sorted into six categories: levels of collaboration, industries, supply chain stages, company scales, forms/methods of collaboration and typology of article, and into corresponding sub-categories. 380 articles employing modelling approach where collaboration forms the core of analysis were screened for hierarchical cluster analysis, resulting in four clusters: information sharing paradigm, joint decision-making paradigm, resource sharing paradigm and coordinating contract paradigm. Eleven themes were finally identified based on the four clusters. The number of articles in the field of supply chain collaboration shows an increasing trend by year. However, most of the collaborations discussed were still at a low level. It is expected to explore a higher level of collaborations and related themes in future research.
Journal: International Journal of Production Research
Pages: 2203-2225
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2018.1535204
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1535204
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:7:p:2203-2225




Template-Type: ReDIF-Article 1.0
Author-Name: Xufeng(Rax) Yao
Author-X-Name-First: Xufeng(Rax)
Author-X-Name-Last: Yao
Author-Name: Ronald Askin
Author-X-Name-First: Ronald
Author-X-Name-Last: Askin
Title: Review of supply chain configuration and design decision-making for new product
Abstract: 
 The nature of competitive markets continuously pushes manufacturers to develop new products to meet the increasingly diversified customer demands. Manufacturers thus have to handle the complexities generated during the total life cycles of various product types, from product design to procurement, production, marketing and recycling. Though some management practices in mass customisation help to improve the performance of manufacturing systems, there are still some fundamental problems not covered. Joint decision-making of product and supply chain design, for example, is one of them. The existing industrial practice tends to treat these two problems separately. Decoupling these two problems decrease the design complexity but may lead to suboptimal decision outcome. To enhance understanding of the interconnected decisions for supply chain management and product design, this review collects related literature on this topic and focuses on the analysis of existing papers from an operation research perspective.
Journal: International Journal of Production Research
Pages: 2226-2246
Issue: 7
Volume: 57
Year: 2019
Month: 4
X-DOI: 10.1080/00207543.2019.1567954
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1567954
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:7:p:2226-2246




Template-Type: ReDIF-Article 1.0
Author-Name: Margaretha Gansterer
Author-X-Name-First: Margaretha
Author-X-Name-Last: Gansterer
Author-Name: Richard F. Hartl
Author-X-Name-First: Richard F.
Author-X-Name-Last: Hartl
Title: The collaborative multi-level lot-sizing problem with cost synergies
Abstract: 
 Collaborative operations planning is a key element of modern supply chains. We introduce the collaborative multi-level lot-sizing problem with cost synergies. This arises if producers can realise reductions of their costs by providing more than one product in a specific time horizon. Since producers are typically not willing to reveal critical information, we propose a decentralised mechanism, where producers do not have to reveal their individual items costs. Additionally, a Genetic Algorithms-based centralised approach is developed, which we use for benchmarking. Our study shows that this approach comes very close to the a central plan, while in the decentralised one no critical information has to be shared. We compare the results to a myopic upstream planning approach, and show that these results are almost 12% worse than the centralised ones. All solution approaches are assessed on available test instances for problems without cost synergies. For the biggest available instances, the proposed centralised mechanism improves the best known solutions on average by 10.8%. The proposed decentralised mechanism can be applied to other problem classes, where collaborative decision makers aim for good plans under incomplete information.
Journal: International Journal of Production Research
Pages: 332-349
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1584415
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1584415
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:2:p:332-349




Template-Type: ReDIF-Article 1.0
Author-Name: Lars Hvam
Author-X-Name-First: Lars
Author-X-Name-Last: Hvam
Author-Name: Christian Lindschou Hansen
Author-X-Name-First: Christian Lindschou
Author-X-Name-Last: Hansen
Author-Name: Cipriano Forza
Author-X-Name-First: Cipriano
Author-X-Name-Last: Forza
Author-Name: Niels Henrik Mortensen
Author-X-Name-First: Niels Henrik
Author-X-Name-Last: Mortensen
Author-Name: Anders Haug
Author-X-Name-First: Anders
Author-X-Name-Last: Haug
Title: The reduction of product and process complexity based on the quantification of product complexity costs
Abstract: 
 Complexity management is an increasing challenge for industrial companies. To address this issue, this paper develops a procedure to reduce the complexity of products and processes. This procedure includes five steps: (1) definition of the scope of the products and processes to be included in the analysis, (2) grouping of products into A,B, and C categories, (3) identification and quantification of the most important complexity cost factors, (4) identification of initiatives for the possible reduction of complexity costs and the quantification of possible cost savings, and (5) evaluation and prioritisation of initiatives. To test the usefulness of the suggested procedure, it was applied at a globally leading manufacturer of mechanical consumer products. The case study demonstrated the usefulness of the proposed procedure in (1) supporting the allocation of complexity costs in relation to individual product variants, (2) achieving a better understanding of the cost structure of product assortment and business processes, and (3) providing a basis for generating and evaluating initiatives aimed at reducing the complexity of products and processes. The case study also showed that the use of the procedure can produce considerable financial benefits.
Journal: International Journal of Production Research
Pages: 350-366
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1587188
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1587188
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Template-Type: ReDIF-Article 1.0
Author-Name: Xu Li
Author-X-Name-First: Xu
Author-X-Name-Last: Li
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Title: A comparative analysis between different resource allocation and operating strategy implementation mechanisms using a system dynamics approach
Abstract: 
 Because of the rapid changes in the market environment and the increasing complexity of companies’ organisational and operational structures, managers should rethink their company’s driving and operations strategies while considering the causal relationships between variables in the feedback loop, resource accumulation, and information delay. This study used a system dynamic approach to examine and compare four different business models to discover how variations in resource accumulation (i.e. market-oriented versus service target–oriented) and operating strategy implementation (i.e. independent versus coordinated operations) affect a firm’s long-term performance. We used managers’ behaviour and policy factors to optimise the system dynamic models. In addition, we used theoretical system dynamics models and the simulation to examine the system profitability, stability, and sensitivity of each model. This study reveals the dynamic influence of managers’ decisions on system performance and provides a roadmap for managers to adjust resource allocation and their corresponding decisions to optimise the system dynamically.
Journal: International Journal of Production Research
Pages: 367-391
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1588480
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1588480
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Template-Type: ReDIF-Article 1.0
Author-Name: Devrim Murat Yazan
Author-X-Name-First: Devrim Murat
Author-X-Name-Last: Yazan
Author-Name: Luca Fraccascia
Author-X-Name-First: Luca
Author-X-Name-Last: Fraccascia
Title: Sustainable operations of industrial symbiosis: an enterprise input-output model integrated by agent-based simulation
Abstract: 
 Industrial symbiosis (IS) is a key for implementing circular economy. Through IS, wastes produced by one company are used as inputs by other companies. The operations of IS suffers from uncertainty barriers since wastes are not produced upon demand but emerge as secondary outputs. Such an uncertainty, triggered by waste supply-demand quantity mismatch, influences IS business dynamics. Accordingly, companies have difficulty to foresee potential costs and benefits of implementing IS. The paper adopts an enterprise input-output model providing a cost–benefit analysis of IS integrated to an agent-based model to simulate how companies share the total economic benefits stemming from IS. The proposed model allows to explore the space of cooperation, defined as the operationally favourable conditions to operate IS in an economically win-win manner. This approach, as a decision-support tool, allows the user to understand whether the IS relationship is created and how should the cost-sharing policy be. The proposed model is applied to a numerical example. Findings show that cost-sharing strategies are dramatically affected by waste supply-demand mismatch and by the relationship between saved and additional costs to run IS. Apart from methodological and theoretical contributions, the paper proposes managerial and practical implications for business strategy development in IS.
Journal: International Journal of Production Research
Pages: 392-414
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1590660
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1590660
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Template-Type: ReDIF-Article 1.0
Author-Name: Matteo M. Savino
Author-X-Name-First: Matteo M.
Author-X-Name-Last: Savino
Author-Name: Carlo Riccio
Author-X-Name-First: Carlo
Author-X-Name-Last: Riccio
Author-Name: Marialuisa Menanno
Author-X-Name-First: Marialuisa
Author-X-Name-Last: Menanno
Title: Empirical study to explore the impact of ergonomics on workforce scheduling
Abstract: 
 This work is focused on the workforce scheduling problem, investigating how the ergonomic exposure of a worker may affect the results of workforce allocation and the relative impact on production performances. A research methodology has been developed within a case study of an assembly flow with the twofold objective of (i) setting up a system able to consider the ergonomic parameters of workers within the solution of a workforce scheduling problem and (ii) finding the possible impacts that ergonomic postures can have on workforce allocation parameters. The ergonomic analysis, joint with the development of a constraint optimisation problem, resulted in a mathematical depiction of the ergonomic exposures and in a workforce ergonomic scheduling model. The study assessed how ergonomics may impact on workforce scheduling and the relative production capacity. Then, an experimental campaign joint with a tuning activity of the model resulted in a workforce scheduling configuration able to front the apparently contrasting objectives of production capacity optimisation and ergonomic stress lowering. The empirical results allowed also to quantify the trade-off between production performances, in terms of production capacity and idle time, versus ergonomic stress of the workers.
Journal: International Journal of Production Research
Pages: 415-433
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1591645
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1591645
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Template-Type: ReDIF-Article 1.0
Author-Name: Tae-Sun Yu
Author-X-Name-First: Tae-Sun
Author-X-Name-Last: Yu
Author-Name: Tae-Eog Lee
Author-X-Name-First: Tae-Eog
Author-X-Name-Last: Lee
Title: Wafer delay analysis and control of dual-armed cluster tools with chamber cleaning operations
Abstract: 
 As the design of integrated circuits has become increasingly complicated and dense, serious wafer quality problems are observed in modern wafer fabrication facilities. Therefore, in cluster tools of leading fabs process chambers are periodically cleaned in order to eliminate residual chemicals and impurities that can damage the wafer quality. A chamber cleaning operation is mainly applied to tools in which a wafer delay has a crucial impact on the wafer quality, and hence the need of wafer delay control becomes more significant when chamber cleaning is considered. Thus, we first examine how wafer delays can be specified for cluster tools with chamber cleaning operations. We confirm that wafer delays are substantially increased when chambers are periodically cleaned, and we show that such increased wafer delays cannot be eliminated or reduced using the existing scheduling methods. In such a case, we prove that a partial loading strategy can minimise both the tool cycle time and the wafer delays by controlling the number of wafers being loaded into parallel chambers. We also present how wafer delays under the partial loading strategy can be further reduced by introducing a timing control method that regulates the start times of robot tasks.
Journal: International Journal of Production Research
Pages: 434-447
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1593547
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1593547
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:2:p:434-447




Template-Type: ReDIF-Article 1.0
Author-Name: Xianghui Peng
Author-X-Name-First: Xianghui
Author-X-Name-Last: Peng
Author-Name: Victor Prybutok
Author-X-Name-First: Victor
Author-X-Name-Last: Prybutok
Author-Name: Heng Xie
Author-X-Name-First: Heng
Author-X-Name-Last: Xie
Title: Integration of supply chain management and quality management within a quality focused organizational framework
Abstract: 
 A paucity of research has explored the integration of supply chain management (SCM) and quality management (QM) within an overall organizational context. The investigation of integrating SCM and QM within an organizational framework has the potential to foster theory development of SCM and QM and to strengthen SCM and QM practice. The Baldrige Award promotes organization performance excellence and the associated framework has evolved into a notable quality focused organizational framework. Prior studies have focused on validating the effectiveness of the Baldrige framework. In this research, we integrate SCM and QM within the context of a quality focused organizational framework by proposing a modified version of the Baldrige framework and validate the proposed framework. We use cross-sectional survey data to test the hypothesized research model through partial least squares – structural equation modeling. The results support the effectiveness of the proposed framework. The research shows the importance of SCM as a major organizational construct with a significant positive direct influence on organizational results. The research also shows that SCM is a mediator for leadership and measurement, analysis and knowledge management that influence organizational results. This work discusses theoretical and managerial implications as well as implications for future research.
Journal: International Journal of Production Research
Pages: 448-466
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1593548
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1593548
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Template-Type: ReDIF-Article 1.0
Author-Name: Cong He
Author-X-Name-First: Cong
Author-X-Name-Last: He
Author-Name: Zailin Guan
Author-X-Name-First: Zailin
Author-X-Name-Last: Guan
Author-Name: Guangyan Xu
Author-X-Name-First: Guangyan
Author-X-Name-Last: Xu
Author-Name: Lei Yue
Author-X-Name-First: Lei
Author-X-Name-Last: Yue
Author-Name: Saif Ullah
Author-X-Name-First: Saif
Author-X-Name-Last: Ullah
Title: Scenario-based robust dominance criteria for multi-objective automated flexible transfer line balancing problem under uncertainty
Abstract: 
 The automated flexible transfer line (AFTL) is designed with flexibility, reconfigurability and reliability to satisfy the requirements in real manufacturing environment. It contains multiple stages in series performing the assigned operations, and each stage consists of multiple machining cells with one robot and multiple identical machines. A multi-objective robust optimisation problem (MOROP) based on AFTL balancing problem under uncertainty with three conflicting objectives, i.e. minimise the expected line cycle time, minimise the probability of real line cycle time exceeding the expected line cycle time and minimise the smoothness index, is proposed in this paper. Three new scenario-based robust dominance (SRD) criteria are proposed, and two novel methods, i.e. heuristic based on branch and bound (HBB) and heuristic based on artificial bee colony (HABC), are designed. Different sizes of experiments on MOROP are made and solved by the methods, and the performances of HBB and HABC are tested against considered problems with different scenarios based on the SRD criteria. Overall results indicate that HBB is quicker in searching solutions and HABC is better in result quality, and both heuristics provide robust solutions for the AFTL balancing problem.
Journal: International Journal of Production Research
Pages: 467-486
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1593549
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1593549
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:2:p:467-486




Template-Type: ReDIF-Article 1.0
Author-Name: Zhi Pei
Author-X-Name-First: Zhi
Author-X-Name-Last: Pei
Author-Name: Xuefang Zhang
Author-X-Name-First: Xuefang
Author-X-Name-Last: Zhang
Author-Name: Li Zheng
Author-X-Name-First: Li
Author-X-Name-Last: Zheng
Author-Name: Mingzhong Wan
Author-X-Name-First: Mingzhong
Author-X-Name-Last: Wan
Title: A column generation-based approach for proportionate flexible two-stage no-wait job shop scheduling
Abstract: 
 Job shop scheduling, as one of the classical scheduling problems, has been widely studied in literatures, and proved to be mostly NP-hard. Although it is extremely difficult to solve job shop scheduling with no-wait constraint to optimality, the two-machine no-wait job shop scheduling to minimise makespan could be solvable in polynomial time when each job has exactly two equal length operations (proportionate job shop). In the present paper, an extension is attempted by considering a proportionate flexible two-stage no-wait job shop scheduling problem with minimum makespan, and a set-covering formulation is put forward which contains a master problem and a pricing problem. To solve this problem, a column generation (CG)-based approach is implemented. In comparison, a mixed integer programming model is constructed and optimised by Cplex. A series of randomly generated numerical instances are calculated. And the testing result shows that the mixed integer model handled by Cplex can only solve small scale cases, while the proposed CG-based method can conquer larger size problems in acceptable time.
Journal: International Journal of Production Research
Pages: 487-508
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1597291
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1597291
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Template-Type: ReDIF-Article 1.0
Author-Name: Rui L. Lopes
Author-X-Name-First: Rui L.
Author-X-Name-Last: Lopes
Author-Name: Gonçalo Figueira
Author-X-Name-First: Gonçalo
Author-X-Name-Last: Figueira
Author-Name: Pedro Amorim
Author-X-Name-First: Pedro
Author-X-Name-Last: Amorim
Author-Name: Bernardo Almada-Lobo
Author-X-Name-First: Bernardo
Author-X-Name-Last: Almada-Lobo
Title: Cooperative coevolution of expressions for (r,Q) inventory management policies using genetic programming
Abstract: 
 There are extensive studies in the literature about the reorder point/order quantity policies for inventory management, also known as  $(r, Q) $(r,Q) policies. Over time different algorithms have been proposed to calculate the optimal parameters given the demand characteristics and a fixed cost structure, as well as several heuristics and meta-heuristics that calculate approximations with varying accuracy.This work proposes a new meta-heuristic that evolves closed-form expressions for both policy parameters simultaneously - Cooperative Coevolutionary Genetic Programming. The implementation used for the experimental work is verified with published results from the optimal algorithm, and a well-known hybrid heuristic. The evolved expressions are compared to those algorithms, and to the expressions of previous Genetic Programming approaches available in the literature. The results outperform the previous closed-form expressions and demonstrate competitiveness against numerical methods, reaching an optimality gap of less than  $1\% $1%, while being two orders of magnitude faster. Moreover, the evolved expressions are compact, have good generalisation capabilities, and present an interesting structure resembling previous heuristics.
Journal: International Journal of Production Research
Pages: 509-525
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1597293
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1597293
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:2:p:509-525




Template-Type: ReDIF-Article 1.0
Author-Name: Jianmai Shi
Author-X-Name-First: Jianmai
Author-X-Name-Last: Shi
Author-Name: Wenyi Chen
Author-X-Name-First: Wenyi
Author-X-Name-Last: Chen
Author-Name: Zhongbao Zhou
Author-X-Name-First: Zhongbao
Author-X-Name-Last: Zhou
Author-Name: Guoqing Zhang
Author-X-Name-First: Guoqing
Author-X-Name-Last: Zhang
Title: A bi-objective multi-period facility location problem for household e-waste collection
Abstract: 
 This paper addresses the multi-period facility location problem during the market expansion stage, where the decision maker plans to add a certain number of new facilities in each period to gradually increase the accessibility of the infrastructural collection network. In order to consider the trade-off between cost efficiency and service coverage, we propose a multi-period bi-objective 0–1 integer programming formulation for the problem. We develop three metaheuristics to solve the problem. The first metaheuristic is based on the NSGA II framework with the traditional operators for the single-period location problem. The second metaheuristic is based on the local search strategy, where five new neighbourhood structures are designed. The last metaheuristic integrates the former two algorithms. The proposed modelling framework is justified by a case study of the system infrastructure design in Vancouver for E-waste collection. To demonstrate the computational performance of the proposed modelling framework, sixty random instances of different sizes (200 or 500 demand points), with different demand distributions (Uniform, Normal and Gamma distributions) are generated. We compare the proposed modelling framework with two popular multi-objective metaheuristics, MOEA/D and NNIA. Computational results show that the proposed metaheuristic based on local search is the most efficient for searching Pareto solutions of the problem.
Journal: International Journal of Production Research
Pages: 526-545
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1598591
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598591
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:2:p:526-545




Template-Type: ReDIF-Article 1.0
Author-Name: Kehong Chen
Author-X-Name-First: Kehong
Author-X-Name-Last: Chen
Author-Name: Yong Zha
Author-X-Name-First: Yong
Author-X-Name-Last: Zha
Author-Name: Layth C. Alwan
Author-X-Name-First: Layth C.
Author-X-Name-Last: Alwan
Author-Name: Lu Zhang
Author-X-Name-First: Lu
Author-X-Name-Last: Zhang
Title: Dynamic pricing in the presence of reference price effect and consumer strategic behaviour
Abstract: 
 This paper presents a model for designing two-stage dynamic pricing strategies when the seller faces strategic consumers in the presence of a reference price effect. The consumers form the utilities of two sequential periods based on anticipated future retail price in the second period and current retail price in the first period as the reference price, and then choose the purchasing timing, representing strategic behaviour. We first consider a centralised system where the seller chooses between two pricing policies: markdown pricing and markup pricing under a centralised system, and find that the seller will not adopt a markup pricing policy. We derive equilibrium prices and optimal pricing strategies for the seller under markdown pricing policy using equilibrium theory and backward induction method. We find that the seller’s profit decreases with the consumer strategic behaviour, and increases (decreases) with the reference price effect when consumer strategic behaviour is low (high), indicating a non-monotonity with respect to the coexistence of consumer strategic behaviour and reference price effect. We then extend our study from a centralised system to a decentralised system and find that double marginalisation is effectively weakened by the two effects. Interestingly, the centralised structure may not always be optimal relative to a decentralised structure, indicating a non-monotone relationship between the wholesale price and the profit in decentralised structure.
Journal: International Journal of Production Research
Pages: 546-561
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1598592
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598592
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:2:p:546-561




Template-Type: ReDIF-Article 1.0
Author-Name: Lu Zhen
Author-X-Name-First: Lu
Author-X-Name-Last: Zhen
Author-Name: Ziheng Xu
Author-X-Name-First: Ziheng
Author-X-Name-Last: Xu
Author-Name: Chengle Ma
Author-X-Name-First: Chengle
Author-X-Name-Last: Ma
Author-Name: Liyang Xiao
Author-X-Name-First: Liyang
Author-X-Name-Last: Xiao
Title: Hybrid electric vehicle routing problem with mode selection
Abstract: 
 With the development of green logistics, logistics companies gradually are paying attention to the application of hybrid electric vehicles (HEVs). HEVs have the advantages of low energy consumption and pollution, while their disadvantage mainly lies in their limited continuous driving range. Therefore, it is necessary to optimize the use of fuel during the distribution process. We study the mode selection system in HEVs based on the background of green logistics and the above characteristics of HEVs. The mode selection system can adjust the driving mode of the HEV according to different road conditions to obtain the optimal use of fuel. In this paper, we propose a new study of a hybrid electric vehicle routing problem with mode selection. This problem is formulated as a mixed integer linear programming model. An improved particle swarm optimization algorithm (IPSO) is developed to solve this problem. Extensive numerical experiments are conducted to validate the effectiveness of the proposed model and the efficiency of the proposed solution method. The experimental results show that our proposed algorithm not only obtains the optimal solution for some small-scale problem instances and some medium-scale problems but also solves some large-scale situations (one hundred customers, eleven vehicles, eleven charging stations, eleven gas stations and four modes) within an hour.
Journal: International Journal of Production Research
Pages: 562-576
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1598593
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598593
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Template-Type: ReDIF-Article 1.0
Author-Name: Rui Miao
Author-X-Name-First: Rui
Author-X-Name-Last: Miao
Author-Name: Hui Zhang
Author-X-Name-First: Hui
Author-X-Name-Last: Zhang
Author-Name: Qi Wu
Author-X-Name-First: Qi
Author-X-Name-Last: Wu
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Using structural equation modeling to analyze patient value, satisfaction, and loyalty: a case study of healthcare in China
Abstract: 
 Understanding patient value is a key mechanism in addressing current healthcare challenges, as well as for establishing a patient-centered healthcare system. With high patient dissatisfaction, and the growing tension between patients and providers in China, understanding patient value and evaluating healthcare delivery performance becomes urgent. The objective of this study is to identify patient value dimensions in healthcare and to understand their relationships with patient satisfaction and loyalty. We conduct a case study in two hospitals in Shanghai, China. We identify economic value, health value, fair value, and supplemental value as four value dimensions. We use the combinational weighting method to evaluate the value-added ability of healthcare services, and use the structural equation model to examine the relationships between patient value, satisfaction, and loyalty. The value-added evaluation indicates significant room for improvement related to economic value for the large hospital, as well as to health value and fair value for the community hospital. Our findings inform hospitals and physicians of areas of focus, particularly improving those with low evaluation and high importance, to maximise patient satisfaction and loyalty. We also provide managerial insights for healthcare policy makers, such as strengthening primary health care, ensuring rational pricing, and improving hospital governance.
Journal: International Journal of Production Research
Pages: 577-596
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1598595
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598595
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Template-Type: ReDIF-Article 1.0
Author-Name: Deming Lei
Author-X-Name-First: Deming
Author-X-Name-Last: Lei
Author-Name: Yue Yuan
Author-X-Name-First: Yue
Author-X-Name-Last: Yuan
Author-Name: Jingcao Cai
Author-X-Name-First: Jingcao
Author-X-Name-Last: Cai
Author-Name: Danyu Bai
Author-X-Name-First: Danyu
Author-X-Name-Last: Bai
Title: An imperialist competitive algorithm with memory for distributed unrelated parallel machines scheduling
Abstract: 
 Distributed scheduling becomes popular with the shift of production from single factory to multiple factories and reveals new features and the increasing optimisation difficulties. In this study, distributed unrelated parallel machines scheduling problem with makespan minimisation is considered in the heterogeneous production network, which is directly simplified as an extended machine assignment. A novel imperialist competitive algorithm with memory (MICA) is presented, in which a machine assignment string is adopted and four neighbourhood structures and a global search operator are introduced. In each empire, some best colonies learn from a member of memory or imperialist and other colonies move toward imperialist or one of the best colonies, and revolution is newly implemented by using good solutions. Global search of imperialist is added into imperialist competition to avoid the addition of the weakest colony of the weakest empire into the winning empire. Lower bound is provided. Extensive experiments are conducted to test the performance of MICA and computational results show that MICA is a very competitive method for the considered problem.
Journal: International Journal of Production Research
Pages: 597-614
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1598596
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598596
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Template-Type: ReDIF-Article 1.0
Author-Name: Thiago Cantos Lopes
Author-X-Name-First: Thiago Cantos
Author-X-Name-Last: Lopes
Author-Name: Celso Gustavo Stall Sikora
Author-X-Name-First: Celso Gustavo Stall
Author-X-Name-Last: Sikora
Author-Name: Adalberto Sato Michels
Author-X-Name-First: Adalberto Sato
Author-X-Name-Last: Michels
Author-Name: Leandro Magatão
Author-X-Name-First: Leandro
Author-X-Name-Last: Magatão
Title: An iterative decomposition for asynchronous mixed-model assembly lines: combining balancing, sequencing, and buffer allocation
Abstract: 
 Asynchronous Mixed-Model Assembly lines are common production layouts dedicated to large-scale manufacturing of similar products. Cyclically scheduling such products is an interesting strategy to obtain high and stable throughput. In order to best optimise these lines, it is necessary to combine line balancing, model sequencing, and buffer allocation. However, few works integrate these three degrees of freedom, and evaluating steady-state performance as a consequence of these decisions is challenging. This paper presents a mathematical model that allows an exact steady-state performance evaluation of these lines, and hence their optimisation. While the combination of degrees of freedom is advantageous, it is also computational costly. An iterative decomposition procedure based on alternation between two mathematical models and on optimality cuts is also presented. The decomposition is tested against the proposed mathematical model in a 700-instance dataset. The developed methods obtained 142 optimal answers. Results show that the decomposition outperforms the monolithic mathematical model, in particular for larger and harder instances in terms of solution quality. The optimality cuts are also shown to help the decomposition steps in terms of solution quality and time. Comparisons to a sequential procedure further demonstrate the importance of simultaneously optimising the three degrees of freedom, as both the proposed model and the decomposition outperformed such procedure.
Journal: International Journal of Production Research
Pages: 615-630
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1598597
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598597
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Template-Type: ReDIF-Article 1.0
Author-Name: Paul Pitiot
Author-X-Name-First: Paul
Author-X-Name-Last: Pitiot
Author-Name: Luis Garces Monge
Author-X-Name-First: Luis Garces
Author-X-Name-Last: Monge
Author-Name: Michel Aldanondo
Author-X-Name-First: Michel
Author-X-Name-Last: Aldanondo
Author-Name: Elise Vareilles
Author-X-Name-First: Elise
Author-X-Name-Last: Vareilles
Author-Name: Paul Gaborit
Author-X-Name-First: Paul
Author-X-Name-Last: Gaborit
Title: Optimisation of the concurrent product and process configuration: an approach to reduce computation time with an experimental evaluation
Abstract: 
 Concurrent configuration of a product and its associated production process is a challenging problem in customer/supplier relations dealing with customisable or configurable products. It gathers in a single model multiple choices and constraints which come simultaneously from products (choices of components or functionalities), from processes (choices of resources and quantities) and from their mutual interrelations. Considering this problem as a Constraint Satisfaction Problem (CSP), the aim of this article is to improve its optimisation, while considering multiple objectives. Using an existing evolutionary optimisation algorithm as a basis, we propose an approach that reduces the computation time required for optimisation. The idea is first to quickly compute a rough Pareto of solutions, then ask the user to select an area of interest, and finally to launch a second computation on this restricted area. After an introduction to the problem, the approach is explained and the algorithm adaptations are presented. Then various computation experiments results demonstrate that computation times are significantly reduced while keeping the optimality level.
Journal: International Journal of Production Research
Pages: 631-647
Issue: 2
Volume: 58
Year: 2020
Month: 1
X-DOI: 10.1080/00207543.2019.1598598
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598598
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Template-Type: ReDIF-Article 1.0
Author-Name: Ernesto D.R. Santibanez Gonzalez
Author-X-Name-First: Ernesto D.R.
Author-X-Name-Last: Santibanez Gonzalez
Author-Name: Lenny Koh
Author-X-Name-First: Lenny
Author-X-Name-Last: Koh
Author-Name: Janny Leung
Author-X-Name-First: Janny
Author-X-Name-Last: Leung
Title: Towards a circular economy production system: trends and challenges for operations management
Journal: International Journal of Production Research
Pages: 7209-7218
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1656844
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656844
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Template-Type: ReDIF-Article 1.0
Author-Name: Nachiappan Subramanian
Author-X-Name-First: Nachiappan
Author-X-Name-Last: Subramanian
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Lin Wu
Author-X-Name-First: Lin
Author-X-Name-Last: Wu
Author-Name: Tinghua Shen
Author-X-Name-First: Tinghua
Author-X-Name-Last: Shen
Title: Role of traditional Chinese philosophies and new product development under circular economy in private manufacturing enterprise performance
Abstract: 
 The new product development (NPD) process–performance link has been sufficiently studied in academic research. However, recent NPD process is significantly different from the conventional NPD specifically with the inclusion of sustainability considerations under circular economy (CE) context. In theory, NPD with CE considerations (CE-NPD), compared with the conventional NPD, is associated with higher costs and longer development times. This study empirically examines the effect of the CE-NPD process on both time-to-market (TTM) and profit performance in the context of Chinese private enterprises. In addition, the role of traditional Chinese philosophies of Confucianism and Taoism in influencing the CE-NPD process–performance link is also investigated. We find that Confucianism positively moderates the relationship between the CE-NPD process and TTM performance. However, it negatively moderates the CE-NPD-profit link. On the other hand, the moderating effect of Taoism is negative on both the CE-NPD-TTM and CE-NPD-profit links. An interesting finding of this study is that the coexistence of Confucian and Taoist values in NPD workers has the strongest positive impact on the relationship between the CE-NPD process and performance. Our study provides insights on the way in which companies should plan to apply Chinese philosophies during the CE-NPD process to maximise the benefits.
Journal: International Journal of Production Research
Pages: 7219-7234
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2018.1530467
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530467
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Template-Type: ReDIF-Article 1.0
Author-Name: Yunshi Mao
Author-X-Name-First: Yunshi
Author-X-Name-Last: Mao
Author-Name: Jing Wang
Author-X-Name-First: Jing
Author-X-Name-Last: Wang
Title: Is green manufacturing expensive? Empirical evidence from China
Abstract: 
 With increasingly serious environmental problems, a circular economy production system is in urgent needs. This study explores whether green manufacturing (GM) is expensive and how external institutional environmental pressures influence the cost of GM among industrial enterprises in emerging economies. Through an analysis of 10,380 observations of 1470 listed manufacturing firms in the Chinese share market from 2008 to 2015, this paper finds that GM increases operating cost (OC). In addition, the positive relationship between GM and OC is strengthened with reduced pollution level in the local city. Furthermore, synergistic effects of the local pollution level and the local government’s pollution information transparency are found. Firms’ OC increases more as firms carry out GM when both the local pollution level and pollution information transparency of local government are high, or when the local pollution level and the local government’s pollution information transparency are low.
Journal: International Journal of Production Research
Pages: 7235-7247
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2018.1480842
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1480842
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Template-Type: ReDIF-Article 1.0
Author-Name: Luciano Batista
Author-X-Name-First: Luciano
Author-X-Name-Last: Batista
Author-Name: Yu Gong
Author-X-Name-First: Yu
Author-X-Name-Last: Gong
Author-Name: Susana Pereira
Author-X-Name-First: Susana
Author-X-Name-Last: Pereira
Author-Name: Fu Jia
Author-X-Name-First: Fu
Author-X-Name-Last: Jia
Author-Name: Alexandre Bittar
Author-X-Name-First: Alexandre
Author-X-Name-Last: Bittar
Title: Circular supply chains in emerging economies – a comparative study of packaging recovery ecosystems in China and Brazil
Abstract: 
 This paper provides a circular supply chain perspective of packaging recovery ecosystems being implemented by Tetra Pak, a prime global player in the food packaging industry, in two major emerging economies: China and Brazil. The circular supply chain archetype considered in the research allowed a consistent comparative analysis of Tetra Pak's circular supply chains in both countries. Through a case study approach, the research provides theoretical propositions and learning points that are valuable for academics and practitioners interested in the Chinese and Brazilian markets as well as in the supply chains supporting recovery ecosystems in the packaging industry. In particular, the distinct environments in the Chinese and Brazilian markets render Tetra Pak opportunities to design circular supply chains in different ways showing adaptation and learning to local market characteristics. The industrial perspectives from these emerging economies add to the contributions offered in the paper. Overall, the conceptual considerations and practical recommendations presented in the paper provide useful insights for the development of further studies and implementation of industrial practices advocated by the circular economy.
Journal: International Journal of Production Research
Pages: 7248-7268
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2018.1558295
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1558295
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Template-Type: ReDIF-Article 1.0
Author-Name: Leila Abuabara
Author-X-Name-First: Leila
Author-X-Name-Last: Abuabara
Author-Name: Alberto Paucar-Caceres
Author-X-Name-First: Alberto
Author-X-Name-Last: Paucar-Caceres
Author-Name: Toni Burrowes-Cromwell
Author-X-Name-First: Toni
Author-X-Name-Last: Burrowes-Cromwell
Title: Consumers’ values and behaviour in the Brazilian coffee-in-capsules market: promoting circular economy
Abstract: 
 Coffee consumption is changing. Monodose, flavoured coffee capsules provide new experiences beyond the traditional custom of brewing coffee. These pods allow access to a selection of premium coffee worldwide but create huge quantities of plastic-aluminium packaging waste. The paper examines the novelty of coffee capsule consumption in Brazil in terms of consumers’ perspectives about ethical enterprise and environmental stewardship. We argue for ‘waste to resource’ management and applying reverse logistics to the coffee production supply chain. Based on circular economy principles and fuelled by the ‘green’ awareness of Brazilian coffee consumers, we propose a conceptual framework to support business decision-making by adopting a systemic intervention from the consumer viewpoint. To structure the situation, we conducted over 40 interviews, using purposive sampling. Analytic hierarchy process, value focused thinking and Rich Picture technique informed our problem structuring approach. Findings illustrate that reverse logistics supply chain in coffee capsule manufacturing presents real challenges to achieving circular practice. Yet, the eco-values of Brazilian coffee enthusiasts may be partly considered a ‘wealth of information flow’ and a potential driving force for change. This paper should be of interest to researchers/practitioners exploring how consumers may contribute to behavioural change, towards more circular business.
Journal: International Journal of Production Research
Pages: 7269-7288
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1629664
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629664
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Template-Type: ReDIF-Article 1.0
Author-Name: Deepak Singhal
Author-X-Name-First: Deepak
Author-X-Name-Last: Singhal
Author-Name: Sarat Kumar Jena
Author-X-Name-First: Sarat Kumar
Author-X-Name-Last: Jena
Author-Name: Sushanta Tripathy
Author-X-Name-First: Sushanta
Author-X-Name-Last: Tripathy
Title: Factors influencing the purchase intention of consumers towards remanufactured products: a systematic review and meta-analysis
Abstract: 
 Rapid growth in end-of-use and end-of-life products and their current unsustainable disposal methods are the cause of worries among the researchers and academicians across the globe. For that, remanufacturing is emerging as a viable option for sustainable production. Moreover, acceptance of remanufactured products by the consumers is highly essential for the success of the circular economy. Therefore, a study of the purchase intention of the consumers towards remanufactured products becomes inevitable. Here, our research uses meta-analysis to statistically synthesise and analyze the factors relevant to the purchase intention of the remanufactured products. Based on the published literature a total of ten studies are found suitable for the meta-analysis. The result shows that purchase intention of consumers is positively and strongly influenced by attitude and subjective norm, whereas it is moderately influenced by perceived green benefits and perceived behaviour control. In addition, meta-analysis supports the negative relationship between perceived risk and purchase intention. The findings also suggest that consumers who purchase remanufactured electrical and electronics products are less environmentally conscious than consumers who purchase remanufactured automotive products. Further, authors have discussed the managerial implications of the factors which influence the purchase intention of the consumers towards remanufactured products.
Journal: International Journal of Production Research
Pages: 7289-7299
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1598590
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598590
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Template-Type: ReDIF-Article 1.0
Author-Name: Mickey Howard
Author-X-Name-First: Mickey
Author-X-Name-Last: Howard
Author-Name: Peter Hopkinson
Author-X-Name-First: Peter
Author-X-Name-Last: Hopkinson
Author-Name: Joe Miemczyk
Author-X-Name-First: Joe
Author-X-Name-Last: Miemczyk
Title: The regenerative supply chain: a framework for developing circular economy indicators
Abstract: 
 There are widely differing experiences and practices in the development of indicators to monitor, report and communicate progress towards the implementation of the circular economy (CE). We present a framework for developing CE indicators which link to the core goals, principles and building blocks of a CE. To do this we utilise the Ellen MacArthur Foundation butterfly model as a coherent systems overview of key material stocks and flows, and representation of relationships between inputs, outputs, recovery processes, emissions, energy and value loops in physical and financial measures which constitute the CE supply chain. Based on nine multinational organisations and four cases of leading companies engaged with CE activity, we address the types of indicators being used and make recommendations for indicators to reflect key goals and principles of CE. Our research on the development and expansion of circular practices leads to the question of what new opportunities and challenges CE raises for such companies in terms of competitive business advantage and resultant requirements for supply chain redesign and indicator development, over and above pre-existing closed-loop production.
Journal: International Journal of Production Research
Pages: 7300-7318
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2018.1524166
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1524166
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Template-Type: ReDIF-Article 1.0
Author-Name: Jose Arturo Garza-Reyes
Author-X-Name-First: Jose Arturo
Author-X-Name-Last: Garza-Reyes
Author-Name: Ailin Salomé Valls
Author-X-Name-First: Ailin
Author-X-Name-Last: Salomé Valls
Author-Name: Simon Peter Nadeem
Author-X-Name-First: Simon
Author-X-Name-Last: Peter Nadeem
Author-Name: Anthony Anosike
Author-X-Name-First: Anthony
Author-X-Name-Last: Anosike
Author-Name: Vikas Kumar
Author-X-Name-First: Vikas
Author-X-Name-Last: Kumar
Title: A circularity measurement toolkit for manufacturing SMEs
Abstract: 
 The development and adoption of the concept of circular economy in the last two decades have been remarkable. However, despite its widespread adoption, little progress has been made regarding its measurement, especially in manufacturing SMEs. This paper, therefore, proposes a Circularity Measurement Toolkit (CMT) which enables the assessment of the degree of circularity in manufacturing SMEs. A conceptual CMT framework, which provided the basis for the proposed tool and that defined the different types of circular practices and a classification or levels of circularity was developed from an extensive literature reviewed. To ensure the structure's accuracy of the proposed CMT in terms of requirements to be measured, the monitoring process and actions involved, the tool was verified through a Delphi-study. Furthermore, its practicality was validated through a case study approach in a manufacturing SME. This paper contributes by filling a gap in the CE measurement field through the proposal of the CMT. Besides providing an evaluation of the degree of circularity in the practices of manufacturing SMEs, companies can also employ the proposed CMT to identify corrective actions or future efforts for the adoption of CE practices.
Journal: International Journal of Production Research
Pages: 7319-7343
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2018.1559961
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1559961
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Template-Type: ReDIF-Article 1.0
Author-Name: Manjot Singh Bhatia
Author-X-Name-First: Manjot Singh
Author-X-Name-Last: Bhatia
Author-Name: Rajiv Kumar Srivastava
Author-X-Name-First: Rajiv
Author-X-Name-Last: Kumar Srivastava
Title: Antecedents of implementation success in closed-loop supply chain: an empirical investigation
Abstract: 
 Implementation of closed-loop supply chain (CLSC) has gained increased consideration in the last few years owing to an increase in environmental concerns, product returns and scarcity of natural resources. It aids in improving environmental, economic and social performances. The purpose of this study is to examine the impact of CLSC critical success factors (CSFs) on performance outcomes. Firstly, CSFs and performance outcomes are extracted by conducting exploratory factor analysis using SPSS software. Then, the relationships between CLSC CSFs and performance outcomes are empirically tested by Partial Least Squares-Structural Equation Modelling (PLS-SEM) approach, using the data collected from 138 professionals working in remanufacturing, refurbishing and recycling operations in North American manufacturing organisations. Empirical analysis demonstrates that CSFs, ‘environmental concerns’, ‘sustainable production’ and ‘product design and collection’ have a significant positive effect on environmental performance. Results also validate the significant positive effect of CSFs, ‘demand and inventory management’ and ‘raw material prices’ on economic performance. In our knowledge, this is the first study that examines the impact of CLSC CSFs on performance outcomes. The results provide managers in manufacturing organisations with insights on most important CSFs that improve performance.
Journal: International Journal of Production Research
Pages: 7344-7360
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1583393
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1583393
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Template-Type: ReDIF-Article 1.0
Author-Name: Thanos E. Goltsos
Author-X-Name-First: Thanos E.
Author-X-Name-Last: Goltsos
Author-Name: Borja Ponte
Author-X-Name-First: Borja
Author-X-Name-Last: Ponte
Author-Name: Shixuan Wang
Author-X-Name-First: Shixuan
Author-X-Name-Last: Wang
Author-Name: Ying Liu
Author-X-Name-First: Ying
Author-X-Name-Last: Liu
Author-Name: Mohamed M. Naim
Author-X-Name-First: Mohamed M.
Author-X-Name-Last: Naim
Author-Name: Aris A. Syntetos
Author-X-Name-First: Aris A.
Author-X-Name-Last: Syntetos
Title: The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems
Abstract: 
 Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems.
Journal: International Journal of Production Research
Pages: 7361-7394
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2018.1510191
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1510191
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Template-Type: ReDIF-Article 1.0
Author-Name: Gianmarco Bressanelli
Author-X-Name-First: Gianmarco
Author-X-Name-Last: Bressanelli
Author-Name: Marco Perona
Author-X-Name-First: Marco
Author-X-Name-Last: Perona
Author-Name: Nicola Saccani
Author-X-Name-First: Nicola
Author-X-Name-Last: Saccani
Title: Challenges in supply chain redesign for the Circular Economy: a literature review and a multiple case study
Abstract: 
 Despite companies face several challenges when redesigning their supply chain for the Circular Economy, the literature lacks a systematisation of such challenges and of the ways to overcome them. Through a systematic literature review, this paper identifies and systematises 24 challenges that may hamper a supply chain redesign for the Circular Economy. Sixteen among these challenges are well known from research in related topics. On the contrary, the remaining eight are relatively new or take a different relevance within the Circular Economy context. A multiple case study in the household appliance supply chain is carried out, to explore how these challenges appear in practice and how companies may tackle them. The cases analysed involve actors at different supply chain levels, and findings suggest that a great degree of vertical integration by one actor in the supply chain is not a necessary condition for Circular Economy implementation. The empirical study, in conjunction with the literature analysis, leads to the development of a framework linking the challenges to specific levers that companies may pursue to overcome them. The framework can be seen as a reference for managers undertaking the path towards Circular Economy.
Journal: International Journal of Production Research
Pages: 7395-7422
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2018.1542176
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1542176
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Template-Type: ReDIF-Article 1.0
Author-Name: Qi Zhang
Author-X-Name-First: Qi
Author-X-Name-Last: Zhang
Author-Name: Qiuhong Zhao
Author-X-Name-First: Qiuhong
Author-X-Name-Last: Zhao
Author-Name: Xuan Zhao
Author-X-Name-First: Xuan
Author-X-Name-Last: Zhao
Title: Manufacturer's product choice in the presence of environment-conscious consumers: brown product or green product
Abstract: 
 Nowadays, the brown products are losing market coverage to their green alternatives due to consumers' increasing environmental awareness. Confronted with this threat, many traditional manufacturers currently producing only brown product are contemplating the launch of green product. Base on this background, this paper explores the optimal product choice for the manufacturer. We first derive the optimal results for each product choice. Then we analyse the optimal product choice for the manufacturer. Next, we study how to induce the production of green product. Finally, the fraudulent behaviour on product's environmental attributes is addressed. Main findings are as follows. First, manufacturer's optimal product choice is to produce green product if the investment-to-value ratio and the unit production cost for green product are low and to produce brown product if the investment-to-value ratio and the unit production cost for green product are high. Second, the two-part tariff contract is applicable to stimulate the manufacturer to produce green product under certain conditions. While exterior intervention is necessary under other conditions. Third, when the manufacturer and the retailer diverge in product preference, the manufacturer has a strong incentive to behave fraudulently, and this type of manufacturer needs strict supervision.
Journal: International Journal of Production Research
Pages: 7423-7438
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1624853
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1624853
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Template-Type: ReDIF-Article 1.0
Author-Name: Yipei Zhang
Author-X-Name-First: Yipei
Author-X-Name-Last: Zhang
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Ada Che
Author-X-Name-First: Ada
Author-X-Name-Last: Che
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Xin Feng
Author-X-Name-First: Xin
Author-X-Name-Last: Feng
Title: Novel model and kernel search heuristic for multi-period closed-loop food supply chain planning with returnable transport items
Abstract: 
 Closed-loop supply chain (CLSC) is of utmost importance to sustainable development and has received increasing attention in recent decades. However, food CLSC with returnable transport items (RTIs) has been rarely studied although its growing applications in practice. This paper aims to investigate a multi-period CLSC planning problem that coordinates the flows of perishable food products and RTIs considering food quality. The objective is to maximise the total profit of the holistic supply chain over a finite planning horizon. To this end, a novel mixed integer linear programming model is first formulated. As the problem is proven NP-hard, an improved kernel search-based heuristic is then developed. A real case study deriving from a food manufacturer in China shows the applicability of the proposed model and method. The results indicate that the manufacturer’s profit can be improved by more than 10% with our method. Numerical experiments on randomly generated instances demonstrate that the proposed heuristic can yield high-quality solutions with much less computation time compared with the commercial solver CPLEX and an existing heuristic.
Journal: International Journal of Production Research
Pages: 7439-7456
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1615650
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1615650
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Template-Type: ReDIF-Article 1.0
Author-Name: Na Duan
Author-X-Name-First: Na
Author-X-Name-Last: Duan
Author-Name: Jun-Peng Guo
Author-X-Name-First: Jun-Peng
Author-X-Name-Last: Guo
Author-Name: Peng Zhou
Author-X-Name-First: Peng
Author-X-Name-Last: Zhou
Author-Name: Bai-Chen Xie
Author-X-Name-First: Bai-Chen
Author-X-Name-Last: Xie
Title: The impacts of the coal-electricity price linkage on the profit efficiency of China’s thermal power plants
Abstract: 
 Under the dual track mechanism of ‘market coal and plan electricity’, China’s power price cannot be adjusted in a timely manner according to the changes in the coal price. The authorities put forward the policy of coal electricity linkage to overcome this dilemma in 2004 and updated the relevant details in 2016. Based on the directional distance function, this study measured the profit efficiency of over 1300 thermal power plants in China during 2002–2011 and investigated the impacts of the linkage policy using scenario analysis. We implemented the bootstrap method to analyse the sensitivity of the estimators of efficiency to sample variation and the impacts of plant-specific factors. The empirical results show that: First, compared to the predetermined directional vector approach, the generalised endogenous projection vectors made the estimated inefficiency scores perform better in objectivity, feasibility, and differentiation. Second, technical inefficiency was the primary cause of the profit inefficiency during the study period rather than allocative inefficiency. The large generation groups attained higher profit efficiencies than the power plants not affiliated to them. Finally, in straightening out the relationship between the coal and power prices, the linkage mechanism could only be a transitory step to the electricity market-oriented reform.
Journal: International Journal of Production Research
Pages: 7457-7470
Issue: 23
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2018.1508902
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1508902
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Template-Type: ReDIF-Article 1.0
Author-Name: Fan-Tien Cheng
Author-X-Name-First: Fan-Tien
Author-X-Name-Last: Cheng
Author-Name: Yao-Sheng Hsieh
Author-X-Name-First: Yao-Sheng
Author-X-Name-Last: Hsieh
Author-Name: Chun-Fang Chen
Author-X-Name-First: Chun-Fang
Author-X-Name-Last: Chen
Author-Name: Jhao-Rong Lyu
Author-X-Name-First: Jhao-Rong
Author-X-Name-Last: Lyu
Title: Automated sampling decision scheme for the AVM system
Abstract: 
 Reducing the sampling rate to as low as possible is a high priority for many factories to reduce production cost. Automatic virtual metrology based intelligent sampling decision (ISD) scheme had been previously developed for reducing the sampling rate and sustaining the virtual metrology (VM) accuracy. However, the desired sampling rate of the ISD scheme is fixed and set manually. Hence, whenever the VM accuracy gets worse, it cannot adaptively increase the default sampling rate in the ISD scheme. As a consequence, it would take more time to collect enough samples for improving the VM accuracy. Moreover, when the VM accuracy performs well all the time, it cannot automatically decrease the default sampling rate in ISD, which may result in unnecessary waste. Accordingly, this paper proposes an automated sampling decision (ASD) scheme to adaptively and automatically modify the sampling rate online and in real time for continuous improvement. The ASD scheme can monitor the VM accuracy online as well as update the VM models in real time for maintaining the VM accuracy when the VM accuracy becomes poor. Also, the ASD scheme can automatically reduce the sampling rate while the VM accuracy performs well.
Journal: International Journal of Production Research
Pages: 6351-6366
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2015.1072649
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1072649
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Template-Type: ReDIF-Article 1.0
Author-Name: Haw-Ching Yang
Author-X-Name-First: Haw-Ching
Author-X-Name-Last: Yang
Author-Name: Hao Tieng
Author-X-Name-First: Hao
Author-X-Name-Last: Tieng
Author-Name: Fan-Tien Cheng
Author-X-Name-First: Fan-Tien
Author-X-Name-Last: Cheng
Title: Automatic virtual metrology for wheel machining automation
Abstract: 
 Total inspection after wheel machining becomes essential for safety consideration and continuous improvement. However, conducting wheel-by-wheel actual metrology is very expensive and time-consuming. A novel idea is to use virtual metrology (VM) that predicts wheel quality based on process data collected from machine tool with a slight supplement of actual metrology data. The technology of automatic virtual metrology (AVM) has been proposed by the authors and successfully deployed in hi-tech industries, such as semiconductor, display and solar cell. The purpose of this study was to propose an approach to apply the AVM system factory-wide to wheel machining automation (WMA) for achieving total inspection of all the precision items of WMA under mass production environment.
Journal: International Journal of Production Research
Pages: 6367-6377
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2015.1109724
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1109724
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Template-Type: ReDIF-Article 1.0
Author-Name: Devashish Das
Author-X-Name-First: Devashish
Author-X-Name-Last: Das
Author-Name: Shiyu Zhou
Author-X-Name-First: Shiyu
Author-X-Name-Last: Zhou
Author-Name: Yong Chen
Author-X-Name-First: Yong
Author-X-Name-Last: Chen
Author-Name: John Horst
Author-X-Name-First: John
Author-X-Name-Last: Horst
Title: Statistical monitoring of over-dispersed multivariate count data using approximate likelihood ratio tests
Abstract: 
 In this paper, we develop a statistical monitoring scheme for multivariate count data. In many applications involving multivariate count data, individual variables are not only correlated to each other, but also over-dispersed. Traditional statistical monitoring methods for multivariate count data that assume simple statistical models fail to fit the data collected when the underlying process is under normal working state, also referred to as the in-control state. Therefore, we propose a monitoring scheme which is based on the Poisson–multivariate Gaussian mixed model. Although such models are quite flexible, efficient statistical monitoring schemes for such models have not been developed. In this paper, we develop likelihood ratio test-based monitoring schemes that are shown to be superior to standard multivariate statistical monitoring schemes. The key challenge in developing likelihood ratio test for the Poisson–multivariate Gaussian mixed models is that the likelihood function can only be calculated by multidimensional numerical integration. We tackle this issue using an approximation of this complex likelihood function.
Journal: International Journal of Production Research
Pages: 6579-6593
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2015.1126373
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1126373
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Template-Type: ReDIF-Article 1.0
Author-Name: Chunlong Yu
Author-X-Name-First: Chunlong
Author-X-Name-Last: Yu
Author-Name: Andrea Matta
Author-X-Name-First: Andrea
Author-X-Name-Last: Matta
Title: A statistical framework of data-driven bottleneck identification in manufacturing systems
Abstract: 
 Data-driven bottleneck identification has received an increasing interest during the recent years. This approach locates the throughput bottleneck of manufacturing systems based on indicators derived from measured machine performance metrics. However, the variability in manufacturing systems may affect the quality of bottleneck indicators, leading to possible inaccurate detection results. This paper presents a statistical framework (SF) to decrease the data-driven detection inaccuracy caused by system variability. Using several statistical tools as building blocks, the proposed SF is able to analyse the logical conditions under which a machine is detected as the bottleneck, and rejects the proposal of bottleneck when no sufficient statistical evidence is collected. A full factorial design experiment is used to study the parameter effects of the SF, and to calibrate the SF. The proposed SF was numerically verified to be effective in decreasing the wrong bottleneck detection rate in serial production lines.
Journal: International Journal of Production Research
Pages: 6317-6332
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2015.1126681
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1126681
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Template-Type: ReDIF-Article 1.0
Author-Name: Kan Wu
Author-X-Name-First: Kan
Author-X-Name-Last: Wu
Author-Name: Ning Zhao
Author-X-Name-First: Ning
Author-X-Name-Last: Zhao
Author-Name: Liang Gao
Author-X-Name-First: Liang
Author-X-Name-Last: Gao
Author-Name: C.K.M. Lee
Author-X-Name-First: C.K.M.
Author-X-Name-Last: Lee
Title: Production control policy for tandem workstations with constant service times and queue time constraints
Abstract: 
 Queue time constraints are commonly imposed to ensure product quality in contemporary production systems. We study the performance of two single stations with deterministic service times and a predetermined time window in between, where both stations suffer time-based pre-emptive breakdowns. To improve productivity, achieving higher capacity and lower rework rate are the two main objectives. While higher capacity requires a higher work-in-process (WIP)-level threshold, a lower rework rate requires a smaller one. To quantify the trade-off between the two objectives, an analytical model is derived. The model is then used to derive the WIP-level threshold control policy for a time-constrained system. We also show that system capacity diminishes with the decrease in WIP-level thresholds.
Journal: International Journal of Production Research
Pages: 6302-6316
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2015.1129468
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1129468
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Template-Type: ReDIF-Article 1.0
Author-Name: Ningxuan Kang
Author-X-Name-First: Ningxuan
Author-X-Name-Last: Kang
Author-Name: Cong Zhao
Author-X-Name-First: Cong
Author-X-Name-Last: Zhao
Author-Name: Jingshan Li
Author-X-Name-First: Jingshan
Author-X-Name-Last: Li
Author-Name: John A. Horst
Author-X-Name-First: John A.
Author-X-Name-Last: Horst
Title: A Hierarchical structure of key performance indicators for operation management and continuous improvement in production systems
Abstract: 
 Key performance indicators (KPIs) are critical for manufacturing operation management and continuous improvement (CI). In modern manufacturing systems, KPIs are defined as a set of metrics to reflect operation performance, such as efficiency, throughput, availability, from productivity, quality and maintenance perspectives. Through continuous monitoring and measurement of KPIs, meaningful quantification and identification of different aspects of operation activities can be obtained, which enable and direct CI efforts. A set of 34 KPIs has been introduced in ISO 22400. However, the KPIs in a manufacturing system are not independent, and they may have intrinsic mutual relationships. The goal of this paper is to introduce a multi-level structure for identification and analysis of KPIs and their intrinsic relationships in production systems. Specifically, through such a hierarchical structure, we define and layer KPIs into levels of basic KPIs, comprehensive KPIs and their supporting metrics, and use it to investigate the relationships and dependencies between KPIs. Such a study can provide a useful tool for manufacturing engineers and managers to measure and utilize KPIs for CI.
Journal: International Journal of Production Research
Pages: 6333-6350
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2015.1136082
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1136082
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingxiao Zhang
Author-X-Name-First: Jingxiao
Author-X-Name-Last: Zhang
Author-Name: Klaus Schmidt
Author-X-Name-First: Klaus
Author-X-Name-Last: Schmidt
Author-Name: Haiyan Xie
Author-X-Name-First: Haiyan
Author-X-Name-Last: Xie
Author-Name: Hui Li
Author-X-Name-First: Hui
Author-X-Name-Last: Li
Title: A new mixed approach for modelling and assessing environmental influences to value co-creation in the construction industry
Abstract: 
 This research studies closely related environmental forces that impact the growth of a company and their respective results of value co-creation in an enterprise (VCCE). With the purpose to coordinate environmental forces and VCCE, this paper presents an innovative mixed model (BP-FA-SD method) using expert grading method, BP neural network, factor analysis and system dynamics. In this BP-FA-SD method, environmental forces are categorised into economic force, cultural force and administrative force. The VCCE value space is mainly divided into social value, symbol value and product value. This research applies an expert grading method to assess the environmental forces of the selected cases, computes the synergy condition using the BP method, and implements the cluster analysis and SD simulation with the FA and SD methods correspondingly. The results of the BP-FA-SD method indicated the positive synchronisation of the development of enterprise forces in the selected construction companies. The findings would help enterprises to find the optimal development paths with synergistic outcomes from the internal and external factors. It further provides a new scheme of the system improvement of the VCCE time-to-performance with the momentum of environmental forces. The research presents a comprehensive instrument for fundamental reconsideration of environmental forces and their influences.
Journal: International Journal of Production Research
Pages: 6548-6562
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1145818
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1145818
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Template-Type: ReDIF-Article 1.0
Author-Name: Timm Ziarnetzky
Author-X-Name-First: Timm
Author-X-Name-Last: Ziarnetzky
Author-Name: Lars Mönch
Author-X-Name-First: Lars
Author-X-Name-Last: Mönch
Title: Incorporating engineering process improvement activities into production planning formulations using a large-scale wafer fab model
Abstract: 
 In most semiconductor wafer fabrication facilities (wafer fabs), both production and engineering lots share the same expensive equipment. Production lots will be shipped to customers whereas engineering lots are used to support production and process development efforts. While production activities might lead to large revenue, engineering activities result in increased future output. In the present paper, we propose three different production planning formulations. The first formulation assumes a reduced available capacity for production due to engineering activities. Costs for production products are minimised. The second formulation is based on the idea that aggregated demand is available for engineering activities for the entire planning window. Costs for production and engineering products are minimised. Learning effects are incorporated to model the capacity increase due to engineering activities. The third model assumes that demand information for engineering activities is available only for the first period. In addition to learning effects, forgetting effects are modelled to provide an incentive to plan releases of engineering lots in later periods. Costs for production and engineering products and forgetting effects are minimised. The performance of the production planning models is assessed using a simulation model of a large-scale wafer fab including specific dispatching strategies to deal with production and engineering lots. The simulation results demonstrate that the second model slightly outperforms the third one when a rolling horizon approach is taken, while the second model provides significantly higher profit than the first one.
Journal: International Journal of Production Research
Pages: 6416-6435
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1151566
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1151566
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Template-Type: ReDIF-Article 1.0
Author-Name: Linhan Ouyang
Author-X-Name-First: Linhan
Author-X-Name-Last: Ouyang
Author-Name: Yizhong Ma
Author-X-Name-First: Yizhong
Author-X-Name-Last: Ma
Author-Name: Jianxiong Chen
Author-X-Name-First: Jianxiong
Author-X-Name-Last: Chen
Author-Name: Zhigang Zeng
Author-X-Name-First: Zhigang
Author-X-Name-Last: Zeng
Author-Name: Yiliu Tu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Tu
Title: Robust optimisation of Nd: YLF laser beam micro-drilling process using Bayesian probabilistic approach
Abstract: 
 Nd: YLF laser beam machining (LBM) process has a great potential to manufacture intricate shaped microproducts with its unique characteristics. Continuous improvement (CI) effort for LBM process is usually realised by response surface methodology, which is an important tool in Design of Six Sigma. However, when determining the optimal machining parameters in CI for LBM process, model parameter uncertainty is typically neglected. Performing worst case analysis in CI, this paper presents a new loss function method that takes model parameter uncertainty into account via Bayesian credible region. Unlike existing CI methods in LBM process, the proposed Bayesian probabilistic approach is based on seemingly unrelated regression which can produce more precise estimations of the model parameters than ordinary least squares in correlated multiple responses problems. An Nd: YLF laser beam micro-drilling process is used to demonstrate the effectiveness of the proposed approach. The comparison results show that micro-holes produced by the proposed approach have better quality than those of existing approaches in terms of robustness and process capability.
Journal: International Journal of Production Research
Pages: 6644-6659
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1154212
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154212
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Template-Type: ReDIF-Article 1.0
Author-Name: Yihai He
Author-X-Name-First: Yihai
Author-X-Name-Last: He
Author-Name: Linbo Wang
Author-X-Name-First: Linbo
Author-X-Name-Last: Wang
Author-Name: Zhenzhen He
Author-X-Name-First: Zhenzhen
Author-X-Name-Last: He
Author-Name: Xun Xiao
Author-X-Name-First: Xun
Author-X-Name-Last: Xiao
Title: Modelling infant failure rate of electromechanical products with multilayered quality variations from manufacturing process
Abstract: 
 The optimisation of product infant failure rate is the most important and difficult task for continuous improvement in manufacturing; how to model the infant failure rate promptly and accurately of the complex electromechanical product in manufacturing is always a dilemma for manufacturers. Traditional methods of reliability analysis for the produced product usually rely on limited test data or field failures, the valuable information of quality variations from the manufacturing process has not been fully utilised. In this paper, a multilayered model structured by ‘part-level, component-level, system-level’ is presented to model the reliability in the form of infant failure rate by quantifying holistic quality variations from manufacturing process for electromechanical products. The mechanism through which the multilayered quality variations affect the infant failure rate is modelled analytically with a positive correlation structure. Furthermore, an integrated failure rate index is derived to model the reliability of electromechanical product in manufacturing by synthetically incorporating overall quality variations with Weibull distribution. A case study on a control board suffering from infant failures in batch production is performed. Results show that the proposed approach could be effective in assessing the infant failure rate and in diagnosing the effectiveness of quality control in manufacturing.
Journal: International Journal of Production Research
Pages: 6594-6612
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1154215
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154215
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Template-Type: ReDIF-Article 1.0
Author-Name: Kostis Taxakis
Author-X-Name-First: Kostis
Author-X-Name-Last: Taxakis
Author-Name: Chrissoleon Papadopoulos
Author-X-Name-First: Chrissoleon
Author-X-Name-Last: Papadopoulos
Title: A design model and a production–distribution and inventory planning model in multi-product supply chain networks
Abstract: 
 Supply chain network (SCN) design implicates decision-making at a strategic level. That includes selecting the right suppliers and determining the number and the location of plants, distribution centres and retailers. An apt design model of the supply chain is imperative for the proper function of the supply chain and consequently for making better operational decisions in an attempt of a continuous improvement. In this paper, we propose two models. The first model is a mixed-integer linear programming model which is concerned with the SCN design problem, whereas the second operational model is a mixed-integer non-linear programming model in respect to the production–distribution and inventory planning problem in a supply chain network. The number of customers and suppliers as well as their demand and capacities are assumed to be known in both models. Two steady-state genetic algorithms were implemented in MATLAB in order to solve both the design and the operational model. The results were compared with GAMS. Some examples were devised in order to demonstrate potential ways of use for the designer of the supply chain network, as well as for the supply chain manager.
Journal: International Journal of Production Research
Pages: 6436-6457
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1158882
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1158882
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Template-Type: ReDIF-Article 1.0
Author-Name: Sanjay Sharma
Author-X-Name-First: Sanjay
Author-X-Name-Last: Sharma
Author-Name: Bharat Sharma
Author-X-Name-First: Bharat
Author-X-Name-Last: Sharma
Title: Optimal selection of application loading on cloud services
Abstract: 
 There is a need for identifying computing power hours and storage utilisation along with total cost optimisation. The present paper focuses on optimal selection of application loading process on the cloud services considering relevant factors. Using this model, small companies that plan to develop applications and use cloud services may determine cost and optimal selection of service by taking into account its own as well as provider’s perspectives into consideration. The paper consists of four stages. First stage deals with the estimation of required computing power hours in the planned duration. Second stage relates to the calculation of storage capacity. Third stage corresponds to the formation of multi objective goal programme to prioritise computing power hours and storage utilisation requirements of applications and optimise total cost of usage. Finally, fourth stage deals with the mixed integer non-linear programming to minimise total cost considering other variable factors. For small application developers who cannot afford in-house IT infrastructure, we find an optimal framework for allocating number of applications on cloud services such as Infrastructure as a Service and Platform as a Service. For ease in planning, the user company can quickly decide corresponding number of applications at appropriate services, and at the same time can reduce overall usage cost. With the help of proposed method, the service provider may keep a suitable inventory of cores to provide backup computing power and storage capacity. This adds value to developers also, as company can plan for their operations corresponding to the business growth.
Journal: International Journal of Production Research
Pages: 6512-6531
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1173256
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173256
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Template-Type: ReDIF-Article 1.0
Author-Name: Qingming Wei
Author-X-Name-First: Qingming
Author-X-Name-Last: Wei
Author-Name: Wenpo Huang
Author-X-Name-First: Wenpo
Author-X-Name-Last: Huang
Author-Name: Wei Jiang
Author-X-Name-First: Wei
Author-X-Name-Last: Jiang
Author-Name: Wenhui Zhao
Author-X-Name-First: Wenhui
Author-X-Name-Last: Zhao
Title: Real-time process monitoring using kernel distances
Abstract: 
 Real-time monitoring is an important task in process control. It often relies on estimation of process parameters in Phase I and Phase II and aims to identify significant differences between the estimates when triggering signals. Real-time contrast (RTC) control charts use classification methods to separate the Phase I and Phase II data and monitor the classification probabilities. However, since the classification probability statistics take discretely distributed values, the corresponding RTC charts become less efficient in the detection ability. In this paper, we propose to use distance-based RTC statistics for process monitoring, which are related to the distance from observations to the classification boundary. We illustrate our idea using the kernel linear discriminant analysis (KLDA) method and develop three distance-based KLDA statistics for RTC monitoring. The performance of the KLDA distance-based charting methods is compared with the classification probability-based control charts. Our results indicate that the distance-based RTC charts are more efficient than the class of probability-based control charts. A real example is used to illustrate the performance of the proposed method.
Journal: International Journal of Production Research
Pages: 6563-6578
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1173257
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173257
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:21:p:6563-6578




Template-Type: ReDIF-Article 1.0
Author-Name: Guo Qing Cheng
Author-X-Name-First: Guo Qing
Author-X-Name-Last: Cheng
Author-Name: Bing Hai Zhou
Author-X-Name-First: Bing Hai
Author-X-Name-Last: Zhou
Author-Name: Ling Li
Author-X-Name-First: Ling
Author-X-Name-Last: Li
Title: Joint optimisation of production rate and preventive maintenance in machining systems
Abstract: 
 This paper studies an integrated control strategy of production and maintenance for a machining system which produces a single type of product to meet the constant demand. Different from previous research, we assume in this study that during the production, the production rate not only influences the life of cutting tool, but also the reliability of the machine. Both the replacement of cutting tool and the preventive maintenance (PM) of machine are considered in this paper. The machine is preventively maintained at the Nth tool replacement or correctively repaired at the machine failure, whichever occurs first. PM and corrective repair may cause shortage which can be reduced by controlling inventory. There are two decision variables p and N, where p denotes the production rate and N denotes the number of cutting tool replacement before the PM is performed. An integrated model is developed to simultaneously determine the optimal production rate and PM policy that minimise the total expected cost per unit item produced. Finally, an illustrative example and sensitivity analysis are given to demonstrate the proposed model.
Journal: International Journal of Production Research
Pages: 6378-6394
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1174343
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1174343
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Template-Type: ReDIF-Article 1.0
Author-Name: Jialing Tao
Author-X-Name-First: Jialing
Author-X-Name-Last: Tao
Author-Name: Kaibo Wang
Author-X-Name-First: Kaibo
Author-X-Name-Last: Wang
Author-Name: Bo Li
Author-X-Name-First: Bo
Author-X-Name-Last: Li
Author-Name: Liang Liu
Author-X-Name-First: Liang
Author-X-Name-Last: Liu
Author-Name: Qi Cai
Author-X-Name-First: Qi
Author-X-Name-Last: Cai
Title: Hierarchical models for the spatial–temporal carbon nanotube height variations
Abstract: 
 Carbon nanotubes (CNTs) are allotropes of carbon with a cylindrical nanostructure. Due to their low production cost and potentially high demand, the large-scale production of CNTs is urgently needed and will be highly profitable. However, quality control will be a great challenge to a large-scale production due to the delicate nature of the production process. Among the problems involved in the quality control of CNT array production, height variation is one of the primary concerns. The objective of this study is to model the height along both the spatial and temporal dimensions, so that the height variations can be controlled during the production process, thus improving the quality and stability of CNT arrays. Specifically, the height variation of the CNT arrays is decomposed into macro-scale and micro-scale variations. The macro-scale variation is modelled by state-space and regression models, and the micro-scale variation is modelled as a spatial process. The models successfully capture both the macro-trends and the micro-patterns. A practical case study shows the effectiveness of the proposed models in terms of goodness of fit and prediction accuracy, and the distinction of the models is summarised to aid in choosing a model to apply to other spatial–temporal data modelling problems.
Journal: International Journal of Production Research
Pages: 6613-6632
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1181809
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1181809
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Template-Type: ReDIF-Article 1.0
Author-Name: Aly Owida
Author-X-Name-First: Aly
Author-X-Name-Last: Owida
Author-Name: P.J. Byrne
Author-X-Name-First: P.J.
Author-X-Name-Last: Byrne
Author-Name: Cathal Heavey
Author-X-Name-First: Cathal
Author-X-Name-Last: Heavey
Author-Name: Paul Blake
Author-X-Name-First: Paul
Author-X-Name-Last: Blake
Author-Name: Khaled S. El-Kilany
Author-X-Name-First: Khaled S.
Author-X-Name-Last: El-Kilany
Title: A simulation based continuous improvement approach for manufacturing based field repair service contracting
Abstract: 
 This paper develops and tests a novel extension to traditional supplier selection practice, with a particular focus on the concluding stages of a manufacturing-based field service. Action-based research was used to design and develop a discrete event simulation decision support for a large multinational manufacturing organisation with a significant after-sales service supply chain. The framework has been designed to identify and validate the value attributable to collaborative supplier contracting with built-in costed performance improvement targets. Use of the framework in the case organisation was found to produce greater cost savings over traditional practice, facilitating extended supply chain contracts. The results provide evidence of the high level of savings achievable while also improving customer delivery through targeted service improvements over the contracts life cycle. This framework advances beyond the prevalent practice of cost-focused short-term adversarial supply contracting and is innovative in terms of its continuous improvement simulation based framework design.
Journal: International Journal of Production Research
Pages: 6458-6477
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1187774
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1187774
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Template-Type: ReDIF-Article 1.0
Author-Name: Yunzhe Qiu
Author-X-Name-First: Yunzhe
Author-X-Name-Last: Qiu
Author-Name: Jie Song
Author-X-Name-First: Jie
Author-X-Name-Last: Song
Author-Name: Zekun Liu
Author-X-Name-First: Zekun
Author-X-Name-Last: Liu
Title: A simulation optimisation on the hierarchical health care delivery system patient flow based on multi-fidelity models
Abstract: 
 The mismatching patient flow distribution in the health care system in urban China is a great social issue that attracts lots of public attention. In this research, we propose a simulation-based optimisation method using the multi-fidelity optimisation with ordinal transformation (OT) and optimal sampling (OS) (MO2TOS$ \mathrm MO ^2\mathrm{TOS} $) algorithm to evaluate the patient flow distribution, so as to continuously improve the hierarchical health care service system. The low-fidelity model applying the queueing network theory is constructed for the OT part of the MO2TOS$ \mathrm MO ^2\mathrm{TOS} $, followed by a high-fidelity but time-consuming discrete event simulation model for the OS part. An empirical study on the background of the hierarchical health care delivery system in China is presented, where the proposed MO2TOS$ \mathrm MO ^2\mathrm{TOS} $ method is implemented to optimise the system profit by guiding the patient flow distribution. A comparison with other widely used simulation optimisation methods sustains the efficacy of the MO2TOS$ \mathrm MO ^2\mathrm{TOS} $ with the evidence that acquiring effective information from the low-fidelity model indeed retrenches the computing budget used to explore the feasible domain.
Journal: International Journal of Production Research
Pages: 6478-6493
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1197437
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1197437
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhiyang Jia
Author-X-Name-First: Zhiyang
Author-X-Name-Last: Jia
Author-Name: Liang Zhang
Author-X-Name-First: Liang
Author-X-Name-Last: Zhang
Author-Name: Jorge Arinez
Author-X-Name-First: Jorge
Author-X-Name-Last: Arinez
Author-Name: Guoxian Xiao
Author-X-Name-First: Guoxian
Author-X-Name-Last: Xiao
Title: Performance analysis for serial production lines with Bernoulli Machines and Real-time WIP-based Machine switch-on/off control
Abstract: 
 In recent years, achieving high energy efficiency has become one of the primary goals in manufacturing, along with maintaining high productivity and quality. In many manufacturing systems, it is sometimes possible to temporarily switch off a machine to reserve energy, and switch it back on when a certain condition is met. Indeed, production control-based shop floor continuous improvement is recognised as one of the most cost-effective ways to achieve energy-efficient production. In this paper, we study serial production lines with Bernoulli machines and finite capacity buffers and assume that some of the machines in the line can be switched on and off during the production process according to a state-based feedback control policy. Mathematical models for the system under consideration are derived and analytical methods are developed for calculating the system performance measures during transients. Specifically, exact Markovian analysis is used for two- and three-machine lines in which the switch-on/off operations of only one machine is considered. For longer lines, the switch-on/off operations of multiple machines are considered and an aggregation-based approximation approach is applied to evaluate the system performance measures. Numerical experiments show that the method developed can be used to efficiently calculate the system’s performance with high accuracy.
Journal: International Journal of Production Research
Pages: 6285-6301
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1197438
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1197438
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingyi Zhang
Author-X-Name-First: Jingyi
Author-X-Name-Last: Zhang
Author-Name: Chao Lu
Author-X-Name-First: Chao
Author-X-Name-Last: Lu
Author-Name: Jie Song
Author-X-Name-First: Jie
Author-X-Name-Last: Song
Title: Dynamic performance-based automatic generation control unit allocation with frequency sensitivity identification
Abstract: 
 With the alteration of energy structures in power system, the allocation of automatic generation control (AGC) is facing new challenges. The emergence of high penetration of manufacturing sectors and renewable energy sources has increased the demand for faster-ramping resources to participate in the frequency regulation service. Additionally, the current regulation service does not properly arrange the output of the resources considering the actual performance while they follow the AGC allocation signals, which affects the accuracy of frequency regulation. The fast-ramping capacity and response accuracy of AGC units are supposed to be considered in the dispatch. Meanwhile, the power outputs of different governors have different impacts on the system frequency, which has important guiding significance for the AGC dispatch. With the purpose of improving frequency regulation service, this paper proposes a dynamic performance-based dispatch model considering the above issues. We first prove that there is a linear relation between the output of the generators and system frequency, defined as frequency sensitivity. Then, the frequency sensitivity of each generator can be identified using the least square (LS) method. Furthermore, a dynamic multi-objective optimization allocation model is established, which considers the units’ economy, ramping capacity and accuracy. Finally, the proposed identification method and allocation model are simulated in the IEEE-9 bus system, and the simulation results verify their validity and feasibility
Journal: International Journal of Production Research
Pages: 6532-6547
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1201602
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1201602
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Template-Type: ReDIF-Article 1.0
Author-Name: Athanassios Manatos
Author-X-Name-First: Athanassios
Author-X-Name-Last: Manatos
Author-Name: Vasilis P. Koutras
Author-X-Name-First: Vasilis P.
Author-X-Name-Last: Koutras
Author-Name: Agapios N. Platis
Author-X-Name-First: Agapios N.
Author-X-Name-Last: Platis
Title: Dependability and performance stochastic modelling of a two-unit repairable production system with preventive maintenance
Abstract: 
 In this paper, a two-unit multistate repairable production system is considered in which preventive maintenance (PM) is implemented in order to improve its dependability and performance. A general model is provided for the production system using a semi-Markov process, for examining system’s limiting behaviour. Apart from combining redundancy with PM, we introduce scenarios like imperfect and failed maintenance which are usually met in real life production systems. For the proposed model, we calculate the availability, the mean time to failure and the total operational cost and we formulate optimisation problems settled with respect to the system’s inspection times. The main aim of our work is to determine the optimal inspection times and consequently the optimal PM policies to be adopted in order to optimise system’s dependability and performance.
Journal: International Journal of Production Research
Pages: 6395-6415
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1201603
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1201603
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Template-Type: ReDIF-Article 1.0
Author-Name: Kun-Tzu Yu
Author-X-Name-First: Kun-Tzu
Author-X-Name-Last: Yu
Author-Name: Kuen-Suan Chen
Author-X-Name-First: Kuen-Suan
Author-X-Name-Last: Chen
Title: Testing and analysing capability performance for products with multiple characteristics
Abstract: 
 Process capability analysis is a vital part of an overall quality improvement programme. Numerous techniques and tools have been proposed for process capability analysis. Among these, indices and charts of process capability are simple and effective tools and widely used in the manufacturing industry. Many scholars have revealed numerous valuable aspects of previously developed tools and methods. Due to the rising demands of product quality, the current tools and methods are insufficient for enabling managers to make informed decisions. To address this gap, this study proposes a hypothesis testing procedure which determines whether the process capabilities satisfy the target level. Furthermore, this study proposes an integrated quality test chart (IQTC), which can display the process potential and performance for an entire product with smaller-the-better, larger-the-better and nominal-the-best specifications. The proposed procedure and IQTC incorporate the quality-level concept of the Six Sigma model and can be used to quantitate the relationships among the quality level, capability indices and process yield. They can be applied to assist managers in measuring, monitoring, analysing and improving process performance in a timely manner which will help ensure that the quality levels of their products meet customer demands. Finally, an example is provided to illustrate how to use the proposed procedure and IQTC.
Journal: International Journal of Production Research
Pages: 6633-6643
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1203469
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1203469
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Template-Type: ReDIF-Article 1.0
Author-Name: Hainan Guo
Author-X-Name-First: Hainan
Author-X-Name-Last: Guo
Author-Name: David Goldsman
Author-X-Name-First: David
Author-X-Name-Last: Goldsman
Author-Name: Kwok-Leung Tsui
Author-X-Name-First: Kwok-Leung
Author-X-Name-Last: Tsui
Author-Name: Yu Zhou
Author-X-Name-First: Yu
Author-X-Name-Last: Zhou
Author-Name: Shui-Yee Wong
Author-X-Name-First: Shui-Yee
Author-X-Name-Last: Wong
Title: Using simulation and optimisation to characterise durations of emergency department service times with incomplete data
Abstract: 
 Simulation models of emergency departments (EDs) are often built based on incomplete data, for example, missing arrival times or service-time durations. The difficulty in collecting reliable and complete data can subsequently lead to invalid simulation results. To tackle this problem, we propose a simulation and optimisation method to characterise the unavailable durations of service times. Since many services in an ED are sequential and dependent on each other, this paper considers these multiple process steps cooperatively. We first use lognormal distributions to characterise the key service durations. Then we propose a new meta-heuristic approach, which combines an Improved Adaptive Genetic Algorithm (AGA) and Simulated Annealing (SA), IAGASA, to search for the optimal set of service-time distribution parameters. To address the difficulties of applying IAGASA when noise is involved in the performance measures and improve the simulation efficiency, we jointly apply IAGASA and Optimal Computing Budget Allocation (OCBA) technology. OCBA minimises the total simulation cost for achieving a desired level of probability of correctly selecting the best set of distribution parameters, which improves the search efficiency significantly. The experimental results indicate that our proposed method can find accurate estimates of service-time distribution parameters within a relatively short time.
Journal: International Journal of Production Research
Pages: 6494-6511
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1205760
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1205760
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:21:p:6494-6511




Template-Type: ReDIF-Article 1.0
Author-Name: Jingshan Li
Author-X-Name-First: Jingshan
Author-X-Name-Last: Li
Author-Name: Chrissoleon T. Papadopoulos
Author-X-Name-First: Chrissoleon T.
Author-X-Name-Last: Papadopoulos
Author-Name: Liang Zhang
Author-X-Name-First: Liang
Author-X-Name-Last: Zhang
Title: Continuous improvement in manufacturing and service systems
Journal: International Journal of Production Research
Pages: 6281-6284
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1228235
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1228235
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: (i)-(i)
Issue: 21
Volume: 54
Year: 2016
Month: 11
X-DOI: 10.1080/00207543.2016.1236524
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1236524
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:21:p:(i)-(i)




Template-Type: ReDIF-Article 1.0
Author-Name: Véronique Nabelsi
Author-X-Name-First: Véronique
Author-X-Name-Last: Nabelsi
Author-Name: Stéphane Gagnon
Author-X-Name-First: Stéphane
Author-X-Name-Last: Gagnon
Title: Information technology strategy for a patient-oriented, lean, and agile integration of hospital pharmacy and medical equipment supply chains
Abstract: 
 Both public and private hospitals are increasingly under pressure to reduce costs while improving patient care across all medical disciplines and departments. Hospitals must become patient-oriented, lean, and agile in order to properly realign and integrate health care processes, helping to reconcile efficiency imperatives with patient needs and hospital mission. One of the highest potential for improvement can be found in supply chain management (SCM) practices for medical supplies, which often represent more than 40% of a hospital’s operating budget. We report on 3 case studies of business process management and reengineering projects, relying on advanced information technology, focused on the supply chains of two major urban hospitals, involving $2 million in minimum stocks for drug inventory. Case study 1 deals with an in-depth analysis of SCM practices around a key medical asset in pharmaceutical supply, i.e. infusion pumps. Case study 2 builds upon the findings of case 1, and proposes an radio-frequency identification solution to support a new hospital-wide asset location process and system, aiming for just-in-time availability of infusion pumps for critical drugs administration. Case study 3 complements cases 1 and 2 by analysing the feasibility of integrating the various components of the hospital pharmacy inventories, which in turn could be integrated to asset location systems. Our 3 case studies lead us to a number of conclusions on how hospitals can develop a patient-oriented, agile, and lean perspectives and practices, as well as ensure the proper integration of patient needs within optimised supply chains.
Journal: International Journal of Production Research
Pages: 3929-3945
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1218082
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1218082
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Template-Type: ReDIF-Article 1.0
Author-Name: Yonit Barron
Author-X-Name-First: Yonit
Author-X-Name-Last: Barron
Author-Name: Dror Hermel
Author-X-Name-First: Dror
Author-X-Name-Last: Hermel
Title: Shortage decision policies for a fluid production model with MAP arrivals
Abstract: 
 We consider on a continuous production/inventory process where a single machine produces a certain product into a finite buffer. The demands arrive according to a Markov Additive Process governed by a continuous-time Markov chain, and their sizes are independent and have phase-type distributions depending on the type of arrival. Two shortage policies are considered: the backorder policy, in which any demand that cannot be satisfied immediately is backlogged, and the order policy, in which any demand that cannot be satisfied immediately is supplied (alternatively, the latter policy can be considered as lost sales). We assume that the total cost includes a production loss cost, a penalty cost, a fixed cost for an order and a variable cost for the ordered amount. By applying the regenerative theory, we use tools from the exit-time theorem for fluid processes to obtain the discounted cost functionals under both policies. In addition, the models are extended to include a non-zero safety stock. Numerical examples, sensitivity analysis and comparative study are included.
Journal: International Journal of Production Research
Pages: 3946-3969
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1218083
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1218083
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:14:p:3946-3969




Template-Type: ReDIF-Article 1.0
Author-Name: Yanyan Yang
Author-X-Name-First: Yanyan
Author-X-Name-Last: Yang
Author-Name: Shenle Pan
Author-X-Name-First: Shenle
Author-X-Name-Last: Pan
Author-Name: Eric Ballot
Author-X-Name-First: Eric
Author-X-Name-Last: Ballot
Title: Mitigating supply chain disruptions through interconnected logistics services in the Physical Internet
Abstract: 
 This paper investigates the resilience of inventory models using interconnected logistics services in the Physical Internet (PI). With traditional supply chain network design, companies define and optimise their own logistics networks, resulting in current logistics systems being a set of independent heterogeneous logistics networks. The concept of PI aims to integrate independent logistics networks into a global, open, interconnected system. Prior research has shown that new inventory models enabled by and applied to PI could help reduce inventory levels thanks to its high flexibility. Continuing along these lines, this paper examines how inventory models applying PI deal with disruptions at hubs and plants. To attain this, a single product inventory problem with uncertain demands and stochastic supply disruptions is studied. A simulation-based optimisation model is proposed to determine inventory control decisions. The results suggest that the PI inventory model, with greater agility and flexibility, outperforms the current classic inventory models in terms of resilience. Moreover, the difference in performance increases when the product value, penalty costs and disruption frequency increases. This paper indicates a novel approach to build a resilient supply network.
Journal: International Journal of Production Research
Pages: 3970-3983
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1223379
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1223379
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Template-Type: ReDIF-Article 1.0
Author-Name: Yue Zhai
Author-X-Name-First: Yue
Author-X-Name-Last: Zhai
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Author-Name: Zhi Li
Author-X-Name-First: Zhi
Author-X-Name-Last: Li
Author-Name: George Huang
Author-X-Name-First: George
Author-X-Name-Last: Huang
Title: Production lead-time hedging and coordination in prefabricated construction supply chain management
Abstract: 
 This paper studies a coordination scheme to solve a production lead-time hedging (PLTH) issue in the prefabricated construction supply chain management. To mitigate tardiness delivery owing to prefab production uncertainty, the project contractor (PC) prefers to inform the prefab factory (PF) an earlier due date which is termed as PLTH strategy. However, this strategy forces the PF to compress its production process. A balance must be optimised through the proposed PLTH coordination scheme. It includes a PLTH-related cost term, i.e. crashing money (charged by the PF to the PC) and a constant transfer term. Three models with different power structures are considered. Firstly, two Stackelberg games with alternative decision-making sequences and an equal power model are discussed to obtain the optimal PLTH amount and crashing money. Later on, a cost-sharing term is used to fairly allocate the system surplus. It is observed that this coordination scheme reduces the PLTH amount and ensures win–win coordination for both parties. Some interesting managerial implications are also obtained from comparison analysis and numerical studies.
Journal: International Journal of Production Research
Pages: 3984-4002
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1231432
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1231432
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianhua Lin
Author-X-Name-First: Jianhua
Author-X-Name-Last: Lin
Author-Name: Min Liu
Author-X-Name-First: Min
Author-X-Name-Last: Liu
Author-Name: Jinghua Hao
Author-X-Name-First: Jinghua
Author-X-Name-Last: Hao
Author-Name: Peng Gu
Author-X-Name-First: Peng
Author-X-Name-Last: Gu
Title: Many-objective harmony search for integrated order planning in steelmaking-continuous casting-hot rolling production of multi-plants
Abstract: 
 This paper investigates a challenging problem of integrated order planning (IOP) in steelmaking-continuous casting-hot rolling production of multiple plants with consideration of four conflicting objectives. The objective functions refer to the earliness/tardiness ratio, the non-hot charge ratio and the imbalance ratio of production capacity utilisation corresponding to SCC plants and HR Plants. The IOP guided by the integration strategy, which includes the vertical integration of production stages and the horizontal integration of steel plants, is regarded as a large-scale many-objective optimisation problem. To deal with the difficulty of large-scale decision variables, we introduce a new concept named ‘order-set’ for modelling. In addition, a novel knee point-driven many-objective global-best harmony search (KGHS) algorithm, mainly integrating a KGHS process and a new knee point-driven Pareto optimisation, is developed to tackle this many-objective problem. The proposed model and algorithm were tested with benchmarks and real production data. Experiments demonstrate that the proposed approach generates effective solutions superior to those generated by the other popular many-objective optimisation methods.
Journal: International Journal of Production Research
Pages: 4003-4020
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1232498
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1232498
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Template-Type: ReDIF-Article 1.0
Author-Name: Danijela Pjevcevic
Author-X-Name-First: Danijela
Author-X-Name-Last: Pjevcevic
Author-Name: Milos Nikolic
Author-X-Name-First: Milos
Author-X-Name-Last: Nikolic
Author-Name: Natasa Vidic
Author-X-Name-First: Natasa
Author-X-Name-Last: Vidic
Author-Name: Katarina Vukadinovic
Author-X-Name-First: Katarina
Author-X-Name-Last: Vukadinovic
Title: Data envelopment analysis of AGV fleet sizing at a port container terminal
Abstract: 
 A decision-making approach based on Data Envelopment Analysis (DEA) for determining the efficient container handling processes (considering the number of employed Automated Guided Vehicles (AGVs)) at a port container terminal (PCT) is presented in this paper. Containers are unloaded from the ship by quay cranes and transported to the storage area by AGVs. We defined performance measures of proposed container handling processes and analysed the effects when changing the number of AGVs. The values of performance measures were collected and/or calculated from simulation. Container handling process, with a fixed number of quay cranes, when a different number of AGVs is used to transport containers from berth to assigned locations within storage area, represents a decision-making unit (DMU). We applied the basic CCR (Charnes, Cooper and Rhodes) DEA model with two inputs: average ship operating delay costs and average operating costs of employed equipment at a PCT, and two outputs: average number of handled import containers per ship and weighted average utilisation rate of equipment at a PCT. DEA method proved to be useful when testing different DMUs and when determining efficient DMUs for planning purposes. This study shows that efficiency evaluation of AGV fleet sizing and operations is useful for planning purposes at PCTs.
Journal: International Journal of Production Research
Pages: 4021-4034
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1241445
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1241445
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Template-Type: ReDIF-Article 1.0
Author-Name: King-Wah Pang
Author-X-Name-First: King-Wah
Author-X-Name-Last: Pang
Author-Name: Hau-Ling Chan
Author-X-Name-First: Hau-Ling
Author-X-Name-Last: Chan
Title: Data mining-based algorithm for storage location assignment in a randomised warehouse
Abstract: 
 Data mining has long been applied in information extraction for a wide range of applications such as customer relationship management in marketing. In the retailing industry, this technique is used to extract the consumers buying behaviour when customers frequently purchase similar products together; in warehousing, it is also beneficial to store these correlated products nearby so as to reduce the order picking operating time and cost. In this paper, we present a data mining-based algorithm for storage location assignment of piece picking items in a randomised picker-to-parts warehouse by extracting and analysing the association relationships between different products in customer orders. The algorithm aims at minimising the total travel distances for both put-away and order picking operations. Extensive computational experiments based on synthetic data that simulates the operations of a computer and networking products spare parts warehouse in Hong Kong have been conducted to test the effectiveness and applicability of the proposed algorithm. Results show that our proposed algorithm is more efficient than the closest open location and purely dedicated storage allocation systems in minimising the total travel distances. The proposed storage allocation algorithm is further evaluated with experiments simulating larger scale warehouse operations. Similar results on the performance comparison among the three storage approaches are observed. It supports the proposed storage allocation algorithm and is applicable to improve the warehousing operation efficiency if items have strong association among each other.
Journal: International Journal of Production Research
Pages: 4035-4052
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1244615
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1244615
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Template-Type: ReDIF-Article 1.0
Author-Name: Borja Ponte
Author-X-Name-First: Borja
Author-X-Name-Last: Ponte
Author-Name: Xun Wang
Author-X-Name-First: Xun
Author-X-Name-Last: Wang
Author-Name: David de la Fuente
Author-X-Name-First: David
Author-X-Name-Last: de la Fuente
Author-Name: Stephen M. Disney
Author-X-Name-First: Stephen M.
Author-X-Name-Last: Disney
Title: Exploring nonlinear supply chains: the dynamics of capacity constraints
Abstract: 
 While most supply chain models assume linearity, real production and distribution systems often operate in constrained contexts. This article aims to analyse the consequences of capacity limits in the order-up-to replenishment policy with minimum mean squared error forecasting under independently and identically distributed random demand. Our study shows that the impact of this nonlinearity is often significant and should not be ignored. In this regard, we introduce the concept of a settling capacity, which informs when our knowledge from a linear analysis is a reasonable approximation in a nonlinear context. If the available capacity is less than the settling capacity, the nonlinear effects can have a significant impact. We compare the Bullwhip Effect and Fill Rate in constrained contexts to well-established results for linear supply chains. We reveal the capacity limit acts as a production smoothing mechanism, at the expense of increasing inventory variability. We proceed to analyse the economic consequences of the capacity constraint and show that it can actually reduce costs. We provide an approximate solution for determining the optimal capacity depending on the demand, the unit costs and the lead time.
Journal: International Journal of Production Research
Pages: 4053-4067
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1245884
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1245884
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:14:p:4053-4067




Template-Type: ReDIF-Article 1.0
Author-Name: Siraj K. Zahran
Author-X-Name-First: Siraj K.
Author-X-Name-Last: Zahran
Author-Name: Mohamad Y. Jaber
Author-X-Name-First: Mohamad Y.
Author-X-Name-Last: Jaber
Author-Name: Simone Zanoni
Author-X-Name-First: Simone
Author-X-Name-Last: Zanoni
Title: Comparing different coordination scenarios in a three-level supply chain system
Abstract: 
 The consignment stock (CS) policy, independently or coupled with vendor managed inventory (VMI), has been practised by businesses and shown to be profitable. It helps to reduce or eliminate out-of-stock instances caused by fluctuations in demand. CS brings several benefits to collaborating parties. Unlike the two-level supply chain models in the literature, this paper considers a three-level supply chain that consists of a supplier, a vendor and a buyer with CS policy agreements. The paper also examines four coordination scenarios (a combination of traditional and CS) in conjunction with a payment scheme between adjacent parties. Nine coordination cases (models) are provided. A sensitivity analysis is performed to study the effects of some parameters on the performance of the developed models. Most of the results showed that a combination of traditional and CS policies returned a higher total system profit.
Journal: International Journal of Production Research
Pages: 4068-4088
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1249431
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1249431
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Template-Type: ReDIF-Article 1.0
Author-Name: Dong-Hui Yang
Author-X-Name-First: Dong-Hui
Author-X-Name-Last: Yang
Author-Name: Xing Gao
Author-X-Name-First: Xing
Author-X-Name-Last: Gao
Title: Online retailer recommender systems: a competitive analysis
Abstract: 
 As thriving and fast-moving technologies, recommender systems have been widely adopted by online retailers to increase their sales recently. This has significant impacts on the stakeholders in the online supply chain. How an online retailer uses recommender systems to maximise its profit through choosing different recommendation strategies for two upstream competing manufacturers is explored in this paper. In particular, a game between one online retailer and two competitive manufacturers is constructed in which these manufacturers can be selectively and strategically recommended by the retailer. The analytical results show that as the recommendation strength of recommender systems increases, neither manufacturers nor the retailer can always enjoy higher profits, which is counterintuitive. Furthermore, this study reveals that (i) a recommended manufacturer may enjoy a higher profit through sharing the recommendation market with its rival than through monopolising this market; (ii) recommending two manufacturers in both is the most feasible way for the online retailer to benefit from controlling the supply chain. Finally, it is interesting that recommender systems are found to be good mechanisms to help to coordinate the online supply chain with one retailer and two manufacturers because the recommendation market generated by recommender systems alleviates channel conflict.
Journal: International Journal of Production Research
Pages: 4089-4109
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1253888
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1253888
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaobing Li
Author-X-Name-First: Xiaobing
Author-X-Name-Last: Li
Author-Name: Zhen He
Author-X-Name-First: Zhen
Author-X-Name-Last: He
Title: Determining importance ratings of patients’ requirements with multi-granular linguistic evaluation information
Abstract: 
 Determination of patients’ requirements (PRs) importance is a critical issue of medical service design. Quality function deployment (QFD) is one of the very effective customer-driven quality system tools typically applied to fulfil PRs. Often the patients cannot easily express their judgements on PRs’ importance with exact numerical values, and they usually present their judgements in different scales. Therefore, this paper aims at providing a systematic method to simultaneously deal with PRs’ fuzziness and multi-granularity in the QFD. Compared to previous research, its contribution is threefold. First, it proposes use of the 2-tuple linguistic model which can effectively manage the imprecise and vague evaluation information in QFD because of its accuracy and no information loss. Second, it develops a new 2-tuple transformation function to solve the unification problem of multi-granular linguistic judgements in QFD. Third, it proposes a qualitative approach to deal with uncertainty existed extensively in establishing modified factors. Finally, a practical case of hospital PRs is provided to illustrate its feasibility and effectiveness of the proposed methodology.
Journal: International Journal of Production Research
Pages: 4110-4122
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1253890
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1253890
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Template-Type: ReDIF-Article 1.0
Author-Name: Hsien-Jen Lin
Author-X-Name-First: Hsien-Jen
Author-X-Name-Last: Lin
Title: Two-critical-number control policy for a stochastic production inventory system with partial backlogging
Abstract: 
 This paper deals with a production–inventory control model with partial backlogging, in which a reflected Brownian motion governs the inventory level variation. We consider a single storage facility with infinite capacity and assume that shortages are allowed and the total amount of stock-out is a mixture of backordering and lost sales. In addition, the production facility is controlled by a two-parameter (m, M) policy, which switches the production rate when the inventory level reaches the threshold values. The aim is to determine the optimal control parameters m and M by minimising the long-run total expected cost of the system. Some results are illustrated using numerical examples. A sensitivity analysis of the optimal solution with respect to major parameters is also carried out.
Journal: International Journal of Production Research
Pages: 4123-4135
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1254353
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1254353
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Template-Type: ReDIF-Article 1.0
Author-Name: Dirk Werthmann
Author-X-Name-First: Dirk
Author-X-Name-Last: Werthmann
Author-Name: Dennis Brandwein
Author-X-Name-First: Dennis
Author-X-Name-Last: Brandwein
Author-Name: Carmen Ruthenbeck
Author-X-Name-First: Carmen
Author-X-Name-Last: Ruthenbeck
Author-Name: Bernd Scholz-Reiter
Author-X-Name-First: Bernd
Author-X-Name-Last: Scholz-Reiter
Author-Name: Michael Freitag
Author-X-Name-First: Michael
Author-X-Name-Last: Freitag
Title: Towards a standardised information exchange within finished vehicle logistics based on RFID and EPCIS
Abstract: 
 Finished vehicle logistics is facing different challenges. In order to cope with these challenges this article presents a case study, analysing a concept to improve finished vehicle logistics using radio frequency identification (RFID)-based and electronic product code information services (EPCIS). Within this case study, vehicles were identified automatically by RFID. For sharing, the information generated by RFID the EPCIS-based InfoBroker was developed according to the needs of the automotive industry. By having data available through the InfoBroker, decision support systems (DSS) can make planning and control of finished vehicle logistics decisions more efficiently. The case study was executed within two finished vehicle logistics cases. Based on this article practitioners can estimate the potentials of RFID and EPCIS for finished vehicle logistics. Based on the data made accessible by the presented concept practitioners and researches can develop innovative DSS to improve finished vehicle logistics
Journal: International Journal of Production Research
Pages: 4136-4152
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1254354
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1254354
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Template-Type: ReDIF-Article 1.0
Author-Name: Anna V. Kitaeva
Author-X-Name-First: Anna V.
Author-X-Name-Last: Kitaeva
Author-Name: Alexandra O. Zhukovskaya
Author-X-Name-First: Alexandra O.
Author-X-Name-Last: Zhukovskaya
Author-Name: Oleg A. Zmeev
Author-X-Name-First: Oleg A.
Author-X-Name-Last: Zmeev
Title: Compound Poisson demand with price-dependent intensity for fast moving items: price optimisation and parameters estimation
Abstract: 
 We consider a single-period single-item inventory system. The demand is a compound Poisson process with price-dependent intensity and continuous batch size distribution. The intensity of the customers’ arrivals is sufficiently high to use a diffusion approximation of the demand process. Equations for retail price maximising of an expected profit with the optimal order quantity are obtained and an approximate solution is proposed. Numerical results illustrating the percentage of the increase in profit for linear price-intensity dependence are given. An approximate distribution of the selling time of a large order is obtained. Demand parameters estimation procedures based on two censored samples – the observed selling durations and demands – are discussed.
Journal: International Journal of Production Research
Pages: 4153-4163
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1257168
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1257168
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Template-Type: ReDIF-Article 1.0
Author-Name: Erinc Albey
Author-X-Name-First: Erinc
Author-X-Name-Last: Albey
Author-Name: Ümit Bilge
Author-X-Name-First: Ümit
Author-X-Name-Last: Bilge
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Title: Multi-dimensional clearing functions for aggregate capacity modelling in multi-stage production systems
Abstract: 
 Nonlinear clearing functions have been proposed in the literature as metamodels to represent the behaviour of production resources that can be embedded in optimisation models for production planning. However, most clearing functions tested to date use a single-state variable to represent aggregate system workload over all products, which performs poorly when product mix affects system throughput. Clearing functions using multiple-state variables have shown promise, but require significant computational effort to fit the functions and to solve the resulting optimisation models. This paper examines the impact of aggregation in state variables on solution time and quality in multi-item multi-stage production systems with differing degrees of manufacturing flexibility. We propose multi-dimensional clearing functions using alternative aggregations of state variables, and evaluate their performance in computational experiments. We find that at low utilisation, aggregation of state variables has little effect on system performance; multi-dimensional clearing functions outperform single-dimensional ones in general; and increasing manufacturing flexibility allows the use of aggregate clearing functions with little loss of solution quality.
Journal: International Journal of Production Research
Pages: 4164-4179
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1257169
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1257169
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Template-Type: ReDIF-Article 1.0
Author-Name: Dilupa Nakandala
Author-X-Name-First: Dilupa
Author-X-Name-Last: Nakandala
Author-Name: Henry Lau
Author-X-Name-First: Henry
Author-X-Name-Last: Lau
Author-Name: Li Zhao
Author-X-Name-First: Li
Author-X-Name-Last: Zhao
Title: Development of a hybrid fresh food supply chain risk assessment model
Abstract: 
 Supply chain managers and scholars recognise the importance of managing supply chain risk, especially in fresh food supply chain due to the perishable nature and short life cycle of products. Supply chain risk management consists of supply chain risk assessment, risk evaluation and formulation and implementation of effective risk response strategies. The commonly adopted qualitative methods such as risk assessment matrix to determine the level of risk have limitations. This paper proposes a hybrid model comprising both fuzzy logic (FL) and hierarchical holographic modelling (HHM) techniques where risk is first identified by the HHM method and then assessed using both qualitative risk assessment model (named risk filtering, ranking and management Framework) and fuzzy-based risk assessment method (named FL approach). The risk assessment results by the two different approaches are compared, and the overall risk level of each risk is calculated using the Root Mean Square calculation before identifying response strategies. This novel approach takes advantage of the benefits of both techniques and offsets their drawbacks in certain aspects. A case study in a fresh food supply chain company has been conducted in order to validate the proposed integrated approach on the feasibility of its functionality in a real environment.
Journal: International Journal of Production Research
Pages: 4180-4195
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1267413
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1267413
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Template-Type: ReDIF-Article 1.0
Author-Name: Wantao Yu
Author-X-Name-First: Wantao
Author-X-Name-Last: Yu
Author-Name: Mark A. Jacobs
Author-X-Name-First: Mark A.
Author-X-Name-Last: Jacobs
Author-Name: Roberto Chavez
Author-X-Name-First: Roberto
Author-X-Name-Last: Chavez
Author-Name: Mengying Feng
Author-X-Name-First: Mengying
Author-X-Name-Last: Feng
Title: The impacts of IT capability and marketing capability on supply chain integration: a resource-based perspective
Abstract: 
 Although previous research has addressed the interface and logical association among marketing, information technology (IT) and supply chain management, there have been few, if any, attempts to investigate how IT capability and marketing capability influence supply chain integration (SCI). Thus, this study investigates the direct and interacting effects of IT capability and marketing capability on SCI. The hypothesised relationships were tested using survey data gathered from 329 firms in China’s manufacturing industry. The results reveal that both IT capability and marketing capability have a significant positive effect on SCI. Interestingly, no significant interaction effect was found, indicating that marketing IT capability and marketing capability influence SCI independently, and not synergistically. However, while IT capability and marketing capability do not interact, IT capability does mediate the impact of marketing capability on SCI.
Journal: International Journal of Production Research
Pages: 4196-4211
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1275874
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1275874
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiang Zhong
Author-X-Name-First: Xiang
Author-X-Name-Last: Zhong
Author-Name: Hyo Kyung Lee
Author-X-Name-First: Hyo Kyung
Author-X-Name-Last: Lee
Author-Name: Jingshan Li
Author-X-Name-First: Jingshan
Author-X-Name-Last: Li
Title: From production systems to health care delivery systems: a retrospective look on similarities, difficulties and opportunities
Abstract: 
 Manufacturing systems have attracted substantial research attentions during the last 50 years. In recent years, there has been growing interest in health care systems research to improve efficiency, safety and care quality. The similarities identified between manufacturing systems and health care delivery systems heighten the importance of transferring the experience and knowledge in manufacturing to health care. In this paper, based on the lessons we learned and the experience we obtained during our journey from production systems research to health care delivery systems study, we discuss the similarities between production systems and health care delivery systems in system modelling, design, performance evaluation and continuous improvements and investigate the differences and difficulties that stem from variability, constraints, dynamics and human behaviour. Building upon these, the opportunities encompassing care operations, planning and scheduling, patient transitions, and safety and teamwork in health care delivery systems are discussed. Finally, the challenges and future directions are proposed. We expect this work to serve as a catalyst to stimulate more in-depth and comprehensive studies.
Journal: International Journal of Production Research
Pages: 4212-4227
Issue: 14
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1277276
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1277276
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Template-Type: ReDIF-Article 1.0
Author-Name: Junhai Ma
Author-X-Name-First: Junhai
Author-X-Name-Last: Ma
Author-Name: Xiaogang Ma
Author-X-Name-First: Xiaogang
Author-X-Name-Last: Ma
Title: Measure of the bullwhip effect considering the market competition between two retailers
Abstract: 
 In order to consider the market competition, a new supply chain with one supplier and two retailers is established in this paper. Two retailers employ different AR(1) demand processes, respectively, and an order-up-to inventory policy characterises the inventory decisions. The bullwhip effect in this supply chain is measured under the moving average forecasting technique. We investigate the effects of the lead time, the span of forecast, market competition and the consistency of demand volatility on the bullwhip effect using the algebraic analysis and numerical simulation. Conclusions indicate that different factors lead to the bullwhip effect following different patterns in the supply chain. Moreover, some suggestions are present to help managers to control parameters that yield the lower bullwhip effect.
Journal: International Journal of Production Research
Pages: 313-326
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1154996
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154996
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Template-Type: ReDIF-Article 1.0
Author-Name: Subir S. Rao
Author-X-Name-First: Subir S.
Author-X-Name-Last: Rao
Author-Name: Gajendra K. Adil
Author-X-Name-First: Gajendra K.
Author-X-Name-Last: Adil
Title: Analytical models for a new turnover-based hybrid storage policy in unit-load warehouses
Abstract: 
 This paper considers a low-level unit-load warehouse employing single-deep storage lanes and a single-command manual storage and retrieval policy. Analytical travel distance models are developed for class-based and full turnover storage policies under across-aisle, within-aisle and a newly proposed hybrid product placement schemes. Our computational studies show that the analytical models developed in this paper are very accurate as compared to simulation results and a comparative study with a real-world warehouse case. Hybrid storage policies proposed in this paper outperform all other traditional storage policies. The paper also presents insights and simple design rules to warehouse practitioners.
Journal: International Journal of Production Research
Pages: 327-346
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1158428
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1158428
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Template-Type: ReDIF-Article 1.0
Author-Name: Dennis Z. Yu
Author-X-Name-First: Dennis Z.
Author-X-Name-Last: Yu
Author-Name: Chen Xiang
Author-X-Name-First: Chen
Author-X-Name-Last: Xiang
Title: A manufacturer’s production and pricing strategies with a salvage channel
Abstract: 
 We study a manufacturer’s production quantity and pricing decisions when the manufacturer has an opportunity to sell surplus inventory through a salvage channel. Before sales begin, the manufacturer determines the production quantity without knowing customer demand. After demand is realised, the manufacturer first satisfies the demand through primary channel while charging a fixed price or adjusting price to maximise profit. At the end of the selling season, the manufacturer resells surplus inventory through the salvage channel, which can be either integrated with or independent of the manufacturer. The manufacturer’s optimal production quantity and expected profit are investigated under different salvage channel structures. We show that the salvage channel improves the manufacturer’s profitability as well as the availability of the product to potential customers through both primary and salvage channels.
Journal: International Journal of Production Research
Pages: 347-357
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1176264
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1176264
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianming Yao
Author-X-Name-First: Jianming
Author-X-Name-Last: Yao
Title: Optimisation of one-stop delivery scheduling in online shopping based on the physical Internet
Abstract: 
 The circulation of online shopping commodities generally involves many entities, such as online manufacturers, wholesalers, retailers and customers. Goods from manufacturers to consumers undergo several exchange stages involving different economic entities. The logistics cost increases in certain supply chain nodes and the risk of backlog or running out of stock is high because of the different income and risk expectations of entities, as well as the varying degrees of information sharing between them. Clearly, a one-stop delivery mode crossing numerous transaction links in online shopping can effectively solve these problems and save social resources. However, realising this one-stop mode requires a series of specific premises, appropriate software and hardware technology support. This study introduces the Physical Internet into the one-stop delivery mode as an important logical and technical support, analyses the operating mechanism of the Physical Internet and discusses the operating conditions of one-stop delivery. It analyses the optimisation contents and objectives of one-stop delivery scheduling to construct a multi-objective optimisation mathematical model and propose a solving algorithm. Finally, this study uses an application case to verify the feasibility and effectiveness of the optimisation mechanism and algorithm.
Journal: International Journal of Production Research
Pages: 358-376
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1176266
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1176266
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Template-Type: ReDIF-Article 1.0
Author-Name: Tommaso Rossi
Author-X-Name-First: Tommaso
Author-X-Name-Last: Rossi
Author-Name: Rossella Pozzi
Author-X-Name-First: Rossella
Author-X-Name-Last: Pozzi
Author-Name: Margherita Pero
Author-X-Name-First: Margherita
Author-X-Name-Last: Pero
Author-Name: Roberto Cigolini
Author-X-Name-First: Roberto
Author-X-Name-Last: Cigolini
Title: Improving production planning through finite-capacity MRP
Abstract: 
 Materials Requirement Planning (MRP) technique is widely employed by most manufacturing companies, even though field applications point out some weaknesses, including ignored production capacity constraints and fixed lead-times. These weaknesses often lead to infeasible production schedules, which trigger fluctuating workloads over time, significant adjustment effort and eventually unpredictably long lead times. This paper introduces a capacity-oriented MRP procedure that combines the traditional MRP procedure with an approach based on linear programming: in this way, requirement of lead times pre-determined a priori outside the MRP procedure is overcome. The new procedure is then applied to a real-life company and results highlight that feasible plans of orders are generated without requiring lead-times as input and without relevant computational burden.
Journal: International Journal of Production Research
Pages: 377-391
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1177235
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1177235
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:377-391




Template-Type: ReDIF-Article 1.0
Author-Name: Oleh Sobeyko
Author-X-Name-First: Oleh
Author-X-Name-Last: Sobeyko
Author-Name: Lars Mönch
Author-X-Name-First: Lars
Author-X-Name-Last: Mönch
Title: Integrated process planning and scheduling for large-scale flexible job shops using metaheuristics
Abstract: 
 In this paper, we discuss an integrated process planning and scheduling problem in large-scale flexible job shops (FJSs). We assume that products can be manufactured in different ways, i.e. using different bills of materials (BOM) and routes for the same product. The total weighted tardiness is the performance measure of interest. A Mixed Integer Programming formulation is provided for the researched problem. Because of the NP-hardness of the investigated problem, an iterative scheme is designed that is based on variable neighbourhood search (VNS) on the process planning level. Appropriate neighbourhood structures for VNS are proposed. Because the evaluation of each move within VNS requires the solution of a large-scale FJS scheduling problem instance, efficient heuristics based on local search from previous research are considered on the scheduling level. Extensive computational experiments based on new randomly generated problem instances are conducted. In addition, a parallel version of the VNS is investigated within the computational experiments. The proposed iterative scheme is benchmarked against a genetic algorithm (GA) from the literature that simultaneously considers process planning and scheduling for the special case where a single BOM is available for each product. It turns out that the new iterative scheme outperforms the GA and a memetic algorithm based on the GA. It is able to solve even large-size problem instances in reasonable amount of time.
Journal: International Journal of Production Research
Pages: 392-409
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1182227
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1182227
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:392-409




Template-Type: ReDIF-Article 1.0
Author-Name: İlker Küçükoğlu
Author-X-Name-First: İlker
Author-X-Name-Last: Küçükoğlu
Author-Name: Nursel Öztürk
Author-X-Name-First: Nursel
Author-X-Name-Last: Öztürk
Title: Two-stage optimisation method for material flow and allocation management in cross-docking networks
Abstract: 
 Cross-docking is a relatively new logistics strategy in which items are moved from suppliers to customers through cross-docking centres without putting them into long-term storage. An important decision during the planning of cross-docking operations is related to the material flow management in the network, which has great potential to reduce transportation costs. However, until now, there has been a lack of studies regarding operations for both transportation of trucks between locations and trans-shipment of items in cross-docking centres. This study presents a novel two-stage mixed integer linear mathematical model for the transportation problem of cross-docking network design integrated with truck–door assignments to minimise total transportation costs from suppliers to customers. This model also considers incoming/outgoing truck-loading plans and product allocations in the cross-docking area with regard to the two-dimensional physical constraints. Due to the complexity of the problem, a genetic algorithm (GA) is proposed to solve large-sized problems. Computational studies are conducted to examine the validity of the two-stage model and performance of the GA. The computational studies show that the introduced model provides a comprehensive plan for material flow management in cross-docking networks and proposed GA is capable of obtaining effective results for the problem within a short computational time.
Journal: International Journal of Production Research
Pages: 410-429
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1184346
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1184346
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Template-Type: ReDIF-Article 1.0
Author-Name: Hui Mu
Author-X-Name-First: Hui
Author-X-Name-Last: Mu
Author-Name: Pingyu Jiang
Author-X-Name-First: Pingyu
Author-X-Name-Last: Jiang
Author-Name: Jiewu Leng
Author-X-Name-First: Jiewu
Author-X-Name-Last: Leng
Title: Costing-based coordination between mt-iPSS customer and providers for job shop production using game theory
Abstract: 
 The industrial product-service system for Computer Numerical Control machine tool (mt-iPSS) has drawn much interest. Under the new paradigm of functional result-oriented mt-iPSS, mt-iPSS customer (i.e. owner of the workshop) pays for time or results of mt-iPSS providers. The present problem for mt-iPSS customer is how to timely identify the optimal machine tools, sequence and cutting parameters of operation to finish the jobs while mt-iPSS providers try to maximise their benefit in a non-cooperative game structure. In this paper, a Stackelberg game model is put forward to solve the coordination problem based on the costing of different job shop scheduling solutions under the result-oriented mt-iPSS paradigm. Then, to solve the established bi-level programming model of the Stackelberg game, a solution procedure based on hierarchical particle swarm optimisation is proposed. Finally, a case from a printing machinery enterprise is analysed to validate the proposed model. This research is expected to improve the quality and effectiveness of coordination for scheduling and process planning decision between mt-iPSS customer and multi-providers.
Journal: International Journal of Production Research
Pages: 430-446
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1184347
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1184347
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianbin Li
Author-X-Name-First: Jianbin
Author-X-Name-Last: Li
Author-Name: Rihuan Huang
Author-X-Name-First: Rihuan
Author-X-Name-Last: Huang
Author-Name: James B. Dai
Author-X-Name-First: James B.
Author-X-Name-Last: Dai
Title: Joint optimisation of order batching and picker routing in the online retailer’s warehouse in China
Abstract: 
 Order picking is the core of warehouse operations and considerable researches have been conducted on improving its efficiency. In this paper, we aim at the joint optimisation of order batching and picker routing based on a famous and typical online retailer of China, which mainly focuses on fast-moving consumer goods. An integer programming is formulated to minimise the total travelling distance involving with order batching and picker routing. In the stage of order batching, an effective batching procedure based on similarity coefficient which is measured by overlapping channels between orders is proposed. In the stage of picker routing, an improved ant colony optimisation algorithm with local search is proposed. Based on those simulated orders generated by actual transaction data, numerical experiments are conducted to verify the performance of the algorithm we proposed. Results show that the proposed joint optimisation algorithm has potential advantages under various order sizes and order structures, which implies that it is effective and efficient particularly in the online retailing of fast-moving consumer goods.
Journal: International Journal of Production Research
Pages: 447-461
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1187313
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1187313
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Template-Type: ReDIF-Article 1.0
Author-Name: Alex J. Ruiz-Torres
Author-X-Name-First: Alex J.
Author-X-Name-Last: Ruiz-Torres
Author-Name: Giuseppe Paletta
Author-X-Name-First: Giuseppe
Author-X-Name-Last: Paletta
Author-Name: Rym M’Hallah
Author-X-Name-First: Rym
Author-X-Name-Last: M’Hallah
Title: Makespan minimisation with sequence-dependent machine deterioration and maintenance events
Abstract: 
 This paper addresses the minimal makespan parallel machine problem where machines are subject to preventive maintenance events of a known deterministic duration. The processing time of a job depends on its predecessors since the machine’s last maintenance. The paper proposes some dominance criteria for sequences of jobs assigned to a machine, and uses these criteria to design constructive heuristics to this NP-hard problem. The computational investigation determines the parameters that make a hard instance and studies the sensitivity of the heuristics to these parameters.
Journal: International Journal of Production Research
Pages: 462-479
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1187776
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1187776
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:462-479




Template-Type: ReDIF-Article 1.0
Author-Name: Joachim Lentes
Author-X-Name-First: Joachim
Author-X-Name-Last: Lentes
Author-Name: Joerg Mandel
Author-X-Name-First: Joerg
Author-X-Name-Last: Mandel
Author-Name: Ursula Schliessmann
Author-X-Name-First: Ursula
Author-X-Name-Last: Schliessmann
Author-Name: Roland Blach
Author-X-Name-First: Roland
Author-X-Name-Last: Blach
Author-Name: Michael Hertwig
Author-X-Name-First: Michael
Author-X-Name-Last: Hertwig
Author-Name: Timm Kuhlmann
Author-X-Name-First: Timm
Author-X-Name-Last: Kuhlmann
Title: Competitive and sustainable manufacturing by means of ultra-efficient factories in urban surroundings
Abstract: 
 The rapid growth of the world population, the finiteness of resources on our planet Earth and the ongoing tendency towards urbanisation result in the need to question our actions and economic activities, also for industrial enterprises. A paradigm shift to decouple growth and resource utilisation is needed. By means of ultra-efficiency, factories are targeted, whose positive impact to their surrounding is optimised instead of only minimising negative influences. In the contribution, the concept of ultra-efficient factories and first tools for their implementation are introduced. Therefore, the term ultra-efficient factory is defined based on the state of the art. On this definition, spheres of activity for ultra-efficient factories under consideration of urban surroundings are determined. For the spheres of activity, criteria to assess the according maturity of companies are identified and aggregated into a comprehensive maturity model. The maturity model enables the determination of potentials for advancements of companies. To support the industrial application of the theoretic work, industrial best practices are determined and a visual tool is developed.
Journal: International Journal of Production Research
Pages: 480-491
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1189106
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1189106
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:480-491




Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Rezaei-Malek
Author-X-Name-First: Mohammad
Author-X-Name-Last: Rezaei-Malek
Author-Name: Jafar Razmi
Author-X-Name-First: Jafar
Author-X-Name-Last: Razmi
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Author-Name: Alireza Taheri-Moghaddam
Author-X-Name-First: Alireza
Author-X-Name-Last: Taheri-Moghaddam
Title: Towards a psychologically consistent cellular manufacturing system
Abstract: 
 In cellular manufacturing systems (CMSs), an operator plays an important role. Because operators work for long-time periods in a production area, an increase in job satisfaction and system productivity occurs if the consistency of operators’ personal characteristics are considered in the design of CMSs. In a CMS, a cell formation problem (CFP) focuses on grouping and allocating machines, part families and operators to manufacturing cells. This paper considers a decision-making style (DMS) as an operator’s personal characteristic index in a CFP for designing a psychologically consistent CMS. DMS influences not only the interaction between two operators, but also the work that operator does on a machine. Hence, this paper develops a novel multi-objective mathematical model for the CFP considering consistency between each two operators in each cell and consistency between operator and his/her assigned machine(s). Because of possibility of a change in the primary DMS of a person to the backup one, this paper tackles this issue by applying a probabilistic procedure. Two hybrid meta-heuristic algorithms are developed for the large-sized test problems. In addition, the PROMETHEE-II method is applied to select the best Pareto solution. Finally, a real case study is presented to show the applicability of the developed approach.
Journal: International Journal of Production Research
Pages: 492-518
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1192299
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1192299
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:492-518




Template-Type: ReDIF-Article 1.0
Author-Name: Ons Sassi
Author-X-Name-First: Ons
Author-X-Name-Last: Sassi
Author-Name: Ammar Oulamara
Author-X-Name-First: Ammar
Author-X-Name-Last: Oulamara
Title: Electric vehicle scheduling and optimal charging problem: complexity, exact and heuristic approaches
Abstract: 
 This paper deals with the Electric Vehicle (EV) Scheduling and Optimal Charging Problem. More precisely, given a fleet of EVs and Combustion Engine Vehicles (CVs), a set of tours to be processed by vehicles and a charging infrastructure, the problem aims to optimise the assignment of vehicles to tours and minimise the charging cost of EVs while considering several operational constraints mainly related to chargers, electricity grid and EVs driving range. We prove that the Electric Vehicle Scheduling and Charging Problem (EVSCP) is NP-hard in the ordinary sense. We provide a mixed-integer linear programming formulation to model the EVSCP and use CPLEX to solve small and medium instances. To solve large instances, we propose two heuristics: a Sequential Heuristic (SH) and a Global Heuristic (GH). The SH considers the EVs sequentially. To each EV, it assigns a set of tours and guarantees the feasibility of a charging schedule. Then, it generates an optimal charging schedule for this EV. However, the GH computes, in the first step, a feasible assignment of tours to all EVs. In the second step, it applies a global Min-Cost-Flow-based charging algorithm to minimise the charging cost of the EVs fleet. To evaluate the efficiency of our solving approaches, computational results on a large set of real and randomly generated test instances are reported and compared.
Journal: International Journal of Production Research
Pages: 519-535
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1192695
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1192695
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:519-535




Template-Type: ReDIF-Article 1.0
Author-Name: İsmail Karaoğlan
Author-X-Name-First: İsmail
Author-X-Name-Last: Karaoğlan
Author-Name: Saadettin Erhan Kesen
Author-X-Name-First: Saadettin Erhan
Author-X-Name-Last: Kesen
Title: The coordinated production and transportation scheduling problem with a time-sensitive product: a branch-and-cut algorithm
Abstract: 
 In many supply chain scenarios in which short lifespan products are considered, production and transportation decisions must be made in a coordinated manner with no inventory stage. Hence, a solution to this problem conveys information about production starting times of each product lot at facility and delivery times of the lots to various customer-sites located in different geographic regions. In this paper, we study a variant of the problem that single product with limited shelf life is produced at single facility. Once produced, production lot is directly distributed to the customers with non-ignorable transportation time by single vehicle having limited capacity before the lifespan. Objective is to determine the minimum time required to produce and deliver all customer demands. To this end, we develop a branch-and-cut (B&amp;C) algorithm using several valid inequalities adopted from the existing literature to improve lower bounds and applying a local search based on simulated annealing approach to improve upper bounds. On test problems available in the literature, we evaluate the performance of the B&amp;C algorithm. Results show the promising performance of the B&amp;C algorithm.
Journal: International Journal of Production Research
Pages: 536-557
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1213916
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213916
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:536-557




Template-Type: ReDIF-Article 1.0
Author-Name: Ran Liu
Author-X-Name-First: Ran
Author-X-Name-Last: Liu
Author-Name: Biao Yuan
Author-X-Name-First: Biao
Author-X-Name-Last: Yuan
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Mathematical model and exact algorithm for the home care worker scheduling and routing problem with lunch break requirements
Abstract: 
 Home health care or home care (HHC/HC) refers to the delivery of social, medical and paramedical services to clients in their own homes. Each day, care workers start from the HHC/HC centre, visit some clients and return to the centre. During the service delivery process, there is usually a lunch break for each worker. In this paper, we address a real-life home care worker scheduling and routing problem with the consideration of lunch break requirements. A three-index mathematical model is constructed for the problem. The problem is decomposed into a master problem and several pricing sub-problems, and is optimally solved by a branch-and-price (B&amp;P) algorithm. Specifically, a sophisticated label-correcting algorithm is designed to address lunch break constraints in pricing sub-problems; some cutting-edge acceleration strategies are applied during the column generation process. Experimental results show that the proposed B&amp;P algorithm is able to produce satisfied solutions within an acceptable runtime and outperforms the mixed integer programming solver CPLEX.
Journal: International Journal of Production Research
Pages: 558-575
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1213917
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213917
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:558-575




Template-Type: ReDIF-Article 1.0
Author-Name: Rafael A. Melo
Author-X-Name-First: Rafael A.
Author-X-Name-Last: Melo
Author-Name: Celso C. Ribeiro
Author-X-Name-First: Celso C.
Author-X-Name-Last: Ribeiro
Title: Formulations and heuristics for the multi-item uncapacitated lot-sizing problem with inventory bounds
Abstract: 
 We consider the multi-item uncapacitated lot-sizing problem with inventory bounds, in which a production plan for multiple items has to be determined considering that they share a storage capacity. We present (a) a shortest path formulation and (b) a formulation based on the a priori addition of valid inequalities, which are compared with a facility location formulation available in the literature. Two easy-to-implement mixed integer programming heuristic frameworks are also presented, (a) a rounding scheme and (b) a relax-and-fix approach performed in a time partitioning fashion. Computational experiments are performed to evaluate the different approaches. The numerical results show that the proposed relax-and-fix heuristic outperforms all other approaches. Its solutions are within 4.0% of optimality in less than 10 minutes of running time for all tested instances, with mean gaps in the order of 2.1 and 1.8% for instances with more relaxed and tighter capacities, respectively. The obtained solutions were always better than those obtained by a commercial MIP solver running for one hour using any of the available formulations.
Journal: International Journal of Production Research
Pages: 576-592
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1215567
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1215567
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:576-592




Template-Type: ReDIF-Article 1.0
Author-Name: C.K.H. Lee
Author-X-Name-First: C.K.H.
Author-X-Name-Last: Lee
Title: A GA-based optimisation model for big data analytics supporting anticipatory shipping in Retail 4.0
Abstract: 
 In Retail 4.0, omni-channels require a seamless and complete integration of all available channels for purchasing. The diversification of channels not only diversifies data sources, but also rapidly generates an enormous amount of data. This highlights a need of big data analytics to extract meaningful knowledge for decision-making. In addition, anticipatory shipping is getting more popular to ensure fast product delivery. The goal is to predict when a customer will make a purchase and then begin shipping the product to the nearest distribution centres before the customer places the orders online. This paper proposes a genetic algorithm (GA)-based optimisation model to support anticipatory shipping. Cloud computing is deployed to store the big data generated from all channels. Cluster-based association rule mining is applied to discover the purchase pattern and predict future purchase in terms of If-Then prediction rules. A modified GA is then used to generate optimal anticipatory shipping plans. Apart from transportation cost and travelling distance, the confidence of prediction rules is also considered in the GA. A number of numerical experiments have been carried out to demonstrate the trade-off of different factors in anticipatory shipping, and the optimisation reliability of the model is verified.
Journal: International Journal of Production Research
Pages: 593-605
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1221162
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1221162
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:593-605




Template-Type: ReDIF-Article 1.0
Author-Name: Pengyu Chen
Author-X-Name-First: Pengyu
Author-X-Name-Last: Chen
Author-Name: He Xu
Author-X-Name-First: He
Author-X-Name-Last: Xu
Author-Name: Yongquan Li
Author-X-Name-First: Yongquan
Author-X-Name-Last: Li
Author-Name: Li Zeng
Author-X-Name-First: Li
Author-X-Name-Last: Zeng
Title: Joint product variety, pricing and scheduling decisions in a flexible facility
Abstract: 
 This paper studies a manufacturer’s optimal product variety, pricing and scheduling decisions in a single flexible production facility when customers have private information in their marginal valuations for product qualities. In addition to determining the product variety and price of each product, the manufacturer needs to optimise a detailed schedule of production (batch sizes and production sequences) to fully utilise the flexibility of this facility. To achieve the second-degree discrimination, the manufacturer provides multiple products and follows a priority rule in the production schedule. To obtain economies of scale, the manufacturer may offer a composite product targeting the whole population, or choose a dedicated product to serve a proportion of customers. Comparing these three production choices, we observe that the optimal product variety strategy is threshold controlled by the relative ratio of customer arrival rates, the relative difference between customers’ marginal valuations and the production technology.
Journal: International Journal of Production Research
Pages: 606-620
Issue: 2
Volume: 55
Year: 2017
Month: 1
X-DOI: 10.1080/00207543.2016.1229065
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1229065
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:606-620




Template-Type: ReDIF-Article 1.0
Author-Name: R. Giri
Author-X-Name-First: R.
Author-X-Name-Last: Giri
Author-Name: M. Kanthababu
Author-X-Name-First: M.
Author-X-Name-Last: Kanthababu
Title: Generating complete disassembly sequences by utilising two-dimensional views
Abstract: 
 This research work proposes a novel method to generate the complete disassembly sequences for mechanical products by utilising the part interference matrix which contains the removal directions of the parts and the part connection graph which indicates the contact among the parts in the assembly. Contrary to the earlier methods, the proposed method considers the two-dimensional views generated from the computer-aided design assembly model for automatically identifying the part removal directions and for generating the part connection graph. Rules are formulated in the proposed method to identify the part removal directions effectively and also to reduce the size of part connection graph, since the method of identifying the part removal directions and the size of the formulated graph plays a vital role in the generation of disassembly sequence. Finally, a heuristic method is developed to generate the best feasible disassembly sequences. The effectiveness of the approach is illustrated with three examples.
Journal: International Journal of Production Research
Pages: 5118-5138
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1005249
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005249
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:17:p:5118-5138




Template-Type: ReDIF-Article 1.0
Author-Name: Thomy Eko Saputro
Author-X-Name-First: Thomy Eko
Author-X-Name-Last: Saputro
Author-Name: Ilyas Masudin
Author-X-Name-First: Ilyas
Author-X-Name-Last: Masudin
Author-Name: Babak Daneshvar Rouyendegh (Babek Erdebilli)
Author-X-Name-First: Babak
Author-X-Name-Last: Daneshvar Rouyendegh (Babek Erdebilli)
Title: A literature review on MHE selection problem: levels, contexts, and approaches
Abstract: 
 This paper presents a review on selection problem of material handling equipment (MHE) and general equipment used in industry area. The issue on MHE is widely paid attention since MHE has contribution on material, good and product accomplishment. Few methods and softwares have been proposed and developed to select the most appropriate MHE for a complex selection problem. Today’s high diverisity of MHE categories and types influence the generation of many possible choices which leads to the complexity. In this paper, a further discussion in terms of MHE and equipment including three major points namely level of selection, the context of selection problem and the approaches are served to highlight the complex MHE selection according to the number of possible choices provided, to analyse the consideration for the problem context, and to reveal the superior method for complex MHE selection. Forty-two papers collected from the past study are presented asscociating each point of the discussion.
Journal: International Journal of Production Research
Pages: 5139-5152
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1005254
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005254
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingjing Hao
Author-X-Name-First: Jingjing
Author-X-Name-Last: Hao
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Linda L. Zhang
Author-X-Name-First: Linda L.
Author-X-Name-Last: Zhang
Title: Optimal design of a 3D compact storage system with the I/O port at the lower mid-point of the storage rack
Abstract: 
 As a new generation of automated warehousing systems, 3D compact storage systems have been increasingly installed worldwide for handling inventory items in warehouses, distribution centres and manufacturing factories. Due to the problem complexity and system novelty, research investigating these systems, design models in particular, lags behind. This study, thus, addresses the design of 3D compact storage systems, where the I/O port is located at the lower mid-point of the storage rack, in attempting to assist practitioners in designing such systems that can achieve optimal performance while meeting system capacity requirements. In view of its importance in system design, we first derive the system expected travel time and subsequently optimise the three dimensions of the storage rack. We consider all the possible configurations of the three rack dimensions and develop closed form expressions for travel time derivation and rack dimension optimisation. We compare the result with an available design model, where the I/O port is located in the lower left-corner of the storage rack. The comparison shows that our model produces shorter system expected travel time, thus higher system throughput. We also elaborate several numerical examples to demonstrate how our model can be applied to design 3D compact storage systems in practice. Based on the numerical examples, we further provide several managerial implications, which are useful for practitioners to make suitable design decisions.
Journal: International Journal of Production Research
Pages: 5153-5173
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1005767
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005767
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Template-Type: ReDIF-Article 1.0
Author-Name: Divesh Ojha
Author-X-Name-First: Divesh
Author-X-Name-Last: Ojha
Author-Name: Richard E. White
Author-X-Name-First: Richard E.
Author-X-Name-Last: White
Author-Name: Pamela P. Rogers
Author-X-Name-First: Pamela P.
Author-X-Name-Last: Rogers
Author-Name: Ching-Chung Kuo
Author-X-Name-First: Ching-Chung
Author-X-Name-Last: Kuo
Title: Information processing-related infrastructural antecedents of manufacturing flexibility – a real options perspective
Abstract: 
 The relationship between manufacturing flexibility and environmental uncertainty has been widely studied; however, research involving manufacturing flexibility and associated infrastructural antecedents is sparse. In this paper, using the real options perspective, we develop a research model to explicate management support’s influence on an organisation’s manufacturing flexibility. We use a second-order, multi-dimensional construct and survey data collected from US manufacturers to test our hypotheses. The study provides evidence to suggest that management support through teamwork, information systems effectiveness, and integrated supply chain effectiveness enhances an organisation’s manufacturing flexibility.
Journal: International Journal of Production Research
Pages: 5174-5192
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1008704
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1008704
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Template-Type: ReDIF-Article 1.0
Author-Name: Shouxu Song
Author-X-Name-First: Shouxu
Author-X-Name-Last: Song
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Qingdi Ke
Author-X-Name-First: Qingdi
Author-X-Name-Last: Ke
Author-Name: Haihong Huang
Author-X-Name-First: Haihong
Author-X-Name-Last: Huang
Title: Proactive remanufacturing timing determination method based on residual strength
Abstract: 
 Nowadays, since the resources of remanufacturing are the ‘cores’, the uncertainty in quantity and quality of the ‘cores’ is an obstacle in remanufacturing engineering. To solve this problem, production management and design for remanufacturing have been discussed in the former studies. However, the current remanufacturing mode, which is carried out in the end of life cycle, is reactive. To delimit the uncertainty of ‘cores’, the concept of proactive remanufacturing is presented in this paper. And one issue is to identify the proactive remanufacturing timing. In the beginning, the reactive remanufacturing timing and proactive remanufacturing timing are introduced. Then, to characterise the remanufacturability of components, the concept of residual strength is proposed. To identify the proactive remanufacturing timing, the mathematical model is established based on the residual strength, remanufacturing value and technical feasibility. Based on this model, the timing determination method in proactive remanufacturing is presented and expanded. Finally, to validate this method, the proactive remanufacturing timing of engines is determined by analysing the crankshaft. As a consequence, in the proactive remanufacturing mode, the remanufacturing rate of product might be increased. Thus, the proactive remanufacturing could provide a new perspective in future remanufacturing engineering.
Journal: International Journal of Production Research
Pages: 5193-5206
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1012599
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1012599
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Template-Type: ReDIF-Article 1.0
Author-Name: Rameshwar Dubey
Author-X-Name-First: Rameshwar
Author-X-Name-Last: Dubey
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Anindya Chakrabarty
Author-X-Name-First: Anindya
Author-X-Name-Last: Chakrabarty
Title: World-class sustainable manufacturing: framework and a performance measurement system
Abstract: 
 Sustainable manufacturing has been the subject of debate in the last few years, amongst both researchers and industrialists. Manufacturing activities have been regarded as amongst the most important factors which have caused major damage to planet. The aim of this paper is to scientifically develop a world-class sustainable manufacturing (WCSM) framework. The study uses a structured questionnaire, which was developed using extant literature and pretested to check content validity. The data was collected following a modified version of Dillman’s total design method to improve the quality of response. The psychometric properties of the instrument including reliability and construct validity were assessed using confirmatory factor analysis and multiple regression analysis for hypotheses testing, and partial least squares approach for testing goodness of fit. We find that the scale and items of our theoretical framework meet the criteria. The multiple regression analysis output suggests that all our hypotheses are supported, which further supports the extant literature. Our present study is unique in terms of scope and its contribution to the theory and practice of supply chain management. This study has empirically tested the research calls of various researchers, extended them to WCSM practices and further developed a scale for the measurement of the framework.
Journal: International Journal of Production Research
Pages: 5207-5223
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1012603
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1012603
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Template-Type: ReDIF-Article 1.0
Author-Name: B.M. Li
Author-X-Name-First: B.M.
Author-X-Name-Last: Li
Author-Name: S.Q. Xie
Author-X-Name-First: S.Q.
Author-X-Name-Last: Xie
Title: Module partition for 3D CAD assembly models: a hierarchical clustering method based on component dependencies
Abstract: 
 Reusing previous CAD assembly models directly in new product development is almost impossible in One-of-a-Kind Production (OKP) in which customer requirements vary from one to another. As such, modularisation of CAD assembly models is required to facilitate modular design for OKP. However, to the authors’ best knowledge, there has been no research carried out on modularisation of CAD assembly models so far. To bridge this gap and make the best use of existing CAD models, this paper proposes a novel module partition approach, to group existing CAD assembly models into modules based on component dependencies. In this approach, an extraction algorithm was developed to extract assembly information from a given assembly model directly, by using automated programmable interfaces of CAD software tools. The extracted information is processed to generate the component design structure matrix (DSM) representing hierarchical relations and dependency strengths between components. Four popular hierarchical clustering methods were used to work with the component DSM to produce results of module partition. A case study was carried out to illustrate the proposed methods and demonstrate their feasibility. It enables OKP companies to respond rapidly to changing customer requirements and develop customised products in a short period.
Journal: International Journal of Production Research
Pages: 5224-5240
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1015748
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1015748
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Template-Type: ReDIF-Article 1.0
Author-Name: Seong-Jong Joo
Author-X-Name-First: Seong-Jong
Author-X-Name-Last: Joo
Author-Name: Hyun-Cheol Paul Choi
Author-X-Name-First: Hyun-Cheol Paul
Author-X-Name-Last: Choi
Title: Assessing comparative production efficiencies for product line management
Abstract: 
 Product line management involves product expansion or elimination depending on various factors, for example, production processes and demands in the market. This study focuses on measuring product performance for a firm’s product line management, using parametric and non-parametric approaches. First, we choose variables related to the production and demand of products and assess the comparative performance of product groups and individual products using data envelopment analysis (DEA). Second, we attempt to detect possible performance differences among the product groups using one-way analysis of variance. Third, we identify the sources of inefficiency using appropriate DEA scores and offer some managerial insights. Last, we try to confirm the determinants of product performance using Tobit regression analysis. The major contribution of this study is the use of a novel approach for product line management by measuring the performance of product groups and individual products using pertinent variables. The approach used in this study is applicable to various manufacturing and service industries. The limitations of this study are the number of product groups selected and examination of performance using cross-sectional data.
Journal: International Journal of Production Research
Pages: 5241-5250
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1015749
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1015749
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Template-Type: ReDIF-Article 1.0
Author-Name: Min Zhang
Author-X-Name-First: Min
Author-X-Name-Last: Zhang
Author-Name: Fiona Lettice
Author-X-Name-First: Fiona
Author-X-Name-Last: Lettice
Author-Name: Xiande Zhao
Author-X-Name-First: Xiande
Author-X-Name-Last: Zhao
Title: The impact of social capital on mass customisation and product innovation capabilities
Abstract: 
 Social capital with customers has three dimensions: structural, relational and cognitive capital. We propose a research model on the joint effects of the three dimensions of social capital on mass customisation capability (MCC) and product innovation capability (PIC). The hypotheses are empirically tested using structural equation modelling and data collected from 276 manufacturing firms in China. The results show that the three dimensions of social capital contribute to MCC and PIC development through different mechanisms. In particular, cognitive capital has a significant impact on MCC; relational capital significantly influences PIC; and structural capital indirectly associates with both MCC and PIC. We also find that structural capital enhances both relational and cognitive capital. MCC improves PIC and fully mediates cognitive capital’s effect on PIC. The findings extend current understanding about the complex interrelationships among structural, relational and cognitive capital and how to develop MCC and PIC by investing in social capital.
Journal: International Journal of Production Research
Pages: 5251-5264
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1015753
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1015753
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Template-Type: ReDIF-Article 1.0
Author-Name: Giorgio Mustafaraj
Author-X-Name-First: Giorgio
Author-X-Name-Last: Mustafaraj
Author-Name: John Cosgrove
Author-X-Name-First: John
Author-X-Name-Last: Cosgrove
Author-Name: Maria J. Rivas-Duarte
Author-X-Name-First: Maria J.
Author-X-Name-Last: Rivas-Duarte
Author-Name: Frances Hardiman
Author-X-Name-First: Frances
Author-X-Name-Last: Hardiman
Author-Name: John Harrington
Author-X-Name-First: John
Author-X-Name-Last: Harrington
Title: A methodology for determining auxiliary and value-added electricity in manufacturing machines
Abstract: 
 A methodology was developed that accurately and flexibly determines the auxiliary (AU) and value-added electricity in manufacturing operations. A tool was developed for production engineers which allows for the verification of machine efficiency in relation to their energy consumption. Historical production and electricity consumption data were collected for a period of three months from four different machines in a value stream at a manufacturing facility. The data were examined using a methodology based on statistical analysis of the historical data collected and were verified using heuristic machines profiles. Results showed AU electricity consumption varied between 10 and 26% per machine. When weekend data (non-productive periods) were excluded from calculations, AU electricity consumption reduced. Past work focuses on optimising single machine, and the quantification of wasted electricity is not always clear. This research work can be applied to one or more machines, and to single or multiple products passing through the same machine. It places particular attention to AU electricity since potential energy and cost reduction of up to 20% could be achieved. Hence, this work can aid in developing key performance indicators to measure energy usage in manufacturing operations, particularly focused towards reducing AU electricity consumption.
Journal: International Journal of Production Research
Pages: 5265-5277
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1026615
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1026615
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Template-Type: ReDIF-Article 1.0
Author-Name: Qiang Wang
Author-X-Name-First: Qiang
Author-X-Name-Last: Wang
Author-Name: Zhiqiang Wang
Author-X-Name-First: Zhiqiang
Author-X-Name-Last: Wang
Author-Name: Xiande Zhao
Author-X-Name-First: Xiande
Author-X-Name-Last: Zhao
Title: Strategic orientations and mass customisation capability: the moderating effect of product life cycle
Abstract: 
 This study examines the influence of three strategic orientations (customer, competitor and innovation) on mass customisation (MC) capability via the organisational learning process known as customisation knowledge utilisation (CKU). The moderating effect of product life cycle (PLC) is also investigated. Using data collected from 204 manufacturers, we show that all three strategic orientations positively contribute to MC capability, both directly and indirectly through CKU. Further, our empirical findings suggest that the effects of customer, competitor and innovation orientation on MC capability are contingent on PLC. The effects of customer orientation on CKU and the effects of competitor orientation on CKU and MC capability are stronger when a product is in the maturity stage of its life cycle, whereas the effect of innovation orientation on CKU and MC capability are stronger in the growth stage. These findings suggest that to effectively improve MC capability, managers need to leverage external and internal orientations at different stages of the PLC.
Journal: International Journal of Production Research
Pages: 5278-5295
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1027012
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1027012
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Template-Type: ReDIF-Article 1.0
Author-Name: S. Djebali
Author-X-Name-First: S.
Author-X-Name-Last: Djebali
Author-Name: S. Segonds
Author-X-Name-First: S.
Author-X-Name-Last: Segonds
Author-Name: J.M. Redonnet
Author-X-Name-First: J.M.
Author-X-Name-Last: Redonnet
Author-Name: W. Rubio
Author-X-Name-First: W.
Author-X-Name-Last: Rubio
Title: Using the global optimisation methods to minimise the machining path length of the free-form surfaces in three-axis milling
Abstract: 
 During the machining of free-form surfaces using three-axis numerically controlled machine (NC), several parameters are chosen arbitrary and one of the most important is the feed motion direction. The main objective of this study is to minimise the machining time of complex surfaces while respecting a scallop height criteria. The analytical expression of the machining time is not known and by hypothesis, it is assumed to be proportional to the path length crossed by the cutting tool. This path length depends on the feed direction. To have an optimal feed direction at any point, the surface is divided into zones with low variation of the steepest slope direction. The optimization problem was formulated aiming at minimizing the global path length. Furthermore, a penalty reflecting the time loss due to the movement of the tool from one zone to another one is taken into account. Several heuristics are used to resolve this problem: Clarke and Wrights, Greedy randomized adaptive search procedure, Tabu search and Nearest neighbour search. An example illustrates our work by applying the different heuristics on a test surface. After simulations, the results obtained present a significant saving of paths length of 24% compared to the machining in one zone.
Journal: International Journal of Production Research
Pages: 5296-5309
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1029648
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1029648
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:17:p:5296-5309




Template-Type: ReDIF-Article 1.0
Author-Name: Der-Chiang Li
Author-X-Name-First: Der-Chiang
Author-X-Name-Last: Li
Author-Name: Wen-Chih Chen
Author-X-Name-First: Wen-Chih
Author-X-Name-Last: Chen
Author-Name: Che-Jung Chang
Author-X-Name-First: Che-Jung
Author-X-Name-Last: Chang
Author-Name: Chien-Chih Chen
Author-X-Name-First: Chien-Chih
Author-X-Name-Last: Chen
Author-Name: I-Hsiang Wen
Author-X-Name-First: I-Hsiang
Author-X-Name-Last: Wen
Title: Practical information diffusion techniques to accelerate new product pilot runs
Abstract: 
 Under the increasing pressure of global competition, product life cycles are becoming shorter and shorter. This means that better methods are needed to analyse the limited information obtained at the trial stage in order to derive useful knowledge that can aid in mass production. Machine learning algorithms, such as data mining techniques, are widely applied to solve this problem. However, a certain amount of training samples is usually required to determine the validity of the information that is obtained. This study uses only a few data points to estimate the range of data attribute domains using a data diffusion method, in order to derive more useful information. Then, based on practical engineering experience, we generate virtual samples with a noise disturbance method to improve the robustness of the predictions derived from a multiple linear regression. One real data set obtained from a large TFT-LCD company is examined in the experiment, and the results show the proposed approach to be effective.
Journal: International Journal of Production Research
Pages: 5310-5319
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1032437
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1032437
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Template-Type: ReDIF-Article 1.0
Author-Name: José Roberto Xavier Alves
Author-X-Name-First: José Roberto Xavier
Author-X-Name-Last: Alves
Author-Name: João Murta Alves
Author-X-Name-First: João Murta
Author-X-Name-Last: Alves
Title: Production management model integrating the principles of lean manufacturing and sustainability supported by the cultural transformation of a company
Abstract: 
 The search for superior production performance has been used by companies to overcome competition in the current global economic scenario. Efficient manufacturing connected to environmental initiatives provides a company with favourable conditions for maintaining uniform and continuous improvement in its competitive performance, while providing operational versatility to respond quickly to volatile markets. As production is one of the most expensive areas for a company, many organisations have sought a new management model for their production system that provides substantial productivity gains, cost saving opportunities and higher customer satisfaction. This study proposes a model of production management and an implementation method integrating the principles of lean manufacturing and sustainability, supported by cultural transformation at the company. Its objective was to achieve productivity gains and improvements on customer satisfaction, as well as develop the ability to provide quick responses to market changes in a globalised economy. The implementation of the proposed model should be gradual, initially addressing fundamental principles, and should operate simultaneously with, and in the same environment as, workforce development and organisational transformation initiatives, to create sustainable improvements.
Journal: International Journal of Production Research
Pages: 5320-5333
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1033032
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1033032
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Template-Type: ReDIF-Article 1.0
Author-Name: Marek Szwejczewski
Author-X-Name-First: Marek
Author-X-Name-Last: Szwejczewski
Author-Name: Keith Goffin
Author-X-Name-First: Keith
Author-X-Name-Last: Goffin
Author-Name: Zissis Anagnostopoulos
Author-X-Name-First: Zissis
Author-X-Name-Last: Anagnostopoulos
Title: Product service systems, after-sales service and new product development
Abstract: 
 After-sales service is a critical element in the successful marketing of many products. Capital goods, for example, manufacturing equipment, require after-sales service such as maintenance and repair in order for customers to get the full value from them. Some manufacturers have started to offer customers an integrated product and service, termed a product-service system in the academic literature. However, in order to deliver such integrated offerings, a different approach to new product development (NPD) is required. This is because the product design influences after-sales service requirements, and so this needs to be considered during NPD. However, researchers have largely ignored the relationship between NPD and service. To address this gap, six in-depth case studies were conducted at leading companies that offer a combined product-service offering, to identify how service requirements are typically evaluated at the design stage. The results show that at companies where after-sales is an important element of the business, service requirements are systematically evaluated during NPD through the involvement of after-sales personnel and the use of field service data to set design goals.
Journal: International Journal of Production Research
Pages: 5334-5353
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1033499
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1033499
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Template-Type: ReDIF-Article 1.0
Author-Name: Sungil Kim
Author-X-Name-First: Sungil
Author-X-Name-Last: Kim
Author-Name: Heeyoung Kim
Author-X-Name-First: Heeyoung
Author-X-Name-Last: Kim
Author-Name: Richard W. Lu
Author-X-Name-First: Richard W.
Author-X-Name-Last: Lu
Author-Name: Jye-Chyi Lu
Author-X-Name-First: Jye-Chyi
Author-X-Name-Last: Lu
Author-Name: Michael J. Casciato
Author-X-Name-First: Michael J.
Author-X-Name-Last: Casciato
Author-Name: Martha A. Grover
Author-X-Name-First: Martha A.
Author-X-Name-Last: Grover
Title: Adaptive combined space-filling and D-optimal designs
Abstract: 
 In the beginning of sequential experimentation, space-filling designs are more appropriate for exploring process behaviour since they do not require any assumptions about the underlying model. In the latter stages of sequential experimentation, however, when data are collected and more knowledge about the process behaviour is gathered, model-based optimal designs may be more appropriate. This article proposes an adaptive combined design (ACD) balancing the characteristics of both design criteria at different stages of the sequential experiments. The tuning parameter associated with the ACD adaptively gauges the amount of process knowledge gain, which is used to improve the estimation of model parameters while still allowing for the exploration of model uncertainties. Rather than employing the weighted-sum method, an ϵ$ \epsilon $-constraint method is proposed to balance the two design criteria. Property investigation shows that the ACD provides better estimation of parameters over the space-filling design, and yet is more robust against model misspecification when compared to optimal designs. Simulated and real-life nanofabrication examples illustrate the needs of the ACD and the interesting features of the tuning parameter in searching for the process optimum.
Journal: International Journal of Production Research
Pages: 5354-5368
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1037067
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1037067
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Template-Type: ReDIF-Article 1.0
Author-Name: Shawnee K. Vickery
Author-X-Name-First: Shawnee K.
Author-X-Name-Last: Vickery
Author-Name: Yemisi A. Bolumole
Author-X-Name-First: Yemisi A.
Author-X-Name-Last: Bolumole
Author-Name: Matthew J. Castel
Author-X-Name-First: Matthew J.
Author-X-Name-Last: Castel
Author-Name: Roger J. Calantone
Author-X-Name-First: Roger J.
Author-X-Name-Last: Calantone
Title: The effects of product modularity on launch speed
Abstract: 
 Extant literature suggests that product modularity positively and directly impacts the timeliness and frequency of new products as well as manufacturing performance, particularly flexibility. Little is known about the nature of these relationships, however, since few empirical studies have been done. Important questions remain unanswered including whether the effect of modularity on launch speed is direct or indirect, and what role other constructs might play. This study explores these issues by examining the effects of product modularity on launch speed within a holistic framework that considers the roles of product platforms and manufacturing flexibility. Drawing upon dynamic capabilities theory in the resource-based view, the model depicts product modularity as antecedent to product platforms, product platforms as antecedent to manufacturing flexibility and manufacturing flexibility as antecedent to launch speed. The model is strongly supported by an analysis of 93 manufacturers. Results reveal a positive effect of product modularity on launch speed, but it is delivered through the mediating effects of product platforms and manufacturing flexibility. In contrast to earlier work, the findings show modularity alone is an insufficient condition for the timely and frequent introduction of new products. Rather, launch speed is engendered by a ‘gestalt’ of dynamic capabilities.
Journal: International Journal of Production Research
Pages: 5369-5381
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1047972
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047972
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiuzhen Li
Author-X-Name-First: Xiuzhen
Author-X-Name-Last: Li
Author-Name: Yanrong Ni
Author-X-Name-First: Yanrong
Author-X-Name-Last: Ni
Author-Name: X.G. Ming
Author-X-Name-First: X.G.
Author-X-Name-Last: Ming
Author-Name: Wenyan Song
Author-X-Name-First: Wenyan
Author-X-Name-Last: Song
Author-Name: Wenkan Cai
Author-X-Name-First: Wenkan
Author-X-Name-Last: Cai
Title: Module-based similarity measurement for commercial aircraft tooling design
Abstract: 
 Similarity measurement (SM) between pairs of features plays an essential role in the tooling retrieval. However, the number of tooling is usually large and difficult to retrieve. What’s more, the most similar tooling model is not always optimal in the case-based reasoning (CBR). To refine this situation, we propose a novel module-based similarity measurement method. Through dividing each tooling model into different modules, a new similarity is obtained by integrating all the most similar modules (MSMs) from existing tooling models. As a result, the new similarity is superior or at least equal to the result which is derived from previous methods. With the proposed method in this paper, feature similarities of modules between a new tooling ontology and each similar tooling ontology are calculated by fuzzy similarity measurement, and the MSMs are restructured to form a new tooling model after conflict resolution. A case study on forming mould is provided to illustrate the applications and prove the higher similarity by comparing with CBR. The proposed method has been adopted in an aircraft manufacturing company.
Journal: International Journal of Production Research
Pages: 5382-5397
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2015.1047973
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1047973
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Template-Type: ReDIF-Article 1.0
Author-Name: Seung-Jun Shin
Author-X-Name-First: Seung-Jun
Author-X-Name-Last: Shin
Author-Name: Suk-Hwan Suh
Author-X-Name-First: Suk-Hwan
Author-X-Name-Last: Suh
Author-Name: Ian Stroud
Author-X-Name-First: Ian
Author-X-Name-Last: Stroud
Title: A green productivity based process planning system for a machining process
Abstract: 
 In the metal cutting industry, manufacturers have strived to increase energy efficiency and to reduce environmental burdens through the use of dust collectors and waste disposers. It is more beneficial and efficient to apply the front-of-pipe technology that prevents the sources of pollutants and minimises energy use through the redesign of products and the change of process planning and machining operations. In particular, process planning for the environment, called eco-process planning, is central to increasing energy efficiency and reducing environmental burdens because process planning decisions greatly influence machining performance. At present, greenability, a term used to indicate environmental friendliness, has been little considered as a major concern in the process planning stage because process planning decisions have focused on improving productivity aspects that include speed, cost and quality. Thus, it is essential to develop an eco-process planning approach that enables the harmonisation and enhancement of greenability performance while improving productivity performance, termed green productivity (GP). This paper presents the development of a GP-based process planning algorithm that enables the derivation of process parameters for improving GP in machining operations. The core mechanism of the algorithm is the realisation of the process improvement cycle that measures GP performance by the collection of machining data, quantifies this performance by categorical representation and predicts the performance through prediction models. To show the feasibility and applicability of the proposed algorithm, we have conducted an experiment and implemented a prototype system for a turning machining process.
Journal: International Journal of Production Research
Pages: 5085-5105
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2014.988884
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988884
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Template-Type: ReDIF-Article 1.0
Author-Name: Yumin He
Author-X-Name-First: Yumin
Author-X-Name-Last: He
Author-Name: Ram Rachamadugu
Author-X-Name-First: Ram
Author-X-Name-Last: Rachamadugu
Author-Name: Milton L. Smith
Author-X-Name-First: Milton L.
Author-X-Name-Last: Smith
Author-Name: Kathryn E. Stecke
Author-X-Name-First: Kathryn E.
Author-X-Name-Last: Stecke
Title: Segment set-based part input sequencing in flexible manufacturing systems
Abstract: 
 In competitive and uncertain business environments, manufacturing firms face various challenges requiring quick response, customisation and cost effectiveness to sustain competitive advantage. This paper proposes a segment set-based approach for the part input sequencing problem of flexible manufacturing systems (FMSs). The segment set theorems are built for the development of the segment set-based approach for the problem. A numerical study is done using simulation, and validated through statistical analyses. Our approach results in the significant performance improvement of the FMSs. Managerial implications are discussed. Further research is also provided.
Journal: International Journal of Production Research
Pages: 5106-5117
Issue: 17
Volume: 53
Year: 2015
Month: 9
X-DOI: 10.1080/00207543.2014.988887
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988887
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianya Ding
Author-X-Name-First: Jianya
Author-X-Name-Last: Ding
Author-Name: Shiji Song
Author-X-Name-First: Shiji
Author-X-Name-Last: Song
Author-Name: Rui Zhang
Author-X-Name-First: Rui
Author-X-Name-Last: Zhang
Author-Name: Jatinder N.D. Gupta
Author-X-Name-First: Jatinder N.D.
Author-X-Name-Last: Gupta
Author-Name: Cheng Wu
Author-X-Name-First: Cheng
Author-X-Name-Last: Wu
Title: Accelerated methods for total tardiness minimisation in no-wait flowshops
Abstract: 
 For the minimisation of total tardiness in no-wait flowshops, objective incremental properties are investigated in this paper to speed up the evaluation of candidate solutions. To explore the properties, we introduce a new concept of sensitive jobs and identify through experiments that the proportion of such jobs is very small. Instead of evaluating the tardiness of each job, we focus on the evaluation of sensitive jobs which will help to reduce the computational efforts. With these properties, the time complexity of the NEH-insertion procedure is reduced from O(n2)$ O(n^2) $ to approximately O(n)$ O(n) $ in average. Then, an accelerated NEH algorithm and an accelerated iterated greedy algorithm are designed for the problem. Since the NEH-insertion procedure constitutes the main computational burden for both algorithms, these algorithms will benefit directly from the speedup. Numerical computations show that the accelerated algorithms perform 10–40 times faster than the original algorithms on the middle- and large-sized instances. In addition, comparisons show that the proposed algorithms perform more efficiently and effectively than the existing heuristics and meta-heuristics.
Journal: International Journal of Production Research
Pages: 1002-1018
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.932935
File-URL: http://hdl.handle.net/10.1080/00207543.2014.932935
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Template-Type: ReDIF-Article 1.0
Author-Name: Yang Liu
Author-X-Name-First: Yang
Author-X-Name-Last: Liu
Author-Name: Liting Liang
Author-X-Name-First: Liting
Author-X-Name-Last: Liang
Title: Evaluating and developing resource-based operations strategy for competitive advantage: an exploratory study of Finnish high-tech manufacturing industries
Abstract: 
 Firms are struggling to achieve and maintain the competitive advantage in today’s turbulent business environment. How can we evaluate and (re)develop strategic initiatives that put into place operational capabilities to provide new sources of firm-level competitive advantage? This paper tries to explore the practical intersection of operations management and strategy from resource-based view by evaluating and developing the sustainability level of operational competitive advantage, that how well the resource-based strategy can support its operations. It develops a theoretical approach to integrate the core factors, which determine operational competitiveness performance – manufacturing strategy and its supporting resource allocation, into conceptual analytical models. The models utilise sense and respond (S&amp;R) methodology for dynamic decision-making to detect and adjust resource allocation and in turn optimise the resource-based strategy in order to develop the operational competitive advantage in a sustainable manner. Eighteen case companies in Finnish high-tech manufacturing industries are selected for in-depth study and analysis with proposed models to conclude how the optimal adjustments of resource-based strategy by supporting its operations can lead to sustainable competitive advantage (SCA). Constantly optimising resource allocation aligning with resource-based operations strategy supported by the S&amp;R idea of agile strategy implementations is proposed as the unique SCA.
Journal: International Journal of Production Research
Pages: 1019-1037
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.932936
File-URL: http://hdl.handle.net/10.1080/00207543.2014.932936
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Template-Type: ReDIF-Article 1.0
Author-Name: S. Mohammad Arabzad
Author-X-Name-First: S. Mohammad
Author-X-Name-Last: Arabzad
Author-Name: Mazaher Ghorbani
Author-X-Name-First: Mazaher
Author-X-Name-Last: Ghorbani
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: An evolutionary algorithm for a new multi-objective location-inventory model in a distribution network with transportation modes and third-party logistics providers
Abstract: 
 This paper proposes a multi-objective optimisation algorithm for solving the new multi-objective location-inventory problem (MOLIP) in a distribution centre (DC) network with the presence of different transportation modes and third-party logistics (3PL) providers. 3PL is an external company that performs all or part of a company’s logistics functions. In order to increase the efficiency and responsiveness in a supply chain, it is assumed that 3PL is responsible to manage inventory in DCs and deliver products to customers according to the provided plan. DCs are determined so as to simultaneously minimise three conflicting objectives; namely, total costs, earliness and tardiness, and deterioration rate. In this paper, a non-dominated sorting genetic algorithm (NSGA-II) is proposed to perform high-quality search using two-parallel neighbourhood search procedures for creating initial solutions. The potential of this algorithm is evaluated by its application to the numerical example. Then, the obtained results are analysed and compared with multi-objective simulated annealing (MOSA). It is concluded that this algorithm is capable of generating a set of alternative DCs considering the optimisation of multiple objectives, significantly improving the decision-making process involved in the distribution network design.
Journal: International Journal of Production Research
Pages: 1038-1050
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.938836
File-URL: http://hdl.handle.net/10.1080/00207543.2014.938836
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1038-1050




Template-Type: ReDIF-Article 1.0
Author-Name: Vincent F. Yu
Author-X-Name-First: Vincent F.
Author-X-Name-Last: Yu
Author-Name: Kuo-Jen Hu
Author-X-Name-First: Kuo-Jen
Author-X-Name-Last: Hu
Author-Name: An-Yuan Chang
Author-X-Name-First: An-Yuan
Author-X-Name-Last: Chang
Title: An interactive approach for the multi-objective transportation problem with interval parameters
Abstract: 
 The basic transportation problem (TP) deals with the transportation of goods from a set of supply points to a set of demand points so as to minimise linear transportation costs. The multi-objective transportation problem (MOTP) extends TP to take into consideration multiple conflicting objectives such as transportation cost, average delivery time of the commodities, unfulfilled demand and so forth. We develop an interactive approach to determine the preferred compromise solution for the MOTP where the coefficients of the objective functions and the source and destination parameters have been expressed as interval values by the decision-maker to deal with the impreciseness in the parameters. The proposed method is applied to a real-world MOTP faced by a leading provider of complete broadband access solutions. Results of the case study indicate that the developed method is a practical technique for solving the MOTP with interval parameters.
Journal: International Journal of Production Research
Pages: 1051-1064
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.939236
File-URL: http://hdl.handle.net/10.1080/00207543.2014.939236
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Template-Type: ReDIF-Article 1.0
Author-Name: Shih-Wei Lin
Author-X-Name-First: Shih-Wei
Author-X-Name-Last: Lin
Author-Name: Kuo-Ching Ying
Author-X-Name-First: Kuo-Ching
Author-X-Name-Last: Ying
Title: A multi-point simulated annealing heuristic for solving multiple objective unrelated parallel machine scheduling problems
Abstract: 
 This study considers the problem of job scheduling on unrelated parallel machines. A multi-objective multi-point simulated annealing (MOMSA) algorithm was proposed for solving this problem by simultaneously minimising makespan, total weighted completion time and total weighted tardiness. To assess the performance of the proposed heuristic and compare it with that of several benchmark heuristics, the obtained sets of non-dominated solutions were assessed using four multi-objective performance indicators. The computational results demonstrated that the proposed heuristic markedly outperformed the benchmark heuristics in terms of the four performance indicators. The proposed MOMSA algorithm can provide a new benchmark for future research related to the unrelated parallel machine scheduling problem addressed in this study.
Journal: International Journal of Production Research
Pages: 1065-1076
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.942011
File-URL: http://hdl.handle.net/10.1080/00207543.2014.942011
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Template-Type: ReDIF-Article 1.0
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Alessandro Persona
Author-X-Name-First: Alessandro
Author-X-Name-Last: Persona
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Title: Order picking system design: the storage assignment and travel distance estimation (SA&amp;TDE) joint method
Abstract: 
 Of all the warehouse activities, order picking is one of the most time-consuming and expensive. In order to improve the task, several researches have pointed out the need to consider jointly the layout of the warehouse, the storage assignment strategy and the routing policy to reduce travelled distances and picking time. This paper presents the storage assignment and travel distance estimation (SA&amp;TDE) joint method, a new approach useful to design and evaluate a manual picker-to-parts picking system, focusing on goods allocation and distances estimation. Starting from a set of picking orders received in a certain time range, this approach allows to evaluate the combinations of product codes assigned to storage locations, aisles, sections or warehouse areas and to assess the most relevant ones, for the best location and warehouse layout, with the aim of ensuring optimal picking routes, through the application of the multinomial probability distribution. A case study is developed as well, in order to clarify the concept that underlies the SA&amp;TDE joint method, and to show the validity and the flexibility of the approach, through the calculation of the saving at different levels of detail.
Journal: International Journal of Production Research
Pages: 1077-1093
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.944282
File-URL: http://hdl.handle.net/10.1080/00207543.2014.944282
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Template-Type: ReDIF-Article 1.0
Author-Name: Bertrand M.T. Lin
Author-X-Name-First: Bertrand M.T.
Author-X-Name-Last: Lin
Title: Two-stage flow shop scheduling with dedicated machines
Abstract: 
 This study is concerned with the manufacturing model that has a common machine at stage one and two parallel dedicated machines at stage two. All jobs need to be processed on the stage-one common machine. After the stage-one processing, the jobs of type 1 (type 2) will route to the first (second) dedicated machine at stage two. We first elaborate several published works on makespan minimisation which are not known to other streams of recent works. While the minimisation of maximum lateness is strongly NP-hard, we develop a linear-time algorithm to solve the case where two sequences of the two job types are given a priori.
Journal: International Journal of Production Research
Pages: 1094-1097
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.944631
File-URL: http://hdl.handle.net/10.1080/00207543.2014.944631
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoming Wang
Author-X-Name-First: Xiaoming
Author-X-Name-Last: Wang
Author-Name: Qingxin Chen
Author-X-Name-First: Qingxin
Author-X-Name-Last: Chen
Author-Name: Ning Mao
Author-X-Name-First: Ning
Author-X-Name-Last: Mao
Author-Name: Xindu Chen
Author-X-Name-First: Xindu
Author-X-Name-Last: Chen
Author-Name: Zhantao Li
Author-X-Name-First: Zhantao
Author-X-Name-Last: Li
Title: Proactive approach for stochastic RCMPSP based on multi-priority rule combinations
Abstract: 
 Most of the research efforts in project scheduling assumed complete information about the scheduling problem to be resolved. But in the real world, there are various uncertainties during the project execution, which made the plan, become invalid. Concerned with this problem, firstly, we analyse several major random events which lead to the uncertainty of available resources in manufacturers with make-to-order production strategy and consider the stochastic resource-constrained multi-project scheduling problem (RCMPSP). Then, we establish a Markov decision processes model and relevant procedures for this stochastic RCMPSP. Moreover, in order to deal with the common problem in stochastic optimisation – the curse of dimensionality, we propose a strategy approximation method that to limit the action space and state space by utilising several existing efficient priority rules and predefined probability threshold, respectively. With that we search for the suboptimal strategy to minimise the excepted total tardiness penalty using dynamic programming. Finally, we have given the proposed approach a computational test, result showing that our solution has good practicability.
Journal: International Journal of Production Research
Pages: 1098-1110
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.946570
File-URL: http://hdl.handle.net/10.1080/00207543.2014.946570
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Template-Type: ReDIF-Article 1.0
Author-Name: Victor Fernandez-Viagas
Author-X-Name-First: Victor
Author-X-Name-Last: Fernandez-Viagas
Author-Name: Jose M. Framinan
Author-X-Name-First: Jose M.
Author-X-Name-Last: Framinan
Title: A bounded-search iterated greedy algorithm for the distributed permutation flowshop scheduling problem
Abstract: 
 As the interest of practitioners and researchers in scheduling in a multi-factory environment is growing, there is an increasing need to provide efficient algorithms for this type of decision problems, characterised by simultaneously addressing the assignment of jobs to different factories/workshops and their subsequent scheduling. Here we address the so-called distributed permutation flowshop scheduling problem, in which a set of jobs has to be scheduled over a number of identical factories, each one with its machines arranged as a flowshop. Several heuristics have been designed for this problem, although there is no direct comparison among them. In this paper, we propose a new heuristic which exploits the specific structure of the problem. The computational experience carried out on a well-known testbed shows that the proposed heuristic outperforms existing state-of-the-art heuristics, being able to obtain better upper bounds for more than one quarter of the problems in the testbed.
Journal: International Journal of Production Research
Pages: 1111-1123
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.948578
File-URL: http://hdl.handle.net/10.1080/00207543.2014.948578
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Template-Type: ReDIF-Article 1.0
Author-Name: Hui Sun
Author-X-Name-First: Hui
Author-X-Name-Last: Sun
Author-Name: Shujin Fan
Author-X-Name-First: Shujin
Author-X-Name-Last: Fan
Author-Name: Xianle Shao
Author-X-Name-First: Xianle
Author-X-Name-Last: Shao
Author-Name: Jiangong Zhou
Author-X-Name-First: Jiangong
Author-X-Name-Last: Zhou
Title: A colour-batching problem using selectivity banks in automobile paint shops
Abstract: 
 This paper studies the colour-batching problem frequently raised in automobile paint shops, where selectivity banks are used as storage and retrieval systems to execute practices of resequencing car bodies before painting operations are performed. The purpose of resequencing is to obtain colour-oriented batches of cars in order to reduce setup costs incurred in paint shops. In this paper, two heuristic procedures, arraying and shuffling heuristics, are developed aimed at quickly and effectively achieving good colour-batching results. The arraying heuristic can be applied in the car placing stage, while the shuffling heuristic can be utilised in the car releasing stage. Computational experiments are carried out to evaluate the performance of the proposed heuristics. It is shown that the shuffling heuristic can generate comparable car retrieval sequences with an exact branch &amp; bound approach, and the proposed arraying and shuffling heuristics can be jointly applied to achieve good colour batching in a very short time duration of less than 0.4 s in comparison with two existing batching methods. These research findings can provide good insights into the practice of colour batching in automobile manufacturing.
Journal: International Journal of Production Research
Pages: 1124-1142
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.948970
File-URL: http://hdl.handle.net/10.1080/00207543.2014.948970
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Template-Type: ReDIF-Article 1.0
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: A branch-and-bound algorithm for two-stage no-wait hybrid flow-shop scheduling
Abstract: 
 This research investigates a two-stage no-wait hybrid flow-shop scheduling problem in which the first stage contains a single machine, and the second stage contains several identical parallel machines. The objective is to minimise the makespan. For this problem, existing literature emphasises on heuristics or optimal solutions for special cases, whereas this paper proposes a branch-and-bound algorithm. Several lower bounds for optimal and partial schedules are derived. Also, three dominance rules are deduced, and seven constructive heuristics are used to obtain initial upper bounds. Extensive computational tests on randomly generated problems are conducted. The results with comparisons indicate that the proposed bounds (especially partial lower bounds), dominance rules and the branch-and-bound algorithm are efficient.
Journal: International Journal of Production Research
Pages: 1143-1167
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.949363
File-URL: http://hdl.handle.net/10.1080/00207543.2014.949363
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Template-Type: ReDIF-Article 1.0
Author-Name: Michael Leyer
Author-X-Name-First: Michael
Author-X-Name-Last: Leyer
Author-Name: Jürgen Moormann
Author-X-Name-First: Jürgen
Author-X-Name-Last: Moormann
Title: Comparing concepts for shop floor control of information-processing services in a job shop setting: a case from the financial services sector
Abstract: 
 Controlling information-based service processes in the short term is a major challenge. Within these processes, information is collected, generated and transformed while customers are directly involved. Typically, such processes are characterised by a job shop layout that increases complexity relating to shop floor control. In contrast to manufacturing, such settings have rarely been addressed in the literature to date. This is surprising, as information-processing services exist in every industry. Thus, evidence about the impact of concepts for shop floor control in such pure service environments is needed. As a case study, we use one of the most intense information-processing industries – the financial services sector. A simulation model is built using process mining as a novel approach to gather a major part of the relevant data from business information systems. We identify nine concepts for shop floor control and simulate the usage of these in six scenarios. The results show that the concept that prioritises customer orders with the longest expected processing time is superior in cycle time over all six scenarios. The application of this concept leads to a reduction of the average cycle time of almost 50% in the case study.
Journal: International Journal of Production Research
Pages: 1168-1179
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.950356
File-URL: http://hdl.handle.net/10.1080/00207543.2014.950356
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1168-1179




Template-Type: ReDIF-Article 1.0
Author-Name: S.H. Choi
Author-X-Name-First: S.H.
Author-X-Name-Last: Choi
Author-Name: X.J. Wang
Author-X-Name-First: X.J.
Author-X-Name-Last: Wang
Title: Stochastic lot sizing for maximisation of shareholder wealth in make-to-order manufacturing
Abstract: 
 Current research in production planning focuses mainly on optimising operational objectives, taking little consideration of the primary principle of corporate governance and investor interests. Such approaches often overlook the critical roles of the cost structure and financial position of a firm, rendering the optimisation results unreliable. This paper studies stochastic lot sizing optimisation in make-to-order manufacturing, with an aim to maximise the full investor interests, well known as shareholder wealth. It presents a relatively simple yet reliable lead time model based on probability theory and stochastic processes. Moreover, the impacts of macroeconomic factors are examined to seek potential drivers for shareholder wealth. Theoretical optimality properties are proved to validate the effectiveness of the proposed model in dealing with batch production planning. Numerical examples and analytical results are presented to illustrate the significance of considering such economic and financial constraints and shareholder wealth. These results highlight that the proposed model can help improve shareholder wealth, and that it is a useful tool for examining the potential challenges and opportunities of shareholder wealth creation in production planning.
Journal: International Journal of Production Research
Pages: 1180-1197
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.951090
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951090
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1180-1197




Template-Type: ReDIF-Article 1.0
Author-Name: Alberto García-Villoria
Author-X-Name-First: Alberto
Author-X-Name-Last: García-Villoria
Author-Name: Said Salhi
Author-X-Name-First: Said
Author-X-Name-Last: Salhi
Title: Scheduling commercial advertisements for television
Abstract: 
 The problem of scheduling the commercial advertisements in the television industry is investigated. Each advertiser client demands that the multiple airings of the same brand advertisement should be as spaced as possible over a given time period. Moreover, audience rating requests have to be taken into account in the scheduling. This is the first time this hard decision problem is dealt with in the literature. We design two mixed integer linear programming (MILP) models. Two constructive heuristics, local search procedures and simulated annealing (SA) approaches are also proposed. Extensive computational experiments, using several instances of various sizes, are performed. The results show that the proposed MILP model which represents the problem as a network flow obtains a larger number of optimal solutions and the best non-exact procedure is one that uses SA.
Journal: International Journal of Production Research
Pages: 1198-1215
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.951095
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951095
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1198-1215




Template-Type: ReDIF-Article 1.0
Author-Name: R. Jamshidi
Author-X-Name-First: R.
Author-X-Name-Last: Jamshidi
Author-Name: Mir Mehdi Seyyed Esfahani
Author-X-Name-First: Mir Mehdi
Author-X-Name-Last: Seyyed Esfahani
Title: Reliability-based maintenance and job scheduling for identical parallel machines
Abstract: 
 Quality has an important role in manufacturing, and on the other hand, machine condition has a significant effect on quality. Based on this fact, all manufacturers integrate the production scheduling with maintenance activities to keep the machines in perfect conditions. In this paper, we propose a mixed integer nonlinear model to optimise the quality cost, maintenance cost, earliness–tardiness cost and interruption cost simultaneously. We assume that if machines work in undesirable conditions, their quality is reduced, resulting in quality cost. On the other hand, if the machines are repaired to decrease the quality cost, maintenance cost and other cost such as earliness–tardiness cost and interruption cost are imposed to the manufacturer. Several numerical instances are implemented by the proposed model to show the model effectiveness to obtain the best maintenance and production scheduling with minimum quality cost.
Journal: International Journal of Production Research
Pages: 1216-1227
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.951739
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951739
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1216-1227




Template-Type: ReDIF-Article 1.0
Author-Name: Gang Li
Author-X-Name-First: Gang
Author-X-Name-Last: Li
Author-Name: Mei-Ling Luo
Author-X-Name-First: Mei-Ling
Author-X-Name-Last: Luo
Author-Name: Wen-Jie Zhang
Author-X-Name-First: Wen-Jie
Author-X-Name-Last: Zhang
Author-Name: Xiao-Yuan Wang
Author-X-Name-First: Xiao-Yuan
Author-X-Name-Last: Wang
Title: Single-machine due-window assignment scheduling based on common flow allowance, learning effect and resource allocation
Abstract: 
 This article considers a single-machine due-window assignment scheduling problem based on a common flow allowance (i.e. all jobs have slack due window (SLKW)). We assume that the actual processing time of a job is a function of its position in a sequence (learning effect) and its continuously divisible and non-renewable resource allocation. The problem is to determine the optimal due windows, the optimal resource allocation and the processing sequence simultaneously to minimise costs for earliness, tardiness, the window location, window size, makespan and resource consumption. For a linear or a convex function of the amount of a resource allocated to the job, we provide a polynomial time algorithm, respectively. Some extensions of the problem are also shown.
Journal: International Journal of Production Research
Pages: 1228-1241
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.954057
File-URL: http://hdl.handle.net/10.1080/00207543.2014.954057
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1228-1241




Template-Type: ReDIF-Article 1.0
Author-Name: Kürşad Ağpak
Author-X-Name-First: Kürşad
Author-X-Name-Last: Ağpak
Author-Name: Saeed Zolfaghari
Author-X-Name-First: Saeed
Author-X-Name-Last: Zolfaghari
Title: Mathematical models for parallel two-sided assembly line balancing problems and extensions
Abstract: 
 In this study, a mixed integer programming model for the parallel two-sided assembly line balancing problem is developed. Several extensions such as a cost-oriented model, a model with time and space constraints and a model with assignment restrictions which considers characteristics of parallel lines are also presented. The model has been tested on a number of test problems from the literature. The results for different objective functions are analysed on the test problems.
Journal: International Journal of Production Research
Pages: 1242-1254
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.955218
File-URL: http://hdl.handle.net/10.1080/00207543.2014.955218
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhitao Xu
Author-X-Name-First: Zhitao
Author-X-Name-Last: Xu
Author-Name: X.G. Ming
Author-X-Name-First: X.G.
Author-X-Name-Last: Ming
Author-Name: Maokuan Zheng
Author-X-Name-First: Maokuan
Author-X-Name-Last: Zheng
Author-Name: Miao Li
Author-X-Name-First: Miao
Author-X-Name-Last: Li
Author-Name: Lina He
Author-X-Name-First: Lina
Author-X-Name-Last: He
Author-Name: Wenyan Song
Author-X-Name-First: Wenyan
Author-X-Name-Last: Song
Title: Cross-trained workers scheduling for field service using improved NSGA-II
Abstract: 
 The proper balancing of geographically distributed task schedules and the associated workforce distributions are critical determinants of productivity in any people-centric production environment. The paper has investigated the cross-trained workers scheduling problem considering the qualified personal allocation and temporally cooperation of engineers simultaneously. A 0–1 programming model is developed and the non-dominated sorting genetic algorithm-II (NSGA-II) is adopted to deal with the NP-hard problem. In order to enforce the NSGA-II, significant improvements are made to function the approach in a more efficient way. It is observed that the improved NSGA-II outperforms the original NSGA-II in the experimental test. The promising outcomes of the formulation in the experiment make its implementation easily customisable and transferable for solving other intricate problems in the context of skilled workforce scheduling. Furthermore, the modified NSGA II can be used as an efficient and effective tool for other multiobjective optimisation problems.
Journal: International Journal of Production Research
Pages: 1255-1272
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.955923
File-URL: http://hdl.handle.net/10.1080/00207543.2014.955923
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1255-1272




Template-Type: ReDIF-Article 1.0
Author-Name: A. Bożek
Author-X-Name-First: A.
Author-X-Name-Last: Bożek
Author-Name: M. Wysocki
Author-X-Name-First: M.
Author-X-Name-Last: Wysocki
Title: Flexible job shop with continuous material flow
Abstract: 
 A new scheduling problem, the continuous flow flexible job shop (CF-FJS) is proposed. The formulation combines the well-known flexible job shop (FJS) problem and a dedicated continuous material flow model (MFM). In the MFM, operations are represented by material flow functions derived by integration of arbitrarily defined speed patterns. Two main concepts of the MFM formalism, i.e. variable speed of processing and continuous material flow, lead to position-dependent processing times and overlapping in operations which extend standard FJS formulation. Properties of the CF-FJS are investigated. A tabu search sched uling algorithm utilising these properties is proposed. Effective neighbourhood functions are defined based on elimination approaches. Two auxiliary procedures: search intensification level switching and fast feasibility detection are added to improve algorithm efficiency. The algorithm is verified using dedicated benchmark instances which comprise non-trivial representations of the CF-FJS specific features, i.e. machine efficiency patterns and minimum inter-operation buffers. The research is motivated by task scheduling in a fastener factory, but the presented results can be useful in many domains, such as production of granular goods, steel details, glass and fluids. The solution can be used in real-world applications. The published results can be helpful in testing new CF-FJS scheduling algorithms.
Journal: International Journal of Production Research
Pages: 1273-1290
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.955925
File-URL: http://hdl.handle.net/10.1080/00207543.2014.955925
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1273-1290




Template-Type: ReDIF-Article 1.0
Author-Name: Y. Emre Kılıç
Author-X-Name-First: Y. Emre
Author-X-Name-Last: Kılıç
Author-Name: Umut Rıfat Tuzkaya
Author-X-Name-First: Umut Rıfat
Author-X-Name-Last: Tuzkaya
Title: A two-stage stochastic mixed-integer programming approach to physical distribution network design
Abstract: 
 In many industries, distribution activities are realised in a dynamic environment including uncertainties. Besides, adding transportation mode alternatives, inventory-stocking opportunities in wholesalers, unmet demand permission in distribution centres, etc. increase the difficulty of problem modelling and solving for large-scale networks. In this study, the problem of physical distribution network (DN) design with profit maximisation objective function is modelled to tackle with realistic cases. Two-stage stochastic mixed-integer programming method is used to handle the uncertainties and to consider the probable scenarios. The first-stage decisions of the proposed model are related with the selection of facility location in strategic level, and the second-stage decisions are related with the transported and stocked products or unmet demand quantities. Here, a multi-product, two-echelon, multi-mode and multi-period network model is applied to a hypothetically created problem, inspired from the physical DN of home appliance companies. Various scenarios including stochastic demand and price data with different realisation probabilities are used in the model. The motivation of this study is the lack of reaching a global optimum result using transportation modes as stochastic parameters, considering their own lead times and capacities. Finally, various results are obtained for different cases and analysed in detail.
Journal: International Journal of Production Research
Pages: 1291-1306
Issue: 4
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.957871
File-URL: http://hdl.handle.net/10.1080/00207543.2014.957871
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1291-1306




Template-Type: ReDIF-Article 1.0
Author-Name: R.S. Ulloa
Author-X-Name-First: R.S.
Author-X-Name-Last: Ulloa
Author-Name: A.F. Mac Cawley
Author-X-Name-First: A.F.
Author-X-Name-Last: Mac Cawley
Author-Name: G.A. Santelices
Author-X-Name-First: G.A.
Author-X-Name-Last: Santelices
Author-Name: R. Pascual
Author-X-Name-First: R.
Author-X-Name-Last: Pascual
Title: Technology investment effects in performance-based maintenance contracts
Abstract: 
 This work analyses the effects of a fixed initial investment in technology or infrastructure on performance-based maintenance contracts. We present a mathematical expression which reflects the trade-off between an upfront technology investment by the vendor and the cost of required future interventions. We develop a mathematical model of a performance-based maintenance contract that uses this technology trade-off expression and determines the value of the contract for each party. Contractually, the client indicates the duration of the contract and the optimal number of maintenance interventions to maximise asset availability; the vendor quotes the cost for the requested interventions. We study how the initial investment and the contract parameters affect the net present value for each party and the supply chain, demonstrating the existence of an optimal relation between the number of preventive maintenance interventions and level of investment. We derive the optimal contract parameters for the client, vendor and chain and show lack of coordination between the parties. To achieve coordination, we present a revenue sharing mechanism which maximises the value for the chain. Finally, an industry study case with data from the mining sector is presented. Results indicate that by investing and coordinating, the entire supply chain can improve the contract NPV by 149.7%.
Journal: International Journal of Production Research
Pages: 2628-2645
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1374573
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1374573
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2628-2645




Template-Type: ReDIF-Article 1.0
Author-Name: Eugene Levner
Author-X-Name-First: Eugene
Author-X-Name-Last: Levner
Author-Name: Alexander Ptuskin
Author-X-Name-First: Alexander
Author-X-Name-Last: Ptuskin
Title: Entropy-based model for the ripple effect: managing environmental risks in supply chains
Abstract: 
 Due to increasing diversity and growing size of modern industrial supply chains, today problems of identification, assessment and mitigation of disruption risks become challenging goals of the supply chain risk management. In this paper, we focus on environmental (ecological) risks in supply chains which represent threats of adverse effects on living organisms, facilities and environment by effluents, emissions, wastes, resource depletion, etc. arising due to supply chain’s activities. Harmful environmental disruptions may ripple through the supply chain components like a wave. The paper presents the entropy-based optimisation model for reducing the supply chain model size and assessing the economic loss caused by the environmental risks subject to the ripple effect. A main advantage of the suggested entropy-based approach is that it permits to essentially simplify the hierarchical tree-like model of the supply chain, at the same time retaining the basic knowledge about main risk sources.
Journal: International Journal of Production Research
Pages: 2539-2551
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1374575
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1374575
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2539-2551




Template-Type: ReDIF-Article 1.0
Author-Name: Bing-Bing Cao
Author-X-Name-First: Bing-Bing
Author-X-Name-Last: Cao
Author-Name: Zhi-Ping Fan
Author-X-Name-First: Zhi-Ping
Author-X-Name-Last: Fan
Title: Ordering and sales effort investment for temperature-sensitive products considering retailer’s disappointment aversion and elation seeking
Abstract: 
 We investigate a retailer’s optimal policy of ordering and sales effort investment for temperature-sensitive products in a stylised newsvendor setting considering the effects of the retailer’s disappointment aversion and elation seeking. We provide a function to describe the demand for temperature-sensitive products and a psychological utility function to capture the retailer’s perceived utility of disappointment aversion and elation seeking. Next, we construct four joint ordering and sales effort decision models by integrating the profit and psychological utility for high temperature-sensitive products, medium temperature-sensitive products, low temperature-sensitive products and high–low temperature-sensitive products, respectively. By solving the constructed models, we determine the optimal policy of order quantity and sales effort level. We find that the average temperature in the selling season, the temperature sensitivity parameter, disappointment aversion degree and elation seeking degree can affect the retailer’s optimal policy, and the trends and extents of the effects for each temperature-sensitive product may be different from those for the other temperature-sensitive products. Our models also suggest that the optimal policy for temperature-sensitive products is more conservative than the one for general non-temperature-sensitive products. The policy of a retailer who is primarily concerned with disappointment aversion is more conservative than the one of a disappointment-neutral retailer. The policy of a retailer who mainly focuses on elation seeking is more radical than the one of an elation-neutral retailer. Our results show that a retailer must consider the effects of temperature and psychological behaviour on policy and should make decisions regarding order quantity and sales effort level according to the temperature sensitivity type of selling products and degrees of disappointment aversion and elation seeking.
Journal: International Journal of Production Research
Pages: 2411-2436
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1374577
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1374577
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2411-2436




Template-Type: ReDIF-Article 1.0
Author-Name: Weixi Han
Author-X-Name-First: Weixi
Author-X-Name-Last: Han
Author-Name: Yuan Huang
Author-X-Name-First: Yuan
Author-X-Name-Last: Huang
Author-Name: Douglas Macbeth
Author-X-Name-First: Douglas
Author-X-Name-Last: Macbeth
Title: Performance measurement of cross-culture supply chain partnership: a case study in the Chinese automotive industry
Abstract: 
 This study explores a performance measurement system for a dynamic supply chain partnership in a cross-cultural context. An initial framework is constructed by reviewing the existing literature, followed by an in-depth case study in the Chinese automotive industry, where the framework is refined to address the multi-cultural setting. A performance measurement, system which includes the relationship strategy and operational measurement criteria for a supply chain partnership, has been developed. The relationship strategy contains elements of strategy orientation, management style, interdependence, mutual organisational characteristics and common goals. The operational measurement criteria consist of commitment, trust, communication behaviour, information sharing, participation decision, quality, production performance, delivery, cost, supplier strength, attitude, compromise and loyalty. The last three operational measurement criteria are found to be particularly relevant to the cross-cultural feature. While existing studies tend to focus on either specific measures or individual organisations, this paper for the first time proposes a comprehensive framework to measure the performance of supply chain partnerships. The cross-cultural perspective provides a further unique view on how a performance measurement system can be responsive to the dynamics in practice.
Journal: International Journal of Production Research
Pages: 2437-2451
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1377357
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1377357
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2437-2451




Template-Type: ReDIF-Article 1.0
Author-Name: Ji-Eun Kim
Author-X-Name-First: Ji-Eun
Author-X-Name-Last: Kim
Author-Name: David A. Nembhard
Author-X-Name-First: David A.
Author-X-Name-Last: Nembhard
Title: Parametric empirical Bayes estimation of individual time-pressure reactivity
Abstract: 
 As the global workplace becomes increasingly industrialised and competitive, organisations are finding that it is crucial to manage their time more efficiently. An important topic in time management is the influence of time pressure under deadlines on individual performance. People often do less work when deadlines are far off; they then increase their work rate as deadlines approach. Although researchers have studied from various perspectives how individuals work towards deadlines, the measurement of individual differences in pacing styles has been based mostly on self-report questionnaire instruments or on frequentist estimation, which often relies on sparse data in practice. The purpose of this study is to estimate distributions of individuals’ time-pressure reactivity using a parametric empirical Bayesian estimation (PEB) approach, and to determine an adequate sample size to estimate posterior distributions. The use of PEB approach was motivated by the varied nature of sample sizes across individuals and task types. In this study, two data-sets were used, one from an online course and another from an Anti-Air Warfare Coordinator task. From these two different data-sets, we generated informative individualised posterior distributions for time-pressure activity, and the PEB approach was validated by showing the intervals of posterior distribution were smaller than the intervals of point estimates for time-pressure reactivity. In addition, we found that 18–40% of the actual number of samples was sufficient to estimate posterior distributions to within 10% error, and this finding is advantageous in cases in which collecting large sets of data may be time-consuming or expensive. This study demonstrates the effectiveness of Bayesian estimation in determining individual differences in time-pressure reactivity to deadlines using individualised posterior distributions rather than point estimates, which is beneficial for understanding differences in behaviour across a diverse population.
Journal: International Journal of Production Research
Pages: 2452-2463
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1380321
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1380321
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2452-2463




Template-Type: ReDIF-Article 1.0
Author-Name: Yaping Zhao
Author-X-Name-First: Yaping
Author-X-Name-Last: Zhao
Author-Name: Xiaoyun Xu
Author-X-Name-First: Xiaoyun
Author-X-Name-Last: Xu
Author-Name: Haidong Li
Author-X-Name-First: Haidong
Author-X-Name-Last: Li
Author-Name: Yanni Liu
Author-X-Name-First: Yanni
Author-X-Name-Last: Liu
Title: Stochastic customer order scheduling with setup times to minimize expected cycle time
Abstract: 
 Short cycle time of customer orders is crucial for companies to achieve mass customization and quick response. However, the complicated and stochastic environment, especially the exist of setup times, makes it extremely challenging to optimize the efficiency of a system. In this study, stochastic customer orders are scheduled to minimize their expect cycle time with the consideration of setup times. Customer orders arrive dynamically, and each order requires multiple product types with random workloads. These workloads will be assigned to a set of unrelated parallel machines to be processed. Particularly, for each machine, setup times are required whenever there is a product type changeover, and the lengthes are both machine- and product type-dependent. This paper intends to minimize the long-run expected order cycle time by proper policies including workload allocation and type sequencing. The impacts of product type sequence and workload variance are evaluated through theoretical study and several analytical properties are developed. With the help of these properties, three scheduling algorithms are proposed, and a lower bound is derived to evaluate the proposed algorithms. Computational experiment is conducted to demonstrate the effectiveness of the lower bound and the algorithms under various circumstances, and several important managerial insights are also provided.
Journal: International Journal of Production Research
Pages: 2684-2706
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1381348
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1381348
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2684-2706




Template-Type: ReDIF-Article 1.0
Author-Name: Santanu Mandal
Author-X-Name-First: Santanu
Author-X-Name-Last: Mandal
Author-Name: Rajneesh Ranjan Jha
Author-X-Name-First: Rajneesh Ranjan
Author-X-Name-Last: Jha
Title: Exploring the importance of collaborative assets to hospital-supplier integration in healthcare supply chains
Abstract: 
 Research has established the dominant influence of collaboration and integration in manufacturing supply chains. However, the role of these characteristics in healthcare supply chain operations and performance has not yet been investigated. The current research proposes three assets under collaboration as dominant enablers of hospital-supplier integration: collaborative planning, collaborative execution and collaborative decision-making. Considering the advances in technology in healthcare, we propose that technology orientation moderates the above linkages. Survey-based responses were collected from hospitals, chemistry and pharmaceuticals, and medical equipment and surgical suppliers that are key entities in healthcare supply chains. In total, 239 completed responses were collected and analysed using structural equation modelling. The findings suggest all three as dominant enablers of hospital-supplier integration. Furthermore, technology orientation was found to positively moderate the impact of planning and execution on hospital-supplier integration. This orientation also suggested that hospital-supplier integration results in positive operational performance.
Journal: International Journal of Production Research
Pages: 2666-2683
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1381349
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1381349
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2666-2683




Template-Type: ReDIF-Article 1.0
Author-Name: Alireza Faraz
Author-X-Name-First: Alireza
Author-X-Name-Last: Faraz
Author-Name: Cédric Heuchenne
Author-X-Name-First: Cédric
Author-X-Name-Last: Heuchenne
Author-Name: Erwin Saniga
Author-X-Name-First: Erwin
Author-X-Name-Last: Saniga
Title: An exact method for designing Shewhart  and S2 control charts to guarantee in-control performance
Abstract: 
 The in-control performance of Shewhart and S2 control charts with estimated in-control parameters has been evaluated by a number of authors. Results indicate that an unrealistically large amount of Phase I data is needed to have the desired in-control average run length (ARL) value in Phase II. To overcome this problem, it has been recommended that the control limits be adjusted based on a bootstrap method to guarantee that the in-control ARL is at least a specified value with a certain specified probability. In this article we present simple formulas using the assumption of normality to compute the control limits and therefore, users do not have to use the bootstrap method. The advantage of our proposed method is in its simplicity for users; additionally, the control chart constants do not depend on the Phase I sample data.
Journal: International Journal of Production Research
Pages: 2570-2584
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1384580
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1384580
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:7:p:2570-2584




Template-Type: ReDIF-Article 1.0
Author-Name: Yoshiki Shimomura
Author-X-Name-First: Yoshiki
Author-X-Name-Last: Shimomura
Author-Name: Yutaro Nemoto
Author-X-Name-First: Yutaro
Author-X-Name-Last: Nemoto
Author-Name: Takatoshi Ishii
Author-X-Name-First: Takatoshi
Author-X-Name-Last: Ishii
Author-Name: Toshiyuki Nakamura
Author-X-Name-First: Toshiyuki
Author-X-Name-Last: Nakamura
Title: A method for identifying customer orientations and requirements for product–service systems design
Abstract: 
 For manufacturers, developing product–service systems (PSSs) is getting more important because of the trends of servitisation and creating social value. A PSS is a social system where multiple actors mutually provide products and services. A PSS design, therefore, must take into account various actors as customers. However, existing methods provide an insufficient solution as to how various customers should be handled in an analysis to identify and accommodate various customer preferences and requirements. To tackle this issue, this article proposes a new method of identifying customers’ orientations and requirements for PSS design. The proposed method employs a combination of topic analysis, persona and scenario approaches. The effectiveness of the method is demonstrated with its application to an urban development case. Through the demonstration, its practical benefits are concluded as follows: consistent and logical results of requirement analysis and insights into a new market for manufacturers.
Journal: International Journal of Production Research
Pages: 2585-2595
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1384581
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1384581
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Template-Type: ReDIF-Article 1.0
Author-Name: Kan Wu
Author-X-Name-First: Kan
Author-X-Name-Last: Wu
Author-Name: Ning Zhao
Author-X-Name-First: Ning
Author-X-Name-Last: Zhao
Author-Name: Yichi Shen
Author-X-Name-First: Yichi
Author-X-Name-Last: Shen
Title: Analysis and approximation for the performance of a workstation with various types of setups
Abstract: 
 Setups commonly exist in flexible manufacturing systems. Modelling the queue time correctly is of fundamental importance in evaluating the performance of manufacturing systems. An insightful classification is the first step towards correct modelling. Through the observation of practical production lines, two types of setups are classified: state-induced setups and product-induced setups. The product-induced setups can be a changeover setup or a replacement setup. Changeover setups are induced by switching manufacturing processes between products, whereas replacement setups are caused by changing components or consumables. Approximate models for the mean queue time of different setup types are proposed based on their distinct properties. The proposed models are validated with simulations and perform well in the examined cases.
Journal: International Journal of Production Research
Pages: 2596-2610
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1384582
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1384582
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Template-Type: ReDIF-Article 1.0
Author-Name: Wolfgang Albrecht
Author-X-Name-First: Wolfgang
Author-X-Name-Last: Albrecht
Author-Name: Martin Steinrücke
Author-X-Name-First: Martin
Author-X-Name-Last: Steinrücke
Title: Coordinating continuous-time distribution and sales planning of perishable goods with quality grades
Abstract: 
 A variety of industries handling perishable goods is faced with the challenge of reducing lead times in order to ensure the best possible freshness of products at the point of sales. Considering a short-term multi-day planning horizon, the implementation of quantitative optimisation approaches with a continuous-time representation is most appropriate for planning and scheduling. However, as the quality measures are usually standardised by discrete grades, coordination take thresholds of maximum delivery times into account. For this purpose, a new mixed-integer linear programming model is developed. It enables to assess complete material flows, whose formal composition originates in a method based on power sets on the one hand, but additionally allows for the exact scheduling of partial material flows between sites. Specific transportation conditions that need to be imposed with respect to shelf-life are included. The efficiency of the model is confirmed by comparison with an equivalent mixed-integer linear formulation that uses path variables for modelling complete material flows. Besides an illustrative example motivated by the real-life problem of a fresh produce company supplying a wholesaler group, both model formulations are validated within a numerical analysis composed of 10 scenarios with different numbers of suppliers, warehouses, markets and product variants. Each scenario includes six instances with randomly generated data. As a result of the computations using high-performance hardware and software, it was shown that the formulation based on power sets was superior in each instance, as it enabled determining optimal solutions within significantly reduced computation times.
Journal: International Journal of Production Research
Pages: 2646-2665
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1384584
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1384584
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Template-Type: ReDIF-Article 1.0
Author-Name: Belgacem Bettayeb
Author-X-Name-First: Belgacem
Author-X-Name-Last: Bettayeb
Author-Name: Nadjib Brahimi
Author-X-Name-First: Nadjib
Author-X-Name-Last: Brahimi
Author-Name: David Lemoine
Author-X-Name-First: David
Author-X-Name-Last: Lemoine
Title: Integrated dynamic single item lot-sizing and quality inspection planning
Abstract: 
 This paper proposes an integrated model for single item dynamic lot-sizing problem and Quality Inspection Planning (QIP). The objective is to provide a model of production planning that takes into account a targeted level of outgoing quality or an Acceptable quality level (AQL) when the manufacturing system inherently generates a proportion of defectives that increases significantly when the system switches from the in-control state to the out-of-control state. The average outgoing quality of each period of time of the planning horizon is bounded as a function of the inspection capacity. The effects of integrating QIP are analysed and discussed through several experiments representing different quality control system’s parameters, i.e. inspection capacity, inspection cost and AQL. The simulation results show that it is very important to take into account the inspection process into production planning decisions. This study will help the decision-makers to negotiate service levels or react properly to given customer quality requirements based on cost and lead time parameters in addition to their process characteristics in terms of capability and stability.
Journal: International Journal of Production Research
Pages: 2611-2627
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1385869
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1385869
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Template-Type: ReDIF-Article 1.0
Author-Name: Milan Zdravković
Author-X-Name-First: Milan
Author-X-Name-Last: Zdravković
Author-Name: Jelena Zdravković
Author-X-Name-First: Jelena
Author-X-Name-Last: Zdravković
Author-Name: Alexis Aubry
Author-X-Name-First: Alexis
Author-X-Name-Last: Aubry
Author-Name: Néjib Moalla
Author-X-Name-First: Néjib
Author-X-Name-Last: Moalla
Author-Name: Wided Guedria
Author-X-Name-First: Wided
Author-X-Name-Last: Guedria
Author-Name: João Sarraipa
Author-X-Name-First: João
Author-X-Name-Last: Sarraipa
Title: Domain framework for implementation of open IoT ecosystems
Abstract: 
 The current Internet-of-things (IoT) hype, pushed by the unprecedented rate of the technological enablers’ innovation, is threatening to leave behind some major, not so obvious, unresolved issues. IoT platforms will extend existing enterprise information systems (EIS) infrastructures to encompass cross-domain sensing and actuating capabilities, thus introducing additional complexity and major risks to the implementation. Furthermore, IoT platforms are typically driven by models of the trivial complexity; they support very simple data structures and almost no business logic implementation. Finally, IoT systems are today managed centrally, which often means less openness, less flexibility and greater change management costs. In this article, we provide the overview of the scientific disciplines which could contribute to the resolution of the IoT implementation problem, namely requirements engineering, change management/continuous improvement, model-based systems engineering, system architecture design, interoperability and policy and regulatory aspects. Then, we identify the challenges of these contributions in the context of IoT and finally make an attempt to identify research directions which could have a significant impact. The discussion of the challenges and opportunities is illustrated by the proposed domain framework for implementation of open IoT ecosystems.
Journal: International Journal of Production Research
Pages: 2552-2569
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1385870
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1385870
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Template-Type: ReDIF-Article 1.0
Author-Name: Anupma Yadav
Author-X-Name-First: Anupma
Author-X-Name-Last: Yadav
Author-Name: S.C. Jayswal
Author-X-Name-First: S.C.
Author-X-Name-Last: Jayswal
Title: Modelling of flexible manufacturing system: a review
Abstract: 
 A flexible manufacturing system (FMS) due to its ability of being flexible in nature is concerned with automatic production of different parts in medium range. In short, it can be regarded as an automated manufacturing system. In this paper, an insight on previous work in the area of FMS modelling has been provided with an overview of research and development for better understanding of FMS. It serves as a medium for investigation of work that are accomplished by using different modelling techniques in FMS like mathematical, artificial intelligence, hierarchical, multi criteria decision-making method, Petri Nets and simulation. This paper will help researchers who are keen to do research in the area of FMS modelling, by highlighting contribution of available techniques in the field of FMS. It will also help them in deciding which modelling techniques can be used for a given problem. At last, comparison of different parameters considered in the recent papers of modelling FMS has been provided in the form of Table, along with a clear vision related to those works that still need to be investigated.
Journal: International Journal of Production Research
Pages: 2464-2487
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1387302
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1387302
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Template-Type: ReDIF-Article 1.0
Author-Name: Oğuzhan Ahmet Arık
Author-X-Name-First: Oğuzhan Ahmet
Author-X-Name-Last: Arık
Author-Name: M. Duran Toksarı
Author-X-Name-First: M. Duran
Author-X-Name-Last: Toksarı
Title: Multi-objective fuzzy parallel machine scheduling problems under fuzzy job deterioration and learning effects
Abstract: 
 This paper investigates a multi-objective parallel machine scheduling problem under fully fuzzy environment with fuzzy job deterioration effect, fuzzy learning effect and fuzzy processing times. Due dates are decision variables for the problem and objective functions are to minimise total tardiness penalty cost, to minimise earliness penalty cost and to minimise cost of setting due dates. Due date assignment problems are significant for Just-in-Time (JIT) thought. A JIT company may want to have optimum schedule by minimising cost combination of earliness, tardiness and setting due dates. In this paper, we compare different approaches for modelling fuzzy mathematical programming models with a local search algorithm based on expected values of fuzzy parameters such as job deterioration effect, learning effect and processing times.
Journal: International Journal of Production Research
Pages: 2488-2505
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1388932
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1388932
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Template-Type: ReDIF-Article 1.0
Author-Name: Xuran Gong
Author-X-Name-First: Xuran
Author-X-Name-Last: Gong
Author-Name: Qianwang Deng
Author-X-Name-First: Qianwang
Author-X-Name-Last: Deng
Author-Name: Guiliang Gong
Author-X-Name-First: Guiliang
Author-X-Name-Last: Gong
Author-Name: Wei Liu
Author-X-Name-First: Wei
Author-X-Name-Last: Liu
Author-Name: Qinghua Ren
Author-X-Name-First: Qinghua
Author-X-Name-Last: Ren
Title: A memetic algorithm for multi-objective flexible job-shop problem with worker flexibility
Abstract: 
 In existing scheduling models, the flexible job-shop scheduling problem mainly considers machine flexibility. However, human factor is also an important element existing in real production that is often neglected theoretically. In this paper, we originally probe into a multi-objective flexible job-shop scheduling problem with worker flexibility (MO-FJSPW). A non-linear integer programming model is presented for the problem. Correspondingly, a memetic algorithm (MA) is designed to solve the proposed MO-FJSPW whose objective is to minimise the maximum completion time, the maximum workload of machines and the total workload of all machines. A well-designed chromosome encoding/decoding method is proposed and the adaptive genetic operators are selected by experimental studies. An elimination process is executed to eliminate the repeated individuals in population. Moreover, a local search is incorporated into the non-dominated sorting genetic algorithm II. In experimental phase, the crossover operator and elimination operator in MA are examined firstly. Afterwards, some extensive comparisons are carried out between MA and some other multi-objective algorithms. The simulation results show that the MA performs better for the proposed MO-FJSPW than other algorithms.
Journal: International Journal of Production Research
Pages: 2506-2522
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1388933
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1388933
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Template-Type: ReDIF-Article 1.0
Author-Name: Guilherme Eduardo da Cunha Barbosa
Author-X-Name-First: Guilherme Eduardo da Cunha
Author-X-Name-Last: Barbosa
Author-Name: Gilberto Francisco Martha de Souza
Author-X-Name-First: Gilberto Francisco Martha de
Author-X-Name-Last: Souza
Title: A method for defence product major overhaul analysis focusing on interfaces redesign and extended life supportability
Abstract: 
 Due to high acquisition costs of new units, defence products can be subjected to life extension processes, sometimes not previously planned during their life cycle. These processes are characterised by widespread maintenance tasks and they can be denominated as major overhauls. The main objective of this paper is to propose a methodology to aid the major overhaul technical management. In general, the major overhaul defines the scope of maintenance and modernisation. Main problems about maintenance are managed by risk-based decision-making for determination of replacement rules and quantities of spares. The need for redesign of parts that interacts with the upgraded subsystems is evaluated by design structure matrix and a HAZOP-based analysis aiming at achieving product performance requirements. The proposed method is a support tool to the major overhaul manager, not replacing technical methodologies that are specific to each branch of the overhauled product. The proposed method was applied to a major overhaul project of an armoured personnel carrier. The results enabled a better characterisation of detailed design, analysing risks in the context of maintenance and modernisation aiming at controlling modernised product life cycle.
Journal: International Journal of Production Research
Pages: 2523-2538
Issue: 7
Volume: 56
Year: 2018
Month: 4
X-DOI: 10.1080/00207543.2017.1391414
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1391414
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Template-Type: ReDIF-Article 1.0
Author-Name: Youngbum Hur
Author-X-Name-First: Youngbum
Author-X-Name-Last: Hur
Author-Name: Jonathan F. Bard
Author-X-Name-First: Jonathan F.
Author-X-Name-Last: Bard
Author-Name: Rodolfo Chacon
Author-X-Name-First: Rodolfo
Author-X-Name-Last: Chacon
Title: Hierarchy machine set-up for multi-pass lot scheduling at semiconductor assembly and test facilities
Abstract: 
 In this paper, we examine the set-up problem at semiconductor assembly and test facilities in a multi-machine, multi-tooling environment. Our primary objectives are to minimise the number of shortages of key devices and to maximise weighted throughput over a 2–5-day planning horizon. When a machine set-up is called for three components must be taken into account: tooling, package size and flow. Each in turn imposes increasing set-up times, ranging from a few minutes to half a day. To balance system efficiency with meeting customer demand, a hierarchical approach is taken. Priority is first given to set-ups that can process (hot) lots that reduce demand shortages. Next, changeover time is factored into the decision. Here, priority is given to the component that takes the least amount of time. Our model determines machine set-ups, lot assignments and lot sequences using a greedy randomised adaptive search procedure. The results indicate that reducing set-up times can reduce hot-lot shortages by up to 6.6% over a two-day period and that following the hierarchy set-up rule while prioritising key device lots can reduce shortages by up to 10%. Moreover, when reentrant flow is taken into account, improvements of up to 42% may be realised.
Journal: International Journal of Production Research
Pages: 4351-4370
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2017.1380327
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1380327
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Template-Type: ReDIF-Article 1.0
Author-Name: Na Geng
Author-X-Name-First: Na
Author-X-Name-Last: Geng
Author-Name: Xiaolan Xie
Author-X-Name-First: Xiaolan
Author-X-Name-Last: Xie
Author-Name: Zheng Zhang
Author-X-Name-First: Zheng
Author-X-Name-Last: Zhang
Title: Addressing healthcare operational deficiencies using stochastic and dynamic programming
Abstract: 
 This paper provides an overview of our 10-year research on the application of stochastic and dynamic programming techniques to address health care operational deficiencies in a demand-driven way. We first describe the main operational deficiencies motivating our research in the capacity allocation and scheduling of diagnostic equipment and operating rooms. We then present main findings of extensive field studies to show current practices and key features of the problems under consideration. Applications of stochastic and dynamic programming to these problems are discussed by giving key assumptions, mathematical models, properties of the optimal solution, solution approaches and main numerical findings. The relaxation of the key assumptions is shown to lead to various future research directions that have drawn significant interests of the operations research and industrial engineering communities. We conclude by identifying barriers and potential solutions on the path from theories to applications.
Journal: International Journal of Production Research
Pages: 4371-4390
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2017.1397789
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1397789
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Template-Type: ReDIF-Article 1.0
Author-Name: Jhonattan Miranda
Author-X-Name-First: Jhonattan
Author-X-Name-Last: Miranda
Author-Name: Roberto Pérez-Rodríguez
Author-X-Name-First: Roberto
Author-X-Name-Last: Pérez-Rodríguez
Author-Name: Vicente Borja
Author-X-Name-First: Vicente
Author-X-Name-Last: Borja
Author-Name: Paul K. Wright
Author-X-Name-First: Paul K.
Author-X-Name-Last: Wright
Author-Name: Arturo Molina
Author-X-Name-First: Arturo
Author-X-Name-Last: Molina
Title: Sensing, smart and sustainable product development (S3 product) reference framework
Abstract: 
 Enterprises must become ‘sensing, smart and sustainable (S3)’ to face global challenges related to local, national and global market dynamics. Therefore, reconceptualisation and redesign in these enterprises must accommodate emergent technologies, new practices and strategies. In this sense, enterprises have used new product development as a strategy for remaining competitive in the marketplace; thus, they can provide a new generation of products offering solutions to contemporary social problems and responding to changing consumer demands. These new-generation products are mostly technology-based and consider sustainable objectives. In this context, concepts such as sensing, smart and sustainable products (S3 products) have emerged to satisfy different social requirements. Therefore, this work focuses on providing a reference framework that presents a systematic process for the development of S3 products. This reference framework is based on the integrated product, process and manufacturing system development reference model. The main objective of this work is to fill the gap vis-à-vis the current lack of design roadmaps that permit the development of this new generation of products in S3 enterprises. The development of a reconfigurable micro-machine tool is presented as that of an S3 product.
Journal: International Journal of Production Research
Pages: 4391-4412
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2017.1401237
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401237
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Template-Type: ReDIF-Article 1.0
Author-Name: Ran Etgar
Author-X-Name-First: Ran
Author-X-Name-Last: Etgar
Author-Name: Roy Gelbard
Author-X-Name-First: Roy
Author-X-Name-Last: Gelbard
Author-Name: Yuval Cohen
Author-X-Name-First: Yuval
Author-X-Name-Last: Cohen
Title: Presenting the several-release-problem and its cluster-based solution accelartion
Abstract: 
 This paper presents a novel technique for improving the runtime of metaheuristic search optimisations. The technique was applied on a new practical problem: several-release-problem (SRP) that characterises the modern industry. Many modern products are replaced by their next version due to incessant R&D activity, resulting in a short marketable life length. There are numerous such examples including the automotive industry, electronic devices and software products. These intermediate releases enable organisations to maximise their value for a given investment. The challenge faced by the industry is to decide which features to include in which version. The paper proves that SRP is NP-hard, thus cannot be solved practically using analytical approaches. A near-optimal, simple technique for determining the feature content of all version releases of the planning horizon is presented. The innovative approach utilises techniques adopted from the clustering domain to enhance the optimisation. The clustering enables skipping significant amounts of unattractive zones of the space. Verification and validation of the proposed technique are presented. The paper compares different heuristics and the shows that embedding the suggested clustering into general methods, yields significantly shorter runtime, and improves the solution’s quality. The enhancement technique can be applied to other combinatorial problems and metaheuristics.
Journal: International Journal of Production Research
Pages: 4413-4434
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2017.1404657
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1404657
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Template-Type: ReDIF-Article 1.0
Author-Name: Lars Hvam
Author-X-Name-First: Lars
Author-X-Name-Last: Hvam
Author-Name: Katrin Kristjansdottir
Author-X-Name-First: Katrin
Author-X-Name-Last: Kristjansdottir
Author-Name: Sara Shafiee
Author-X-Name-First: Sara
Author-X-Name-Last: Shafiee
Author-Name: Niels Henrik Mortensen
Author-X-Name-First: Niels Henrik
Author-X-Name-Last: Mortensen
Author-Name: Zaza Nadja Lee Herbert-Hansen
Author-X-Name-First: Zaza Nadja Lee
Author-X-Name-Last: Herbert-Hansen
Title: The impact of applying product-modelling techniques in configurator projects
Abstract: 
 This paper aims to increase understanding of the impact of using product-modelling techniques to structure and formalise knowledge in configurator projects. Companies that provide customised products increasingly apply configurators in support of sales and design activities, reaping benefits that include shorter lead times, improved quality of specifications and products, and lower overall product costs. The design and implementation of configurators are a challenging task that calls for scientifically based modelling techniques to support the formal representation of configurator knowledge. Even though extant literature has shown the importance of formal modelling techniques, the impact of utilising these techniques remains relatively unknown. Therefore, this article studies three main areas: (1) the impact of using modelling techniques based on Unified Modelling Language (UML), in which the phenomenon model and information model are considered visually, (2) non-UML-based modelling techniques, in which only the phenomenon model is considered and (3) non-formal modelling techniques. This study analyses the impact to companies from increased availability of product knowledge and improved control of product variants. The methodology employed is an exploratory survey, followed by interviews with 18 manufacturing companies providing customised products. The results indicate that companies using UML-based modelling techniques tend to have improved documentation of their product knowledge and an improved ability to reduce the number of product variants. This paper contributes to an increased understanding of what companies can gain from using more formalised modelling techniques in configurator projects, and under what circumstances they should be used.
Journal: International Journal of Production Research
Pages: 4435-4450
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1436783
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1436783
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaona Luan
Author-X-Name-First: Xiaona
Author-X-Name-Last: Luan
Author-Name: Song Zhang
Author-X-Name-First: Song
Author-X-Name-Last: Zhang
Author-Name: Jie Chen
Author-X-Name-First: Jie
Author-X-Name-Last: Chen
Author-Name: Gang Li
Author-X-Name-First: Gang
Author-X-Name-Last: Li
Title: Energy modelling and energy saving strategy analysis of a machine tool during non-cutting status
Abstract: 
 Increasing energy cost and environmental problems push forward research on energy modelling and saving strategy in the sustainable manufacturing field. A manufacturing process usually includes cutting process and non-cutting status. Energy consumption of non-cutting status accounts for a large amount of the total energy consumption during a machining process. This paper focuses on the energy modelling and saving potential analysis in non-cutting status. First, power of non-cutting status was modelled, which included the fixed power, spindle idle power, feed motion power and rapid feed power. Secondly, milling experiments were conducted to study the characteristic and modelling method of the non-cutting status power. The experiments were divided into two types, some experiments were used to calculate the coefficients, and the others were applied to verify the proposed model. Finally, regression analysis and Analysis of Variance (ANOVA) were applied to illustrate the prediction accuracy of the proposed model. The energy saving strategy was developed for the non-cutting status, which includes shortening the air cutting time and not frequently changing the spindle speed to avoid a power peak. It indicates that the proposed model can predict the power consumption of non-cutting status accurately.
Journal: International Journal of Production Research
Pages: 4451-4467
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1436787
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1436787
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Template-Type: ReDIF-Article 1.0
Author-Name: Yaqi Lou
Author-X-Name-First: Yaqi
Author-X-Name-Last: Lou
Author-Name: Zhen He
Author-X-Name-First: Zhen
Author-X-Name-Last: He
Author-Name: Yanrong Li
Author-X-Name-First: Yanrong
Author-X-Name-Last: Li
Author-Name: Shuguang He
Author-X-Name-First: Shuguang
Author-X-Name-Last: He
Title: Should short warranty always be interpreted as low quality: the effect of brand advantages on warranty’s signalization
Abstract: 
 Brand and warranty information have been always been accepted as signals of unknown product quality. Given this, offering an attractive warranty is suggested as an effective competitive strategy. However, manufacturers with strong brand tend to provide the minimal industry standard warranty period in reality. This paper considers two competing manufacturers with different brand reputations selling their products through common retailer. The demand of products depends on price, brand and warranty period. A model for this problem is proposed when the manufacturers decide the warranty periods and the wholesale prices meanwhile the retailer decides the retail prices. We find that brand reputations influence all the optimal decisions of each party. We show that under certain condition, the strong brand manufacturer realises his profit maximisation by providing a shorter warranty compared to the weaker brand manufacturer. To a certain extent, this brand advantage modifies signalisation of manufacturers’ warranty. Several numerical examples and managerial insights are presented and used to illustrate the model presented in this paper.
Journal: International Journal of Production Research
Pages: 4468-4479
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1436791
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1436791
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Template-Type: ReDIF-Article 1.0
Author-Name: Iwona Paprocka
Author-X-Name-First: Iwona
Author-X-Name-Last: Paprocka
Title: The model of maintenance planning and production scheduling for maximising robustness
Abstract: 
 The accuracy of prediction and detection capability have a strong influence over the efficiency of the bottleneck, all equipment and the production system. The function of predictive scheduling is to obtain stable and robust schedules for a shop floor. The first objective is to present an innovative maintenance planning and production scheduling method. The approach consists of four modules: a database to collect information about failure-free times, a prediction module of failure-free times, predictive scheduling and rescheduling module, a module for evaluating the accuracy of prediction and maintenance performance. The second objective is to apply the proposed methods for a job shop scheduling problem. Usually, researchers who are concerned about maintenance scheduling do not take unexpected disturbances into account. They assume that machines are always available for processing tasks during the future-planned production time. Moreover, researches use the criteria that are not effective to deal with the situation of unpredicted failures. In this paper, a method based on probability theory is proposed for maintenance scheduling. For unpredicted failures, a rescheduling method is also proposed. The evaluation module which gives information about the degradation of each performance measure and the stability of a schedule is proposed.
Journal: International Journal of Production Research
Pages: 4480-4501
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1492752
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1492752
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Template-Type: ReDIF-Article 1.0
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Title: Two-period vs. multi-period model for supply chain disruption management
Abstract: 
 A novel two-period modelling approach is developed for supply chain disruption mitigation and recovery and compared with a multi-period approach. For the two-period model, planning horizon is divided into two aggregate periods: before disruption and after disruption. The corresponding mitigation and recovery decisions are: (1) primary supply and demand portfolios and production before a disruption, and (2) recovery supply, transshipment and demand portfolios and production after the disruption. In the multi-period model, a multi-period planning horizon is applied to account for a detailed timing of supplies and production. The primary and recovery portfolios are determined simultaneously and for both approaches the integrated decision-making, stochastic mixed integer programming models are developed. While the simplified two-period setting may overestimate (for best-case capacity constraints) or underestimate (for worst-case capacity constraints) the available production capacity, it can be easily applied in practice for a fast, rough-cut evaluation of disruption mitigation and recovery policy. The findings indicate that for both two- and multi-period setting, the developed multi-portfolio approach leads to computationally efficient mixed integer programming models with an embedded network flow structure resulting in a very strong linear programming relaxation.
Journal: International Journal of Production Research
Pages: 4502-4518
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1504246
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504246
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Template-Type: ReDIF-Article 1.0
Author-Name: Sourabh Kulkarni
Author-X-Name-First: Sourabh
Author-X-Name-Last: Kulkarni
Author-Name: Priyanka Verma
Author-X-Name-First: Priyanka
Author-X-Name-Last: Verma
Author-Name: R. Mukundan
Author-X-Name-First: R.
Author-X-Name-Last: Mukundan
Title: Assessing manufacturing strategy definitions utilising text-mining
Abstract: 
 The variations in Manufacturing Strategy (MS) definitions create confusion and lead to lack of shared understanding between academic researchers and practitioners on its scope. The purpose of this study is to provide an empirical analysis of the paradox in the difference between academic and industry definitions of MS. Natural Language Processing (NLP) based text mining is used to extract primary elements from the various academic, and industry definitions of MS. Co-word and Principal Component Analysis (PCA) provide empirical support for the grouping into nine primary elements. We posit from the terms evolution analysis that there is a stasis currently faced in academic literature towards MS definition while the industry with its emphasis on ‘context’ has been dynamic. We believe that the proposed approach and results of the present empirical analysis can contribute to overcoming the current challenges to MS design and deployment – imprecise definition leading to its inadequate operationalisation.
Journal: International Journal of Production Research
Pages: 4519-4546
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1512764
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1512764
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Template-Type: ReDIF-Article 1.0
Author-Name: Amir Hossein Nobil
Author-X-Name-First: Amir Hossein
Author-X-Name-Last: Nobil
Author-Name: Sunil Tiwari
Author-X-Name-First: Sunil
Author-X-Name-Last: Tiwari
Author-Name: Fatemeh Tajik
Author-X-Name-First: Fatemeh
Author-X-Name-Last: Tajik
Title: Economic production quantity model considering warm-up period in a cleaner production environment
Abstract: 
 Currently, the primary objective of every manufacturing organization is in customers’ satisfaction and system cost reduction while keeping in mind both production quantity (economic issues) and environmental issues (sustainability). This study investigates the effects of machine warm-up period on an imperfect production process with rework. In this case, the maintenance process is intended to maximize the efficiency and effectiveness of the production machine. In this manufacturing system, it assumed that after the setup time, the machine starts at the lower rate than the regular production process, commonly called as warm-up period. The warm-up period will increase the useful life of the machine. On the other hand, the machine's defects that occur during this warm-up period are identified and repaired before the regular production starts. Also, this warm-up period reduces waste as it improves machine performance; resulting in the decrease of scrapped items that makes the process friendly for the environment. The purpose of this proposed model is to determine the optimum value of production quantity to minimize the total costs by considering the warm-up period and set-up time. Finally, numerical experiments have been conducted to validate the efficacy of the model as well as to obtain some managerial insights.
Journal: International Journal of Production Research
Pages: 4547-4560
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1518608
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518608
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Template-Type: ReDIF-Article 1.0
Author-Name: Fei Lv
Author-X-Name-First: Fei
Author-X-Name-Last: Lv
Title: Should competing original equipment manufacturers outsource procurement activities under asymmetric cost information?
Abstract: 
 This paper considers a supply chain in which two competing heterogeneous original equipment manufacturers (OEMs) outsource production to a common contract manufacturer (CM) that possesses private cost information. Along with production outsourcing, the OEMs can either purchase components by themselves and only assign the production tasks to the CM (Consignment), or delegate both the procurement and production tasks to the CM (Turnkey). The main question we address is whether the OEMs should adopt Consignment or Turnkey. To answer this question, we first analyse the OEMs’ optimal mechanism design problems under three scenarios: both OEMs adopt Consignment strategy; both OEMs adopt Turnkey strategy; one OEM adopts Consignment and the other one adopts Turnkey. Building upon the OEMs’ equilibrium decisions under each scenario, we then characterise the equilibrium outcome for the procurement game. The results show that the CM’s procurement cost distribution and the market size play critical roles in the equilibrium outcome. Additionally, we find that both the competition intensity and cost heterogeneity between the OEMs affect the equilibrium outcome.
Journal: International Journal of Production Research
Pages: 4561-4578
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1521023
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521023
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Template-Type: ReDIF-Article 1.0
Author-Name: Chu A. My
Author-X-Name-First: Chu A.
Author-X-Name-Last: My
Author-Name: Chi Hieu Le
Author-X-Name-First: Chi Hieu
Author-X-Name-Last: Le
Author-Name: Michael Packianather
Author-X-Name-First: Michael
Author-X-Name-Last: Packianather
Author-Name: Erik L.J. Bohez
Author-X-Name-First: Erik L.J.
Author-X-Name-Last: Bohez
Title: Novel robot arm design and implementation for hot forging press automation
Abstract: 
 Manual handling of hot and heavy workpiece in forging press industry increases the process time and causes safety risks to workers. To increase the productivity and optimise the use of manpower, manipulators are needed to be designed for supporting the workers handling the workpiece. Designing robots for such applications is challenging since the robot suffers from a heavy payload at the arm tip, and it operates at a high speed in a large workspace. This research addresses the design and implementation of a novel robot for handling workpiece for a given forging press cell. A novel robotic mechanism is designed with two key features: (i) the addition of parallel links in between serial links and (ii) the use of hydraulic actuators for driving robot’s joints. The addition of parallel links and the use of hydraulic cylinders are to increase the structural rigidity. It is also to reduce the number of joint variables and restrict the end-effector moving parallel to the ground surface so that the robot grips and releases the workpiece in a more efficient and simplified manner. The effectiveness of the designed robot mechanism is demonstrated through functional tests, and experimental results are carried out on the implemented robot.
Journal: International Journal of Production Research
Pages: 4579-4593
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1521026
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521026
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Template-Type: ReDIF-Article 1.0
Author-Name: Xinsheng Xu
Author-X-Name-First: Xinsheng
Author-X-Name-Last: Xu
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: Chi Kin Chan
Author-X-Name-First: Chi Kin
Author-X-Name-Last: Chan
Title: Optimal option purchase decision of a loss-averse retailer under emergent replenishment
Abstract: 
 This paper studies the optimal option purchase of a loss-averse retailer under emergent replenishment. It is assumed that all or part of the excess demands in a stock-out situation can be replenished, and the loss-averse retailer's optimal option purchase quantity is investigated. It is found that the loss-averse retailer should not purchase options and only needs to replenish the inventory under certain conditions. When maximizing the expected utility without shortage cost, the loss-averse retailer's optimal option purchase quantity is decreasing in the loss aversion coefficient. To maximise the expected utility with shortage cost, a larger shortage cost implies a bigger option purchase quantity. If the shortage cost exists, there will be a loss on the expected profit and utility for the loss-averse retailer who selects an optimal option purchase quantity without shortage cost. Given the optimal option purchase quantity, it is proven that the loss-averse retailer's expected profit is decreasing in the loss aversion coefficient. Therefore the retailer should choose a proper loss aversion preference to balance between the two objectives of profit maximization and loss aversion preference. As a result of these findings, some management insights are recommended to the loss-averse retailer in selecting the option purchase quantity.
Journal: International Journal of Production Research
Pages: 4594-4620
Issue: 14
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2019.1579935
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1579935
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Template-Type: ReDIF-Article 1.0
Author-Name: Jonas Hauke
Author-X-Name-First: Jonas
Author-X-Name-Last: Hauke
Author-Name: Iris Lorscheid
Author-X-Name-First: Iris
Author-X-Name-Last: Lorscheid
Author-Name: Matthias Meyer
Author-X-Name-First: Matthias
Author-X-Name-Last: Meyer
Title: Individuals and their interactions in demand planning processes: an agent-based, computational testbed
Abstract: 
 The demand planning process in semiconductor supply chains faces many challenges. In this process, individuals, their properties such as sensing capabilities and their interactions play a crucial role. This paper shows how agent-based modelling (ABM) can provide a computational testbed to investigate these aspects with respect to forecast accuracy. Based on the requirements of the demand planning context, we develop an empirically validated agent-based model of the demand planning process. In this model, we incorporate different concepts from behavioural science and the distributed cognition perspective. We show the usefulness of this agent-based computational testbed by using a case study from the semiconductor industry. Our model shows that demand planning accuracy does not depend on the planning capabilities of planners alone, but that the interactions of the individuals, emerging from the planning process design, may both positively and negatively affect accuracy.
Journal: International Journal of Production Research
Pages: 4644-4658
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1377356
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1377356
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Template-Type: ReDIF-Article 1.0
Author-Name: Stefan Woerner
Author-X-Name-First: Stefan
Author-X-Name-Last: Woerner
Author-Name: Marco Laumanns
Author-X-Name-First: Marco
Author-X-Name-Last: Laumanns
Author-Name: Stephan M. Wagner
Author-X-Name-First: Stephan M.
Author-X-Name-Last: Wagner
Title: Joint optimisation of capacity and safety stock allocation
Abstract: 
 We study the joint optimisation of capacity and safety stock allocation in assembly systems. Particularly, we consider capacitated systems with base-stock policies and periodic review. Capacity allocation is restricted by budget constraints, which can connect multiple systems. Our objective is to minimise overall inventory holding costs while satisfying service level as well as budget constraints. We propose an algorithm to jointly approximate optimal capacity allocation and base-stock levels. To this end, we introduce a set of convex approximations for this non-convex optimisation problem. In order to solve the resulting convex programmes, we analytically compute sample path derivatives via infinitesimal perturbation analysis. By iteratively adapting the approximations, we achieve good capacity allocations and base-stock levels for the original problem. Furthermore, we introduce a heuristic to allocate capacity, which originates from link capacity allocation in communication networks and use it as a benchmark. The algorithm is applied to small illustrative examples as well as cases motivated by the semiconductor manufacturing process at IBM Systems. It turns out that particularly for high utilisation levels, our algorithm can achieve significant improvements compared to the capacity allocation heuristic.
Journal: International Journal of Production Research
Pages: 4612-4628
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1380323
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1380323
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Template-Type: ReDIF-Article 1.0
Author-Name: Junyi Lin
Author-X-Name-First: Junyi
Author-X-Name-Last: Lin
Author-Name: Virginia L.M. Spiegler
Author-X-Name-First: Virginia L.M.
Author-X-Name-Last: Spiegler
Author-Name: M.M. Naim
Author-X-Name-First: M.M.
Author-X-Name-Last: Naim
Title: Dynamic analysis and design of a semiconductor supply chain: a control engineering approach
Abstract: 
 The combined make-to-stock and make-to-order (MTS-MTO) supply chain is well-recognised in the semiconductor industry in order to find a competitive balance between agility, including customer responsiveness and minimum reasonable inventory, to achieve cost efficiency while maintaining customer service levels. Such a hybrid MTS-MTO supply chain may suffer from the bullwhip effect, but few researchers have attempted to understand the dynamic properties of such a hybrid system. We utilise a model of the Intel supply chain to analytically explore the underlying mechanisms of bullwhip generation and compare its dynamic performance to the well-known Inventory and Order-Based Production Control System (IOBPCS) archetype. Adopting a control engineering approach, we find that the feedforward forecasting compensation in the MTO element plays a major role in the degree of bullwhip and the Customer Order Decoupling Point (CODP) profoundly impacts both the bullwhip effect and the inventory variance in the MTS part. Thus, managers should carefully tune the CODP inventory correction and balance the benefit between CODP inventory and bullwhip costs in hybrid MTS-MTO supply chains.
Journal: International Journal of Production Research
Pages: 4585-4611
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1396507
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1396507
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Template-Type: ReDIF-Article 1.0
Author-Name: Konstantina Spanaki
Author-X-Name-First: Konstantina
Author-X-Name-Last: Spanaki
Author-Name: Zeynep Gürgüç
Author-X-Name-First: Zeynep
Author-X-Name-Last: Gürgüç
Author-Name: Richard Adams
Author-X-Name-First: Richard
Author-X-Name-Last: Adams
Author-Name: Catherine Mulligan
Author-X-Name-First: Catherine
Author-X-Name-Last: Mulligan
Title: Data supply chain (DSC): research synthesis and future directions
Abstract: 
 In the digital economy, the volume, variety and availability of data produced in myriad forms from a diversity of sources has become an important resource for competitive advantage, innovation opportunity as well as source of new management challenges. Building on the theoretical and empirical foundations of the traditional manufacturing Supply Chain (SC), which describes the flow of physical artefacts as raw materials through to consumption, we propose the Data Supply Chain (DSC) along which data are the primary artefact flowing. The purpose of this paper is to outline the characteristics and bring conceptual distinctiveness to the context around DSC as well as to explore the associated and emergent management challenges and innovation opportunities. To achieve this, we adopt the systematic review methodology drawing on the operations management and supply chain literature and, in particular, taking a framework synthetic approach which allows us to build the DSC concept from the pre-existing SC template. We conclude the paper by developing a set of propositions and outlining an agenda for future research that the DSC concept implies.
Journal: International Journal of Production Research
Pages: 4447-4466
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1399222
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1399222
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Template-Type: ReDIF-Article 1.0
Author-Name: Lars Mönch
Author-X-Name-First: Lars
Author-X-Name-Last: Mönch
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Author-Name: John W. Fowler
Author-X-Name-First: John W.
Author-X-Name-Last: Fowler
Title: A survey of semiconductor supply chain models part I: semiconductor supply chains, strategic network design, and supply chain simulation
Abstract: 
 Supply chain management issues have become increasingly important to the semiconductor industry over the last two decades due to the global distribution of facilities and increasing numbers of firms specialising in particular stages. This series of three papers reviews the literature on modelling and analysis of the larger semiconductor supply chain. After describing the structure of semiconductor supply chains to provide context for the research efforts, we propose a classification scheme for the relevant literature. The remainder of this paper (Part I) then focuses on Strategic Network Design models for this industry, supply chain coordination through contracting and semiconductor supply chain simulation. Part II discusses Demand Planning, Inventory Management and Capacity Planning, while Part III addresses Master Planning, Production Planning and Demand Fulfilment.
Journal: International Journal of Production Research
Pages: 4524-4545
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1401233
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401233
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Template-Type: ReDIF-Article 1.0
Author-Name: Lars Mönch
Author-X-Name-First: Lars
Author-X-Name-Last: Mönch
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Author-Name: John W. Fowler
Author-X-Name-First: John W.
Author-X-Name-Last: Fowler
Title: A survey of semiconductor supply chain models part III: master planning, production planning, and demand fulfilment
Abstract: 
 Part I of this three-part series described semiconductor supply chains from the decision-making and functional perspectives, using this as a framework to review the industrial engineering (IE) and operations research (OR) literature on the problems arising in these supply chains. Part I then reviewed the literature on Strategic Network Design, Supply Chain Coordination, Sustainability and Semiconductor Supply Chain Simulation, while Part II reviewed Demand Planning, Inventory Management, and Capacity Planning. This paper concludes the series, discussing Master Planning, Production Planning, Demand Fulfilment, and Available to Promise (ATP) in semiconductor supply chains.
Journal: International Journal of Production Research
Pages: 4565-4584
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1401234
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401234
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Template-Type: ReDIF-Article 1.0
Author-Name: Gema Calleja
Author-X-Name-First: Gema
Author-X-Name-Last: Calleja
Author-Name: Albert Corominas
Author-X-Name-First: Albert
Author-X-Name-Last: Corominas
Author-Name: Carme Martínez-Costa
Author-X-Name-First: Carme
Author-X-Name-Last: Martínez-Costa
Author-Name: Rocío de la Torre
Author-X-Name-First: Rocío
Author-X-Name-Last: de la Torre
Title: Methodological approaches to supply chain design
Abstract: 
 This paper reviews methodological approaches to the design (or redesign) of the supply chain (SC), including comprehensive approaches (proposals concerning the entire process of designing the SC) and those that deal with four specific aspects of the process (definition of the SC objectives, reverse SC, finance, and generation and use of scenarios) that have a decisive influence on the whole design of the SC. The comprehensive approaches include those based on typologies of products, markets and SCs and those that propose a succession of the stages to follow through the design process. The discussion shows that the use of typologies is not adequate to face SC design and that the methods proposing a succession of stages may suit, provided that they are developed and presented in a manner appropriate to their use for practitioners. The discussion leads also to suggest several research lines.
Journal: International Journal of Production Research
Pages: 4467-4489
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1412526
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412526
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Template-Type: ReDIF-Article 1.0
Author-Name: Sanjoy Kumar Paul
Author-X-Name-First: Sanjoy Kumar
Author-X-Name-Last: Paul
Author-Name: Shams Rahman
Author-X-Name-First: Shams
Author-X-Name-Last: Rahman
Title: A quantitative and simulation model for managing sudden supply delay with fuzzy demand and safety stock
Abstract: 
 In this paper, a recovery model is developed for managing sudden supply delays that affect retailers’ economic order quantity model. For this, a mathematical model is developed that considers fuzzy demand and safety stock, and generates a recovery plan for a finite future period immediately after a sudden supply delay. An efficient heuristic solution is developed that generates the recovery plan after a sudden supply delay. An experiment with scenario-based analysis is conducted to test our heuristic and to analyse the results. To assess the quality and consistency of solutions, the performance of the proposed heuristic is compared with the performance of the generalised reduced gradient method, which is widely applied in constrained mathematical programming. A simulation model is also designed to bring the recovery model closer to real-world processes. Several numerical examples are presented and a sensitivity analysis is performed to demonstrate the effects of various parameters on the performance of the heuristic method. The results show that safety stock plays an important role in recovery from sudden supply delays, and there is a trade-off between backorder and lost sales costs in the recovery plan. With the help of the proposed model, supply chain decision-makers can make accurate and prompt decision regarding recovery plans in case of sudden supply delay.
Journal: International Journal of Production Research
Pages: 4377-4395
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1412528
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412528
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Template-Type: ReDIF-Article 1.0
Author-Name: Ying-Jen Chen
Author-X-Name-First: Ying-Jen
Author-X-Name-Last: Chen
Author-Name: Chen-Fu Chien
Author-X-Name-First: Chen-Fu
Author-X-Name-Last: Chien
Title: An empirical study of demand forecasting of non-volatile memory for smart production of semiconductor manufacturing
Abstract: 
 As high-speed computing is crucial to empower intelligent manufacturing for Industry 4.0, non-volatile memory (NVM) is critical semiconductor component of the cloud and data centre for the infrastructures. The NVM manufacturing is capital intensive, in which capacity utilisation significantly affects the capital effectiveness and profitability of semiconductor companies. Since capacity migration and expansion involve long lead times, demand forecasting plays a critical role for smart production of NVM manufacturers for revenue management. However, the shortening product life cycles of integrated circuits (IC), the fluctuations of semiconductor supply chains, and uncertainty involved in demand forecasting make the present problem increasingly difficult in the consumer electronics era. Focusing on the realistic needs of NVM demand forecasting, this study aims to develop a decision framework that integrates an improved technology diffusion model and a proposed adjustment mechanism to incorporate domain insights. An empirical study was conducted in a leading semiconductor company for validation. A comparison of alternative approaches is also provided. The results have shown the practical viability of the proposed approach.
Journal: International Journal of Production Research
Pages: 4629-4643
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1421783
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421783
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:13:p:4629-4643




Template-Type: ReDIF-Article 1.0
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Author-Name: John W. Fowler
Author-X-Name-First: John W.
Author-X-Name-Last: Fowler
Author-Name: Lars Mönch
Author-X-Name-First: Lars
Author-X-Name-Last: Mönch
Title: A survey of semiconductor supply chain models Part II: demand planning, inventory management, and capacity planning
Abstract: 
 Part I of this three-part series described semiconductor supply chains from the decision-making and functional perspectives, using this as a framework to review the industrial engineering and operations research literature on the problems arising in these supply chains. Part I then reviewed the literature on Strategic Network Design, supply chain coordination, sustainability and simulation-based decision support. This paper, Part II, reviews the areas of Demand Planning, Inventory Management and Capacity Planning in semiconductor supply chains. Part III concludes the series by discussing models to support Master Planning, Production Planning and Demand Fulfilment in this industry.
Journal: International Journal of Production Research
Pages: 4546-4564
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1424363
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424363
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:13:p:4546-4564




Template-Type: ReDIF-Article 1.0
Author-Name: Ratapol Wudhikarn
Author-X-Name-First: Ratapol
Author-X-Name-Last: Wudhikarn
Author-Name: Nopasit Chakpitak
Author-X-Name-First: Nopasit
Author-X-Name-Last: Chakpitak
Author-Name: Gilles Neubert
Author-X-Name-First: Gilles
Author-X-Name-Last: Neubert
Title: A literature review on performance measures of logistics management: an intellectual capital perspective
Abstract: 
 Today, logistics management requires a comprehensive set of performance indicators that measure both tangible assets and intellectual capital (IC) of organisations. Nevertheless, most of the measures used in the past mainly related to the financial aspect, although some specific components of IC, such as process efficiency and effectiveness, have been considered. Logistics literature lacks a comprehensive consideration of the diverse IC measures, and it is unclear which area of IC requires more focus and development. Therefore, to explore and identify an opportunity for improvement, this study reviews the academic literature related to IC measures in logistics management. This literature review considers 111 academic articles published between 1994 and 2016. Following the six dimensions of the IC-Index, all indicators obtained from the literature are classified according to IC elements. The key contribution of this review is that it addresses the following gaps in the literature: the limited adoption of comprehensive IC methods in logistics studies; underdevelopment of specific indicators and measures used; failure to consider all human capital as well as renewal and development elements; and, finally, lack of academic research considering the influences among the different IC elements and logistics and financial performance.
Journal: International Journal of Production Research
Pages: 4490-4520
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1431414
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1431414
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:13:p:4490-4520




Template-Type: ReDIF-Article 1.0
Author-Name: Stella Despoudi
Author-X-Name-First: Stella
Author-X-Name-Last: Despoudi
Author-Name: Grammatoula Papaioannou
Author-X-Name-First: Grammatoula
Author-X-Name-Last: Papaioannou
Author-Name: George Saridakis
Author-X-Name-First: George
Author-X-Name-Last: Saridakis
Author-Name: Samir Dani
Author-X-Name-First: Samir
Author-X-Name-Last: Dani
Title: Does collaboration pay in agricultural supply chain? An empirical approach
Abstract: 
 This paper examines the effect of different types of collaboration on the level of Postharvest Food Losses (PHFL) and the proportion of low-quality peaches produced using a unique data-set of Greek peach producers. Quantile regression techniques are adopted to estimate the effects at different points of the conditional distribution of our variables of interest. The findings of this study suggest that high levels of collaboration between producers and cooperatives are associated with both low levels of PHFL and a low proportion of low-quality peaches. We also find that specific types of collaboration, such as ‘goal congruence’, can play a significant role in reducing PHFL and improving the quality of peach production at the extremes of the distribution. Important policy implications regarding collaborative practices and systems that can be implemented to reduce PHFL and boost a producer’s performance together with sustainability credentials are drawn from this study.
Journal: International Journal of Production Research
Pages: 4396-4417
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1440654
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1440654
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:13:p:4396-4417




Template-Type: ReDIF-Article 1.0
Author-Name: Mahesh Gupta
Author-X-Name-First: Mahesh
Author-X-Name-Last: Gupta
Author-Name: Soeren Andersen
Author-X-Name-First: Soeren
Author-X-Name-Last: Andersen
Title: Throughput/inventory dollar-days: TOC-based measures for supply chain collaboration
Abstract: 
 As the semiconductor industry moves away from vertical integration, performance measures play an increasingly important role to ensure effective collaboration. This paper demonstrates that the theory of constraints (TOC)-based measures, Throughput and Inventory Dollar-Days (T/IDD), induce autonomous supply chain (SC) links to function as a synergistic whole and thereby, improve the performance of the whole SC network significantly. We model an SC network of a well-known TOC case study using discrete event simulation and discuss managerial implications of these measures via a set of scenarios. The scenarios explain how these measures – without sharing sensitive financial data – allow members of an SC network to monitor both the effectiveness (TDD) and efficiency (IDD) of SC members and lead them to create win-win solutions following well-known TOC-based planning and control concepts. We conclude this paper by discussing some limitations of the proposed research and provide directions for future theoretical research.
Journal: International Journal of Production Research
Pages: 4659-4675
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1444805
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1444805
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:13:p:4659-4675




Template-Type: ReDIF-Article 1.0
Author-Name: Ana Esteso
Author-X-Name-First: Ana
Author-X-Name-Last: Esteso
Author-Name: M.M.E. Alemany
Author-X-Name-First: M.M.E.
Author-X-Name-Last: Alemany
Author-Name: Angel Ortiz
Author-X-Name-First: Angel
Author-X-Name-Last: Ortiz
Title: Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models
Abstract: 
 Agri-food sector performance strongly impacts global economy, which means that developing optimisation models to support the decision-making process in agri-food supply chains (AFSC) is necessary. These models should contemplate AFSC’s inherent characteristics and sources of uncertainty to provide applicable and accurate solutions. To the best of our knowledge, there are no conceptual frameworks available to design AFSC through mathematical programming modelling while considering their inherent characteristics and sources of uncertainty, nor any there literature reviews that address such characteristics and uncertainty sources in existing AFSC design models. This paper aims to fill these gaps in the literature by proposing such a conceptual framework and state of the art. The framework can be used as a guide tool for both developing and analysing models based on mathematical programming to design AFSC. The implementation of the framework into the state of the art validates its. Finally, some literature gaps and future research lines were identified.
Journal: International Journal of Production Research
Pages: 4418-4446
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1447706
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1447706
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:13:p:4418-4446




Template-Type: ReDIF-Article 1.0
Author-Name: Lars Mönch
Author-X-Name-First: Lars
Author-X-Name-Last: Mönch
Author-Name: Chen-Fu Chien
Author-X-Name-First: Chen-Fu
Author-X-Name-Last: Chien
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Hans Ehm
Author-X-Name-First: Hans
Author-X-Name-Last: Ehm
Author-Name: John W. Fowler
Author-X-Name-First: John W.
Author-X-Name-Last: Fowler
Title: Modelling and analysis of semiconductor supply chains
Journal: International Journal of Production Research
Pages: 4521-4523
Issue: 13
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1464680
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1464680
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:13:p:4521-4523




Template-Type: ReDIF-Article 1.0
Author-Name: Christian König
Author-X-Name-First: Christian
Author-X-Name-Last: König
Author-Name: Nigel D. Caldwell
Author-X-Name-First: Nigel D.
Author-X-Name-Last: Caldwell
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Title: Service provider boundaries in competitive markets: the case of the logistics industry
Abstract: 
 This study empirically investigates service provider firms’ attempts to move to higher value-added market segments in competitive and fragmented markets, using logistics services as a context. Novelty is added by taking the provider not the customer or outsourcing actor perspective, common to current third-party logistics perspectives. Data were collected in the form of semi-structured interviews with management at various provider firms. The interview guide was based on theoretical constructs regarding tangible and intangible capabilities (RBV) as well as constructs related to governance and integration (TCE). Unlike customer focused studies, this study is able to identify what distinguishes the rare successful boundary crossing attempts that lead to a more profitable market position. The key finding which contradicts studies based on the customer/outsourcing actor perspective is that a switch from a highly commoditised market position to a higher margin position is only possible, if relationships and network capabilities are leveraged, regardless of the assets and physical resources available to the firm. The presentation of service boundaries as both dynamic and fluid and the use of RBV are contributions, building on existing theory, illustrating why providers of commoditised services cannot escape from low-margin, competitive market positions simply by acquiring tangible assets.
Journal: International Journal of Production Research
Pages: 5624-5639
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1535203
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1535203
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Template-Type: ReDIF-Article 1.0
Author-Name: Audrey Cerqueus
Author-X-Name-First: Audrey
Author-X-Name-Last: Cerqueus
Author-Name: Xavier Delorme
Author-X-Name-First: Xavier
Author-X-Name-Last: Delorme
Title: A branch-and-bound method for the bi-objective simple line assembly balancing problem
Abstract: 
 The design of a production system is a strategic level decision. One of the key problems to solve is the line balancing problem that determines the efficiency of a production or assembly line. This class of problem has been widely studied in the literature. It determines important features, such as the number of stations, the takt time or the working conditions. Most of the variants of this problem consider only one objective function, but nowadays companies have to take into account different criteria. In this study, we consider a bi-objective variant of the simple assembly line balancing problem. We present a generic branch-and-bound method to solve exactly this problem. The objective functions are to minimise the takt time and the number of stations. To do so, bounds and bound sets are developed. The resulting method is numerically tested and compared to an ϵ-constraint method. These experiments show that the bi-objective branch-and-bound algorithm outperforms an ϵ-constraint method using a state-of-the-art single objective algorithm for more than 80% of the instances. Finally, we propose an analysis of the cases where the branch-and-bound method is outperformed.
Journal: International Journal of Production Research
Pages: 5640-5659
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1539266
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1539266
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:18:p:5640-5659




Template-Type: ReDIF-Article 1.0
Author-Name: Xinjun Lai
Author-X-Name-First: Xinjun
Author-X-Name-Last: Lai
Author-Name: Qixiang Zhang
Author-X-Name-First: Qixiang
Author-X-Name-Last: Zhang
Author-Name: Qingxin Chen
Author-X-Name-First: Qingxin
Author-X-Name-Last: Chen
Author-Name: Yunbao Huang
Author-X-Name-First: Yunbao
Author-X-Name-Last: Huang
Author-Name: Ning Mao
Author-X-Name-First: Ning
Author-X-Name-Last: Mao
Author-Name: Jianjun Liu
Author-X-Name-First: Jianjun
Author-X-Name-Last: Liu
Title: The analytics of product-design requirements using dynamic internet data: application to Chinese smartphone market
Abstract: 
 To accommodate the diverse users demands for consumer products, enterprises need to design and develop different lines of products according to different groups of users. Dynamic internet data, including product reviews, user attributes, and product configurations, are utilised to model users' stochastic product choice behaviours and mine the product design requirements of features, performance levels, and quantity. First, the web crawler is applied to collect internet data, and then the data are structured and the demand information is retrieved. Second, a product choice model is employed to capture the heterogeneity and correlation of user demands on product features. In particular, users' implicit requirements in terms of product function and performance are elicited from the text mining of product reviews. Third, incorporating various user requirements mined from dynamic internet data, graph theory analysis is introduced into design generation, product improvement, and market analysis. A case study on Chinese smartphones is presented, where the results show that the proposed method is practical and suitable for product-design analysis using the large volume of dynamic internet data.
Journal: International Journal of Production Research
Pages: 5660-5684
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1541200
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1541200
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:18:p:5660-5684




Template-Type: ReDIF-Article 1.0
Author-Name: Matthieu Godichaud
Author-X-Name-First: Matthieu
Author-X-Name-Last: Godichaud
Author-Name: Lionel Amodeo
Author-X-Name-First: Lionel
Author-X-Name-Last: Amodeo
Title: EOQ inventory models for disassembly systems with disposal and lost sales
Abstract: 
 The economic order quantity (EOQ) for disassembly systems consists of determining quantities of a products to disassemble at different times over an infinite planning horizon. As for basic EOQ settings, the demands for the product components are known, continuous and constant and the sum of ordering, operation and inventory costs has to be minimised. Despite the diversity of EOQ-related literature, there is no model that applies directly to disassembly. Three new EOQ models for disassembly systems are proposed in this paper. Two level product structures are considered with demands for the components. In this context, each disassembly operation leads to unnecessary inventories when the demands are not balanced. The proposed models integrates decisions for the management of the inventory surplus by allowing disposal operations and lost sales. The models with disposal orders use integer multipliers to model the coordination between disassembly and disposal orders. The detailed analysis of each model shows however that simple inventory policies allow avoiding the inventory surplus. The models with lost sales show that the policy is different from the one obtain in the single item EOQ model. Solution methods to determine the parameters of the policies are provided and illustrated.
Journal: International Journal of Production Research
Pages: 5685-5704
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1542180
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1542180
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:18:p:5685-5704




Template-Type: ReDIF-Article 1.0
Author-Name: Xiaolin Wang
Author-X-Name-First: Xiaolin
Author-X-Name-Last: Wang
Author-Name: Lishuai Li
Author-X-Name-First: Lishuai
Author-X-Name-Last: Li
Author-Name: Min Xie
Author-X-Name-First: Min
Author-X-Name-Last: Xie
Title: Optimal preventive maintenance strategy for leased equipment under successive usage-based contracts
Abstract: 
 In the context of equipment leasing, maintenance service is usually bundled with the leased equipment and offered by the lessor as an integrated package under a lease contract. The lessor is then responsible to prescribe an effective maintenance policy to keep the equipment operational in an economical way. This paper investigates upgrade and preventive maintenance (PM) strategies for industrial equipment during successive usage-based lease contracts with consideration of a warranty period, from the lessor's perspective. The accelerated failure time model and age reduction model are adopted to capture the effect of usage rate and imperfect PM/upgrade on the equipment reliability, respectively. More importantly, since equipment usage rates may vary across different lease contracts, this study develops an age correspondence framework to characterise usage rate shifts between successive lease periods. The optimal upgrade degree and the optimal number and level of PM actions are progressively updated for each upcoming lease period to minimise the total expected lease servicing cost, by considering the usage rate and maintenance implementation history. Numerical studies show that under given cost structures, periodical PM activities within each lease period tends to outperform the pre-leasing upgrade actions, though both of them can reduce the lease servicing cost.
Journal: International Journal of Production Research
Pages: 5705-5724
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1542181
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1542181
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:18:p:5705-5724




Template-Type: ReDIF-Article 1.0
Author-Name: Cui Zhao
Author-X-Name-First: Cui
Author-X-Name-Last: Zhao
Author-Name: Yao Zhang
Author-X-Name-First: Yao
Author-X-Name-Last: Zhang
Title: Dynamic quality and pricing decisions in customer-intensive service systems with online reviews
Abstract: 
 In this paper, we investigate dynamic quality and pricing decisions for customer-intensive service systems with online reviews. We construct a dynamic programming model to determine the optimal quality and pricing strategies. We find that with online reviews, the supplier is forced to provide a higher quality at a higher price for fewer customers, especially when the customer intensity is high. Interestingly, although online reviews deliver quality information for later consumers, the provided quality may decrease over time. Next, we compare the optimal strategies with those of models of either quality flexibility or pricing flexibility, respectively, to examine the merits of our developed model of both quality and pricing flexibilities. The comparison results demonstrate that our model can achieve higher profits, and the advantages of our model increase with the number of periods. In addition, quality (pricing) flexibility is more valuable when consumers are more sensitive to service price (quality). Furthermore, we compare our formulated model with the model for a regular service system, and we illustrate that the optimal quality and pricing strategies in our system are quite different from those of the regular service system.
Journal: International Journal of Production Research
Pages: 5725-5748
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1543972
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543972
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:18:p:5725-5748




Template-Type: ReDIF-Article 1.0
Author-Name: Zhiyang Jia
Author-X-Name-First: Zhiyang
Author-X-Name-Last: Jia
Author-Name: Kaixin Zhao
Author-X-Name-First: Kaixin
Author-X-Name-Last: Zhao
Author-Name: Yan Zhang
Author-X-Name-First: Yan
Author-X-Name-Last: Zhang
Author-Name: Yaping Dai
Author-X-Name-First: Yaping
Author-X-Name-Last: Dai
Author-Name: Chang Liu
Author-X-Name-First: Chang
Author-X-Name-Last: Liu
Title: Real-time performance evaluation and improvement of assembly systems with Bernoulli machines and finite production runs
Abstract: 
 Extensive research has been investigated in the past several decades to evaluate the performance of manufacturing systems under rigid production mode. Based on the deployment of the new manufacturing strategies (e.g. smart manufacturing), real-time performance analysis, continuous improvement and efficient production management of flexible production systems are urgently to be investigated. Therefore, we study the problems of real-time performance evaluation and bottleneck of assembly systems in this paper. The system is assumed to have Bernoulli machines and finite production runs. We first derive the mathematical model of the system and then, derive the analytical formulas for performance evaluation of systems with three Bernoulli machines. In addition, we propose a decomposition and aggregation-based algorithm to approximate the system performances with high accuracy and computational efficiency. The idea is then extended to generalised assembly systems. Finally, the method of bottleneck analysis by using completion time bottleneck indicator is introduced and evaluated by numerical justification.
Journal: International Journal of Production Research
Pages: 5749-5766
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1544426
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1544426
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:18:p:5749-5766




Template-Type: ReDIF-Article 1.0
Author-Name: Yun Dong
Author-X-Name-First: Yun
Author-X-Name-Last: Dong
Author-Name: Ren Zhao
Author-X-Name-First: Ren
Author-X-Name-Last: Zhao
Title: Solving steel coil ship stowage-planning problem using hybrid differential evolution
Abstract: 
 As an important optimisation problem in the finished product terminal of an iron and steel enterprise, the steel coil ship stowage-planning problem is to determine the stowing locations for the planned coils on a ship. Although the problem has attracted attention, the research has focused only on the optimisation for the ship. In this study, the problem is investigated from the view of improving operation efficiency of the cranes on the quay and in the warehouse. For this purpose, an integer-programming model is established to minimise the coil dispersion on the ship and the moving distance of the warehouse cranes by determining the stowing locations and loading sequence of the coils. To improve the solution efficiency, a two-level hybrid differential evolution (TLDE) composed of a continuous DE and a discrete DE is designed to assign the coils to the rows on the ship, and then allocate locations for them. Further, a subpopulation-based local search and a human experience-based heuristic are developed to further adjust the coils within each row and to produce initial population for TLDE, respectively. Extensive comparison experiments are performed to demonstrate the proposed algorithm. Numerical results confirm that TLDE is an efficient method for solving the SSPP.
Journal: International Journal of Production Research
Pages: 5767-5786
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1550270
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1550270
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Template-Type: ReDIF-Article 1.0
Author-Name: Gian Luca Gregori
Author-X-Name-First: Gian Luca
Author-X-Name-Last: Gregori
Author-Name: Maria Rosaria Marcone
Author-X-Name-First: Maria Rosaria
Author-X-Name-Last: Marcone
Title: R&D and manufacturing activities regarding managerial effectiveness and open strategy: an industry focus on luxury knitwear firms
Abstract: 
 The authors structure the field of over-design, over-specification, and over-requirement (OOO) drawing from extant knowledge related to innovative managerial procedures in manufacturing systems, project portfolio management, and performance management. More specifically, we propose allowing the dominant perspectives of OOO and paving the way towards a coherent recognition foundation of innovative strategies in manufacturing systems. This lends itself to an analysis of innovative phenomena in design and production systems that generate OOO and helps to understand what the effects of the OOO on business performance are. The clothing industry in Italy was chosen as a target context because many innovative pioneering medium sized enterprises (MSEs) were operating in the industry. Because of the exploratory nature of the research, a multiple case study approach is adopted in this study. Drawing from extant managerial literature, the proposed structure shows which business model objects and interactions within R&D-manufacturing-marketing activities should be considered when engaging in managing innovative and temporary project portfolio.
Journal: International Journal of Production Research
Pages: 5787-5800
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1550271
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1550271
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:18:p:5787-5800




Template-Type: ReDIF-Article 1.0
Author-Name: Jinxin Pan
Author-X-Name-First: Jinxin
Author-X-Name-Last: Pan
Author-Name: Shuai Ding
Author-X-Name-First: Shuai
Author-X-Name-Last: Ding
Author-Name: Desheng Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Wu
Author-Name: Shanlin Yang
Author-X-Name-First: Shanlin
Author-X-Name-Last: Yang
Author-Name: Jun Yang
Author-X-Name-First: Jun
Author-X-Name-Last: Yang
Title: Exploring behavioural intentions toward smart healthcare services among medical practitioners: a technology transfer perspective
Abstract: 
 Recently, a variety of artificial intelligence (AI)-driven smart healthcare services are rapidly emerging in the medical market, such as intelligent image analysis, surgical navigation systems, and aided diagnosis. However, one of the major challenges is practitioners’ hesitation and unwillingness to employ these new technologies in medical practice. This study focuses on identifying the influential factors of adoption intention of smart healthcare services for both clinicians and non-clinicians from the perspective of technology transfer. Through collecting 484 questionnaire data from doctors in Anhui, China, we find support to show that perceived usefulness (PU), attitude, and the experience of using mHealth are key factors that influence both clinicians and non-clinician’s adoption intention. Meanwhile, it is confirmed that subjective norm has a positive effect on only clinicians’ behavioural intention (BI) while perceived risk (PR) has a negative impact on only non-clinicians’ attitude. Among all the constructs, the experience of using mHealth has the strongest positive effect on doctors’ adoption intention on smart healthcare services, a positive impact on the PU and perceived ease of use, and a negative impact on the PR. This study provides an improved understanding of doctors’ BI of smart healthcare services, and practice guidance for product development and marketing strategies.
Journal: International Journal of Production Research
Pages: 5801-5820
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1550272
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1550272
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:18:p:5801-5820




Template-Type: ReDIF-Article 1.0
Author-Name: Hung-Yu Lee
Author-X-Name-First: Hung-Yu
Author-X-Name-Last: Lee
Author-Name: Chase C. Murray
Author-X-Name-First: Chase C.
Author-X-Name-Last: Murray
Title: Robotics in order picking: evaluating warehouse layouts for pick, place, and transport vehicle routing systems
Abstract: 
 Motivated by recent technological advances in mobile robotics, this paper explores a novel approach for warehouse order picking. In particular, this work considers two types of commercially available mobile robots – one that can grasp items from a shelf (a picker) and another (a transporter) that can quickly deliver all items from the pick list to the packing station. A new vehicle routing problem is defined which seeks to minimise the time to deliver all items from a pick list to the packing station, a problem termed the pick, place, and transport vehicle routing problem. A mixed integer linear programming formulation is developed to answer three related research questions. First, what combination of picker and transport robots is required to obtain performance exceeding traditional human-based picking operations? Second, how should the composition of the robot fleet be altered to affect the greatest performance improvements? Finally, what are the impacts of warehouse layout designs when coordinated mobile robots are deployed? An extensive numerical analysis reveals that, (1) increasing the number of cross aisles decreases system performance; (2) centrally located packing stations improve system performance; and (3) the average distance from each pick location to the packing station and the average distance between pick locations are effective metrics for identifying specific fleet modifications that are likely to yield system improvements.
Journal: International Journal of Production Research
Pages: 5821-5841
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1552031
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1552031
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhiqiang Lu
Author-X-Name-First: Zhiqiang
Author-X-Name-Last: Lu
Author-Name: Hongwei Zhu
Author-X-Name-First: Hongwei
Author-X-Name-Last: Zhu
Author-Name: Xiaole Han
Author-X-Name-First: Xiaole
Author-X-Name-Last: Han
Author-Name: Xinming Hu
Author-X-Name-First: Xinming
Author-X-Name-Last: Hu
Title: Integrated modelling and algorithm of material delivery and line-side storage for aircraft moving assembly lines
Abstract: 
 This paper considers the material supply problem for aircraft moving assembly lines. Distinguished from general automobile assembly lines, multiple parallel jobs are assembled concurrently and durations of assembly jobs are quite long, thus amounts of materials are orderly stored at the line-side space at the same time. In addition, the line-side space should be reused in the time dimension. With these characteristics, decisions on line-side storage of materials were introduced on the basis of material batching and tow-trains scheduling problems. An integrated decision–making mathematical model with the objective of minimising the number of deliveries was established. A hybrid endocrine-immune algorithm (HEIA) was proposed to jointly make decisions on the delivery batch, delivery time and storage positions of each job’s materials. Numerical experiments with the real-world data and randomly generated instances validate the effectiveness and efficiency of HEIA.
Journal: International Journal of Production Research
Pages: 5842-5856
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1554917
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1554917
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Template-Type: ReDIF-Article 1.0
Author-Name: Christian Hueber
Author-X-Name-First: Christian
Author-X-Name-Last: Hueber
Author-Name: Gudrun Fischer
Author-X-Name-First: Gudrun
Author-X-Name-Last: Fischer
Author-Name: Nikolaus Schwingshandl
Author-X-Name-First: Nikolaus
Author-X-Name-Last: Schwingshandl
Author-Name: Ralf Schledjewski
Author-X-Name-First: Ralf
Author-X-Name-Last: Schledjewski
Title: Production planning optimisation for composite aerospace manufacturing
Abstract: 
 Composite materials proved highly successful for aerospace applications in the last decades, but increased cost pressure forces the composite industry to become more efficient. This requires new manufacturing technologies and optimised processes as raw material costs and labour costs are basically fixed when wanting to keep production on site. Probably the most defining process for aerospace composite production is manual layup of prepreg material with subsequent curing in an autoclave. From production planning view, this combination poses the challenge of transition from discrete layup manufacturing to batch curing processing with the restriction of limited allowed storage time of the prepreg material prior to cure. In this paper, a new approach for production order optimisation at the conjunction of discrete and batch processing is presented. The APOLLO named tool is designed to decrease throughput times, streamline production and increase autoclave utilisation in the composite aerospace industry.
Journal: International Journal of Production Research
Pages: 5857-5873
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1554918
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1554918
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Template-Type: ReDIF-Article 1.0
Author-Name: Shujuan Guo
Author-X-Name-First: Shujuan
Author-X-Name-Last: Guo
Author-Name: Fei Geng
Author-X-Name-First: Fei
Author-X-Name-Last: Geng
Author-Name: Katsuhiko Takahashi
Author-X-Name-First: Katsuhiko
Author-X-Name-Last: Takahashi
Author-Name: Xiaohan Wang
Author-X-Name-First: Xiaohan
Author-X-Name-Last: Wang
Author-Name: Zhihong Jin
Author-X-Name-First: Zhihong
Author-X-Name-Last: Jin
Title: A MCVRP-based model for PCB assembly optimisation on the beam-type placement machine
Abstract: 
 The beam-type placement machine is capable of picking up multiple components simultaneously from the feeders in printed circuit board (PCB) assembly. Simultaneous pickup occurs only if the heads in the beam are aligned with the feeders and the nozzle-types on these heads match with the component-types on the feeders. In order to minimise the assembly cycle time, the optimisation problem is decomposed into two sub-problems, the pickup combination and sequencing problem, and the placement cluster and sequencing problem. These two sub-problems are simultaneously solved by the proposed hybrid genetic algorithm (HGA). The pickup combination and sequencing problem is similar to the popular multi-compartment vehicle routing problem (MCVRP); a genetic algorithm (GA) for the MCVRP is therefore modified and applied to solving the pickup combination and sequencing problem. A greedy heuristic algorithm is used to solve the placement cluster and sequencing problem. The numerical experiments reveal that the HGA outperforms the algorithms proposed by previous papers.
Journal: International Journal of Production Research
Pages: 5874-5891
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1555380
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1555380
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Template-Type: ReDIF-Article 1.0
Author-Name: Nilesh Perlekar
Author-X-Name-First: Nilesh
Author-X-Name-Last: Perlekar
Author-Name: Jitesh J. Thakkar
Author-X-Name-First: Jitesh J.
Author-X-Name-Last: Thakkar
Title: Risk management framework for outsourcing in the defence sector: a case from India
Abstract: 
 A nation automatically becomes strong if it has self-sufficiency to fulfil its defence requirements. India is moving in the direction to attain self-reliance in the defence sector. The aim of this paper is to analyse the critical issues faced in outsourcing by an organisation in Indian Defence Sector and extend easy, quick, complete and practically implementable risk mitigation strategies for enabling better decision-making. In this research, a list of 20 risk criteria is finalised on the basis of the literature survey and expert’s opinion. Analysis in this research shows that, three criteria which can seriously affect the outsourcing are Material shortage risk, Quality Risk and On-time delivery risk. The paper employs an integrated framework which includes ‘Grey Theory, Failure Mode and Effect Analysis (FMEA) and Risk Management Matrices’ for a comprehensive risk management in the defence sector. The paper delivers a 10-point risk management action plan to counter the various problems faced during outsourcing in the defence sector, especially in the Indian context. In brief, this paper investigates the various important issues related to outsourcing, which are faced by organisations working in Indian Defence Sector and extends a practically implementable methodology to derive a practically amicable solution for the case organisation.
Journal: International Journal of Production Research
Pages: 5892-5919
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1555381
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1555381
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Template-Type: ReDIF-Article 1.0
Author-Name: Luiz J.P. Araújo
Author-X-Name-First: Luiz J.P.
Author-X-Name-Last: Araújo
Author-Name: Ender Özcan
Author-X-Name-First: Ender
Author-X-Name-Last: Özcan
Author-Name: Jason A.D. Atkin
Author-X-Name-First: Jason A.D.
Author-X-Name-Last: Atkin
Author-Name: Martin Baumers
Author-X-Name-First: Martin
Author-X-Name-Last: Baumers
Title: Analysis of irregular three-dimensional packing problems in additive manufacturing: a new taxonomy and dataset
Abstract: 
 With most Additive Manufacturing (AM) technology variants, build processes take place inside an internal enclosed build container, referred to as a ‘build volume’. It has been demonstrated that the effectiveness with which this volume is filled with product geometries forms an important determinant of overall process efficiency in AM. For effective operations management, it is important to understand not only the problem faced, but also which methods have proved effective (or ineffective) for problems with these characteristics in the past. This research aims to facilitate this increased understanding. The build volume packing task can be formulated as a three-dimensional irregular packing (3DIP) problem, which is a combinatorial optimisation problem requiring the configuration of a set of arbitrary volumetric items. This paper reviews existing general cutting and packing taxonomies and provides a new specification which is more appropriate for classifying the problems encountered in AM. This comprises a clear-cut problem definition, a set of precise categorisation criteria for objectives and problem instances, and a simple notation. Furthermore, the paper establishes an improved terminology with terms that are familiar to, but not limited to, researchers and practitioners in the field of AM. Finally, this paper describes a new dataset to be used in the evaluation of existing and proposed computational solution methods for 3DIP problems encountered in AM and discusses the importance of this research for further underpinning work.
Journal: International Journal of Production Research
Pages: 5920-5934
Issue: 18
Volume: 57
Year: 2019
Month: 9
X-DOI: 10.1080/00207543.2018.1534016
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1534016
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenyan Song
Author-X-Name-First: Wenyan
Author-X-Name-Last: Song
Author-Name: Xinguo Ming
Author-X-Name-First: Xinguo
Author-X-Name-Last: Ming
Author-Name: Yi Han
Author-X-Name-First: Yi
Author-X-Name-Last: Han
Author-Name: Zhitao Xu
Author-X-Name-First: Zhitao
Author-X-Name-Last: Xu
Author-Name: Zhenyong Wu
Author-X-Name-First: Zhenyong
Author-X-Name-Last: Wu
Title: An integrative framework for innovation management of product–service system
Abstract: 
 This paper presents a framework of innovation management for product–service system (PSS). Manufacturers today tend to place more emphasis on adding value to customers through PSS innovation due to competitions and environment regulations. However, PSS development is a kind of complex innovation facing challenges such as heterogeneity of stakeholders, interaction of product and service elements and complex performance measurement. Thus, manufacturers need systematic innovation management for the success of the PSS. However, the past fragmental studies mainly focus on the design domain rather than the systematic innovation management which provides useful guidance for PSS innovation. In this research, the authors propose an integrative framework for managing PSS innovation. In addition, an application in a PSS innovation project of vending machine is introduced to demonstrate potentials of the framework.
Journal: International Journal of Production Research
Pages: 2252-2268
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.932929
File-URL: http://hdl.handle.net/10.1080/00207543.2014.932929
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Template-Type: ReDIF-Article 1.0
Author-Name: Ting Kong
Author-X-Name-First: Ting
Author-X-Name-Last: Kong
Author-Name: Gang Li
Author-X-Name-First: Gang
Author-X-Name-Last: Li
Author-Name: Taiwen Feng
Author-X-Name-First: Taiwen
Author-X-Name-Last: Feng
Author-Name: Linyan Sun
Author-X-Name-First: Linyan
Author-X-Name-Last: Sun
Title: Effects of marketing–manufacturing integration across stages of new product development on performance
Abstract: 
 Our understanding on the benefits of marketing–manufacturing integration (MMI) across various stages of new product development (NPD) process is limited. Based on the resource-based view of a firm, this study empirically examines the direct and interactive effects of MMI in four stages of NPD process on three dimensions of new product performance. Survey data from 214 completed NPD projects in Chinese manufacturing firms are employed to test the developed hypotheses using hierarchical regression. The results indicate that greater MMI in each stage is, respectively, associated with faster NPD speed. Stronger MMI in business/market opportunity analysis (BMA), technical development (TD) and product testing (PT) stage is, respectively, associated with higher NPD cost efficiency. Higher MMI in BMA and PT stage is, respectively, associated with better market performance. In addition, the interactions of MMI in BMA and TD stages and MMI in PT and product commercialization (PC) stages have positive effects on NPD speed and NPD cost efficiency, while the interaction of MMI in BMA and PC stages has negative effects on NPD speed and NPD cost efficiency. The interaction of MMI in BMA, TD and PC stages is positively related to market performance; surprisingly, the interactions of MMI in BMA, TD and PT stages and MMI in BMA, PT and PC stages are negatively related to market performance. These findings have important implications for research and practice in both the cross-functional integration and NPD areas.
Journal: International Journal of Production Research
Pages: 2269-2284
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.932934
File-URL: http://hdl.handle.net/10.1080/00207543.2014.932934
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiunn-Chenn Lu
Author-X-Name-First: Jiunn-Chenn
Author-X-Name-Last: Lu
Author-Name: Taho Yang
Author-X-Name-First: Taho
Author-X-Name-Last: Yang
Title: Implementing lean standard work to solve a low work-in-process buffer problem in a highly automated manufacturing environment
Abstract: 
 Over the past few decades, a considerable number of studies have been reported on assembly lines or less automated factories. Little attention has been given to implementing lean tools to a highly automated manufacturing environment. It is, therefore, necessary to make a more highly automated factory lean by considering both the manufacturing system variability and demand uncertainty. The purpose of this paper is to propose an effective lean tool to help practical lean participants successfully implement lean practices in a highly automated manufacturing environment. This study presents an example of how lean standard work is implemented and the throughput of a pacemaker workstation is improved by solving the low work-in-process buffer problem. A practical case from a photovoltaic module process with a semi-automated production line is used to illustrate the proposed method. The implementation results are promising. They showed a 37.5% labour reduction prior to the pacemaker workstation and a 304.7% increase in the daily throughput at the bottleneck workstation.
Journal: International Journal of Production Research
Pages: 2285-2305
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.937009
File-URL: http://hdl.handle.net/10.1080/00207543.2014.937009
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Template-Type: ReDIF-Article 1.0
Author-Name: Shuoguo Wei
Author-X-Name-First: Shuoguo
Author-X-Name-Last: Wei
Author-Name: Ou Tang
Author-X-Name-First: Ou
Author-X-Name-Last: Tang
Title: Real option approach to evaluate cores for remanufacturing in service markets
Abstract: 
 Acquisition of cores is important for the success of remanufacturing business, but evaluating the value of cores is difficult due to many uncertain issues in the remanufacturing system. In this paper, we examine the value of cores using the real option valuation (ROV) approach, which well captures the production flexibility and represents different operations options in remanufacturing. First, in a system where the demand of remanufactured products is low, we focus on the uncertainty of price. We compare the cases where disposing cores occurs only at the expiration time and before that. The model also identifies under which circumstances disposing core early brings in more benefit. Furthermore, we study a remanufacturing system where demand and return are both uncertain. In this case, a spread option is used for evaluating the marginal value of obtaining additional cores. This approach also brings the advantage of linking the correlation between demand and return, which in fact is often exhibited in remanufacturing. The numerical experiments indicate that this correlation has an impact on collecting policies. This study illustrates the possibility of using ROV for core pricing modelling, and the study results also provide some managerial insights in managing returned cores.
Journal: International Journal of Production Research
Pages: 2306-2320
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.939243
File-URL: http://hdl.handle.net/10.1080/00207543.2014.939243
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcel Langer
Author-X-Name-First: Marcel
Author-X-Name-Last: Langer
Author-Name: Dirk Söffker
Author-X-Name-First: Dirk
Author-X-Name-Last: Söffker
Title: Event-discrete formal representation of a semi-automated manufacturing process as framework for human guidance and assistance concepts: analysis and application
Abstract: 
 This contribution focuses on the task of guiding and supervision processes realised by human operators. The trade-off between manual manufacturing and automation is addressed by semi-automation of a mould manufacturing process, traditionally handmade. Within this process, the human operator plays a central role (i.e. knowledge and expertise), whereas the (intelligent) automation is carrying out physical operation, which is guided and supervised by the human operator. Process guiding assistance is given based on the formalisation of the human-machine-interaction. By deducing information of interest with respect to the current process goal, the established process model can be easily used for supervision and assistance. The integrated human-automation-system is initially evaluated. The results are discussed for the future work with respect to the individual process understanding and process reproducibility.
Journal: International Journal of Production Research
Pages: 2321-2341
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.942756
File-URL: http://hdl.handle.net/10.1080/00207543.2014.942756
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiao-Feng Shao
Author-X-Name-First: Xiao-Feng
Author-X-Name-Last: Shao
Title: Product differentiation design under sequential consumer choice process
Abstract: 
 We consider a product variety design problem with respect to both vertical and horizontal differentiation dimensions under a sequential consumer choice process. Consumers have heterogeneous valuations for product quality as well as different preferences for product type. We consider two sequential consumer choice processes: a quality-based choice model where consumers consider product quality first and then product type, and a type-based choice model with the reversed order. Under the quality-based model, the category manager can either adopt vertical differentiation strategy or bi-dimensional differentiation strategy, whereas under the type-based model, the category manager can either adopt horizontal differentiation strategy or bi-dimensional differentiation strategy. We characterise the structure of optimal product category and prices for each product differentiation strategy and develop efficient algorithms for the quality-based consumer choice model. We find that under the quality-based choice model, vertical differentiation strategy is more profitable than bi-dimensional differentiation strategy, whereas under the type-based choice model, horizontal differentiation strategy is preferred over bi-dimensional differentiation strategy. The result is robust considering the impact of heterogeneity in consumer choice process. Thus, further differentiation in quality or type is actually not preferred when consumers follow a sequential consumer choice process.
Journal: International Journal of Production Research
Pages: 2342-2364
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.951091
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951091
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Template-Type: ReDIF-Article 1.0
Author-Name: Gangfeng Wang
Author-X-Name-First: Gangfeng
Author-X-Name-Last: Wang
Author-Name: Xitian Tian
Author-X-Name-First: Xitian
Author-X-Name-Last: Tian
Author-Name: Junhao Geng
Author-X-Name-First: Junhao
Author-X-Name-Last: Geng
Author-Name: Biao Guo
Author-X-Name-First: Biao
Author-X-Name-Last: Guo
Title: A knowledge accumulation approach based on bilayer social wiki network for computer-aided process innovation
Abstract: 
 Under the fierce competition, manufacturing companies pay more attention to innovation and the knowledge that enables innovation. Manufacturing process innovation is a knowledge-intensive activity, and efficient knowledge accumulation is the prerequisite and basis for computer-aided process innovation (CAPI). Hence, this research aims to build an open knowledge accumulation approach to obtain organised and refined process innovation knowledge (PIK). By considering the similarity of PIK network with biological neural network and combining the technical characteristics of social network with wiki, a novel PIK accumulation schema based on bilayer social wiki network is proposed. In social wiki network environment, PIK is accumulated in public knowledge space through participants’ social interactions and knowledge activities. The process of knowledge fusion is investigated to form the preliminary knowledge containing collective intelligence, and the mechanisms of collaborative editing and collaborative evolution are studied to refine the knowledge. The outcomes of this study lay the foundation for knowledge application of CAPI. Finally, a case study is presented to demonstrate the applicability of the proposed approach.
Journal: International Journal of Production Research
Pages: 2365-2382
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.958591
File-URL: http://hdl.handle.net/10.1080/00207543.2014.958591
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Template-Type: ReDIF-Article 1.0
Author-Name: I.O. Sanya
Author-X-Name-First: I.O.
Author-X-Name-Last: Sanya
Author-Name: E.M. Shehab
Author-X-Name-First: E.M.
Author-X-Name-Last: Shehab
Title: A framework for developing engineering design ontologies within the aerospace industry
Abstract: 
 This paper presents a framework for developing engineering design ontologies within the aerospace industry. The aim of this approach is to strengthen the modularity and reuse of engineering design ontologies to support knowledge management initiatives within the aerospace industry. Successful development and effective utilisation of engineering ontologies strongly depends on the method/framework used to develop them. Ensuring modularity in ontology design is essential for engineering design activities due to the complexity of knowledge that is required to be brought together to support the product design decision-making process. The proposed approach adopts best practices from previous ontology development methods, but focuses on encouraging modular architectural ontology design. The framework is comprised of three phases namely: (1) Ontology design and development; (2) Ontology validation and (3) Implementation of ontology structure. A qualitative research methodology is employed which is composed of four phases. The first phase defines the capture of knowledge required for the framework development, followed by the ontology framework development, iterative refinement of engineering ontologies and ontology validation through case studies and experts’ opinion. The ontology-based framework is applied in the combustor and casing aerospace engineering domain. The modular ontologies developed as a result of applying the framework and are used in a case study to restructure and improve the accessibility of information on a product design information-sharing platform. Additionally, domain experts within the aerospace industry validated the strengths, benefits and limitations of the framework. Due to the modular nature of the developed ontologies, they were also employed to support other project initiatives within the case study company such as role-based computing (RBC), IT modernisation activity and knowledge management implementation across the sponsoring organisation. The major benefit of this approach is in the reduction of man-hours required for maintaining engineering design ontologies. Furthermore, this approach strengthens reuse of ontology knowledge and encourages modularity in the design and development of engineering ontologies.
Journal: International Journal of Production Research
Pages: 2383-2409
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.965352
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965352
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei-Kang Wang
Author-X-Name-First: Wei-Kang
Author-X-Name-Last: Wang
Author-Name: Yee Chuann Chan
Author-X-Name-First: Yee Chuann
Author-X-Name-Last: Chan
Author-Name: Wen-Min Lu
Author-X-Name-First: Wen-Min
Author-X-Name-Last: Lu
Author-Name: Hua Chang
Author-X-Name-First: Hua
Author-X-Name-Last: Chang
Title: The impacts of asset impairments on performance in the Taiwan listed electronics industry
Abstract: 
 This paper explores whether the recognition of asset impairments provides an opportunity for earnings management by examining changes in the performance. First, we apply a dynamic data envelopment analysis model to evaluate the operating performance of Taiwanese electronics firms for the period from 2004 to 2013. Statistical tests are next applied to assess the average efficiency variation between the periods before and after firms recognise asset impairments. Several empirical findings are as follows: managers recognise asset impairments when their firms have poor performance as compared to other firms that do not record any asset impairments recognition, and that their performance keeps on improving in both the year of recognising asset impairments and the year after asset impairments recognition. That is, managers tend to recognise asset impairments to improve operating performance, while the firms are performing poorly, supporting the opportunistic behaviour theory.
Journal: International Journal of Production Research
Pages: 2410-2426
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.972526
File-URL: http://hdl.handle.net/10.1080/00207543.2014.972526
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Template-Type: ReDIF-Article 1.0
Author-Name: Chih-Hsuan Wang
Author-X-Name-First: Chih-Hsuan
Author-X-Name-Last: Wang
Title: Integrating Kansei engineering with conjoint analysis to fulfil market segmentation and product customisation for digital cameras
Abstract: 
 Diverse customer desires coupled with technological advances have forced companies to manufacture products with ultimate performance, low cost, high quality and much shorter time-to-market. Recently, the popularity of smart phones has given rise to seriously declined product sales of digital cameras. In this paper, a two-phase framework is presented to offer decision supports on developing next-generation cameras. In the phase of market segmentation, Kansei engineering is employed to capture customer perceptions of affective features. Then, rough set theory is conducted to generate decision rules for partitioning the whole market into the consumer segment and the professional segment, respectively. In the phase of product customisation, conjoint analysis is applied to extract customer preferences for functional features. Furthermore, Grey relational analysis is conducted to select the top three varieties with regard to two distinct segments. In particular, this paper is capable to help brand companies or camera manufacturers better capture customer perceptions and preferences for digital cameras, effectively perform market segmentation (based on affective features) and efficiently conduct product customisation (based on functional features).
Journal: International Journal of Production Research
Pages: 2427-2438
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.974840
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974840
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Template-Type: ReDIF-Article 1.0
Author-Name: Khaled Medini
Author-X-Name-First: Khaled
Author-X-Name-Last: Medini
Author-Name: Catherine Da Cunha
Author-X-Name-First: Catherine
Author-X-Name-Last: Da Cunha
Author-Name: Alain Bernard
Author-X-Name-First: Alain
Author-X-Name-Last: Bernard
Title: Tailoring performance evaluation to specific industrial contexts – application to sustainable mass customisation enterprises
Abstract: 
 This paper proposes an approach for measuring performance improvement through prioritising and aggregating performance indicators (PIs). The proposed approach helps practitioners build, in a formal way, their performance measurement systems. The novelty of the methodology lies in: (i) adapting PIs to specific industrial contexts according to companies concerns and (ii) supporting the decision-making process by providing a holistic and limited number of aggregated PIs. The context considered in the current research is sustainable mass customisation (SMC). Accordingly, a set of SMC indicators are used to illustrate the applicability of the methodology. The implementation and illustration with a real case showed some evidence of its usefulness and pointed out several improvement rooms.
Journal: International Journal of Production Research
Pages: 2439-2456
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.974844
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974844
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Template-Type: ReDIF-Article 1.0
Author-Name: Prashant Tuli
Author-X-Name-First: Prashant
Author-X-Name-Last: Tuli
Author-Name: Ravi Shankar
Author-X-Name-First: Ravi
Author-X-Name-Last: Shankar
Title: Collaborative and lean new product development approach: a case study in the automotive product design
Abstract: 
 Collaboration between buyer and the supplier has been widely studied in the contemporary research to enhance the efficiency of the product development process. Early involvement of stakeholders in development leads to reduced development time and cost and enhanced quality. The current study presents an approach termed as ‘collaborative and lean’ (C&amp;L) approach to new product development (NPD). It involves application of lean principles in a collaborative environment between an automotive component supplier and the original equipment manufacturer (OEM). The study compares the deployment of two methodologies of development – generic process and the C&amp;L process for developing the same part by a supplier for two different OEMs. Development with one OEM was done using generic process and the other using the C&amp;L process. The study uses value stream mapping of the various phases of the development and attempts to understand the application of the proposed approach in the automotive domain. It highlights the potential of a combined C&amp;L approach in reducing non-value-adding activities, cycle time and effort during NPD. The study attempts to enhance the understanding of NPD in a collaborative environment and explores the possible merits of the proposed approach.
Journal: International Journal of Production Research
Pages: 2457-2471
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.974849
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974849
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Template-Type: ReDIF-Article 1.0
Author-Name: Huimin Jiang
Author-X-Name-First: Huimin
Author-X-Name-Last: Jiang
Author-Name: C.K. Kwong
Author-X-Name-First: C.K.
Author-X-Name-Last: Kwong
Author-Name: Y. Liu
Author-X-Name-First: Y.
Author-X-Name-Last: Liu
Author-Name: W.H. Ip
Author-X-Name-First: W.H.
Author-X-Name-Last: Ip
Title: A methodology of integrating affective design with defining engineering specifications for product design
Abstract: 
 Affective design and the determination of engineering specifications are commonly conducted separately in early product design stage. Generally, designers and engineers are required to determine the settings of design attributes (for affective design) and engineering requirements (for engineering design), respectively, for new products. Some design attributes and some engineering requirements could be common. However, the settings of the design attributes and engineering requirements could be different because of the separation of the two processes. In previous studies, a methodology that considers the determination of the settings of the design attributes and engineering requirements simultaneously was not found. To bridge this gap, a methodology for considering affective design and the determination of engineering specifications of a new product simultaneously is proposed. The proposed methodology mainly involves generation of customer satisfaction models, formulation of a multi-objective optimisation model and its solving using a chaos-based NSGA-II. To illustrate and validate the proposed methodology, a case study of mobile phone design was conducted. A validation test was conducted and the test results showed that the customer satisfaction values obtained based on the proposed methodology were higher than those obtained based on the combined standalone quality function deployment and standalone affective design approach.
Journal: International Journal of Production Research
Pages: 2472-2488
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.975372
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975372
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Kach
Author-X-Name-First: Andrew
Author-X-Name-Last: Kach
Author-Name: Arash Azadegan
Author-X-Name-First: Arash
Author-X-Name-Last: Azadegan
Author-Name: Stephan M. Wagner
Author-X-Name-First: Stephan M.
Author-X-Name-Last: Wagner
Title: The influence of different knowledge workers on innovation strategy and product development performance in small and medium-sized enterprises
Abstract: 
 Despite significant interest on the topic of knowledge workers, the understanding of how they influence certain aspects of firm innovativeness remains limited. In particular, while different types of knowledge workers exist, their particular synergistic effects on new and improved product development within smaller firms has received less attention. Drawing on the knowledge-based view (KBV), we posit that innovation strategy plays an instrumental role in linking the effects of knowledge workers, thereby leading to greater product development outcomes from different types of knowledge workers. Moreover, some suggest that beyond a certain point, there is a diminishing return to increasing the proportion of knowledge workers in an organisation; however, the basis of this finding is within larger firms. This study investigates whether high-level (e.g. engineers and scientists) and low-level (e.g. technicians and machine operators) knowledge workers exert varying effects on performance in terms of new and improved product development. Data from 205 small and medium-sized high-tech manufacturing firms provide support that distinguishing among types of knowledge workers is important given that they impact new and improved product development differently. Furthermore, innovation strategy plays a synergistic role, positively mediating the effects of different types of knowledge workers on innovation outcomes.
Journal: International Journal of Production Research
Pages: 2489-2505
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.975856
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975856
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Template-Type: ReDIF-Article 1.0
Author-Name: Yemisi A. Bolumole
Author-X-Name-First: Yemisi A.
Author-X-Name-Last: Bolumole
Author-Name: Roger J. Calantone
Author-X-Name-First: Roger J.
Author-X-Name-Last: Calantone
Author-Name: C. Anthony Di Benedetto
Author-X-Name-First: C. Anthony
Author-X-Name-Last: Di Benedetto
Author-Name: Steven A. Melnyk
Author-X-Name-First: Steven A.
Author-X-Name-Last: Melnyk
Title: New product development in new ventures: the quest for resources
Abstract: 
 Innovation and new product development (NPD) are becoming more important as strategic initiatives. Yet, innovation creates challenges for most existing organisations, thus leading to the emergence of new ventures (NVs) as vehicles to deliver innovation. NVs present owners and management with unique opportunities and challenges. On one hand, the NV can focus its attention on specific innovation(s) without having to compete with other goals and departments for resource access. Resources are critical to the successful development and launch of new products and can come from financial lenders and/or suppliers. However, because they are new and because their only asset of worth is the highly risky innovation, NVs are at a strong disadvantage in securing access to these resources. This study explores the effectiveness of using personal equity investments as a strategy for securing access and for enhancing NPD success. Using signalling theory as the theoretical framework and data from 745 NPD projects representing manufacturing innovations, this study finds that equity investment is particularly successful in its NPD impact although not impactful with suppliers. As a signal, it can be argued that equity is a strong, high-quality signal. Reasons for these findings and directions for future research are provided.
Journal: International Journal of Production Research
Pages: 2506-2523
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.975858
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975858
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Template-Type: ReDIF-Article 1.0
Author-Name: Yongwen Huang
Author-X-Name-First: Yongwen
Author-X-Name-Last: Huang
Author-Name: Zuhua Jiang
Author-X-Name-First: Zuhua
Author-X-Name-Last: Jiang
Author-Name: Chengneng He
Author-X-Name-First: Chengneng
Author-X-Name-Last: He
Author-Name: Jianfeng Liu
Author-X-Name-First: Jianfeng
Author-X-Name-Last: Liu
Author-Name: Bo Song
Author-X-Name-First: Bo
Author-X-Name-Last: Song
Author-Name: Lijun Liu
Author-X-Name-First: Lijun
Author-X-Name-Last: Liu
Title: A semantic-based visualised wiki system (SVWkS) for lesson-learned knowledge reuse situated in product design
Abstract: 
 In the process of product design, engineers usually find it is difficult to precisely find and reuse others’ empirical knowledge resources, especially the lesson-learned knowledge, which is usually not well collected by the organisation. This study proposes a novel approach, which uses a semantic-based visualised wiki system (SVWkS) to support lesson-learned knowledge reuse. The core of visualised knowledge search framework is a semantic-based topic knowledge map. The architecture of this knowledge map creation method is designed, which has five major modules: lesson-learned items pre-processing, topic extraction, topic relation computation, topic weight computation and topic knowledge map generation modules. Then a working scenario of SVWkS is briefly introduced. We have conducted three sets of experiments to evaluate quality of visualised results-knowledge map, the effectiveness of semantic-based visualised searching mechanisms and the performance of utilising SVWkS for knowledge reuse in outfitting design of a ship-building company. The first experiment shows that knowledge maps generated by SVWkS are accepted by domain experts from the evaluation since precision and recall are high. The second experiment shows a semantic-based visualised searching mechanism supported by semantic relations is more useful than a traditional keyword search in terms of precision and recall. The third experiment shows that SVWkS-based group outperforms keyword search-based group in both learning score and satisfaction level, which are two measurements of performance of utilising SVWkS. The promising results confirm the feasibility of SVWkS in helping engineers to find needed lesson-learned knowledge and reuse-related knowledge.
Journal: International Journal of Production Research
Pages: 2524-2541
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.975861
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975861
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Template-Type: ReDIF-Article 1.0
Author-Name: Chih-Hsuan Wang
Author-X-Name-First: Chih-Hsuan
Author-X-Name-Last: Wang
Title: A market-oriented approach to accomplish product positioning and product recommendation for smart phones and wearable devices
Abstract: 
 Recently, several global companies start to develop wearable devices like smart watches or smart glasses to avoid market saturation in smart phones, especially when wireless technology was rapidly shifting from the third to the fourth generation. In order to better understand the relative strengths and weaknesses of smart alternatives, this paper presents a market-oriented framework to accomplish product positioning and product recommendation. Initially, correspondence analysis is applied to elicit expert perceptions for conducting product positioning. Then, based on customer preferences, product recommendation can be accomplished in either an unsupervised way (purchase profiles for new products are unavailable) or a supervised manner (for justifying the validity of the proposed recommender system). In particular, analytical hierarchy process is employed to elicit customers’ choices among smart alternatives (treated as prior information or decision labels). In summary, managerial insights are provided as follows: (1) smart phones are good at providing a platform for satisfying home entertainment, (2) smart watches are perceived as auxiliary carriers to accomplish health care and safety monitoring and (3) smart glasses are promising to fulfill industrial operation, logistics service and homeland security.
Journal: International Journal of Production Research
Pages: 2542-2553
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.991046
File-URL: http://hdl.handle.net/10.1080/00207543.2014.991046
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Template-Type: ReDIF-Article 1.0
Author-Name: Princely Ifinedo
Author-X-Name-First: Princely
Author-X-Name-Last: Ifinedo
Author-Name: Dag Håkon Olsen
Author-X-Name-First: Dag Håkon
Author-X-Name-Last: Olsen
Title: An Empirical Research on the Impacts of organisational decisions’ locus, tasks structure rules, knowledge, and IT function’s value on ERP system success
Abstract: 
 This research examined the impacts of organisational decisions’ locus, tasks structure, rules and procedures, organisational actors’ information technology (IT) skills/knowledge and IT department’s or function’s value perceptions on enterprise resource planning (ERP) system success. While such antecedent factors matter in the discourse, research on their impacts on ERP success is rare. To increase understanding in the area, we proposed a research model and developed pertinent hypotheses that included the above-mentioned factors. Using a cross-sectional field survey, we collected data from 165 firms in three European countries. Data analysis was performed using the partial least squares (PLS) technique. Statistical support was found for 11 out of the 17 hypotheses formulated. Organisational design constructs, i.e. tasks structure, rules and procedures, in-house IT personnel skills/knowledge have impacts on ERP success, whereas the perceptions of IT function’s value and business employees’ IT skills/knowledge did not. Contributions and practical implications of the research are discussed.
Journal: International Journal of Production Research
Pages: 2554-2568
Issue: 8
Volume: 53
Year: 2015
Month: 4
X-DOI: 10.1080/00207543.2014.991047
File-URL: http://hdl.handle.net/10.1080/00207543.2014.991047
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Template-Type: ReDIF-Article 1.0
Author-Name: Peter E. Johansson
Author-X-Name-First: Peter E.
Author-X-Name-Last: Johansson
Author-Name: Christer Osterman
Author-X-Name-First: Christer
Author-X-Name-Last: Osterman
Title: Conceptions and operational use of value and waste in lean manufacturing – an interpretivist approach
Abstract: 
 In this article, we explore how the key concepts of lean manufacturing, value, value adding and waste are conceived and operationally used by Lean trainers in operational work processes. A comparative case study with a mixed method approach, using an explanatory sequential design, was conducted. This means that a set of quantitative data were collected, which was followed by the collection of qualitative data with the purpose of explaining and understanding the quantitative measures. An interpretivist approach is used as a framework, which implies a perspective on contemporary operations management paradigms, such as lean manufacturing, as a continuous construction of inter-subjective experiences. What becomes evident in the empirical findings is that there are both similarities and differences in the Lean trainers conceptions and use of value adding and waste. The similarities and differences can be explained by variations in two dimensions: (a) the character of the work process, which ranges between mechanical and craftsmanship, and (b) Lean trainers approach to key concepts, which ranges between being rule-based and reflective. By using a research design where the concepts of value adding and waste were used simultaneously, and adopting an interpretivist approach on lean manufacturing, we were able to reveal conditions that in other cases remain hidden.
Journal: International Journal of Production Research
Pages: 6903-6915
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1326642
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1326642
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammed Saad
Author-X-Name-First: Mohammed
Author-X-Name-Last: Saad
Author-Name: Vikas Kumar
Author-X-Name-First: Vikas
Author-X-Name-Last: Kumar
Author-Name: John Bradford
Author-X-Name-First: John
Author-X-Name-Last: Bradford
Title: An investigation into the development of the absorptive capacity of manufacturing SMEs
Abstract: 
 To sustain their competitive advantage in a highly competitive landscape, SMEs, in spite of their limited resources, need to effectively learn. The ability to access and successfully use knowledge is at the heart of absorptive capacity. The main purpose of this empirical study is to investigate the importance of awareness as an antecedent dimension of the concept of absorptive capacity of manufacturing SMEs from aerospace and advanced engineering industry in the UK. The study will also attempt to explore the impact of awareness on the other dimensions of absorptive capacity. Awareness is related to the importance, motivation and interest of learning and innovating. Our study, which focuses on internal processes adopts a mixed method approach and is based on the data collected from 43 SMEs. Our finding suggests that awareness as an antecedent dimension can play a vital role in helping SMEs to improve their knowledge-based resources through changes within their internal organisational and cognitive processes.
Journal: International Journal of Production Research
Pages: 6916-6931
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1327728
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1327728
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Template-Type: ReDIF-Article 1.0
Author-Name: Alice Rondini
Author-X-Name-First: Alice
Author-X-Name-Last: Rondini
Author-Name: Fabiana Tornese
Author-X-Name-First: Fabiana
Author-X-Name-Last: Tornese
Author-Name: Maria Grazia Gnoni
Author-X-Name-First: Maria Grazia
Author-X-Name-Last: Gnoni
Author-Name: Giuditta Pezzotta
Author-X-Name-First: Giuditta
Author-X-Name-Last: Pezzotta
Author-Name: Roberto Pinto
Author-X-Name-First: Roberto
Author-X-Name-Last: Pinto
Title: Hybrid simulation modelling as a supporting tool for sustainable product service systems: a critical analysis
Abstract: 
 Manufacturing companies are increasingly shifting their value proposition from a product-centric perspective to Product-Service-System (PSS). This evolution allows companies to improve the customisation of their offer and to contribute to reduce material flows and consumption, thus enhancing sustainability. However, when companies introduce PSS offers, they have to face higher complexity and dynamism, as customer behaviours, process requirements and sustainability assessment must be considered during the design and the development of the new solutions. In this paper, after the identification of the main PSS dynamic features, the authors argue that business process simulation (BPS) could represent an effective tool to cope with the dynamics and the complexity entailed in a sustainable PSS. This paper analyses and compares existing BPS approaches identifying the hybrid simulation (HS) modelling as a promising approach. In fact, according to the critical PSS features, HS allows grasping PSS features and integrating customer, company and environmental sustainability perspectives into the model, thus, supporting effective PSS design and assessment. These findings have been validated in a test case where a hybrid model (integrating Discrete Event Simulation with Agent-Based Modelling) has been compared against a pure DES model. The results highlight the advantages of the hybrid modelling approach with respect to DES in supporting the engineering of a sustainable, customer-oriented PSS provision process.
Journal: International Journal of Production Research
Pages: 6932-6945
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1330569
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330569
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Template-Type: ReDIF-Article 1.0
Author-Name: Rodrigo Pascual
Author-X-Name-First: Rodrigo
Author-X-Name-Last: Pascual
Author-Name: Matías Siña
Author-X-Name-First: Matías
Author-X-Name-Last: Siña
Author-Name: Gabriel Santelices
Author-X-Name-First: Gabriel
Author-X-Name-Last: Santelices
Author-Name: Milton Román
Author-X-Name-First: Milton
Author-X-Name-Last: Román
Author-Name: Enrique López Droguett
Author-X-Name-First: Enrique
Author-X-Name-Last: López Droguett
Title: Optimal channel coordination in use-based product-service system contracts
Abstract: 
 Nowadays, service economy efficiencies are key to keep competitiveness and increase market advantages. The development of Product-Service Systems (PSS) can be an interesting strategy as they seek to improve the business performance of all the participants in the value chain. This paper proposes a novel reliability-based reward scheme for use-oriented PSS contracts. In a PSS instead of paying for the product, the client pays a fee for its performance. The contribution of this work to the existing literature is to provide a quantitative tool for the development of a use-oriented PSS contract based on non-repairable component reliability and risk sharing. It can be extended to other performance metrics such as availability and reliability. A well designed PSS achieves a mutual growth agreement for the client and the supplier if it aligns their interests through channel coordination. This is achieved by balancing the improvement in the expected cost and profit for the client and the supplier, respectively. The improvement is measured with respect to a baseline scenario where no PSS contract exists. The methodology is tested using a case study that analyses mining haul truck tires. The results show a significant overall improvement in the main key performance indicators and environmental impact of the value chain.
Journal: International Journal of Production Research
Pages: 6946-6956
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1332793
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1332793
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Template-Type: ReDIF-Article 1.0
Author-Name: Martin Baumers
Author-X-Name-First: Martin
Author-X-Name-Last: Baumers
Author-Name: Luca Beltrametti
Author-X-Name-First: Luca
Author-X-Name-Last: Beltrametti
Author-Name: Angelo Gasparre
Author-X-Name-First: Angelo
Author-X-Name-Last: Gasparre
Author-Name: Richard Hague
Author-X-Name-First: Richard
Author-X-Name-Last: Hague
Title: Informing additive manufacturing technology adoption: total cost and the impact of capacity utilisation
Abstract: 
 Informing Additive Manufacturing (AM) technology adoption decisions, this paper investigates the relationship between build volume capacity utilisation and efficient technology operation in an inter-process comparison of the costs of manufacturing a complex component used in the packaging industry. Confronting the reported costs of a conventional machining and welding pathway with an estimator of the costs incurred through an AM route utilising Direct Metal Laser Sintering (DMLS), we weave together four aspects: optimised capacity utilisation, ancillary process steps, the effect of build failure and design adaptation. Recognising that AM users can fill unused machine capacity with other, potentially unrelated, geometries, we posit a characteristic of ‘fungible’ build capacity. This aspect is integrated in the cost estimation framework through computational build volume packing, drawing on a basket of sample geometries. We show that the unit cost in mixed builds at full capacity is lower than in builds limited to a single type of geometry; in our study, this results in a mean unit cost overstatement of 157%. The estimated manufacturing cost savings from AM adoption range from 36 to 46%. Additionally, we indicate that operating cost savings resulting from design adaptation are likely to far outweigh the manufacturing cost advantage.
Journal: International Journal of Production Research
Pages: 6957-6970
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1334978
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1334978
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Template-Type: ReDIF-Article 1.0
Author-Name: Min Zhang
Author-X-Name-First: Min
Author-X-Name-Last: Zhang
Author-Name: Yinan Qi
Author-X-Name-First: Yinan
Author-X-Name-Last: Qi
Author-Name: Hangfei Guo
Author-X-Name-First: Hangfei
Author-X-Name-Last: Guo
Title: Impacts of intellectual capital on process innovation and mass customisation capability: direct and mediating effects
Abstract: 
 This paper presents an empirical survey study. We propose a model to examine the individual and joint effects of the three components of intellectual capital (i.e. human, social and structural capital) on process innovation and mass customisation (MC) capability. The hypotheses are empirically tested using structural equation modelling and data collected from 645 manufacturing plants in 10 countries/regions. The results show that human and social capital are positively associated with structural capital. Human capital directly improves both process innovation and MC capability. The direct effect of social capital on MC capability and that of structural capital on process innovation is positive and significant. Moreover, process innovation is positively associated with MC capability. In addition, we find that structural capital mediates human and social capital’s effects on process innovation, and process innovation mediates human and structural capital’s effects on MC capability. This study contributes to the literature by providing insights into how human, social and structural capital jointly improve process innovation and MC capability, as well as how the different types of knowledge residing in a manufacturer affect MC capability development.
Journal: International Journal of Production Research
Pages: 6971-6983
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1343505
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1343505
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Template-Type: ReDIF-Article 1.0
Author-Name: Dorota Stadnicka
Author-X-Name-First: Dorota
Author-X-Name-Last: Stadnicka
Author-Name: R.M. Chandima Ratnayake
Author-X-Name-First: R.M. Chandima
Author-X-Name-Last: Ratnayake
Title: Enhancing performance in service organisations: a case study based on value stream analysis in the telecommunications industry
Abstract: 
 Performance-enhancing efforts in the manufacturing industry have centred on ‘lean’ principles and philosophies since the early 1970s. Lean principles, philosophies, tools and methods have also been significantly deployed to enhance performance in service processes within the manufacturing industry, as well as the process industry (e.g. inspection, maintenance and modification-related). It has been observed that when the main business is mostly centred on service-providing processes, significantly less effort is put into exploiting the use of lean approaches to enhance performance. Therefore, it is vital to investigate the potential of ‘lean’ concepts’ implementation in a service-providing organisation. This manuscript is based on the value stream mapping and the value stream analysis (VSA) performed in a Polish telecommunication-industry-related service-providing company. A plain old telephone services-based case study is presented. The service-providing process is analysed in order to identify the current existing drawbacks and to propose improvements to enhance performance. Based on the current state value stream map and the VSA results, a future state value stream map was developed. Then, process efficiency was calculated in order to assess the level of performance improvement.
Journal: International Journal of Production Research
Pages: 6984-6999
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1346318
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346318
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Template-Type: ReDIF-Article 1.0
Author-Name: Milia Habib
Author-X-Name-First: Milia
Author-X-Name-Last: Habib
Author-Name: Farouk Yalaoui
Author-X-Name-First: Farouk
Author-X-Name-Last: Yalaoui
Author-Name: Hicham Chehade
Author-X-Name-First: Hicham
Author-X-Name-Last: Chehade
Author-Name: Iman Jarkass
Author-X-Name-First: Iman
Author-X-Name-Last: Jarkass
Author-Name: Nazir Chebbo
Author-X-Name-First: Nazir
Author-X-Name-Last: Chebbo
Title: Multi-objective design optimisation of repairable -out-of- subsystems in series with redundant dependency
Abstract: 
 Several researches have been investigated on Multi-Objective Redundancy Allocation Problems (MORAPs), but none of them have considered the redundant dependency at the design stage. This latter which is a special kind of failure dependency can affect significantly the system performance. Due to this fact, this paper deals with the multi-objective system design optimisation with dependent components by focusing on two objectives: maximisation of system availability and minimisation of system cost with components choice and weight constraints. A system consisting of many k-out-of-n repairable subsystems connected in series is considered. The components of a subsystem are supposed to be identical and may be dependent. They are selected from a set of available component types. In addition to the redundancy level and the number of repair teams allocated to each subsystem, the choice of components type and the dependency level are also considered as decision variables. Since the described problem is NP hard, we propose three multi-objective meta-heuristic algorithms based on Non-dominated Sorting Genetic Algorithm (NSGA II) and Strength Pareto Evolutionary Algorithm (SPEA II) with different constraints handling. An exact method is also applied. To analyse their performances, numerical applications are provided and comparisons based on different well-known metrics are presented.
Journal: International Journal of Production Research
Pages: 7000-7021
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1346319
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346319
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Template-Type: ReDIF-Article 1.0
Author-Name: Mesbahuddin Chowdhury
Author-X-Name-First: Mesbahuddin
Author-X-Name-Last: Chowdhury
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Author-Name: Daniel Prajogo
Author-X-Name-First: Daniel
Author-X-Name-Last: Prajogo
Title: The influence of socialisation and absorptive capacity on buyer’s innovation performance
Abstract: 
 In contrast to prior literature, we hypothesise that socialisation with suppliers plays a key role in the success of buyer’s innovation programmes. Using the theoretical lens of social capital theory and knowledge-based view of a firm; we propose a framework of antecedents and consequences of socialisation. We use data from a large sample of firms in Australia to test our framework. We also corroborate our results with a small sample of qualitative case studies that were carried out in conjunction with the large-scale empirical study. Taken together, the results supported the claim of the importance of socialisation as well as absorptive capacity in influencing innovation performance of buyers. The results suggest that managers ought to consider socialisation as a mechanism to enhance collaborative competence which in turn helps innovation performance via tapping the potential of absorptive capacity of knowledge.
Journal: International Journal of Production Research
Pages: 7022-7039
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1346321
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346321
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Template-Type: ReDIF-Article 1.0
Author-Name: Rabah Ammour
Author-X-Name-First: Rabah
Author-X-Name-Last: Ammour
Author-Name: Edouard Leclercq
Author-X-Name-First: Edouard
Author-X-Name-Last: Leclercq
Author-Name: Eric Sanlaville
Author-X-Name-First: Eric
Author-X-Name-Last: Sanlaville
Author-Name: Dimitri Lefebvre
Author-X-Name-First: Dimitri
Author-X-Name-Last: Lefebvre
Title: State estimation of discrete event systems for RUL prediction issue
Abstract: 
 This paper concerns Remaining Useful Life (RUL) estimation of discrete event systems. For that purpose, physics-based models with partially observed stochastic Petri nets are used to represent the system and its sensors. The advantage of the proposed modelling approach is to provide a realistic representation of the system, including the interaction between the normal behaviours and the failure processes. From the proposed modelling and collected measurements, timed trajectories, which are consistent with the observations, are obtained. Based on the event dates, our approach consists in evaluating the probabilities of the consistent behaviours using probabilistic models. State estimation is obtained as a consequence. The most probable future degradations, from the current state, are then considered and a method for fault prognosis is presented. Finally, the prognosis result is used to estimate the RUL as a time interval. A case study is proposed to show the applicability of the proposed method.
Journal: International Journal of Production Research
Pages: 7040-7057
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1346835
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346835
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Template-Type: ReDIF-Article 1.0
Author-Name: Shuguang He
Author-X-Name-First: Shuguang
Author-X-Name-Last: He
Author-Name: Zhaomin Zhang
Author-X-Name-First: Zhaomin
Author-X-Name-Last: Zhang
Author-Name: Guohua Zhang
Author-X-Name-First: Guohua
Author-X-Name-Last: Zhang
Author-Name: Zhen He
Author-X-Name-First: Zhen
Author-X-Name-Last: He
Title: Two-dimensional base warranty design based on a new demand function considering heterogeneous usage rate
Abstract: 
 Warranties are prevalent in the market. The manufacturer of products sold with warranties often faces a problem of balancing a trade-off between warranty cost and boosted demand by warranties when designing the warranties. For a two-dimensional base warranty with both age limit and usage limit, the heterogeneous usage rate of customers not only has an effect on warranty cost but also differentiates customers’ perceptions on warranty period. For example, the high-usage customers are more concerned about the usage limit of the warranty period, while the low-usage customers are more preferred to a longer age limit. This paper defines an attractiveness index based on the available warranty region to describe the extent of attractiveness of a two-dimensional warranty period to customers with heterogeneous usage rate. Moreover, a demand function based on the attractiveness index is proposed to describe the boosted demand of extending the warranty period. From the perspective of the manufacturer, the optimal two-dimensional base warranty period is designed by maximising the expected profit considering the trade-off. Both numerical examples and a case study are presented to illustrate the application of the proposed method.
Journal: International Journal of Production Research
Pages: 7058-7072
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1346837
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346837
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Template-Type: ReDIF-Article 1.0
Author-Name: Eleftherios Andreadis
Author-X-Name-First: Eleftherios
Author-X-Name-Last: Andreadis
Author-Name: Jose Arturo Garza-Reyes
Author-X-Name-First: Jose Arturo
Author-X-Name-Last: Garza-Reyes
Author-Name: Vikas Kumar
Author-X-Name-First: Vikas
Author-X-Name-Last: Kumar
Title: Towards a conceptual framework for value stream mapping (VSM) implementation: an investigation of managerial factors
Abstract: 
 Despite the relatively extensive literature on VSM, limited reflection has been reported regarding how managerial proceedings actually put VSM into practice. This research therefore investigates these issues as part of the overall lean philosophy and in correlation with some of its main tools. Five hypotheses and three complementary research questions were formulated and tested using a combination of descriptive statistics and Pearson correlation, 2-Sample proportion, one-way ANOVA, 1-Sample t-tests and Tukey-Pairwise comparison tests. Data were collected through a survey questionnaire responded by 168 manufacturing organisations worldwide. The results establish, among other ‘soft’ aspects; (1) whether organisations that have adopted lean have also employed VSM as an essential tool to identify waste, (2) the position that VSM normally takes in the time frame hierarchy of lean implementation, (3) the complexity of VSM implementation in terms of easiness and time taken for training when compared to other lean tools such as TPM, JIT and Jidoka, and the (4) critical success factors and barriers for the VSM implementation. A conceptual framework to support the implementation and management of VSM is developed through the unification of the results obtained. This study supports the very limited empirical research on the implementation and management of VSM.
Journal: International Journal of Production Research
Pages: 7073-7095
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1347302
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1347302
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Template-Type: ReDIF-Article 1.0
Author-Name: Chia-Yu Hsu
Author-X-Name-First: Chia-Yu
Author-X-Name-Last: Hsu
Author-Name: Sirirat Sae Lim
Author-X-Name-First: Sirirat Sae
Author-X-Name-Last: Lim
Author-Name: Chin-Sheng Yang
Author-X-Name-First: Chin-Sheng
Author-X-Name-Last: Yang
Title: Data mining for enhanced driving effectiveness: an eco-driving behaviour analysis model for better driving decisions
Abstract: 
 With the growing demand for energy efficient vehicles, automobile companies are constantly searching for better ways to study their customers’ driving behaviour for effective new product design and development. One emerging driving behaviour among modern, eco-friendly drivers is the utilising of advanced vehicle technology for smarter, safer and more fuel-efficient driving. While many eco-driving studies focus on minimising fuel consumption, little attention is paid to how the behaviour of an individual driver and the type of vehicle used impact driving effectiveness. This study addresses this gap by proposing a novel overall drive effectiveness index that uses data mining for better driving decisions. Utilising data mining techniques, the index examines the impact of driving behaviour on driving effectiveness. A novel fuel consumption prediction model based on vehicle speed, engine speed and engine load was constructed. This decision-making support model accurately predicts real-time fuel consumption based on different driving behaviours, and hence, the driving effectiveness. Both the proposed index and fuel consumption model can be used to support decision-making in new product design and development.
Journal: International Journal of Production Research
Pages: 7096-7109
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1349946
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1349946
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Template-Type: ReDIF-Article 1.0
Author-Name: Rayan Saleem M. Omar
Author-X-Name-First: Rayan Saleem M.
Author-X-Name-Last: Omar
Author-Name: Uday Venkatadri
Author-X-Name-First: Uday
Author-X-Name-Last: Venkatadri
Author-Name: Claver Diallo
Author-X-Name-First: Claver
Author-X-Name-Last: Diallo
Author-Name: Sakher Mrishih
Author-X-Name-First: Sakher
Author-X-Name-Last: Mrishih
Title: A data-driven approach to multi-product production network planning
Abstract: 
 The clearing function models the non-linear relationship between work-in-process and throughput and has been proposed for production planning in environments with queuing (congestion) effects. One approach in multi-product, multi-stage environments has been to model the clearing function at the bottleneck machine only. However, since the bottleneck shifts as the product release mix changes, this approach has its limitations. The other approach is the Alternative Clearing Function formulation, where the clearing function is first estimated at the resource level using piecewise linear regression from simulation experiments, and then embedded into a linear programme. This paper develops an alternative to the Allocated Clearing Function formulation, wherein system throughput is estimated at discrete work-in-process points. A mixed integer programming formulation is then presented to use these throughput estimates for discrete release choices. The strength of the formulation is illustrated with a numerical example and the new approach is compared with the ACF.
Journal: International Journal of Production Research
Pages: 7110-7134
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1349952
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1349952
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohamed Larbi Rebaiaia
Author-X-Name-First: Mohamed Larbi
Author-X-Name-Last: Rebaiaia
Author-Name: Daoud Ait-kadi
Author-X-Name-First: Daoud
Author-X-Name-Last: Ait-kadi
Author-Name: Afshin Jamshidi
Author-X-Name-First: Afshin
Author-X-Name-Last: Jamshidi
Title: Periodic replacement strategies: optimality conditions and numerical performance comparisons
Abstract: 
 In maintenance engineering, age replacement policy (ARP) and block replacement policy (BRP) are the most popular basic strategies. They have been intensively studied and compared using different performance measures. Several of these comparisons are stochastics on the basis of the renewal theory, and a few of them are of economic benefit. This paper presents a comparative study for analysing ARP and BRP models using the expected costs function as the principal criterion. To provide this comparison, we propose a numerical approach allowing to combine cost/distribution for the determination of the optimal strategy. For that, we resume the main analytical results and prove that a finite solution exists if the failure rate increases. Results clearly show that both strategies are very close, which intuitively confirm the statement of Barlow and Proschan’s theorem. Based on the computational results, we show that the ultimate decision to select the best strategy is conditioned by the choice of the distribution function, the value of its parameters and that the periodic replacement unit cost must be much lower than the replacement unit cost at failure.
Journal: International Journal of Production Research
Pages: 7135-7152
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1349953
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1349953
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Template-Type: ReDIF-Article 1.0
Author-Name: Saeed Z. Gavidel
Author-X-Name-First: Saeed Z.
Author-X-Name-Last: Gavidel
Author-Name: Jeremy L. Rickli
Author-X-Name-First: Jeremy L.
Author-X-Name-Last: Rickli
Title: Quality assessment of used-products under uncertain age and usage conditions
Abstract: 
 Quality of a used-product is often highly uncertain, impacts pricing decisions, and is influenced by many factors like age and usage. However, analysis of usage and its uncertain nature is not well understood. In this paper, joint effects of age and usage on quality of used/end-of-life products are analysed. To conduct this research, Product State Transformation Diagram is proposed and used to analyse quality of used-products under uncertain age and usage conditions. Subsequently, governing multivariate stochastic partial differential equation is derived and paired with operational conditions to develop Quality Degradation Model (QDM). Then, QDM is numerically analysed and compared with common age-based model. Results indicate that age-based models overestimate quality. Using one-factor-at-time approach, sensitivity of QDM to its parameters and inputs is analysed. In a real-life case study, QDM is applied to evaluate prices of used-cars. To validate QDM and to generate insights towards its accuracy, a pool of popular statistical and machine learning models are trained and compared with QDM. Results show that performance of QDM is comparable to known models like SVM, LR, ANN-MLP for this application.
Journal: International Journal of Production Research
Pages: 7153-7167
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1349954
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1349954
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Template-Type: ReDIF-Article 1.0
Author-Name: Rodney McAdam
Author-X-Name-First: Rodney
Author-X-Name-Last: McAdam
Author-Name: Umit Bititci
Author-X-Name-First: Umit
Author-X-Name-Last: Bititci
Author-Name: Brendan Galbraith
Author-X-Name-First: Brendan
Author-X-Name-Last: Galbraith
Title: Technology alignment and business strategy: a performance measurement and Dynamic Capability perspective
Abstract: 
 Rapid changes in market structures and technology lead to misalignment between strategy and operations. Whist this phenomenon is most prevalent in technology-based manufacturing industries, utility organisations (e.g. electricity and telecoms) provide a useful context to explore the Performance measurement (PM) and technology alignment challenges from a Dynamic Capabilities Theory perspective where there is a progressive shift towards deregulated markets. The aim of this paper is twofold: first, to explore the role of Dynamic Capabilities Theory and PM approaches in improving the alignment between business strategy and technology strategy (Level 1 alignment); second, to explore the role of Dynamic Capabilities Theory and PM approaches in aligning technology strategy with operational technology routines and practices (Level 2 alignment). In the absence of overarching theory, an inductive approach draws upon Dynamic Capabilities theory. Four longitudinal case studies are used leading to the development of a conceptual framework and propositions for multilevel technology alignment. Data from 38 interviews and 8 separate focus groups, documentation and participant observations (over a three-year period) are used. The theory-building process shows the need to identify and develop PM-based technology alignment Dynamic Capabilities (PM-DCs) which help in improving and maintaining alignment between business strategy and technology strategy (Level 1 alignment) and between technology strategy and technology practices (Level 2 alignment). This approach requires critically reflective action-learning approaches to identify and nurture these PM-DCs.
Journal: International Journal of Production Research
Pages: 7168-7186
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1351633
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1351633
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Template-Type: ReDIF-Article 1.0
Author-Name: Chao Zhang
Author-X-Name-First: Chao
Author-X-Name-Last: Zhang
Author-Name: Guanghui Zhou
Author-X-Name-First: Guanghui
Author-X-Name-Last: Zhou
Author-Name: Qi Lu
Author-X-Name-First: Qi
Author-X-Name-Last: Lu
Author-Name: Fengtian Chang
Author-X-Name-First: Fengtian
Author-X-Name-Last: Chang
Title: Graph-based knowledge reuse for supporting knowledge-driven decision-making in new product development
Abstract: 
 Pre-existing knowledge buried in manufacturing enterprises can be reused to help decision-makers develop good judgements to make decisions about the problems in new product development, which in turn speeds up and improves the quality of product innovation. This paper presents a graph-based approach to knowledge reuse for supporting knowledge-driven decision-making in new product development. The paper first illustrates the iterative process of knowledge-driven decision-making in new product development. Then, a novel framework is proposed to facilitate this process, where knowledge maps and knowledge navigation are involved. Here, OWL ontologies are employed to construct knowledge maps, which appropriately capture and organise knowledge resources generated at various stages of product lifecycle; the Personalised PageRank algorithm is used to perform knowledge navigation, which finds the most relevant knowledge in knowledge maps for a given problem in new product development. Finally, the feasibility and effectiveness of the proposed approach are demonstrated through a case study and two performance evaluation experiments.
Journal: International Journal of Production Research
Pages: 7187-7203
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1351643
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1351643
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Template-Type: ReDIF-Article 1.0
Author-Name: Abdourahim Sylla
Author-X-Name-First: Abdourahim
Author-X-Name-Last: Sylla
Author-Name: Elise Vareilles
Author-X-Name-First: Elise
Author-X-Name-Last: Vareilles
Author-Name: Thierry Coudert
Author-X-Name-First: Thierry
Author-X-Name-Last: Coudert
Author-Name: Konstantinos Kirytopoulos
Author-X-Name-First: Konstantinos
Author-X-Name-Last: Kirytopoulos
Author-Name: Michel Aldanondo
Author-X-Name-First: Michel
Author-X-Name-Last: Aldanondo
Author-Name: Laurent Geneste
Author-X-Name-First: Laurent
Author-X-Name-Last: Geneste
Title: Readiness, feasibility and confidence: how to help bidders to better develop and assess their offers
Abstract: 
 In a bidding process, the bidder must define and evaluate potential offers in order to propose the most suitable one to the potential customer. Proposing attractive but also realistic offers to various potential customers is a key factor for the bidder to stay competitive. In order to achieve this, the bidder needs to be very sure about the technical specifications and the constructability of the proposal. However, performing a detailed design is resource and time-consuming. This article proposes the foundation of a new framework which can help bidders to define the right offer: (i) in the context of a non-routine design process, while avoiding a detailed design and (ii) taking into account two new indicators that reflect the bidder’s confidence that they can meet the commitments once the offer is accepted. The first indicator (OCS) characterises the Overall Confidence in the technical System, while the second one (OCP) gives the Overall Confidence in the delivery Process. Both OCS and OCP are based firstly on two factual objective indicators, Technology Readiness Level (TRL) for OCS and Activity Feasibility Level (AFL) for OCP, and secondly on two human-based subjective indicators, Confidence In System (CIS) for the OCS and Confidence In Process for the OCP. An illustrative application shows how this framework can really help bidders define an offer, while avoiding detailed design and enable them to evaluate the confidence level in each potential offer.
Journal: International Journal of Production Research
Pages: 7204-7222
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1353156
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1353156
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Template-Type: ReDIF-Article 1.0
Author-Name: Chao-chao Liu
Author-X-Name-First: Chao-chao
Author-X-Name-Last: Liu
Author-Name: Zhan-wen Niu
Author-X-Name-First: Zhan-wen
Author-X-Name-Last: Niu
Author-Name: Pei-Chann Chang
Author-X-Name-First: Pei-Chann
Author-X-Name-Last: Chang
Author-Name: Bo Zhang
Author-X-Name-First: Bo
Author-X-Name-Last: Zhang
Title: Assessment approach to stage of lean transformation cycle based on fuzzy nearness degree and TOPSIS
Abstract: 
 This paper presents an assessment method to measure the lean transformation (LT) stage of an LT enterprise. Although there are many assessment tools to measure the various aspects of lean practices in enterprises, there is none to measure the stage of LT using the enterprise transformation characteristics from enterprise level. In this paper, the characteristic metrics and characteristic model of LT cycle were extracted from the basic capacity, process power and transformation results. Then, an assessment approach based on fuzzy nearness degree and TOPSIS is proposed to determine the stage of LT. Finally, an example is shown to highlight the procedure of the proposed method. This paper shows that the proposed model is very well suited as an assessment tool for enterprises in the manufacturing industry and other industries to evaluate the LT stage.
Journal: International Journal of Production Research
Pages: 7223-7235
Issue: 23
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1355124
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355124
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcus Brandenburg
Author-X-Name-First: Marcus
Author-X-Name-Last: Brandenburg
Title: Low carbon supply chain configuration for a new product – a goal programming approach
Abstract: 
 Green supply chain management and product innovation both have become sources of competitive advantage for companies from different industries. However, research on the configuration of green supply chains for new products represents a comparably new trend. In this paper, a goal programming approach is suggested to optimise the supply chain (SC) configuration for a new consumer product under consideration of economic and environmental criteria. The approach is illustrated by the case example of a fast moving consumer goods manufacturer. In this context, trade-offs between the ecologic factor of carbon emission, on the one hand, and financial value creation and customer service level on the other hand, are assessed in the deterministic analyses. The influence of long-term demand uncertainties is modelled in a scenario approach. It is observed that decentralised SC configurations enable carbon emission reduction without deteriorating the economic SC performance. Furthermore, it is detected that a focused economic optimisation strongly amplifies negative environmental impacts of demand uncertainties.
Journal: International Journal of Production Research
Pages: 6588-6610
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1005761
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005761
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Template-Type: ReDIF-Article 1.0
Author-Name: Paweł Sitek
Author-X-Name-First: Paweł
Author-X-Name-Last: Sitek
Author-Name: Jarosław Wikarek
Author-X-Name-First: Jarosław
Author-X-Name-Last: Wikarek
Title: A hybrid framework for the modelling and optimisation of decision problems in sustainable supply chain management
Abstract: 
 This paper describes the hybrid framework for the modelling and optimisation of decision problems in sustainable supply chain management. The constraint-based environments used so far to model and solve the decision-making problems have turned out to be ineffective in cases where a number of interbound variables are added up in multiple constraints. The hybrid approach proposed here combines the strengths of mathematical programming and constraint programming. This approach allows a significant reduction in the search time necessary to find the optimal solution, and facilitates solving larger problems. Two software packages, LINGO and ECLiPSe, were employed to solve optimisation problems. The hybrid method appears to be not only as good as either of its components used independently, but in most cases it is much more effective. Its advantages are illustrated with simplified models of cost optimisation, for which optimal solutions are found ten times faster. The application of the proposed framework has contributed to more than 20 fivefold reduction in the size of the combinatorial problem.
Journal: International Journal of Production Research
Pages: 6611-6628
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1005762
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005762
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Template-Type: ReDIF-Article 1.0
Author-Name: Martin Riegler
Author-X-Name-First: Martin
Author-X-Name-Last: Riegler
Author-Name: Nicolas André
Author-X-Name-First: Nicolas
Author-X-Name-Last: André
Author-Name: Manfred Gronalt
Author-X-Name-First: Manfred
Author-X-Name-Last: Gronalt
Author-Name: Timothy M. Young
Author-X-Name-First: Timothy M.
Author-X-Name-Last: Young
Title: Real-time dynamic simulation of continuous bulk material flow to improve the statistical modelling of final product strength properties
Abstract: 
 In regression analyses, correlations between independent variables (e.g. process variables) and dependent variables (e.g. product quality) are of major interest. However, only statistically significant correlations ensure a reliable interpretation of how process variables affect product qualities. In this respect, accurate time alignment of independent variables is crucial to obtain regression models with acceptable validation that are influenced by temporal phenomena (e.g. industrial processes) only. In this study, the commonly used static form of time alignment, where only the distances between consecutive process parameters and the average production speed are considered, is compared to a newly developed dynamic calculation of time lags. The dynamic calculation of time lags was achieved by modelling the continuous bulk material flow. The two different methods of calculation were then applied on an industrial production of particleboards to predict final board strength properties. Results of regression models showed that the use of dynamically calculated time lags improved the predictability of the internal bond strength of boards by 67% compared to statically calculated time lags. Consequently, final product strength properties could be predicted more accurately, which should lead to lower costs of rejects and a higher efficiency of material inputs.
Journal: International Journal of Production Research
Pages: 6629-6636
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1055844
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055844
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Template-Type: ReDIF-Article 1.0
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Title: Decision support models for production ramp-up: a systematic literature review
Abstract: 
 Production ramp-up is a critical step in the life cycle of a new product, and efficiently managing ramp-ups is a key to business success and market leadership. To support the planning of ramp-ups in practice, researchers have developed decision support models in the past that help to solve problems that arise during the ramp-up phase, such as lot sizing, the assignment of workers to workplaces or the determination of the capacity of the production equipment. Decision support models for production ramp-up typically consider the specific characteristics of this phase, such as uncertainty, growth in demand, worker learning or imperfect production processes. The aim of this paper is to provide a comprehensive overview of decision support models for production ramp-up and to identify areas where more research is needed. First, the paper develops a conceptual framework of production ramp-up by categorising typical planning problems and process characteristics of the ramp-up phase. Secondly, a systematic literature review with a focus on mathematical planning models for the ramp-up phase is conducted. The analysis shows that various decision support models that help to realise an efficient production ramp-up exist, but that there are still many opportunities for future research in this area.
Journal: International Journal of Production Research
Pages: 6637-6651
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1064185
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1064185
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Template-Type: ReDIF-Article 1.0
Author-Name: Arijit Bhattacharya
Author-X-Name-First: Arijit
Author-X-Name-Last: Bhattacharya
Author-Name: Prasanta Kumar Dey
Author-X-Name-First: Prasanta Kumar
Author-X-Name-Last: Dey
Author-Name: William Ho
Author-X-Name-First: William
Author-X-Name-Last: Ho
Title: Green manufacturing supply chain design and operations decision support
Abstract: 
 This special issue of International Journal of Production Research provides a platform for sharing the knowledge base, recent research outputs and a review of recent developments highlighting the critical aspects of green manufacturing supply chain design and operations decision support. The special issue includes 15 contributions presenting new and significant research in the relevant area. Contributions mainly present either a novel green/sustainable manufacturing supply chain design and operations decision support approach applied to a problem, or a state-of-the-art method on green/sustainable factors in supply chain design and operations. The article delineates an overview of the contributions and their significance, and an introspection on the ‘green’ factors involved.
Journal: International Journal of Production Research
Pages: 6339-6343
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2015.1065021
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1065021
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Template-Type: ReDIF-Article 1.0
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Devika Kannan
Author-X-Name-First: Devika
Author-X-Name-Last: Kannan
Author-Name: Madan Shankar
Author-X-Name-First: Madan
Author-X-Name-Last: Shankar
Title: Evaluation of green manufacturing practices using a hybrid MCDM model combining DANP with PROMETHEE
Abstract: 
 The advent of increasing industrialisation and globalisation has put pressure on Indian enterprises to increase the integration of environmentally conscious manufacturing practices into their operations. Numerous studies have explored this strategy but there are significant gaps in the existing literature, particularly in environmental practices specific to India. In this connection, there is a need to explore green manufacturing practices (GMP) in an Indian context. The purpose of this article is to select the best GMP based on dimensions and relevant criteria with the assistance of a hybrid multi-criteria decision-making model combining DEMATEL based on ANP (DANP) with Preference Ranking Organisation METHod for Enrichment Evaluations. A methodological framework is proposed to evaluate GMP and the same is validated within a particular single case industry situated in the southern part of India, who is the leading manufacturer of rubber tyres and tubes. By virtue of these findings, industries can identify the best GM practice to adopt in order to increase the chances of profit and performance throughout their systems. This study concludes by successfully identifying the best GM practice for this case industry, and it provides some important managerial implications. This research explores some future trends to make the study more reliable in changing real life scenarios.
Journal: International Journal of Production Research
Pages: 6344-6371
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.898865
File-URL: http://hdl.handle.net/10.1080/00207543.2014.898865
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Template-Type: ReDIF-Article 1.0
Author-Name: V. Kumar
Author-X-Name-First: V.
Author-X-Name-Last: Kumar
Author-Name: D. Holt
Author-X-Name-First: D.
Author-X-Name-Last: Holt
Author-Name: A. Ghobadian
Author-X-Name-First: A.
Author-X-Name-Last: Ghobadian
Author-Name: J.A. Garza-Reyes
Author-X-Name-First: J.A.
Author-X-Name-Last: Garza-Reyes
Title: Developing green supply chain management taxonomy-based decision support system
Abstract: 
 The aim of this paper is to develop a comprehensive taxonomy of green supply chain management (GSCM) practices and develop a structural equation modelling-driven decision support system following GSCM taxonomy for managers to provide better understanding of the complex relationship between the external and internal factors and GSCM operational practices. Typology and/or taxonomy play a key role in the development of social science theories. The current taxonomies focus on a single or limited component of the supply chain. Furthermore, they have not been tested using different sample compositions and contexts, yet replication is a prerequisite for developing robust concepts and theories. In this paper, we empirically replicate one such taxonomy extending the original study by (a) developing broad (containing the key components of supply chain) taxonomy; (b) broadening the sample by including a wider range of sectors and organisational size; and (c) broadening the geographic scope of the previous studies. Moreover, we include both objective measures and subjective attitudinal measurements. We use a robust two-stage cluster analysis to develop our GSCM taxonomy. The main finding validates the taxonomy previously proposed and identifies size, attitude and level of environmental risk and impact as key mediators between internal drivers, external drivers and GSCM operational practices.
Journal: International Journal of Production Research
Pages: 6372-6389
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.917215
File-URL: http://hdl.handle.net/10.1080/00207543.2014.917215
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Template-Type: ReDIF-Article 1.0
Author-Name: Wantao Yu
Author-X-Name-First: Wantao
Author-X-Name-Last: Yu
Author-Name: Ramakrishnan Ramanathan
Author-X-Name-First: Ramakrishnan
Author-X-Name-Last: Ramanathan
Title: An empirical examination of stakeholder pressures, green operations practices and environmental performance
Abstract: 
 This study explores two key attributes constituting green operations practices (i.e. internal green management and green product/process design) and examines the links of adopting green operations practices with its antecedent factors (stakeholder pressures) and consequent performance outcomes (environmental performance). Data collected from 167 manufacturing firms in the UK were analysed using structural equation modelling. The results reveal that stakeholder pressures have a significant positive effect on internal green management, and that internal green management significantly affects green product/process design. The two attributes of green operations practices are significantly and positively related to environmental performance. More specifically, we find that internal green management fully mediates the relationship between stakeholder pressures and green product/process design and the relationship between stakeholder pressures and environmental performance.
Journal: International Journal of Production Research
Pages: 6390-6407
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.931608
File-URL: http://hdl.handle.net/10.1080/00207543.2014.931608
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Template-Type: ReDIF-Article 1.0
Author-Name: Xu Chen
Author-X-Name-First: Xu
Author-X-Name-Last: Chen
Author-Name: Gang Hao
Author-X-Name-First: Gang
Author-X-Name-Last: Hao
Title: Sustainable pricing and production policies for two competing firms with carbon emissions tax
Abstract: 
 This paper studies the incentive for a firm’s sustainable pricing and production policies with carbon dioxide emissions tax policy. We consider two competing firms who have different operation efficiencies and produce a same product to the end-users. Based on game theory models, we derive the competing firms’ optimal pricing and production policies, and show that the high-efficiency firm will set a lower retail price than that of the low-efficiency firm, either with same carbon emissions tax or without carbon emissions tax. When the two competing firms absorbed same carbon emissions tax, we show that both of them will set higher retail price than that without carbon emissions tax, and the high-efficiency firm’s both profit reduction and carbon emissions reduction percentages are lesser than that of low-efficiency firm. In addition, we find that when a firm incurs a higher carbon emissions tax, the firm gains a higher carbon emissions reduction percentage, but the competing firm gains a lower carbon emissions reduction percentage. We also find that in order to achieve a certain desired carbon emissions reduction percentage, the carbon emissions tax imposed on the high-efficiency firm should be more than that on the low-efficiency firm.
Journal: International Journal of Production Research
Pages: 6408-6420
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.932928
File-URL: http://hdl.handle.net/10.1080/00207543.2014.932928
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenbo Shi
Author-X-Name-First: Wenbo
Author-X-Name-Last: Shi
Author-Name: K. Jo Min
Author-X-Name-First: K. Jo
Author-X-Name-Last: Min
Title: Remanufacturing decisions and implications under material cost uncertainty
Abstract: 
 In this paper, for a firm of a single product, we construct and analyse how economically rational decisions on remanufacturing are made from a real options perspective under material cost uncertainty. Specifically, under the assumption that the material cost follows a Geometric Brownian Motion process, we derive the optimal condition (i.e. material cost threshold) to implement a remanufacturing system. Further analysis, analytically and/or numerically, yields numerous managerial insights and policy implications. For example, as the material cost becomes more uncertain, economically rational decision-makers will defer the implementation of the remanufacturing system. Furthermore, we also demonstrate that a product unit-based subsidy is more effective than a lump sum remanufacturing system implementation subsidy if our goal is to encourage a longer operational period of the remanufacturing system.
Journal: International Journal of Production Research
Pages: 6421-6435
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.932933
File-URL: http://hdl.handle.net/10.1080/00207543.2014.932933
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Template-Type: ReDIF-Article 1.0
Author-Name: Che-Wei Tsui
Author-X-Name-First: Che-Wei
Author-X-Name-Last: Tsui
Author-Name: Gwo-Hshiung Tzeng
Author-X-Name-First: Gwo-Hshiung
Author-X-Name-Last: Tzeng
Author-Name: Ue-Pyng Wen
Author-X-Name-First: Ue-Pyng
Author-X-Name-Last: Wen
Title: A hybrid MCDM approach for improving the performance of green suppliers in the TFT-LCD industry
Abstract: 
 The awareness of environmental protection/conservation and sustainable development has increased in the last two decades. In the competitive thin film transistor liquid crystal display (TFT-LCD) industry, green supplier evaluation involves environmental criteria in the traditional evaluation process and emphasises that TFT-LCD manufacturers should improve the performance of their suppliers with limited resources. The purpose of this study is to develop a hybrid multiple criteria decision-making with preference ranking organisation method for enrichment evaluations to evaluate and assist polariser suppliers for improving the performance of green suppliers in the TFT-LCD industry to achieve the aspiration level. Based on supplier audit forms, the proposed methods are as follows: to develop a decision framework by an influential network relation map (INRM); to obtain the influential weights of the criteria; to involve the concept of aspiration levels in the preference function; and to evaluate and reduce the gaps of suppliers in each criterion based on the INRM by systematically making decisions in the process of striving toward the aspirations. The results show the ranking as well as the suppliers’ strengths/weaknesses and provide an improvement report to enhance the suppliers’ competitiveness. In the evaluation procedure, the managers place importance on ‘green management’, ‘technology’ and ‘organisation’ aspects. To achieve the goal of being a cost-effective and high-performance manufacturer, the subsidiary polariser supplier should improve performance on ‘health and safety’ first and next develop technology to become the primary supplier by using the proposed methods.
Journal: International Journal of Production Research
Pages: 6436-6454
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.935829
File-URL: http://hdl.handle.net/10.1080/00207543.2014.935829
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Template-Type: ReDIF-Article 1.0
Author-Name: David Gallear
Author-X-Name-First: David
Author-X-Name-Last: Gallear
Author-Name: Abby Ghobadian
Author-X-Name-First: Abby
Author-X-Name-Last: Ghobadian
Author-Name: Qile He
Author-X-Name-First: Qile
Author-X-Name-Last: He
Title: The mediating effect of environmental and ethical behaviour on supply chain partnership decisions and management appreciation of supplier partnership risks
Abstract: 
 Green supply chain management and environmental and ethical behaviour (EEB), a major component of corporate responsibility (CR), are rapidly developing fields in research and practice. The influence and effect of EEB at the functional level, however, is under-researched. Similarly, the management of risk in the supply chain has become a practical concern for many firms. It is important that managers have a good understanding of the risks associated with supplier partnerships. This paper examines the effect of firms’ investment in EEB as part of corporate social responsibility in mediating the relationship between supply chain partnership (SCP) and management appreciation of the risk of partnering. We hypothesise that simply entering into a SCP does not facilitate an appreciation of the risk of partnering and may even hamper such awareness. However, such an appreciation of the risk is facilitated through CR’s environmental and stakeholder management ethos. The study contributes further by separating risk into distinct relational and performance components. The results of a firm-level survey confirm the mediation effect, highlighting the value to supply chain strategy and design of investing in EEB on three fronts: building internal awareness, monitoring and sharing best practice.
Journal: International Journal of Production Research
Pages: 6455-6472
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.937010
File-URL: http://hdl.handle.net/10.1080/00207543.2014.937010
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Template-Type: ReDIF-Article 1.0
Author-Name: Paolo Taticchi
Author-X-Name-First: Paolo
Author-X-Name-Last: Taticchi
Author-Name: Patrizia Garengo
Author-X-Name-First: Patrizia
Author-X-Name-Last: Garengo
Author-Name: Sai S. Nudurupati
Author-X-Name-First: Sai S.
Author-X-Name-Last: Nudurupati
Author-Name: Flavio Tonelli
Author-X-Name-First: Flavio
Author-X-Name-Last: Tonelli
Author-Name: Roberto Pasqualino
Author-X-Name-First: Roberto
Author-X-Name-Last: Pasqualino
Title: A review of decision-support tools and performance measurement and sustainable supply chain management
Abstract: 
 In recent years, interest on sustainable supply chain management (SSCM) has risen significantly in both the academic and business communities. This is confirmed by the growing number of conferences, journal publications, special issues and websites dedicated to the topic. Within this context, this paper reviews the existing literature related to decision-support tools and performance measurement for SSCM. A narrative literature review is carried out to capture qualitative evidence, while a systematic literature review is performed using classic bibliometric techniques to analyse the relevant body of knowledge identified in 384 papers published from 2000 to 2013. The key conclusions include: the evidence of a research field that is growing, the call for establishing the scope of current research, i.e. the need for integrated performance frameworks with new generation decision-support tools incorporating triple bottom line (TBL) approach for managing sustainable supply chains. There is a need to identify a wide range of specific industry-related TBL metrics and indexes, and assess their usefulness through empirical research and case-base analysis. We need mixed methods to thoroughly analyse and investigate sustainable aspects of the product life cycle across the supply chains, through empirical evidence, building and/or testing theory from and in practice.
Journal: International Journal of Production Research
Pages: 6473-6494
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.939239
File-URL: http://hdl.handle.net/10.1080/00207543.2014.939239
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Template-Type: ReDIF-Article 1.0
Author-Name: A. Lake
Author-X-Name-First: A.
Author-X-Name-Last: Lake
Author-Name: A. Acquaye
Author-X-Name-First: A.
Author-X-Name-Last: Acquaye
Author-Name: A. Genovese
Author-X-Name-First: A.
Author-X-Name-Last: Genovese
Author-Name: N. Kumar
Author-X-Name-First: N.
Author-X-Name-Last: Kumar
Author-Name: S.C.L. Koh
Author-X-Name-First: S.C.L.
Author-X-Name-Last: Koh
Title: An application of hybrid life cycle assessment as a decision support framework for green supply chains
Abstract: 
 In an effort to achieve sustainable operations, green supply chain management has become an important area for firms to concentrate on due to its inherent involvement with all the processes that provide foundations to successful business. Modelling methodologies of product supply chain environmental assessment are usually guided by the principles of life cycle assessment (LCA). However, a review of the extant literature suggests that LCA techniques suffer from a wide range of limitations that prevent a wider application in real-world contexts; hence, they need to be incorporated within decision support frameworks to aid environmental sustainability strategies. Thus, this paper contributes in understanding and overcoming the dichotomy between LCA model development and the emerging practical implementation to inform carbon emissions mitigation strategies within supply chains. Therefore, the paper provides both theoretical insights and a practical application to inform the process of adopting a decision support framework based on a LCA methodology in a real-world scenario. The supply chain of a product from the steel industry is considered to evaluate its environmental impact and carbon ‘hotspots’. The study helps understanding how operational strategies geared towards environmental sustainability can be informed using knowledge and information generated from supply chain environmental assessments, and for highlighting inherent challenges in this process.
Journal: International Journal of Production Research
Pages: 6495-6521
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.951092
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951092
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Template-Type: ReDIF-Article 1.0
Author-Name: Behnam Fahimnia
Author-X-Name-First: Behnam
Author-X-Name-Last: Fahimnia
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Author-Name: John Boland
Author-X-Name-First: John
Author-X-Name-Last: Boland
Author-Name: Mohsen Reisi
Author-X-Name-First: Mohsen
Author-X-Name-Last: Reisi
Author-Name: Mark Goh
Author-X-Name-First: Mark
Author-X-Name-Last: Goh
Title: Policy insights from a green supply chain optimisation model
Abstract: 
 This paper introduces a practical supply chain optimisation model that incorporates both economic and carbon emission objectives. The proposed model is implemented to examine the possible economic and environmental trade-offs for various carbon-pricing and fuel-pricing scenarios in an actual case company representing the discrete, durable parts manufacturing sector. Analysis of the numerical results provides important managerial implications and policy insights. For industry practitioners, the findings can assist in identifying the critical activities along the supply chain on which to focus in order to minimise the cost implications of a carbon-pricing regulation. For related policy-makers, the findings provide insights on how carbon should be priced to make meaningful impacts on emissions reduction while matching variations in fuel prices.
Journal: International Journal of Production Research
Pages: 6522-6533
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.958592
File-URL: http://hdl.handle.net/10.1080/00207543.2014.958592
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Template-Type: ReDIF-Article 1.0
Author-Name: Michael Altmann
Author-X-Name-First: Michael
Author-X-Name-Last: Altmann
Title: A supply chain design approach considering environmentally sensitive customers: the case of a German manufacturing SME
Abstract: 
 Sustainable business development is one of the main topics of research and management in recent years. Since the environmental pillar is a part of the sustainability concept, companies are forced to (re-)design their supply chain according to environmental issues. Both government and other stakeholders, e.g. non-governmental organisations and customers, pay a lot of attention on a company’s environmental performance. Hence there is a risk of losing reputation if a company does not comply with environmental norms. We focus on the impact of customers’ requirements regarding the environmental performance of a product on strategic supply chain design decisions of the manufacturer of the product. Thus, we consider the case of a German manufacturing company and present a mixed-integer linear programming supply chain design model with a demand function that is influenced by sustainability requirements. The company is assumed to be able to improve the environmental performance of the products sold and affect the customer demand positively by designing an environmentally conscious supply chain.
Journal: International Journal of Production Research
Pages: 6534-6550
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.961203
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961203
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Template-Type: ReDIF-Article 1.0
Author-Name: Gareth R.T. White
Author-X-Name-First: Gareth R.T.
Author-X-Name-Last: White
Author-Name: Xiaojun Wang
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Wang
Author-Name: Dong Li
Author-X-Name-First: Dong
Author-X-Name-Last: Li
Title: Inter-organisational green packaging design: a case study of influencing factors and constraints in the automotive supply chain
Abstract: 
 Green packaging is playing an increasingly important role in greening the supply chain. However, the issues that companies face when developing green packaging solutions for the transportation of products within supply chains are poorly understood. A case study of an automotive component manufacturer is presented that explores the complexity of the decisions that surround the decision of inter-organisational packaging design. Drawing upon the literature, legislation and the expert evaluation provided by the case organisation, it identifies the important criteria that influence packaging design and comprise customer requirements, legislation, operational and environmental concerns. This research finds that even though the company makes significant efforts to improve its environmental performance, operational concerns are most influential factors in the design of packaging. Initiatives that aim to improve the environmental performance of packaging are also constrained by external influences in the supply chain, such as customer pressure to adopt branded packaging systems and the inability to influence the design of incoming goods and material packaging.
Journal: International Journal of Production Research
Pages: 6551-6566
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.975854
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975854
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:21:p:6551-6566




Template-Type: ReDIF-Article 1.0
Author-Name: Antonella Meneghetti
Author-X-Name-First: Antonella
Author-X-Name-Last: Meneghetti
Author-Name: Luca Monti
Author-X-Name-First: Luca
Author-X-Name-Last: Monti
Title: Greening the food supply chain: an optimisation model for sustainable design of refrigerated automated warehouses
Abstract: 
 An optimisation model for the sustainable design of refrigerated automated storage and retrieval systems is proposed, which takes into account specific features of the food supply chain, such as temperature control. Rack configuration as well as surfaces and volumes of the cold cell are conjointly optimised in order to minimise the total yearly cost of the automated storage facility, introducing energy requirements both for refrigeration and picking operations explicitly, other than investment costs. Crane plus satellite systems are modelled in order to enable deep lane solutions and space savings, as suitable for cold storage. The model allows a deep analysis of the impact of supply chain decision variables, such as the facility location, the storage temperature and the incoming product temperature on costs, energy use and carbon dioxide emissions, so that storage facilities attributes for supply chain design models can be properly assessed to re-optimise the whole cold chain. The design problem is modelled and solved by Constraint Programming in order to easily manage non-linear functions.
Journal: International Journal of Production Research
Pages: 6567-6587
Issue: 21
Volume: 53
Year: 2015
Month: 11
X-DOI: 10.1080/00207543.2014.985449
File-URL: http://hdl.handle.net/10.1080/00207543.2014.985449
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Template-Type: ReDIF-Article 1.0
Author-Name: Emre Cevikcan
Author-X-Name-First: Emre
Author-X-Name-Last: Cevikcan
Author-Name: Dicle Aslan
Author-X-Name-First: Dicle
Author-X-Name-Last: Aslan
Author-Name: Fatma Betul Yeni
Author-X-Name-First: Fatma Betul
Author-X-Name-Last: Yeni
Title: Disassembly line design with multi-manned workstations: a novel heuristic optimisation approach
Abstract: 
 As the first and the most time consuming step of product recovery, disassembly is described as the systematic separation of constituent parts from end-of-life products through a series of operations. In this context, designing and balancing disassembly lines are critical in terms of the efficiency of product recovery. Recent research on disassembly line balancing (DLB) has focused on classical stations where only one worker is allocated. However, such a line results in larger space requirement and longer disassembly lead time. In this paper, disassembly line balancing problem (DLBP) with multi-manned stations is introduced to the relevant literature as a solution to overcome these disadvantages. A mixed integer linear programming (MILP) model and two novel framework heuristic algorithms are developed to minimise the number of workers and workstations. MILP model has been applied to a dishwasher disassembly system. The application results indicate the superiority of establishing multi-manned stations over classical disassembly system design with single-worker stations with shorter disassembly lead time (80.9%) and line length (60.2%). Moreover, the proposed heuristics have been compared on newly generated test problems (instances) for DLBP. The results validate that the heuristics provide acceptable solutions in a reasonable amount of time even for large-sized problems.
Journal: International Journal of Production Research
Pages: 649-670
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1587190
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1587190
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Template-Type: ReDIF-Article 1.0
Author-Name: H. Murat Afsar
Author-X-Name-First: H.
Author-X-Name-Last: Murat Afsar
Author-Name: Faicel Hnaien
Author-X-Name-First: Faicel
Author-X-Name-Last: Hnaien
Title: Formulations and solution algorithms for dynamic assembly routing problem
Abstract: 
 We study a dynamic version of the assembly routing problem. The assembly lot sizing section deals with decisions concerning the production phase, whereas the routing section organises the collection of raw materials necessary for the production. Traditionally, these two problems are treated separately, and more specifically, in a hierarchical way. We propose three linear programming models: a non-vehicle index model, a two-commodity flow formulation and a logic-based benders decomposition. We develop aggregated rounded capacity constraints for non-vehicle index model and separated them dynamically during the Branch & Cut procedure. Logic-based benders decomposition algorithm solves the Dynamic Assembly Routing Problem iteratively and obtains a feasible solution at each iteration. The numerical tests show that, the two first models are particularly effective at finding the optimal solutions in a reasonable amount of time on instances with up to 50 components and 3 periods.
Journal: International Journal of Production Research
Pages: 671-688
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1588481
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1588481
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:671-688




Template-Type: ReDIF-Article 1.0
Author-Name: Kai Li
Author-X-Name-First: Kai
Author-X-Name-Last: Li
Author-Name: Shuling Xu
Author-X-Name-First: Shuling
Author-X-Name-Last: Xu
Author-Name: Hong Fu
Author-X-Name-First: Hong
Author-X-Name-Last: Fu
Title: Work-break scheduling with real-time fatigue effect and recovery
Abstract: 
 In many situations, employees' performance decrements have generally been attributed to fatigue, and a flexibly designed work-break schedule can reduce their fatigue effect. This paper focuses upon the development and solution of model which minimises the actual completion time of all jobs, subject to a given fixed workload, through the selection of optimal work-break schedules. In this paper, several break periods are considered where each break activity is scheduled after a periodic time interval, and the employees' work rate first maintains a certain level and then declines during the work period. We propose a mathematical programming model and a heuristic algorithm to solve this problem. Our analysis finds that compared to the actual completion time of an employee without having a break, setting several reasonable fixed breaks makes work efficiency increased and improves employee satisfaction and reduces the makespan. Our findings light on the importance of understanding and setting break time in the work periods, and contribute to the improvement of employee satisfaction.
Journal: International Journal of Production Research
Pages: 689-702
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1598600
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598600
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:689-702




Template-Type: ReDIF-Article 1.0
Author-Name: Hui Lei
Author-X-Name-First: Hui
Author-X-Name-Last: Lei
Author-Name: Jingru Wang
Author-X-Name-First: Jingru
Author-X-Name-Last: Wang
Author-Name: Lusheng Shao
Author-X-Name-First: Lusheng
Author-X-Name-Last: Shao
Author-Name: Honglin Yang
Author-X-Name-First: Honglin
Author-X-Name-Last: Yang
Title: Ex post demand information sharing between differentiated suppliers and a common retailer
Abstract: 
 We consider ex post demand information sharing in a two-echelon supply chain in which two suppliers sell differentiated products through a common retailer. We model three scenarios of information sharing to characterise the conditions under which information sharing may benefit or hurt different players: (1) no supplier is informed; (2) only one supplier is informed; and (3) both suppliers are informed. We find that the retailer may voluntarily share the low demand information when the product differentiation and demand magnitude satisfy certain conditions. In contrast, the retailer has no incentive to share the high demand information, even though this information benefits the suppliers. To achieve information sharing, we propose a side payment mechanism, which allows benefitted players to subsidise hurtful players. Finally, we extend our model by considering a situation where the suppliers have limited capacity and may invest to ramp up production capacity to satisfy a high demand.
Journal: International Journal of Production Research
Pages: 703-728
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1600758
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1600758
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Template-Type: ReDIF-Article 1.0
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: David Bogataj
Author-X-Name-First: David
Author-X-Name-Last: Bogataj
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Ilenia Zennaro
Author-X-Name-First: Ilenia
Author-X-Name-Last: Zennaro
Title: Ageing workforce management in manufacturing systems: state of the art and future research agenda
Abstract: 
 The workforce ageing phenomenon is recently affecting most of the Organisation for Economic Co-operation and Development (OECD) member countries, due to a general ageing of their populations and a higher average retirement age of the workforce. In this paper, the topic of ageing workforce management is addressed from a production research standpoint, with the aim of understanding how older workers can be supported and involved in a manufacturing system. First, the current state of the art related to the ageing workforce in production systems is presented. This is structured according to four main topics: (1) analysis and evaluation of ageing workers’ functional capacities, (2) consideration of ageing workers’ capacities in industrial system modelling and management, (3) analysis and exploitation of ageing workers’ expertise, (4) acknowledgement, analysis, design and integration of supporting technologies. Next, the discussion on the impact of the ageing workforce on manufacturing systems’ performances leads to the comparison of some technological advances that are related to the Industry 4.0 paradigms. Finally, a future research agenda on this topic is proposed, based on the same topics classification proposed for the literature analysis. Five different research areas are derived, suggesting future directions for appropriate research concerning the employ of older workers in production environments.
Journal: International Journal of Production Research
Pages: 729-747
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1600759
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1600759
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanjuan Hu
Author-X-Name-First: Yanjuan
Author-X-Name-Last: Hu
Author-Name: Lizhe Wu
Author-X-Name-First: Lizhe
Author-X-Name-Last: Wu
Author-Name: Chao Shi
Author-X-Name-First: Chao
Author-X-Name-Last: Shi
Author-Name: Yilin Wang
Author-X-Name-First: Yilin
Author-X-Name-Last: Wang
Author-Name: Feifan Zhu
Author-X-Name-First: Feifan
Author-X-Name-Last: Zhu
Title: Research on optimal decision-making of cloud manufacturing service provider based on grey correlation analysis and TOPSIS
Abstract: 
 It is of great practical significance to optimise the decision-making of cloud manufacturing service providers, which can ensure the efficient operation of the cloud manufacturing services. In order to effectively optimise, this paper constructs the evaluation index system, sorts out 7 important evaluation indexes. A method is proposed on the basis of the TOPSIS method and Grey Correlation Analysis (GRA), which is a decision-making method combining static distance and dynamic trend, and make the evaluation results more reasonable. In addition, in order to reflect the true weight of the high dimensional index, the evaluation model of projection pursuit index is established. The improved Particle Swarm Optimisation (PSO) algorithm is used to optimise the projection index function and model parameters, and to obtain the objective weights of evaluation indexes. Then the objective weights combine with the subjective weights obtained by the Analytic hierarchy process (AHP), which makes the weights of the evaluation indexes achieve the unity of subjective and objective. Finally, 20 sets of simulation examples are given to illustrate the feasibility and effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 748-757
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1600760
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1600760
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenqiang Dai
Author-X-Name-First: Wenqiang
Author-X-Name-Last: Dai
Author-Name: Zhuolin Yang
Author-X-Name-First: Zhuolin
Author-X-Name-Last: Yang
Author-Name: Yi Feng
Author-X-Name-First: Yi
Author-X-Name-Last: Feng
Author-Name: Meng Zheng
Author-X-Name-First: Meng
Author-X-Name-Last: Zheng
Title: Real-time procurement policy with yield and price uncertainty
Abstract: 
 This study formulates and analyses a procurement model in which a procurer faces both yield and price uncertainty. We propose a simple and effective real-time procurement policy where the decisions are made only based on the current arriving price and inventory level. The only information we need is the first two moments for the random yield rate, and the lower and upper bounds for price. Thus, our policy delivers robust performance to changing yield and price over time. In addition, simple decision rules are summarised for determining the optimal procurement quantity for different cases. Analytical results and numerical experiments are presented to show that the proposed policy achieves a superior performance guarantee.
Journal: International Journal of Production Research
Pages: 758-782
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1600761
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1600761
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:758-782




Template-Type: ReDIF-Article 1.0
Author-Name: Rosangela Maria Vanalle
Author-X-Name-First: Rosangela Maria
Author-X-Name-Last: Vanalle
Author-Name: W.C. Lucato
Author-X-Name-First: W.C.
Author-X-Name-Last: Lucato
Author-Name: G.M.D. Ganga
Author-X-Name-First: G.M.D.
Author-X-Name-Last: Ganga
Author-Name: A.G. Alves Filho
Author-X-Name-First: A.G.
Author-X-Name-Last: Alves Filho
Title: Risk management in the automotive supply chain: an exploratory study in Brazil
Abstract: 
 The main objective of this study was to identify the main characteristics of risk management in the automotive supply chain in Brazil, considering companies in the first and second tiers. This objective was achieved through the proposition of three hypotheses that were tested based on a survey of 211 auto parts producers scattered throughout the country, from which 77 completed forms were received. This research enabled us to conclude that the risks perceived in tier 2 are higher than those observed in tier 1. Also, it was possible to verify that the performance of companies in tier 2 (higher risk) is lower than those in tier 1. Contrary to what was observed in the literature, this research could not find evidence to confirm that risk management tools are prioritized to reduce the risk of companies in the supply chain. Therefore, this research contributes to both theory and practice: this is the first study that performs an analysis of risk management in supply chains with tier 1 and 2 companies in the Brazilian automotive industry, becoming an important complement to recent studies on this topic. For practitioners and business executives who manage risks in automotive supply chains in Brazil, this paper shows the reality of the issue in first- and second-tier companies, which can provide them with important contexts for their decision making in the day-to-day business of the automotive sector.
Journal: International Journal of Production Research
Pages: 783-799
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1600762
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1600762
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:783-799




Template-Type: ReDIF-Article 1.0
Author-Name: Jesica de Armas
Author-X-Name-First: Jesica
Author-X-Name-Last: de Armas
Author-Name: Manuel Laguna
Author-X-Name-First: Manuel
Author-X-Name-Last: Laguna
Title: Parallel machine, capacitated lot-sizing and scheduling for the pipe-insulation industry
Abstract: 
 We develop a solution procedure for a production problem that involves the optimal lot-sizing and scheduling of multiple products on parallel machines over a long planning horizon. The objective is to determine the product assignment, production quantities, and production sequence on each machine in order to meet demand and maximise the total production amount in a given planning horizon. We study this problem in the context of the manufacturing of pipe insulation, in which multiple features have to be considered simultaneously. The solution procedure combines mathematical programming and a post-processing sequencing heuristic. We also develop a procedure to determine safety stock levels and use Monte Carlo simulation to assess the risk associated with inventory shortages due to stochastic production rates. Computational tests are performed on both real and artificially-generated data.
Journal: International Journal of Production Research
Pages: 800-817
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1600763
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1600763
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:800-817




Template-Type: ReDIF-Article 1.0
Author-Name: Ivan Svetunkov
Author-X-Name-First: Ivan
Author-X-Name-Last: Svetunkov
Author-Name: John E. Boylan
Author-X-Name-First: John E.
Author-X-Name-Last: Boylan
Title: State-space ARIMA for supply-chain forecasting
Abstract: 
 ARIMA is seldom used in supply chains in practice. There are several reasons, not the least of which is the small sample size of available data, which restricts the usage of the model. Keeping in mind this restriction, we discuss in this paper a state-space ARIMA model with a single source of error and show how it can be efficiently used in the supply-chain context, especially in cases when only two seasonal cycles of data are available. We propose a new order selection algorithm for the model and compare its performance with the conventional ARIMA on real data. We show that the proposed model performs well in terms of both accuracy and computational time in comparison with other ARIMA implementations, which makes it efficient in the supply-chain context.
Journal: International Journal of Production Research
Pages: 818-827
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1600764
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1600764
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:818-827




Template-Type: ReDIF-Article 1.0
Author-Name: Pooya Alavian
Author-X-Name-First: Pooya
Author-X-Name-Last: Alavian
Author-Name: Yongsoon Eun
Author-X-Name-First: Yongsoon
Author-X-Name-Last: Eun
Author-Name: Semyon M. Meerkov
Author-X-Name-First: Semyon M.
Author-X-Name-Last: Meerkov
Author-Name: Liang Zhang
Author-X-Name-First: Liang
Author-X-Name-Last: Zhang
Title: Smart production systems: automating decision-making in manufacturing environment
Abstract: 
 Smart production systems (SPS) are manufacturing systems capable of autonomously diagnosing their health and autonomously designing continuous improvement projects, leading to the desired productivity improvement. The main component of SPS, developed in this paper, is the Programmable Manufacturing Advisor (PMA), which evaluates the system's health and calculates optimal steps for continuous improvement. The analytics of PMA are based on the theory of Production Systems Engineering (PSE); the numerics of PMA are based on PSE Toolbox, which implements the PSE methods. In this paper, the PMA-based SPS architecture with manager-in-the-loop is described, theoretical/analytical foundations of PMA are outlined, its software/hardware implementations are commented upon, and demonstrations of PMA-based SPS operation are provided using two production systems: automotive underbody assembly (large volume manufacturing) and hot-dip galvanisation plant (small manufacturing organisation).
Journal: International Journal of Production Research
Pages: 828-845
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1600765
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1600765
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Template-Type: ReDIF-Article 1.0
Author-Name: Yilin Fang
Author-X-Name-First: Yilin
Author-X-Name-Last: Fang
Author-Name: Hao Ming
Author-X-Name-First: Hao
Author-X-Name-Last: Ming
Author-Name: Miqing Li
Author-X-Name-First: Miqing
Author-X-Name-Last: Li
Author-Name: Quan Liu
Author-X-Name-First: Quan
Author-X-Name-Last: Liu
Author-Name: Duc Truong Pham
Author-X-Name-First: Duc Truong
Author-X-Name-Last: Pham
Title: Multi-objective evolutionary simulated annealing optimisation for mixed-model multi-robotic disassembly line balancing with interval processing time
Abstract: 
 This paper considers the design and balancing of mixed-model disassembly lines with multi-robotic workstations under uncertainty. Tasks of different models are performed simultaneously by the robots which have different capacities for disassembly. The robots have unidentical task times and energy consumption respectively. Task precedence diagrams are used to model the precedence relations among tasks. Considering uncertainties in disassembly process, the task processing times are assumed to be interval numbers. A mixed-integer mathematical programming model is proposed to minimise the cycle time, peak workstation energy consumption, and total energy consumption. This model has a significant managerial implication in real-life disassembly line systems. Since the studied problem is known as NP-hard, a metaheuristic approach based on an evolutionary simulated annealing algorithm is developed. Computational experiments are conducted and the results demonstrate the proposed algorithm outperforms other multi-objective algorithms on optimisation quality and computational efficiency.
Journal: International Journal of Production Research
Pages: 846-862
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1602290
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1602290
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:846-862




Template-Type: ReDIF-Article 1.0
Author-Name: Jeong-Hoon Shin
Author-X-Name-First: Jeong-Hoon
Author-X-Name-Last: Shin
Author-Name: Jae-Min Yu
Author-X-Name-First: Jae-Min
Author-X-Name-Last: Yu
Author-Name: Hyoung-Ho Doh
Author-X-Name-First: Hyoung-Ho
Author-X-Name-Last: Doh
Author-Name: Hyung-Won Kim
Author-X-Name-First: Hyung-Won
Author-X-Name-Last: Kim
Author-Name: Dong-Ho Lee
Author-X-Name-First: Dong-Ho
Author-X-Name-Last: Lee
Title: Batching and scheduling for a single-machine flexible machining cell with multi-fixturing pallets and controllable processing times
Abstract: 
 This study addresses an integrated batching and scheduling problem for a single-machine flexible machining cell in which each pallet can load multiple parts, i.e. multi-fixturing pallets, and part processing times can be changed with different processing costs, i.e. controllable processing times. The batching sub-problem is to select the set of parts to be produced in each period of a planning horizon and the resulting scheduling sub-problem is to determine the set of parts to be loaded on each multi-fixturing pallet, the part processing times and the pallet input/processing sequences for the parts selected in each period. A bi-criterion objective is considered that minimises the total tardiness and the total processing cost simultaneously. A solution approach is proposed that consists of three phases from the first to the last period: (a) generating the whole schedule over the planning horizon; (b) selecting the parts to be produced during the current period using the scheduling information; and (c) determining the final schedule for the selected parts. Simulation experiments were done on a number of test instances and the results are reported.
Journal: International Journal of Production Research
Pages: 863-877
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1602742
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1602742
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Template-Type: ReDIF-Article 1.0
Author-Name: Amel Ben Mabrouk
Author-X-Name-First: Amel
Author-X-Name-Last: Ben Mabrouk
Author-Name: Anis Chelbi
Author-X-Name-First: Anis
Author-X-Name-Last: Chelbi
Author-Name: Lazher Tlili
Author-X-Name-First: Lazher
Author-X-Name-Last: Tlili
Author-Name: Mehdi Radhoui
Author-X-Name-First: Mehdi
Author-X-Name-Last: Radhoui
Title: A quasi-optimal inspection strategy for leased equipment
Abstract: 
 This paper presents a quasi-optimal inspection policy for equipment that is leased for a given period and whose failures can be detected only through inspections. Maintenance including inspections and replacements is entrusted to the lessor. Whenever inspection reveals that the equipment is in failed state, it is replaced (or restored to a state as good as new). In case the average downtime between failures and their detection exceeds a contractual pre-specified duration, a penalty is incurred by the lessor. The proposed mathematical model and numerical algorithm allow finding a quasi-optimal sequence of inspection instants (θ1*, θ2*, … , θN*) which minimises the expected total cost incurred by the lessor over the lease period L. A numerical example is presented and the obtained results are discussed. We investigate numerically the effect of the variation of the downtime penalty cost, the inspection cost, the lease period length, and the equipment reliability on the quasi-optimal inspection policy to be adopted by the lessor.
Journal: International Journal of Production Research
Pages: 878-892
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1602743
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1602743
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Template-Type: ReDIF-Article 1.0
Author-Name: Francesco Gabriele Galizia
Author-X-Name-First: Francesco Gabriele
Author-X-Name-Last: Galizia
Author-Name: Hoda ElMaraghy
Author-X-Name-First: Hoda
Author-X-Name-Last: ElMaraghy
Author-Name: Marco Bortolini
Author-X-Name-First: Marco
Author-X-Name-Last: Bortolini
Author-Name: Cristina Mora
Author-X-Name-First: Cristina
Author-X-Name-Last: Mora
Title: Product platforms design, selection and customisation in high-variety manufacturing
Abstract: 
 Product platforms represent an effective strategy implemented by manufacturers to cope with dynamic market demands, decrease lead-time and delay products differentiation. A decision support system (DSS) for product platforms design and selection in high-variety manufacturing is presented. It applies median-joining phylogenetic networks (MJPN) for the platforms design and phylogenetic tree decomposition for platforms selection by determining the product family phylogenetic network and defines the platforms at various levels of assembly corresponding to different trade-offs between number of platforms (variety) and number of assembly/disassembly tasks (customisation effort). Product platforms are reconfigured and customised to derive final product variants. The phylogenetic tree is decomposed in multiple levels, from the native platforms to the final variants. New Platforms Reconfiguration Index (PRI) and Platforms Customisation Index (PCI) were developed as metrics to evaluate the platforms customisation effort. A case study of a large family of plastic valves is used to demonstrate the DSS application. It shows reduction of 60% in platforms variety and increases in platform customisation assembly/disassembly tasks by only 20% leading to significant production and inventory efficiencies and cost savings. This methodology supports companies in the design and selection of best product platforms for high-variety to reduce cost and delivery time.
Journal: International Journal of Production Research
Pages: 893-911
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1602745
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1602745
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:893-911




Template-Type: ReDIF-Article 1.0
Author-Name: Stanisław Bylka
Author-X-Name-First: Stanisław
Author-X-Name-Last: Bylka
Title: The consignment stock of inventories under buyer's warehouse space limitation
Abstract: 
 In this paper, coordination between a single vendor (or manufacturer) and a buyer (or retailer) via the delivery schedule in a production and distribution system is presented. A continuous deterministic model with centralised decision process is developed. To satisfy the buyer's demands, the product is delivered in discrete batches from the vendor's stock to the buyer's stock subject to consignee's warehouse space capacity constraint. A more general type of consignment stock (CS) policies is analysed. The inventory patterns and the cost structure of production distribution cycles (PDC) are described under the constraint – when the ratio α of the sizes of delayed to just in time (JIT) for the vendor deliveries is given. Also, an analysis how an upper buyer's warehouse space limit can act as a key factor for implementing the generalised CS-policies successfully. Numerical examples are presented to illustrate the performance of model and the results. A comparative study of the results shows that the generalised CS-policies performs better.
Journal: International Journal of Production Research
Pages: 912-930
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1605223
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1605223
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:912-930




Template-Type: ReDIF-Article 1.0
Author-Name: Salah Haridy
Author-X-Name-First: Salah
Author-X-Name-Last: Haridy
Author-Name: Mohammad Shamsuzzaman
Author-X-Name-First: Mohammad
Author-X-Name-Last: Shamsuzzaman
Author-Name: Imad Alsyouf
Author-X-Name-First: Imad
Author-X-Name-Last: Alsyouf
Author-Name: Amitava Mukherjee
Author-X-Name-First: Amitava
Author-X-Name-Last: Mukherjee
Title: An improved design of exponentially weighted moving average scheme for monitoring attributes
Abstract: 
 The Exponentially Weighted Moving Average (EWMA) schemes are a potent tool for monitoring small to moderate variations in the quality characteristics in production lines of manufacturing industries. Practitioners in various sectors widely use the EWMA schemes for scrutinising both the variables and attributes. In the present article, we investigate a modified EWMA scheme based on the power of the difference between the actual number of nonconforming items and its technical specification in an in-control (IC) situation. We abbreviate it as a wEWMA scheme and show that the traditional EWMA scheme is a particular case of the proposed scheme when the power is unity. We establish that the powers lower than unity are more effective for detecting smaller shifts, while for detecting substantial variations in process parameter, one should prefer higher powers greater than unity. Noting that possible magnitude of a shift is often unknown, we propose the optimal design procedure of the scheme, including the determination of its charting parameters to ensure the best overall performance. The results reveal that the optimal wEWMA schemes can be beneficial in detecting a shift very quickly when the sample size is small, particularly for high-precision production processes.
Journal: International Journal of Production Research
Pages: 931-946
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1605224
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1605224
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Template-Type: ReDIF-Article 1.0
Author-Name: Shivam Gupta
Author-X-Name-First: Shivam
Author-X-Name-Last: Gupta
Author-Name: Sachin Modgil
Author-X-Name-First: Sachin
Author-X-Name-Last: Modgil
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Title: Big data in lean six sigma: a review and further research directions
Abstract: 
 Manufacturing and service organisations improve their processes on a continuous basis to have better operational performance. They use lean six sigma (LSS) projects for process improvement. Therefore, this study aims to investigate the existing literature in LSS and the application of big data analytics (BDA) to have more confident and predictable decisions in each phase of LSS. Fifty-two articles have been identified after a careful and vigilant screening of closely related themes. Future research directions in the big data and LSS have been highlighted on the basis of organisational theories. Review presents an investigation framework consisting of BDA techniques applicable to each phase of LSS in all the dimensions such as volume, variety, velocity and veracity of big data. Review highlights the concerns of big data in LSS such as system design and integration, system performance, security and reliability of data, sustaining the control and conducting the experiments, distributed material and information flow. The review unveils the application of 8 modern organisational theories to big data in LSS with 21 key aspects of related theories and 19 distinct research gaps as opportunities for future research.
Journal: International Journal of Production Research
Pages: 947-969
Issue: 3
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1598599
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598599
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Template-Type: ReDIF-Article 1.0
Author-Name: Tomas Ambra
Author-X-Name-First: Tomas
Author-X-Name-Last: Ambra
Author-Name: An Caris
Author-X-Name-First: An
Author-X-Name-Last: Caris
Author-Name: Cathy Macharis
Author-X-Name-First: Cathy
Author-X-Name-Last: Macharis
Title: Towards freight transport system unification: reviewing and combining the advancements in the physical internet and synchromodal transport research
Abstract: 
 To achieve socio-economic and environmental sustainability, utilization of existing capacities and assets has become a key challenge for the transportation sector. This challenge has been recognised by many scholars, policy makers and practitioners leading to a substantial body of new concepts and models. The rather parallel evolution of the Physical Internet (PI) and synchromodal transport presents an opportunity to improve the current unsustainable freight transportation, by inducing a positive modal shift from roads to rails and inland waterways, and improving service levels by better connecting production research with freight movement. This paper thus examines the synchromodal and PI state-of-the-art models together with their designs, methodologies and findings proposed in the scientific literature. The main objective is to assess and explore the correlations between these two concepts in order to understand how they can reinforce each other. Despite the integrated vision of the Alliance for Logistics Innovation through Collaboration in Europe, the findings of this paper yield no well-established interconnections in the scientific literature between PI and synchromodality as they both merely coexist in parallel and address different dimensions, scales and levels of abstraction. This paper thus identifies potential synergies, future research directions and critical questions to be considered by modellers, developers and policy makers.
Journal: International Journal of Production Research
Pages: 1606-1623
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1494392
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1494392
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Template-Type: ReDIF-Article 1.0
Author-Name: Cheng-Hu Yang
Author-X-Name-First: Cheng-Hu
Author-X-Name-Last: Yang
Author-Name: Xin Ma
Author-X-Name-First: Xin
Author-X-Name-Last: Ma
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Title: Optimal acquisition decision in a remanufacturing system with partial random yield information
Abstract: 
 When making decisions to acquire used products or components (cores), a remanufacturer faces limited information on the quality or proportional yield of cores during the recovery process. In this paper, we propose and analyse a robust optimisation model for studying the remanufacturing decision problem with partial random yield information, that is, when the quality information of cores is partly unknown in a remanufacturing system. Regarding the impacts of unknown yield information, we only require the support and mean of the proportional yield rather than the true distributions. The closed-form solutions of acquisition quantities are derived based on the minimax regret approach. In addition, to validate the effectiveness of the analytical results, particularly the acquisition of yield information, numerical experiments are designed and implemented using (1) the support and mean of the proportional yield based on the manufacturer’s knowledge and (2) a sampling inspection to evaluate the performance of the robust optimisation approach, the benchmark, and the naïve approach. We observe that the minimax regret approach slightly underperforms compared to the benchmark but performs much better than the naïve approach. As an acceptable choice, this approach is less complicated and extremely easy to implement to meet the needs of practical situations based on its robust closed-form solutions.
Journal: International Journal of Production Research
Pages: 1624-1644
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1494393
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1494393
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Template-Type: ReDIF-Article 1.0
Author-Name: Rodrigo Romero-Silva
Author-X-Name-First: Rodrigo
Author-X-Name-Last: Romero-Silva
Author-Name: Sabry Shaaban
Author-X-Name-First: Sabry
Author-X-Name-Last: Shaaban
Title: Influence of unbalanced operation time means and uneven buffer allocation on unreliable merging assembly line efficiency
Abstract: 
 Unbalanced, unreliable (UR), unpaced, merging assembly lines are simulated in this study with varying line lengths, buffer storage capacities, imbalance degrees and unequal mean operation time configurations and uneven buffer capacity (BC) allocation. This paper contributes to the literature by suggesting that, in many cases, imbalance can improve merging lines’ performance, as compared to a corresponding balanced merging line. It was found that an inverted bowl or descending patterns for mean operation times (MTs), and an inverted bowl (concentrating BC towards the centre of the line) or an ascending pattern for buffer allocation, result in higher throughput (TR). In terms of average buffer level (ABL), the best pattern is a monotone decreasing order regarding MTs and a monotone increasing order with respect to BC allocation. Additionally, it was found that when considering a profit function, the best performing patterns for UR lines tend to be the patterns that reduce ABL, even when considering very low inventory holding costs; contrary to the behaviour of the profit function in reliable lines, which suggests that either patterns that increase TR or reduce ABL can lead to a good performance, depending on the values of the unitary inventory holding costs.
Journal: International Journal of Production Research
Pages: 1645-1666
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1495344
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1495344
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Template-Type: ReDIF-Article 1.0
Author-Name: Min Ji
Author-X-Name-First: Min
Author-X-Name-Last: Ji
Author-Name: Wenya Zhang
Author-X-Name-First: Wenya
Author-X-Name-Last: Zhang
Author-Name: Lijuan Liao
Author-X-Name-First: Lijuan
Author-X-Name-Last: Liao
Author-Name: T. C. E. Cheng
Author-X-Name-First: T. C. E.
Author-X-Name-Last: Cheng
Author-Name: Yuanyuan Tan
Author-X-Name-First: Yuanyuan
Author-X-Name-Last: Tan
Title: Multitasking parallel-machine scheduling with machine-dependent slack due-window assignment
Abstract: 
 We consider the problem of parallel-machine scheduling with machine-dependent slack (SLK) due-window assignment in the multitasking environment, which exists in various application domains such as Internet services, project management, and manufacturing. Motivated by practical observations, we extend the original model of multitasking to a more general model where each job’s interruption proportion depends on the job itself and its processing position. In the light of individualised service, we consider SLK due-window assignment. Our objective is to minimise the total cost that comprises the earliness, tardiness, and due-window-related costs. Finding that an optimal schedule exists when each machine is occupied by at least one job, we show that the problem is polynomially solvable. We provide a more efficient solution algorithm for a special case of the problem. Finally, we present numerical examples to illustrate the application of the theoretical results and working of the solution algorithms.
Journal: International Journal of Production Research
Pages: 1667-1684
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1497312
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1497312
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Template-Type: ReDIF-Article 1.0
Author-Name: Yonit Barron
Author-X-Name-First: Yonit
Author-X-Name-Last: Barron
Title: Critical level policy for a production-inventory model with lost sales
Abstract: 
 We consider a storage process $W\lpar t\rpar$W(t) under the generalised order-up-to-level policy, based on a continuous-time Markov chain (CTMC). Specifically, the process starts at level S; whenever it drops to s, an order is sent, which is carried out after an exponential lead time. If during the lead time level S is reached, the order is cancelled, incurring some fee. This paper is written as an extension of Barron [2016. “An $(s,k,S)$(s,k,S) Fluid Inventory Model with Exponential Lead Times and Order Cancellations.” Stochastic Models 32 (2): 301–332]. While the latter paper considered a fluid inventory model with backlogging and focused on discounted analysis only, the case of lost sales was not solved. The present paper generalises the analysis to incorporate unsatisfied demand for the expected discounted costs and for the average costs per time unit. We consider four costs. There is a fixed nonzero ordering cost or a fee for each order cancellation, a purchase cost for each ordered item, a storage cost for the stock, and a penalty cost due to the unmet demand. Applying renewal theory, multi-dimensional martingales, and stopping time theory, we obtain explicit expressions of the cost components. Numerical study provides several guidelines on the optimal controls.
Journal: International Journal of Production Research
Pages: 1685-1705
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1504243
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504243
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Xin Liu
Author-X-Name-First: Xin
Author-X-Name-Last: Liu
Author-Name: E. Zhang
Author-X-Name-First: E.
Author-X-Name-Last: Zhang
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Scenario-based heuristic to two-stage stochastic program for the parallel machine ScheLoc problem
Abstract: 
 Scheduling-Location (ScheLoc) problem is a new and interesting topic in manufacturing, considering location and scheduling decisions simultaneously. Most existing works focus on the deterministic problems. In practice, however, job-processing times are usually uncertain due to some factors. This paper investigates the stochastic parallel machine ScheLoc problem to minimise the weighted sum of the location cost and the expectation of the total completion time. A two-stage stochastic programming formulation is proposed, then the sample average approximation (SAA) method is adapted to solve the small-size problems. To efficiently address the large-scale problems, a genetic algorithm (GA) and a scenario-based heuristic are designed. Numerical experiments on 450 instances are conducted. Computational results show that the scenario-based heuristic outperforms SAA method and GA in terms of solution quality and computational time.
Journal: International Journal of Production Research
Pages: 1706-1723
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1504247
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504247
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Template-Type: ReDIF-Article 1.0
Author-Name: Kathleen M. Iacocca
Author-X-Name-First: Kathleen M.
Author-X-Name-Last: Iacocca
Author-Name: Stephen Mahar
Author-X-Name-First: Stephen
Author-X-Name-Last: Mahar
Title: Cooperative partnerships and pricing in the pharmaceutical supply chain
Abstract: 
 The pharmaceutical supply chain has become highly consolidated. Currently, over 70% of all prescriptions are handled by three pharmacy benefit managers which each own a mail-order pharmacy. To compete in this environment, small and midsized pharmacies must seek efficiencies in their operations. The paper considers the value of cooperative partnerships between mail-order and chain pharmacies to leverage strengths of both players. To examine the viability of the strategy we develop a mathematical model that assesses the value of partnerships between independent organizations operating in different channels. The model is used to determine whether and to what extent pharmacies should consider partnerships that leverage a competing channel to allow mail-order customers to pick up prescriptions at chain stores in particular regions. Computational results provide insight into the impact of drug prices, reimbursement contracts, and revenue/cost-sharing policies on the optimal supply chain design and highlight conditions under which it is beneficial for chain and/or mail-order pharmacies to enter partnerships.
Journal: International Journal of Production Research
Pages: 1724-1740
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1504249
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504249
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Author-Name: Martin J. Land
Author-X-Name-First: Martin J.
Author-X-Name-Last: Land
Author-Name: Larry D. Fredendall
Author-X-Name-First: Larry D.
Author-X-Name-Last: Fredendall
Title: On the combined effect of due date setting, order release, and output control: an assessment by simulation
Abstract: 
 Workload Control is a production control concept for high-variety shops built on the principle of input/output control. The literature, however, has argued that input/output control overemphasises throughput improvements to the detriment of the timing of individual orders and, consequently, that it needs to be supplemented by a preceding customer enquiry stage where due dates are set. Yet, although there are broad separate literature streams on due date setting, order release, and output control, there is a lack of research on the three functions together. In response, this study uses simulation to assess the combined performance effect of all three functions. Results show that each control function can be related to a specific performance objective. The degree of emphasis that should be placed on each function, therefore, depends on a company’s specific performance needs. Due date setting and capacity adjustments (output control) are shown to support each other as they address different performance objectives. Meanwhile, order release (input control) is effective in reducing work-in-process and can play a role in making throughput improvements when capacity adjustments are not possible. Findings enhance existing literature on the diagnosis of delivery reliability performance in high-variety shops, with important implications for research and practice.
Journal: International Journal of Production Research
Pages: 1741-1755
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1504250
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504250
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Template-Type: ReDIF-Article 1.0
Author-Name: En-da Jiang
Author-X-Name-First: En-da
Author-X-Name-Last: Jiang
Author-Name: Ling Wang
Author-X-Name-First: Ling
Author-X-Name-Last: Wang
Title: An improved multi-objective evolutionary algorithm based on decomposition for energy-efficient permutation flow shop scheduling problem with sequence-dependent setup time
Abstract: 
 With the increasing attention on environment issues, green scheduling in manufacturing industry has been a hot research topic. As a typical scheduling problem, permutation flow shop scheduling has gained deep research, but the practical case that considers both setup and transportation times still has rare research. This paper addresses the energy-efficient permutation flow shop scheduling problem with sequence-dependent setup time to minimise both makespan as economic objective and energy consumption as green objective. The mathematical model of the problem is formulated. To solve such a bi-objective problem effectively, an improved multi-objective evolutionary algorithm based on decomposition is proposed. With decomposition strategy, the problem is decomposed into several sub-problems. In each generation, a dynamic strategy is designed to mate the solutions corresponding to the sub-problems. After analysing the properties of the problem, two heuristics to generate new solutions with smaller total setup times are proposed for designing local intensification to improve exploitation ability. Computational tests are carried out by using the instances both from a real-world manufacturing enterprise and generated randomly with larger sizes. The comparisons show that dynamic mating strategy and local intensification are effective in improving performances and the proposed algorithm is more effective than the existing algorithms.
Journal: International Journal of Production Research
Pages: 1756-1771
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1504251
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504251
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Template-Type: ReDIF-Article 1.0
Author-Name: Preetam Basu
Author-X-Name-First: Preetam
Author-X-Name-Last: Basu
Author-Name: Qindong Liu
Author-X-Name-First: Qindong
Author-X-Name-Last: Liu
Author-Name: Jan Stallaert
Author-X-Name-First: Jan
Author-X-Name-Last: Stallaert
Title: Supply chain management using put option contracts with information asymmetry
Abstract: 
 We study the problem of hedging demand uncertainty in a supply chain consisting of a risk-neutral supplier and a risk-averse retailer under a buyback contract. We use semi-variance of the possible profit values as a measure of the retailer’s risk attitude. We first study the setting where the supplier can observe the risk type of the retailer and find that in this case the supplier can design a buyback contract that extracts the maximum profit for the supplier. When the retailer’s type is unobservable, a new contract needs to be designed (the ‘option buyback contract’) and we show that in this case the retailers will self-select and chose an order quantity that maximises the total supply chain profit. Through numerical computations, we analyse the dynamics between the benefits of hedging risk, information rent and the retailer’s type, and outline cases when, depending on the shape of the reservation utilities of the retailers, it is too costly for the supplier to manage risk. In conclusion, our results show that whereas semi-variance has appealing properties as a measure of risk, its use introduces analytical challenges that can only be overcome through numerical computation.
Journal: International Journal of Production Research
Pages: 1772-1796
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1508900
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1508900
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Template-Type: ReDIF-Article 1.0
Author-Name: B. A. R. Soares
Author-X-Name-First: B. A. R.
Author-X-Name-Last: Soares
Author-Name: E. Henriques
Author-X-Name-First: E.
Author-X-Name-Last: Henriques
Author-Name: I. Ribeiro
Author-X-Name-First: I.
Author-X-Name-Last: Ribeiro
Author-Name: M. Freitas
Author-X-Name-First: M.
Author-X-Name-Last: Freitas
Title: Cost analysis of alternative automated technologies for composite parts production
Abstract: 
 Composite material usage in aircraft has been rising since the 1990s, with significant increases in manufacturing productivity and repeatability due to automation in the production of aeronautic parts made of composite materials, becoming a strong driver for widespread adoption of composites in this industry. Automated Tape Layup (ATL) and Automated Fibre Placement (AFP) are two of the most important automated manufacturing technologies within aeronautics composites, although their cost implications and economic comparison have not been widely studied. This paper presents an economic evaluation of ATL and AFP technologies. Using process-based cost models, the manufacturing process of a horizontal stabiliser is modelled, determining for each technology the associated consumption and use of resources and their implications towards the part final cost. Results show that ATL is less expensive than AFP, due to lower material costs, although with less material efficiency and slower cycle time.
Journal: International Journal of Production Research
Pages: 1797-1810
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1508903
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1508903
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Template-Type: ReDIF-Article 1.0
Author-Name: Junbo Tuo
Author-X-Name-First: Junbo
Author-X-Name-Last: Tuo
Author-Name: Fei Liu
Author-X-Name-First: Fei
Author-X-Name-Last: Liu
Author-Name: Peiji Liu
Author-X-Name-First: Peiji
Author-X-Name-Last: Liu
Title: Key performance indicators for assessing inherent energy performance of machine tools in industries
Abstract: 
 Increasing attention has been paid toward enhancing energy retrofitting in machine tools due to its enormous energy consumption and high energy-saving potential. Developing energy-efficient machine tools and selecting appropriate machine tools in procurement processes are two effective approaches for saving energy. However, existing studies on the evaluation of energy performance to support the design and selection of machine tools, rarely consider various process controls, which have considerable impact on the energy performance of machine tools. This study proposes a group of key performance indicators, which are referred to as ‘inherent energy performance’ (IEP) indexes, to support the design and selection of machine tools with the consideration of the main process controls in the usage phase and their interaction. A systematic method is introduced to acquire the IEP indexes. The method involves a simplified measurement of basic data and the calculation of the indexes from the data. A case study indicates that the proposed indicators succeed in obtaining the energy demand information of almost all machine system activities and can be used to provide basic data for developing energy information labels, selecting matching machine tools, and designing energy-efficient machine tools.
Journal: International Journal of Production Research
Pages: 1811-1824
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1508904
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1508904
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcello Braglia
Author-X-Name-First: Marcello
Author-X-Name-Last: Braglia
Author-Name: Marco Frosolini
Author-X-Name-First: Marco
Author-X-Name-Last: Frosolini
Author-Name: Mosè Gallo
Author-X-Name-First: Mosè
Author-X-Name-Last: Gallo
Author-Name: Leonardo Marrazzini
Author-X-Name-First: Leonardo
Author-X-Name-Last: Marrazzini
Title: Lean manufacturing tool in engineer-to-order environment: Project cost deployment
Abstract: 
 The present paper proposes a modified version of the Manufacturing cost deployment (MCD) method to analyse engineer-to-order (ETO) production systems. The novel approach, named Project cost deployment (PCD), introduces two substantial and innovative modifications. To begin with, the concept of manual assembly macro-activity replaces the traditional concept of station. Then, a brand-new structure for classifying and analysing losses is introduced, that is specifically defined to deal with the inefficiencies of the manual assembly tasks. The validity of the approach is proved by a real-world industrial application. The obtained results demonstrate that the PCD method allows the analyst to identify the hidden losses and to quantify the wastes from an economical point of view. In addition, PCD permits to estimate the impacts of potential (lean) improvement activities and projects in terms of both efficiency and effectiveness.
Journal: International Journal of Production Research
Pages: 1825-1839
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1508905
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1508905
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhaoxiang Chen
Author-X-Name-First: Zhaoxiang
Author-X-Name-Last: Chen
Author-Name: Yihai He
Author-X-Name-First: Yihai
Author-X-Name-Last: He
Author-Name: Yixiao Zhao
Author-X-Name-First: Yixiao
Author-X-Name-Last: Zhao
Author-Name: Xiao Han
Author-X-Name-First: Xiao
Author-X-Name-Last: Han
Author-Name: Zhen He
Author-X-Name-First: Zhen
Author-X-Name-Last: He
Author-Name: Yu Xu
Author-X-Name-First: Yu
Author-X-Name-Last: Xu
Author-Name: Anqi Zhang
Author-X-Name-First: Anqi
Author-X-Name-Last: Zhang
Title: Mission reliability evaluation based on operational quality data for multistate manufacturing systems
Abstract: 
 Modern and intelligent manufacturing systems have a prominent multistate feature. However, previous studies of reliability analysis of multistate manufacturing systems mostly focused on the basic reliability of manufacturing systems but disregarded their operating characteristics, which has hindered the development of Prognostics and Health Management technique for intelligent manufacturing systems. Therefore, an evaluation approach of mission reliability for multistate manufacturing systems based on operational quality data is proposed in this paper. First, from the systematic viewpoint of the composition and operational principle of the manufacturing system, the relationship among production task execution state, production equipment degradation state, and produced product quality state is expounded, and the connotation of the mission reliability of multistate manufacturing systems is defined. Second, an extended state task network (ESTN) is presented to organise operational quality data by considering the quality state of work in process (WIP). Third, a fusion model of operational quality data for manufacturing systems is established with the aid of the ESTN, and an operational quality data-oriented evaluation method of mission reliability is been put forward. Finally, a case study of a manufacturing system for a cylinder head is conducted to verify the proposed approach.
Journal: International Journal of Production Research
Pages: 1840-1856
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1508906
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1508906
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Reza Rasouli
Author-X-Name-First: Mohammad Reza
Author-X-Name-Last: Rasouli
Title: Intelligent process-aware information systems to support agility in disaster relief operations: a survey of emerging approaches
Abstract: 
 Agility is a key characteristic in disaster relief operations. Intelligent process-aware information systems (IPAISs) can support agility in disaster relief operations through providing information and process reach and richness to manage dynamic inter-operations. In this research, based on relevant reference architectures, a conceptual overview of an IPAIS to support agility in disaster relief operations is described. This conceptual overview includes the dynamic partnering, the collaborative process composition, the collaborative ontology management, the global workflow engine, the run-time coordination, the dynamic rule management, the run-time process proposer, and the dynamic interoperability adaptor components. Based on this conceptual overview, a systematic literature review is conducted to explore emerging approaches that can be applied to realise intelligent process-centred collaborative inter-operations to respond disasters. The findings of the conducted review show the applicability of the emerging multi-agent service-oriented modelling and analysis approaches, optimal control theory based methodologies, social network analysis techniques, data-driven inductive methods, resilient-centred approaches for robustness and agility, self-organisation mechanisms based on cyber physical systems and systems of systems perspectives, simulation methods, and trust management procedures to support the realisation of the components of an IPAIS in the context of disaster relief operations.
Journal: International Journal of Production Research
Pages: 1857-1872
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1509392
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1509392
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Template-Type: ReDIF-Article 1.0
Author-Name: Xinyu Sun
Author-X-Name-First: Xinyu
Author-X-Name-Last: Sun
Author-Name: Xin-Na Geng
Author-X-Name-First: Xin-Na
Author-X-Name-Last: Geng
Author-Name: Ji-Bo Wang
Author-X-Name-First: Ji-Bo
Author-X-Name-Last: Wang
Author-Name: Feng Liu
Author-X-Name-First: Feng
Author-X-Name-Last: Liu
Title: Convex resource allocation scheduling in the no-wait flowshop with common flow allowance and learning effect
Abstract: 
 We study the problem of two-machine no-wait flowshop scheduling with learning effect and convex resource-dependent processing times. Under the condition of the due-date assignment with common flow allowance (i.e. slack (SLK) due-date assignment), we provide a bi-criteria analysis where the first criterion is to minimise the scheduling criteria (i.e. the weighted sum of earliness, tardiness and flow allowance costs), and the second criterion is to minimise the resource consumption cost (i.e. the weighted sum of resource consumption cost). The objective is to determine the optimal job sequence, resource allocations and common (flow allowance) slack time that minimise the three different versions of the two criteria. We prove that these problems can be solved in polynomial time.
Journal: International Journal of Production Research
Pages: 1873-1891
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1510559
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1510559
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Template-Type: ReDIF-Article 1.0
Author-Name: Klaus Altendorfer
Author-X-Name-First: Klaus
Author-X-Name-Last: Altendorfer
Title: Effect of limited capacity on optimal planning parameters for a multi-item production system with setup times and advance demand information
Abstract: 
 An analytical production/inventory model to optimise the planning parameters lot-size, safety stock and planned lead time is developed for a stochastic single-stage production system with multiple items and limited capacity. Based on queuing analysis, the influence of item specific lot-sizes on the production lead time distribution is modelled. Applying stochastic advance demand information, the expected values for finished-goods-inventory, backorders and service level are explicitly stated. Numerical optimisation is applied to solve the respective cost minimisation problem and a solution heuristic is developed to support this approach. A numerical study provides managerial insights concerning capacity limitation effects on the optimal planning parameters. Higher shop loads, i.e. tighter capacity constraints, are found to significantly increase optimal lot-size and optimal safety stock. Safety stock and planned lead time are substitutes, an increase of both leads to higher FGI and lower backorders, however, the specific trade-off depends on the demand information quality. A sensitivity analysis investigating other (non-) financial system parameters is conducted as well. The main contribution of this paper is that the interaction of different planning parameters, i.e. lot-size, safety stock and planned lead time, for different items is simultaneously studied for a capacity constrained production/inventory system.
Journal: International Journal of Production Research
Pages: 1892-1913
Issue: 6
Volume: 57
Year: 2019
Month: 3
X-DOI: 10.1080/00207543.2018.1511925
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1511925
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:6:p:1892-1913




Template-Type: ReDIF-Article 1.0
Author-Name: Asma Amdouni
Author-X-Name-First: Asma
Author-X-Name-Last: Amdouni
Author-Name: Philippe Castagliola
Author-X-Name-First: Philippe
Author-X-Name-Last: Castagliola
Author-Name: Hassen Taleb
Author-X-Name-First: Hassen
Author-X-Name-Last: Taleb
Author-Name: Giovanni Celano
Author-X-Name-First: Giovanni
Author-X-Name-Last: Celano
Title: A variable sampling interval Shewhart control chart for monitoring the coefficient of variation in short production runs
Abstract: 
 Monitoring the coefficient of variation (CV) allows process monitoring to be performed when both the process mean and the standard deviation are not constant but, nevertheless, proportional. Until now, few research papers have investigated the monitoring of the CV in a short production run context. This paper investigates the design and implementation of a Variable Sampling Interval Shewhart control chart to monitor the coefficient of variation in a short production run context. Formulas for the truncated average time to signal are derived and a performance comparison is carried out with a Fixed Sampling Rate Shewhart chart monitoring the CV. An example illustrates the use of this chart on real industrial data.
Journal: International Journal of Production Research
Pages: 5521-5536
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1285076
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1285076
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Template-Type: ReDIF-Article 1.0
Author-Name: Nicole Stricker
Author-X-Name-First: Nicole
Author-X-Name-Last: Stricker
Author-Name: Fabio Echsler Minguillon
Author-X-Name-First: Fabio
Author-X-Name-Last: Echsler Minguillon
Author-Name: Gisela Lanza
Author-X-Name-First: Gisela
Author-X-Name-Last: Lanza
Title: Selecting key performance indicators for production with a linear programming approach
Abstract: 
 Modern production systems are prone to disruptions due to shorter product life cycles, growing variant diversity and progressively distributed production. At the same time, reduced time and capacity buffers diminish mitigation opportunities, requiring better tools for production control. Performance measurement with key performance indicators (KPIs) is a widely used instrument to detect changes in production system performance in order to coordinate appropriate countermeasures. The main challenge in planning KPI systems consists in determining relevant KPIs. On the one hand, enough KPIs must be selected for a sufficiently high information content. On the other hand, the cognitive abilities of users are not to be overstrained by selecting too many KPIs. This tradeoff is addressed in a proposed selection process using an integer linear programme for objective KPI selection. In order to achieve this goal, crucial facets of the information content requirement are formalised mathematically. The developed method is validated using a practical application example, showing the influence of model parameter selection on optimisation results. The formalisation of the information content is shown to be a novel and promising approach.
Journal: International Journal of Production Research
Pages: 5537-5549
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1287444
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1287444
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Template-Type: ReDIF-Article 1.0
Author-Name: Gang Chen
Author-X-Name-First: Gang
Author-X-Name-Last: Chen
Author-Name: Wen He
Author-X-Name-First: Wen
Author-X-Name-Last: He
Author-Name: Lawrence C. Leung
Author-X-Name-First: Lawrence C.
Author-X-Name-Last: Leung
Author-Name: Tian Lan
Author-X-Name-First: Tian
Author-X-Name-Last: Lan
Author-Name: Yingying Han
Author-X-Name-First: Yingying
Author-X-Name-Last: Han
Title: Assigning licenced technicians to maintenance tasks at aircraft maintenance base: a bi-objective approach and a Chinese airline application
Abstract: 
 Assigning technicians to maintenance tasks at an aircraft maintenance base is challenging and needs to consider technician licences, fairness and such operational constraints as hangar capacity and work shifts. We formulate the problem as a bi-objective optimisation model, which minimises total cost while simultaneously achieving fairness in workload allocation among different technicians. A tabu-based heuristic algorithm is developed to obtain Pareto efficient solutions. The algorithm is shown to be effective through comparison with CPLEX. A case study from a major Chinese airline demonstrates that our optimisation-based approach is applicable and beneficial to the practice. Managerial issues on maintenance workforce management are examined as well. The results show that training technicians and upgrading their licences may not be better off, and increasing the number of technicians has both favourable and unfavourable effects.
Journal: International Journal of Production Research
Pages: 5550-5563
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1296204
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1296204
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Template-Type: ReDIF-Article 1.0
Author-Name: Lijian Sun
Author-X-Name-First: Lijian
Author-X-Name-Last: Sun
Author-Name: Mingjun Ren
Author-X-Name-First: Mingjun
Author-X-Name-Last: Ren
Author-Name: Yuehong Yin
Author-X-Name-First: Yuehong
Author-X-Name-Last: Yin
Title: Domain-specific Gaussian process-based intelligent sampling for inspection planning of complex surfaces
Abstract: 
 Precision measurement of complex surfaces requires intensive sampling for fully characterising the surface geometry and reducing the measurement uncertainty, which is, however, less efficient when the data are costly to acquire. This paper presents a Gaussian process (GP)-based intelligent sampling method for achieving well balance between the measurement efficiency and accuracy. The method makes use of GP to model the surface with domain-specific composite covariance kernel functions. The statistical nature of the GP makes it capable of giving credibility to the arbitrary prediction over the entire established model which can be used in a critical criterion to perform intelligent sampling of the surfaces. The method is independent from the coordinate frames, which makes the sampling plan easily utilised without accurate pre-positioning in actual measurement. The effectiveness of the method is verified through a series of comparison study and actual application in measuring a multi-scaled complex mould insert on coordinate measuring machine.
Journal: International Journal of Production Research
Pages: 5564-5578
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1301688
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1301688
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Template-Type: ReDIF-Article 1.0
Author-Name: E. Skordilis
Author-X-Name-First: E.
Author-X-Name-Last: Skordilis
Author-Name: R. Moghaddass
Author-X-Name-First: R.
Author-X-Name-Last: Moghaddass
Title: A condition monitoring approach for real-time monitoring of degrading systems using Kalman filter and logistic regression
Abstract: 
 We present a new model for reliability analysis that is able to employ condition monitoring data in order to simultaneously monitor the latent degradation level and track failure progress over time. The method presented in this paper is a bridge between Bayesian filtering and classical binary classification, both of which have been employed successfully in various application domains. The Kalman filter is used to model a discrete-time continuous-state degradation process that is hidden and for which only indirect information is available through a multi-dimensional observation process. Logistic regression is then used to connect the latent degradation state with the failure process that is itself a discrete-space stochastic process. We present a closed-form solution for the marginal log-likelihood function and provide formulas for few important reliability measures. A dynamic cost-effective maintenance policy is finally introduced that can employ sensor signals for real-time decision-making. We finally demonstrate the accuracy and usefulness of our framework via numerical experiments.
Journal: International Journal of Production Research
Pages: 5579-5596
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1308573
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1308573
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhe Wei
Author-X-Name-First: Zhe
Author-X-Name-Last: Wei
Author-Name: Yixiong Feng
Author-X-Name-First: Yixiong
Author-X-Name-Last: Feng
Author-Name: Zhaoxi Hong
Author-X-Name-First: Zhaoxi
Author-X-Name-Last: Hong
Author-Name: Rongxia Qu
Author-X-Name-First: Rongxia
Author-X-Name-Last: Qu
Author-Name: Jianrong Tan
Author-X-Name-First: Jianrong
Author-X-Name-Last: Tan
Title: Product quality improvement method in manufacturing process based on kernel optimisation algorithm
Abstract: 
 Quality data in manufacture process has the features of mixed type, uneven distribution, dimension curse and data coupling. To apply the massive manufacturing quality data effectively to the quality analysis of the manufacture enterprise, the data pre-processing algorithm based on equivalence relation is employed to select the characteristic of hybrid data and preprocess data. KML-SVM (Optimised kernel-based hybrid manifold learning and support vector machines algorithm) is proposed. KML is adopted to solve the problems of manufacturing process quality data dimension curse. SVM is adopted to classify and predict low-dimensional embedded data, as well as to optimise support vector machine kernel function so that the classification accuracy can be maximised. The actual manufacturing process data of AVIC Shenyang Liming Aero-Engine Group Corporation Ltd is demonstrated to simulate and verify the proposed algorithm.
Journal: International Journal of Production Research
Pages: 5597-5608
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1324223
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1324223
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Template-Type: ReDIF-Article 1.0
Author-Name: Na Geng
Author-X-Name-First: Na
Author-X-Name-Last: Geng
Author-Name: Letian Chen
Author-X-Name-First: Letian
Author-X-Name-Last: Chen
Author-Name: Ran Liu
Author-X-Name-First: Ran
Author-X-Name-Last: Liu
Author-Name: Yanhong Zhu
Author-X-Name-First: Yanhong
Author-X-Name-Last: Zhu
Title: Optimal patient assignment for W queueing network in a diagnostic facility setting
Abstract: 
 Quick examination is becoming increasingly critical for the diagnosis of patients. Increasing demand and insufficient diagnostic facilities lead to longer patient waiting times. It is important for hospital managers to reduce the waiting time of high-priority patients. To reduce the patients’ waiting time, the capacity in working time is divided into special time slots for high-priority patients and regular time slots for all patients. Low-priority patients are allowed to be referred to extra time slots by overtime or using the capacity of other hospitals. Two types of patients and three types of capacities form a W queueing network. This paper proposes an average-cost Markov Decision Process (MDP) model to assign the patients to the appropriate queue with the objective of minimising the weighted waiting cost and referral penalty. Structural properties of the optimal control policy under a given capacity are proved via discount-cost MDP. Extensive numerical experiments are performed to show the efficiency of the proposed patient assignment policy and to explore the impact of different parameters on the control policy.
Journal: International Journal of Production Research
Pages: 5609-5631
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1324650
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1324650
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Template-Type: ReDIF-Article 1.0
Author-Name: Andy Wu
Author-X-Name-First: Andy
Author-X-Name-Last: Wu
Title: A supportive pricing model for suppliers with purchase order financing
Abstract: 
 Traditionally, lowering the purchase price is welcomed by a business buyer since people believe it can reduce the costs. However, it can be another story if her supplier is short of money and applies for purchase order financing to fund the production. This paper identifies the conditions under which a buyer has the motivation of allowing higher purchase price to facilitate the supplier’s loan application and consequently improve the supply availability. We use a Stackelberg model to describe the interaction between the supplier’s plan (deciding the loan amount and production input simultaneously) and the buyer’s order design (deciding the purchase price and order size jointly). We show the buyer’s optimal order design has four kinds of closed-form solutions as the supplier’s operational state follows a two-point distribution. The design choice should depend on the item value and the supplier’s reliability. In short, this research shows when to increase the purchase price and how to coordinate the order size with it. Generally speaking, if the item value is high and the supplier’s reliability is medium, a buyer allowing a premium price can ensure the supply and actually maximise her expected profit.
Journal: International Journal of Production Research
Pages: 5632-5646
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1327727
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1327727
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Template-Type: ReDIF-Article 1.0
Author-Name: Na Li
Author-X-Name-First: Na
Author-X-Name-Last: Li
Author-Name: Nan Kong
Author-X-Name-First: Nan
Author-X-Name-Last: Kong
Author-Name: Quanlin Li
Author-X-Name-First: Quanlin
Author-X-Name-Last: Li
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Evaluation of reverse referral partnership in a tiered hospital system – A queuing-based approach
Abstract: 
 Reverse referral implies referring patients from a comprehensive hospital to a community healthcare centre. In recent years, it has become popular for post-acute care in the tiered Chinese hospital system as it helps achieve more balanced utilisation between facilities at different levels. Nevertheless, it remains unclear how to implement the reverse referral partnership given the likely conflicting interests between the involved hospitals. In this paper, we evaluate a reversal referral partnership involving one hospital of each type, for which we develop queuing models for the two hospitals to capture multiple patient waits, services and transitions, with reverse referral in place. We use queuing-based performance outcomes to evaluate the profitability of each hospital and its willingness to join the partnership. We combine the above evaluations to further assess the partnership effectiveness. Through this work, we expect to provide policy insights to the government for forming hospital partnerships effectively.
Journal: International Journal of Production Research
Pages: 5647-5663
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1327731
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1327731
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Template-Type: ReDIF-Article 1.0
Author-Name: Na Li
Author-X-Name-First: Na
Author-X-Name-Last: Li
Author-Name: Xin Yu
Author-X-Name-First: Xin
Author-X-Name-Last: Yu
Author-Name: Andrea Matta
Author-X-Name-First: Andrea
Author-X-Name-Last: Matta
Title: Modelling and workload reallocation of call centres with multi-type customers
Abstract: 
 In consulting services, call centres serve several types of customers. The demand of different customers who ask for specific skills hinders the ability to balance the workload among servers; thus, task reallocation may be needed. In this paper, we model a call centre with multi-type customers as a multi-class tandem queue and examine how to reallocate the workload among servers. To evaluate the performance of the system, we propose an approximate analytical method based on the aggregation of Markov chain models. To optimally reallocate the workload, we propose a search algorithm based on the optimal computing budget allocation method. A simulation is employed to validate the analytical method and identify regions in which it can be successfully applied. A case study shows the applicability of the approach and quantifies its benefits in a realistic situation.
Journal: International Journal of Production Research
Pages: 5664-5680
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1329958
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1329958
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiawen Hu
Author-X-Name-First: Jiawen
Author-X-Name-Last: Hu
Author-Name: Zuhua Jiang
Author-X-Name-First: Zuhua
Author-X-Name-Last: Jiang
Author-Name: Haitao Liao
Author-X-Name-First: Haitao
Author-X-Name-Last: Liao
Title: Preventive maintenance of a batch production system under time-varying operational condition
Abstract: 
 This paper proposes a dynamic opportunistic preventive maintenance (PM) strategy for a production system with a time-varying batch production pattern. The operation of such a system is generic in that the operational condition (OC) varies from batch to batch and the information about the next batch can be confirmed only upon the completion of the current batch. To accommodate time-varying OC, a modified imperfect maintenance model is developed to optimise the performance of maintenance actions that can only be performed at batch-shift points. The first study presents a PM policy for a single machine with short-term production plans. Then, a multi-machine system is studied with a goal of developing an optimum dynamic opportunistic PM strategy for a group of machines at batch-shift points. Numerical examples are proceeded to illustrate the proposed maintenance strategy in practice. The result reveals that more cost will be incurred if OC is ignored. Moreover, the proposed opportunistic PM strategy achieves the lowest total cost comparing with other strategies as the system downtime cost and maintenance cost has been jointly minimised.
Journal: International Journal of Production Research
Pages: 5681-5705
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1330565
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330565
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Template-Type: ReDIF-Article 1.0
Author-Name: Hesham K. Alfares
Author-X-Name-First: Hesham K.
Author-X-Name-Last: Alfares
Author-Name: Ahmed M. Attia
Author-X-Name-First: Ahmed M.
Author-X-Name-Last: Attia
Title: A supply chain model with vendor-managed inventory, consignment, and quality inspection errors
Abstract: 
 This paper considers the integration between quality control and production inventory control in supply chain management. Specifically, we study the effect of inspection errors on the costs incurred in a supply chain system with a single vendor and multiple buyers. In this system, the vendor enters into a vendor-managed inventory (VMI) and a consignment stock (CS) partnership with several buyers. We assume that the items made by the vendor are not in perfect quality, but they contain a given proportion of defective units. We also assume that quality inspection of these items by the buyers is subject to sampling errors. Three cases indicating to different levels of supply integration are considered: VMI–CS system, traditional system and integrated system. For each case, a mathematical model is formulated, an optimum solution is developed, and a numerical example is solved.
Journal: International Journal of Production Research
Pages: 5706-5727
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1330566
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330566
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Template-Type: ReDIF-Article 1.0
Author-Name: Hong Sun
Author-X-Name-First: Hong
Author-X-Name-Last: Sun
Author-Name: Weida Chen
Author-X-Name-First: Weida
Author-X-Name-Last: Chen
Author-Name: Zhiliang Ren
Author-X-Name-First: Zhiliang
Author-X-Name-Last: Ren
Author-Name: Biyu Liu
Author-X-Name-First: Biyu
Author-X-Name-Last: Liu
Title: Optimal policy in a hybrid manufacturing/remanufacturing system with financial hedging
Abstract: 
 This paper proposes a hybrid manufacturing/remanufacturing model with the financial hedging in the case where the randomness in demand is correlated with the financial markets. The provided models are mainly for those risk-averse remanufacturers who faced with random demand and yield. The aim of this paper is to maximise remanufacturer utility by purchasing financial instruments and producing new and remanufactured products. A hybrid manufacturing/remanufacturing system production planning model is first built under mean-variance framework, and then the financial hedging is integrated into the hybrid production system. There are three main findings. First, the variance of profit with financial hedging is always less than the variance of the model without financial hedging. Second, the remanufacturer with high (low) risk aversion is more likely to produce new (remanufactured) products. Third, the model without (with) financial hedging tends to produce new (remanufactured) products unless remanufacturing cost is low (high) enough. All those findings proved that financial hedging can reduce the operational uncertainty effectively and increase the proportion of remanufacturing, which will make remanufacturing firms more economical and environmentally friendly. Therefore, remanufacturing firms can consider using financial hedging to reduce operational uncertainty.
Journal: International Journal of Production Research
Pages: 5728-5742
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1330570
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330570
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Template-Type: ReDIF-Article 1.0
Author-Name: Peng Tong
Author-X-Name-First: Peng
Author-X-Name-Last: Tong
Author-Name: Xuefeng Song
Author-X-Name-First: Xuefeng
Author-X-Name-Last: Song
Author-Name: Liu Zixian
Author-X-Name-First: Liu
Author-X-Name-Last: Zixian
Title: A maintenance strategy for two-dimensional extended warranty based on dynamic usage rate
Abstract: 
 Maintenance strategies are commonly used for repairable products or items to reduce the warranty cost in the warranty coverage. This study proposes a new warranty maintenance strategy for two-dimensional extended warranty (EW) based on dynamic usage rate. Unlike previous studies that assumed a constant usage rate, the present study regards the consumer usage rate as dynamic in the two-dimensional EW coverage. A maintenance model is constructed to determine the optimal maintenance degree of warranty claim points and help service providers accurately estimate and reduce warranty cost. A numerical example of an automobile made in China is discussed to demonstrate the effectiveness of the proposed model. The formulated model can effectively reflect the changes in the consumer usage rate and thus helps service providers develop an accurate maintenance strategy. Meanwhile, the developed model can better reduce warranty cost compared with maintenance strategies with minimal repair.
Journal: International Journal of Production Research
Pages: 5743-5759
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1330573
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330573
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Template-Type: ReDIF-Article 1.0
Author-Name: Hui-Yu Zhang
Author-X-Name-First: Hui-Yu
Author-X-Name-Last: Zhang
Author-Name: Qing-Xin Chen
Author-X-Name-First: Qing-Xin
Author-X-Name-Last: Chen
Author-Name: James MacGregor Smith
Author-X-Name-First: James MacGregor
Author-X-Name-Last: Smith
Author-Name: Ning Mao
Author-X-Name-First: Ning
Author-X-Name-Last: Mao
Author-Name: Ai-Lin Yu
Author-X-Name-First: Ai-Lin
Author-X-Name-Last: Yu
Author-Name: Zhan-Tao Li
Author-X-Name-First: Zhan-Tao
Author-X-Name-Last: Li
Title: Performance analysis of open general  queuing networks with blocking and feedback
Abstract: 
 Queuing network models have been extensively used for performance evaluation in many modern manufacturing and communication systems. The phenomenon of feedback reflects many practical situations, e.g. reworking in the production systems. However, existing research on open queuing network with feedback mainly concentrates on the models with infinite buffers or the models with finite buffers but exponentially distributed inter-arrival and service times. Research on open queuing networks with finite buffers, feedback and general inter-arrival and service times has not been reported. In this paper, a Rate Iterative Method embedded with the Generalised Expansion Method, is proposed for modelling this type of queuing network. System performance measures include the mean throughput, work-in-process and sojourn time all calculated by the proposed method. The accuracy and the efficiency of the proposed method are tested by comparing the results with other methods or simulation results from the experiments. Finally, a case study of a practical production system used in the manufacturing industry is studied and illustrates the applications of the proposed method. The results in this paper can be used as a basis for system design analysis and resource planning.
Journal: International Journal of Production Research
Pages: 5760-5781
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1334975
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1334975
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Template-Type: ReDIF-Article 1.0
Author-Name: Daniel W. Steeneck
Author-X-Name-First: Daniel W.
Author-X-Name-Last: Steeneck
Author-Name: Subhash C. Sarin
Author-X-Name-First: Subhash C.
Author-X-Name-Last: Sarin
Title: Determining end-of-life policy for recoverable products
Abstract: 
 We address a problem that arises for an original equipment manufacturer (OEM) who produces a product both in new and remanufactured forms. A remanufactured product is produced using the parts harvested from recovered products (cores) upon their disassembly, and it may contain some new parts while the excess good parts from cores are salvaged for profit. Other options are available to the OEM for handling cores that do not require disassembly. It follows that the per-unit remanufacturing cost is not constant and it may change depending on the number of recovered cores, good-part reclamation yields, and sales of remanufactured products. We present analytical results for determining an optimal solution with regard to: (i) quantity of cores to collect, (ii) end-of-life (EOL) options for the cores and (iii) product pricing of new and remanufactured products. Our analysis reveals existence of a ‘limiting part’ that dictates the number of cores to collect and a ‘key part’ that determines the number of remanufactured products to make as well as the fact that the availability of cores does not impact the EOL policy type for a product. Our analysis also enables mapping of product characteristics onto corresponding EOL policy types.
Journal: International Journal of Production Research
Pages: 5782-5800
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1334977
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1334977
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:19:p:5782-5800




Template-Type: ReDIF-Article 1.0
Author-Name: Rui Miao
Author-X-Name-First: Rui
Author-X-Name-Last: Miao
Author-Name: Qi Wu
Author-X-Name-First: Qi
Author-X-Name-Last: Wu
Author-Name: Zheng Wang
Author-X-Name-First: Zheng
Author-X-Name-Last: Wang
Author-Name: Xilin Zhang
Author-X-Name-First: Xilin
Author-X-Name-Last: Zhang
Author-Name: Yuqin Song
Author-X-Name-First: Yuqin
Author-X-Name-Last: Song
Author-Name: Hui Zhang
Author-X-Name-First: Hui
Author-X-Name-Last: Zhang
Author-Name: Qingfang Sun
Author-X-Name-First: Qingfang
Author-X-Name-Last: Sun
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Factors that influence users’ adoption intention of mobile health: a structural equation modeling approach
Abstract: 
 Mobile health represents the future trend of health care due to its great potential in improving health care efficiency, accessibility and quality. It is particularly beneficial for chronic disease patients who require long-term and regular services. To improve the products, mobile health developers need to understand patient needs, values and preferences, and assess the key factors that influence their mobile health adoption intentions. This study focuses on identifying the influential factors of patients’ adoption intention of m-Health. A structural equation model is constructed, and the confirmatory factor analysis and standard path coefficient are used to explore the key factors in chronic disease patients’ adoption process of m-Health. The results show that perceived usefulness and perceived ease of use have the strongest positive effect on patients’ adoption intention. Meanwhile, subjective norm, existing degree of satisfaction, network effect, and cost factor also influence adoption intention. Finally, the House of Quality method is used to examine the relative importance of various properties of m-Health. The Teoriya Resheniya Izobreatatelskikh Zadatch method is applied to resolve the contradictions between these properties. Our study offers important insights for mobile health developers on how to optimally design a product, thereby increasing users’ adoption intention and overall satisfaction.
Journal: International Journal of Production Research
Pages: 5801-5815
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1336681
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1336681
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Template-Type: ReDIF-Article 1.0
Author-Name: Sirong Luo
Author-X-Name-First: Sirong
Author-X-Name-Last: Luo
Author-Name: Jianrong Wang
Author-X-Name-First: Jianrong
Author-X-Name-Last: Wang
Title: A technical note on the dynamic nonstationary inventory-pricing control model with lost sale
Abstract: 
 This paper studies a non-stationary, periodic review and finite horizon dynamic inventory-pricing problem with lost sale. The existing research on this problem suffers from a lack of concavity. Thus, strong conditions have to be assumed to obtain the optimal policy, i.e. stationary system and additive demand. This paper uses multiplicative demand model, which significantly outperforms the additive demand models from statistical prediction accuracy prospect. We establish the concavity which results in the optimality of Base Stock List Price (BSLP) policy. The conditions for the concavity can be satisfied by many commonly used convex demand and distributions in the literature. Our results complement the existing research for the non-stationary lost sale models in this area.
Journal: International Journal of Production Research
Pages: 5816-5825
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1337946
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1337946
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Template-Type: ReDIF-Article 1.0
Author-Name: Alp Akcay
Author-X-Name-First: Alp
Author-X-Name-Last: Akcay
Author-Name: Canan G. Corlu
Author-X-Name-First: Canan G.
Author-X-Name-Last: Corlu
Title: Simulation of inventory systems with unknown input models: a data-driven approach
Abstract: 
 Stochastic simulation is a commonly used tool by practitioners for evaluating the performance of inventory policies. A typical inventory simulation starts with the determination of the best-fit input models (e.g. probability distribution function of the demand random variable) and then obtains a performance measure estimate under these input models. However, this sequential approach ignores the uncertainty around the input models, leading to inaccurate performance measures, especially when there is limited historical input data. In this paper, we take an alternative approach and propose a simulation replication algorithm that jointly estimates the input models and the performance measure, leading to a credible interval for the performance measure under input-model uncertainty. Our approach builds on a nonparametric Bayesian input model and frees the inventory manager from making any restrictive assumptions on the functional form of the input models. Focusing on a single-product inventory simulation, we show that the proposed method improves the estimation of the service levels when compared to the traditional practice of using the best-fit or the empirical distribution as the unknown demand distribution.
Journal: International Journal of Production Research
Pages: 5826-5840
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1343503
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1343503
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:19:p:5826-5840




Template-Type: ReDIF-Article 1.0
Author-Name: Yihai He
Author-X-Name-First: Yihai
Author-X-Name-Last: He
Author-Name: Changchao Gu
Author-X-Name-First: Changchao
Author-X-Name-Last: Gu
Author-Name: Zhaoxiang Chen
Author-X-Name-First: Zhaoxiang
Author-X-Name-Last: Chen
Author-Name: Xiao Han
Author-X-Name-First: Xiao
Author-X-Name-Last: Han
Title: Integrated predictive maintenance strategy for manufacturing systems by combining quality control and mission reliability analysis
Abstract: 
 Predictive maintenance (PdM) is an effective means to eliminate potential failures, ensure stable equipment operation and improve the mission reliability of manufacturing systems and the quality of products, which is the premise of intelligent manufacturing. Therefore, an integrated PdM strategy considering product quality level and mission reliability state is proposed regarding the intelligent manufacturing philosophy of ‘prediction and manufacturing’. First, the key process variables are identified and integrated into the evaluation of the equipment degradation state. Second, the quality deviation index is defined to describe the quality of the product quantitatively according to the co-effect of manufacturing system component reliability and product quality in the quality–reliability chain. Third, to achieve changeable production task demands, mission reliability is defined to characterise the equipment production states comprehensively. The optimal integrated PdM strategy, which combines quality control and mission reliability analysis, is obtained by minimising the total cost. Finally, a case study on decision-making with the integrated PdM strategy for a cylinder head manufacturing system is presented to validate the effectiveness of the proposed method. The final results shows that proposed method achieves approximately 26.02 and 20.54% cost improvement over periodic preventive maintenance and conventional condition-based maintenance respectively.
Journal: International Journal of Production Research
Pages: 5841-5862
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1346843
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346843
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Template-Type: ReDIF-Article 1.0
Author-Name: G. Nenes
Author-X-Name-First: G.
Author-X-Name-Last: Nenes
Author-Name: Y. Nikolaidis
Author-X-Name-First: Y.
Author-X-Name-Last: Nikolaidis
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 5863-5863
Issue: 19
Volume: 55
Year: 2017
Month: 10
X-DOI: 10.1080/00207543.2017.1346944
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346944
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Template-Type: ReDIF-Article 1.0
Author-Name: Shasha Wang
Author-X-Name-First: Shasha
Author-X-Name-Last: Wang
Author-Name: Mary Kurz
Author-X-Name-First: Mary
Author-X-Name-Last: Kurz
Author-Name: Scott Jennings Mason
Author-X-Name-First: Scott Jennings
Author-X-Name-Last: Mason
Author-Name: Eghbal Rashidi
Author-X-Name-First: Eghbal
Author-X-Name-Last: Rashidi
Title: Two-stage hybrid flow shop batching and lot streaming with variable sublots and sequence-dependent setups
Abstract: 
 A paint manufacturing firm's customers typically place orders for two or more products simultaneously. Each product belongs to a family that denotes batching compatibility during manufacturing. Further, products can be split into several sublots to allow overlapping production in a two-stage hybrid flow shop wherein various identical, capacitated machines operate in parallel at each stage. We present a mixed-integer linear program (MILP) for this integrated batching and lot streaming problem with variable sublots, incompatible job families, and sequence-dependent setup times. The model determines the number and size of sublots for each product and the production sequencing for each sublot such that the total weighted completion time is minimised. To promote practical implementation, we develop and evaluate heuristics to efficiently solve this problem.
Journal: International Journal of Production Research
Pages: 6893-6907
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1571251
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1571251
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:22:p:6893-6907




Template-Type: ReDIF-Article 1.0
Author-Name: Dimitris Mourtzis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Mourtzis
Author-Name: Sophia Fotia
Author-X-Name-First: Sophia
Author-X-Name-Last: Fotia
Author-Name: Nikoletta Boli
Author-X-Name-First: Nikoletta
Author-X-Name-Last: Boli
Author-Name: Ekaterini Vlachou
Author-X-Name-First: Ekaterini
Author-X-Name-Last: Vlachou
Title: Modelling and quantification of industry 4.0 manufacturing complexity based on information theory: a robotics case study
Abstract: 
 The new industrial revolution called Industry 4.0 imposes new challenges to the research community. One of the main issues in Industry 4.0 is the management of the huge amount of information exchanged among its different integrated systems. The present work demonstrates how the traditional manufacturing system is transformed to the Industry 4.0 manufacturing system and proposes a modelling and quantification approach, which includes metrics from the Information Theory estimating the complexity and the capacity of the Industry 4.0, from the perspective of the communication among the systems. The application impact of the proposed Industry 4.0 system and the comparison of these metrics before and after shifting to Industry 4.0 is also analysed and validated in a case study from the Robotics Industry.
Journal: International Journal of Production Research
Pages: 6908-6921
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1571686
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1571686
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:22:p:6908-6921




Template-Type: ReDIF-Article 1.0
Author-Name: Jun-qing Li
Author-X-Name-First: Jun-qing
Author-X-Name-Last: Li
Author-Name: Shun-Chang Bai
Author-X-Name-First: Shun-Chang
Author-X-Name-Last: Bai
Author-Name: Pei-yong Duan
Author-X-Name-First: Pei-yong
Author-X-Name-Last: Duan
Author-Name: Hong-yan Sang
Author-X-Name-First: Hong-yan
Author-X-Name-Last: Sang
Author-Name: Yu-yan Han
Author-X-Name-First: Yu-yan
Author-X-Name-Last: Han
Author-Name: Zhi-xin Zheng
Author-X-Name-First: Zhi-xin
Author-X-Name-Last: Zheng
Title: An improved artificial bee colony algorithm for addressing distributed flow shop with distance coefficient in a prefabricated system
Abstract: 
 This paper proposes an improved artificial bee colony (IABC) algorithm for addressing the distributed flow shop considering the distance coefficient found in precast concrete production system, with the minimisation of the makespan. In the proposed algorithm, each solution is first represented by a two-dimensional vector, where the first dimensional vector is the factory and the second dimensional vector lists the operation scheduling sequence of each factory. Second, considering the distributed problem feature, a distributed iterated greedy heuristic (DIG) is developed where destruction and construction processes are designed in detail while considering the distributed structures. Third, an efficient population initialisation method that considers the factory workload balance is presented. Then, a local search approach that randomly replaces two factories with two randomly selected jobs and that finds an optimal position for the two inserted operations via the DIG method is proposed. For the canonical ABC algorithm, using the DIG approach, the main three parts are improved, namely, the employee, onlooker, and scout bees. Finally, the proposed algorithm is tested on sets of extended instances based on the well-known benchmarks. Through an analysis of the experimental results, the highly effective proposed IABC algorithm is compared to several efficient algorithms drawn from the literature.
Journal: International Journal of Production Research
Pages: 6922-6942
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1571687
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1571687
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Template-Type: ReDIF-Article 1.0
Author-Name: Vijaya Dixit
Author-X-Name-First: Vijaya
Author-X-Name-Last: Dixit
Author-Name: Atanu Chaudhuri
Author-X-Name-First: Atanu
Author-X-Name-Last: Chaudhuri
Author-Name: Rajiv Kumar Srivastava
Author-X-Name-First: Rajiv Kumar
Author-X-Name-Last: Srivastava
Title: Assessing value of customer involvement in engineered-to-order shipbuilding projects using fuzzy set and rough set theories
Abstract: 
 Customer involvement plays a crucial role in engineered-to-order (ETO) projects. The present study investigates the involvement of customers, with thorough technical knowledge, as resources and co-producers. The study also analyses the impact of customer involvement in sourcing decisions and project execution on project performance (PP) of ETO shipbuilding projects by considering project and customer characteristics. The contributions of this study to the current body of knowledge on customer involvement in ETO projects are twofold. First, it demonstrates that customer involvement at different stages of shipbuilding projects have differential impacts on PP. Customer involvement in sourcing decisions during the early stages of the project has a positive impact, whereas involvement in project execution during the later stages of the project has a negative impact on PP. Second, it reveals that project complexity and customer type together significantly affect the PP. Therefore, the role of project complexity and customer type as potential contingent factors in explaining PP is emphasised. This study also makes a significant methodological contribution by demonstrating the use of fuzzy inference system and rough set theory to analyse qualitative inputs from interviews, when conducting surveys is not possible.
Journal: International Journal of Production Research
Pages: 6943-6962
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1572928
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1572928
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:22:p:6943-6962




Template-Type: ReDIF-Article 1.0
Author-Name: Rahma Lahyani
Author-X-Name-First: Rahma
Author-X-Name-Last: Lahyani
Author-Name: Anne-Lise Gouguenheim
Author-X-Name-First: Anne-Lise
Author-X-Name-Last: Gouguenheim
Author-Name: Leandro C. Coelho
Author-X-Name-First: Leandro C.
Author-X-Name-Last: Coelho
Title: A hybrid adaptive large neighbourhood search for multi-depot open vehicle routing problems
Abstract: 
 In this paper we address the multi-depot open vehicle routing problem (MDOVRP), a complex and difficult problem arising in several real-life applications. In the MDOVRP vehicles start from several depots and do not need to return to the depot at the end of their routes. We propose a hybrid adaptive large neighbourhood search algorithm to solve the MDOVRP coupled with improvement procedures yielding a hybrid metaheuristic. The performance of the proposed metaheuristic is assessed on various benchmark instances proposed for this problem and its special cases, containing up to 48 customers (single-depot version) and up to six depots and 288 customers. The computational results indicate that the proposed algorithm is very competitive compared with the state-of-the-art methods and improves 15 best-known solutions for multi-depot instances and one best-known solution for a single-depot instance. A detailed sensitivity analysis highlights which components of the metaheuristic contribute most to the solution quality.
Journal: International Journal of Production Research
Pages: 6963-6976
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1572929
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1572929
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:22:p:6963-6976




Template-Type: ReDIF-Article 1.0
Author-Name: Thomas Frandsen
Author-X-Name-First: Thomas
Author-X-Name-Last: Frandsen
Author-Name: Sofie Østergaard Boa
Author-X-Name-First: Sofie Østergaard
Author-X-Name-Last: Boa
Author-Name: Jawwad Z. Raja
Author-X-Name-First: Jawwad Z.
Author-X-Name-Last: Raja
Title: Pricing structures for solutions: an exploratory study within the oil and gas industry
Abstract: 
 A growing number of companies have begun to realise the potential for differentiating their product offerings by integrating services to provide customised solutions. Although there is now an extensive and growing literature on this trend, researchers have only recently begun to consider the pricing structures for such solutions. To address this shortcoming, the present study adopts an exploratory case-based approach to investigate a buyer (drilling contractor) and two suppliers of offshore capital equipment, each of whom provides condition-based maintenance solutions for offshore drilling units in the upstream oil and gas industry. The findings of the study identify a number of underlying mechanisms for solution offerings (i.e. innovativeness, benchmarking alternatives, measurability, replicability and operational risk) that are important considerations in the process of determining appropriate pricing structures based on the buyer’s business model, procurement practices and maintenance strategy vis-à-vis the supplier’s capabilities and the buyer–supplier relationship. The present study contributes to the literature by providing empirical evidence on and insight into the complexity of determining the pricing structure for solution offerings from the perspective of the supplier as well as the buyer.
Journal: International Journal of Production Research
Pages: 6977-6992
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1572933
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1572933
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:22:p:6977-6992




Template-Type: ReDIF-Article 1.0
Author-Name: Elia Balugani
Author-X-Name-First: Elia
Author-X-Name-Last: Balugani
Author-Name: Francesco Lolli
Author-X-Name-First: Francesco
Author-X-Name-Last: Lolli
Author-Name: Rita Gamberini
Author-X-Name-First: Rita
Author-X-Name-Last: Gamberini
Author-Name: Bianca Rimini
Author-X-Name-First: Bianca
Author-X-Name-Last: Rimini
Author-Name: M. Z. Babai
Author-X-Name-First: M. Z.
Author-X-Name-Last: Babai
Title: A periodic inventory system of intermittent demand items with fixed lifetimes
Abstract: 
 Perishable items with a limited lifespan and intermittent/erratic consumption are found in a variety of industrial settings: dealing with such items is challenging for inventory managers. In this study, a periodic inventory control system is analysed, in which items are characterised by intermittent demand and known expiration dates. We propose a new inventory management method, considering both perishability and intermittency constraints. The new method is a modification of a method proposed in the literature, which uses a periodic order-up-to-level inventory policy and a compound Bernoulli demand. We derive the analytical expression of the fill rate and propose a computational procedure to calculate the optimal solution. A comparative numerical analysis is conducted to evaluate the performance of the proposed solution against the standard inventory control method, which does not take into account perishability. The proposed method leads to a bias that is only affected by demand size, in contrast to the standard method which is impacted by more severe biases driven by intermittence and periods before expiration.
Journal: International Journal of Production Research
Pages: 6993-7005
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1572935
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1572935
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:22:p:6993-7005




Template-Type: ReDIF-Article 1.0
Author-Name: H. Grillo
Author-X-Name-First: H.
Author-X-Name-Last: Grillo
Author-Name: M.M.E. Alemany
Author-X-Name-First: M.M.E.
Author-X-Name-Last: Alemany
Author-Name: A. Ortiz
Author-X-Name-First: A.
Author-X-Name-Last: Ortiz
Author-Name: B. De Baets
Author-X-Name-First: B.
Author-X-Name-Last: De Baets
Title: Possibilistic compositions and state functions: application to the order promising process for perishables
Abstract: 
 In this paper, we propose the concepts of the composition of possibilistic variables and state functions. While in conventional compositional data analysis, the interdependent components of a deterministic vector must add up to a specific quantity, we consider such components as possibilistic variables. The concept of state function is intended to describe the state of a dynamic variable over time. If a state function is used to model decay in time, it is called the ageing function. We present a practical implementation of our concepts through the development of a model for a supply chain planning problem, specifically the order promising process for perishables. We use the composition of possibilistic variables to model the existence of different non-homogeneous products in a lot (sub-lots with lack of homogeneity in the product), and the ageing function to establish a shelf life-based pricing policy. To maintain a reasonable complexity and computational efficiency, we propose the procedure to obtain an equivalent interval representation based on α-cuts, allowing to include both concepts by means of linear mathematical programming. Practical experiments were conducted based on data of a Spanish supply chain dedicated to pack and distribute oranges and tangerines. The results validated the functionality of both, the compositions of possibilistic variables and ageing functions, showing also a very good performance in terms of the interpretation of a real problem with a good computational performance.
Journal: International Journal of Production Research
Pages: 7006-7031
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1574039
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1574039
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Template-Type: ReDIF-Article 1.0
Author-Name: Jinho Shin
Author-X-Name-First: Jinho
Author-X-Name-Last: Shin
Author-Name: Dean Grosbard
Author-X-Name-First: Dean
Author-X-Name-Last: Grosbard
Author-Name: James R. Morrison
Author-X-Name-First: James R.
Author-X-Name-Last: Morrison
Author-Name: Adar Kalir
Author-X-Name-First: Adar
Author-X-Name-Last: Kalir
Title: Decomposition without aggregation for performance approximation in queueing network models of semiconductor manufacturing
Abstract: 
 Accurate and speedy forecasts of production cycle time are key components that support the operation of modern semiconductor wafer fabricators. Estimates of cycle time can be obtained via simulation, but such an approach, though common, requires significant computational investment and model maintenance. Queueing network models and approximations for their performance can provide a viable alternative. As modern semiconductor manufacturing systems exhibit largely reentrant product routing, but contain essential probabilistic routes (for metrology and rework), prior mean cycle time approximation methods are not well suited to the system structure. In this paper, we extend the decomposition without aggregation (DWOA) approach – which is tailored to systems with deterministic routing – to allow for the existence of probabilistic paths. Numerical and simulation studies are conducted with numerous practically inspired datasets to assess the quality of the resulting mean cycle time approximations. The results reveal that our approach outperforms the existing mean cycle time approximations on datasets inspired by the semiconductor industry MIMAC benchmark datasets. For example, in MIMAC dataset 1, our mean cycle time approximations exhibit an average of 10.33% error compared to 18.82% error for existing approaches.
Journal: International Journal of Production Research
Pages: 7032-7045
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1574041
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1574041
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Template-Type: ReDIF-Article 1.0
Author-Name: Chunguang Bai
Author-X-Name-First: Chunguang
Author-X-Name-Last: Bai
Author-Name: Simonov Kusi-Sarpong
Author-X-Name-First: Simonov
Author-X-Name-Last: Kusi-Sarpong
Author-Name: Hadi Badri Ahmadi
Author-X-Name-First: Hadi
Author-X-Name-Last: Badri Ahmadi
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: Social sustainable supplier evaluation and selection: a group decision-support approach
Abstract: 
 Organisational and managerial decisions are influenced by corporate sustainability pressures. Organisations need to consider economic, environmental and social sustainability dimensions in their decisions to become sustainable. Supply chain decisions play a distinct and critical role in organisational good and service outputs sustainability. Sustainable supplier selection influences the supply chain sustainability allowing many organisations to build competitive advantage. Within this context, the social sustainability dimension has received relatively minor investigation; with emphasis typically on economic and environmental sustainability. Neglecting social sustainability can have serious repercussions for organisational supply chains. This study proposes a social sustainability attribute decision framework to evaluate and select socially sustainable suppliers. A grey-based multi-criteria decision-support tool composed of the ‘best-worst method’ (BWM) and TODIM (TOmada de Decisão Interativa e Multicritério – in Portuguese ‘Interactive and Multicriteria Decision Making’) is introduced. A grey-BWM approach is used to determine social sustainability attribute weights, and a grey-TODIM method is utilised to rank suppliers. This process is completed in a group decision setting. A case study of an Iranian manufacturing company is used to exemplify the applicability and suitability of the proposed social sustainability decision framework. Managerial implications, limitations, and future research directions are introduced after the application of the model.
Journal: International Journal of Production Research
Pages: 7046-7067
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1574042
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1574042
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian-Wu Bi
Author-X-Name-First: Jian-Wu
Author-X-Name-Last: Bi
Author-Name: Yang Liu
Author-X-Name-First: Yang
Author-X-Name-Last: Liu
Author-Name: Zhi-Ping Fan
Author-X-Name-First: Zhi-Ping
Author-X-Name-Last: Fan
Author-Name: Erik Cambria
Author-X-Name-First: Erik
Author-X-Name-Last: Cambria
Title: Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model
Abstract: 
 With the rapid advances in information technology, an increasing number of online reviews are posted daily on the Internet. Such reviews can serve as a promising data source to understand customer satisfaction. To this end, in this paper, we proposed a method for modelling customer satisfaction from online reviews. In the method, customer satisfaction dimensions (CSDs) are first extracted from online reviews based on latent dirichlet allocation (LDA). The sentiment orientations of the extracted CSDs are identified using a support vector machine (SVM). Then, considering the existence of complex relationships among different CSDs and the customer satisfaction, an ensemble neural network based model (ENNM) is proposed to measure the effects of customer sentiments toward different CSDs on customer satisfaction. On this basis, to identify the category of each CSD from the customer’s perspective, an effect-based Kano model (EKM) is proposed. Finally, an empirical study, which consists of two parts (phones and cameras), is given to illustrate the effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 7068-7088
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1574989
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1574989
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Template-Type: ReDIF-Article 1.0
Author-Name: Igor Lazov
Author-X-Name-First: Igor
Author-X-Name-Last: Lazov
Title: Risk-based analysis of manufacturing systems
Abstract: 
 A manufacturing system considered here consists of a machine that processes parts and an automatic conveyor that transports immediately a finished part to an assembly cell (i.e. a single workstation facility is examined). The system can hold a maximum number of processed parts on the conveyor, which determines its size. Modelling the system as a family of Birth–Death Processes with finite size in equilibrium, indexed by the system utilisation parameter, and depending on the concepts of system information and system entropy (i.e. mean information), we promote a risk-based analysis of manufacturing systems. The current number of processed parts on the conveyor determines the system particular states. The performance measures of a system are: risk (i.e. uncertainty) of the system (represented by system entropy), throughput of the system, utilisation of the machine, utilisation of the conveyor, and information range of the system. They are simultaneously investigated with respect to the system utilisation parameter, in order for an optimal trade-off among them to be established. This analysis is illustrated on the information linear, Erlang, Binomial and Pascal held manufacturing systems. Regarding the managerial insights, a use case of a system target output is considered, comparing the above system types. This approach can also be used for analysis of an assembly line consisting of multiple machines that have different operation times and buffers between them.
Journal: International Journal of Production Research
Pages: 7089-7103
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1577564
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1577564
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhiwen Liu
Author-X-Name-First: Zhiwen
Author-X-Name-Last: Liu
Author-Name: Xinguo Ming
Author-X-Name-First: Xinguo
Author-X-Name-Last: Ming
Title: A framework with revised rough-DEMATEL to capture and evaluate requirements for smart industrial product-service system of systems
Abstract: 
 Smart industrial product-service system of systems (SiP-S3) is a new extension of industrial PSS via smart technology and SoS (system of systems) engineering. A framework with revised rough-DEMATEL method is proposed to capture and evaluate requirements for SiP-S3. From the various interactions in value stream mapping of SiP-S3, business, functional and non-functional requirements can be captured and converged into SiP-S3 requirements. Due to the interrelation between requirements of SiP-S3 and uncertainty of expert judgments, rough-DEMATEL is adopted but is revised in two aspects. Generally, SiP-S3 requirement items are plentiful, a set of programming code for rough set approximation is firstly given to reduce manual calculation burden. Moreover, compared to multiple operators of modified-CFCS (converting fuzzy values into crisp scores) plus SVL (single vector-length), a feasible and simpler operator of AVL (average vector-length) on rough-prominence and rough-relation is firstly devised to prioritise requirements. As such, roughness can be remained till at the end of calculation procedure to avoid uncertain assessment information loss. Surface mount technology (SMT) is not trivial in electronic manufacturing service industry, an illustrative case study of SMTE-S3 (SMT equipment-service system of systems) is demonstrated to verify feasibility and potential of proposal methodological framework.
Journal: International Journal of Production Research
Pages: 7104-7122
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1577566
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1577566
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Template-Type: ReDIF-Article 1.0
Author-Name: Jooh Lee
Author-X-Name-First: Jooh
Author-X-Name-Last: Lee
Author-Name: He-Boong Kwon
Author-X-Name-First: He-Boong
Author-X-Name-Last: Kwon
Title: The synergistic effect of environmental sustainability and corporate reputation on market value added (MVA) in manufacturing firms
Abstract: 
 This study is an attempt to explore the predictive effect, in terms of operational capability, of a large manufacturing firm’s environmental greening efforts carried out in the interest of sustainability, and of the firm’s reputation for social responsibility. Through both a traditional and a new, innovative approach, this study investigates the potential synergistic effect of environmental sustainability and the improvement of corporate reputation on a firm’s market performance in terms of shareholders’ equity value (market value added, or MVA) when taken together with the firm’s other key differential business factors. The findings of this study provide notable implications that establish the integrative paradigm for the influence of environmental greening sustainability on firm performance through the use of an innovative methodological approach regardless of a priori theoretical assumptions. Through this, the impact of environmental sustainability and corporate reputation, as well as their synergistic effect, on firm performance push forward a new foundation in business practice. The major findings and new methodological approach (Back-Propagation Neural Networks; BPNN) in this study will open a broad new spectrum of opportunities for further research on these topical issues.
Journal: International Journal of Production Research
Pages: 7123-7141
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1578430
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1578430
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Template-Type: ReDIF-Article 1.0
Author-Name: Urszula Boryczka
Author-X-Name-First: Urszula
Author-X-Name-Last: Boryczka
Author-Name: Krzysztof Szwarc
Author-X-Name-First: Krzysztof
Author-X-Name-Last: Szwarc
Title: Selected variants of a Memetic Algorithm for JSP – a comparative study
Abstract: 
 The article aims to address a research gap concerning the adequate configuration of a Memetic Algorithm adapted to solve the Job-Shop Scheduling Problem. The goal was accomplished by means of conducting a comparative study of 16 variants of a Memetic Algorithm, characterised with different places of hybridisation and local search methods applied. The study involved the solution of eleven instances of JSP and the comparison of the results with the results achieved with an Evolutionary Algorithm lacking the mechanism of hybridisation and selected local search methods. The utilitarian significance of the problem also involved the use of assessment measures intended for both practical applications and research purposes.
Journal: International Journal of Production Research
Pages: 7142-7157
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1581385
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1581385
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Template-Type: ReDIF-Article 1.0
Author-Name: Jing Huang
Author-X-Name-First: Jing
Author-X-Name-Last: Huang
Author-Name: Wensheng Yang
Author-X-Name-First: Wensheng
Author-X-Name-Last: Yang
Author-Name: Yiliu Tu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Tu
Title: Supplier credit guarantee loan in supply chain with financial constraint and bargaining
Abstract: 
 This paper adopts a multiunit bilateral bargaining framework on financial decision. In a two-echelon supply chain, the supplier sells products through a financial constraint retailer. If needed, the retailer gets a short-term financing from a bank by supplier credit guarantee loan (CGL). Through applying the Nash bargaining framework, we formulate two-level game models, i.e. Retailer-Supply System negotiation and Supplier-Bank negotiation. In this paper, we study and discuss the equilibrium order quantity which is affected by initial working capital and interest rate, the retailer-supply system negotiation and upstream wholesale price effects for supply chain performance, the supplier-bank negotiation and interest rate decisions with different capital markets. The results show: (i) there exists loan size limit for financial constraint retailer under CGL. (ii) The upstream wholesale price increase will weaken retailer’s bargaining position, and the supply system may gain or lose depending on the bargaining power. (iii) There exists unique equilibrium sharing ratio in supply system, which means CGL can achieve risk sharing. (iv) Within a supply system, the upstream wholesale price advantage will weaken bank’s profit, whereas supplier may gain or lose depending on his bargaining power.
Journal: International Journal of Production Research
Pages: 7158-7173
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1581386
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1581386
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Template-Type: ReDIF-Article 1.0
Author-Name: Abolfazl Rezaei Aderiani
Author-X-Name-First: Abolfazl
Author-X-Name-Last: Rezaei Aderiani
Author-Name: Kristina Wärmefjord
Author-X-Name-First: Kristina
Author-X-Name-Last: Wärmefjord
Author-Name: Rikard Söderberg
Author-X-Name-First: Rikard
Author-X-Name-Last: Söderberg
Author-Name: Lars Lindkvist
Author-X-Name-First: Lars
Author-X-Name-Last: Lindkvist
Title: Developing a selective assembly technique for sheet metal assemblies
Abstract: 
 Applying the concept of Digital Twin in production processes supports the manufacturing of products of optimal geometry quality. This concept can be further supported by a strategy of finding the optimal combination of individual parts to maximise the geometrical quality of the final product, known as selective assembly technique. However, application of this technique has been limited to assemblies where the final dimensions are just function of the mating parts' dimensions and this is not applicable in sheet metal assemblies. This paper develops a selective assembly technique for sheet metal assemblies and investigates the effect of batch size on the improvements. The presented method utilises a variation simulation tool (Computer-Aided Tolerancing tool) and an optimisation algorithm to find the optimal combination of the mating parts. The approach presented is applied to three industrial cases of sheet metal assemblies. The results show that using this technique leads to a considerable reduction of the final geometrical variation and mean deviation for these kinds of assemblies. Moreover, increasing the batch size reduces the amount of achievable improvement in variation but increases the amount of achievable improvement in the mean deviation.
Journal: International Journal of Production Research
Pages: 7174-7188
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1581387
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1581387
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Template-Type: ReDIF-Article 1.0
Author-Name: Mattia Bianchi
Author-X-Name-First: Mattia
Author-X-Name-Last: Bianchi
Author-Name: Giacomo Marzi
Author-X-Name-First: Giacomo
Author-X-Name-Last: Marzi
Author-Name: Lamberto Zollo
Author-X-Name-First: Lamberto
Author-X-Name-Last: Zollo
Author-Name: Andrea Patrucco
Author-X-Name-First: Andrea
Author-X-Name-Last: Patrucco
Title: Developing software beyond customer needs and plans: an exploratory study of its forms and individual-level drivers
Abstract: 
 Excessive software development is the tendency to develop new software above and beyond the requirements of the market and/or planned specifications. It is a widespread phenomenon involving both risks and flexibility advantages. As it represents a challenging dilemma for software developers, it is important to study its human origins. Drawing on the tripartite model of individual attitudes, this study investigates the influence of developers’s cognitive (intuitive and rational thinking styles), affective (emotional attachment) and behavioural (reliance on past experiences) traits on two forms of excess, beyond needs and beyond plans. Using survey data on 307 software developers, this study shows that different manifestations of excess are associated with distinct traits of software developers. Emotional attachment drives beyond needs excess. A positive (negative) association is found between relying on past experiences and beyond needs excess (beyond plans excess). An intuitive cognitive style fosters the inclusion of extra features in the new product scope, whereas a rational style might lead to developing one-size-fits-all software that targets the needs of a broad user base. These findings contribute to research on the development of digital new products and production technologies by offering a comprehensive yet fine-grained picture of excessive software development’s nature and drivers.
Journal: International Journal of Production Research
Pages: 7189-7208
Issue: 22
Volume: 57
Year: 2019
Month: 11
X-DOI: 10.1080/00207543.2019.1581953
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1581953
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Template-Type: ReDIF-Article 1.0
Author-Name: Qingkai Ji
Author-X-Name-First: Qingkai
Author-X-Name-Last: Ji
Author-Name: Lijun Sun
Author-X-Name-First: Lijun
Author-X-Name-Last: Sun
Author-Name: Xiangpei Hu
Author-X-Name-First: Xiangpei
Author-X-Name-Last: Hu
Author-Name: Jing Hou
Author-X-Name-First: Jing
Author-X-Name-Last: Hou
Title: Optimal policies of a two-echelon serial inventory system with general limited capacities
Abstract: 
 We study optimal policies of capacitated two-echelon serial inventory systems under periodic review. For a system with smaller downstream capacity, we fully characterise the optimal policy as a further modified echelon base stock policy using an intuitive backward induction. The key lies in the magnitude relation between the initial upstream stock level and the downstream capacity. For a system with smaller upstream capacity, we demonstrate that the optimal policy is of a more complex structure where there can be at most four/five target levels up to which the upstream/downstream echelon tries to produce/order. The numbers of levels and their values depend on the length of remaining horizons and the amount of initial upstream inventories. We also specify these potential target levels and then suggest a way to simplify the search of optimal solutions.
Journal: International Journal of Production Research
Pages: 6142-6155
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1015752
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1015752
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Template-Type: ReDIF-Article 1.0
Author-Name: Wen-Chyuan Chiang
Author-X-Name-First: Wen-Chyuan
Author-X-Name-Last: Chiang
Author-Name: Timothy L. Urban
Author-X-Name-First: Timothy L.
Author-X-Name-Last: Urban
Author-Name: Chunyong Luo
Author-X-Name-First: Chunyong
Author-X-Name-Last: Luo
Title: Balancing stochastic two-sided assembly lines
Abstract: 
 In a two-sided assembly line, tasks can be executed simultaneously on both sides of the line. One task cannot be started until both of its direct predecessors on the left and right sides are completed. Therefore, the start time of the task is the maximum of the two predecessors’ finish times. In many realistic situations, it is assumed that the task times are independent and normally distributed with known means and variances. However, the maximum of two normal variables is not normally distributed, but can be well approximated by results from extreme value theory. In this paper, we utilise these results to develop a solution methodology to balance two-sided assembly lines with stochastic task times, minimising the line length and the number of stations while guaranteeing all tasks are completed within the cycle time with a given confidence level.
Journal: International Journal of Production Research
Pages: 6232-6250
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1029084
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1029084
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Template-Type: ReDIF-Article 1.0
Author-Name: Tanja Mlinar
Author-X-Name-First: Tanja
Author-X-Name-Last: Mlinar
Author-Name: Philippe Chevalier
Author-X-Name-First: Philippe
Author-X-Name-Last: Chevalier
Title: Dynamic admission control for two customer classes with stochastic demands and strict due dates
Abstract: 
 We study a dynamic capacity allocation problem with admission control decisions of a company that caters for two demand classes with random arrivals, capacity requirements and strict due dates. We formulate the problem as a Markov decision process (MDP) in order to find the optimal admission control policy that maximises the expected profit of the company. Such a formulation suffers a state-space explosion. Moreover, it involves an additional dimension arising from the multiple possible order sizes that customers can request which further increases the complexity of the problem. To reduce the cardinality of possible policies, and, thus, the computational requirements, we propose a threshold-based policy. We formulate an MDP to generate such a policy. To deal with the curse of dimensionality, we develop threshold-based approximate algorithms based on the state-reduction heuristics with aggregation proposed previously. Our results reveal that for the majority of instances considered the optimal policy has a threshold structure. We then demonstrate the superiority of the proposed threshold-based approximate algorithms over two benchmark policies in terms of the generated profits and the robustness of the solutions to changes in operational conditions. Finally, we show that our proposed policies are also robust to changes in actual demand from its estimation.
Journal: International Journal of Production Research
Pages: 6156-6173
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1055846
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1055846
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Template-Type: ReDIF-Article 1.0
Author-Name: Rong Yuan
Author-X-Name-First: Rong
Author-X-Name-Last: Yuan
Author-Name: Stephen C. Graves
Author-X-Name-First: Stephen C.
Author-X-Name-Last: Graves
Title: Setting optimal production lot sizes and planned lead times in a job shop
Abstract: 
 In this research, we model a job shop that produces a set of discrete parts in a make-to-stock setting. The intent of the research is to develop a planning model to determine the optimal tactical policies that minimise the relevant manufacturing costs subject to workload variability and capacity limits. We consider two tactical decisions, namely the production lot size for each part and the planned lead time for each work station. We model the relevant manufacturing costs, entailing production overtime costs and inventory-related costs, as functions of these tactical decisions. We formulate a non-linear optimisation model and implement it in the Excel spreadsheet. We test the model with actual factory data from our research sponsor. The results are consistent with our intuition and demonstrate the potential value from jointly optimising over these tactical policies.
Journal: International Journal of Production Research
Pages: 6105-6120
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1073859
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1073859
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Template-Type: ReDIF-Article 1.0
Author-Name: S. Otten
Author-X-Name-First: S.
Author-X-Name-Last: Otten
Author-Name: R. Krenzler
Author-X-Name-First: R.
Author-X-Name-Last: Krenzler
Author-Name: H. Daduna
Author-X-Name-First: H.
Author-X-Name-Last: Daduna
Title: Models for integrated production-inventory systems: steady state and cost analysis
Abstract: 
 We consider a two-echelon production-inventory system with a central supplier connected to production systems (servers) at several locations, each with a local inventory. Demand of customers arrives at each production system according to a Poisson process and is lost if the local inventory is depleted. To satisfy a customer’s demand, a server at the production system takes exactly one unit of raw material from the associated local inventory. The central supplier manufactures raw material to replenish the local inventories, which are controlled by a continuous review base stock policy. We derive stationary distributions of joint queue length and inventory processes in explicit product form. After performing a cost analysis, we find out that the global search for the vector of optimal base stock levels can be reduced to a set of independent optimisation problems. The explicit form of the stationary distribution enables us to get additional structural insights, e.g. about monotonicity properties and stability conditions. Obtaining the product form relies on some simplifying assumptions. The results are therefore compared with simulations of a more realistic system, which supports to use it as approximation.
Journal: International Journal of Production Research
Pages: 6174-6191
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1082669
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1082669
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Template-Type: ReDIF-Article 1.0
Author-Name: Justus Arne Schwarz
Author-X-Name-First: Justus Arne
Author-X-Name-Last: Schwarz
Author-Name: Martin Epp
Author-X-Name-First: Martin
Author-X-Name-Last: Epp
Title: Performance evaluation of a transportation-type bulk queue with generally distributed inter-arrival times
Abstract: 
 This paper is motivated by the performance evaluation of circulating vertical conveyor systems (CVCSs). CVCSs are bulk queues of transportation type. These material handling systems feature generally distributed inter-arrival times, which can be longer than the bulk service time. This leads to interdependencies between the number of arrivals in consecutive service intervals and the number of loads in the queue. We propose a new discrete-time approach for the steady-state analysis of such bulk service queues of transportation type with general arrival and service processes and finite server and limited queue capacities. The approach is based on a finite Markov chain that generates complete probability distributions for the key performance measures, including the queue length, waiting time and departing batch size. The proposed approach is exact in the cases of discrete-time slots, e.g. as in communication systems. We investigate the discretisation error that arises if the approach is used as an approximation for the continuous time using a numerical comparison to a discrete-event simulation. Moreover, we examine the impact of arrival stream variability on the system performance and compare the positive effects of a higher frequency of server visits with the effects arising from larger pickup capacities.
Journal: International Journal of Production Research
Pages: 6251-6264
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1092613
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1092613
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Template-Type: ReDIF-Article 1.0
Author-Name: Chu A. My
Author-X-Name-First: Chu A.
Author-X-Name-Last: My
Author-Name: Erik L.J. Bohez
Author-X-Name-First: Erik L.J.
Author-X-Name-Last: Bohez
Title: New algorithm to minimise kinematic tool path errors around 5-axis machining singular points
Abstract: 
 The singular points of a given 5-axis CNC machine could be found in the domain of the joint variables of the machine. In the neighbourhood of a singular point, even for a small change of the tooltip position, an enormous change of axis displacements of the machine is often required. This causes a large deviation between the real cutting path and the desired tool path, and the machining surface could be destroyed. This paper provides with an analytical scheme for identifying singular configuration of 5-axis CNC machines. In particular, an efficient and robust algorithm is proposed to compute the cutter path across the neighbourhood of the singular points identified such that the computed cutter path tracks the desired tool path within a controllable error. Numerical examples and real cutting parts are carried out and discussed to show the effectiveness and the efficiency of the presented method.
Journal: International Journal of Production Research
Pages: 5965-5975
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2015.1134838
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1134838
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Template-Type: ReDIF-Article 1.0
Author-Name: Qing-Hui Wang
Author-X-Name-First: Qing-Hui
Author-X-Name-Last: Wang
Author-Name: Shuai Wang
Author-X-Name-First: Shuai
Author-X-Name-Last: Wang
Author-Name: Fei Jiang
Author-X-Name-First: Fei
Author-X-Name-Last: Jiang
Author-Name: Jing-Rong Li
Author-X-Name-First: Jing-Rong
Author-X-Name-Last: Li
Title: Adaptive trochoidal toolpath for complex pockets machining
Abstract: 
 This work proposes a novel adaptive trochoidal (TR) toolpath model for complex pocket machining. The proposed model is able to adjust its TR radius, while simultaneously offers an adaptive trochoidal step for generation of each toolpath cycle. With the varying radius, complex regions can be machined by a single strip of TR toolpath. Moreover, the step of each TR cycle can be adjusted with reference to the varied radius so as to maintain a constant radial depth of cut, and hence more stable material removal rate among all TR cycles can be achieved. For the pocket machining cases with complex inner and outer boundaries, experimental study has shown that the proposed TR toolpath can effectively minimise the fluctuation of cutting forces, and achieve better toolpath efficiency.
Journal: International Journal of Production Research
Pages: 5976-5989
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1143135
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1143135
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Template-Type: ReDIF-Article 1.0
Author-Name: Jie Wu
Author-X-Name-First: Jie
Author-X-Name-Last: Wu
Author-Name: Junfei Chu
Author-X-Name-First: Junfei
Author-X-Name-Last: Chu
Author-Name: Qingyuan Zhu
Author-X-Name-First: Qingyuan
Author-X-Name-Last: Zhu
Author-Name: Pengzhen Yin
Author-X-Name-First: Pengzhen
Author-X-Name-Last: Yin
Author-Name: Liang Liang
Author-X-Name-First: Liang
Author-X-Name-Last: Liang
Title: DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection
Abstract: 
 Data envelopment analysis (DEA) has been extended to cross-efficiency evaluation to provide better discrimination and ranking of decision-making units (DMUs). However, the non-uniqueness of optimal weights in the traditional DEA models (CCR and BCC models) has reduced the usefulness of the DEA cross-efficiency evaluation method. To solve this problem, we introduce the concept of the satisfaction degree of a DMU towards a set of optimal weights for another DMU. Then, a new DEA cross-efficiency evaluation approach, which contains a maxmin model and two algorithms, is proposed based on the satisfaction degrees of the DMUs. Our maxmin model and algorithm 1 can obtain for each DMU an optimal set of weights that maximises the least satisfaction degrees among all the other DMUs. Further, our algorithm 2 can then be used to guarantee the uniqueness of the optimal weights for each DMU. Finally, our approach is applied to a real-world case study of technology selection.
Journal: International Journal of Production Research
Pages: 5990-6007
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1148278
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1148278
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Template-Type: ReDIF-Article 1.0
Author-Name: Sandra Mattsson
Author-X-Name-First: Sandra
Author-X-Name-Last: Mattsson
Author-Name: Malin Tarrar
Author-X-Name-First: Malin
Author-X-Name-Last: Tarrar
Author-Name: Åsa Fast-Berglund
Author-X-Name-First: Åsa
Author-X-Name-Last: Fast-Berglund
Title: Perceived production complexity – understanding more than parts of a system
Abstract: 
 To successfully manage today’s complex production systems it is essential to study operators’ perception of the system. The paper presents perceived production complexity assessed at seven manufacturing companies with the CompleXity Index (CXI) method. While other methods have measured product variants, layout, work content, tools and information items, CXI combines them into three areas. These three complexity areas (Station design, Work variance and Disturbance handling) help to create an understanding of the complex system by visualising how they contribute to complexity, and show the need to support the operators’ ability to handle the varying work.
Journal: International Journal of Production Research
Pages: 6008-6016
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1154210
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154210
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Template-Type: ReDIF-Article 1.0
Author-Name: Qingfeng Wang
Author-X-Name-First: Qingfeng
Author-X-Name-Last: Wang
Author-Name: Xu Sun
Author-X-Name-First: Xu
Author-X-Name-Last: Sun
Author-Name: Sue Cobb
Author-X-Name-First: Sue
Author-X-Name-Last: Cobb
Author-Name: Glyn Lawson
Author-X-Name-First: Glyn
Author-X-Name-Last: Lawson
Author-Name: Sarah Sharples
Author-X-Name-First: Sarah
Author-X-Name-Last: Sharples
Title: 3D printing system: an innovation for small-scale manufacturing in home settings? – early adopters of 3D printing systems in China
Abstract: 
 This study investigates Chinese consumers’ adoption of the innovative 3D printing systems for small-scale manufacturing in home settings. Empirical studies were conducted in a survey with 256 participants. The number of significant determinants that affect an individual’s decision to adopt 3D printing systems has been identified by applying a model that integrates the Technology Acceptance Model and Innovation Diffusion Theory. A number of moderation effects of demographic variables (e.g. gender, design background) on the association between motivational variables and participants’ adoption have also been analysed with factor analysis, structural equation modelling and hierarchical regression. Our results shed some light on the characteristics of early adopters of home 3D printing systems in China. This study contributes to the early understanding of Chinese consumers’ adoption of innovative 3D printing systems.
Journal: International Journal of Production Research
Pages: 6017-6032
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1154211
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1154211
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Template-Type: ReDIF-Article 1.0
Author-Name: Julian Englberger
Author-X-Name-First: Julian
Author-X-Name-Last: Englberger
Author-Name: Frank Herrmann
Author-X-Name-First: Frank
Author-X-Name-Last: Herrmann
Author-Name: Michael Manitz
Author-X-Name-First: Michael
Author-X-Name-Last: Manitz
Title: Two-stage stochastic master production scheduling under demand uncertainty in a rolling planning environment
Abstract: 
 This paper proposes a scenario-based two-stage stochastic programming model with recourse for master production scheduling under demand uncertainty. We integrate the model into a hierarchical production planning and control system that is common in industrial practice. To reduce the problem of the disaggregation of the master production schedule, we use a relatively low aggregation level (compared to other work on stochastic programming for production planning). Consequently, we must consider many more scenarios to model demand uncertainty. Additionally, we modify standard modelling approaches for stochastic programming because they lead to the occurrence of many infeasible problems due to rolling planning horizons and interdependencies between master production scheduling and successive planning levels. To evaluate the performance of the proposed models, we generate a customer order arrival process, execute production planning in a rolling horizon environment and simulate the realisation of the planning results. In our experiments, the tardiness of customer orders can be nearly eliminated by the use of the proposed stochastic programming model at the cost of increasing inventory levels and using additional capacity.
Journal: International Journal of Production Research
Pages: 6192-6215
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1162917
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1162917
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Template-Type: ReDIF-Article 1.0
Author-Name: Stanislav Chankov
Author-X-Name-First: Stanislav
Author-X-Name-Last: Chankov
Author-Name: Marc-Thorsten Hütt
Author-X-Name-First: Marc-Thorsten
Author-X-Name-Last: Hütt
Author-Name: Julia Bendul
Author-X-Name-First: Julia
Author-X-Name-Last: Bendul
Title: Synchronization in manufacturing systems: quantification and relation to logistics performance
Abstract: 
 The term ‘synchronization’ in manufacturing refers to the provision of the right components to the subsequent production steps at the right moment in time. It is widely assumed that synchronization is beneficial to the logistics performance of manufacturing systems. However, it has been shown that synchronization phenomena can be detrimental to systems in which they emerge. To study if synchronization phenomena also occur in and affect manufacturing systems’ performance, a formal quantification and holistic understanding of the types of synchronization phenomena emerging in manufacturing are needed. This article aims to fill this research gap by developing synchronization measures for manufacturing systems, applying these measures to real-world production feedback data and utilising them to test the assumption about synchronization’s beneficial effect on logistics performance. We identify two distinct synchronization types occurring in manufacturing systems, logistics and physics synchronization, and show that they are negatively correlated. Further, we show that logistics synchronization and due date performance exhibit anti-correlation and thus question the assumption that synchronization leads to higher efficiency in manufacturing systems. This article aids production managers in designing and optimising production systems, and supports further empirical research in production planning and control and production system design.
Journal: International Journal of Production Research
Pages: 6033-6051
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1165876
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165876
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Template-Type: ReDIF-Article 1.0
Author-Name: Hui-Yu Zhang
Author-X-Name-First: Hui-Yu
Author-X-Name-Last: Zhang
Author-Name: Qing-Xin Chen
Author-X-Name-First: Qing-Xin
Author-X-Name-Last: Chen
Author-Name: Ning Mao
Author-X-Name-First: Ning
Author-X-Name-Last: Mao
Title: System performance analysis of flexible flow shop with match processing constraint
Abstract: 
 Blocking makes the analytical modelling of open queuing networks with finite buffers intractable because the product-form solutions are unavailable. In this paper, about mould manufacturing, a four-stage flexible flow shop with match processing constraint is first modelled as an open queuing network with finite buffers. According to the characteristics of the matching node, the inter-arrival time distributions of parts arriving at the nodes are assumed to be exponential or general. Next, based on approximation of queuing theory, the Decomposition of State Space Method and the Generalized Expansion Method are developed for system performance evaluation. Then, experiments to assess the accuracy of the proposed methods are reported by comparing the analytical results with simulations. Finally, a case of a real-life production system of mould manufacturing is studied to show the application of the proposed methods. The results of experiments reveal that the proposed methods are feasible and effective for system performance evaluation and they can even solve large-size practical problems in a reasonable time. The results in this paper can provide a basis for system design or resource planning, to solve buffer allocation problems and capacity configuration problems.
Journal: International Journal of Production Research
Pages: 6052-6070
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1166286
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1166286
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Template-Type: ReDIF-Article 1.0
Author-Name: Pankaj Kumar Medhi
Author-X-Name-First: Pankaj Kumar
Author-X-Name-Last: Medhi
Author-Name: Sandeep Mondal
Author-X-Name-First: Sandeep
Author-X-Name-Last: Mondal
Title: A neural feature extraction model for classification of firms and prediction of outsourcing success: advantage of using relational sources of information for new suppliers
Abstract: 
 Clustering is a family of classification techniques, often preceding further analysis or application in a number of fields like data analysis, strategy selection, supplier selection, etc. Data based neural techniques are gaining popularity in clustering applications due to flexibility and adaptability. Kohonen’s Self Organizing Map (SOM) is often used when the objects to be clustered have many attributes. In both supervised and un-supervised modes, Kohonen’s map exhibit good capability to extract a classification which assigns highest weight to the most important attribute. In this paper, we have applied SOM for classification of firms based on their sources of information for new suppliers/customers. Additional data regarding the outsourcing success of the firms’ is added to see if there is an association between a particular set of information sources and the probability of firms’ success to outsource to partner firms. Using data from World Bank BEEPS survey of German industries, we could produce three distinct clusters of industries. When successful outsourcing data were included, it still showed three clusters. The hits were obtained using specific support vector for identification of clusters. We found evidence of associations between relational sources and firms’ ability to outsource successfully.
Journal: International Journal of Production Research
Pages: 6071-6081
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1174342
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1174342
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Template-Type: ReDIF-Article 1.0
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Michael Hassoun
Author-X-Name-First: Michael
Author-X-Name-Last: Hassoun
Author-Name: Alejandro Sendon
Author-X-Name-First: Alejandro
Author-X-Name-Last: Sendon
Title: Allocating metrology capacity to multiple heterogeneous machines
Abstract: 
 The measurement of lots to check process quality is crucial but also a non-added value operation in manufacturing systems. This paper is motivated by semiconductor manufacturing, where metrology tools are expensive, thus limiting metrology capacity which must be optimally used. In a context where multiple heterogeneous machines are sharing a common metrology workshop, the problem of minimising risk while considering metrology capacity arises. An integer linear programming (ILP) model is presented, which corresponds to a multiple-choice knapsack problem. Simple rounding heuristics are proposed, whose results on randomly generated instances are compared with the optimal solutions obtained using a standard solver on the ILP. Additionally, numerical experiments on industrial data are presented and discussed.
Journal: International Journal of Production Research
Pages: 6082-6091
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1187775
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1187775
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Template-Type: ReDIF-Article 1.0
Author-Name: Mustapha Nourelfath
Author-X-Name-First: Mustapha
Author-X-Name-Last: Nourelfath
Author-Name: Tariq Aldowaisan
Author-X-Name-First: Tariq
Author-X-Name-Last: Aldowaisan
Author-Name: Jawad Hassan
Author-X-Name-First: Jawad
Author-X-Name-Last: Hassan
Title: Evaluating Six Sigma failure rate for inverse Gaussian cycle times
Abstract: 
 Six Sigma is a quality philosophy and methodology that aims to achieve operational excellence and delighted customers. The cost of poor quality depends on the sigma quality level and its corresponding failure rate. Six Sigma provides a well-defined target of 3.4 defects per million. This failure rate is commonly evaluated under the assumption that the process is normally distributed and its specifications are two-sided. However, these assumptions may lead to implementation of quality-improvement strategies that are based on inaccurate evaluations of quality costs and profits. This paper defines the relationship between failure rate and sigma quality level for inverse Gaussian processes. The inverse Gaussian distribution has considerable applications in describing cycle times, product life, employee service times, and so on. We show that for these processes attaining Six Sigma target failure rate requires higher quality efforts than for normal processes. A generic model is presented to characterise cycle times in manufacturing systems. In this model, the asymptotic production is described by a drifted Brownian motion, and the cycle time is evaluated by using the first passage time theory of a Wiener process to a boundary. The proposed method estimates the right efforts required to reach Six Sigma goals.
Journal: International Journal of Production Research
Pages: 6092-6101
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1190880
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1190880
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Template-Type: ReDIF-Article 1.0
Author-Name: Chunyan Gao
Author-X-Name-First: Chunyan
Author-X-Name-Last: Gao
Author-Name: T.C. Edwin Cheng
Author-X-Name-First: T.C. Edwin
Author-X-Name-Last: Cheng
Author-Name: Houcai Shen
Author-X-Name-First: Houcai
Author-X-Name-Last: Shen
Author-Name: Liang Xu
Author-X-Name-First: Liang
Author-X-Name-Last: Xu
Title: Incentives for quality improvement efforts coordination in supply chains with partial cost allocation contract
Abstract: 
 In this paper, we consider quality improvement efforts coordination in a two-stage decentralised supply chain with a partial cost allocation contract. The supply chain consists of one supplier and one manufacturer, both of which produce defective products. Two kinds of failure cost occur within the supply chain: internal and external. The supplier and the manufacturer determine their individual quality levels to maximise their own profits. We propose a partial cost allocation contract, under which the external failure cost is allocated between the manufacturer and the supplier at different rates based on information derived from failure root cause analysis. If the quality levels of the supplier and the manufacturer are observable, we show that the partial cost allocation contract coordinates the supply chain, provided that the failure root cause analysis does not erroneously identify the manufacturer’s fault as the supplier’s, and the supplier does not take responsibility for the manufacture’s fault. In the single moral hazard model, where only the quality level of the supplier is unobservable, the optimal share rates require the supplier to take some responsibility for the manufacture’s fault. However, in the double moral hazard model, where quality levels of the supplier and the manufacturer are unobservable to each other, the optimal share rates require the supplier not to take responsibility for the manufacturer’s fault. It is noted that the root cause analysis conducted by the manufacturer may have its disadvantage in attributing the fault to the supplier when both sides are at fault. We also propose a contract based on the dual root cause analysis to reduce the supplier’s penalty cost. Numerical results illustrate that the partial cost allocation contract satisfies the fairness criterion compared with the traditional cost allocation contract.
Journal: International Journal of Production Research
Pages: 6216-6231
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1191691
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1191691
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Template-Type: ReDIF-Article 1.0
Author-Name: Gwo-Liang Liao
Author-X-Name-First: Gwo-Liang
Author-X-Name-Last: Liao
Title: Optimal economic production quantity policy for a parallel system with repair, rework, free-repair warranty and maintenance
Abstract: 
 Hot standby redundancy maintains the working order of a system, repairs offer restoration in case of failure, and preventive maintenance (PM) prevents trouble. Warranties provide assurance to customers, and a superior warranty signifies higher product quality. The running costs of redundancy, maintenance and warranties influence decisions during product manufacture. Therefore, this paper presents an economic production quantity (EPQ) model for a parallel system with maintenance, production, and free-repair warranty (FRW) programmes. The production system begins with a basic unit and produces conforming items. PM is performed after the production run period and is classified as imperfect or perfect. If the basic unit fails, it is repaired and returned to operation after perfect PM; the spare unit is online only during the repair time of the basic unit. The spare will produce some number of defective goods, which are reworked in the same inventory cycle. The hot spare is minimally repaired if it fails in its standby or online mode. In this study, an inferior item is defined as one that satisfies specifications on inspection and is usable but is likely to incur postsale servicing costs when sold under an FRW. The total cost of this EPQ model includes setup, holding, PM, restoration, minimal repair, and warranty costs. The optimal production runtime is determined by minimising the total cost. Several cases are discussed in this paper, and the proposed model is illustrated using a numerical example and sensitivity.
Journal: International Journal of Production Research
Pages: 6265-6280
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1203074
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1203074
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Template-Type: ReDIF-Article 1.0
Author-Name: George Liberopoulos
Author-X-Name-First: George
Author-X-Name-Last: Liberopoulos
Author-Name: Chrissoleon T. Papadopoulos
Author-X-Name-First: Chrissoleon T.
Author-X-Name-Last: Papadopoulos
Author-Name: James MacGregor Smith
Author-X-Name-First: James
Author-X-Name-Last: MacGregor Smith
Author-Name: Horst Tempelmeier
Author-X-Name-First: Horst
Author-X-Name-Last: Tempelmeier
Author-Name: Tullio Tolio
Author-X-Name-First: Tullio
Author-X-Name-Last: Tolio
Title: New developments in stochastic models of manufacturing and service operations
Journal: International Journal of Production Research
Pages: 6102-6104
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2016.1220674
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1220674
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Template-Type: ReDIF-Article 1.0
Author-Name: Chuan Shi
Author-X-Name-First: Chuan
Author-X-Name-Last: Shi
Author-Name: Stanley B. Gershwin
Author-X-Name-First: Stanley B.
Author-X-Name-Last: Gershwin
Title: A segmentation approach for solving buffer allocation problems in large production systems
Abstract: 
 Buffer space allocation is an important step in production line design. In this paper, we focus on maximising the profit rate of a line subject to a production rate constraint. We describe a newly observed property of production line optimisation. The property is that the production rate constraint, if it is effective, allows an original line to be decoupled into several short lines for optimisation. An approximation method is developed from this property. Instead of optimising a long line, the method divides it into several short lines, optimises them separately and combines their optimal buffer distributions to find the optimal or near optimal buffer distribution of the original line. The method greatly improves the computation efficiency for solving buffer allocation problem for long lines, while ensuring the accuracy of the optimal buffer distribution. A heuristic explanation is proposed. Numerical experiments are provided to show the accuracy and efficiency of the method. The effect of the number and length of line segments on the performance of the method is discussed.
Journal: International Journal of Production Research
Pages: 6121-6141
Issue: 20
Volume: 54
Year: 2016
Month: 10
X-DOI: 10.1080/00207543.2014.991842
File-URL: http://hdl.handle.net/10.1080/00207543.2014.991842
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Template-Type: ReDIF-Article 1.0
Author-Name: Jose-Fernando Jimenez
Author-X-Name-First: Jose-Fernando
Author-X-Name-Last: Jimenez
Author-Name: Abdelghani Bekrar
Author-X-Name-First: Abdelghani
Author-X-Name-Last: Bekrar
Author-Name: Gabriel Zambrano-Rey
Author-X-Name-First: Gabriel
Author-X-Name-Last: Zambrano-Rey
Author-Name: Damien Trentesaux
Author-X-Name-First: Damien
Author-X-Name-Last: Trentesaux
Author-Name: Paulo Leitão
Author-X-Name-First: Paulo
Author-X-Name-Last: Leitão
Title: Pollux: a dynamic hybrid control architecture for flexible job shop systems
Abstract: 
 Nowadays, manufacturing control systems can respond more effectively to exigent market requirements and real-time demands. Indeed, they take advantage of changing their structural and behavioural arrangements to tailor the control solution from a diverse set of feasible configurations. However, the challenge of this approach is to determine efficient mechanisms that dynamically optimise the configuration between different architectures. This paper presents a dynamic hybrid control architecture that integrates a switching mechanism to control changes at both structural and behavioural level. The switching mechanism is based on a genetic algorithm and strives to find the most suitable operating mode of the architecture with regard to optimality and reactivity. The proposed approach was tested in a real flexible job shop to demonstrate the applicability and efficiency of including an optimisation algorithm in the switching process of a dynamic hybrid control architecture.
Journal: International Journal of Production Research
Pages: 4229-4247
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1218087
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1218087
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Template-Type: ReDIF-Article 1.0
Author-Name: Ann-Christine Falck
Author-X-Name-First: Ann-Christine
Author-X-Name-Last: Falck
Author-Name: Roland Örtengren
Author-X-Name-First: Roland
Author-X-Name-Last: Örtengren
Author-Name: Mikael Rosenqvist
Author-X-Name-First: Mikael
Author-X-Name-Last: Rosenqvist
Author-Name: Rikard Söderberg
Author-X-Name-First: Rikard
Author-X-Name-Last: Söderberg
Title: Proactive assessment of basic complexity in manual assembly: development of a tool to predict and control operator-induced quality errors
Abstract: 
 A major challenge for manufacturing companies today is to manage a huge amount of product variants and build options at the same time in manufacturing engineering and in production. The overall complexity and risk of quality errors in manual assembly will increase placing high demands on the operators who must manage many different tasks in current production. Therefore, methods for decreasing and controlling assembly complexity are urgent because managing complex product and installation conditions will result in distinct competitive advantages. The objective of this paper is to present a method for predictive assessment of basic manual assembly complexity and explain how included complexity criteria were arrived at. The verified method includes 16 high complexity and 16 low complexity criteria to aid designers in preventing costly errors during assembly and create good basic assembly conditions in early design phases of new manufacturing concepts.
Journal: International Journal of Production Research
Pages: 4248-4260
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1227103
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1227103
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Template-Type: ReDIF-Article 1.0
Author-Name: YaoAn Lu
Author-X-Name-First: YaoAn
Author-X-Name-Last: Lu
Author-Name: Ye Ding
Author-X-Name-First: Ye
Author-X-Name-Last: Ding
Author-Name: LiMin Zhu
Author-X-Name-First: LiMin
Author-X-Name-Last: Zhu
Title: Tool path generation via the multi-criteria optimisation for flat-end milling of sculptured surfaces
Abstract: 
 A method of generating optimal tool paths for sculptured surface machining with flat-end cutters is presented in this paper. The inclination and tilt angles, as well as the feed directions of the cutter at each cutter contact point on a machining path are optimised as a whole so that the machining width of the tool path can be as large as possible, and concerns such as smooth cutter motion, gouging avoidance, scallop height and machining widths overlap are also considered when calculating a path. A multi-criteria tool path optimisation model is introduced, and it is converted into a single objective optimisation with the weighted sum method. The Differential Evolution (DE) algorithm is suitable for solving this highly non-linear problem. However, the searching process of the DE algorithm may be trapped in local minima due to large number of design variables. Therefore, an algorithm combining the DE algorithm and the sequence linear programming algorithm is developed to solve this optimisation model. The proposed method is applied to two freeform surfaces to illustrate its effectiveness.
Journal: International Journal of Production Research
Pages: 4261-4282
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1232496
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1232496
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Template-Type: ReDIF-Article 1.0
Author-Name: Yassine Qamsane
Author-X-Name-First: Yassine
Author-X-Name-Last: Qamsane
Author-Name: Abdelouahed Tajer
Author-X-Name-First: Abdelouahed
Author-X-Name-Last: Tajer
Author-Name: Alexandre Philippot
Author-X-Name-First: Alexandre
Author-X-Name-Last: Philippot
Title: A synthesis approach to distributed supervisory control design for manufacturing systems with Grafcet implementation
Abstract: 
 In supervisory control, computational complexity and implementation flexibility represent major challenges when a large number of local components compose a target system. To overcome these difficulties, we propose a formal approach to distributed control synthesis and implementation for automated manufacturing systems (AMS). We assume that the system is modelled with automata in a local modular fashion. Local control specifications are defined for each local subsystem by means of logical equations to construct local controllers (LCs). Then, global control specifications, stated as logical implications, are applied to the LCs, which allows synchronisation and cooperative interaction among the subsystems. This paper makes two contributions. First, it outlines a formal method for constructing minimally restrictive and deadlock-free distributed controllers (DCs). Second, it proposes a method for the interpretation of these DCs into Grafcet, which is a graphical modelling formalism widely used to design the controller’s dynamic behaviour for AMS. An experimental manufacturing system illustrates the approach.
Journal: International Journal of Production Research
Pages: 4283-4303
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1235804
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1235804
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Template-Type: ReDIF-Article 1.0
Author-Name: Min Zhang
Author-X-Name-First: Min
Author-X-Name-Last: Zhang
Author-Name: Hangfei Guo
Author-X-Name-First: Hangfei
Author-X-Name-Last: Guo
Author-Name: Xiande Zhao
Author-X-Name-First: Xiande
Author-X-Name-Last: Zhao
Title: Effects of social capital on operational performance: impacts of servitisation
Abstract: 
 Studies on servitisation have largely overlooked the roles of social capital with suppliers and knowledge management. We propose a moderated mediation model to investigate the impacts of servitisation on the mechanisms through which social capital with suppliers improves operational performance. The hypotheses are empirically tested using structural equation modelling and data collected from 276 manufacturing firms in China. The results show that social capital improves operational performance both directly and indirectly through knowledge management, and the relationships are influenced by servitisation. In particular, social capital improves operational performance directly and indirectly through knowledge combination in servitised firms, whereas social capital only improves operational performance indirectly through knowledge acquisition in traditional manufacturers. The findings contribute to the literature by revealing that the effects of social capital with suppliers on operational performance are partially mediated by knowledge acquisition and knowledge combination and the mediation effects are moderated by servitisation, and by providing insights into how to design purchasing and production systems to profit from servitisation.
Journal: International Journal of Production Research
Pages: 4304-4318
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1246764
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1246764
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Template-Type: ReDIF-Article 1.0
Author-Name: Taieb Ben Romdhane
Author-X-Name-First: Taieb
Author-X-Name-Last: Ben Romdhane
Author-Name: Ahmed Badreddine
Author-X-Name-First: Ahmed
Author-X-Name-Last: Badreddine
Author-Name: Manel Sansa
Author-X-Name-First: Manel
Author-X-Name-Last: Sansa
Title: A new model to implement Six Sigma in small- and medium-sized enterprises
Abstract: 
 The Six Sigma approach improves the quality of products in order to ensure customers’ satisfaction. This approach has yielded to interesting results for large enterprises. However, its implementation remains difficult for small- and medium-sized enterprises (SME). In fact, the use of the same tools is insufficient to achieve the objectives when considering financial constraints and the lack of data. The regular tools are complex for SMEs which require an adapted model to implement the approach successfully. In this paper, we propose a new model having the objective to facilitate the integration of Six Sigma in SMEs by avoiding the use of Black Belts, optimising the implementation costs and period, simplifying the Six Sigma structure and enhancing the communication between staff and managers. The model includes two imbricated loops: the first offers immediate improvement actions by estimating the capability and the stability of the process, while the second provides profound improvement actions using the fuzzy logic system and the analytic hierarchical process (AHP) method. An example illustrates the application of the proposed model in an SME.
Journal: International Journal of Production Research
Pages: 4319-4340
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1249430
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1249430
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Template-Type: ReDIF-Article 1.0
Author-Name: Yang Yu
Author-X-Name-First: Yang
Author-X-Name-Last: Yu
Author-Name: Ray Qing Cao
Author-X-Name-First: Ray Qing
Author-X-Name-Last: Cao
Author-Name: Dara Schniederjans
Author-X-Name-First: Dara
Author-X-Name-Last: Schniederjans
Title: Cloud computing and its impact on service level: a multi-agent simulation model
Abstract: 
 Supply chains are increasingly becoming more complex, making collaboration progressively difficult to establish and maintain. It is imperative to understand not only the consequences, but also the drivers of effective and efficient collaboration. In this study, we attempt to show how varying levels of collaboration impact service level and how cloud computing fosters these levels of collaboration. We introduce a framework detailing how cloud computing impacts three levels of collaboration: (1) information centralisation, (2) vendor managed inventory and continuous replenishment programmes and (3) business intelligence (BI) collaborative planning, forecasting and replenishment. In addition, we use multi-agent-based simulation to analyse how each level of collaboration (enhanced through cloud computing) impacts service level as measured by fill rate. Obtained results show that cloud computing can enhance all three levels of collaboration. Further, our results demonstrate that BI collaborative planning, forecasting and replenishment have significantly greater service level benefits in comparison to other collaboration levels.
Journal: International Journal of Production Research
Pages: 4341-4353
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1251624
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1251624
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Template-Type: ReDIF-Article 1.0
Author-Name: Marco Grasso
Author-X-Name-First: Marco
Author-X-Name-Last: Grasso
Author-Name: Bianca Maria Colosimo
Author-X-Name-First: Bianca Maria
Author-X-Name-Last: Colosimo
Author-Name: Fugee Tsung
Author-X-Name-First: Fugee
Author-X-Name-Last: Tsung
Title: A phase I multi-modelling approach for profile monitoring of signal data
Abstract: 
 Many industrial processes exhibit multiple in-control signatures, where signal data vary over time without affecting the final product quality. They are known as multimode processes. With regard to profile monitoring methodologies, the existence of multiple in-control patterns entails the study and development of novel monitoring schemes. We propose a method based on coupling curve classification and monitoring that inherits the so-called ‘multi-modelling framework’. The goal is to design a monitoring tool that is able to automatically adapt the control chart parameters to the current operating mode. The proposed approach allows assessing which mode new data belong to before applying a control chart to determine if they are actually in control or not. Contrary to mainstream multi-modelling techniques, we propose extending the classification step to include a novelty detection capability, in order to deal with the possible occurrence of in-control operating modes during the design phase that were not observed previously. The functional data depth paradigm is proposed to design both the curve classification and the novelty detection algorithm. A simulation study is presented to demonstrate the performances of the proposed methodology, which is compared against benchmark methods. A real case study is presented too, which consists of a multimode end-milling process, where different operating conditions yield different cutting force profile patterns.
Journal: International Journal of Production Research
Pages: 4354-4377
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1251626
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1251626
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Template-Type: ReDIF-Article 1.0
Author-Name: Ruey-Chyn Tsaur
Author-X-Name-First: Ruey-Chyn
Author-X-Name-Last: Tsaur
Author-Name: I-Fei Chen
Author-X-Name-First: I-Fei
Author-X-Name-Last: Chen
Author-Name: Yu-Shan Chan
Author-X-Name-First: Yu-Shan
Author-X-Name-Last: Chan
Title: TFT-LCD industry performance analysis and evaluation using GRA and DEA models
Abstract: 
 In this study we propose a four-stage approach, which includes data envelopment analysis, Malmquist productivity index (MPI), entropy method and grey relation analysis (GRA), to investigate the operational performance of six thin film transistor liquid crystal display (TFT-LCD) companies in Taiwan during 2009–2012. The input variables are fixed assets, operating expenses, R&amp;D expenses and number of employees, while the output variables are cash flow and net sales. The empirical results showed that companies AUO and HannStar could increase their operation efficiency by improving their VRS efficiency and scale efficiency. When using the MPI model to measure the productivity changes for these TFT-LCD companies, we found that the technology changes in most of the companies are downward tendencies during 2009–2012 except for Ampire. Thus, not only could the proposed GRA with entropy weights evaluate the current performances of each firm effectively, it can also predict their future performances.
Journal: International Journal of Production Research
Pages: 4378-4391
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1252863
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1252863
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Template-Type: ReDIF-Article 1.0
Author-Name: Xi Gu
Author-X-Name-First: Xi
Author-X-Name-Last: Gu
Title: The impact of maintainability on the manufacturing system architecture
Abstract: 
 The rapid development of big data technologies can improve the maintainability of machines and equipment in manufacturing systems, which could impact the selection of the optimal system architecture. In this paper, two typical architectures for large manufacturing systems − serial lines in parallel and reconfigurable manufacturing systems − are considered, and their productivities are compared. A decision locus is calculated that divides the configuration space into two areas; in each area, one of the architectures is the preferred one. It is also investigated how the locus is affected by different parameters, such as system size, buffer capacity and machine or gantry maintainability. The analysis provides valuable managerial insights for designing the architecture of large manufacturing systems.
Journal: International Journal of Production Research
Pages: 4392-4410
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1254356
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1254356
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Template-Type: ReDIF-Article 1.0
Author-Name: Yeu-Shiang Huang
Author-X-Name-First: Yeu-Shiang
Author-X-Name-Last: Huang
Author-Name: Shiang-An Wang
Author-X-Name-First: Shiang-An
Author-X-Name-Last: Wang
Author-Name: Chih-Chiang Fang
Author-X-Name-First: Chih-Chiang
Author-X-Name-Last: Fang
Title: Optimization of the LCD optical film cutting problem
Abstract: 
 The manufacturing of liquid crystal display (LCD) plays an important role in electronics manufacturing industries, such as televisions, smart phones, pads, laptops, monitors and electronic appliances. Due to the fact that the cost of LCD’s film materials may reach 60–70% of the production cost, appropriate cutting schemes can lead to better raw material utilisation and thus enhance manufacturers’ profitability. Accordingly, the determination of the optimal production plan for cutting different-sized LCD optimal films with the designed cutting angles to fulfil the customers’ orders is a critical issue for the LCD industry. In the past, few studies integrated the different cutting allocation strategies into a synthetic decision. This study proposes a mathematical programming model for the two-stage cutting problem for LCD optical films to determine the optimal cutting allocation strategy with consideration of the costs of raw materials, processing and disposal during the manufacturing process. For large-scale problems in which the runtime for obtaining the optimal solution may grow exponentially as the problem size increases, a heuristic algorithm is also provided to obtain the approximate solution within a reasonable time. Finally, the results of the practical case shows that, compared with the existing fixed-angle cutting method, the proposed approach reduces the total cost by 6.2% due to the better material utilisation. In addition, the processing cost is also reduced due to a decrease in the required materials.
Journal: International Journal of Production Research
Pages: 4411-4435
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1256507
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1256507
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Template-Type: ReDIF-Article 1.0
Author-Name: Song-Man Wu
Author-X-Name-First: Song-Man
Author-X-Name-Last: Wu
Author-Name: Hu-Chen Liu
Author-X-Name-First: Hu-Chen
Author-X-Name-Last: Liu
Author-Name: Li-En Wang
Author-X-Name-First: Li-En
Author-X-Name-Last: Wang
Title: Hesitant fuzzy integrated MCDM approach for quality function deployment: a case study in electric vehicle
Abstract: 
 Quality function deployment (QFD) is a product planning management instrument which has been used in a broad range of industries. However, the traditional QFD method has been criticised much for its deficiencies in acquiring experts’ opinions, weighting customer requirements (CRs) and ranking engineering characteristics (ECs). To overcome the limitations, an integrated analytical model is presented in this study for obtaining the importance ratings of ECs in QFD by integrating decision-making trial and evaluation laboratory (DEMATEL) technique and Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method under hesitant fuzzy environment. In particular, the hesitant fuzzy DEMATEL is used to analyse the interrelationships among CRs and determine their weights, and the hesitant fuzzy VIKOR is utilised to prioritise ECs. Finally, the feasibility and practicality of the proposed method are verified by an example regarding the product development of electric vehicle.
Journal: International Journal of Production Research
Pages: 4436-4449
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1259670
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1259670
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Template-Type: ReDIF-Article 1.0
Author-Name: Gökan May
Author-X-Name-First: Gökan
Author-X-Name-Last: May
Author-Name: Bojan Stahl
Author-X-Name-First: Bojan
Author-X-Name-Last: Stahl
Title: The significance of organizational change management for sustainable competitiveness in manufacturing: exploring the firm archetypes
Abstract: 
 The successful development and deployment of adequate sustainable manufacturing strategies are still open issues and of utmost interest for research and practice. Guided by this particular challenge, we investigate the significance of organisational change management for sustainable competitiveness in manufacturing. By using six case studies from the Lombardia region in Italy and basing our research on the theoretical constructs of competitive aggressiveness and organisational change, we discover four archetypes of companies that show an increasing sustainable competitiveness with an increasing formalism and persistence in organisational change. Our findings suggest that change management practices are conditional hypothesis for creating competitive advantage through sustainability, and implementation gaps do hinder companies in realising the full potential. The study offers guidance to stakeholders, on how change management actions may potentially affect company performance in the manufacturing sector, as well as providing direction on the impact improved planning and leadership instances can have on the sustainability performance.
Journal: International Journal of Production Research
Pages: 4450-4465
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1261197
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1261197
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Template-Type: ReDIF-Article 1.0
Author-Name: Farbod Khameneifar
Author-X-Name-First: Farbod
Author-X-Name-Last: Khameneifar
Author-Name: Hsi-Yung Feng
Author-X-Name-First: Hsi-Yung
Author-X-Name-Last: Feng
Title: Extracting sectional contours from scanned point clouds via adaptive surface projection
Abstract: 
 This paper presents a new and fully automatic method to extract cross-sectional contour profiles of a physical object from the point cloud data scanned from its surface. Correctly extracting the sectional contours is of particular importance in the quality inspection of airfoil blades as the tolerances specified on a manufactured aero-engine blade are generally imposed at specific blade sections. The collected point cloud via 3D laser scanning is, however, distributed all over the blade surface rather than at the desired specific sections. In fact, no point in the point cloud is located exactly on the sectional planes. The desired sectional data have to be extracted from the nearby data points. If the underlying smooth surface geometry of the point cloud in the vicinity of a nearby data point can be approximated by a mathematical function, the approximated local surface formulation can be used to project the nearby point onto the desired sectional plane along a curvilinear trajectory. This is achieved in this work by fitting a local quadric surface to the neighbouring points of the point of interest. A systematic approach to establish a balanced set of neighbouring points is employed to avoid bias in fitting the local quadric surface as well as to guide the selection of points to be projected onto the sectional plane. The projected points are then used to construct the desired sectional contour profile. Implementation results have demonstrated the superior performance of the proposed fully automatic method in comparison with the existing methods.
Journal: International Journal of Production Research
Pages: 4466-4480
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1262565
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1262565
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Template-Type: ReDIF-Article 1.0
Author-Name: Anass Cherrafi
Author-X-Name-First: Anass
Author-X-Name-Last: Cherrafi
Author-Name: Said Elfezazi
Author-X-Name-First: Said
Author-X-Name-Last: Elfezazi
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Jose Arturo Garza-Reyes
Author-X-Name-First: Jose Arturo
Author-X-Name-Last: Garza-Reyes
Author-Name: Khalid Benhida
Author-X-Name-First: Khalid
Author-X-Name-Last: Benhida
Author-Name: Ahmed Mokhlis
Author-X-Name-First: Ahmed
Author-X-Name-Last: Mokhlis
Title: A framework for the integration of Green and Lean Six Sigma for superior sustainability performance
Abstract: 
 Evidence suggests that Lean, Six Sigma and Green approaches make a positive contribution to the economic, social and environmental (i.e. sustainability) performance of organisations. However, evidence also suggests that organisations have found their integration and implementation challenging. The purpose of this research is therefore to present a framework that methodically guides companies through a five stages and sixteen steps process to effectively integrate and implement the Green, Lean and Six Sigma approaches to improve their sustainability performance. To achieve this, a critical review of the existing literature in the subject area was conducted to build a research gap, and subsequently develop the methodological framework proposed. The paper presents the results from the application of the proposed framework in four organisations with different sizes and operating in a diverse range of industries. The results showed that the integration of Lean Six Sigma and Green helped the organisations to averagely reduce their resources consumption from 20 to 40% and minimise the cost of energy and mass streams by 7–12%. The application of the framework should be gradual, the companies should assess their weaknesses and strengths, set priorities, and identify goals for successful implementation. This paper is one of the very first researches that presents a framework to integrate Green and Lean Six Sigma at a factory level, and hence offers the potential to be expanded to multiple factories or even supply chains.
Journal: International Journal of Production Research
Pages: 4481-4515
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1266406
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1266406
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Template-Type: ReDIF-Article 1.0
Author-Name: Liaqat A. Shah
Author-X-Name-First: Liaqat A.
Author-X-Name-Last: Shah
Author-Name: Alain Etienne
Author-X-Name-First: Alain
Author-X-Name-Last: Etienne
Author-Name: Ali Siadat
Author-X-Name-First: Ali
Author-X-Name-Last: Siadat
Author-Name: François Vernadat
Author-X-Name-First: François
Author-X-Name-Last: Vernadat
Title: Process-oriented risk assessment methodology for manufacturing process evaluation
Abstract: 
 A process-oriented quantitative risk assessment methodology is proposed to evaluate risk associated with processes using modelling, simulation and decision-making approaches. For this purpose, risks involved in a process and the corresponding risk factors are identified through an objective-oriented risk identification approach. The identified risks are first analysed qualitatively in the failure mode effect and critical analysis process and then evaluated quantitatively in a simulation environment employing a process-based risk measurement model. To ease the decision-making process in case of multiple but heterogeneous risk measures, a global risk indicator is developed using the normalisation and aggregation techniques of the decision theory. Using the proposed methodology as a decision-making tool, alternative manufacturing scenarios (i.e. manufacturing process plans) are developed and ranked on the basis of desirability. Although the methodology is illustrated with a case study issued from the part manufacturing, it is also applicable to a wide range of other processes.
Journal: International Journal of Production Research
Pages: 4516-4529
Issue: 15
Volume: 55
Year: 2017
Month: 8
X-DOI: 10.1080/00207543.2016.1268728
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1268728
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Template-Type: ReDIF-Article 1.0
Author-Name: Jafar Rezaei
Author-X-Name-First: Jafar
Author-X-Name-Last: Rezaei
Title: A two-way approach to supply chain partner selection
Abstract: 
 All organisations face partner selection. It is the first step in establishing partnership. Over recent decades, a one-way selection approach has been dominant in the literature. It is assumed that a buyer searches for one or more suppliers from a set of suppliers. Once the best supplier is found and selected, a partnership is formed. However, in reality, not only is the selection not a one-way process as the relationship itself is bilateral, but the existence of other buyers and suppliers also needs to be taken into account. In this study, a two-way partner selection approach is proposed, where not only the buyers evaluate suppliers, but also the suppliers have the opportunity to evaluate buyers. Considering a marketplace where there are several buyers and suppliers, an integrative model is proposed in the form of an assignment model to optimally match all the buyers and suppliers. A generalised model is also formulated to take the suppliers’ capacity and buyers’ demand into account. The proposed models are illustrated using some numerical examples. Finally, conclusions and recommendations for future research are provided.
Journal: International Journal of Production Research
Pages: 4888-4902
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.1003663
File-URL: http://hdl.handle.net/10.1080/00207543.2014.1003663
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Template-Type: ReDIF-Article 1.0
Author-Name: Brian B. Hanson
Author-X-Name-First: Brian B.
Author-X-Name-Last: Hanson
Author-Name: Thom J. Hodgson
Author-X-Name-First: Thom J.
Author-X-Name-Last: Hodgson
Author-Name: Michael G. Kay
Author-X-Name-First: Michael G.
Author-X-Name-Last: Kay
Author-Name: Russell E. King
Author-X-Name-First: Russell E.
Author-X-Name-Last: King
Author-Name: Kristin A. Thoney-Barletta
Author-X-Name-First: Kristin A.
Author-X-Name-Last: Thoney-Barletta
Title: On the economic lot scheduling problem: stock-out prevention and system feasibility
Abstract: 
 The Economic Lot Scheduling Problem is a classical scheduling problem with the objective of minimising the long-run inventory and set-up costs of a single machine, multi-product inventory system. Demand rates, production rates and set-up times are assumed to be deterministic. The problem has been extensively studied and methods exist to obtain cyclic schedules which minimise total cost. In order to apply a cyclic schedule without a stock-out occurring, certain initial inventory levels are required. This paper considers the scenario where inventory levels are critically low and the cyclic schedule cannot be applied. Analytical methods are developed to determine: if the initial inventory is sufficient to prevent a stock-out from occurring; the maximum time until a stock-out will occur if a stock-out is unavoidable; and the minimum time required to obtain the necessary inventory to resume the cyclic schedule if a stock-out can be avoided.
Journal: International Journal of Production Research
Pages: 4903-4916
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1005246
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005246
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Template-Type: ReDIF-Article 1.0
Author-Name: Miguel Afonso Sellitto
Author-X-Name-First: Miguel Afonso
Author-X-Name-Last: Sellitto
Author-Name: Giancarlo Medeiros Pereira
Author-X-Name-First: Giancarlo Medeiros
Author-X-Name-Last: Pereira
Author-Name: Miriam Borchardt
Author-X-Name-First: Miriam
Author-X-Name-Last: Borchardt
Author-Name: Rosnaldo Inácio da Silva
Author-X-Name-First: Rosnaldo Inácio
Author-X-Name-Last: da Silva
Author-Name: Cláudia Viviane Viegas
Author-X-Name-First: Cláudia Viviane
Author-X-Name-Last: Viegas
Title: A SCOR-based model for supply chain performance measurement: application in the footwear industry
Abstract: 
 Supply Chain Operations Reference (SCOR) is a widely employed model for SC performance assessment, regardless its generic nature. This article presents a SCOR-based model for performance measurement in supply chains (SC) and apply it in the context of Brazilian footwear industry. The model has two dimensions: SCOR processes (source, make, deliver and return) and performance standards adapted from original SCOR (cost, quality, delivery and flexibility). This structure delivers a 4 × 4 matrix, with each component assessed under analytical hierarchy process. Using focus groups, SC’s experts weighted each component of the matrix regarding their relevance. Thereafter, SC’s managers indicated respective results. The SC’s overall performance was obtained by adding the performance of all indicators. The model application embraced one focal footwear manufacturer, four suppliers, three distribution channels and a return channel, with 85 indicators assessed. The achieved performance for the whole SC is 75.29%.The main gaps were found in deliver process (12.78 percentual points of difference between relevance and achieved proportions) and in flexibility performance (9.82). Further application is recommended in order to find consolidated results.
Journal: International Journal of Production Research
Pages: 4917-4926
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1005251
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005251
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Template-Type: ReDIF-Article 1.0
Author-Name: Maxime Ogier
Author-X-Name-First: Maxime
Author-X-Name-Last: Ogier
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: Sai Ho Chung
Author-X-Name-First: Sai Ho
Author-X-Name-Last: Chung
Author-Name: Van-Dat Cung
Author-X-Name-First: Van-Dat
Author-X-Name-Last: Cung
Author-Name: Julien Boissière
Author-X-Name-First: Julien
Author-X-Name-Last: Boissière
Title: Decentralised capacitated planning with minimal-information sharing in a 2-echelon supply chain
Abstract: 
 This paper aims at modelling decentralised planning at the tactical level, with minimal-information sharing coordination, in a 2-echelon supply chain with multiple actors at each echelon. Suppliers manage production and storage at the upstream echelon, while retailers manage transportation and storage at the downstream echelon. The main features of the planning process are (1) decentralisation and coordination using contracts and sharing of only order/supply proposals, and (2) iteration on a rolling horizon. Actor planning is modelled as a capacitated lot-sizing problem on a finite horizon, with the focus on quality of service. The objective is to minimise costs, with a high lost sales penalty if demand is not met. Two other decision problems are pointed out and modelled with Mixed Integer Programming: (1) lost sales allocation between the retailers when their demands cannot be satisfied; and (2) allocation of orders between the suppliers. A multi-agent system combines simulation of the planning process and optimisation of the local decision processes. Several strategies, including retailers’ beliefs about suppliers’ production capacity are proposed and experimentally tested, with two patterns of production capacities. The results compare the proposed allocation strategies and highlight the relevance of the proposed framework for the studied planning problem.
Journal: International Journal of Production Research
Pages: 4927-4950
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1005763
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005763
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Template-Type: ReDIF-Article 1.0
Author-Name: Stefan Bock
Author-X-Name-First: Stefan
Author-X-Name-Last: Bock
Author-Name: Filiz Isik
Author-X-Name-First: Filiz
Author-X-Name-Last: Isik
Title: A new two-dimensional performance measure in purchase order sizing
Abstract: 
 Lack of knowledge about demand responses or about behavioural aspects of decision-making within procurement processes is a significant cost driver in modern supply chains. Very often, this lack of knowledge leads to a substantial increase in inventories and may endanger negotiated service levels. For instance, various studies reveal that decision- makers tend to anchor orders close to the average past demand although the target order size is significantly higher or lower. In order to improve this situation, feedback has to be systematically provided to the decision-makers. In combination with modern big data analytics and reporting instruments that enable exhaustive monitoring, effective indicators have to be applied in order to directly detect processes with significant potential for improvement. Hence, this paper proposes a new approach for measuring the intricacy in purchase order sizing that addresses self-awareness skills of decision-makers. By simultaneously analysing the amount and structure of occurring costs, processes with a significant and simple structured error pattern are identified. In order to identify these processes more reliably, a new approach that supplements former information-theoretic entropy measures by an additional cost value is proposed. By analysing costs and the structure of deviations from target values in a two-dimensional measure, a more comprehensive understanding of the considered order sizing process is pursued. In order to illustrate the application of the new approach and show limitations of one-dimensional measures, different scenarios that exemplify the new approach are presented.
Journal: International Journal of Production Research
Pages: 4951-4962
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1005769
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005769
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Template-Type: ReDIF-Article 1.0
Author-Name: Frank Wiengarten
Author-X-Name-First: Frank
Author-X-Name-Last: Wiengarten
Author-Name: Vikram Bhakoo
Author-X-Name-First: Vikram
Author-X-Name-Last: Bhakoo
Author-Name: Cristina Gimenez
Author-X-Name-First: Cristina
Author-X-Name-Last: Gimenez
Title: The impact of host country regulatory quality on the value creation process in e-business supply chains
Abstract: 
 The use of e-business (EB) applications has reshaped an organisations’ supply chain structure. EB applications have enabled supply chain organisations to integrate their upstream and downstream supply chain processes to reach higher performance outcomes. Employing the resource-based view and contingency perspective as theoretical anchors, we propose and test a model of the relationship between EB applications, supply chain integration and financial performance that is moderated by a country’s regulatory quality. Cross-country data have been collected from 637 organisations through the International Manufacturing Strategy Survey research initiative. We hypothesise that the efficacy of the EB value creation process depends on the regulatory quality of the country that companies are located in. Results indicate that EB has a stronger impact on supply chain integration and supply chain integration has a stronger impact on financial performance, if the companies are situated in countries with high quality regulatory levels.
Journal: International Journal of Production Research
Pages: 4963-4978
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1008108
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1008108
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Template-Type: ReDIF-Article 1.0
Author-Name: Işık Biçer
Author-X-Name-First: Işık
Author-X-Name-Last: Biçer
Title: Dual sourcing under heavy-tailed demand: an extreme value theory approach
Abstract: 
 We consider a single-period dual-sourcing problem in which a buyer purchases its products from two different suppliers and sells them to a market with uncertain demand. One supplier is cheaper but less responsive, whereas the other supplier is more responsive but more expensive. The buyer determines the order quantity from the low-cost supplier and the capacity level from the responsive supplier in such a way that maximises its profit. We apply extreme value theory to analyse the impact of tail heaviness of demand distribution on optimal dual-sourcing strategy. We numerically find that tail heaviness moderates the effect of increasing demand uncertainty on optimal order levels. We also show that dual sourcing allows companies to increase their fill rates cost effectively under heavy-tailed demand if the capacity reservation cost of the responsive supplier is relatively low.
Journal: International Journal of Production Research
Pages: 4979-4992
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1008111
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1008111
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Template-Type: ReDIF-Article 1.0
Author-Name: J.N. Roul
Author-X-Name-First: J.N.
Author-X-Name-Last: Roul
Author-Name: K. Maity
Author-X-Name-First: K.
Author-X-Name-Last: Maity
Author-Name: S. Kar
Author-X-Name-First: S.
Author-X-Name-Last: Kar
Author-Name: M. Maiti
Author-X-Name-First: M.
Author-X-Name-Last: Maiti
Title: Multi-item reliability dependent imperfect production inventory optimal control models with dynamic demand under uncertain resource constraint
Abstract: 
 In this paper, imperfect multi-item production inventory models are considered over a finite time horizon with known dynamic demands. The production rates are functions of time which are taken as control variables. In the production process, reliability plays an important role to improve the quality of products and to decrease the defective rate. The said defective units are partially or fully reworked. The unit production cost is a function of production rate and also dependent on raw material cost, development cost due to reliability and wear-tear cost. There is a constraint on the total production cost termed as budget constraint which is crisp/imprecise/random in nature. The objective of the present investigation is to fix the optimum reliabilities of the production system to have maximum return. Thus, the models are formulated as optimal control problems for the maximisation of profit and solved using Hamiltonian (Pontryagin’s Maximum Principle), fixed-final time and free-final state system, Kuhn–Tucker conditions and Generalised Reduced Gradient Method. Several particular cases are derived from the general model. The models are illustrated numerically and graphically and some managerial decisions are derived.
Journal: International Journal of Production Research
Pages: 4993-5016
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1012601
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1012601
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Template-Type: ReDIF-Article 1.0
Author-Name: Albert Corominas
Author-X-Name-First: Albert
Author-X-Name-Last: Corominas
Author-Name: Manel Mateo
Author-X-Name-First: Manel
Author-X-Name-Last: Mateo
Author-Name: Imma Ribas
Author-X-Name-First: Imma
Author-X-Name-Last: Ribas
Author-Name: Sergio Rubio
Author-X-Name-First: Sergio
Author-X-Name-Last: Rubio
Title: Methodological elements of supply chain design
Abstract: 
 After a discussion of the methodological proposals for supply chain (SC) design published so far, we describe a hierarchical method consisting of five stages, as well as related concepts and tools. The aim of this method, named SC outline process, is to provide a frame for the decision-making about the SC configuration. This approach is applicable for all types of SCs.
Journal: International Journal of Production Research
Pages: 5017-5030
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1013641
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1013641
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Template-Type: ReDIF-Article 1.0
Author-Name: William Ho
Author-X-Name-First: William
Author-X-Name-Last: Ho
Author-Name: Tian Zheng
Author-X-Name-First: Tian
Author-X-Name-Last: Zheng
Author-Name: Hakan Yildiz
Author-X-Name-First: Hakan
Author-X-Name-Last: Yildiz
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Title: Supply chain risk management: a literature review
Abstract: 
 Risk management plays a vital role in effectively operating supply chains in the presence of a variety of uncertainties. Over the years, many researchers have focused on supply chain risk management (SCRM) by contributing in the areas of defining, operationalising and mitigating risks. In this paper, we review and synthesise the extant literature in SCRM in the past decade in a comprehensive manner. The purpose of this paper is threefold. First, we present and categorise SCRM research appearing between 2003 and 2013. Second, we undertake a detailed review associated with research developments in supply chain risk definitions, risk types, risk factors and risk management/mitigation strategies. Third, we analyse the SCRM literature in exploring potential gaps.
Journal: International Journal of Production Research
Pages: 5031-5069
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1030467
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1030467
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Template-Type: ReDIF-Article 1.0
Author-Name: Bibhas Chandra Giri
Author-X-Name-First: Bibhas Chandra
Author-X-Name-Last: Giri
Author-Name: Sudarshan Bardhan
Author-X-Name-First: Sudarshan
Author-X-Name-Last: Bardhan
Title: Coordinating a supply chain under uncertain demand and random yield in presence of supply disruption
Abstract: 
 A two-echelon supply chain involving one manufacturer and one retailer for a single product is considered in this paper. The end customers’ demand is assumed to be random. The production of the manufacturer is subject to random yield, and there is a possibility of supply disruption in which case no item from her can reach the retailer. The retailer has a backup supplier who is costlier but perfectly reliable, and is having a limit up to which he may deliver. In addition to placing an order to the manufacturer, the retailer is allowed to reserve a quantity from the backup supplier in the ordering period; he may buy up to the reserved quantity after realising actual market demand in the trading period. Aiming at studying the effects of the various uncertainties involved in the chain on the optimal decisions, we develop and analyse centralised and decentralised models. We also propose a contract mechanism to coordinate the chain and find threshold conditions for which the coordinated model would collapse. Numerical examples are provided to illustrate the developed model.
Journal: International Journal of Production Research
Pages: 5070-5084
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2015.1030469
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1030469
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohit Goswami
Author-X-Name-First: Mohit
Author-X-Name-Last: Goswami
Author-Name: M. K. Tiwari
Author-X-Name-First: M. K.
Author-X-Name-Last: Tiwari
Title: Product feature and functionality driven integrated framework for product commercialization in presence of qualitative consumer reviews
Abstract: 
 The purpose of this research is to aid manufacturers operating in multiple market segments (characterised by a number of product variants) to formulate and synchronise their product commercialisation strategy. Product commercialisation is primarily characterised by upgrading/launching product features aimed at meeting customer’s preferences, while at the same time, enabling the enterprise to achieve its major commercial objectives. Firstly, by employing the semi-automated crowd sourcing-based approach and considering qualitative customer evaluations, customer-preferred product features have been identified and their relative weights determined. Thereafter, a detailed mixed integer quadratic programming formulation has been evolved taking into account pertinent commercial objectives of the enterprise and engineering-level constraints of the product. The developed formulation has been solved using the Branch and Cut method of commercial solver, LINGO. Detailed sensitivity analysis has been carried out, followed by populating key managerial insights. The proposed framework has been illustrated using a real-life case example of operator cabin used in heavy construction equipment industry. Our focus has been on development and illustration of devised framework; hence, the superiority of results has not been claimed. Better results may be obtained using other heuristics/algorithms.
Journal: International Journal of Production Research
Pages: 4769-4788
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.987358
File-URL: http://hdl.handle.net/10.1080/00207543.2014.987358
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Template-Type: ReDIF-Article 1.0
Author-Name: Atul B. Borade
Author-X-Name-First: Atul B.
Author-X-Name-Last: Borade
Author-Name: Edward Sweeney
Author-X-Name-First: Edward
Author-X-Name-Last: Sweeney
Title: Decision support system for vendor managed inventory supply chain: a case study
Abstract: 
 Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs).
Journal: International Journal of Production Research
Pages: 4789-4818
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.993047
File-URL: http://hdl.handle.net/10.1080/00207543.2014.993047
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Template-Type: ReDIF-Article 1.0
Author-Name: Ilkyeong Moon
Author-X-Name-First: Ilkyeong
Author-X-Name-Last: Moon
Author-Name: Xue-Hao Feng
Author-X-Name-First: Xue-Hao
Author-X-Name-Last: Feng
Author-Name: Kwang-Yeol Ryu
Author-X-Name-First: Kwang-Yeol
Author-X-Name-Last: Ryu
Title: Channel coordination for multi-stage supply chains with revenue-sharing contracts under budget constraints
Abstract: 
 Real-life situations show that revenue-sharing (RS) contracts used in multi-stage supply chains have more complex structures than those that have been studied in recent research. In this paper, we study RS contracts in multi-stage supply chains where some members work with more than one upstream member. This general supply chain structure closely resembles those in actual practice under RS contracts. The literature on supply chain contracts has not adequately addressed contract design for supply chains with members who face budget constraints. We show that the RS contract could fail to coordinate supply chains when members are under particular budget constraints. In response, we propose a revenue-sharing with budget constraints (RSB) contract that adds no administrative cost. A properly designed RSB contract can be used to achieve supply chain coordination and to arbitrarily allocate profits in multi-stage supply chains. Our numerical results provide insights into ways supply chain coordination can be achieved under budget constraints through the RSB contract.
Journal: International Journal of Production Research
Pages: 4819-4836
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.993438
File-URL: http://hdl.handle.net/10.1080/00207543.2014.993438
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenfang Shang
Author-X-Name-First: Wenfang
Author-X-Name-Last: Shang
Author-Name: Lei Yang
Author-X-Name-First: Lei
Author-X-Name-Last: Yang
Title: Contract negotiation and risk preferences in dual-channel supply chain coordination
Abstract: 
 This study employs profit-sharing contracts to coordinate dual-channel supply chains and examines the selection of profit-sharing parameters and the allocation of extra system profit gained from coordination. We characterise the Pareto-optimal contracts for the two- and three-stage dual-channel supply chains, by developing and maximising system utility function related to risk preferences and negotiating power. Under the optimal profit-sharing parameter in a two-stage supply chain, both members are reluctant to cooperate; however, in a three-stage supply chain, under the optimal two profit-sharing parameters selected by optimising the system utility function, the retailer is always reluctant to cooperate, but the distributor or the supplier may have incentives to deviate from cooperation. In this case, the distributor and the supplier will negotiate again as in a two-stage supply chain so that all three members can benefit from coordination with profit-sharing contracts. Besides acting independently, the distributor, in the process of contract negotiation, may choose to form an alliance with the upstream supplier or the downstream retailer, which means the relationship among the three members involving profit allocation after coordination is quite different from that for a two-stage supply chain and is not necessarily interest-contrary. In the contract negotiation, in any kind of scenario, risk aversion and negotiation power have a significant impact on the selection of optimal profit-sharing parameters and the allocation of extra system profit. One member’s risk aversion or its negotiation power may be advantageous to the other. Mathematical examples are illustrated to clarify the contract negotiation process.
Journal: International Journal of Production Research
Pages: 4837-4856
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.998785
File-URL: http://hdl.handle.net/10.1080/00207543.2014.998785
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Template-Type: ReDIF-Article 1.0
Author-Name: Timothy D. Fry
Author-X-Name-First: Timothy D.
Author-X-Name-Last: Fry
Author-Name: Joan M. Donohue
Author-X-Name-First: Joan M.
Author-X-Name-Last: Donohue
Author-Name: Brooke A. Saladin
Author-X-Name-First: Brooke A.
Author-X-Name-Last: Saladin
Author-Name: Guangzhi Shang
Author-X-Name-First: Guangzhi
Author-X-Name-Last: Shang
Title: The internationalisation of operations management research
Abstract: 
 Operations management (OM) is a relatively new field of business, having become recognised as a standalone discipline in the mid 1980s. With this in mind, this study analyses the origins, geographical regions, countries, and institutions, of OM research in 11 top level academic journals from 1985 through 2010. Since the field is rather new and is still being developed, an analysis of current and past research constituents offers a unique opportunity to assess how research and education in OM has spread across the globe. We identify those geographic regions and countries that encourage and support OM research and education from the academic institutions within their boundaries. Further, through the research contributions of affiliated authors and PhD graduates, we identify those institutions within each country that are the leaders in terms of OM research and education efforts. We consider the research of faculty affiliated with each institution as well as the research of each institution’s PhD graduates. We find that the early development of the field was centred in the US and UK but, in recent years, much of the research is being published by authors and institutions from many other geographic regions and countries.
Journal: International Journal of Production Research
Pages: 4857-4887
Issue: 16
Volume: 53
Year: 2015
Month: 8
X-DOI: 10.1080/00207543.2014.998792
File-URL: http://hdl.handle.net/10.1080/00207543.2014.998792
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Kusiak
Author-X-Name-First: Andrew
Author-X-Name-Last: Kusiak
Title: Smart manufacturing
Abstract: 
 Manufacturing has evolved and become more automated, computerised and complex. In this paper, the origin, current status and the future developments in manufacturing are disused. Smart manufacturing is an emerging form of production integrating manufacturing assets of today and tomorrow with sensors, computing platforms, communication technology, control, simulation, data intensive modelling and predictive engineering. It utilises the concepts of cyber-physical systems spearheaded by the internet of things, cloud computing, service-oriented computing, artificial intelligence and data science. Once implemented, these concepts and technologies would make smart manufacturing the hallmark of the next industrial revolution. The essence of smart manufacturing is captured in six pillars, manufacturing technology and processes, materials, data, predictive engineering, sustainability and resource sharing and networking. Material handling and supply chains have been an integral part of manufacturing. The anticipated developments in material handling and transportation and their integration with manufacturing driven by sustainability, shared services and service quality and are outlined. The future trends in smart manufacturing are captured in ten conjectures ranging from manufacturing digitisation and material-product-process phenomenon to enterprise dichotomy and standardisation.
Journal: International Journal of Production Research
Pages: 508-517
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1351644
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1351644
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:508-517




Template-Type: ReDIF-Article 1.0
Author-Name: Guang Victor Shi
Author-X-Name-First: Guang Victor
Author-X-Name-Last: Shi
Author-Name: James Baldwin
Author-X-Name-First: James
Author-X-Name-Last: Baldwin
Author-Name: S.C. Lenny Koh
Author-X-Name-First: S.C. Lenny
Author-X-Name-Last: Koh
Author-Name: Thomas Y. Choi
Author-X-Name-First: Thomas Y.
Author-X-Name-Last: Choi
Title: Fragmented institutional fields and their impact on manufacturing environmental practices
Abstract: 
 In the extant literature, manufacturing environmental practices have been attributed to institutional pressures. This study extends this view by observing how different levels of the institutional field (national level vs. regional market level) would have varied effects on manufacturing environmental practices. We empirically investigate, using structural equation modelling, how different types of the manufacturing environmental practices react differently to pressures from a fragmented institutional field. Two distinct types of manufacturing environmental practices occur at the administrative planning operation and technical core operation. Our results confirm such manufacturing environmental practices at different operations lead to different performance benefits – the administrative environmental planning (AEPs) benefit market growth, whereas the technical core environmental practice (TEP) benefit the environment. National-level pressures do not lead to manufacturing environmental practices. Instead, the findings show that institutional pressures at the regional market level influence both types of manufacturing environmental practices. In the contribution, our study has offered an empirical examination of a fragmented institutional field and the impact on two types of manufacturing environmental practices. Further, we also explicitly identified AEPs that lead to market growth and TEPs that create environmental improvement.
Journal: International Journal of Production Research
Pages: 431-446
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1353712
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1353712
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:431-446




Template-Type: ReDIF-Article 1.0
Author-Name: Kevin P. Scheibe
Author-X-Name-First: Kevin P.
Author-X-Name-Last: Scheibe
Author-Name: Jennifer Blackhurst
Author-X-Name-First: Jennifer
Author-X-Name-Last: Blackhurst
Title: Supply chain disruption propagation: a systemic risk and normal accident theory perspective
Abstract: 
 When a disruption occurs in a firm, its effects are often felt throughout the supply chain. As supply chains expand globally and companies pursue velocity and efficiency, the probability of disruptions propagating throughout a chain grows. In this paper, we employ a qualitative, grounded theory case study approach to help understand what drives supply chain disruption propagation and to provide theoretical insights into this emerging area. For a more complete perspective, we study three interconnected tiers in seven unique supply chains. Each supply chain triad consists of (1) a focal firm (a manufacturer), (2) a supplier to the focal firm and (3) a customer of the focal firm allowing us to gain perspective from three levels in multiple supply chains. Three aggregate dimensions are defined which help explain the propagation of supply chain disruptions: the nature of the disruption, structure and dependence, and managerial decision-making. Within these dimensions, six themes are identified giving an increased level of granularity into disruption propagation: correlation of risk, compounding effects, cyclical linkages, counterparty risk, herding and misaligned incentives. Organisations should consider these themes and their interactions to effectively deal with supply chain disruptions.
Journal: International Journal of Production Research
Pages: 43-59
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1355123
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355123
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Template-Type: ReDIF-Article 1.0
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Author-Name: Qingyun Zhu
Author-X-Name-First: Qingyun
Author-X-Name-Last: Zhu
Title: Environmental sustainability and production: taking the road less travelled
Abstract: 
 The research on production and operations management and its linkage to environmental sustainability has seen growth in recent years. The International Journal of Production Research (IJPR) community of scholars has contributed to the advancement of this field. This paper provides an overview of how the research in IJPR has evolved alongside the social-environmental evolution. An overview of the literature of the past 55 years, especially more recent works, is provided. Future predictions of research topics and influences are introduced. Overall, this review found that the call for incorporating environmental sustainability into production research goes back for decades to the early years of IJPR publications. Recent work shows a broader perspective on production research expanding to inter-organisational, supply chain, research. This expanded focus is especially evident in environmental sustainability research. There is still a need and call for expanding the horizon of production and operations management research and environmental sustainability. Travelling the road less travelled is more difficult and complex, but the rewards at the end of this road are a healthy society and environment.
Journal: International Journal of Production Research
Pages: 743-759
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1365182
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1365182
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohsen Moghaddam
Author-X-Name-First: Mohsen
Author-X-Name-Last: Moghaddam
Author-Name: Shimon Y. Nof
Author-X-Name-First: Shimon Y.
Author-X-Name-Last: Nof
Title: Collaborative service-component integration in cloud manufacturing
Abstract: 
 The Industrial Internet technologies are anticipated to enable agile manufacturing processes in response to the growing demand for personalised products/services with shorter lifecycles. This trend has resulted in a gradual transformation of traditional ‘tree-like’ and monolithic systems into complex networks of self-contained and autonomous ‘components’ (a.k.a., Internet of things) and ‘services’ (a.k.a., Internet of services). Cloud Manufacturing is an emerging concept that enables modularisation and service-orientation in the context of manufacturing, in which systematic orchestration, matching, and sharing of services and components are the key. This work develops a framework for dynamic integration of manufacturing services and components in a collaborative network of organisations. The framework dynamically recommends the best matching of services, components and organisations, as well as the best collaboration decisions in terms of sharing (shareable) services and/or components between organisations. The problem is formulated as a bi-objective mixed-integer program, and solved via an efficient socio-inspired tabu search. The objectives of the model are to increase service level and enhance collaboration through maximising service fulfilment and minimising unnecessary sharing of services/components, respectively. Numerical experiments are conducted to demonstrate the benefits of the developed framework for efficient and optimal (re)configuration of collaborative networked organisations, addressing the Industry 4.0 demand for agility through modularisation and service-orientation.
Journal: International Journal of Production Research
Pages: 677-691
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1374574
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1374574
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:677-691




Template-Type: ReDIF-Article 1.0
Author-Name: Joseph Geunes
Author-X-Name-First: Joseph
Author-X-Name-Last: Geunes
Title: Revisiting the two-stage EOQ/EPQ model with inelastic demand: decentralisation and coordination
Abstract: 
 Two-stage operations models serve as a basic unit of analysis for understanding economic trade-offs and conflicting incentives among supply chain partners. We discuss the evolution of such buyer–supplier inventory control models based on the economic order quantity model during the past four decades. In particular, we focus on coordination factors that come into play when the two stages are managed by separate parties based on local incentives. Within this model setting, we characterise conditions under which channel coordination can be achieved using a simple mechanism that does not require costly interaction or negotiation between the two parties. The associated mechanism uses a simple wholesale price with the possible addition of a minimum order quantity (or, alternatively, an associated quantity discount structure). This analysis highlights the key structural drivers that lead to tension between the supplier’s and buyer’s operations preferences and applies a simple approach for mitigating this tension.
Journal: International Journal of Production Research
Pages: 238-250
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1378829
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1378829
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:238-250




Template-Type: ReDIF-Article 1.0
Author-Name: James D. Abbey
Author-X-Name-First: James D.
Author-X-Name-Last: Abbey
Author-Name: V. Daniel R. Guide
Author-X-Name-First: V. Daniel R.
Author-X-Name-Last: Guide
Title: A typology of remanufacturing in closed-loop supply chains
Abstract: 
 This manuscript defines a typology of remanufacturing based on multiple decades of direct observations across various remanufacturing industries. The manuscript also details how managers adapt their remanufacturing operations and strategies to the idiosyncrasies of the varied remanufacturing industries. The typology identifies four distinct typological groupings based on the dimensions of a firm’s strategic focus and product design philosophy. Before delving into typology and implications on strategic and design issues, the manuscript provides recent information on the current state of the remanufacturing industry based on governmental and industry reports. To assist readers who may be less familiar with the remanufacturing industry and closed-loop supply chains, the discussion also provides a brief overview of remanufacturing processes and the overall remanufacturing industry.
Journal: International Journal of Production Research
Pages: 374-384
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1384078
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1384078
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:374-384




Template-Type: ReDIF-Article 1.0
Author-Name: Dante Chavarría-Barrientos
Author-X-Name-First: Dante
Author-X-Name-Last: Chavarría-Barrientos
Author-Name: Rafael Batres
Author-X-Name-First: Rafael
Author-X-Name-Last: Batres
Author-Name: Paul K. Wright
Author-X-Name-First: Paul K.
Author-X-Name-Last: Wright
Author-Name: Arturo Molina
Author-X-Name-First: Arturo
Author-X-Name-Last: Molina
Title: A methodology to create a sensing, smart and sustainable manufacturing enterprise
Abstract: 
 Next-generation manufacturing enterprises need to be sensing, smart and sustainable to be competitive: ‘sensing’ refers to context awareness at internal and external levels; ‘smart’ refers to knowledge-based organisations that adapt to changes and ‘sustainable’ refers to the ability to operate without damaging the environment, community or economy. Although technologies do exist to support the development of such enterprises, there is a need for methodologies that help in the entire enterprise engineering problem. This paper proposes a methodology, based on the principles of enterprise architecture, to design a sensing, smart and sustainable manufacturing enterprise. The methodology aims at adopting the best practices used in enterprise engineering while dealing with the relevant gaps. An analysis of the characteristics of the ‘Sensing, Smart and Sustainable Manufacturing Enterprise’ (S3-ME) is presented to understand the advantages of using the proposed methodology. The methodology comprises the instantiation of five viewpoints presented in the Reference Model of Open Distributed Processing (ISO/IEC 10746 RM-ODP) and redefined by the Smart and Sensing Enterprise Reference Model (S2E-RM). The viewpoint instantiation is described and then exemplified with a case study. As a result of the instantiation, the enterprise is defined through an enterprise model.
Journal: International Journal of Production Research
Pages: 584-603
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1386333
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1386333
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:584-603




Template-Type: ReDIF-Article 1.0
Author-Name: Wallace J. Hopp
Author-X-Name-First: Wallace J.
Author-X-Name-Last: Hopp
Title: Positive lean: merging the science of efficiency with the psychology of work
Abstract: 
 Lean is a powerful management system aimed at improving efficiency and operational effectiveness. Since its emergence in the automotive industry, lean has been adapted for use in almost all manufacturing and service industries. And yet, most lean implementations fail to achieve their efficiency goals and many have deleterious impacts on the workforce. We trace both failures to a historical departure of lean practices from known principles of factory physics and job design. By leveraging these principles, we describe how lean practices can be designed to promote both operational efficiency and increased workforce satisfaction.
Journal: International Journal of Production Research
Pages: 398-413
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1387301
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1387301
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:398-413




Template-Type: ReDIF-Article 1.0
Author-Name: E.W.T. Ngai
Author-X-Name-First: E.W.T.
Author-X-Name-Last: Ngai
Author-Name: Chuck C.H. Law
Author-X-Name-First: Chuck C.H.
Author-X-Name-Last: Law
Author-Name: Carlos W.H. Lo
Author-X-Name-First: Carlos W.H.
Author-X-Name-Last: Lo
Author-Name: J.K.L. Poon
Author-X-Name-First: J.K.L.
Author-X-Name-Last: Poon
Author-Name: Shanshan Peng
Author-X-Name-First: Shanshan
Author-X-Name-Last: Peng
Title: Business sustainability and corporate social responsibility: case studies of three gas operators in China
Abstract: 
 This study investigates the corporate social responsibility (CSR) practices of three gas operators in China and the benefits resulting from these practices. The current paper provides the proposed conceptual framework, literature review of CSR theories and prior research on the experiences of companies operating in various sectors. Data from in-depth case studies of the three gas distributors in Mainland China are collected, analysed and summarised. The three gas distributors proactively developed their respective CSR objectives and engaged in CSR practices in many dimensions that related to employees, consumers, investors, community and the environment. Consequently, the benefits realised for various stakeholders and for the three companies include high-quality products and service offerings, reliable and efficient supply chain, stable cash flow, loyal customer bases, positive social image and reputation, and overall top firm’s performance. On the bases of the literature review and case analysis, implications that focus on two areas are derived and presented in this paper. Governments and other nonprofit organisations such as professional associations and trade unions play their respective roles in CSR. Government authorities can shape the CSR practices of business enterprises by providing a legal framework and related policies to guide company practices.
Journal: International Journal of Production Research
Pages: 660-676
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1387303
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1387303
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:660-676




Template-Type: ReDIF-Article 1.0
Author-Name: Yoram Koren
Author-X-Name-First: Yoram
Author-X-Name-Last: Koren
Author-Name: Xi Gu
Author-X-Name-First: Xi
Author-X-Name-Last: Gu
Author-Name: Weihong Guo
Author-X-Name-First: Weihong
Author-X-Name-Last: Guo
Title: Choosing the system configuration for high-volume manufacturing
Abstract: 
 When designing a new large manufacturing system with high throughput, the corporation should weigh several factors: the capital investment cost, the system’s responsiveness to future varying market demand, the production losses due to disruptive events, and the product quality. These performance metrics depend heavily on the system configuration. In this paper, typical configurations of large-volume manufacturing systems for mechanical products are compared from cost, responsiveness and product quality perspectives. In addition to traditional serial lines and pure parallel systems, we also discuss two practical configurations – parallel serial lines, and reconfigurable manufacturing systems. The results offer managerial insights for selecting the system configuration that creates the maximum economic value over the lifetime of the system, and fits the corporation needs and culture.
Journal: International Journal of Production Research
Pages: 476-490
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1387678
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1387678
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:476-490




Template-Type: ReDIF-Article 1.0
Author-Name: Matias Siebert
Author-X-Name-First: Matias
Author-X-Name-Last: Siebert
Author-Name: Kelly Bartlett
Author-X-Name-First: Kelly
Author-X-Name-Last: Bartlett
Author-Name: Haejoong Kim
Author-X-Name-First: Haejoong
Author-X-Name-Last: Kim
Author-Name: Shabbir Ahmed
Author-X-Name-First: Shabbir
Author-X-Name-Last: Ahmed
Author-Name: Junho Lee
Author-X-Name-First: Junho
Author-X-Name-Last: Lee
Author-Name: Dima Nazzal
Author-X-Name-First: Dima
Author-X-Name-Last: Nazzal
Author-Name: George Nemhauser
Author-X-Name-First: George
Author-X-Name-Last: Nemhauser
Author-Name: Joel Sokol
Author-X-Name-First: Joel
Author-X-Name-Last: Sokol
Title: Lot targeting and lot dispatching decision policies for semiconductor manufacturing: optimisation under uncertainty with simulation validation
Abstract: 
 Because semiconductor manufacturing is a complex and dynamic process, production scheduling in this industry typically relies on simple decision policies that use local rather than global information. Such myopic policies may lead to increased congestion in the material handling system and negatively impact throughput. In this paper, we propose a fluid-model lot dispatching policy that iteratively optimises lot selection based on current WIP distribution of the entire system. Furthermore, we propose to split the decision policies into two phases in order to include travel times information into the dispatching and targeting decisions. We provide simulation results for a prototype facility that show that our proposed policies outperform commonly used dispatching rules in throughput, machine utilisation and machine target accuracy.
Journal: International Journal of Production Research
Pages: 629-641
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1387679
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1387679
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Boris Sokolov
Author-X-Name-First: Boris
Author-X-Name-Last: Sokolov
Title: Ripple effect in the supply chain: an analysis and recent literature
Abstract: 
 In this study, the ripple effect in the supply chain is analysed. Ripple effect describes the impact of a disruption propagation on supply chain performance and disruption-based scope of changes in supply chain structural design and planning parameters. We delineate major features of the ripple effect as compared to the bullwhip effect. Subsequently, we review recent quantitative literature that tackled the ripple effect explicitly or implicitly and give our vision of the state of the art and perspectives. The literature is classified into mathematical optimisation, simulation, control theoretic and complexity and reliability research. We observe the reasons and mitigation strategies for the ripple effect in the supply chain and present the ripple effect control framework that includes redundancy, flexibility and resilience analysis. Even though a variety of valuable insights has been developed in the said area in recent years, some crucial research avenues have been identified for the near future.
Journal: International Journal of Production Research
Pages: 414-430
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1387680
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1387680
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:414-430




Template-Type: ReDIF-Article 1.0
Author-Name: ManMohan S. Sodhi
Author-X-Name-First: ManMohan S.
Author-X-Name-Last: Sodhi
Author-Name: Christopher S. Tang
Author-X-Name-First: Christopher S.
Author-X-Name-Last: Tang
Title: Corporate social sustainability in supply chains: a thematic analysis of the literature
Abstract: 
 This paper maps out different research strands using thematic analysis on the literature pertaining to large companies’ efforts on social sustainability in their supply chains. The data corpus for this thematic analysis is a broad sample of the literature with articles from different journals and employing different research methodologies. Each of the high-level themes is identified at a level high enough to apply to research into not only social but also economic or environmental sustainability. These eight themes – stakeholder pressure; governance; contingencies; practices; partnerships; barriers and enablers; performance; and optimisation for performance improvement and trade-off – are then woven into a thematic map. We call this map the ‘4P’ model as it suggests that pressure and partnerships influence practices, which in turn impact performance. Researchers can use this thematic classification not only to position their research within the social sustainability literature but also to integrate research on economic, environmental and social sustainability.
Journal: International Journal of Production Research
Pages: 882-901
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1388934
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1388934
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:882-901




Template-Type: ReDIF-Article 1.0
Author-Name: Javad Navaei
Author-X-Name-First: Javad
Author-X-Name-Last: Navaei
Author-Name: Hoda ElMaraghy
Author-X-Name-First: Hoda
Author-X-Name-Last: ElMaraghy
Title: Optimal operations sequence retrieval from master operations sequence for part/product families
Abstract: 
 This research capitalises on commonalities between members of a product family to increase the speed, consistency and efficiency of constructing a master operations sequence and optimal operations sequences for new variants. Two novel mixed integer programming (MIP) models are developed for generating master operations sequence based on available operations sequences of a family of part/product variants. The use of master operations sequence reduces the time, cost and effort required for developing new operations sequences, hence improving the planning efficiency and productivity. The first MIP model is developed for variants with serial operations sequence while the second is a generalised model for serial, networked operations sequences or a combination of both structures. The developed models generate master operations sequences which have minimum total dissimilarity distance from existing variants. The master operations sequence is then used to construct the operations sequence for new variants falling within or significantly overlapping with the boundary of the considered product family. As the number of operations increases, the efficiency of mathematical models decreases. Therefore, a novel algorithm is proposed to generate master operations sequences for product variants with any type of process sequence structure (i.e. serial, networked, or combination). Computational results demonstrated the capability of developed MIP algorithms to find optimum solutions and optimal operations sequence for new variants in a fraction of a second in most cases of small, medium and large size studied problems. Two assembly and fabrication case studies are provided for demonstration.
Journal: International Journal of Production Research
Pages: 140-163
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1391417
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1391417
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:140-163




Template-Type: ReDIF-Article 1.0
Author-Name: Yongli Wang
Author-X-Name-First: Yongli
Author-X-Name-Last: Wang
Author-Name: Juliang Zhang
Author-X-Name-First: Juliang
Author-X-Name-Last: Zhang
Author-Name: T.C. Edwin Cheng
Author-X-Name-First: T.C. Edwin
Author-X-Name-Last: Cheng
Author-Name: Guowei Hua
Author-X-Name-First: Guowei
Author-X-Name-Last: Hua
Title: Quick response under strategic consumers with risk preference and decreasing valuation
Abstract: 
 This paper addresses the impact of the quick response (QR) strategy on the profit of a retailer that sells a product to strategic consumers with risk preference and decreasing valuation, and makes pricing and order quantity decisions. We find that the optimal pricing and expected profit decrease in consumers’ risk preference and valuation decreasing rate, and the optimal inventory is unrelated to them. The effect of the QR strategy depends on the QR cost, consumers’ risk preference, and valuation decreasing rate. When the QR cost is low, the QR strategy can mitigate strategic consumers’ behaviour and bring profit to the retailer. Otherwise, the QR strategy may further reduce the retailer’s expected profit and intensify the negative effect of strategic consumers’ behaviour. The profit brought by the QR strategy decreases in consumers’ risk preference and valuation decreasing rate. Furthermore, we consider the case involving heterogeneous strategic consumers. We find that the proportion of high-valuation consumers in the market has an impact on the optimal decisions of the retailer and the effect of the QR strategy. The more high-valuation consumers there are, the greater is the profit brought by the QR strategy.
Journal: International Journal of Production Research
Pages: 72-85
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1391421
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1391421
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:72-85




Template-Type: ReDIF-Article 1.0
Author-Name: Steven A. Melnyk
Author-X-Name-First: Steven A.
Author-X-Name-Last: Melnyk
Author-Name: Barbara B. Flynn
Author-X-Name-First: Barbara B.
Author-X-Name-Last: Flynn
Author-Name: Amrou Awaysheh
Author-X-Name-First: Amrou
Author-X-Name-Last: Awaysheh
Title: The best of times and the worst of times: empirical operations and supply chain management research
Abstract: 
 We assess the current state of empirical research in operations and supply chain management (OSM), using Dickens’ contrast between the best of times and the worst of times as a frame. The best of times refers to the future that empirical OSM research is now entering, with exciting opportunities available using big data and other new data sources, new empirical approaches and analytical techniques and innovative tools for developing theory. These are well aligned with new research questions related to the digital economy, Industry 4.0, the impact of the millennial generation as consumers, social media, 3D printing, etc. However, we also explore how it is the worst of times, focusing on the challenges and problems that plague empirical OSM research. Our goal is to show how OSM researchers can learn from the worst of times, in order to be poised to take advantage of the best of times. We introduce the research diamond as a vehicle for emphasising the importance of a balanced research perspective that treats the research problem, theory, data collection and data analysis as equally important, requiring alignment between them. By learning and addressing the issues in this period of the best of times and the worst of times, we can take advantage of the opportunities facing our field to generate research that is balanced, insightful, rigorous, relevant, impactful and interesting.
Journal: International Journal of Production Research
Pages: 164-192
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1391423
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1391423
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:164-192




Template-Type: ReDIF-Article 1.0
Author-Name: Joachim Scholl
Author-X-Name-First: Joachim
Author-X-Name-Last: Scholl
Author-Name: David Boywitz
Author-X-Name-First: David
Author-X-Name-Last: Boywitz
Author-Name: Nils Boysen
Author-X-Name-First: Nils
Author-X-Name-Last: Boysen
Title: On the quality of simple measures predicting block relocations in container yards
Abstract: 
 The blocks relocation problem aims to minimise the number of unproductive relocation moves where blocking containers have to be removed to other stacks when retrieving containers in a given sequence from a container yard. Sometimes there is not enough time to solve this complex optimisation problem and information on the crane performance, which mainly depends on the relocation effort, is required under great time pressure. In this case, simple measures are required, which are quickly computed and, nonetheless, accurately predict the amount of relocation moves. This paper is dedicated to comparing twelve different known and new measures. Our computational study shows that composite measures combining a lower bound argument with a simple rule-based upper bound lead to predictions of remarkable accuracy.
Journal: International Journal of Production Research
Pages: 60-71
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1394595
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394595
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:60-71




Template-Type: ReDIF-Article 1.0
Author-Name: Changyi Deng
Author-X-Name-First: Changyi
Author-X-Name-Last: Deng
Author-Name: Ruifeng Guo
Author-X-Name-First: Ruifeng
Author-X-Name-Last: Guo
Author-Name: Chao Liu
Author-X-Name-First: Chao
Author-X-Name-Last: Liu
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Title: Data cleansing for energy-saving: a case of Cyber-Physical Machine Tools health monitoring system
Abstract: 
 Cyber-Physical Production Systems (CPPS) often use wireless sensor networks (WSNs) for monitoring purposes. However, data from WSNs may be inaccurate and unreliable due to power exhaustion, noise and other issues. In order to achieve a reliable and accurate data acquisition while ensuring low energy consumption and long lifetime of WSNs, data cleansing algorithms for energy-saving are proposed in this research. The cleansing algorithms are computationally lightweight in local sensors and energy-efficient due to low energy consumption in communications. Dynamic voltage scaling and dynamic power management are adopted for reducing energy consumption, without compromising the performance at system level. A low-power protocol for sink node communication is proposed at network level. A health monitoring system for a Cyber-Physical Machine Tool (a typical example of CPPS) is designed. Experiment results show that the proposed energy-saving data cleansing algorithm yields high-performance and effective monitoring.
Journal: International Journal of Production Research
Pages: 1000-1015
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1394596
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394596
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:1000-1015




Template-Type: ReDIF-Article 1.0
Author-Name: Michel Minoux
Author-X-Name-First: Michel
Author-X-Name-Last: Minoux
Title: Robust and stochastic multistage optimisation under Markovian uncertainty with applications to production/inventory problems
Abstract: 
 A generic class of multistage optimisation problems related to production/inventory management under Markovian uncertainty is introduced and investigated. For each instance in the class, it is shown how to construct state-space representable uncertainty sets at any probability level, thus leading to efficient resolution of both the stochastic and robust versions of the problem. Computational experiments aimed at comparing the optimal strategies corresponding to both versions in terms of risk are then reported and discussed; it is observed that the robust optimisation approach can significantly outperform the stochastic optimisation approach when targeting lower risk levels (typically less than 2%).
Journal: International Journal of Production Research
Pages: 565-583
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1394597
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394597
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:565-583




Template-Type: ReDIF-Article 1.0
Author-Name: Leandro R. Mundim
Author-X-Name-First: Leandro R.
Author-X-Name-Last: Mundim
Author-Name: Marina Andretta
Author-X-Name-First: Marina
Author-X-Name-Last: Andretta
Author-Name: Maria Antónia Carravilla
Author-X-Name-First: Maria Antónia
Author-X-Name-Last: Carravilla
Author-Name: José Fernando Oliveira
Author-X-Name-First: José Fernando
Author-X-Name-Last: Oliveira
Title: A general heuristic for two-dimensional nesting problems with limited-size containers
Abstract: 
 Cutting raw-material into smaller parts is a fundamental phase of many production processes. These operations originate raw-material waste that can be minimised. These problems have a strong economic and ecological impact and their proper solving is essential to many sectors of the economy, such as the textile, footwear, automotive and shipbuilding industries, to mention only a few. Two-dimensional (2D) nesting problems, in particular, deal with the cutting of irregularly shaped pieces from a set of larger containers, so that either the waste is minimised or the value of the pieces actually cut from the containers is maximised. Despite the real-world practical relevance of these problems, very few approaches have been proposed capable of dealing with concrete characteristics that arise in practice. In this paper, we propose a new general heuristic (H4NP) for all 2D nesting problems with limited-size containers: the Placement problem, the Knapsack problem, the Cutting Stock problem, and the Bin Packing problem. Extensive computational experiments were run on a total of 1100 instances. H4NP obtained equal or better solutions for 73% of the instances for which there were previous results against which to compare, and new benchmarks are proposed.
Journal: International Journal of Production Research
Pages: 709-732
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1394598
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394598
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:709-732




Template-Type: ReDIF-Article 1.0
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Yahaya Y. Yusuf
Author-X-Name-First: Yahaya Y.
Author-X-Name-Last: Yusuf
Author-Name: Ezekiel O. Adeleye
Author-X-Name-First: Ezekiel O.
Author-X-Name-Last: Adeleye
Author-Name: Thanos Papadopoulos
Author-X-Name-First: Thanos
Author-X-Name-Last: Papadopoulos
Title: Agile manufacturing practices: the role of big data and business analytics with multiple case studies
Abstract: 
 The purpose of this study was to examine the role of big data and business analytics (BDBA) in agile manufacturing practices. Literature has discussed the benefits and challenges related to the deployment of big data within operations and supply chains, but there has not been a study of the facilitating roles of BDBA in achieving an enhanced level of agile manufacturing practices. As a response to this gap, and drawing upon multiple qualitative case studies undertaken among four UK organisations, we present and validate a framework for the role of BDBA within agile manufacturing. The findings show that market turbulence has negative universal effects and that agile manufacturing enablers are being progressively deployed and aided by BDBA to yield better competitive and business performance objectives. Further, the level of intervention was found to differ across companies depending on the extent of deployment of BDBA, which accounts for variations in outcomes.
Journal: International Journal of Production Research
Pages: 385-397
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1395488
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1395488
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:385-397




Template-Type: ReDIF-Article 1.0
Author-Name: Nynke Faber
Author-X-Name-First: Nynke
Author-X-Name-Last: Faber
Author-Name: René B.M. De Koster
Author-X-Name-First: René B.M.
Author-X-Name-Last: De Koster
Author-Name: Ale Smidts
Author-X-Name-First: Ale
Author-X-Name-Last: Smidts
Title: Survival of the fittest: the impact of fit between warehouse management structure and warehouse context on warehouse performance
Abstract: 
 Warehouse operations are vital for the success of a supply chain. This paper explores fit among warehouse management structure and the context in which the warehouse operates as an important driver of warehouse performance. Warehouse management structure has been operationalised as the extensiveness by which warehouse operations are planned and controlled, and the complexity of the decision rules used for optimisation of the operations. Warehouse performance is measured using data envelopment analysis (DEA). Hypotheses are developed and tested in a survey study among 111 distribution warehouses in the Netherlands and Belgium. Our results show that indeed warehouse management structure should be adapted to context. In order to obtain high warehouse performance more complex warehouse tasks require more and more complex decision rules, and warehouses with more unpredictable demand require fewer tactical plans. These results can help warehouse managers to structure their warehouse management contingent on the context in which the warehouse operates.
Journal: International Journal of Production Research
Pages: 120-139
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1395489
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1395489
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:120-139




Template-Type: ReDIF-Article 1.0
Author-Name: Yael Deutsch
Author-X-Name-First: Yael
Author-X-Name-Last: Deutsch
Author-Name: Boaz Golany
Author-X-Name-First: Boaz
Author-X-Name-Last: Golany
Title: A parcel locker network as a solution to the logistics last mile problem
Abstract: 
 We consider the problem of designing a parcel locker network as a solution to the Logistics Last Mile Problem: Choosing the optimal number, locations, and sizes of parcel locekers facilities. The objective is to maximize the total profit, consisting of the revenue from customers who use the service, minus the facilities’ fixed and operational setup costs, the discounts in the delivery costs for customers who need to travel in order to collect their parcels, and the loss of potential customers who are not willing to travel for service. The problem is expressed as a 0–1 integer linear program. We show that it is equivalent to the well-known Uncapacitated Facility Location Problem. We then solve the modified problem, and apply it to an industrial-sized network.
Journal: International Journal of Production Research
Pages: 251-261
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1395490
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1395490
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:251-261




Template-Type: ReDIF-Article 1.0
Author-Name: Stanley B. Gershwin
Author-X-Name-First: Stanley B.
Author-X-Name-Last: Gershwin
Title: The future of manufacturing systems engineering
Abstract: 
 Manufacturing systems engineering will be greatly affected by advances in technology, including cheaper, ubiquitous sensors, increasing computational speeds, the ability to hold more data and move it faster, and artificial intelligence. This paper discusses the importance of human involvement in the field, especially the role of intuition. The issues examined are the purposes of manufacturing systems engineering; the importance of intuition, and more generally, the role that humans play in the design and operations of manufacturing systems; the effects of new systems-related technologies; how analytical models help the development of intuition; how the use of generic software without intuition can lead to trouble; how intuition is needed to determined what data, and how much of it, is needed for a given purpose. It also describes some successful applications of manufacturing systems research and proposes an organisational structure for manufacturing systems groups.
Journal: International Journal of Production Research
Pages: 224-237
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1395491
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1395491
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:224-237




Template-Type: ReDIF-Article 1.0
Author-Name: Henk A. Akkermans
Author-X-Name-First: Henk A.
Author-X-Name-Last: Akkermans
Author-Name: Luk N. Van Wassenhove
Author-X-Name-First: Luk N.
Author-X-Name-Last: Van Wassenhove
Title: A dynamic model of managerial response to grey swan events in supply networks
Abstract: 
 In our increasingly volatile world, very unlikely events, so-called black swans, occur more often, inflicting massive damage on production environments. But there are also so-called grey swan events, equally destructive, but not utterly unpredictable. They have already occurred in the past, perhaps in related production settings. We present a dynamic model that analyses how grey swan events originate in supply networks and how they can be prevented. Most of the literature so far has focused on external risks, beyond the scope of managerial control. This paper introduces a formal model in which a central role is played by management and its inability to observe and act timely on signals of growing operational issues which cause grey swan events. The paper starts with an empirical investigation of one grey swan event, the Airbus A380 introduction. Our model can replicate this type of grey swan behaviour. With this model, we conduct a system dynamics analysis of the mechanisms that can create or prevent a particular type of grey swan event, a business tsunami. The level of managerial preparedness to actively ‘search for the grey swans’ is found to be a key prerequisite to prevent destructive impact on production supply networks. Our paper suggests ways in which the field of production research can help foster such structurally high managerial preparedness.
Journal: International Journal of Production Research
Pages: 10-21
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1395492
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1395492
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:10-21




Template-Type: ReDIF-Article 1.0
Author-Name: Jasneet Kaur
Author-X-Name-First: Jasneet
Author-X-Name-Last: Kaur
Author-Name: Ramneet Sidhu
Author-X-Name-First: Ramneet
Author-X-Name-Last: Sidhu
Author-Name: Anjali Awasthi
Author-X-Name-First: Anjali
Author-X-Name-Last: Awasthi
Author-Name: Satyaveer Chauhan
Author-X-Name-First: Satyaveer
Author-X-Name-Last: Chauhan
Author-Name: Suresh Goyal
Author-X-Name-First: Suresh
Author-X-Name-Last: Goyal
Title: A DEMATEL based approach for investigating barriers in green supply chain management in Canadian manufacturing firms
Abstract: 
 Green supply chain management (GSCM) involves consideration of environmental impacts of all the processes involved in a typical supply chain to minimise their negative consequences. In this paper, we present a DEMATEL-based approach for investigating barriers in GSCM in Canadian context. Seven manufacturing firms from electronic goods sector are involved. The results of our study yield three main categories of barriers. These barriers are knowledge-related (lack of awareness of the environmental impacts on business, lack of training courses/consultancy/institutions to train, monitor/mentor progress specific to each industry, lack of technical expertise and difficulty in identifying environmental opportunities), commitment-related (lack of corporate social responsibility) and product design-related (complexity of design to reuse/recycle used products). The proposed study is one of the first few to be conducted in the Canadian context for green supply chain barrier analysis for electronic goods sector. Secondly, the barriers are investigated through causality and prominence relations which can help decision-makers, policy planners and managers of organisations in addressing those critical few for making green supply chain practices a success.
Journal: International Journal of Production Research
Pages: 312-332
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1395522
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1395522
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:312-332




Template-Type: ReDIF-Article 1.0
Author-Name: Chelliah Sriskandarajah
Author-X-Name-First: Chelliah
Author-X-Name-Last: Sriskandarajah
Author-Name: Bala Shetty
Author-X-Name-First: Bala
Author-X-Name-Last: Shetty
Title: A review of recent theoretical development in scheduling dual-gripper robotic cells
Abstract: 
 A robotic cell is a set of machines or processing centres served by a robot or a set of robots. Robotic cells can be classified by certain physical and operating characteristics such as robot type (single- or dual-gripper), robot travel-time (constant, additive or Euclidean) and types of parts processed (no-wait, interval processing time or free-pickup). Robotic cells are used in automated manufacturing systems where jobs or parts are produced in a typical flow shop type environment. A significant research effort has been directed towards analysing the problem of robot move sequencing in robotic cells served by single- or dual-gripper robot. In this review paper, we examine the recent theoretical developments on the analysis of throughput optimisation in robotic cells served by a dual-gripper robot. We focus on the problem of scheduling operations in dual-gripper robotic cells that produce identical parts. The objective is to find a cyclic sequence of robot moves that minimises the long-run average time to produce a part or, equivalently, maximises the throughput. The goals of this review paper are to: (i) provide a discussion of existing structural analysis, algorithmic and complexity results for robotic cells under conditions that are common in practice and (ii) present a set of open problems and future research directions. In addition to reporting recent results for dual-gripper robotic cell scheduling problems, we provide insight into a class of cyclic sequences that are not considered in practice but can improve throughput.
Journal: International Journal of Production Research
Pages: 817-847
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1397792
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1397792
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:817-847




Template-Type: ReDIF-Article 1.0
Author-Name: Jiho Yoon
Author-X-Name-First: Jiho
Author-X-Name-Last: Yoon
Author-Name: Claudia Rosales
Author-X-Name-First: Claudia
Author-X-Name-Last: Rosales
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Title: Inter-firm partnerships – strategic alliances in the pharmaceutical industry
Abstract: 
 In recent years, strategic alliances have become key to success in sectors such as pharmaceutical and high-tech industry. Strategic partnerships between start-ups and big pharmaceutical companies have become more prevalent and are typically motivated by the benefits that can be obtained from complementary capabilities. These contractual relationships typically use different financial incentives such as royalties, upfront or milestone payments. The best type of contractual conditions for these strategic alliances may not always be clear. We study three different types of contracts, milestone and optional upfront payment, royalty and optional upfront payment, and acquisition contract. We characterise the optimal decisions for each contract option and provide insights into the benefits each contract type offers for start-ups and big pharmaceutical companies.
Journal: International Journal of Production Research
Pages: 862-881
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1397793
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1397793
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:862-881




Template-Type: ReDIF-Article 1.0
Author-Name: Michael F. Gorman
Author-X-Name-First: Michael F.
Author-X-Name-Last: Gorman
Author-Name: Daniel G. Conway
Author-X-Name-First: Daniel G.
Author-X-Name-Last: Conway
Title: A tutorial of integrating duality and branch and bound in earliness–tardiness scheduling with idle insertion time problems
Abstract: 
 We present a conceptual tutorial of the value of the dual representation to branching strategies of idle insertion time in a single-machine scheduling problem. We consider the problem where scheduling generally occurs in two phases: a sequence of activities is first determined, then idle time is inserted into the schedule to minimise the sum of early and tardy costs. Typically, the sequence of jobs is determined first using a heuristic method. The idle time insertion problem is solved via linear programming to establish starting and ending times of the activities. In this paper, we show how the dual of the idle time insertion problem can be used as a means of generating insights for earliness–tardiness sequencing algorithms. We provide an extended tutorial on a new way of branching based on dual information. We find that in our simple examples, the search space can be vastly reduced, improving the feasibility of branch-and-bound improvements to heuristic solutions. We suggest that the dual approach is a useful and intuitive way to improve scheduling solutions in short order.
Journal: International Journal of Production Research
Pages: 262-277
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1397794
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1397794
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:262-277




Template-Type: ReDIF-Article 1.0
Author-Name: David L. Olson
Author-X-Name-First: David L.
Author-X-Name-Last: Olson
Title: View of IJPR contributions to knowledge management in supply chains
Abstract: 
 Knowledge management can be viewed as the ability to identify, store and retrieve knowledge. This paper presents a view of four perspectives of IJPR papers related to knowledge management, focusing on the specific perspectives related to information systems, computer software and analytics support of supply chain management. IJPR publications since 2006 that used these key terms are included in a primitive network analysis of these papers. A dichotomy of knowledge management into information systems versus quantitative analysis is detected, with some minimal overlap. This analysis elaborates the evolution of both analytics and information systems in knowledge management. The network is also viewed from specific relation to three fields considered important now and in the near future: sustainability, multiple criteria decision-making and supply chain risk management. The intent is to identify a view of the state-of-the-art of IJPR published research related to knowledge management in supply chains.
Journal: International Journal of Production Research
Pages: 733-742
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1398427
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398427
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:733-742




Template-Type: ReDIF-Article 1.0
Author-Name: Rong Yuan
Author-X-Name-First: Rong
Author-X-Name-Last: Yuan
Author-Name: Tolga Cezik
Author-X-Name-First: Tolga
Author-X-Name-Last: Cezik
Author-Name: Stephen C. Graves
Author-X-Name-First: Stephen C.
Author-X-Name-Last: Graves
Title: Stowage decisions in multi-zone storage systems
Abstract: 
 The stowage decision determines how arriving products are distributed in a storage system or warehouse. In particular, we consider the zone-stowage decision for large warehouses that are organised into distinct storage zones. An example would be a multi-floor warehouse where each floor is a storage zone. Each storage zone has limited picking capacity; we want to stow the product inventory across the storage zones so as to be able to meet uncertain demand requirements with the limited picking capacity in each zone. Determining how to spread the inventory across the storage zones is the zone-stowage decision that we consider in this paper. With a simulation study, we identify two zone-stowage policies that are effective in balancing the picking workload across different storage zones. The first zone-stowage policy achieves a chaining-inspired allocation by splitting the received quantity for each product across two storage zones; the second zone-stowage policy explicitly tracks the expected workload for each storage zone, termed the velocity of the zone, and then stows arriving products to the storage zone with the smallest velocity.
Journal: International Journal of Production Research
Pages: 333-343
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1398428
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398428
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:333-343




Template-Type: ReDIF-Article 1.0
Author-Name: Patricia van Loon
Author-X-Name-First: Patricia
Author-X-Name-Last: van Loon
Author-Name: Charles Delagarde
Author-X-Name-First: Charles
Author-X-Name-Last: Delagarde
Author-Name: Luk N. Van Wassenhove
Author-X-Name-First: Luk N.
Author-X-Name-Last: Van Wassenhove
Title: The role of second-hand markets in circular business: a simple model for leasing versus selling consumer products
Abstract: 
 This paper explores the role of the second-hand market when transitioning to a closed-loop system where products are leased multiple times. The total cost of ownership for consumers and profitability for manufacturers are compared in circular and linear business cases. We find that while second-hand markets were beneficial for manufacturers of durable goods in a linear system, since they increased the consumers’ willingness-to-pay for new products, the same second-hand markets might restrict the profitability of a closed-loop business model. A high resale value results in a relatively low cost of ownership in the sales system and additional activities in the closed-loop model (such as managing the lease contracts and refurbishment) add significant costs to the supply chain. Consequently, the economic (and environmental) benefits of leasing products already traded on second-hand markets in the linear system are often limited. Our simple analytical model allows a quick and dirty analysis of multiple scenarios with a minimum of inputs. We argue that manufacturers lack these kinds of models to guide them in navigating circular economy business models.
Journal: International Journal of Production Research
Pages: 960-973
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1398429
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398429
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:960-973




Template-Type: ReDIF-Article 1.0
Author-Name: Haihong Yu
Author-X-Name-First: Haihong
Author-X-Name-Last: Yu
Author-Name: Suresh P. Sethi
Author-X-Name-First: Suresh P.
Author-X-Name-Last: Sethi
Author-Name: Xi Shan
Author-X-Name-First: Xi
Author-X-Name-Last: Shan
Title: Creative delinquency or destructive selfishness?
Abstract: 
 We study two competing firms with different production costs and moral standards making decisions to sell their products in the market by choosing their optimal production quantities and degrees of disobedience of a guiding rule imposed by a regulatory authority such as the government. We model this problem as a Cournot–Nash game in which. We introduce rules unfairness as a behavioural factor at work. We answer the questions of why firms disobey rules and to what degree and what are the effects of such actions. Our results show that firms disobey the rules for self-interest and harm other incentives. The case when the firms’ disobediences can improve the total surplus (sum of their profits) is referred to as creative delinquency, whereas destructive selfishness refers to situation in which one’s behaviour only benefits self and leads to a decreased total surplus. Our results indicate that rules unfairness could be beneficial in some cases. Finally, our derivation of the optimal decision rules allows a regulatory authority to put into effect a coordinated punishment strategies that can benefit one firm or both firms.
Journal: International Journal of Production Research
Pages: 783-794
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1398430
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398430
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:783-794




Template-Type: ReDIF-Article 1.0
Author-Name: Ronald G. Askin
Author-X-Name-First: Ronald G.
Author-X-Name-Last: Askin
Author-Name: Girish Jampani Hanumantha
Author-X-Name-First: Girish Jampani
Author-X-Name-Last: Hanumantha
Title: Queueing network models for analysis of nonstationary manufacturing systems
Abstract: 
 Queueing and queueing network models have been extensively employed for the performance analysis of manufacturing systems. They have enjoyed successful applications in rapid modelling for system design and performance evaluation of operational plans. In this paper, we briefly review literature on significant queuing network models developed and applied to the analysis of manufacturing systems. Previous work has focused almost exclusively on static environments of various types including open and closed networks for serial and general systems with various attributes such as unreliable machines, general arrival and service distributions, finite buffers and controlled work-in-process levels. As many systems experience dynamic demand and time-dependent resource availability, we propose a framework for the analysis of manufacturing systems under dynamic conditions. Numerical validation of this framework against simulation estimates is performed for realistic sized flowshop and jobshop instances.
Journal: International Journal of Production Research
Pages: 22-42
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1398432
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398432
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Template-Type: ReDIF-Article 1.0
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Title: Selection of a dynamic supply portfolio under delay and disruption risks
Abstract: 
 The problem of a multi-period supplier selection and order quantity allocation in the presence of supply chain disruption and delay risks is considered. Given a set of customer orders for finished products, the decision-maker needs to decide from which supplier and when to deliver product-specific parts required for each customer order to meet customer requested due date at a low cost or a high service level and to mitigate the impact of supply chain risks. For the selection of risk-neutral or risk-averse dynamic supply portfolio, a scenario-based stochastic mixed integer programming approach is developed. In the scenario analysis, the low probability and high impact supply disruptions are combined with the high probability and low impact supply delays. The risk-neutral portfolio is optimised by minimising expected cost or maximising expected service level. The risk-averse portfolio is optimised by calculating cost- or service-at-risk and minimising conditional cost-at risk or maximising conditional service at risk. The proposed dynamic portfolio approach leads to a time-indexed stochastic MIP formulation with a strong LP relaxation, which has proven to be computationally very efficient. The findings indicate that neglecting potential delay risks in supplier selection may lead to greater supply fluctuations and manufacturing delays.
Journal: International Journal of Production Research
Pages: 760-782
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1401238
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401238
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:760-782




Template-Type: ReDIF-Article 1.0
Author-Name: Agostino Villa
Author-X-Name-First: Agostino
Author-X-Name-Last: Villa
Author-Name: Teresa Taurino
Author-X-Name-First: Teresa
Author-X-Name-Last: Taurino
Title: From industrial districts to SME collaboration frames
Abstract: 
 Industrial networks have evolved from aggregations of a number of suppliers around a few final producers, towards more balanced organisations of small- and medium-sized enterprises (SMEs) that within the European industrial system, today compose by more than 95% of all small-mid enterprises in the non-financial sector. The crucial character of a SME aggregation into a cluster is the existence of an effective collaboration among SMEs possibly supported by clear interactions (e.g. production flows and information), by a commonly recognised management objective and by well assessed connections with external markets. Based on these conditions, the paper first discusses a general conceptual model of a SME cluster, making evidence of the above-mentioned three basic characters of the cluster itself. Then, the conceptual model is used to formalise a SME cluster and its organisation in terms of amid-term cluster management optimisation problem. The model can help a cluster management and control unit in evaluating the cluster performance and the positive effects of an effective collaboration among SMEs. Based on the formal general model, a survey of typical SME clusters in some European countries is presented in order to compare the different types of SME aggregations and of their collaborative frames.
Journal: International Journal of Production Research
Pages: 974-982
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1401244
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401244
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Template-Type: ReDIF-Article 1.0
Author-Name: Demetris Petrides
Author-X-Name-First: Demetris
Author-X-Name-Last: Petrides
Author-Name: Alexios Papacharalampopoulos
Author-X-Name-First: Alexios
Author-X-Name-Last: Papacharalampopoulos
Author-Name: Panagiotis Stavropoulos
Author-X-Name-First: Panagiotis
Author-X-Name-Last: Stavropoulos
Author-Name: George Chryssolouris
Author-X-Name-First: George
Author-X-Name-Last: Chryssolouris
Title:  Dematerialisation of products and manufacturing-generated knowledge content: relationship through paradigms
Abstract: 
 Dematerialisation refers to the decline, over time, of material usage in industrial products. The subject of this paper is to identify the relationship between the material and knowledge content of several products. The issue is whether the knowledge content, through time, will be affecting the products, in terms of dematerialisation. Specifically, a study has been conducted on widely used products in order to determine the way they have changed through their life-timeline. Two different indicators have been introduced for the quantification of the trend, in terms of material and knowledge content.
Journal: International Journal of Production Research
Pages: 86-96
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1401246
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401246
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:86-96




Template-Type: ReDIF-Article 1.0
Author-Name: Zhongshun Shi
Author-X-Name-First: Zhongshun
Author-X-Name-Last: Shi
Author-Name: Zewen Huang
Author-X-Name-First: Zewen
Author-X-Name-Last: Huang
Author-Name: Leyuan Shi
Author-X-Name-First: Leyuan
Author-X-Name-Last: Shi
Title: Customer order scheduling on batch processing machines with incompatible job families
Abstract: 
 This paper addresses the order scheduling problems under configurations of single batch machine and parallel batch machines. Each order consists of several kinds of jobs from different incompatible job families with specific quantities. The batch machine is able to handle a group of jobs simultaneously. Incompatible job families are considered. The objectives are to minimise the order makespan and total weighted order completion time. We prove that the problems with minimising order makespan can be solved in polynomial time for single batch machine and parallel batch machines. As for minimising the total weighted order completion time, efficient heuristic algorithms together with the worst-case analysis are proposed. Numerical results show that the proposed algorithms can achieve high-quality solutions.
Journal: International Journal of Production Research
Pages: 795-808
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1401247
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401247
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Template-Type: ReDIF-Article 1.0
Author-Name: Robert W. Grubbström
Author-X-Name-First: Robert W.
Author-X-Name-Last: Grubbström
Title: Risk preference evaluation – a fourth dimension of the application of the Laplace transform
Abstract: 
 In this paper, we apply the Laplace transform to risk preference theory (decision theory, decision analysis). We show that with a constant measure of absolute risk aversion, the certainty monetary equivalent (CME) can be developed into an expression involving the logarithm of the bilateral Laplace transform of the probability density of the outcome of risky projects. We also introduce a measure named internal risk aversion (IRA). This is in analogy with the earlier application of the transform to net present value problems. Properties of the CME function are examined. Basic examples of application are introduced followed by applications to portfolio theory and option pricing.
Journal: International Journal of Production Research
Pages: 344-373
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1401248
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401248
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:344-373




Template-Type: ReDIF-Article 1.0
Author-Name: Oliver Thomasson
Author-X-Name-First: Oliver
Author-X-Name-Last: Thomasson
Author-Name: Maria Battarra
Author-X-Name-First: Maria
Author-X-Name-Last: Battarra
Author-Name: Güneş Erdoğan
Author-X-Name-First: Güneş
Author-X-Name-Last: Erdoğan
Author-Name: Gilbert Laporte
Author-X-Name-First: Gilbert
Author-X-Name-Last: Laporte
Title: Scheduling twin robots in a palletising problem
Abstract: 
 This paper introduces the Twin Robot Palletising Problem (TRPP) in which two robots must be scheduled and routed to pick up and deliver products at specified locations along a rail. The robots are initially located at the opposite ends of the rail and must preserve a minimum safe distance from one another. The objective is to minimise the makespan, defined as the time required to complete all operations and for both robots to return to their starting positions. The paper presents a proof of NP-Hardness of the TRPP, as well as two mixed integer linear programming models. Local search operators are introduced, before an iterated local search and an iterated local search and a genetic algorithm are developed, in which a linear-time scheduling algorithm and dynamic programming are utilised to evaluate the quality of solutions. Extensive computational results demonstrate the limits of the mathematical models, the effectiveness of the metaheuristics, and the savings obtained using twin robots instead of a single one.
Journal: International Journal of Production Research
Pages: 518-542
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1401249
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401249
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:518-542




Template-Type: ReDIF-Article 1.0
Author-Name: Jan Olhager
Author-X-Name-First: Jan
Author-X-Name-Last: Olhager
Author-Name: Andreas Feldmann
Author-X-Name-First: Andreas
Author-X-Name-Last: Feldmann
Title: Distribution of manufacturing strategy decision-making in multi-plant networks
Abstract: 
 This paper is concerned with the manufacturing strategy decision-making structure in multi-plant networks, i.e. how strategic manufacturing decision-making authority is distributed between the network level (i.e. headquarters) and the plant level. We use survey data from 107 manufacturing plants. This research identifies three different structures: centralised at the network headquarter, decentralised to the plant and integrated between central headquarters and the plant. All decision areas follow the same pattern, i.e. full centralisation, full decentralisation or full integration. We do not find any support for that some decisions are centralised while others are decentralised. Product volume and process type are significantly associated with the choice of decision-making structure. In particular, high product volumes are associated with a centralised approach, and a low degree of process flow orientation (such as project manufacturing, job shop and flow shop) is associated with a decentralised approach. The integrated approach is associated with a combination of lower product volumes and higher degrees of flow orientation. Choosing the right decision-making structure for the product and process mix seems to lead to high levels of operational performance.
Journal: International Journal of Production Research
Pages: 692-708
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1401749
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401749
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Template-Type: ReDIF-Article 1.0
Author-Name: Ton G. de Kok
Author-X-Name-First: Ton G.
Author-X-Name-Last: de Kok
Title: Modelling short-term manufacturing flexibility by human intervention and its impact on performance
Abstract: 
 Short-term manufacturing flexibility is the capability to respond to unforeseen short-term and immediate events during operation. Explicitly modelling short-term manufacturing flexibility is extremely hard as it implies that it is possible to prescribe responses to all possible events in all possible states of the system under consideration. We propose an implicit modelling approach where we only model the frequency of responses to unforeseen events and the impact of the response on the evolution of the process under consideration. This allows us to dramatically reduce model complexity while preserving empirical validity of the model. We introduce the concepts of intervention–independent performance (IIP) and intervention–dependent performance (IDP). We present a methodology to gather IIP and IDP indicator information. We propose another process to use this information together with historical transactional data and forecasts to make tactical trade-offs that result in control policy parameters. We illustrate our modelling approach by a generic inventory control model with replanning of replenishment orders. We apply the model in a case study characterised by highly utilised production lines, high set-up times and dynamic demand. We provide empirical evidence of the validity of the proposed methodologies.
Journal: International Journal of Production Research
Pages: 447-458
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1401750
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401750
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Template-Type: ReDIF-Article 1.0
Author-Name: Mark S. Daskin
Author-X-Name-First: Mark S.
Author-X-Name-Last: Daskin
Author-Name: Emily L. Tucker
Author-X-Name-First: Emily L.
Author-X-Name-Last: Tucker
Title: The trade-off between the median and range of assigned demand in facility location models
Abstract: 
 In this paper, we present an extension of the classic p-median facility location model. The new formulation allows the user to trace the trade-off between the demand-weighted average distance (the traditional p-median objective) and the range in assigned demand. We extend the model to incorporate additional constraints that significantly reduce the computation time associated with the model. We also outline a genetic algorithm-based approach for solving the problem. The paper shows that significant reductions in the range in assigned demand are possible with relatively minor degradations in the average distance metric. The paper also shows that the genetic algorithm does very well at identifying the approximate trade-off curve. The model and algorithms were tested on real-life data-sets ranging in size from 33 nodes to 880 nodes.
Journal: International Journal of Production Research
Pages: 97-119
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1401751
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401751
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:97-119




Template-Type: ReDIF-Article 1.0
Author-Name: Xingxing Chen
Author-X-Name-First: Xingxing
Author-X-Name-Last: Chen
Author-Name: Panos Kouvelis
Author-X-Name-First: Panos
Author-X-Name-Last: Kouvelis
Author-Name: Maryam Biazaran
Author-X-Name-First: Maryam
Author-X-Name-Last: Biazaran
Title: Value of operational flexibility in co-production systems with yield and demand uncertainty
Abstract: 
 We study the production decisions of a firm that operates a co-production system (single input but multiple simultaneous outputs) with random yield and demand. The firm uses its outputs to meet multiple end-market demands with different quality requirements. Outputs serving a market segment may be a result of a blending process of different quality products of the co-production system. After the realisation of yield and before the realisation of demand, the firm has the option to upgrade the quality of outputs in order to better position itself to meet market demands. With the goal of maximising expected profits, we formulate a three stage stochastic programming problem, to investigate the value of intermediate upgrading flexibility. Using a stylised model of two products and two markets with different quality requirements, we characterise the optimal decisions and show that the quality upgrading policy is of a single-threshold type. Although upgrading is costly, it creates value for the firm through reducing total production cost and better managing the yield uncertainty. Positive correlation between demands of the end-markets decreases the value of upgrading. The more general model formulation offers the blueprint of a stochastic programming model that can be solved for realistic applications.
Journal: International Journal of Production Research
Pages: 491-507
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1402138
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1402138
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Template-Type: ReDIF-Article 1.0
Author-Name: Kelsey M. Taylor
Author-X-Name-First: Kelsey M.
Author-X-Name-Last: Taylor
Author-Name: Stephan Vachon
Author-X-Name-First: Stephan
Author-X-Name-Last: Vachon
Title: Empirical research on sustainable supply chains: IJPR’s contribution and research avenues
Abstract: 
 This paper reviews the empirical research pertaining to sustainable supply chain management (SSCM) published in the International Journal of Production Research (IJPR). The review allows an assessment of IJPR’s contribution to the empirical SSCM literature and its shortcomings. One of the key shortcomings was the relatively small number of papers that address the social dimension of SSCM. An avenue for potential and fruitful research is proposed building on the notion of network capital. Research questions that can lead to the application of network capital are presented to spark more research on the social dimension of SSCM for prospective contributors to IJPR.
Journal: International Journal of Production Research
Pages: 950-959
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1402139
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1402139
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:950-959




Template-Type: ReDIF-Article 1.0
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Mia Hasanagic
Author-X-Name-First: Mia
Author-X-Name-Last: Hasanagic
Title: A systematic review on drivers, barriers, and practices towards circular economy: a supply chain perspective
Abstract: 
 In the last few years, the circular economy has received considerable attention worldwide because it offers an opportunity to optimise and promote sustainable production and consumption through new models based on continuous growth and limitless resources. Although various advantages have been identified that emerge from the application of a circular economy, no concrete studies exist that investigate current state-of-the-art drivers, barriers and practices in this relevant field. An in-depth exploration of current practices would enhance the circular economy’s significance and would help understand its present level of implementation. With this concern, this study provides an analysis of the drivers, barriers and practices that influence the implementation of the circular economy in the context of supply chains through a systematic review. In order to analyse the circular economy’s level of implementation, we correlate stakeholders’ perspectives with drivers, barriers, and practices; thus, a multi-perspective framework is proposed. From the results, it is evident that among various stakeholders, the governmental perspective has the maximum positive impact on the implementation of the circular economy in supply chains. Specifically, the circular economy can be promoted through laws, policies, risk reduction (through tax levies) and strict governance.
Journal: International Journal of Production Research
Pages: 278-311
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1402141
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1402141
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Template-Type: ReDIF-Article 1.0
Author-Name: Yong Yin
Author-X-Name-First: Yong
Author-X-Name-Last: Yin
Author-Name: Kathryn E. Stecke
Author-X-Name-First: Kathryn E.
Author-X-Name-Last: Stecke
Author-Name: Dongni Li
Author-X-Name-First: Dongni
Author-X-Name-Last: Li
Title: The evolution of production systems from Industry 2.0 through Industry 4.0
Abstract: 
 This paper discusses production systems with a focus on the relationships between product supply and customer demand in the context of Industry 2.0–4.0. One driver of production evolution is changes in customer demand over time, which is categorised into several dimensions. Major production systems – flow line, Toyota production system (TPS), job shop, cell, flexible manufacturing system and seru – have been developed and applied to supplies to match different demand dimensions over time. For each production system, two questions are addressed: what and how. Comparisons between seru with TPS and cell are given. The possibilities of a future smart factory equipped with internet of things are discussed. The demand dimensions of Industry 4.0, the product architecture change in the automobile industry and the impact of 3D printing are elaborated. Potential applications of lean and seru principles for Industry 4.0 are presented.
Journal: International Journal of Production Research
Pages: 848-861
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1403664
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1403664
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Template-Type: ReDIF-Article 1.0
Author-Name: Reza Imani Asrai
Author-X-Name-First: Reza
Author-X-Name-Last: Imani Asrai
Author-Name: Stephen T. Newman
Author-X-Name-First: Stephen T.
Author-X-Name-Last: Newman
Author-Name: Aydin Nassehi
Author-X-Name-First: Aydin
Author-X-Name-Last: Nassehi
Title: A mechanistic model of energy consumption in milling
Abstract: 
 In this paper, a novel mechanistic model is proposed and validated for the consumption of energy in milling processes. The milling machine is considered as a thermodynamic system. Mechanisms of the significant energy conversion processes within the system are used to construct an explicit expression for the power consumption of the machine as a function of the cutting parameters. This model has been validated experimentally and is shown to be significantly more accurate than popular existing models. A simplified form of the model is also proposed that provides a balance between complexity and accuracy. The novelty of the model is that it maps the flow of energy within a machine tool, based solely on the active mechanisms of energy conversion. As a result, only limited assumptions are made in the model, resulting in an error of less than one per cent, verified by experiments. This accurate model can be used to substantially reduce energy consumption in milling processes at machine and factory levels leading to massive cost savings and reduction of environmental impact of numerous industries. The generality of the modelling method makes it applicable to other types of machine tools with minimal adjustments.
Journal: International Journal of Production Research
Pages: 642-659
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1404160
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1404160
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Template-Type: ReDIF-Article 1.0
Author-Name: David Simchi-Levi
Author-X-Name-First: David
Author-X-Name-Last: Simchi-Levi
Author-Name: Michelle Xiao Wu
Author-X-Name-First: Michelle Xiao
Author-X-Name-Last: Wu
Title: Powering retailers’ digitization through analytics and automation
Abstract: 
 Retailers face significant pressure to improve revenue, margins and market share by applying price optimisation models. These are mathematical models that calculate how demand varies at different price levels, then combine that data with information on costs and inventory levels to recommend prices that will improve revenue and profits. These models have been around for a while-so what is different now? We have identified three important changes: (1) Data: availability of internal and external real-time data such as traffic to a website, consumers making buy/no buy decisions and competitor pricing strategies; (2) Analytics: advances in machine learning and ease of access (R, Python) have enabled the development of systems that learn on the fly about consumer behaviour and preferences and generate effective estimates of demand-price relationships; and (3) Automation: increase in computing speed enables real-time optimisation of prices of hundreds of competing products sold by the same retailer. We take advantage of these new opportunities by showing how they were applied at Boston-based flash sales retailer Rue La La, online market maker Groupon, and the largest online retailer in Latin America, B2W Digital (B2W). While all these examples are of on-line businesses which have readily available data and can change prices dynamically, we have also implemented similar methods for brick-and-mortar retailed in applications such as promotional pricing, new product introduction, and assortment optimisation with similar business impacts. Thus, beyond applications to price optimisations, these new trends enable companies to revolutionise their business from procurement to supply chain all the way to revenue management.
Journal: International Journal of Production Research
Pages: 809-816
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1404161
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1404161
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:809-816




Template-Type: ReDIF-Article 1.0
Author-Name: N. Viswanadham
Author-X-Name-First: N.
Author-X-Name-Last: Viswanadham
Title: Performance analysis and design of competitive business models
Abstract: 
 In this paper, we define the business model of a company and its eight main components which are the customer value proposition, profit formula, partner network, the other four business model pillars include supply/service chain processes; key resources; delivery mechanisms and institutional and social constraints and finally the operational governance. The business model achieves the objective of making money by producing the products/services using the resources following the social and institutional constraints and delivering to various customer segments the products and services using all the sales opportunities including to the primary, secondary customers and cross-sales. We call this framework as the business model ecosystem. Then, we map the unified ecosystem for a unified company and illustrate using several examples. Our business model ecosystem is a generalised version of the business models published in the literature. We then present the GRIP (Governance, Risk, Innovation and Performance) framework. We present some of the example both established and new to illustrate our framework. We compare the traditional retail and e-retail in terms of their business models and discuss the issues involved in business model change. The takeaways from this paper are opportunities for both research and start-ups.
Journal: International Journal of Production Research
Pages: 983-999
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1406171
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1406171
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:983-999




Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Author-Name: Yerasani Sinjana
Author-X-Name-First: Yerasani
Author-X-Name-Last: Sinjana
Author-Name: Sri Krishna Kumar
Author-X-Name-First: Sri Krishna
Author-X-Name-Last: Kumar
Author-Name: Young-Jun Son
Author-X-Name-First: Young-Jun
Author-X-Name-Last: Son
Title: Optimising integrated inventory policy for perishable items in a multi-stage supply chain
Abstract: 
 The value of perishable products is most affected by the time delays in a supply chain. A major issue is how to integrate the existing practices in production, inventory holding and distribution, besides considering the perishable nature of the products, so as to deliver an optimised policy for the perishable commodities. Standard inventory control models are often not adequate for perishable products and there is a need for a new integrated model to focus on consolidation of production, inventory and distribution processes. We develop such a mathematical model to search for an optimal integrated inventory policy for perishable items in a multi-stage supply chain. We specifically assume the exponential deterioration rate so as to be consistent with the growth rate of the micro-organisms responsible for deterioration. We propose and analyse some general properties of the model and apply it to a three-stage supply chain. We show that this integrated model which includes inventory control and fleet selection can be optimised with an evolutionary technique like genetic algorithm. A novel genetic algorithm that avoids revisits and employs a parameter-less self-adaptive mutation operator is developed. The results are compared with those obtained with CPLEX for small-sized problems. We show that our model and optimisation approach gives near optimal results for varied demand scenarios.
Journal: International Journal of Production Research
Pages: 902-925
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1407500
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1407500
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Template-Type: ReDIF-Article 1.0
Author-Name: Giulia Pedrielli
Author-X-Name-First: Giulia
Author-X-Name-Last: Pedrielli
Author-Name: Andrea Matta
Author-X-Name-First: Andrea
Author-X-Name-Last: Matta
Author-Name: Arianna Alfieri
Author-X-Name-First: Arianna
Author-X-Name-Last: Alfieri
Author-Name: Mengyi Zhang
Author-X-Name-First: Mengyi
Author-X-Name-Last: Zhang
Title: Design and control of manufacturing systems: a discrete event optimisation methodology
Abstract: 
 Simulation optimisation has gained a great attention due to its success in the design of complex manufacturing systems. In this paper, we look at manufacturing as a special class of queueing systems and propose the Discrete Event Optimisation (DEO) methodology, which provides a formal way to develop integrated mathematical models for the simultaneous simulation and optimisation. In the case, the obtained model is a mixed integer linear programming model; the methodology provides a formal way to generate approximations of them. The analytical properties of DEO models are analysed for the first time in the framework of sample path optimisation and mathematical programming. The methodology represents a reference for the use of mathematical programming as a way to model simulation optimisation for queueing systems. The applicability of the DEO methodology to complex problems is showed using the task and buffer allocation problem in a production line.
Journal: International Journal of Production Research
Pages: 543-564
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1412532
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412532
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Template-Type: ReDIF-Article 1.0
Author-Name: X. Wang
Author-X-Name-First: X.
Author-X-Name-Last: Wang
Author-Name: S.K. Ong
Author-X-Name-First: S.K.
Author-X-Name-Last: Ong
Author-Name: A.Y.C. Nee
Author-X-Name-First: A.Y.C.
Author-X-Name-Last: Nee
Title: A comprehensive survey of ubiquitous manufacturing research
Abstract: 
 In the past 10 years, ubiquitous manufacturing (UM) has received a growing amount of attention among researchers in the manufacturing community because ubiquitous computing technologies (UCTs) can be applied to address a wide range of issues in the manufacturing industry, e.g. manufacturing processes and equipment, manufacturing management and planning. However, to the best of the authors’ knowledge, there is a lack of comprehensive and critical review from a holistic view of the state-of-the-art UM and its systems. This paper aims to provide a concise overview of the technical features, characteristics and broad range of applications of UM systems published between 1997 and 2017. Among these selected articles, more than 70% of them were published between 2012 and 2017, and they are considered as recent pertinent works which will be discussed in detail. The unique aspects of this paper lie in that this paper summarises and analyses a broad range of the state-of-the-art implementation of UM systems from a holistic and comprehensive view of manufacturing technology, including UM for manufacturing processes, manufacturing control systems, logistics, remanufacturing, cloud manufacturing, production scheduling, production quality control and evaluation, etc. In addition, the current limitation factors and future trends of UM development will also be discussed.
Journal: International Journal of Production Research
Pages: 604-628
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1413259
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1413259
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Template-Type: ReDIF-Article 1.0
Author-Name: Tullio A.M. Tolio
Author-X-Name-First: Tullio A.M.
Author-X-Name-Last: Tolio
Author-Name: Andrea Ratti
Author-X-Name-First: Andrea
Author-X-Name-Last: Ratti
Title: Performance evaluation of two-machine lines with generalized thresholds
Abstract: 
 An analytical model for evaluating the performance of two-machine continuous flow systems with finite buffer capacity, multiple up and down states and generalised thresholds is presented in this paper. The idea is that the machines can behave differently above or below certain buffer levels named thresholds. In addition, when the buffer level crosses one of the thresholds, certain changes of state of the machines can happen. With the method presented in the paper it is possible to consider all the different types of two machine lines which can be modelled with multiple up and down states, like for example cases with machines having phase-type failure and repair time distributions, serial/parallel machines and quality control machines. The proposed approach, allows to include system control by means of thresholds in the system model and provides a way to analyse the performance of a wide range of two-machine systems. Some of these cases are proposed in the numerical examples at the end of the paper. Moreover, the proposed two-machine line can be used as a building block for the analysis of larger systems, including systems with loops.
Journal: International Journal of Production Research
Pages: 926-949
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2017.1420922
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1420922
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Erratum
Journal: International Journal of Production Research
Pages: (v)-(v)
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2018.1428489
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1428489
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Leading scholars in Production Research for the 55th volume anniversary of IJPR
Journal: International Journal of Production Research
Pages: 1-9
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2018.1429119
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1429119
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Template-Type: ReDIF-Article 1.0
Author-Name: Philipp Melchiors
Author-X-Name-First: Philipp
Author-X-Name-Last: Melchiors
Author-Name: Roel Leus
Author-X-Name-First: Roel
Author-X-Name-Last: Leus
Author-Name: Stefan Creemers
Author-X-Name-First: Stefan
Author-X-Name-Last: Creemers
Author-Name: Rainer Kolisch
Author-X-Name-First: Rainer
Author-X-Name-Last: Kolisch
Title: Dynamic order acceptance and capacity planning in a stochastic multi-project environment with a bottleneck resource
Abstract: 
 We study the integration of order acceptance and capacity planning in multi-project environments with dynamically arriving projects. We model this planning problem as a continuous-time Markov decision process to determine long-term optimal decisions. We examine whether macro-process planning should be performed before or after order acceptance. We characterise the structure of optimal policies, and explore the dependence on a number of parameters such as project payoff, project cost and order arrival time. We also look into the effects of set-up costs and the use of non-regular capacity.
Journal: International Journal of Production Research
Pages: 459-475
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2018.1431417
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1431417
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:459-475




Template-Type: ReDIF-Article 1.0
Author-Name: Lin Lin
Author-X-Name-First: Lin
Author-X-Name-Last: Lin
Author-Name: Mitsuo Gen
Author-X-Name-First: Mitsuo
Author-X-Name-Last: Gen
Title: Hybrid evolutionary optimisation with learning for production scheduling: state-of-the-art survey on algorithms and applications
Abstract: 
 Evolutionary Algorithms (EAs) has attracted significantly attention with respect to complexity scheduling problems, which is referred to evolutionary scheduling. However, EAs differ in the implementation details and the nature of the particular scheduling problem applied. In order to have an effective implementation of EAs for production scheduling, this paper focuses on making a survey of researches based on using hybrid EAs. Starting from scheduling description, we identify the classification and graph representation of scheduling problems. Then, we present the various representations, hybridisation techniques and machine-learning techniques to enhancing EAs. Finally, we also present successful applications in manufacturing.
Journal: International Journal of Production Research
Pages: 193-223
Issue: 1-2
Volume: 56
Year: 2018
Month: 1
X-DOI: 10.1080/00207543.2018.1437288
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1437288
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Template-Type: ReDIF-Article 1.0
Author-Name: Biao Yu
Author-X-Name-First: Biao
Author-X-Name-Last: Yu
Author-Name: Han Zhao
Author-X-Name-First: Han
Author-X-Name-Last: Zhao
Author-Name: Deyi Xue
Author-X-Name-First: Deyi
Author-X-Name-Last: Xue
Title: A multi-population co-evolutionary genetic programming approach for optimal mass customisation production
Abstract: 
 Development of mass customised products demands various activities in the product development process, such as design, manufacturing process planning, manufacturing resource planning and maintenance process planning, to be considered and coordinated. In this research, a multi-population co-evolutionary genetic programming (MCGP) approach is introduced to identify the optimal design and its downstream product life cycle activities for developing mass customised product considering these different product life cycle activities and their relationships. In this research, two types of relationships between downstream product life cycle activities are considered: sequential relationships and concurrent relationships. The product design and its downstream life cycle descriptions are modelled by a multi-level graph data structure. These product life cycle descriptions are defined at two different levels: generic level for modelling the descriptions in a product family and specific level for modelling the descriptions of a customised product. The optimal design and its downstream life cycle activities are identified through the MCGP approach based on evaluations in different product life cycle aspects. Various methods have been developed to improve computation efficiency for the MCGP. Industrial case studies and comparative case studies have been implemented to demonstrate the effectiveness of the developed approach.
Journal: International Journal of Production Research
Pages: 621-641
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1194538
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1194538
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Template-Type: ReDIF-Article 1.0
Author-Name: Vittorio D’Aleo
Author-X-Name-First: Vittorio
Author-X-Name-Last: D’Aleo
Author-Name: Bruno Sergio Sergi
Author-X-Name-First: Bruno Sergio
Author-X-Name-Last: Sergi
Title: Human factor: the competitive advantage driver of the EU’s logistics sector
Abstract: 
 This article aims to test the weight that main sub-components of the global competitiveness index might have on the logistics performance index. We deploy a novel technique based on three newly particularised clusters (‘infrastructure’, ‘institutions’ and ‘human factor’) to look into whether such clusters are related to efficiency in the 28 European Union’s countries. It is manifest that the human factor is far more important for improving the logistics performance index than infrastructure and institutions. It follows that in this new domain of analysis, all initiatives to prioritise investment on the human factor are appropriate means of stimulating innovation and economic outlook, perceived that the logistics sector accounts for an average of 10% of the European Union’s GDP.
Journal: International Journal of Production Research
Pages: 642-655
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1194540
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1194540
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:3:p:642-655




Template-Type: ReDIF-Article 1.0
Author-Name: Alexander Seitz
Author-X-Name-First: Alexander
Author-X-Name-Last: Seitz
Author-Name: Martin Grunow
Author-X-Name-First: Martin
Author-X-Name-Last: Grunow
Title: Increasing accuracy and robustness of order promises
Abstract: 
 Accurate order promising is a key requirement for customer satisfaction. Nevertheless, practitioners struggle with the reliability of the delivery dates they promise to customers. Consequently, the costs of demand fulfilment soar due to intensified communication, emergency processes in logistics and acquisition of costly external production resources. We identify and formalise product and process flexibilities in supply chains that can be exploited in production planning. Product flexibility is the possibility to produce several kinds of products from one predecessor product. Process flexibility is the possibility to use one production process to manufacture several products. In order to increase the accuracy and robustness of delivery dates, we develop an order promising methodology able to deal with demand mix uncertainty and heterogeneous customer order lead times. The approach anticipates changes in production plans made possible by product and process flexibilities. In a numerical study based on a case from the semiconductor industry, we demonstrate that our method increases the accuracy and robustness of order promises. For the studied case, we find that the consideration of process flexibility is more important for the generation of accurate and robust order promises than the consideration of product flexibility.
Journal: International Journal of Production Research
Pages: 656-670
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1195024
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1195024
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Template-Type: ReDIF-Article 1.0
Author-Name: Junguang Zhang
Author-X-Name-First: Junguang
Author-X-Name-Last: Zhang
Author-Name: Xiwei Song
Author-X-Name-First: Xiwei
Author-X-Name-Last: Song
Author-Name: Estrella Díaz
Author-X-Name-First: Estrella
Author-X-Name-Last: Díaz
Title: Critical chain project buffer sizing based on resource constraints
Abstract: 
 Project scheduling is a complex process involving many types of resources and activities that require optimisation. The resource-constrained project scheduling problem is one of the well-known problematic issues when project activities have to be scheduled to minimise the project duration. Consequently, several methods have been proposed for adjusting the buffer size but none of these traditional methods consider buffer sizing accuracy based on resource constraints. The purpose of this paper is to develop a buffer sizing method based on a fuzzy resource-constrained project scheduling problem in order to obtain an appropriate proportionality between the activity duration and the buffer size. Specifically, a comprehensive resource-constrained method that considers both the general average resource constraints (GARC) and the highest peak of resource constraints (HPRC) is proposed in order to obtain a new buffer sizing method. This paper contributes to the research by considering several different aspects. First, this paper adopts a fuzzy method to calculate and obtain the threshold amount. Second, this paper discusses the resource levelling problem and proposes the HPRC method. Third, the proposed method uses a fuzzy quantitative model to calculate the resource requirement. The findings indicate that the project achieved higher efficiency, providing effective protection and an appropriate buffer size.
Journal: International Journal of Production Research
Pages: 671-683
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1200151
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1200151
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Template-Type: ReDIF-Article 1.0
Author-Name: Doina Pisla
Author-X-Name-First: Doina
Author-X-Name-Last: Pisla
Author-Name: Bogdan Galdau
Author-X-Name-First: Bogdan
Author-X-Name-Last: Galdau
Author-Name: Florin Covaciu
Author-X-Name-First: Florin
Author-X-Name-Last: Covaciu
Author-Name: Calin Vaida
Author-X-Name-First: Calin
Author-X-Name-Last: Vaida
Author-Name: Daniela Popescu
Author-X-Name-First: Daniela
Author-X-Name-Last: Popescu
Author-Name: Nicolae Plitea
Author-X-Name-First: Nicolae
Author-X-Name-Last: Plitea
Title: Safety issues in the development of the experimental model for an innovative medical parallel robot used in brachytherapy
Abstract: 
 The paper presents a medical parallel robot (BR-1), designed for the minimally invasive, targeted, treatment of cancer through brachytherapy. The analysis of Jacobi matrices allows a complete study of the singularities while generating also a set of conditions which, implemented in the control system, enable the safe behaviour of the robot. Brachytherapy is an advanced form of cancer treatment involving the placement of small radioactive seeds directly inside the malignant tumour, allowing a very effective, local treatment of cancer. For this task an innovative parallel robotic system has been developed, having five degrees of freedom, constructed in two versions, BR-1R and BR-1T with a slight variation at the level of a passive joint. The two solutions revealed different accuracy distributions and by selecting the proper variant based on the tumour location, an increased universality degree for the BR-1 robot is obtained. The singularity-free workspace is determined using the assessment of singularities for both robot versions. The control system for both robot versions is simple, robust and intuitive allowing clinicians to have an accurate procedure, having real-time force monitoring during the needle insertion. The experimental data demonstrate that the robotic structure is a worthy candidate for robotic-assisted brachytherapy.
Journal: International Journal of Production Research
Pages: 684-699
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1200153
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1200153
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Template-Type: ReDIF-Article 1.0
Author-Name: Fatma Pakdil
Author-X-Name-First: Fatma
Author-X-Name-Last: Pakdil
Author-Name: Karen Moustafa Leonard
Author-X-Name-First: Karen Moustafa
Author-X-Name-Last: Leonard
Title: Implementing and sustaining lean processes: the dilemma of societal culture effects
Abstract: 
 Lean processes allow the elimination of waste and the resulting improvements in productivity. However, implementing and sustaining lean processes are easier in some organisations than in others. There may be societal culture differences, as the successes in initial implementation in Japan have not been followed by global success. As organisations accelerate their lean efforts to gain or maintain competitive advantage, studying societal cultural effects seems timely. Understanding of the societal culture that the firm or subsidiary is operating in would be useful in determining how lean processes should lead the effort. Using the cultural dimensions developed by Hofstede, we examine the interconnection of societal culture and lean processes. For example, a societal emphasis on individualism is positively associated with a high level of lean process adoption, in terms of individual employee involvement, individual creativity and firm efficiency. A societal emphasis on high uncertainty avoidance is positively associated with a high level of lean process adoption, in terms of control and standardisation, efficiency and long-term philosophy. A societal emphasis on high power distance is positively associated with a high level of lean process adoption, in terms of control and standardisation, and efficiency. A long-term orientation in the society will be positively associated with a high level of lean process adoption, in terms of all of the dimensions. A societal emphasis on femininity will be positively associated with a high level of lean process adoption, in terms of employee involvement, creativity and long-term philosophy.
Journal: International Journal of Production Research
Pages: 700-717
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1200761
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1200761
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenyu Zhang
Author-X-Name-First: Wenyu
Author-X-Name-Last: Zhang
Author-Name: Shuai Zhang
Author-X-Name-First: Shuai
Author-X-Name-Last: Zhang
Author-Name: Shanshan Guo
Author-X-Name-First: Shanshan
Author-X-Name-Last: Guo
Author-Name: Yushu Yang
Author-X-Name-First: Yushu
Author-X-Name-Last: Yang
Author-Name: Yong Chen
Author-X-Name-First: Yong
Author-X-Name-Last: Chen
Title: Concurrent optimal allocation of distributed manufacturing resources using extended Teaching-Learning-Based Optimization
Abstract: 
 The optimal allocation of distributed manufacturing resources is a challenging task for supply chain deployment in the current competitive and dynamic manufacturing environments, and is characterised by multiple objectives including time, cost, quality and risk that require simultaneous considerations. This paper presents an improved variant of the Teaching-Learning-Based Optimisation (TLBO) algorithm to concurrently evaluate, select and sequence the candidate distributed manufacturing resources allocated to subtasks comprising the supply chain, while dealing with the trade-offs among multiple objectives. Several algorithm-specific improvements are suggested to extend the standard form of TLBO algorithm, which is only well suited for the one-dimensional continuous numerical optimisation problem well, to solve the two-dimensional (i.e. both resource selection and resource sequencing) discrete combinatorial optimisation problem for concurrent allocation of distributed manufacturing resources through a focused trade-off within the constrained set of Pareto optimal solutions. The experimental simulation results showed that the proposed approach can obtain a better manufacturing resource allocation plan than the current standard meta-heuristic algorithms such as Genetic Algorithm, Particle Swarm Optimisation and Harmony Search. Moreover, a near optimal resource allocation plan can be obtained with linear algorithmic complexity as the problem scale increases greatly.
Journal: International Journal of Production Research
Pages: 718-735
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1203078
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1203078
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Template-Type: ReDIF-Article 1.0
Author-Name: Dong Ding
Author-X-Name-First: Dong
Author-X-Name-Last: Ding
Author-Name: Fugee Tsung
Author-X-Name-First: Fugee
Author-X-Name-Last: Tsung
Author-Name: Jian Li
Author-X-Name-First: Jian
Author-X-Name-Last: Li
Title: Ordinal profile monitoring with random explanatory variables
Abstract: 
 Profiles characterise the functional relationship between the response variable and one or more explanatory variables and have been playing an important role in many applications. Profile monitoring mainly aims at checking the stability of this relationship. In many situations, we observe that the response variable is categorical with three or more attribute levels, and that there is natural order among the levels. Moreover, the explanatory variables are also random rather than fixed at some predefined values. To fully exploit the ordinal information, it is assumed that there is an unknown latent continuous distribution determining the levels of the ordinal response. Based on this, we propose a novel control chart for jointly monitoring the functional relationship, location shifts in the latent continuous distribution, and the random explanatory variables. Simulation results show that our proposed chart is efficient in detecting abnormalities and is robust to various latent distributions.
Journal: International Journal of Production Research
Pages: 736-749
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1204476
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1204476
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Template-Type: ReDIF-Article 1.0
Author-Name: Runkang Ding
Author-X-Name-First: Runkang
Author-X-Name-Last: Ding
Author-Name: Fan Jiang
Author-X-Name-First: Fan
Author-X-Name-Last: Jiang
Author-Name: Jingui Xie
Author-X-Name-First: Jingui
Author-X-Name-Last: Xie
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Title: Algorithmic prediction of individual diseases
Abstract: 
 The enormous and increasing cost of health care is burdensome for most low- to middle-income families, especially those families whose members are battling chronic diseases. If effective interventions can be conducted at earlier stages, many costs are avoidable. Correspondingly, predicting the future disease one patient may develop with accuracy is a crucial step towards solving this problem. We have developed a system called CAC, which integrates Clustering, Association analysis and Collaborative filtering to predict patients’ future conditions. The data-set used in this study is health insurance data collected from a provincial capital city of China. Specifically, the data-set includes 151,237 insured patients who have reimbursement records between 2007 and 2014. The patients are artificially classified into acute patients and chronic patients. For both sets of patients, we utilise a training set to generate the prediction rules and a testing set to test the prediction results. The results show that for 71% of acute patients and 82% of chronic patients, their future conditions are predictable.
Journal: International Journal of Production Research
Pages: 750-768
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1208372
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1208372
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Template-Type: ReDIF-Article 1.0
Author-Name: Maurizio Bevilacqua
Author-X-Name-First: Maurizio
Author-X-Name-Last: Bevilacqua
Author-Name: Filippo Emanuele Ciarapica
Author-X-Name-First: Filippo Emanuele
Author-X-Name-Last: Ciarapica
Author-Name: Ilaria De Sanctis
Author-X-Name-First: Ilaria
Author-X-Name-Last: De Sanctis
Title: Lean practices implementation and their relationships with operational responsiveness and company performance: an Italian study
Abstract: 
 Although many firms report large benefits from lean implementation, a lot of scepticism still remains regarding attainable results and the possibility to apply Lean approach outside high-volume manufacturing and stable context. In this work, combining field interviews with literature review, theoretical connections have been developed among Lean manufacturing techniques, operational responsiveness and company growth performances. A conceptual model has been proposed for investigating the network of influences among lean practices (supplier management, human resource management, just-in-time and total quality management practices), operational responsiveness (Product mix variety, Product innovation and Time effectiveness) and company growth performances in Italian companies. Using structural equation modelling, a second-order confirmatory factor analysis has been used to test the hypothesised relationships in the structural models. This study highlights that the operational responsiveness is only partially connected to a Lean strategy of a company. Indeed, the lean practices implementations are negatively influenced by product mix variety and innovation, while positively influenced by time effectiveness variables. Moreover, product mix variety and time effectiveness are the main characteristics of the operational responsiveness that positively influences company growth performances. So time effectiveness could be considered as a mediator between Lean best practices and firm growth. Moreover, no direct relationship has been found between lean bundles and firm’s performances. Lack of resources and mainly poor communication and managers’ commitment and support seem to be the main obstacles of lean implementation and success.
Journal: International Journal of Production Research
Pages: 769-794
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1211346
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1211346
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Template-Type: ReDIF-Article 1.0
Author-Name: Yvan Beauregard
Author-X-Name-First: Yvan
Author-X-Name-Last: Beauregard
Author-Name: Vladimir Polotski
Author-X-Name-First: Vladimir
Author-X-Name-Last: Polotski
Author-Name: Nadia Bhuiyan
Author-X-Name-First: Nadia
Author-X-Name-Last: Bhuiyan
Author-Name: Vincent Thomson
Author-X-Name-First: Vincent
Author-X-Name-Last: Thomson
Title: Optimal utilisation level for lean product development in a multitasking context
Abstract: 
 Flow of information is of utmost importance during product development (PD) endeavours with timely feedback supporting the resolution of higher risk elements. PD task size, multitasking and resource utilisation levels of the PD system influence information flow and the value ultimately realised from the investment in PD. In this paper, a model incorporating a methodology developed using queuing theory, and in particular, results obtained for Jackson networks are extended to help engineering management to improve PD task flow and consequently become more ‘lean’. Considered factors include: optimal PD task size and multitasking (focus) level as well as the utilisation level of PD resources. Empirical data were collected from a case study company and compared to optimal values. The benefits of the proposed model and approaches are discussed.
Journal: International Journal of Production Research
Pages: 795-818
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1213448
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213448
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Template-Type: ReDIF-Article 1.0
Author-Name: Thomas D. Hedberg
Author-X-Name-First: Thomas D.
Author-X-Name-Last: Hedberg
Author-Name: Nathan W. Hartman
Author-X-Name-First: Nathan W.
Author-X-Name-Last: Hartman
Author-Name: Phil Rosche
Author-X-Name-First: Phil
Author-X-Name-Last: Rosche
Author-Name: Kevin Fischer
Author-X-Name-First: Kevin
Author-X-Name-Last: Fischer
Title: Identified research directions for using manufacturing knowledge earlier in the product life cycle
Abstract: 
 Design for manufacturing (DFM), especially the use of manufacturing knowledge to support design decisions, has received attention in the academic domain. However, industry practice has not been studied enough to provide solutions that are mature for industry. The current state of the art for DFM is often rule-based functionality within computer-aided design (CAD) systems that enforce specific design requirements. That rule-based functionality may or may not dynamically affect geometry definition. And, if rule-based functionality exists in the CAD system, it is typically a customisation on a case-by-case basis. Manufacturing knowledge is a phrase with vast meanings, which may include knowledge on the effects of material properties decisions, machine and process capabilities or understanding the unintended consequences of design decisions on manufacturing. One of the DFM questions to answer is: How can manufacturing knowledge, depending on its definition, be used earlier in the product life cycle to enable a more collaborative development environment? This paper will discuss the results of a workshop on manufacturing knowledge that highlights several research questions needing more study. This paper proposes recommendations for investigating the relationship of manufacturing knowledge with shape, behaviour and context characteristics of a product to produce a better understanding of what knowledge is most important. In addition, the proposal includes recommendations for investigating the system-level barriers to reusing manufacturing knowledge and how model-based manufacturing may ease the burden of knowledge sharing. Lastly, the proposal addresses the direction of future research for holistic solutions of using manufacturing knowledge earlier in the product life cycle.
Journal: International Journal of Production Research
Pages: 819-827
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1213453
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213453
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Template-Type: ReDIF-Article 1.0
Author-Name: Nong Ye
Author-X-Name-First: Nong
Author-X-Name-Last: Ye
Title: A reverse engineering algorithm for mining a causal system model from system data
Abstract: 
 Although having structural system models which determine system behaviours is critical to plan, control and manage many complex systems (e.g. manufacturing and production systems), we often do not have pre-defined structural system models. We need to perform reverse engineering which is to collect and mine observable system data in order to discover structural system models. This paper presents a reverse engineering algorithm that can be used to discover a causal system model which is one kind of structural system model and represents causal relations of system factors. In a causal relation, the presence of one system factor causes the presence of another system factor. The paper also shows the computational complexity of the algorithm. The paper presents the application and performance of the reverse engineering algorithms to data in two application fields.
Journal: International Journal of Production Research
Pages: 828-844
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1213913
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213913
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Template-Type: ReDIF-Article 1.0
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Author-Name: Per Medbo
Author-X-Name-First: Per
Author-X-Name-Last: Medbo
Title: Simulating operator learning during production ramp-up in parallel vs. serial flow production
Abstract: 
 The aim of this research is to demonstrate how human learning models can be integrated into discrete event simulation to examine ramp-up time differences between serial and parallel flow production strategies. The experimental model examined three levels of learning rate and minimum cycle times. Results show that while the parallel flow system had longer ramp-up times than serial flow systems, they also had higher maximum throughput capacity. As a result, the parallel flow system frequently outperformed lines within the first weeks of operation. There is a critical lack of empirical evidence or methods that would allow designers to accurately determine what the critical learning paramters might be in their specific operations, and further research is needed to create predictive tools in this important area.
Journal: International Journal of Production Research
Pages: 845-857
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1217362
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1217362
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Template-Type: ReDIF-Article 1.0
Author-Name: Erik Lindskog
Author-X-Name-First: Erik
Author-X-Name-Last: Lindskog
Author-Name: Johan Vallhagen
Author-X-Name-First: Johan
Author-X-Name-Last: Vallhagen
Author-Name: Björn Johansson
Author-X-Name-First: Björn
Author-X-Name-Last: Johansson
Title: Production system redesign using realistic visualisation
Abstract: 
 The process of redesigning production systems is usually complex, for which virtual design tools are available. These tools are used to analyse and evaluate planned changes prior to implementation, making it possible to identify and prevent costly design mistakes. Despite this, design mistakes arise during and after the implementation. A source for design mistakes is incorrect or insufficient spatial data of the production systems used in the virtual design tools. The aim of this paper is to show how to reduce the time required for planning and implementing the redesign by supporting the process with realistic visualisation, created from accurate spatial data of the real production systems. Three industrial studies were carried out to evaluate how address realistic visualisation in order to support the redesign process. The result shows terrestrial 3D laser scanning to be suitable for capturing spatial data for realistic visualisation of production systems. The realistic visualisation can be used to virtually analyse design alternatives of the production systems, by, for example, combining the 3D laser scan data with 3D CAD models. The realistic visualisation enabling effective and accurate planning, which gives the opportunity to reduce the time required for planning and implementing redesigned production systems.
Journal: International Journal of Production Research
Pages: 858-869
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1218085
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1218085
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Template-Type: ReDIF-Article 1.0
Author-Name: David S. Cochran
Author-X-Name-First: David S.
Author-X-Name-Last: Cochran
Author-Name: Joseph T. Foley
Author-X-Name-First: Joseph T.
Author-X-Name-Last: Foley
Author-Name: Zhuming Bi
Author-X-Name-First: Zhuming
Author-X-Name-Last: Bi
Title: Use of the manufacturing system design decomposition for comparative analysis and effective design of production systems
Abstract: 
 The focus of this paper is on the use of the Manufacturing System Design Decomposition (MSDD) to make effective cost and production system design decisions. A comparative study is conducted to illustrate how and why the total cost is reduced when the functional requirements defined by the MSDD are achieved. The ultimate goal of this research was to advance manufacturing and production system development to being guided by engineering science and design rather than the common practice of duplicating another person’s or entity’s notion of the best physical implementation.
Journal: International Journal of Production Research
Pages: 870-890
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1218088
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1218088
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Template-Type: ReDIF-Article 1.0
Author-Name: Robert Lewis Wood
Author-X-Name-First: Robert Lewis
Author-X-Name-Last: Wood
Title: A dynamic curation method for manufacturing-related knowledge
Abstract: 
 A method for the dynamic curation of manufacturing-related knowledge is proposed, based on the impact of successive paradigm introduction on the network structure within manufacturing companies. This draws together manufacturing system structure in terms of interacting component network types, the nature and consequences of knowledge silos and the underpinning dichotomous influence of language. The need and opportunities for an objective- rather than subjective paradigm-based view of manufacturing are identified, leading to a curation process in which paradigms and other knowledge specialisms are different viewpoints based on particular models of manufacturing processes and resources. The consequences of this are explored in terms of knowledge silo reduction, improved communication within component social- and information networks, increased operational resilience and better informed decision-making for future business.
Journal: International Journal of Production Research
Pages: 891-903
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1222089
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1222089
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenbo Cai
Author-X-Name-First: Wenbo
Author-X-Name-Last: Cai
Author-Name: Ying-Ju Chen
Author-X-Name-First: Ying-Ju
Author-X-Name-Last: Chen
Title: Channel management and product design with consumers’ probabilistic choices
Abstract: 
 In this paper, we study how a seller should design the prices and qualities of products or services offered in both a direct channel and an indirect channel when facing consumers with probabilistic purchasing behaviour. We first consider three schemes under personalised offering: independent pricing, revenue sharing and profit sharing. We show that, in the independent pricing scheme, the seller can achieve the same profit using both channels as using only the direct channel. In the revenue sharing scheme, however, the seller’s channel strategy depends on consumers’ sensitivities on the cross-channel differences in both price and quality. Finally, the quality inefficiency in the second scheme can be eliminated in a profit sharing scheme. We then study the scenario in which consumers are heterogeneous with privately observed sensitivities, and show that it is always optimal to offer a single price-quality plan when both sensitive and insensitive consumers co-exist.
Journal: International Journal of Production Research
Pages: 904-923
Issue: 3
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1223377
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1223377
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaofei Qian
Author-X-Name-First: Xiaofei
Author-X-Name-Last: Qian
Author-Name: Xinbao Liu
Author-X-Name-First: Xinbao
Author-X-Name-Last: Liu
Author-Name: Jun Pei
Author-X-Name-First: Jun
Author-X-Name-Last: Pei
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Title: A new game of information sharing and security investment between two allied firms
Abstract: 
 In consideration of business information sharing, this paper investigates a new game of information sharing and security investment between two allied firms. Firms’ strategies in three decision models (Nash Equilibrium decision, partially centralised decision and totally centralised decision) are analysed. We provide some quantitative analyses on how some parameters affect firms’ decisions in the three decision models. Our Nash Equilibrium analysis shows that when firms make decisions individually, they will share no information with each other. When information sharing is determined by a social planner, firms will share some information with each other, which increases the risk of information leakage. Thus, firms should increase their security investments to mitigate the higher information leakage risk. However, our analysis shows that instead of investing more in information security, firms will reduce their security investment, which will further aggravate the risk. Hence, a social planner is required to designate the security investments and information sharing levels for both firms. Our theoretical analysis shows that firms’ strategies can achieve global optimality in the totally centralised decision model. Furthermore, a numerical experiment is conducted and the result demonstrates that totally centralised decision model is more efficient than the other two decision models. At last, we propose two compensation mechanisms to help firms coordinate their strategies when making decisions individually.
Journal: International Journal of Production Research
Pages: 4069-4086
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2017.1400704
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1400704
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhe Yin
Author-X-Name-First: Zhe
Author-X-Name-Last: Yin
Author-Name: Chen Wang
Author-X-Name-First: Chen
Author-X-Name-Last: Wang
Title: Strategic cooperation with a backup supplier for the mitigation of supply disruptions
Abstract: 
 We study optimal sourcing decisions for a firm with a dedicated supplier and a backup supplier. The dedicated supplier charges a lower wholesale price but faces a potential disruption risk. The backup supplier is assumed to be perfectly reliable but charges a higher wholesale price. The primary question we address is how the firm should cooperate with the backup supplier to hedge against the disruption risk. We consider three common cooperation options: advance purchase, reservation and contingency purchase. Our basic results show that the firm should choose advance purchase strategy if the disruption probability is high, while contingency purchase strategy benefits the firm more if the disruption probability is low. Under an intermediate disruption probability, the firm should choose reservation strategy only if the reservation fee is sufficiently low. Then, we explore the optimal backup strategy under partial disruption risk. The results show that the advance purchase and the reservation strategy should be adopted more widely when the dedicated supplier guarantees a relatively high yield rate after disruption.
Journal: International Journal of Production Research
Pages: 4300-4312
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2017.1410246
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1410246
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Template-Type: ReDIF-Article 1.0
Author-Name: Stephen Mahar
Author-X-Name-First: Stephen
Author-X-Name-Last: Mahar
Author-Name: Peter A. Salzarulo
Author-X-Name-First: Peter A.
Author-X-Name-Last: Salzarulo
Author-Name: P. Daniel Wright
Author-X-Name-First: P. Daniel
Author-X-Name-Last: Wright
Title: Simultaneous use of customer, product and inventory information in dynamic product promotion
Abstract: 
 Currently, retail data are both accessible and plentiful while the retail space has become increasingly competitive. When combined with technology like mobile computing and low cost analytic techniques, data can now be leveraged by companies to dynamically offer individualised promotions in real time. This paper considers the relative value of three retail information elements which can be used by retailers to dynamically identify a subset of product offerings to promote to their customers. The retail information elements considered are: (a) product markup, (b) customer preference estimates gleaned from purchase history and (c) retailer inventory positions. The importance of each element is evaluated singularly and in combination as is their effect on promotion success, inventory costs and average markup. Computational results show that, on average, dynamic promotion policies incorporating all retail information elements can increase expected profit by 14.5% over policies that consider only customer preference and by 8.4–9.1% over policies that consider only product margin or inventory. Results demonstrate that customer preference information alone does little to improve performance but provides substantial synergistic benefits when combined with either inventory or markup information elements. The most information intensive dynamic promotion policy is then extended to include price as a decision variable.
Journal: International Journal of Production Research
Pages: 4283-4299
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2017.1412529
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412529
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Template-Type: ReDIF-Article 1.0
Author-Name: Cong Cheng
Author-X-Name-First: Cong
Author-X-Name-Last: Cheng
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Title: Robust policies for a multi-stage production/inventory problem with switching costs and uncertain demand
Abstract: 
 In this paper, we seek robust policies for a multi-stage production/inventory problem to minimise total costs, including switching, production, inventory or shortage costs. While minimising switching costs often leads to non-convexity in the model, 0–1 variables are introduced to linearise the objective function. Considering the impossibility of obtaining the exact distribution of uncertain demand, we study the production/inventory problem under worst cases to resist uncertainty. In contrast to traditional inventory problems, unexpected yields in production are considered. Robust support vector regression is developed to approximate the yields of each unit. A mixed-integer linear programming is proposed, employing the duality theory to address the min–max model. A practical case study from cold rolling is considered. Experiments on the actual steel production data are reported to illustrate the validity of the proposed approach.
Journal: International Journal of Production Research
Pages: 4264-4282
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2017.1413257
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1413257
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Template-Type: ReDIF-Article 1.0
Author-Name: John R. Macdonald
Author-X-Name-First: John R.
Author-X-Name-Last: Macdonald
Author-Name: Christopher W. Zobel
Author-X-Name-First: Christopher W.
Author-X-Name-Last: Zobel
Author-Name: Steven A. Melnyk
Author-X-Name-First: Steven A.
Author-X-Name-Last: Melnyk
Author-Name: Stanley E. Griffis
Author-X-Name-First: Stanley E.
Author-X-Name-Last: Griffis
Title: Supply chain risk and resilience: theory building through structured experiments and simulation
Abstract: 
 The research literature of supply chain risk and resilience is at a critical developmental stage. Studies have established the importance of these topics both to researchers and practitioners. They also have identified factors contributing to risk, the impact of risk and disruptions on performance, and the strategies and tactics used to build the capacity for supply chain resilience. Although these efforts can provide support for constructing a theory of risk and resilience, researchers are currently restricted in their ability to build such a theory by the difficulty of collecting the necessary data. This paper contributes to this literature development effort by summarising prior research reviews and developing a three-component framework aimed at helping researchers to build better theories. This is accomplished through combining structured experimental design with discrete-event simulations of supply chains. The result is a methodology that allows researchers to develop better understanding of the factors that link a disruption to its impact on supply chain performance through both direct and interaction effects. Following the methodology development, the paper concludes with an example using the factors of shock interarrival time, supply chain connectivity and buffer stocks to illustrate the potential for contributing to the theory-building process.
Journal: International Journal of Production Research
Pages: 4337-4355
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2017.1421787
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421787
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Template-Type: ReDIF-Article 1.0
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Author-Name: Shih-Wen Liu
Author-X-Name-First: Shih-Wen
Author-X-Name-Last: Liu
Title: A new lot sentencing approach by variables inspection based on process yield
Abstract: 
 This study applies the concept of repetitive group sampling (RGS) to develop a new variables sampling plan for lot sentencing on the basis of process fraction nonconforming. The product acceptance determination problem is formulated as a nonlinear optimization problem where the objective function is to minimise the average sample number required for inspection, and the constraints are set by satisfying the acceptable quality level, limiting quality level, producer’s risk and consumer’s risk in the contract. The proposed lot sentencing approach’s behaviour is examined and discussed. The results indicate that the performance of the proposed variables RGS plan is better than that of a conventional variables single sampling plan in terms of the required sample size for inspection. Thus, the proposed approach can help the practitioner efficiently make a decision to determine whether the submitted lots should be accepted.
Journal: International Journal of Production Research
Pages: 4087-4099
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1424365
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424365
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Template-Type: ReDIF-Article 1.0
Author-Name: Biao Xu
Author-X-Name-First: Biao
Author-X-Name-Last: Xu
Author-Name: Zhong Yao
Author-X-Name-First: Zhong
Author-X-Name-Last: Yao
Author-Name: Pengfei Tang
Author-X-Name-First: Pengfei
Author-X-Name-Last: Tang
Title: Pricing strategies for information products with network effects and complementary services in a duopolistic market
Abstract: 
 In this paper, we model a fully covered duopoly market in which two firms offer a differentiated information product that exhibits positive network effects and a complementary premium service to consumers. For each firm, there are two marketing strategies: the freemium strategy and the bundling strategy. We find that, under the market equilibrium, a firms’ decision whether to employ the freemium strategy or not depends largely on the quality of the information product compared to its rival. When the information product quality is similar and the products’ intrinsic values are sufficiently large, both firms will be better off by adopting the freemium strategy, while the bundling strategy will prevail if the products’ intrinsic values are sufficiently small. Additionally, when the magnitude of complementary effects or network effects exceeds a given threshold, both firms’ profit can be enhanced by an increase in the degree of product complementarity or in the intensity of network effects. We also demonstrate that a firm can benefit from an increasing market size only if the intrinsic value of its information product is sufficiently large. Finally, we extend our model to the uncovered market and derive the equilibrium prices and profits.
Journal: International Journal of Production Research
Pages: 4243-4263
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1425558
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1425558
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Template-Type: ReDIF-Article 1.0
Author-Name: Roberto Sarmiento
Author-X-Name-First: Roberto
Author-X-Name-Last: Sarmiento
Author-Name: Garvan Whelan
Author-X-Name-First: Garvan
Author-X-Name-Last: Whelan
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Title: A note on ‘beyond the trade-off and cumulative capabilities models: alternative models of operations strategy’
Abstract: 
 A recent thought provoking paper affirms that in practice, the trade-offs model is not used. In this study, we reanalyse the data based on a more complete understanding of Skinner’s model. Our results indicate that while there may be some evidence of firms that are capable of achieving high performance across a number of manufacturing capabilities in that investigation,  there is also plenty of evidence generally consistent with the core tenet of the trade-offs model. We also emphasise that more practical and definitive statements about Skinner’s model must necessarily involve detailed studies of market leading firms, or, individual product/services. Opportunities to move forward on the topic of strategic trade-offs are outlined.
Journal: International Journal of Production Research
Pages: 4368-4375
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1428773
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1428773
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Template-Type: ReDIF-Article 1.0
Author-Name: Min Wang
Author-X-Name-First: Min
Author-X-Name-Last: Wang
Author-Name: Lindu Zhao
Author-X-Name-First: Lindu
Author-X-Name-Last: Zhao
Author-Name: Michael Herty
Author-X-Name-First: Michael
Author-X-Name-Last: Herty
Title: Modelling carbon trading and refrigerated logistics services within a fresh food supply chain under carbon cap-and-trade regulation
Abstract: 
 Carbon cap-and-trade regulation is widely adopted to reduce carbon emissions. Under this regulation, we propose a carbon trading mechanism considering refrigerated logistics services in a fresh food supply chain. In addition to supplying fresh food, the supplier offers refrigerated logistics services and overstocked carbon emission permits to the retailer. We study the decisions on the price of emission permits traded within the supply chain, the retail price and the price of refrigerated logistics services in different carbon trading options, without carbon trade, inner carbon trade, inner and outer carbon trade. Pricing strategies for fresh food, emission permits and refrigerated logistics services are provided for supply chain members. We also reveal the relationship between carbon trading and refrigerated logistics services, and investigate their joint influence on the supplier–retailer cooperative relationship. In addition, it is shown that with the implementation of a transfer payment mechanism, supply chain members are motivated to participate in the carbon trading mechanism, which has advantages including improved resource utilisation and more competitive supply chains.
Journal: International Journal of Production Research
Pages: 4207-4225
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1430904
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1430904
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:12:p:4207-4225




Template-Type: ReDIF-Article 1.0
Author-Name: Yao Zhang
Author-X-Name-First: Yao
Author-X-Name-Last: Zhang
Author-Name: Cui Zhao
Author-X-Name-First: Cui
Author-X-Name-Last: Zhao
Author-Name: Bo Pang
Author-X-Name-First: Bo
Author-X-Name-Last: Pang
Title: Budget allocation in coping with supply chain disruption risks
Abstract: 
 Disruption management, as an important research topic, has attracted scholars’ broad attention in recent years due to the increasing exposure of disruption risks in supply chains. To date, researches in this field often focus on either prevention or mitigation measures and the budget allocation problem is paid relatively little attention. This paper therefore proposes an approach to determine the optimal budget allocation based on prevention measures in combination with mitigation measures. First, considering different disruption situations, the bow-tie is applied to developing the disruption management frameworks that integrate risk prevention and risk mitigation. Second, the corresponding optimization models are formulated to determine the optimal budget allocation plans. In order to validate the proposed approach, we compare the computation results with those obtained from the prevention approach and the mitigation approach. Also, random experiments are conducted to analyse the impacts of randomly generated disruption and response scenarios. Finally, a real-life case is provided to testify the usefulness and merits of our proposed approach. The results show that the proposed approach can help decision-makers reduce more loss caused by the disruption risks.
Journal: International Journal of Production Research
Pages: 4152-4167
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1430905
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1430905
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:12:p:4152-4167




Template-Type: ReDIF-Article 1.0
Author-Name: Ville Sillanpää
Author-X-Name-First: Ville
Author-X-Name-Last: Sillanpää
Author-Name: Juuso Liesiö
Author-X-Name-First: Juuso
Author-X-Name-Last: Liesiö
Title: Forecasting replenishment orders in retail: value of modelling low and intermittent consumer demand with distributions
Abstract: 
 In retail, distribution centres can forecast the stores’ future replenishment orders by computing planned orders for each stock-keeping-unit. Planned orders are obtained by simulating the future replenishment ordering of each stock-keeping-unit based on information about the delivery schedules, the inventory levels, the order policies and the point-estimate forecasts of consumer demand. Point-estimate forecasts are commonly used because automated store ordering systems do not provide information on the demand distribution. However, it is not clear how accurate the resulting planned orders are in the case of products with low and intermittent demand, which make up large parts of the assortment in retail. This paper examines the added value of modelling consumer demand with distributions, when computing the planned orders of products with low and intermittent demand. We use real sales data to estimate two versions of a planned order model: One that uses point-estimates and another that uses distributions to model the consumer demand. We compare the forecasting accuracies of the two models and apply them to two example applications. Our results show that using distributions instead of point-estimates results in a significant improvement in the accuracy of replenishment order forecasts and offers potential for substantial cost savings.
Journal: International Journal of Production Research
Pages: 4168-4185
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1431413
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1431413
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Template-Type: ReDIF-Article 1.0
Author-Name: Mauricio Varas
Author-X-Name-First: Mauricio
Author-X-Name-Last: Varas
Author-Name: Sergio Maturana
Author-X-Name-First: Sergio
Author-X-Name-Last: Maturana
Author-Name: Susan Cholette
Author-X-Name-First: Susan
Author-X-Name-Last: Cholette
Author-Name: Alejandro Mac Cawley
Author-X-Name-First: Alejandro
Author-X-Name-Last: Mac Cawley
Author-Name: Franco Basso
Author-X-Name-First: Franco
Author-X-Name-Last: Basso
Title: Assessing the benefits of labelling postponement in an export-focused winery
Abstract: 
 Supporting wine production operations in an increasingly global market has grown ever more challenging. Export-focused wineries supply many foreign clients, often requiring different labels for the same kind of wine. Order forecasts tend to be highly inaccurate, and wineries must be able to quickly react to changes, making lot-sizing an important consideration. One tool to reduce product misallocation is postponing product differentiation, where the natural decoupling point for premium wine is the labelling process. However, the double handling involved incurs additional costs and time penalties. We analyse the performance impact of postponing the labelling of bottled wines by developing a multi-stage mixed-integer stochastic programming model with full recourse for demand scenarios. The underlying data and policies are based on an unnamed Chilean export-focused winery. The model supports lot-sizing under several winery production policies. We experiment with different levels of capacity tightness, demand variability and demand correlation between wines, optimising for reducing order backlogs, inventory levels and line set-ups. While we find that some amount of postponement will always be recommended, the exact mix and degree depend on these external factors. Postponement has the most benefits when production capacity is moderately tight, demand variability is high and wines have negatively correlated demands.
Journal: International Journal of Production Research
Pages: 4132-4151
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1431415
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1431415
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Template-Type: ReDIF-Article 1.0
Author-Name: Philippe Lacomme
Author-X-Name-First: Philippe
Author-X-Name-Last: Lacomme
Author-Name: Aziz Moukrim
Author-X-Name-First: Aziz
Author-X-Name-Last: Moukrim
Author-Name: Alain Quilliot
Author-X-Name-First: Alain
Author-X-Name-Last: Quilliot
Author-Name: Marina Vinot
Author-X-Name-First: Marina
Author-X-Name-Last: Vinot
Title: Supply chain optimisation with both production and transportation integration: multiple vehicles for a single perishable product
Abstract: 
 This paper deals with an extension of the integrated production and transportation scheduling problem (PTSP) by considering multiple vehicles (PTSPm) for optimisation of supply chains. The problem reflects a real concern for industry since production and transportation subproblems are commonly addressed independently or sequentially, which leads to sub-optimal solutions. The problem includes specific capacity constraints, the short lifespan of products and the special case of the single vehicle that has already been studied in the literature. A greedy randomised adaptive search procedure (GRASP) with an evolutionary local search (ELS) is proposed to solve the instances with a single vehicle as a special case. The method has been proven to be more effective than those published and provides shorter computational times with new best solutions for the single vehicle case. A new set of instances with multiple vehicles is introduced to favour equitable future research. Our study extends previous research using an indirect resolution approach and provides an algorithm to solve a wide range of one-machine scheduling problems with the proper coordination of single or multiple vehicles.
Journal: International Journal of Production Research
Pages: 4313-4336
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1431416
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1431416
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:12:p:4313-4336




Template-Type: ReDIF-Article 1.0
Author-Name: Agus Darmawan
Author-X-Name-First: Agus
Author-X-Name-Last: Darmawan
Author-Name: Hartanto Wong
Author-X-Name-First: Hartanto
Author-X-Name-Last: Wong
Author-Name: Anders Thorstenson
Author-X-Name-First: Anders
Author-X-Name-Last: Thorstenson
Title: Integration of promotion and production decisions in sales and operations planning
Abstract: 
 This paper presents a new modelling framework for developing a sales and operations plan that integrates promotion and production planning decisions. We adopt a rich demand function that captures the dynamics and heterogeneity of consumer response to price promotions by simulating purchase incidence, consumer choice and quantity decisions, as well as household’s inventory level. Our numerical study reveals interesting findings on the benefits of developing an integrated sales and operations plan as well as the optimal timing and number of promotions, and more importantly, how these findings are influenced by the mutual dependence of marketing- and production-related factors.
Journal: International Journal of Production Research
Pages: 4186-4206
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1431418
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1431418
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:12:p:4186-4206




Template-Type: ReDIF-Article 1.0
Author-Name: Kathleen Iacocca
Author-X-Name-First: Kathleen
Author-X-Name-Last: Iacocca
Author-Name: Matthew Liberatore
Author-X-Name-First: Matthew
Author-X-Name-Last: Liberatore
Title: An empirical study of service postponement: locating the push–pull boundary
Abstract: 
 The purpose of this paper is to determine if service firms can profitably perform postponement. We develop a general model to identify the optimal location of the push–pull boundary, or extent of postponement. While previous literature discusses the benefit of applying postponement to the service industry this is the first paper to-date that mathematically models the benefit of service postponement. This paper illustrates how service companies can balance the trade-off between increased responsiveness and increased costs. The single-stage newsvendor model is iteratively applied to each stage of the service process to determine the optimal level of postponement. Two examples demonstrate the value of postponement and the impact of changes in service characteristics are investigated. Finally, this paper provides guidance for service industry professionals on policy-level decisions and applications of postponement.
Journal: International Journal of Production Research
Pages: 4100-4114
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1436786
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1436786
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:12:p:4100-4114




Template-Type: ReDIF-Article 1.0
Author-Name: Ming Li
Author-X-Name-First: Ming
Author-X-Name-Last: Li
Author-Name: Zheng Wang
Author-X-Name-First: Zheng
Author-X-Name-Last: Wang
Title: An integrated robust replenishment/production/distribution policy under inventory inaccuracy
Abstract: 
 In this paper, a centralised production/distribution system is studied, in which the manufacturer controls the processes of raw material ordering, production and final goods distribution. The inventory records of raw materials, work-in-process, final goods in the manufacturer and the retailers are inaccurate. The objective of this research is to develop an integrated policy that can hedge against the negative impact of inventory inaccuracy at all stages of a supply chain. To achieve this aim, a backward recursive integrated robust policy is constructed. First, the time, quantity and vehicle route of the next distribution are forecasted by a distribution sub-policy; then the forecasted distribution time and quantity are used as the objective of the production process control, which is implemented by a production control sub-policy. Raw materials are ordered by a replenishment sub-policy according to the forecasted raw materials consumption in the production process. Numerical experiments are conducted to verify the feasibility and robustness of the proposed policy, which shows that besides of deploying radio frequency identification (RFID) devices in inventory management systems for raw materials, WIPs, final goods of the manufacturer and the retailers, integrated robust policies also can be employed to hedge against the impact of inventory inaccuracy.
Journal: International Journal of Production Research
Pages: 4115-4131
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1444808
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1444808
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Template-Type: ReDIF-Article 1.0
Author-Name: Oussama Ben-Ammar
Author-X-Name-First: Oussama
Author-X-Name-Last: Ben-Ammar
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Optimal order release dates for two-level assembly systems with stochastic lead times at each level
Abstract: 
 In this paper, we examine an optimisation problem for component replenishment in two-level assembly systems under stochastic lead times. The Assembly-to-Order principle is applied. The demand for a finished product and its planned due date are known. The capacity of the assembly system at each level is considered infinite. At each level, the assembly process starts when all the required components or semi-finished items are available. At the second level, the components are ordered from external suppliers and order release dates are decision variables of the problem. A backlogging cost is incurred if the finished product demand is satisfied after the planned due date. If the finished product, a given component or a semi-finished product is available before the corresponding assembly date, an inventory holding cost is considered. Genetic algorithms (GA) reinforced with different techniques are developed to find order release dates that minimise the total expected cost. A Branch and Bound method is also developed to assess the effectiveness of the hybrid GA. Regardless of the number of components and the variability of the costs related to the finished product, the experimental results indicate that the proposed GA are highly efficient.
Journal: International Journal of Production Research
Pages: 4226-4242
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1449268
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1449268
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:12:p:4226-4242




Template-Type: ReDIF-Article 1.0
Author-Name: Nada Sanders
Author-X-Name-First: Nada
Author-X-Name-Last: Sanders
Author-Name: Xiang Wan
Author-X-Name-First: Xiang
Author-X-Name-Last: Wan
Title: Mitigating forecast errors from product variety through information sharing
Abstract: 
 We examine the impact of increasing product variety on two measures of a firm’s forecast performance – forecast accuracy and forecast bias – and test whether shared information mitigates this impact. With companies under pressure to expand product variety yet maintain good forecast accuracy understanding this relationship is critical. We use data gathered pre and post a vertical integration event, where some information forecasted prior to the merger was now available. We show that increasing product variety, and thus the number of forecasts, indeed deteriorates both forecast accuracy and bias. The vertical integration event, providing information sharing, results in improved forecast performance. Further, different product variety attributes (e.g. brand variety and pack variety) are found to have differing impacts. Increasing brand variety is found to have a significantly greater impact on forecast accuracy than pack variety. Using the vertical integration event as a natural experiment we document that expanding product variety negatively impacts forecasts and that information can help mitigated the impact. This is an important contribution as it tests the value of ‘truthful’ information given the elimination of the firm boundary post merger. Further, we show that a firm’s decision to expand product variety should include product variety attributes given their differential impact.
Journal: International Journal of Production Research
Pages: 4356-4367
Issue: 12
Volume: 56
Year: 2018
Month: 6
X-DOI: 10.1080/00207543.2018.1449974
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1449974
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:12:p:4356-4367




Template-Type: ReDIF-Article 1.0
Author-Name: Jingchen Hou
Author-X-Name-First: Jingchen
Author-X-Name-Last: Hou
Author-Name: Andy Neely
Author-X-Name-First: Andy
Author-X-Name-Last: Neely
Title: Investigating risks of outcome-based service contracts from a provider’s perspective
Abstract: 
 Outcome-based contracts (OBC) refer to agreements between providers and customers where providers are paid based on the outcomes they deliver to customers. OBCs have become common for manufacturing firms that are servitising, especially those firms providing advanced services focusing on availability and capability. Whilst many authors acknowledge the importance of understanding risks in OBCs from a provider’s perspective, there are relatively few in depth extant studies. To address this gap in the literature, we conducted 24 interviews with 11 companies to explore risks and risk factors in OBCs from the provider’s perspective. The case studies reveal that the two major risk categories in OBCs are commercial risk regarding the contract negotiations and contract decisions at the contracting stage, and operational risk regarding the implementation and the delivery of OBCs. Our study identifies 23 risk factors that can lead to commercial risk and operational risk in five dimensions: (i) complexity and (ii) dynamism regarding the context of OBCs, (iii) capability, (iv) alignment and (v) dependency regarding the stakeholders of OBCs. The paper explores the links between these risk factors and commercial and operational risk. In doing so, the paper provides a framework for understanding risk in OBCs.
Journal: International Journal of Production Research
Pages: 2103-2115
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1319089
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1319089
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2103-2115




Template-Type: ReDIF-Article 1.0
Author-Name: Marco Ardolino
Author-X-Name-First: Marco
Author-X-Name-Last: Ardolino
Author-Name: Mario Rapaccini
Author-X-Name-First: Mario
Author-X-Name-Last: Rapaccini
Author-Name: Nicola Saccani
Author-X-Name-First: Nicola
Author-X-Name-Last: Saccani
Author-Name: Paolo Gaiardelli
Author-X-Name-First: Paolo
Author-X-Name-Last: Gaiardelli
Author-Name: Giovanni Crespi
Author-X-Name-First: Giovanni
Author-X-Name-Last: Crespi
Author-Name: Carlo Ruggeri
Author-X-Name-First: Carlo
Author-X-Name-Last: Ruggeri
Title: The role of digital technologies for the service transformation of industrial companies
Abstract: 
 The role of digital technologies in service business transformation is under-investigated. This paper contributes to filling this gap by addressing how the Internet of things (IoT), cloud computing (CC) and predictive analytics (PA) facilitate service transformation in industrial companies. Through the Data–Information–Knowledge–Wisdom (DIKW) model, we discuss how the abovementioned technologies transform low-level entities such as data into information and knowledge to support the service transformation of manufacturers. We propose a set of digital capabilities, based on the extant literature and the findings from four case studies. Then, we discuss how these capabilities support the service transformation trajectories of manufacturers. We find that IoT is foundational to any service transformation, although it is mostly needed to become an availability provider. PA is essential for moving to the performance provider profile. Besides providing scalability in all profiles, CC is specifically used to implement an industrialiser strategy, therefore leading to standardised, repeatable and productised offerings.
Journal: International Journal of Production Research
Pages: 2116-2132
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1324224
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1324224
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2116-2132




Template-Type: ReDIF-Article 1.0
Author-Name: Tonci Grubic
Author-X-Name-First: Tonci
Author-X-Name-Last: Grubic
Author-Name: Ian Jennions
Author-X-Name-First: Ian
Author-X-Name-Last: Jennions
Title: Remote monitoring technology and servitised strategies – factors characterising the organisational application
Abstract: 
 This paper introduces factors that characterise the organisational application of remote monitoring technology (RMT) for servitised strategies. Factors were developed through in-depth case studies of four manufacturers operating in aerospace, industrial equipment, marine and transportation sector. They suggest a very complex, multi-levelled, multifaceted and circular relationship between RMT and servitisation. When unfolding this relationship we need to consider: the value proposition, nature of the product and its hierarchical position in the customer’s business, RMT functionality, type and amount of data required, and a number of other factors that either complement or constrain the use of RMT. By providing the necessary lenses, the proposed factors can help in exploring this complexity. One such exploration questions our understanding of outcome-based contracting.
Journal: International Journal of Production Research
Pages: 2133-2149
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1332791
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1332791
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2133-2149




Template-Type: ReDIF-Article 1.0
Author-Name: Johannes Matschewsky
Author-X-Name-First: Johannes
Author-X-Name-Last: Matschewsky
Author-Name: Marianna Lena Kambanou
Author-X-Name-First: Marianna Lena
Author-X-Name-Last: Kambanou
Author-Name: Tomohiko Sakao
Author-X-Name-First: Tomohiko
Author-X-Name-Last: Sakao
Title: Designing and providing integrated product-service systems – challenges, opportunities and solutions resulting from prescriptive approaches in two industrial companies
Abstract: 
 Due to customer pressure and growing competition, industrial companies are increasingly moving towards providing integrated offerings of products and services (PSS). Despite this trend, literature providing a deep understanding of the challenges associated with this transition is limited, while publications discussing approaches that focus on overcoming these challenges are particularly lacking. This article is based on a multi-case study of two Swedish industrial companies undergoing the transition to designing and providing PSS. It reports on the challenges identified at the case companies as well as opportunities arising from and solutions to these challenges. Subsequent to initial research on the challenges, prescriptive approaches such as a life cycle costing method and a PSS design method were applied in the case companies over an extended time frame. On the one hand, these prescriptive approaches provided both a deeper understanding of the challenges, which include a persistent product centred mindset, a lack of adjustment to changed incentive structures and the separation of product and service design. On the other hand, they also led to effective solutions such as focusing on customer value and introducing a PSS transition facilitator for the design team. These solutions were adapted to the situations in the respective companies and they partly went beyond the prescriptive measures first introduced. Therefore, the article shows the applicability of prescriptive approaches and methods to detect, understand and alleviate the challenges of PSS design and provision. Further, the article provides broadly applicable learning for industrial companies undergoing this process.
Journal: International Journal of Production Research
Pages: 2150-2168
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1332792
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1332792
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2150-2168




Template-Type: ReDIF-Article 1.0
Author-Name: Ali Ziaee Bigdeli
Author-X-Name-First: Ali
Author-X-Name-Last: Ziaee Bigdeli
Author-Name: Oscar F. Bustinza
Author-X-Name-First: Oscar F.
Author-X-Name-Last: Bustinza
Author-Name: Ferran Vendrell-Herrero
Author-X-Name-First: Ferran
Author-X-Name-Last: Vendrell-Herrero
Author-Name: Tim Baines
Author-X-Name-First: Tim
Author-X-Name-Last: Baines
Title: Network positioning and risk perception in servitization: evidence from the UK road transport industry
Abstract: 
 For manufacturing firms, the integration of advanced services into their customer offerings has become a crucial decision. Such commercial decisions require weighting the risks and rewards of implementing a business model based on advanced services. While academic experts acknowledge uncertainty of returns on investment despite potential advantages, research generally fails to address the challenge of calculating the actual risks involved in ‘servitization’. This paper seeks better understanding of managers’ risk perception and of servitization implications for strategic partnerships and network positioning, while considering the impact of factors such as entry barriers, technological knowledge and position in the supply chain (SC). Qualitative evidence is drawn from an industrial case study involving firms in the UK’s road transport industry: 14 in-depth interviews with senior executives from seven companies (manufacturers, operators, technology providers). During interviews, a payment card exercise measured risk perception and willingness to take strategic ‘make-or-buy’ decisions. Results suggest that implementing advanced services is perceived as a high-risk strategy, especially when firms lack in-house technological knowledge. However, collaborative strategic partnerships within supply chain networks can mitigate this risk and prove crucial to building entry barriers against external competitors. Based on these findings, implications for network positioning are developed.
Journal: International Journal of Production Research
Pages: 2169-2183
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1341063
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1341063
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2169-2183




Template-Type: ReDIF-Article 1.0
Author-Name: Wim Coreynen
Author-X-Name-First: Wim
Author-X-Name-Last: Coreynen
Author-Name: Paul Matthyssens
Author-X-Name-First: Paul
Author-X-Name-Last: Matthyssens
Author-Name: Roel De Rijck
Author-X-Name-First: Roel
Author-X-Name-Last: De Rijck
Author-Name: Ivo Dewit
Author-X-Name-First: Ivo
Author-X-Name-Last: Dewit
Title: Internal levers for servitization: How product-oriented manufacturers can upscale product-service systems
Abstract: 
 Manufacturing companies that venture into servitisation can experience difficulties when upscaling product-service systems (PSS) for further growth. This research study has two main objectives: first, to develop insight into the internal levers to increase firms’ servitisation capacity, and second, to apply a new methodology to support companies in upscaling PSS. For these purposes, we conduct an exploratory research study of eight manufacturing companies, consisting of both multiple-case and participatory action research methods. We find that manufacturers often experience challenges when either designing or rolling out PSS, which varies based on the company’s chosen strategy. Additionally, they can be confronted with an organisational logic that hinders PSS upscaling efforts. This research offers guidance to practitioners facing internal barriers for servitisation, providing a new method to explore, prioritise and work out concrete PSS-enhancing projects.
Journal: International Journal of Production Research
Pages: 2184-2198
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1343504
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1343504
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2184-2198




Template-Type: ReDIF-Article 1.0
Author-Name: Vicki E. Hodges
Author-X-Name-First: Vicki E.
Author-X-Name-Last: Hodges
Author-Name: John P.T. Mo
Author-X-Name-First: John P.T.
Author-X-Name-Last: Mo
Title: Transitioning defence aerospace support solution to service commercial sector maintenance repair and overhaul
Abstract: 
 Civil aviation as an industry has driven continued growth using third party MRO providers. This growing market attracted Defence organisations to explore the business opportunities of servicing in the commercial sector but they will face significant risks to overcome a large initial handicap before they can compete. This research compares the service requirements of MRO systems in defence sector and commercial sector to identify gaps between the two servicescapes. This paper contributes to defining the servicescapes between defence and commercial MRO service systems and enables the relevant service providers to be responsive to customer requests, but with scope to tailor the final design, and identify system efficiencies in the transition. A new support system is then designed for the defence organisations leverage off experience in the design and support of military aircraft to migrate to adjacent market.
Journal: International Journal of Production Research
Pages: 2199-2217
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1346315
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346315
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2199-2217




Template-Type: ReDIF-Article 1.0
Author-Name: Anna Karlsson
Author-X-Name-First: Anna
Author-X-Name-Last: Karlsson
Author-Name: Lisa Larsson
Author-X-Name-First: Lisa
Author-X-Name-Last: Larsson
Author-Name: Anna Öhrwall Rönnbäck
Author-X-Name-First: Anna
Author-X-Name-Last: Öhrwall Rönnbäck
Title: Product-service system innovation capabilities: linkages between the fuzzy front end and subsequent development phases
Abstract: 
 In an attempt to remain competitive, manufacturers increasingly offer integrated product-service systems (PSSs). This transition from physical products to PSSs calls for new ways of working, for example in the product development process. However, so far only limited attention has been put on capabilities needed to succeed with PSS innovation in the very early development phases – often referred to as the fuzzy front end (FFE). This article, therefore, has a dual aim: first, to further our understanding of capabilities for PSS innovation in the FFE, and second, to determine how these capabilities are linked to PSS innovation capabilities needed in subsequent development phases. Empirical data were collected from an ongoing industrial project developing an innovative PSS offering in a large manufacturing company. Individuals connected to the project reported major challenges, both experienced in the FFE and anticipated in later phases, which provided valuable information regarding capabilities needed to succeed with the endeavour. Findings reveal four links of PSS innovation capabilities: (1) adapting vocabulary and mental models to PSS, (2) handling the ‘intangible aspect’, (3) bridging organisational structures, and (4) managing new business models. PSS innovation capabilities in the FFE are also found to be of higher order (dynamic) compared to capabilities in later development phases.
Journal: International Journal of Production Research
Pages: 2218-2232
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1365181
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1365181
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2218-2232




Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Lahy
Author-X-Name-First: Andrew
Author-X-Name-Last: Lahy
Author-Name: Ai Qiang Li
Author-X-Name-First: Ai Qiang
Author-X-Name-Last: Li
Author-Name: Pauline Found
Author-X-Name-First: Pauline
Author-X-Name-Last: Found
Author-Name: Aris Syntetos
Author-X-Name-First: Aris
Author-X-Name-Last: Syntetos
Author-Name: Mike Wilson
Author-X-Name-First: Mike
Author-X-Name-Last: Wilson
Author-Name: Nicole Ayiomamitou
Author-X-Name-First: Nicole
Author-X-Name-Last: Ayiomamitou
Title: Developing a product–service system through a productisation strategy: a case from the 3PL industry
Abstract: 
 A Product–Service System (PSS) is created by combing a tangible product and an intangible service into one integrated offering. Thus, a PSS can be achieved by a production company adding intangible services to a product using a servitisation strategy or by a service company adding a tangible product to a service by means of a productisation strategy. The focus of this paper is on the latter. Our work demonstrates a significant gap in the literature in this area. To address this, we adapt an existing PSS conceptual framework as a means to identify the driving and restraining forces considered by a service company as it explored the possibility of pursuing a PSS productisation strategy. The conceptual framework is applied in an exploratory case study with a 3PL service provider. Application of the framework reveals new driving and restraining forces not previously discussed in the literature. Furthermore, it allows a preliminary quantification of the driving and restraining forces using a force field analysis approach. Our work contributes towards the expansion of the empirical knowledge base in the area of PSS.
Journal: International Journal of Production Research
Pages: 2233-2249
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1367861
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1367861
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2233-2249




Template-Type: ReDIF-Article 1.0
Author-Name: Gabriela Estrada
Author-X-Name-First: Gabriela
Author-X-Name-Last: Estrada
Author-Name: Dan L. Shunk
Author-X-Name-First: Dan L.
Author-X-Name-Last: Shunk
Author-Name: Feng Ju
Author-X-Name-First: Feng
Author-X-Name-Last: Ju
Title: Systematic continuous improvement model for variation management of key characteristics running with low capability
Abstract: 
 A systematic continuous improvement model (SCIM) is described in this paper. This model responds to improvements opportunities that were identified in the literature and aerospace companies to aim in variation management of KCs and for developing solutions to improve issues in KCs. This approach helps to identify and improve key characteristics (KCs) in products that most influence in rework and scrap costs, especially in material removal processes. SCIM complies with two purposes; a mathematical method to calculate the rework cost for KCs as a variable in function of expected amount of material to be removed. This cost plus scrap cost is used to prioritise KCs running with low capability; this prioritisation is performed by predicting rework and scrap costs based on historical data of manufacturing processes performance, costs associated to rework and scrap parts out of specification and forecast for product demand. Once critical KCs are identified, the second purpose of this model helps engineers to develop solutions to eliminate what is causing KCs running with low capability; this is possible using knowledge management methodologies to capture, structure and storage solutions developed, in order to reuse them in future similar issues. A case study is presented in this paper to apply this model.
Journal: International Journal of Production Research
Pages: 2370-2387
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1369599
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1369599
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Template-Type: ReDIF-Article 1.0
Author-Name: Jafar Namdar
Author-X-Name-First: Jafar
Author-X-Name-Last: Namdar
Author-Name: Xueping Li
Author-X-Name-First: Xueping
Author-X-Name-Last: Li
Author-Name: Rupy Sawhney
Author-X-Name-First: Rupy
Author-X-Name-Last: Sawhney
Author-Name: Ninad Pradhan
Author-X-Name-First: Ninad
Author-X-Name-Last: Pradhan
Title: Supply chain resilience for single and multiple sourcing in the presence of disruption risks
Abstract: 
 This paper investigates the use of sourcing strategies to achieve supply chain resilience under disruptions. The coping strategies considered are single and multiple sourcing, backup supplier contracts, spot purchasing, and collaboration and visibility. Collaboration and visibility, which affect suppliers’ recovery capabilities and a buyer’s warning capability, have not been similarly modelled in the past. A scenario-based mathematical model is developed such that it considers objectives under uncertainties including disruption risks and operational risks. A broad numerical study examines its output for various risk attitudes in a decision-maker, ranging from risk neutral to risk averse. The sensitivity of procurement strategies to other key parameters such as recovery and warning capabilities is examined. One of the major findings is that buyer’s warning capability plays a vital role in enhancing supply chain resilience. We seek to build on these efforts to further support disruption planning and mitigation and to obtain a deeper understanding of the relationship between supply chain characteristics and resilience.
Journal: International Journal of Production Research
Pages: 2339-2360
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1370149
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1370149
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2339-2360




Template-Type: ReDIF-Article 1.0
Author-Name: Fu Gao
Author-X-Name-First: Fu
Author-X-Name-Last: Gao
Author-Name: Mengqi Liu
Author-X-Name-First: Mengqi
Author-X-Name-Last: Liu
Author-Name: Jian-Jun Wang
Author-X-Name-First: Jian-Jun
Author-X-Name-Last: Wang
Author-Name: Yuan-Yuan Lu
Author-X-Name-First: Yuan-Yuan
Author-X-Name-Last: Lu
Title: No-wait two-machine permutation flow shop scheduling problem with learning effect, common due date and controllable job processing times
Abstract: 
 We consider a two-machine no-wait permutation flow shop common due date assignment scheduling problem where the processing time of a job is given as a function of its position in the sequence and its amount of resource allocated to this job. The common due date (CON) assignment method means that all the jobs are given a common due date. We need to make a decision on the common due date, resource allocation and the sequence of jobs to minimise total earliness, tardiness, common due date cost and total resource cost. We show that the problem remains polynomially solvable under the proposed model.
Journal: International Journal of Production Research
Pages: 2361-2369
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1371353
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1371353
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2361-2369




Template-Type: ReDIF-Article 1.0
Author-Name: Jingsi Huang
Author-X-Name-First: Jingsi
Author-X-Name-Last: Huang
Author-Name: Jie Song
Author-X-Name-First: Jie
Author-X-Name-Last: Song
Title: Optimal inventory control with sequential online auction in agriculture supply chain: an agent-based simulation optimisation approach
Abstract: 
 With the development of e-commerce, in agriculture supply chain, online auction is adopted as an inventory clearing tool. Comparing to mathematical models studying inventory control over online sequential auctions, our agent-based simulation model could systematically describe the complexities of bidders’ information interactions and behaviour preferences caused from financial and production perspectives, and by other supply chain members. In addition, we take into account the complex and dynamic market environment, which will impact the operation effect of auction policies. With identical auction items, the profit-maximising firm must decide auction lot-size, which is the number of units in each auction, minimum initial bid, and the time interval between auctions. To obtain the optimal solution, nested partitions framework and optimal expected opportunity cost algorithm are integrated to improve computation accuracy and efficiency. A case study based on real data is conducted to implement and validate the proposed approach. Furthermore, based on the model, the paper studies the sensitivities of the decision variables under different supply and demand scenarios.
Journal: International Journal of Production Research
Pages: 2322-2338
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1373203
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1373203
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2322-2338




Template-Type: ReDIF-Article 1.0
Author-Name: R.B. Seno Wulung
Author-X-Name-First: R.B.
Author-X-Name-Last: Seno Wulung
Author-Name: Katsuhiko Takahashi
Author-X-Name-First: Katsuhiko
Author-X-Name-Last: Takahashi
Author-Name: Katsumi Morikawa
Author-X-Name-First: Katsumi
Author-X-Name-Last: Morikawa
Title: A model for selecting appropriate technology for incubator-university collaboration by considering the technology transfer mechanism
Abstract: 
 A technology incubator provides an important support for a technology transfer mechanism. A technology incubator bridges the incubatees to the technology provider. In our research, we propose a technology selection model for the incubatees. Incubator managers, as decision-makers, attempt to evaluate new technology for the incubatees by comparing its profit with that of the old or established technology. The technology is proposed by a technology provider, which in this case is a university. In the technology selection activity, the distance between the technology level of incubatees and transferred technology should be considered. Unfortunately, there has been no effort to formulate a technology selection model in the technology incubator that considers the technology distance and is linked to the incubatees’ profit as financial performance. We examine the impact of the technological-level and technology assimilation rate in the technology selection process in the technology incubator. We analyse the external factor of customer acceptance of new technology with a probabilistic value and technology obsolescence. Furthermore, we introduce a profit-sharing scheme to share the profit of the incubatees with the university as a technology provider. Utilising a profit-sharing scheme means sharing the risk between incubatees and the university.
Journal: International Journal of Production Research
Pages: 2309-2321
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1374569
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1374569
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming-Chuan Chiu
Author-X-Name-First: Ming-Chuan
Author-X-Name-Last: Chiu
Author-Name: Chih-Yuan Chu
Author-X-Name-First: Chih-Yuan
Author-X-Name-Last: Chu
Author-Name: Chih-Chuan Chen
Author-X-Name-First: Chih-Chuan
Author-X-Name-Last: Chen
Title: An integrated product service system modelling methodology with a case study of clothing industry
Abstract: 
 Product-service system (PSS) is a business model designed to help enterprises achieve servitisation. PSS not only considers service-oriented logic to increase product value but also supports enterprises with waste reduction. An increasing number of studies have emphasised PSS development. However, much of the literature remains focused on separate development phases, such as idea generation or a specific product or industry application. An integrative system modelling methodology designed to help companies formulate a complete scenario is absent. This study provides a methodology for developing a systematic and complete PSS strategy. It combines failure modes and effects and importance-performance analysis to identify potential customer needs. A service-product development matrix and a product-service life cycle analysis are developed. Following the service concepts generation, grey relational analysis and scenario analysis are utilised to evaluate the alternatives. A case study involving the clothing industry was conducted to test the proposed approach. Results indicate the methodology can help service providers identify existing problems and develop service alternatives systematically. These alternatives can then be evaluated and the scenario which achieves the highest profitability, is the most environmental friendly, and is the most social friendly can be identified.
Journal: International Journal of Production Research
Pages: 2388-2409
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1374570
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1374570
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2388-2409




Template-Type: ReDIF-Article 1.0
Author-Name: Cheng-Hsiung Lee
Author-X-Name-First: Cheng-Hsiung
Author-X-Name-Last: Lee
Title: A dispatching rule and a random iterated greedy metaheuristic for identical parallel machine scheduling to minimize total tardiness
Abstract: 
 This paper addresses a real-life production scheduling problem with identical parallel machines, originating from a plant producing Acrylonitrile-Butadiene-Styrene (ABS) plate products. In the considered practical scheduling problem, ABS plate has some specific specifications and each specification has several different levels. Because there is at least one different level of specification between two ABS plate products, it is necessary to make a set-up adjustment on each machine whenever a switch occurs from processing one ABS plate product to another product. As tardiness leads to extra penalty costs and opportunity losses, the objective of minimising total tardiness has become one of the most important tasks for the schedule manager in the plant. The problem can be classified as an identical parallel machine scheduling problem to minimise the total tardiness. A dispatching rule is proposed for this problem and evaluated by comparing it with the current scheduling method and several existing approaches. Moreover, an iterated greedy-based metaheuristic is developed to further improve the initial solution. The experimental results show that the proposed metaheuristic can perform better than an existing tabu search algorithm, and obtain the optimal solution for small-sized problems and significantly improve the initial solutions for large-sized problems.
Journal: International Journal of Production Research
Pages: 2292-2308
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1374571
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1374571
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2292-2308




Template-Type: ReDIF-Article 1.0
Author-Name: Stephan M. Wagner
Author-X-Name-First: Stephan M.
Author-X-Name-Last: Wagner
Author-Name: Ruben Jönke
Author-X-Name-First: Ruben
Author-X-Name-Last: Jönke
Author-Name: Eleni Hadjiconstantinou
Author-X-Name-First: Eleni
Author-X-Name-Last: Hadjiconstantinou
Title: Relationship archetypes in aftermarkets
Abstract: 
 Aftermarket sales and profits have become an increasingly important part of an Original Equipment Manufacturer’s (OEM) business model. The attractiveness of the after-sales business, however, has also been recognised by other parties (e.g. competitors, suppliers) who try to capture a share of the aftermarket. A highly profitable aftermarket creates a strong incentive for the supplier to disintermediate the established supply chain and sell directly to the OEM’s aftermarket customers. To counter this threat, OEMs must be aware of the activities and actors on their aftermarket, and should understand and systematically analyse the existing or changing business relationships among the incumbent and emergent actors in the aftermarket ecosystem. In this exploratory study we use case study research with 29 companies (customer, OEM, supplier, or competitor) and draw on social network theory – in particular the concepts of structural embeddedness, structural hole and supply chain disintermediation – to examine and discuss triadic and tetradic relationship constellations (archetypes) in aftermarkets. Recognising these relationship archetypes in aftermarkets can help firms to adapt their after-sales strategies and protect the competitive advantage, revenues and profits stemming from their after-sales business.
Journal: International Journal of Production Research
Pages: 2250-2268
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1378826
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1378826
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2250-2268




Template-Type: ReDIF-Article 1.0
Author-Name: Sergio Cavalieri
Author-X-Name-First: Sergio
Author-X-Name-Last: Cavalieri
Author-Name: Zied M. Ouertani
Author-X-Name-First: Zied M.
Author-X-Name-Last: Ouertani
Author-Name: Jiang Zhibin
Author-X-Name-First: Jiang
Author-X-Name-Last: Zhibin
Author-Name: Alice Rondini
Author-X-Name-First: Alice
Author-X-Name-Last: Rondini
Title: Service transformation in industrial companies
Journal: International Journal of Production Research
Pages: 2099-2102
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1378830
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1378830
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2099-2102




Template-Type: ReDIF-Article 1.0
Author-Name: Stelian Brad
Author-X-Name-First: Stelian
Author-X-Name-Last: Brad
Author-Name: Mircea Murar
Author-X-Name-First: Mircea
Author-X-Name-Last: Murar
Author-Name: Emilia Brad
Author-X-Name-First: Emilia
Author-X-Name-Last: Brad
Title: Design of smart connected manufacturing resources to enable changeability, reconfigurability and total-cost-of-ownership models in the factory-of-the-future
Abstract: 
 The fourth industrial revolution requires higher capabilities of changeability and reconfigurability (C–R) of the future factories (FoF), as well as a higher focus on business models that are based on total-cost-of-ownership (TCO) paradigm. Up to date, there are little scientific contributions to deploy C–R into TCO models, as well as to systematic plan and design manufacturing resources such as to facilitate FoF ecosystem. In order to address this issue, this paper introduces research results that show how to deploy C–R, connectivity, smartness and TCO requirements into the technical solutions of manufacturing resources of FoF. Contributions emerging from this research include an index to measure C–R capability of manufacturing resources, a model to assess economic feasibility of a FoF over its lifecycle, as well as a methodology and related tools to design smart connected manufacturing resources with embedded features to facilitate changeability and reconfigurability in a FoF. Theoretical contributions are explained through a case study of a fast reconfigurable robotic manufacturing cell. Preliminary results demonstrate that it is possible to rapid design smart connected manufacturing resources and integrate them into FoF architectures that support convertibility, integrability, modifiability, adaptability, serviceability, scalability, integration of resources from various producers, service clustering and cloud-based services.
Journal: International Journal of Production Research
Pages: 2269-2291
Issue: 6
Volume: 56
Year: 2018
Month: 3
X-DOI: 10.1080/00207543.2017.1400705
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1400705
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2269-2291




Template-Type: ReDIF-Article 1.0
Author-Name: Roberto Montanari
Author-X-Name-First: Roberto
Author-X-Name-Last: Montanari
Author-Name: Gino Ferretti
Author-X-Name-First: Gino
Author-X-Name-Last: Ferretti
Author-Name: Marta Rinaldi
Author-X-Name-First: Marta
Author-X-Name-Last: Rinaldi
Author-Name: Eleonora Bottani
Author-X-Name-First: Eleonora
Author-X-Name-Last: Bottani
Title: Investigating the demand propagation in EOQ supply networks using a probabilistic model
Abstract: 
 In this paper, we introduce a new demand probabilistic approach, named M.DPA.eoq (Montanari Demand Probabilistic Approach in economic order quantity [EOQ] scenario), for predicting the demand seen by an upper tier echelon (e.g. a distribution centre) of a supply network, serving several lower tier echelons operating according to an EOQ reorder policy. The M.DPA.eoq is based on an analytic approach, by which we derive the distribution of the demand seen by the upper tier echelon of the supply network. The approach has been designed to be very simple, so as to gain in pedagogical value. The simplicity and ease of application of this approach are confirmed by the possibility of exploiting general purpose software, such as Microsoft ExcelTM, to implement and validate it. Moreover, the M.DPA.eoq has potential to be directly exploited by practitioners, such as supply network managers, to estimate the distribution of the demand the upper tier echelon will face under a defined network structure. Students and researchers could also benefit from such a model, given its ease of understanding and usage. With the purpose of showing its potential usefulness in real cases, we discuss two practical implications of the M.DPA.eoq, referring to the use of its results for: (1) computing the bullwhip effect of the network; and (2) analysing the impact of each retail store on the variance of the demand seen by the upper tier echelon.
Journal: International Journal of Production Research
Pages: 1307-1324
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.917772
File-URL: http://hdl.handle.net/10.1080/00207543.2014.917772
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:5:p:1307-1324




Template-Type: ReDIF-Article 1.0
Author-Name: Chen Qian
Author-X-Name-First: Chen
Author-X-Name-Last: Qian
Author-Name: Ching-Yuen Chan
Author-X-Name-First: Ching-Yuen
Author-X-Name-Last: Chan
Title: A new production approach for compensating forecast error and customer loss in waiting
Abstract: 
 It is noticeable that forecast information is always subject to some deviations, but it helps reduce the product time-to-market. This is important as customer loyalty decreases as the waiting time becomes longer; thus, to have a balance between forecast error and customer loss becomes essential. This paper presents a production approach that aims at compensating the forecast error and the possible customer loss in waiting for either a product (or a service) to boost the profit. A novel model to tackle this scenario is presented. The results showed that it could offer a better production solution than the Make-To-Stock or the Make-To-Order approaches by starting the production sometime in between these two traditional approaches.
Journal: International Journal of Production Research
Pages: 1325-1336
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.918292
File-URL: http://hdl.handle.net/10.1080/00207543.2014.918292
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:5:p:1325-1336




Template-Type: ReDIF-Article 1.0
Author-Name: M. Lees
Author-X-Name-First: M.
Author-X-Name-Last: Lees
Author-Name: R. Ellen
Author-X-Name-First: R.
Author-X-Name-Last: Ellen
Author-Name: P. Brodie
Author-X-Name-First: P.
Author-X-Name-Last: Brodie
Author-Name: M. Steffens
Author-X-Name-First: M.
Author-X-Name-Last: Steffens
Author-Name: B. Newell
Author-X-Name-First: B.
Author-X-Name-Last: Newell
Author-Name: D. Wilkey
Author-X-Name-First: D.
Author-X-Name-Last: Wilkey
Title: An online Utilities Consumption Model for real-time load identification
Abstract: 
 A novel architecture for a real-time Utilities Consumption Model (UCM) has been developed. The online UCM is capable of estimating the contributions from individual items of equipment towards the total instantaneous load of key utilities in a manufacturing plant. It also has the capability to forecast future consumption for areas of a plant that are scheduled. The UCM is a useful addition to the industrial control tool-set as it provides an effective means of minimising the energy impact of the timing and scheduling aspects of plant operations. A case study, demonstrating the application of the UCM at the Carlton &amp; United Breweries (CUB) plant at Yatala, Australia, is included.
Journal: International Journal of Production Research
Pages: 1337-1357
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.919415
File-URL: http://hdl.handle.net/10.1080/00207543.2014.919415
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:5:p:1337-1357




Template-Type: ReDIF-Article 1.0
Author-Name: Masoud Khakdaman
Author-X-Name-First: Masoud
Author-X-Name-Last: Khakdaman
Author-Name: Kuan Yew Wong
Author-X-Name-First: Kuan Yew
Author-X-Name-Last: Wong
Author-Name: Bahareh Zohoori
Author-X-Name-First: Bahareh
Author-X-Name-Last: Zohoori
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Author-Name: Rico Merkert
Author-X-Name-First: Rico
Author-X-Name-Last: Merkert
Title: Tactical production planning in a hybrid Make-to-Stock–Make-to-Order environment under supply, process and demand uncertainties: a robust optimisation model
Abstract: 
 In this paper, we consider a hybrid ‘Make-to-Stock–Make-to-Order’ environment to develop a novel optimisation model for medium-term production planning of a typical multi-product firm based on the competencies of the robust optimisation methodology. Three types of uncertainties: suppliers, processes and customers, are incorporated into the model to construct a robust practical model in an uncertain business environment. The modelling procedure is started with applying deterministic linear programming to develop a new multi-objective approach for the combination of multi-product multi-period production planning and aggregate production planning problems. Then, the proposed deterministic model is transformed into a robust optimisation framework and the solution procedure is designed according to the Lp-Metric methodology. Next, using the IBM ILOG CPLEX optimisation software, the proposed model is evaluated by applying the data collected from an industrial case study. Final results illustrate the applicability of the proposed model.
Journal: International Journal of Production Research
Pages: 1358-1386
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.935828
File-URL: http://hdl.handle.net/10.1080/00207543.2014.935828
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Template-Type: ReDIF-Article 1.0
Author-Name: Gilbert Fridgen
Author-X-Name-First: Gilbert
Author-X-Name-Last: Fridgen
Author-Name: Christian Stepanek
Author-X-Name-First: Christian
Author-X-Name-Last: Stepanek
Author-Name: Thomas Wolf
Author-X-Name-First: Thomas
Author-X-Name-Last: Wolf
Title: Investigation of exogenous shocks in complex supply networks – a modular Petri Net approach
Abstract: 
 Global supply networks that can be considered as interlaced supply chains are shaping existing economic structures. These supply networks are creating a high level of complexity. Simultaneously, the perceived number of exogenous shocks such as natural disasters is increasing. These exogenous shocks can directly or indirectly impact the participating companies of a supply network, which can also threaten the network as a whole. However, the complexity and opacity of today’s supply networks inhibit an accurate prediction and quantification of such impacts. Therefore, companies are unable to develop adequate safeguards, while existing mechanisms are insufficient. The objective of this study is to model, analyse and quantify the impacts of exogenous shocks on supply networks. Therefore, we use a Petri Net-based approach, which enables a simulation of different supply network constellations, to assess the vulnerability to exogenous shocks. Furthermore, we include a detailed description of modelling and evaluation of the presented method. For an exemplary supply network, we simulate different intensities of an exogenous shock combined with different safety stocks of the entities. Statistical tests are conducted to verify the results. We thereby illustrate the results that could be yielded from a real-world application.
Journal: International Journal of Production Research
Pages: 1387-1408
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.942009
File-URL: http://hdl.handle.net/10.1080/00207543.2014.942009
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Template-Type: ReDIF-Article 1.0
Author-Name: Jesús F. Lampón
Author-X-Name-First: Jesús F.
Author-X-Name-Last: Lampón
Author-Name: Santiago Lago-Peñas
Author-X-Name-First: Santiago
Author-X-Name-Last: Lago-Peñas
Author-Name: Javier González-Benito
Author-X-Name-First: Javier
Author-X-Name-Last: González-Benito
Title: International relocation and production geography in the European automobile components sector: the case of Spain
Abstract: 
 This article, based on the various approaches to location theory, analyses relocation processes in the Spanish automobile components industry in order to explain the importance of internal factors at both corporate and production plant levels. While acknowledging that location advantages play a relevant role, we show that changes in production geography can, to a great extent, be explained by corporate strategies, other decision-making mechanisms and firms’ characteristics. The results obtained from an empirical study during the period 2001–2008 show that the search for lower labour costs and corporate restructuring in order to achieve global production efficiency are the main factors determining relocation in the Spanish sector. These processes are facilitated by the operational flexibility of the multinational firms that dominate the sector. Lean supply and technological requirements are the main barriers to such processes of production plant mobility. From the point of view of practical relevance, the article shows that these logistic and technological determinants should be considered by managers in their relocation decisions not only in terms of cost efficiency but also in terms of the risks involved in relocation processes. Any relocation project must include measures to mitigate such risks.
Journal: International Journal of Production Research
Pages: 1409-1424
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.942757
File-URL: http://hdl.handle.net/10.1080/00207543.2014.942757
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Template-Type: ReDIF-Article 1.0
Author-Name: Cheng-Hu Yang
Author-X-Name-First: Cheng-Hu
Author-X-Name-Last: Yang
Author-Name: Jian Wang
Author-X-Name-First: Jian
Author-X-Name-Last: Wang
Author-Name: Ping Ji
Author-X-Name-First: Ping
Author-X-Name-Last: Ji
Title: Optimal acquisition policy in remanufacturing under general core quality distributions
Abstract: 
 The quality of acquirable used products (cores) is highly variable, which has made production planning and control of remanufacturing systems difficult. This paper studies an acquisition problem in presence of uncertain core quality. In order to derive optimal acquisition policy, the problem is formulated as a non-linear integer programming model in the framework of order statistics. The model is a strictly discrete convex problem with a unique global minimal solution. Then, a single bisection method is developed to obtain the optimal solution under a general continuous quality distribution. Moreover, the expressions of the optimal solution in some frequently used quality distributions are derived. Furthermore, the model is extended to the case of a general remanufacturing cost function, and corresponding results are presented. Finally, numerical experiments are conducted to test the effects of quality distribution, cost relationships of acquirable cores and remanufacturing cost function.
Journal: International Journal of Production Research
Pages: 1425-1438
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.944283
File-URL: http://hdl.handle.net/10.1080/00207543.2014.944283
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Template-Type: ReDIF-Article 1.0
Author-Name: Mustapha Sali
Author-X-Name-First: Mustapha
Author-X-Name-Last: Sali
Author-Name: Evren Sahin
Author-X-Name-First: Evren
Author-X-Name-Last: Sahin
Author-Name: Alain Patchong
Author-X-Name-First: Alain
Author-X-Name-Last: Patchong
Title: An empirical assessment of the performances of three line feeding modes used in the automotive sector: line stocking vs. kitting vs. sequencing
Abstract: 
 In high diversity, Just In Time production environments, mixed-model assembly lines aim at producing a large amount of end products that use alternative variants of components used in the assembly process. Therefore, the availability of parts required at the border of the assembly line is critical for the production process. To ensure the availability of parts needed on the line, three line feeding modes are commonly used in practice: line stocking, kitting and sequencing. The relative performance of each mode, in terms of average total operating cost, depends on various factors such as the diversity of components, parts’ physical features (i.e. weight and volume), to name a few. The impact of such parameters on the performance of line feeding modes remains still weakly studied in the literature. Through an empirical approach based on a real case, our study aims at evaluating the average total cost pertaining to each mode. The total cost includes parts preparation before assembly, picking, in-plant transportation and storage costs. A thorough comparative study enables then to characterise situations which make one mode less costly compared with the others. Each situation corresponds to specific values taken by parameters that are considered in the cost formulation.
Journal: International Journal of Production Research
Pages: 1439-1459
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.944630
File-URL: http://hdl.handle.net/10.1080/00207543.2014.944630
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Template-Type: ReDIF-Article 1.0
Author-Name: Xuejun Hu
Author-X-Name-First: Xuejun
Author-X-Name-Last: Hu
Author-Name: Nanfang Cui
Author-X-Name-First: Nanfang
Author-X-Name-Last: Cui
Author-Name: Erik Demeulemeester
Author-X-Name-First: Erik
Author-X-Name-Last: Demeulemeester
Title: Effective expediting to improve project due date and cost performance through buffer management
Abstract: 
 The rapidly changing marketplace together with the increasing complexity of contemporary projects makes it more likely that project activities will have uncertain durations, incurring a generally low probability of on-time delivery. Thus, project control that aims to track the project performance and to expedite relevant activities when necessary has become the main aspect within the scope of project management in order to ensure a successful scheduling outcome. The Critical Chain Scheduling and Buffer Management (CC/BM) has shown to provide a popular approach to build robust project schedules and to offer a valuable control tool for coping with schedule variability. However, the most current buffer management (BM) practice faces a problem of neglecting the cost information when taking expediting actions. In view of this defect, we introduce a new control procedure on the basis of CC/BM that evaluates the probability of successful project completion relative to the cost of crashing and that determines when to expedite which activities in a cost-effective manner. Results of an experimental application of the proposed method present its relative dominance over the currently widely adopted BM approach with respect to project time and cost performance.
Journal: International Journal of Production Research
Pages: 1460-1471
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.948972
File-URL: http://hdl.handle.net/10.1080/00207543.2014.948972
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Template-Type: ReDIF-Article 1.0
Author-Name: Devendra Choudhary
Author-X-Name-First: Devendra
Author-X-Name-Last: Choudhary
Author-Name: Ravi Shankar
Author-X-Name-First: Ravi
Author-X-Name-Last: Shankar
Title: The value of VMI beyond information sharing under time-varying stochastic demand
Abstract: 
 This study aims to determine the incremental value vendor-managed inventory (VMI) provides beyond that of independent decision-making with full information sharing (IS) under time-varying stochastic demand with service-level constraints. For this purpose, we apply mixed integer linear programming formulations to examine benefits for a supplier, a retailer and the system as a whole. To highlight the benefits of VMI vs. IS, a comprehensive numerical study is carried out considering a large number of business settings under both static and rolling horizons.
Journal: International Journal of Production Research
Pages: 1472-1486
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.951093
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951093
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Template-Type: ReDIF-Article 1.0
Author-Name: Lu Zhen
Author-X-Name-First: Lu
Author-X-Name-Last: Zhen
Title: Task assignment under uncertainty: stochastic programming and robust optimisation approaches
Abstract: 
 The assignment of tasks to teams is a challenging combinatorial optimisation problem. The uncertainty in the tasks’ execution processes further complicates the assignment decisions. This study investigates a variant of the typical assignment problem, in which each task can be divided into two parts, one is deterministic and the other is uncertain with respect to their workloads. From the stochastic perspective, this paper proposes both a stochastic programming model that can cope with arbitrary probability distributions of tasks’ random workload requirements, and a robust optimisation model that is applicable to situations in which limited information about probability distributions is available. An example of its application in the software project management is given. Some numerical experiments are also performed to validate the effectiveness of the proposed models and the relationships between the two models.
Journal: International Journal of Production Research
Pages: 1487-1502
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.951094
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951094
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Template-Type: ReDIF-Article 1.0
Author-Name: Angus Jeang
Author-X-Name-First: Angus
Author-X-Name-Last: Jeang
Title: Project management for uncertainty with multiple objectives optimisation of time, cost and reliability
Abstract: 
 This research adopts an approach that uses computer simulation and statistical analysis of uncertain activity time, activity cost, due date and project budget to address quality and the learning process with regard to project scheduling. Since the learning process affects the scheduling problem, a Cobb–Douglas multiplicative power model is used to represent the relationship between the dependent variable, which is the standard deviation of activity time, and the independent variables, which are the cumulative trials and the mean of activity time. The mean value and standard deviation are used to randomly generate activity times for project scheduling analysis. Response surface methodology (RSM) is used in order to develop a rationale of the time-cost trade-off problem. The solutions found with RSM are optimised only for a single objective, such as project completion time, total project cost, completion time probability and total cost probability. Thus, multiple objectives for further optimisation become necessary and a limited project budget, restricted completion time, allowable total cost probability and acceptable completion time probability have to be considered at the same time as the learning effect. With response functions from RSM, compromise programming is adopted in order to formulate the proposed project scheduling problem for multi-objective optimisation.
Journal: International Journal of Production Research
Pages: 1503-1526
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.952792
File-URL: http://hdl.handle.net/10.1080/00207543.2014.952792
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Template-Type: ReDIF-Article 1.0
Author-Name: Jafar Rezaei
Author-X-Name-First: Jafar
Author-X-Name-Last: Rezaei
Author-Name: Roland Ortt
Author-X-Name-First: Roland
Author-X-Name-Last: Ortt
Author-Name: Paul Trott
Author-X-Name-First: Paul
Author-X-Name-Last: Trott
Title: How SMEs can benefit from supply chain partnerships
Abstract: 
 In recent literature on supply chain partnerships in small and medium-sized enterprises (SMEs), there is controversy regarding the benefits of these partnerships. To resolve this controversy, specific information is needed on the implementation of these partnerships by SMEs; an area, that, thus far, has received little academic attention. In this paper, we examine different business functions (production, marketing and sales, purchasing and logistics, research and development (R&amp;D) and finance) within a supply chain partnership. We collected data for each individual function from 279 high-tech SMEs and examined the relationship between the specific types of partnerships and the overall performance of the SMEs. The results indicate that it is only in the area of R&amp;D that partnerships have a significant positive effect on overall firm performance. The results imply that SMEs primarily can benefit from particular types of supply chain partnerships, i.e. R&amp;D partnerships. The results contribute to the debate in the literature by explaining why many SMEs were found not to benefit from these partnerships. We also provide implications for firms and how SMEs can better utilise supply chain management (SCM).
Journal: International Journal of Production Research
Pages: 1527-1543
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.952793
File-URL: http://hdl.handle.net/10.1080/00207543.2014.952793
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Template-Type: ReDIF-Article 1.0
Author-Name: Anssi Käki
Author-X-Name-First: Anssi
Author-X-Name-Last: Käki
Author-Name: Juuso Liesiö
Author-X-Name-First: Juuso
Author-X-Name-Last: Liesiö
Author-Name: Ahti Salo
Author-X-Name-First: Ahti
Author-X-Name-Last: Salo
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Title: Newsvendor decisions under supply uncertainty
Abstract: 
 We analyse the impact of supply uncertainty on newsvendor decisions. First, we derive a solution for a newsvendor facing stochastic supply yield, in addition to stochastic demand. While earlier research has considered independent uncertainties, we derive the optimal order quantity for interdependent demand and supply and provide a closed-form solution for a specific copula-based dependence structure. This allows us to give insights into how dependence impacts the newsvendor’s decision, profit and risk level. In addition to the theory, we present experimental results that show how difficult newsvendor decisions under supply uncertainty are for human subjects. In our experiment, the control group replicated a well-known newsvendor experiment, whereas the test group faced additional supply yield uncertainty. Comparison of these results shows that under low-profit condition, subjects are able to incorporate supply uncertainty quite well in their decisions. Under high-profit condition, the deviation from the optimum is much more significant. We discuss this asymmetry and also propose some ways to improve newsvendor decision-making.
Journal: International Journal of Production Research
Pages: 1544-1560
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.952798
File-URL: http://hdl.handle.net/10.1080/00207543.2014.952798
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Template-Type: ReDIF-Article 1.0
Author-Name: Canan Aglan
Author-X-Name-First: Canan
Author-X-Name-Last: Aglan
Author-Name: Mehmet Bulent Durmusoglu
Author-X-Name-First: Mehmet Bulent
Author-X-Name-Last: Durmusoglu
Title: Lot-splitting approach of a hybrid manufacturing system under CONWIP production control: a mathematical model
Abstract: 
 This paper discusses the advantages of lot splitting in hybrid manufacturing environments where cellular and functional layouts are combined under Constant Work in Process (CONWIP) production control. The proposed model fills a research gap in the related literature by applying lot splitting and pull production simultaneously. A linear CONWIP control mathematical model that minimises the average flow time is developed in case of lot splitting. The developed model has sequence-dependent set-up times. The demand level, coefficient of variation (CV) impact and set-up time reduction effect on CONWIP production control are also investigated. The model is solved using GAMS21.6 optimisation software; the optimal backlog list, the number and size of sublots are reported. The proposed model is compared with lot production under push control in different settings as well as with two different heuristics from the literature. Experimental results indicate that in all settings, the lot splitting is more advantageous than lot production in terms of average flow time. CV has a greater effect than set-up time reduction on average flow time.
Journal: International Journal of Production Research
Pages: 1561-1583
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.957873
File-URL: http://hdl.handle.net/10.1080/00207543.2014.957873
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Template-Type: ReDIF-Article 1.0
Author-Name: Soumojit Kumar
Author-X-Name-First: Soumojit
Author-X-Name-Last: Kumar
Author-Name: Ashis Kumar Chatterjee
Author-X-Name-First: Ashis Kumar
Author-X-Name-Last: Chatterjee
Title: A profit maximising product line optimisation model under monopolistic competition
Abstract: 
 Existing research on product line optimisation have focused mainly on designing a product line based on the trade-offs between sellers’ and buyers’ utility, without any explicit consideration of the underlying market structure. A few studies can be found that consider the monopolists’ optimal product line offering. In this study, we examine the optimal product line decision of an entrant firm under monopolistic competitive markets. Specifically, we develop a mathematical programming formulation of an entrant firm’s problem of deciding on the market segments to enter and the corresponding product designs to offer, to maximise its profit. A heuristic has been presented for solving the resulting mixed integer non-linear programming problem. The specifications of the problem increase exponentially with the size of the problem and as such, commercial solvers are not useful for solving a generalised instance. A small example has been presented and solved using both the heuristic and the ILOG CPLEX 10.2. Both result in identical solutions. We attempt an explanation on why the heuristic gives an optimal solution.
Journal: International Journal of Production Research
Pages: 1584-1595
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.957874
File-URL: http://hdl.handle.net/10.1080/00207543.2014.957874
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Template-Type: ReDIF-Article 1.0
Author-Name: Aliakbar Hasani
Author-X-Name-First: Aliakbar
Author-X-Name-Last: Hasani
Author-Name: Seyed Hessameddin Zegordi
Author-X-Name-First: Seyed Hessameddin
Author-X-Name-Last: Zegordi
Author-Name: Ehsan Nikbakhsh
Author-X-Name-First: Ehsan
Author-X-Name-Last: Nikbakhsh
Title: Robust closed-loop global supply chain network design under uncertainty: the case of the medical device industry
Abstract: 
 Improving performance of global supply chains requires careful consideration of various factors including distance from markets, access to resources, exchange and tax rates, import tariffs, and trade regulations. In this paper, a comprehensive optimization model is proposed to maximise the after-tax profit of a closed-loop global supply chain for medical devices under uncertainty. The uncertainty of the decision-making environment is modelled using the budget of uncertainty concept in interval robust optimization. International financial issues due to the Economic Cooperation Organisation Trade Agreement as well as national regulations including transfer pricing limitations, exchange rates, tax rates, and import tariffs are considered. The proposed model considers various realistic assumptions pertaining to medical device supply chains such as multiple products, multiple periods, multiple echelons, and limited warehousing lifetime. In addition, reverse flows of perished and defective products are considered to address environmental concerns and customers’ requirements as well as to gain economic advantages. To tackle this problem, an efficient memetic algorithm is developed that incorporates adaptive variable neighbourhood search as its local search heuristic. Computational results demonstrate the efficiency of the proposed model in dealing with uncertainty in an agile manufacturing context. In addition, several managerial insights are discussed based on the results.
Journal: International Journal of Production Research
Pages: 1596-1624
Issue: 5
Volume: 53
Year: 2015
Month: 3
X-DOI: 10.1080/00207543.2014.965349
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965349
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Template-Type: ReDIF-Article 1.0
Author-Name: Alex J. Ruiz-Torres
Author-X-Name-First: Alex J.
Author-X-Name-Last: Ruiz-Torres
Author-Name: Nelson Alomoto
Author-X-Name-First: Nelson
Author-X-Name-Last: Alomoto
Author-Name: Giuseppe Paletta
Author-X-Name-First: Giuseppe
Author-X-Name-Last: Paletta
Author-Name: Eduardo Pérez
Author-X-Name-First: Eduardo
Author-X-Name-Last: Pérez
Title: Scheduling to maximise worker satisfaction and on-time orders
Abstract: 
 Two important managerial objectives incorporated in production planning are the maximisation of the on-time delivery of orders and worker satisfaction. While the maximisation of on-time deliveries has frequently been considered in past production planning research, the component of maximising worker satisfaction has typically been ignored. The assignment of workers to their preferred jobs is an important factor since it results in a productive working environment with high worker performance and a low turnover rate. This study presents a job scheduling model that considers both criteria simultaneously and derives solution approaches to generate non-dominated solutions. The solution approaches are examined under various experimental conditions to evaluate their performance. Finally, a prototype tool developed as a proof of concept is presented.
Journal: International Journal of Production Research
Pages: 2836-2852
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2015.1005764
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1005764
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Template-Type: ReDIF-Article 1.0
Author-Name: Hamed Samarghandi
Author-X-Name-First: Hamed
Author-X-Name-Last: Samarghandi
Title: A particle swarm optimisation for the no-wait flow shop problem with due date constraints
Abstract: 
 This paper considers the no-wait flow shop scheduling problem with due date constraints. In the no-wait flow shop problem, waiting time is not allowed between successive operations of jobs. Moreover, a due date is associated with the completion of each job. The considered objective function is makespan. This problem is proved to be strongly NP-Hard. In this paper, a particle swarm optimisation (PSO) is developed to deal with the problem. Moreover, the effect of some dispatching rules for generating initial solutions are studied. A Taguchi-based design of experience approach has been followed to determine the effect of the different values of the parameters on the performance of the algorithm. To evaluate the performance of the proposed PSO, a large number of benchmark problems are selected from the literature and solved with different due date and penalty settings. Computational results confirm that the proposed PSO is efficient and competitive; the developed framework is able to improve many of the best-known solutions of the test problems available in the literature.
Journal: International Journal of Production Research
Pages: 2853-2870
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2015.1007245
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1007245
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Template-Type: ReDIF-Article 1.0
Author-Name: Hermann Lödding
Author-X-Name-First: Hermann
Author-X-Name-Last: Lödding
Author-Name: Arif Kuyumcu
Author-X-Name-First: Arif
Author-X-Name-Last: Kuyumcu
Title: Modelling schedule reliability
Abstract: 
 The significance of schedule reliability as a particularly important logistic objective is indisputable. In comparison to the objectives WIP, utilisation and throughput time, the modelling of the schedule reliability is, however, not very advanced until now. This paper transfers the process capability indices used in quality management to schedule reliability and demonstrates two methods for depicting the schedule reliability as a function of its influencing parameters.
Journal: International Journal of Production Research
Pages: 2871-2884
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2015.1008703
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1008703
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:9:p:2871-2884




Template-Type: ReDIF-Article 1.0
Author-Name: Mahmoud Masoud
Author-X-Name-First: Mahmoud
Author-X-Name-Last: Masoud
Author-Name: Erhan Kozan
Author-X-Name-First: Erhan
Author-X-Name-Last: Kozan
Author-Name: Geoff Kent
Author-X-Name-First: Geoff
Author-X-Name-Last: Kent
Title: Hybrid metaheuristic techniques for optimising sugarcane rail operations
Abstract: 
 Mixed integer programming and parallel-machine job shop scheduling are used to solve the sugarcane rail transport scheduling problem. Constructive heuristics and metaheuristics were developed to produce a more efficient scheduling system and so reduce operating costs. The solutions were tested on small and large size problems. High-quality solutions and improved CPU time are the result of developing new hybrid techniques which consist of different ways of integrating simulated annealing and Tabu search techniques.
Journal: International Journal of Production Research
Pages: 2569-2589
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.957870
File-URL: http://hdl.handle.net/10.1080/00207543.2014.957870
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Template-Type: ReDIF-Article 1.0
Author-Name: Dvir Shabtay
Author-X-Name-First: Dvir
Author-X-Name-Last: Shabtay
Author-Name: Omri Dover
Author-X-Name-First: Omri
Author-X-Name-Last: Dover
Author-Name: Moshe Kaspi
Author-X-Name-First: Moshe
Author-X-Name-Last: Kaspi
Title: Single-machine two-agent scheduling involving a just-in-time criterion
Abstract: 
 We study a set of single-machine two-agent scheduling problems where the performance measure of the first agent, F1$ F_{1} $, is the weighted number of jobs completed exactly at the due date, i.e. completed in a just-in-time mode. The performance measure of the second agent, F2$ F_{2} $, is either the makespan, the total completion times or the weighted number of jobs completed exactly at the due date. For each combination of performance measures of the two agents, we study four different variations of the problem. We show that all four-problem variations are strongly NP$ \mathcal NP $-hard for when the performance measure of the second agent is either the makespan or the total completion time, even if all of the first agent’s weights are equal. We also study the special case of these problems where the job processing times of the second agent are all equal. For this special case, we prove that three variations of this problem are ordinary NP$ \mathcal NP $-hard with respect to the instance size, while all four problem variations are polynomial solvable with respect to the number of jobs. For the problem where the performance measure of both agents is the weighted number of jobs completed at the due date, we show that one problem variation is solvable in polynomial time, while all other three variations are ordinary NP$ \mathcal NP $-hard.
Journal: International Journal of Production Research
Pages: 2590-2604
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.970706
File-URL: http://hdl.handle.net/10.1080/00207543.2014.970706
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Template-Type: ReDIF-Article 1.0
Author-Name: Jin Young Choi
Author-X-Name-First: Jin Young
Author-X-Name-Last: Choi
Title: Design and comparative performance analysis of a heuristic-based parameterised Banker’s algorithm using the CRL scheduling problems
Abstract: 
 In this paper, we suggest an efficient sub-optimal deadlock avoidance policy (DAP), called a heuristic-based parameterised Banker’s algorithm (H-pBA). It has the main three steps such as (i) for a state s$ s $, explicitly identifying j$ j $-job instances and feasible y$ y $-processing steps for them to be proceeded, (ii) generating a new state s′$ s^{\prime } $ by applying the (j,y)$ (j, y) $-choice to the state s$ s $ and (iii) determining the safety of the state s$ s $ by checking if all the resources required by all the job instances in the state s′$ s^{\prime } $ up to completion are available. The algorithm iteratively applies these steps to a state by changing the values of j$ j $ and y$ y $, up to their upper bounds in the worst case, until it makes a decision about the safety. For performance evaluation, we perform a comparative performance analysis by conducting numerical experiments using a set of prototypical examples for capacitated re-entrant line (CRL) configurations, while comparing with the most common polynomial-kernel DAPs reported in the literature. By suggesting two performance indices representing the operational flexibility and effectiveness, we show that the performance of the suggested H-pBA is consistently superior to that of other PK-DAPs, and furthermore, it is beneficial to integrate it with the first-buffer first-serve policy for system throughput in the CRL.
Journal: International Journal of Production Research
Pages: 2605-2616
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.970710
File-URL: http://hdl.handle.net/10.1080/00207543.2014.970710
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Template-Type: ReDIF-Article 1.0
Author-Name: Jonathan F. Bard
Author-X-Name-First: Jonathan F.
Author-X-Name-Last: Bard
Author-Name: Shihui Jia
Author-X-Name-First: Shihui
Author-X-Name-Last: Jia
Author-Name: Rodolfo Chacon
Author-X-Name-First: Rodolfo
Author-X-Name-Last: Chacon
Author-Name: John Stuber
Author-X-Name-First: John
Author-X-Name-Last: Stuber
Title: Integrating optimisation and simulation approaches for daily scheduling of assembly and test operations
Abstract: 
 The purpose of this paper is to show how the results of an optimisation model that can be integrated with the decisions made within a simulation model to schedule back-end operations in a semiconductor assembly and test facility. The problem is defined by a set of resources that includes machines and tooling, process plans for each product and the following four hierarchical objectives: minimise the weighted sum of key device shortages, maximise weighted throughput, minimise the number of machines used and minimise the makespan for a given set of lots in queue. A mixed integer programming model is purposed and first solved with a greedy randomised adaptive search procedure (GRASP). The results associated with the prescribed facility configuration are then fed to the simulation model written in AutoSched AP. However, due to the inadequacy of the options built into AutoSched, three new rules were created: the first two are designed to capture the machine set-up profiles provided by the GRASP and the third to prioritise the processing of hot lots containing key devices. The computational analysis showed that incorporating the set-up from the GRASP in dynamic operations of the simulation greatly improved its performance with respect to the four objectives.
Journal: International Journal of Production Research
Pages: 2617-2632
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.970713
File-URL: http://hdl.handle.net/10.1080/00207543.2014.970713
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohmmad Hanafy
Author-X-Name-First: Mohmmad
Author-X-Name-Last: Hanafy
Author-Name: Hoda ElMaraghy
Author-X-Name-First: Hoda
Author-X-Name-Last: ElMaraghy
Title: Developing assembly line layout for delayed product differentiation using phylogenetic networks
Abstract: 
 Effective formation of product platforms helps adapt to product demand changes and decrease time-to-market and lead time. The product platform groups the core elements of product family members into a common module used to derive different product variants by combining it with different components. A new delayed product differentiation (DPD) platform network model, which applies median-joining phylogenetic networks (MJPN), is proposed. It is used for forming product platforms and determining the assembly line layout of modular product families. The MJPN is traditionally used for DNA sequences’ mapping, analysis, clustering and tracing evolutionary trends. The concept of assembly/disassembly modular platforms, whereby both assembly and disassembly of components are used to derive the final product variants from the platform, is utilised. The proposed model determines the required number and composition of a product platform and defines the DPD points. The developed dynamic assembly/disassembly platforms enhance routing and product mix flexibility due to having different platforms that can be used to produce the same product variant. A family of household kettles is used to demonstrate the application of the proposed model. A metric is presented for determining the effectiveness of a given platform in delaying the product differentiation, hence increasing the efficiency of mass customisation. The proposed metric, applied to the case study, demonstrated that the proposed platform formation model using MJPN is more capable of postponing the product differentiation point.
Journal: International Journal of Production Research
Pages: 2633-2651
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.974839
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974839
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Template-Type: ReDIF-Article 1.0
Author-Name: Hamed Samarghandi
Author-X-Name-First: Hamed
Author-X-Name-Last: Samarghandi
Title: Studying the effect of server side-constraints on the makespan of the no-wait flow-shop problem with sequence-dependent set-up times
Abstract: 
 This paper deals with the problem of scheduling the no-wait flow-shop system with sequence-dependent set-up times and server side-constraints. No-wait constraints state that there should be no waiting time between consecutive operations of jobs. In addition, sequence-dependent set-up times are considered for each operation. This means that the set-up time of an operation on its respective machine is dependent on the previous operation on the same machine. Moreover, the problem consists of server side-constraints i.e. not all machines have a dedicated server to prepare them for an operation. In other words, several machines share a common server. The considered performance measure is makespan. This problem is proved to be strongly NP-Hard. To deal with the problem, two genetic algorithms are developed. In order to evaluate the performance of the developed frameworks, a large number of benchmark problems are selected and solved with different server limitation scenarios. Computational results confirm that both of the proposed algorithms are efficient and competitive. The developed algorithms are able to improve many of the best-known solutions of the test problems from the literature. Moreover, the effect of the server side-constraints on the makespan of the test problems is explained using the computational results.
Journal: International Journal of Production Research
Pages: 2652-2673
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.974846
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974846
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Template-Type: ReDIF-Article 1.0
Author-Name: Danping Lin
Author-X-Name-First: Danping
Author-X-Name-Last: Lin
Author-Name: Chee Chong Teo
Author-X-Name-First: Chee Chong
Author-X-Name-Last: Teo
Author-Name: Carman Ka Man Lee
Author-X-Name-First: Carman Ka Man
Author-X-Name-Last: Lee
Title: Heuristics for integrated job assignment and scheduling in the multi-plant remanufacturing system
Abstract: 
 We consider a multi-plant remanufacturing system where decisions have to be made on the choice of plant to perform the remanufacturing and the remanufacturing options. Each plant is in different geographical locations and differs in technological capability, labour cost, distance from customers, taxes and duties. There are three options of remanufacture: replacement, repair and recondition. Furthermore, the probability that each remanufacture job needs to be reworked depends on the remanufacturing option selected. We show the interdependencies among the plant selection, remanufacturing option and job scheduling when subject to resource constraints, which motivate the integrated solution proposed in this paper. The solution method is composed of the linear physical programming and the multi-level encoding genetic algorithm (GA). By performing a case study, we illustrate the use of the model and we present the resulting managerial insights. The results show that the proposed integrated approach performs better compared with the regular GA in terms of makespan.
Journal: International Journal of Production Research
Pages: 2674-2689
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.975851
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975851
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:9:p:2674-2689




Template-Type: ReDIF-Article 1.0
Author-Name: Shahla Paslar
Author-X-Name-First: Shahla
Author-X-Name-Last: Paslar
Author-Name: M.K.A. Ariffin
Author-X-Name-First: M.K.A.
Author-X-Name-Last: Ariffin
Author-Name: Mehran Tamjidy
Author-X-Name-First: Mehran
Author-X-Name-Last: Tamjidy
Author-Name: Tang Sai Hong
Author-X-Name-First: Tang Sai
Author-X-Name-Last: Hong
Title: Biogeography-based optimisation for flexible manufacturing system scheduling problem
Abstract: 
 Biogeography-based optimisation (BBO) algorithm is a new evolutionary optimisation algorithm based on geographic distribution of biological organisms. With probabilistic operators, this algorithm is able to share more information from good solutions to poor ones. BBO prevents the good solutions to be demolished during the evolution. This feature leads to find the better solutions in a short time rather than other metaheuristics. This paper provides a mathematical model which integrates machine loading, part routing, sequencing and scheduling decision in flexible manufacturing systems (FMS). Moreover, it tackles the scheduling problem when various constraints are imposed on the system. Since this problem is considered to be NP-hard, BBO algorithm is developed to find the optimum /near optimum solution based on various constraints. In the proposed algorithm, different types of mutation operators are employed to enhance the diversity among the population. The proposed BBO has been applied to the instances with different size and degrees of complexity of problem adopted from the FMS literature. The experimental results demonstrate the effectiveness of the proposed algorithm to find optimum /near optimum solutions within reasonable time. Therefore, BBO algorithm can be used as a useful solution for optimisation in various industrial applications within a reasonable computation time.
Journal: International Journal of Production Research
Pages: 2690-2706
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.975855
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975855
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:9:p:2690-2706




Template-Type: ReDIF-Article 1.0
Author-Name: Xuesong Li
Author-X-Name-First: Xuesong
Author-X-Name-Last: Li
Author-Name: Hiroaki Ishii
Author-X-Name-First: Hiroaki
Author-X-Name-Last: Ishii
Author-Name: Minghao Chen
Author-X-Name-First: Minghao
Author-X-Name-Last: Chen
Title: Single machine parallel-batching scheduling problem with fuzzy due-date and fuzzy precedence relation
Abstract: 
 A problem of single machine parallel-batching problem with fuzzy due-date and fuzzy precedence relation is investigated. Each job has a positive processing time. Set-up times are assumed to be identical for all batches. All batch sizes cannot exceed a common upper bound. The length of a batch is equal to the largest processing time among all jobs in the batch. Fuzzy due-date denotes the degree of satisfaction with respect to completion times of jobs. Fuzzy precedence constraint expresses the satisfaction level about precedence between two jobs. The objective is to minimise maximum completion time, maximise the minimum value of desirability of the fuzzy due-date and the minimum value of desirability of the fuzzy precedence. First, we propose a fuzzy due-date and ordinary precedence model, which maximises the minimum satisfaction degree of fuzzy due-date. An efficient iterative algorithm based on Procedure HL is designed. On that basis, another efficient algorithm to seek non-dominated solution is presented for the main problem in this paper. The non-dominated solution is defined to be consists of batch size, batch number and allocation of jobs to batches. The whole solution procedure needs at most O(n4logn)$ O({n^4}\log n) $ computational time. Finally, we illustrate the procedure with a numerical example.
Journal: International Journal of Production Research
Pages: 2707-2717
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.975866
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975866
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:9:p:2707-2717




Template-Type: ReDIF-Article 1.0
Author-Name: Jia Shu
Author-X-Name-First: Jia
Author-X-Name-Last: Shu
Author-Name: Ting Wu
Author-X-Name-First: Ting
Author-X-Name-Last: Wu
Author-Name: Kaike Zhang
Author-X-Name-First: Kaike
Author-X-Name-Last: Zhang
Title: Warehouse location and two-echelon inventory management with concave operating cost
Abstract: 
 In this paper, we study a location–inventory network design problem which jointly optimises the warehouse location, the warehouse–retailer assignments, the warehouse–retailer echelon inventory replenishment and the safety stock-level decisions over an infinite planning horizon. The consideration of the facility operating cost, the safety stock cost and the two-echelon inventory cost results in an MIP model with several nonlinear terms. Due to the complex trade-offs among the various costs and multiple nonlinear terms in the model, traditional solution approaches no longer work for this problem. We outline a polymatroid cutting-plane approach based on the submodular property of the cost terms to address this problem. Computational results demonstrate that the cutting-plane method based on polymatroid inequalities can efficiently solve randomly generated instances with moderate sizes.
Journal: International Journal of Production Research
Pages: 2718-2729
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.977456
File-URL: http://hdl.handle.net/10.1080/00207543.2014.977456
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:9:p:2718-2729




Template-Type: ReDIF-Article 1.0
Author-Name: Youkyung Won
Author-X-Name-First: Youkyung
Author-X-Name-Last: Won
Author-Name: Rasaratnam Logendran
Author-X-Name-First: Rasaratnam
Author-X-Name-Last: Logendran
Title: Effective two-phase p-median approach for the balanced cell formation in the design of cellular manufacturing system
Abstract: 
 In this paper, we present an effective two-phase p-median approach for the balanced cell formation (CF) in the design of cellular manufacturing system. In phase 1, the p-median mathematical model of machine CF, which adopts a linear integer programming formulation, is developed. Our formulation uses a new similarity coefficient based on the generalised nonbinary part-machine incidence matrix (PMIM) which incorporates realistic manufacturing aspects such as setup time, processing time, operation sequences and lot size of parts and duplicate machine types. In phase 2, a systematic part assignment procedure based on the new classification scheme of part types is established in pursuit of balancing the workload among machine cells. New efficiency measures for evaluating the quality of the binary and nonbinary PMIM-based block diagonal solutions are proposed to judge the degree of cell load imbalance. Computational experiments with moderately intermediate-sized data-sets selected from the literature show effectiveness of our two-phase p-median approach for the balanced CF.
Journal: International Journal of Production Research
Pages: 2730-2750
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.977457
File-URL: http://hdl.handle.net/10.1080/00207543.2014.977457
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Template-Type: ReDIF-Article 1.0
Author-Name: S. Gürel
Author-X-Name-First: S.
Author-X-Name-Last: Gürel
Author-Name: D. Cincioğlu
Author-X-Name-First: D.
Author-X-Name-Last: Cincioğlu
Title: Rescheduling with controllable processing times for number of disrupted jobs and manufacturing cost objectives
Abstract: 
 We consider a machine rescheduling problem that arises when a disruption such as machine breakdown occurs to a given schedule. Machine unavailability due to a breakdown requires repairing the schedule as the original schedule becomes infeasible. When repairing a disrupted schedule a desirable goal is to complete each disrupted job on time, i.e. not later than the planned completion time in the original schedule. We consider the case where processing times of jobs are controllable and compressing the processing time of a job requires extra processing cost. Usually, there exists a nonlinear relation between the processing time and manufacturing cost. We solve a bicriteria rescheduling problem that trades off the number of on-time jobs and manufacturing cost objectives. We give a mixed-integer second-order cone programming formulation for the problem. We develop a heuristic search algorithm to generate efficient solutions for the problem. Heuristic algorithm searches solution space by moving and swapping jobs among machines. We develop cost change estimates for job moves and swaps so that the heuristic implements only promising moves and hence generates a set of efficient solutions in reasonably short CPU times.
Journal: International Journal of Production Research
Pages: 2751-2770
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.980452
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980452
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:9:p:2751-2770




Template-Type: ReDIF-Article 1.0
Author-Name: Pieter Leyman
Author-X-Name-First: Pieter
Author-X-Name-Last: Leyman
Author-Name: Mario Vanhoucke
Author-X-Name-First: Mario
Author-X-Name-Last: Vanhoucke
Title: A new scheduling technique for the resource–constrained project scheduling problem with discounted cash flows
Abstract: 
 In this paper, we discuss the resource–constrained project scheduling problem with discounted cash flows. We introduce a new schedule construction technique which moves sets of activities to improve the project net present value and consists of two steps. In particular, the inclusion of individual activities into sets, which are then moved together, is crucial in both steps. The first step groups the activities based on the predecessors and successors in the project network, and adds these activities to a set based on their finish time and cash flow. The second step on the contrary does so based on the neighbouring activities in the schedule, which may but need not include precedence related activities. The proposed scheduling method is implemented in a genetic algorithm metaheuristic and we employ a penalty function to improve the algorithm’s feasibility with respect to a tight deadline. All steps of the proposed solution methodology are tested in detail and an extensive computational experiment shows that our results are competitive with existing work.
Journal: International Journal of Production Research
Pages: 2771-2786
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.980463
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980463
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:9:p:2771-2786




Template-Type: ReDIF-Article 1.0
Author-Name: Jian Chen
Author-X-Name-First: Jian
Author-X-Name-Last: Chen
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Author-Name: Hao Luo
Author-X-Name-First: Hao
Author-X-Name-Last: Luo
Author-Name: Junqiang Wang
Author-X-Name-First: Junqiang
Author-X-Name-Last: Wang
Title: Synchronisation of production scheduling and shipment in an assembly flowshop
Abstract: 
 This paper studies a synchronised scheduling problem of production simultaneity and shipment punctuality in a two-stage assembly flowshop system. Production simultaneity seeks to ensure all products belonging to a same customer order are simultaneously completed (at least as close as possible). Shipment punctuality attempts to satisfy orders’ individual shipment due dates. We provide two criteria, i.e. mean longest waiting duration and mean earliness and tardiness, for measuring production simultaneity and shipment punctuality, respectively. A synchronised scheduling model is developed by balancing the two criteria using linear weighted sum method. A modified genetic algorithm (GA) is then proposed for solving this model. Numerical studies demonstrate the effectiveness of the proposed approach. The results indicate that considering production simultaneity can remarkably reduce finished products inventory. A prioritised weight combination interval for production simultaneity and shipment punctuality has been suggested. Production simultaneity is affected by the production system configuration, especially in peak seasons.
Journal: International Journal of Production Research
Pages: 2787-2802
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.994075
File-URL: http://hdl.handle.net/10.1080/00207543.2014.994075
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Template-Type: ReDIF-Article 1.0
Author-Name: Asiye Aydilek
Author-X-Name-First: Asiye
Author-X-Name-Last: Aydilek
Author-Name: Harun Aydilek
Author-X-Name-First: Harun
Author-X-Name-Last: Aydilek
Author-Name: Ali Allahverdi
Author-X-Name-First: Ali
Author-X-Name-Last: Allahverdi
Title: Production in a two-machine flowshop scheduling environment with uncertain processing and setup times to minimize makespan
Abstract: 
 A wide range of uncertainties exists in some real-world production environments which result in uncertain setup and/or processing times. Factors such as crew skills, shortages in equipment and resource breakdowns can be the sources of these uncertainties. This study considers a two-machine production flowshop scheduling problem where both setup and processing times are treated as uncertain variables. The objective is to minimise makespan which is an effective way of resource utilisation. There exists a dominance relation in the literature for the two-machine flowshop scheduling problem with uncertain setup and processing times. However, the dominance relation has not been evaluated. In this study, we evaluate the existing dominance relation. Moreover, a new dominance relation is established and shown to be more effective than the existing one. Furthermore, twenty-five implementations of a polynomial time algorithm are developed. Extensive computational experiments are conducted to evaluate the performance of the implementations of the algorithm. The computational experiments indicate that the overall gap (error) of the best implementation of the algorithm is less than 0.3% when compared to the optimal solution. Moreover, the performance of this implementation of the algorithm is the best one when compared to the remaining implementations for all the considered experimental environments. Additionally, the performance of this implementation of the algorithm is shown to be insensitive to the uncertainty in setup times.
Journal: International Journal of Production Research
Pages: 2803-2819
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.997403
File-URL: http://hdl.handle.net/10.1080/00207543.2014.997403
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Template-Type: ReDIF-Article 1.0
Author-Name: Byung Jun Joo
Author-X-Name-First: Byung Jun
Author-X-Name-Last: Joo
Author-Name: Paul Xirouchakis
Author-X-Name-First: Paul
Author-X-Name-Last: Xirouchakis
Title: A production scheduling problem with uncertain sequence-dependent set-up times and random yield
Abstract: 
 A scheduling problem in a real production line with uncertain sequence-dependent set-up times and a random yield is considered. The production line can produce multiple product types as production lots, each of which is composed of a number of products of the same product type. To changeover product types, a sequence-dependent set-up operation should be performed, and only the lower and upper bounds are known for the sequence-dependent set-up times. Moreover, the processing time to produce the required number of product for each production lot is uncertain due to the random yield. For the objective of minimising the average tardy probability of given production lots, a systematic approximation scheme to estimate tardy probabilities of lots in any given production sequence is developed by taking not only the uncertainties but also the computational efficiency into account. As practical solution approaches, a simulated annealing and a discrete particle swarm optimisation algorithms using the approximation scheme are developed, and their performance are evaluated by computational experiments. Since there has been no research on the scheduling problems with uncertain sequence-dependent set-up times and random yield, the authors expect this research will make an excellent contribution to develop practical scheduling methodologies in uncertain scheduling environments.
Journal: International Journal of Production Research
Pages: 2820-2835
Issue: 9
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.998790
File-URL: http://hdl.handle.net/10.1080/00207543.2014.998790
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:9:p:2820-2835




Template-Type: ReDIF-Article 1.0
Author-Name: Yaolei Wang
Author-X-Name-First: Yaolei
Author-X-Name-Last: Wang
Author-Name: Yiming Fan
Author-X-Name-First: Yiming
Author-X-Name-Last: Fan
Author-Name: Taozeng Zhu
Author-X-Name-First: Taozeng
Author-X-Name-Last: Zhu
Author-Name: Ping Cao
Author-X-Name-First: Ping
Author-X-Name-Last: Cao
Author-Name: Jingui Xie
Author-X-Name-First: Jingui
Author-X-Name-Last: Xie
Title: An approximation method for 2-chain flexible queues with preemptive priority
Abstract: 
 Chaining configurations (e.g. 2-chain) have been widely applied in service systems to improve responsiveness to customer demand. In this paper, we propose an approximation method for the analysis of symmetric parallel queueing systems with 2-chain configuration and preemptive priority. In the queueing system of interest, the arrival processes of different types of customers follow independent Poisson processes with identical arrival rate λ, and service times of different types of customers are exponentially distributed with identical service rate μ. Each server serves its primary customers with preemptive priority. When there are no primary customers in the system, the server serves secondary customers. We first derive the system stability condition. Then, we analyse the system's various performance measures. Our approach relies on the matrix-analytic method coupled with the idle probability of each server, which is proved to be  $ 1-\lambda /\mu $ 1−λ/μ. The average queue length of each queue and the rate that each server serves its secondary customers (i.e. the helping rate) can be estimated using our proposed method. Finally, we conduct numerical studies to demonstrate the accuracy of our proposed approximation method.
Journal: International Journal of Production Research
Pages: 5935-5950
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1556410
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1556410
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Rezaei-Malek
Author-X-Name-First: Mohammad
Author-X-Name-Last: Rezaei-Malek
Author-Name: Ali Siadat
Author-X-Name-First: Ali
Author-X-Name-Last: Siadat
Author-Name: Jean-Yves Dantan
Author-X-Name-First: Jean-Yves
Author-X-Name-Last: Dantan
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: A trade-off between productivity and cost for the integrated part quality inspection and preventive maintenance planning under uncertainty
Abstract: 
 This paper proposes a robust possibilistic and multi-objective mixed-integer linear programming mathematical model to concurrently plan part quality inspection and Preventive Maintenance (PM) activities for a serial multi-stage production system. This system contains the deteriorating stages and faces the uncertainty about estimated cost components and demand amount. The integrated model reaches two significant decisions which are the right time and place for performing the part quality inspection and PM. These decisions are made while the model is to simultaneously optimise the implied system productivity and total cost. To measure the implied system productivity, a new piecewise utility function for the ratio of produced conforming products to input workpieces is developed. A real case study and a numerical example are explored to validate and verify the developed model. The results prove the significance and effectiveness of considering the uncertainty and conflicting practical objectives for the problem.
Journal: International Journal of Production Research
Pages: 5951-5973
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1556411
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1556411
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Lijie An
Author-X-Name-First: Lijie
Author-X-Name-Last: An
Author-Name: Jiantong Zhang
Author-X-Name-First: Jiantong
Author-X-Name-Last: Zhang
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Energy-oriented bi-objective optimisation for a multi-module reconfigurable manufacturing system
Abstract: 
 This paper investigates a multi-module reconfigurable manufacturing system for multi-product manufacturing. The system consists of a rotary table and multiple machining modules (turrets and spindles). The production plan of the system is divided into the system design phase and the manufacturing phase, where the installation cost and the energy consumption cost correspond to the two phases, respectively. A mixed-integer programming model for a more general problem is presented. The objectives are to minimise the total cost and minimise the cycle time simultaneously. To solve the optimisation problem, the ε-constraint method is adopted to obtain the Pareto front for small size problems. Since the ε-constraint method is time consuming when problem size increases, we develop a multi-objective simulated annealing algorithm for practical size problems. To demonstrate the efficiency of the proposed algorithm, we compare it with a classic non-dominated sorting genetic algorithm. Experimental results demonstrate the efficiency of the multi-objective simulated annealing algorithm in terms of solution quality and computation time.
Journal: International Journal of Production Research
Pages: 5974-5995
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1556413
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1556413
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Template-Type: ReDIF-Article 1.0
Author-Name: Weihao Wang
Author-X-Name-First: Weihao
Author-X-Name-Last: Wang
Author-Name: Zhongshun Shi
Author-X-Name-First: Zhongshun
Author-X-Name-Last: Shi
Author-Name: Leyuan Shi
Author-X-Name-First: Leyuan
Author-X-Name-Last: Shi
Author-Name: Qingbin Zhao
Author-X-Name-First: Qingbin
Author-X-Name-Last: Zhao
Title: Integrated optimisation on flow-shop production with cutting stock
Abstract: 
 This paper addresses the integrated scheduling optimisation on flow-shop production with one-dimensional cutting stock in make-to-order environments. The upstream cutting-stock process provides the items for the downstream production, while the flow-shop production can be executed only when the required items are released. The efficient schedules on cutting plan and the production sequence should be determined in a coordinated manner to improve the overall efficiency. This study aims to find an integrated schedule to minimise the makespan of the entire manufacturing process. We develop a hybrid algorithm by integrating a local search method and some efficient strategies under the nested partitions framework. Numerical experiments show that the proposed approach is capable of achieving high-quality solutions within a reasonable time.
Journal: International Journal of Production Research
Pages: 5996-6012
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1556823
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1556823
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Template-Type: ReDIF-Article 1.0
Author-Name: Karthick Gopalswamy
Author-X-Name-First: Karthick
Author-X-Name-Last: Gopalswamy
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Title: A data-driven iterative refinement approach for estimating clearing functions from simulation models of production systems
Abstract: 
 Clearing functions that describe the expected output of a production resource as a function of its expected workload have yielded promising production planning models. However, there is as yet no fully satisfactory approach to estimating clearing functions from data. We identify several issues that arise in estimating clearing functions such as sampling issues, systematic underestimation and model misspecification. We address the model misspecification problem by introducing a generalised functional form, and the sampling issues via iterative refinement of initial parameter estimates. The iterative refinement approach yields improved performance for planning models at higher levels of utilisation, and the generalised functional form results in significantly better production plans both alone and when combined with the iterative refinement approach. The IR approach also obtains solutions of similar quality to the much more computationally demanding simulation optimisation approaches used in previous work.
Journal: International Journal of Production Research
Pages: 6013-6030
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1557351
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1557351
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Template-Type: ReDIF-Article 1.0
Author-Name: Hengyu Liu
Author-X-Name-First: Hengyu
Author-X-Name-Last: Liu
Author-Name: Juliang Zhang
Author-X-Name-First: Juliang
Author-X-Name-Last: Zhang
Author-Name: Chen Zhou
Author-X-Name-First: Chen
Author-X-Name-Last: Zhou
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Author-Name: Yihong Ru
Author-X-Name-First: Yihong
Author-X-Name-Last: Ru
Title: Optimal purchase and selling strategy for wholesaler of produce: sorted or unsorted selling?
Abstract: 
 Produce (e.g. fruit and vegetable) varies in quality when it is picked from plants. Then a produce wholesaler has two sales strategies: (1) unsorted selling (US), i.e. selling the produce to the market at one price and (2) sorted selling (SS), i.e. pre-sorting the produce into different grades by quality and selling them at different prices. When the SS strategy is adopted, the demands of the different grades are uncertain and substitutable. In this paper, we study the joint optimal purchase and sales strategy for selling mixed quality produce to customers with heterogeneous quality preferences. We first derive the optimal purchase policies under the two strategies and then identify the conditions under which the SS or US strategy is optimal. We show that the optimal sales strategy is determined by the marginal purchase and sorting cost and the fixed investment cost, the overall quality level of the produce, and the substitution rate for the high-quality and low-quality produce. This finding differs from the conventional wisdom that the SS strategy is optimal in the produce retail business. Finally, we conduct numerical studies based on real-world data to generate managerial insights from the analytical findings.
Journal: International Journal of Production Research
Pages: 6031-6047
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1558296
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1558296
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Template-Type: ReDIF-Article 1.0
Author-Name: Hossein Tohidi
Author-X-Name-First: Hossein
Author-X-Name-Last: Tohidi
Author-Name: Tarek AlGeddawy
Author-X-Name-First: Tarek
Author-X-Name-Last: AlGeddawy
Title: Change management in modular assembly systems to correspond to product geometry change
Abstract: 
 Modular assembly systems are a category of changeable manufacturing systems, which can handle the rapid change in customer demands, product design change and market fluctuations. On the operational level, jigs and fixtures are fundamental elements of assembly systems. They are used to hold parts and subassemblies in place, and directly affect assembly cost, quality and time. Therefore, modular fixtures that can adapt to different geometries are becoming a very important enabler for changeable manufacturing. In this paper, two mathematical models are presented to optimise the use of a passive modular assembly fixture plan in an automated assembly system by considering different production scenarios and constraints. These models optimise the changeability plan of the modular fixture by minimising the number of dowel replacements between different part geometries assuming that the candidate dowels locations for each part have been determined using existing methods in the literature by considering different assembly requirements. The first model, LRTE, considers all possible part rotations and translations on the fixture to minimise setup time. In addition, the second model, SLRTE, enables the system to simultaneously optimise job sequence. This paper presents various examples in different sizes, and the results show that the model can effectively reduce the fixture setup time up to %50.
Journal: International Journal of Production Research
Pages: 6048-6060
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1559374
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1559374
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Template-Type: ReDIF-Article 1.0
Author-Name: Xinfeng Lai
Author-X-Name-First: Xinfeng
Author-X-Name-Last: Lai
Author-Name: Zhixiang Chen
Author-X-Name-First: Zhixiang
Author-X-Name-Last: Chen
Author-Name: Bopaya Bidanda
Author-X-Name-First: Bopaya
Author-X-Name-Last: Bidanda
Title: Optimal decision of an economic production quantity model for imperfect manufacturing under hybrid maintenance policy with shortages and partial backlogging
Abstract: 
 Considering the characteristics of the stochastic shift of the machine state and the uncertainty of the product quality of production, in this paper, we develop an optimisation decision of economic production quantity model for an imperfect manufacturing system under hybrid maintenance policy with shortages and partial backlogging. We assume that the production process is imperfect stemming from the machine reliability and the probability of out-of-control, a hybrid maintenance policy combined of emergency maintenance and preventive maintenance is executed during each production run. Three decision models based on the scenarios of machine breakdown and repair time are developed. The optimal production quantity and maintenance inspection number during each production run are solved with minimising the expected average cost of the system. Numerical examples are used to demonstrate the effectiveness and feasibility of the model. Sensitivity analysis is conducted to analyse the impacts of key parameters on the optimal decision. Some implications related to the effective and economical execution of maintenance policy for practitioners are derived.
Journal: International Journal of Production Research
Pages: 6061-6085
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1562249
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1562249
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Template-Type: ReDIF-Article 1.0
Author-Name: Akhilesh Kumar
Author-X-Name-First: Akhilesh
Author-X-Name-Last: Kumar
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Nagendra R Velaga
Author-X-Name-First: Nagendra R
Author-X-Name-Last: Velaga
Author-Name: Alok Choudhary
Author-X-Name-First: Alok
Author-X-Name-Last: Choudhary
Author-Name: Ravi Shankar
Author-X-Name-First: Ravi
Author-X-Name-Last: Shankar
Title: Modelling and analysis of sustainable freight transportation
Journal: International Journal of Production Research
Pages: 6086-6089
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1642689
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1642689
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Template-Type: ReDIF-Article 1.0
Author-Name: K. Nageswara Reddy
Author-X-Name-First: K. Nageswara
Author-X-Name-Last: Reddy
Author-Name: Akhilesh Kumar
Author-X-Name-First: Akhilesh
Author-X-Name-Last: Kumar
Author-Name: Erica E. F. Ballantyne
Author-X-Name-First: Erica E. F.
Author-X-Name-Last: Ballantyne
Title: A three-phase heuristic approach for reverse logistics network design incorporating carbon footprint
Abstract: 
 Reverse logistics (RL) is emerging as a significant area of activity for business and industry, motivated by both commercial profitability and wider environmental sustainability factors. However, planning and implementing an appropriate RL network within existing supply chains for product recovery that increases customer satisfaction, decreases overall costs, and provides a competitive advantage over other companies is complex. In the current study, we developed a mixed integer linear programming (MILP) model for a reverse logistics network design (RLND) in a multi-period setting. The RL network consists of collection centres, capacitated inspection and remanufacturing centres and customer zones to serve. Moreover, the model incorporates significant characteristics such as vehicle type selection and carbon emissions (through transportation and operations). Since the network design problems are NP-hard, we first propose a solution approach based on Benders decomposition (BD). Then, based on the structure of the problem we propose a three-phase heuristic approach. Finally, to establish the performance and robustness of the proposed solution approach, the results are compared with benchmark results obtained using CPLEX in terms of both solution quality and computational time. From the computational results, we validated that the three-phase heuristic approach performs superior to the BD and Branch &Cut approach.
Journal: International Journal of Production Research
Pages: 6090-6114
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1526422
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1526422
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Template-Type: ReDIF-Article 1.0
Author-Name: Lan Zhu
Author-X-Name-First: Lan
Author-X-Name-Last: Zhu
Author-Name: Dawei Hu
Author-X-Name-First: Dawei
Author-X-Name-Last: Hu
Title: Study on the vehicle routing problem considering congestion and emission factors
Abstract: 
 To meet the requirement of greening transportation in poor traffic condition, vehicle routing problem (VRP) with consideration of fuel consumption and congestion is studied. We formulated a time-dependent green vehicle routing problem (TD-GVRP) model with minimised total cost as the objective function which includes fuel consumption cost, and the measurement of fuel consumption is based on the Comprehensive Modal Emissions Model (CMEM). In the model, the situation of waiting at customer nodes to avoid bad traffic is defined. To solve this model, a Response Surface Method (RSM)-based hybrid algorithm (HA) that combines genetic algorithm (GA) and particle swarm optimisation (PSO) is constructed. Finally, using instances from PRPLIB database, the following experiments are carried out and the corresponding conclusions are drawn. (i) Comparison of the proposed objective and traditional VRP objectives shows that fuel consumption can be greatly reduced by introducing fuel consumption factor into the objective function. (ii) Sensitivity analysis of congestion duration provides the influence of congestion duration on fuel consumption and travel time. (iii) Experiments based on different waiting time reveal that the optimisation of departure time can reduce fuel consumption and total cost to some extent.
Journal: International Journal of Production Research
Pages: 6115-6129
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2018.1533260
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1533260
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhengyang Hu
Author-X-Name-First: Zhengyang
Author-X-Name-Last: Hu
Author-Name: Ronald G. Askin
Author-X-Name-First: Ronald G.
Author-X-Name-Last: Askin
Author-Name: Guiping Hu
Author-X-Name-First: Guiping
Author-X-Name-Last: Hu
Title: Hub relay network design for daily driver routes
Abstract: 
 Hub-based relay networks for long haul trucking offer an opportunity to improve the work–life balance of drivers while simultaneously supporting faster delivery through near-continuous flow of containers from source to destination. In this paper, we develop a model for deciding hub location and sizing along with the routing of loads. Costs of hub construction and operation, transportation and penalties for multi-day driver trips are included. Both deterministic and two-stage stochastic programming models have been formulated in this paper. The goal is to determine the optimal hub and route decisions so that overall cost is minimised. A case study on the highway network for the Western United States demonstrates the computational tractability of the approach along with the importance of considering demand uncertainty.
Journal: International Journal of Production Research
Pages: 6130-6145
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1571253
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1571253
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Template-Type: ReDIF-Article 1.0
Author-Name: Hamdi Giray Resat
Author-X-Name-First: Hamdi Giray
Author-X-Name-Last: Resat
Author-Name: Metin Turkay
Author-X-Name-First: Metin
Author-X-Name-Last: Turkay
Title: A bi-objective model for design and analysis of sustainable intermodal transportation systems: a case study of Turkey
Abstract: 
 This paper presents a mixed-integer linear optimisation model to analyse the intermodal transportation systems in the Turkish transportation industry. The solution approach includes mathematical modelling, data analysis from real-life cases and solving the resulting mathematical programming problem to minimise total transportation cost and carbon dioxide emissions by using two different exact solution methods in order to find the optimal solutions. The novel approach of this paper generates Pareto solutions quickly and allows the decision makers to identify sustainable solutions by using a newly developed solution methodology for bi-objective mixed-integer linear problems in real-life cases.
Journal: International Journal of Production Research
Pages: 6146-6161
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1587187
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1587187
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Template-Type: ReDIF-Article 1.0
Author-Name: Emrah Demir
Author-X-Name-First: Emrah
Author-X-Name-Last: Demir
Author-Name: Martin Hrušovský
Author-X-Name-First: Martin
Author-X-Name-Last: Hrušovský
Author-Name: Werner Jammernegg
Author-X-Name-First: Werner
Author-X-Name-Last: Jammernegg
Author-Name: Tom Van Woensel
Author-X-Name-First: Tom
Author-X-Name-Last: Van Woensel
Title: Green intermodal freight transportation: bi-objective modelling and analysis
Abstract: 
 Efficient planning of freight transportation requires a comprehensive look at wide range of factors in the operation and management of any transportation mode to achieve safe, fast, and environmentally suitable movement of goods. In this regard, a combination of transportation modes offers flexible and environmentally friendly alternatives to transport high volumes of goods over long distances. In order to reflect the advantages of each transportation mode, it is the challenge to develop models and algorithms in Transport Management System software packages. This paper discusses the principles of green logistics required in designing such models and algorithms which truly represent multiple modes and their characteristics. Thus, this research provides a unique practical contribution to green logistics literature by advancing our understanding of the multi-objective planning in intermodal freight transportation. Analysis based on a case study from hinterland intermodal transportation in Europe is therefore intended to make contributions to the literature about the potential benefits from combining economic and environmental criteria in transportation planning. An insight derived from the experiments conducted shows that there is no need to greatly compromise on transportation costs in order to achieve a significant reduction in carbon-related emissions.
Journal: International Journal of Production Research
Pages: 6162-6180
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1620363
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1620363
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Template-Type: ReDIF-Article 1.0
Author-Name: Mithu Rani Kuiti
Author-X-Name-First: Mithu Rani
Author-X-Name-Last: Kuiti
Author-Name: Debabrata Ghosh
Author-X-Name-First: Debabrata
Author-X-Name-Last: Ghosh
Author-Name: Sirish Gouda
Author-X-Name-First: Sirish
Author-X-Name-Last: Gouda
Author-Name: Sanjeev Swami
Author-X-Name-First: Sanjeev
Author-X-Name-Last: Swami
Author-Name: Ravi Shankar
Author-X-Name-First: Ravi
Author-X-Name-Last: Shankar
Title: Integrated product design, shelf-space allocation and transportation decisions in green supply chains
Abstract: 
 In this paper, we examine a supply chain consisting of a manufacturer and retailer where the manufacturer undertakes greening efforts in terms of pack-size reduction and transportation cost reduction. The retailer decides on shelf-space allocation for the product. Both the players benefit from the greening efforts of the manufacturer. In such a setting, we examine strategic decisions of the players and compare and contrast the performance of the decentralised supply chain with the centralised supply chain. We also examine the effect of collaborative mechanisms by modelling two contracts in which the retailer offers a transportation cost reduction effort based contract and a two-part tariff contract. We find that the decentralised supply chain leads to lower greening efforts and shelf-space allocation decisions. We also find that the contracts improve pack-size reduction effort, transportation cost reduction effort and shelf-space allocation, while also improving the profitability of individual players. The findings demonstrate a scope for supply chain collaboration between manufacturer–retailer pairs in this setting. The paper uniquely combines three critical elements in supply chains, namely, product design, transportation and retailing decisions, and aims to provide insights into the decision making of players considering environmental waste and pollution. The paper also reflects consumer behavior and trade-offs that the supply chain players face.
Journal: International Journal of Production Research
Pages: 6181-6201
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1597292
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1597292
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Template-Type: ReDIF-Article 1.0
Author-Name: Devendra Kumar Pathak
Author-X-Name-First: Devendra Kumar
Author-X-Name-Last: Pathak
Author-Name: Lakshman S. Thakur
Author-X-Name-First: Lakshman S.
Author-X-Name-Last: Thakur
Author-Name: Shams Rahman
Author-X-Name-First: Shams
Author-X-Name-Last: Rahman
Title: Performance evaluation framework for sustainable freight transportation systems
Abstract: 
 Sustainability in freight transportation demands for a balance among economic, environmental, and social aspects in shipping commodities throughout a supply chain. The performance evaluation of sustainable freight transportation (SFT) systems is of prime importance as it facilitates perpetual and objective assessment for advancements towards sustainability targets. In this study, we propose a comprehensive framework to assess the sustainability performance of freight transportation systems. We pinpoint critical success factors (CSFs) affecting the performance of SFT by carrying out an extensive literature review and conducting a Delphi study to seek experts’ opinions from industry as well as academia. Further, a comprehensive hierarchical framework is developed to establish inter-relationships among these CSFs followed by prioritisation of these CSFs. The application of the proposed framework is illustrated through a case example. This framework would also serve as a reference for decision-makers in selecting the most sustainable freight transportation system.
Journal: International Journal of Production Research
Pages: 6202-6222
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1602741
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1602741
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Template-Type: ReDIF-Article 1.0
Author-Name: Krishna Kumar Dadsena
Author-X-Name-First: Krishna
Author-X-Name-Last: Kumar Dadsena
Author-Name: S. P. Sarmah
Author-X-Name-First: S. P.
Author-X-Name-Last: Sarmah
Author-Name: V. N. A. Naikan
Author-X-Name-First: V. N. A.
Author-X-Name-Last: Naikan
Title: Risk evaluation and mitigation of sustainable road freight transport operation: a case of trucking industry
Abstract: 
 Road freight transportation sustainability is gaining increasing importance due to an ever-increasing freight movement, globalisation and operational flexibility. The transport managers across the globe are finding it difficult to manage the increasing risks in its operation and implementation of risk-mitigation strategies under economical sustainability. However, very few literatures have examined the impact of sustainable risk management practices on road freight transportation. Our study addresses this important gap in the literature by proposing an integrated fuzzy failure mode and effects analysis (FMEA) approach in the selection of risk-mitigation strategy on the trucking industry. Our findings direct to the managers that risk-mitigation strategies must be selected considering the criticality of risks along with the limited budget. In addition, we find that considering subjective evaluations of expert’s judgment and cost benefit justification gives a convincing outcome while calculating of risk-mitigation number in FMEA approach. Proposed approach provides supportive guidelines to the manager to improve the decision-making process.
Journal: International Journal of Production Research
Pages: 6223-6245
Issue: 19
Volume: 57
Year: 2019
Month: 10
X-DOI: 10.1080/00207543.2019.1578429
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1578429
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Template-Type: ReDIF-Article 1.0
Author-Name: Shouyu Ma
Author-X-Name-First: Shouyu
Author-X-Name-Last: Ma
Author-Name: Zied Jemai
Author-X-Name-First: Zied
Author-X-Name-Last: Jemai
Author-Name: Evren Sahin
Author-X-Name-First: Evren
Author-X-Name-Last: Sahin
Author-Name: Yves Dallery
Author-X-Name-First: Yves
Author-X-Name-Last: Dallery
Title: The news-vendor problem with drop-shipping and resalable returns
Abstract: 
 As e-commerce expands, more and more products are offered online to attract internet consumers’ interest. These products are then shipped to consumers’ home by a drop-shipper. Drop-shipping seems to be a good option to sell products in addition to physical stores. Furthermore, both types of products, either sold in store or on Internet can be returned by consumers, with often a higher return ratio for those purchased on Internet. To model these two sales channel and the interactions between them, we consider a News-Vendor (NV) managing both a physical store and an online sale channel that can be fulfilled by a drop-shipping option. We also consider the possibility of reselling products that are returned by consumers during the selling season. The concavity of the expected profit is proven and the optimality condition is obtained. Promising results are obtained from a numerical analysis. In particular, we show that the expected profit can be 14.4% less than the optimal expected profit if the return effect is ignored. Using drop-shipping option can reduce the optimal store inventory by 31.2% and if the NV has no drop-shipping option, the expected profit can be 9% less.
Journal: International Journal of Production Research
Pages: 6547-6571
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1324221
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1324221
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Template-Type: ReDIF-Article 1.0
Author-Name: Fernanda Strozzi
Author-X-Name-First: Fernanda
Author-X-Name-Last: Strozzi
Author-Name: Claudia Colicchia
Author-X-Name-First: Claudia
Author-X-Name-Last: Colicchia
Author-Name: Alessandro Creazza
Author-X-Name-First: Alessandro
Author-X-Name-Last: Creazza
Author-Name: Carlo Noè
Author-X-Name-First: Carlo
Author-X-Name-Last: Noè
Title: Literature review on the ‘Smart Factory’ concept using bibliometric tools
Abstract: 
 The objective of this paper is to depict a landscape of the scientific literature on the concept of the ‘Smart Factory’, which in recent years is gaining more and more attention from academics and practitioners because of significant innovations in the production systems within the manufacturing sector. To achieve this objective, a dynamic methodology called ‘Systematic Literature Network Analysis (SLNA)’ has been applied. This methodology combines the Systematic Literature Review approach with the analysis of bibliographic networks. The adopted methodology allows complementing traditional content-based literature reviews by extracting quantitative information from bibliographic networks to detect emerging topics, and by revealing the dynamic evolution of the scientific production of a discipline. This dynamic analysis allowed highlighting research directions and critical areas for the development of the ‘Smart Factory’. At the same time, it offers insights on the fields on which companies, associations, politicians and technology providers need to focus in order to allow a real transition towards the implementation of large-scale Smart Factory.
Journal: International Journal of Production Research
Pages: 6572-6591
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1326643
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1326643
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Template-Type: ReDIF-Article 1.0
Author-Name: Huihui Liu
Author-X-Name-First: Huihui
Author-X-Name-Last: Liu
Author-Name: Shuguang Sun
Author-X-Name-First: Shuguang
Author-X-Name-Last: Sun
Author-Name: Ming Lei
Author-X-Name-First: Ming
Author-X-Name-Last: Lei
Author-Name: Honghui Deng
Author-X-Name-First: Honghui
Author-X-Name-Last: Deng
Author-Name: G. Keong Leong
Author-X-Name-First: G. Keong
Author-X-Name-Last: Leong
Title: The impact of retailers’ alliance on manufacturer’s profit in a dual-channel structure
Abstract: 
 When a manufacturer adds a direct sales channel to its existing retail channel, retailers may cooperate with one another to respond to this new competition. Our study develops a Cournot competition model in a dual-channel supply chain consisting of a manufacturer and multiple retailers. In a Stackelberg decision model, the manufacturer first sets the direct sales quantity and wholesale price, and then the retailers decide the order quantities. The results indicate that forming an alliance is not always beneficial for retailers. When direct sales cost is high, there is less likelihood for retailers to collaborate. On the other hand, retailers will form an alliance when direct sales cost is sufficiently low. This will likely reduce the manufacturer’s profit. As such decreasing direct sales cost is not necessarily beneficial for the manufacturer because of the retailers’ possible collaborative efforts. In addition, the study finds that when demand fluctuation increases or the manufacturer’s information accuracy decreases, it is more likely that retailers will form an alliance. After relaxing the assumption of homogeneous retailers, our numerical study validates the possibility of partial alliance. If some retailers’ marginal costs are sufficiently high, we could see the formation of a partial alliance.
Journal: International Journal of Production Research
Pages: 6592-6607
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1330563
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330563
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Template-Type: ReDIF-Article 1.0
Author-Name: Robert Grüter
Author-X-Name-First: Robert
Author-X-Name-Last: Grüter
Author-Name: David A. Wuttke
Author-X-Name-First: David A.
Author-X-Name-Last: Wuttke
Title: Option matters: valuing reverse factoring
Abstract: 
 The value of reverse factoring consists of interest arbitrage and the potential option to enable production. We provide closed-form expressions for both components, building on financial theory and a stochastic model of liquidity needs. We characterise industries in terms of growth and volatility to identify supply chains that benefit most from adopting reverse factoring. Our results suggest how buyers should introduce reverse factoring to their supply chain to maximise their profit. Besides contributing to the understanding of reverse factoring, we provide managers with both an exact formula and an approximate rule to assess their value of reverse factoring. Our analytic and numerical results also indicate that, in many but not all cases, buyers should ask for payment term extensions rather than price reductions to obtain direct benefits from reverse factoring.
Journal: International Journal of Production Research
Pages: 6608-6623
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1330564
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330564
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Template-Type: ReDIF-Article 1.0
Author-Name: Chih-Yang Tsai
Author-X-Name-First: Chih-Yang
Author-X-Name-Last: Tsai
Title: The impact of cost structure on supply chain cash flow risk
Abstract: 
 Managing supply chain cash flow risk has become a crucial task for many cash-stressed businesses. Cash flows usually lag behind operating earnings and exhibit higher volatility than earnings, making them less predictable. Through the three components of the cash conversion cycle – days in inventory, receivables, and payables, this study investigates the impact of cost structure – cost ratios and cost compositions – on cash flow risk (standard deviation) and explains why and how management philosophies, such as Just-In-Time, and new production technologies, such as 3D printing, can lower cash flow risk by shortening days in inventory and shifting cost structure. An analytical model built on a simple demand process examines the basic relationship between cost structure and cash flow risk while a simulation approach studies the same relationship under a more general demand process with additional modelling considerations and a benchmark test. The simulation approach is applied on a publicly traded company’s financial data to demonstrate how supply chain process improvement can reduce the cash flow risk.
Journal: International Journal of Production Research
Pages: 6624-6637
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1330568
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330568
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Template-Type: ReDIF-Article 1.0
Author-Name: Marco Marconi
Author-X-Name-First: Marco
Author-X-Name-Last: Marconi
Author-Name: Eugenia Marilungo
Author-X-Name-First: Eugenia
Author-X-Name-Last: Marilungo
Author-Name: Alessandra Papetti
Author-X-Name-First: Alessandra
Author-X-Name-Last: Papetti
Author-Name: Michele Germani
Author-X-Name-First: Michele
Author-X-Name-Last: Germani
Title: Traceability as a means to investigate supply chain sustainability: the real case of a leather shoe supply chain
Abstract: 
 In recent years, the growing attention to environmental challenges has shown that these issues are becoming of more and more interest to both research and industry. Companies are expected to ensure their products are fully traceable and more sustainable, which requires the involvement of all of the actors in the production network. According to this aim, this study proposes a structured approach that uses the traditional traceability concept as a means to identify the main information needed to assess environmental impacts along the whole supply chain (SC). The proposed approach is composed of four main steps: (i) SC modelling to identify all stakeholders and their inter-relations, (ii) data sharing to collect all relevant data, (iii) data elaboration to calculate performance at different levels of detail and (iv) result interpretation to optimise the SC. The distributed implementation of the approach at different SC steps represents a useful means to practically realise a sustainable SC management. A case study involving a leather shoe SC is used to demonstrate the effectiveness of the approach in identifying criticalities, supporting the selection of the most appropriate suppliers and correctly setting a management strategy towards the optimisation of internal and external traceability and environmental sustainability performances.
Journal: International Journal of Production Research
Pages: 6638-6652
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1332437
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1332437
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Template-Type: ReDIF-Article 1.0
Author-Name: Ali Emrouznejad
Author-X-Name-First: Ali
Author-X-Name-Last: Emrouznejad
Author-Name: Marianna Marra
Author-X-Name-First: Marianna
Author-X-Name-Last: Marra
Title: The state of the art development of AHP (1979–2017): a literature review with a social network analysis
Abstract: 
 Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979–1990, 1991–2001 and 2002–2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions.
Journal: International Journal of Production Research
Pages: 6653-6675
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1334976
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1334976
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei-Guo Zhang
Author-X-Name-First: Wei-Guo
Author-X-Name-Last: Zhang
Author-Name: Qun Zhang
Author-X-Name-First: Qun
Author-X-Name-Last: Zhang
Author-Name: Kamil J. Mizgier
Author-X-Name-First: Kamil J.
Author-X-Name-Last: Mizgier
Author-Name: Yue Zhang
Author-X-Name-First: Yue
Author-X-Name-Last: Zhang
Title: Integrating the customers’ perceived risks and benefits into the triple-channel retailing
Abstract: 
 Multiple channel retailing and channel selection strategy have become key issues for many corporations to place themselves at the heart of a new era of retailing. This paper studies a triple-channel system in which a manufacturer operates a conventional channel, a direct online channel, as well as increases its online presence with an online shopping platform. It also takes the heterogeneity of consumers’ price sensitivity and channel preferences into account. It highlights that the perceived risks and perceived benefits are aggregated into an inhibitor or activator entering the customers’ acceptance of triple channels and further affecting their purchasing decisions. Three cases are discussed to investigate the demand distributions, the profit behaviours, the optimal pricing strategies and the channel selection strategies. Theoretical analysis is further validated by a case study with the aid of agent-based modelling. Sensitivity analysis demonstrates that two acceptance indices – respectively, regarded as the consumers’ willingness to tolerate the perceived risks of the online channel and approve the perceived benefits from the third-party online platform – significantly govern the total profit in two stylised scenarios. This study schematically characterises the structure of demand distributions, helps the corporation to discern consumers’ channel choices and then focus its marketing efforts towards more profitable customers and strategic channel structures. Furthermore, some implications are outlined for the optimal supply chain designation decision.
Journal: International Journal of Production Research
Pages: 6676-6690
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1336679
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1336679
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Template-Type: ReDIF-Article 1.0
Author-Name: Anderson Luis Szejka
Author-X-Name-First: Anderson Luis
Author-X-Name-Last: Szejka
Author-Name: Osiris Canciglieri 
Author-X-Name-First: Osiris
Author-X-Name-Last: Canciglieri 
Author-Name: Hervé Panetto
Author-X-Name-First: Hervé
Author-X-Name-Last: Panetto
Author-Name: Eduardo Rocha Loures
Author-X-Name-First: Eduardo
Author-X-Name-Last: Rocha Loures
Author-Name: Alexis Aubry
Author-X-Name-First: Alexis
Author-X-Name-Last: Aubry
Title: Semantic interoperability for an integrated product development process: a systematic literature review
Abstract: 
 Global competitiveness challenges manufacturing industry to rationalise different ways of bringing to the market new products in a short lead-time with competitive prices whilst ensuring higher quality levels and customisation. Industries need to effectively share heterogeneous information during Product Development Process (PDP) within and across their institutional boundaries to be competitive. However, problems with misinterpretation and mistakes have been identified during information exchange due to the semantic interoperability obstacles. Thus, this research proposes a systematic literature review to identify the main researches and the milestones reference works on semantic interoperability field. A rigorous methodology was conducted in different databases, covering the articles published in scientific journals from 2005 to 2015 as a preliminary study had indicated that the incidence of articles related to the subject was more frequent from the second half of the 2000s. The research structure consisted of four steps: Survey – searching, analysis and selection of recent researches; Categorisation – categorisation of the selected papers; References citation frequency analysis – the selected papers were analysed and the main researches and milestones references were identified; and Main researches critical analysis – the main researches were analysed for their contributions and limitations, their contributions and limitations, resulting in 14 selected scientific articles and 8 identified milestones references. It is evident that this field has interesting perspectives on future research opportunities on semantic interoperability of information issues across PDP, contributing to the new concepts of future factories.
Journal: International Journal of Production Research
Pages: 6691-6709
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1346314
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346314
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Template-Type: ReDIF-Article 1.0
Author-Name: Peng Ma
Author-X-Name-First: Peng
Author-X-Name-Last: Ma
Author-Name: Kevin W. Li
Author-X-Name-First: Kevin W.
Author-X-Name-Last: Li
Author-Name: Zhou-Jing Wang
Author-X-Name-First: Zhou-Jing
Author-X-Name-Last: Wang
Title: Pricing decisions in closed-loop supply chains with marketing effort and fairness concerns
Abstract: 
 We investigate closed-loop supply chains (CLSCs) under four reverse channel structures where a central planner, a manufacturer (M), a retailer (R) or a third party (T), respectively, serves as the collector of used product and demand depends on R’s marketing effort. We derive supply chain profitability under both the centralised and decentralised CLSCs and furnish the optimal marketing effort, collection rate and pricing decisions for the supply chain members. We then extend the base models along two directions: the first extension incorporates R’s distributional fairness concerns into the M collection model and the second extension considers potential recycle cost advantages by R and T compared to the M collection model.
Journal: International Journal of Production Research
Pages: 6710-6731
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1346324
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346324
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Template-Type: ReDIF-Article 1.0
Author-Name: Ying Wu
Author-X-Name-First: Ying
Author-X-Name-Last: Wu
Author-Name: Haiyan Li
Author-X-Name-First: Haiyan
Author-X-Name-Last: Li
Author-Name: Qinglong Gou
Author-X-Name-First: Qinglong
Author-X-Name-Last: Gou
Author-Name: Jibao Gu
Author-X-Name-First: Jibao
Author-X-Name-Last: Gu
Title: Supply chain models with corporate social responsibility
Abstract: 
 Currently, corporate social responsibility (CSR) has become a critical issue because more than 88% of consumers think companies should try to achieve their business goals while improving society and the environment. This paper focuses on a CSR supply chain where an Original Equipment Manufacturer’s (OEM’s) sales can be significantly reduced because of its oversea supplier’s social misconduct. Specifically, as in a conventional wholesale price contract the supplier determines its wholesale price and the OEM decides its order quantity, but in a CSR supply chain, the supplier can autonomously change its CSR cost once a minimum requirement is satisfied. A higher CSR cost means that the supplier invests more in its corporate social responsibility and the OEM’s sales will be less likely to be influenced by negative CSR events. The equilibrium solutions show an important dilemma – although the supplier’s profit increases in the basic CSR requirement, the supplier will always use the minimum CSR cost under the conventional wholesale price contract, which eventually leads to a low supply chain profit. Thus, we introduce two different contracts to handle this problem: the flexible quantity contract and the wholesale price incentive contract, which are, respectively, a ‘tough’ way and a ‘beneficent’ way for the OEM to solve the problem. Although the two ways cannot (always) coordinate the supply chain, we show that they both will significantly improve the supply chain performance. Our results also show that in some conditions, one strategy will dominate, whereas in different conditions the other strategy dominates.
Journal: International Journal of Production Research
Pages: 6732-6759
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1346833
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346833
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Template-Type: ReDIF-Article 1.0
Author-Name: B.C. Giri
Author-X-Name-First: B.C.
Author-X-Name-Last: Giri
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Title: A closed-loop supply chain with stochastic product returns and worker experience under learning and forgetting
Abstract: 
 This paper addresses a single-manufacturer single-retailer closed-loop supply chain with stochastic product returns considering worker experience under learning and forgetting in production and inspection of returned items at the manufacturer. Customer demand is assumed to be dependent linearly on the retail price, and it is fulfilled by using both manufactured and remanufactured products. The manufacturer delivers the buyer’s order quantity in a number of equal-sized batches. The optimal number of shipments, the shipment size and the retail price are determined by maximising the average expected profit of the closed-loop supply chain. It is observed from the numerical study that high learning effects in production and inspection lead to high recovery rates of used products, which, besides an economic advantage, may have a positive effect on the environment. Even though forgetting has an adverse effect, the average expected profit of the closed-loop supply chain is much higher than that of the basic model which ignores worker learning.
Journal: International Journal of Production Research
Pages: 6760-6778
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1347301
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1347301
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:22:p:6760-6778




Template-Type: ReDIF-Article 1.0
Author-Name: Vipul Jain
Author-X-Name-First: Vipul
Author-X-Name-Last: Jain
Author-Name: Sameer Kumar
Author-X-Name-First: Sameer
Author-X-Name-Last: Kumar
Author-Name: Umang Soni
Author-X-Name-First: Umang
Author-X-Name-Last: Soni
Author-Name: Charu Chandra
Author-X-Name-First: Charu
Author-X-Name-Last: Chandra
Title: Supply chain resilience: model development and empirical analysis
Abstract: 
 The purpose of this study is to develop a hierarchy-based model for supply chain resilience (SCRES), explaining the dynamics between various enablers and validating the model empirically. Literature review and a survey identified the enablers. Interpretive structural modelling (ISM) is used to analyse the levels of relationships among enablers. Based on their driving power and dependence, these enablers are also classified into different categories. Structural equation modelling is used to validate the hierarchical SCRES model and test the path analytical model. The study provides empirical justification for a framework that identifies 13 key enablers of resilient supply chain practices and describes the relationship among them using ISM. It also classifies them using Matrix of Cross Impact Multiplications Applied to Classification analysis on the basis of their driver power and dependence. The key finding is that using the proposed model, organisations can enhance their resilience potential by modifying their strategic assets. The model was tested using rigorous statistical tests including convergent validity, discriminant validity and reliability. The holistic view offered by the proposed model depicts the relationship among enablers to achieve SCRES.
Journal: International Journal of Production Research
Pages: 6779-6800
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1349947
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1349947
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Template-Type: ReDIF-Article 1.0
Author-Name: Viktoryia Buhayenko
Author-X-Name-First: Viktoryia
Author-X-Name-Last: Buhayenko
Author-Name: Dick den Hertog
Author-X-Name-First: Dick
Author-X-Name-Last: den Hertog
Title: Adjustable Robust Optimisation approach to optimise discounts for multi-period supply chain coordination under demand uncertainty
Abstract: 
 In this research, a problem of supply chain coordination with discounts under demand uncertainty is studied. To solve the problem, an Affinely Adjustable Robust Optimisation model is developed. At the time when decisions about order periods, ordering quantities and discounts to offer are made, only a forecasted value of demand is available to a decision-maker. The proposed model produces a discount schedule, which is robust against the demand uncertainty. The model is also able to utilise the information about the realised demand from the previous periods in order to make decisions for future stages in an adjustable way. We consider both box and budget uncertainty sets. Computational results show the necessity of accounting for uncertainty, as the total costs of the nominal solution increase significantly even when only a small percentage of uncertainty is in place. It is testified that the affinely adjustable model produces solutions, which perform significantly better than the nominal solutions, not only on average, but also in the worst case. The trade-off between reduction of the conservatism of the model and the uncertainty protection is investigated as well.
Journal: International Journal of Production Research
Pages: 6801-6823
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1351635
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1351635
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:22:p:6801-6823




Template-Type: ReDIF-Article 1.0
Author-Name: Romain Guillaume
Author-X-Name-First: Romain
Author-X-Name-Last: Guillaume
Author-Name: Caroline Thierry
Author-X-Name-First: Caroline
Author-X-Name-Last: Thierry
Author-Name: Paweł Zieliński
Author-X-Name-First: Paweł
Author-X-Name-Last: Zieliński
Title: Robust material requirement planning with cumulative demand under uncertainty
Abstract: 
 In this paper, we deal with the problem of tactical capacitated production planning with the demand under uncertainty modelled by closed intervals. We propose a single-item with backordering model under small uncertainty in the cumulative demand for the Master Production Scheduling (MPS) problem with different rules, namely the Lot For Lot rule and the Periodic Order Quantity rule. Then we study a general multilevel, multi-item, multi-resource model with backordering and the external demand on components for the Material Requirement Planning (MRP) problem under uncertainty in the cumulative demand. In order to choose robust production plans for the above problems that hedge against uncertainty, we adopt the well-known minmax criterion. We propose polynomial methods for evaluating the impact of uncertainty on a given production plan in terms of its cost and for computing optimal robust production plans for both problems (MPS/MRP) under the assumed interval uncertainty representation. We show in this way that the robust problems (MPS/MRP) under this uncertainty representation are not much computationally harder than their deterministic counterparts.
Journal: International Journal of Production Research
Pages: 6824-6845
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1353157
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1353157
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:22:p:6824-6845




Template-Type: ReDIF-Article 1.0
Author-Name: Thorsten Krægpøth
Author-X-Name-First: Thorsten
Author-X-Name-Last: Krægpøth
Author-Name: Jan Stentoft
Author-X-Name-First: Jan
Author-X-Name-Last: Stentoft
Author-Name: Jesper Kronborg Jensen
Author-X-Name-First: Jesper Kronborg
Author-X-Name-Last: Jensen
Title: Dynamic supply chain design: a Delphi study of drivers and barriers
Abstract: 
 Supply chain management has both in academia and practice proven its important role to sustain and further develop companies’ competitive advantages. This is with initiatives that focus on cost-efficiencies and turnover improvement. During the last two decades, companies have faced complexity in their supply chains currently with increased global operations. The dynamic business environment forces companies to secure a competitive (re-) design of their supply chains. This paper seeks to advance the understanding on the drivers and barriers for such designs. In total, 39 experts (30 from industrial enterprises, 4 senior supply chain consultants and 5 supply chain management professors) have participated in a four-step Delphi study and have identified main drivers for dynamic supply chain design as being cost reduction, delivery reliability and change in demand for agility. The main barriers are identified as forecasting being too weak, supply chain complexity and product portfolio complexity. In addition, an explorative factor analysis has been carried out to identify how drivers and barriers can be grouped together. Finally, the paper compares the drivers and barriers underlining different competitive strategies.
Journal: International Journal of Production Research
Pages: 6846-6856
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1355122
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei Xie
Author-X-Name-First: Wei
Author-X-Name-Last: Xie
Title: Optimal pricing and two-dimensional warranty policies for a new product
Abstract: 
 For commercial products, pricing and warranty are two crucial marketing strategies, which are used to promote the potential market share. The warranty policy adopted by most of the capital-intensive products, such as machines and automobiles, usually has two dimensions, i.e. warranty age and warranty usage. In this paper, we propose to investigate the profit-maximisation problem, in which the revenue and costs will be affected by the product price and the area of warranty region, for a new product sold under two-dimensional warranty. We assume that the product sales can be captured by a stochastic Bass model based on the nonhomogeneous Poisson process. The product follows a two-dimensional failure process and is covered by a non-renewable free minimal-repair warranty, with age and usage limits. We focus on three revenue/cost components, i.e. sales revenue, warranty cost and production cost, that will significantly affect a firm’s total profit. The profit is maximised by jointly optimising three decision variables, i.e. product price, warranty age limit and warranty usage limit. Numerical experiments are conducted to illustrate the effects of some key parameters, including product reliability, price elasticity, warranty elasticity and learning effect factor, on the optimal settings of the price and warranty region.
Journal: International Journal of Production Research
Pages: 6857-6870
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1355578
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355578
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Template-Type: ReDIF-Article 1.0
Author-Name: Minyue Jin
Author-X-Name-First: Minyue
Author-X-Name-Last: Jin
Author-Name: Jiajia Nie
Author-X-Name-First: Jiajia
Author-X-Name-Last: Nie
Author-Name: Feng Yang
Author-X-Name-First: Feng
Author-X-Name-Last: Yang
Author-Name: Yu Zhou
Author-X-Name-First: Yu
Author-X-Name-Last: Zhou
Title: The impact of third-party remanufacturing on the forward supply chain: a blessing or a curse?
Abstract: 
 It is widely agreed that the entry of third-party remanufacturers (TPRs) hurts original equipment manufacturers (OEMs) because remanufacturing cannibalises the new product sales. In this paper, motivated by the practice of mobile phone remanufacturing, we develop a game theoretical model to revisit the impact of third-party remanufacturing on a forward supply chain in which one OEM purchases critical components from one dominant supplier. The OEM may operate the remanufacturing business as cost-efficient as the TPR. Our analytical results show that regardless of the OEM’s remanufacturing capability, third-party remanufacturing could be beneficial to the OEM in that the supplier would lower the wholesale price as a response to the entry of the TPR; in addition, compared with the case without remanufacturing, third-party remanufacturing is always detrimental to the supplier, but the supplier should not always attempt to deter the entry of the TPR because third-party remanufacturing could be less detrimental than the OEM’s in-house remanufacturing. Under certain conditions, the two players in the forward supply chain both prefer third-party remanufacturing over in-house remanufacturing. The key intuition driving this finding is that third-party remanufacturing makes the OEM and the supplier allied; while in-house remanufacturing makes them against each other.
Journal: International Journal of Production Research
Pages: 6871-6882
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1357860
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Template-Type: ReDIF-Article 1.0
Author-Name: Jinting Wang
Author-X-Name-First: Jinting
Author-X-Name-Last: Wang
Author-Name: Xuelu Zhang
Author-X-Name-First: Xuelu
Author-X-Name-Last: Zhang
Title: Optimal pricing in a service-inventory system with delay-sensitive customers and lost sales
Abstract: 
 We consider a single-server service-inventory system where customers arrive according to a Poisson process and the service times are independent and exponentially distributed. A customer takes exactly one item from the inventory after service if it is available, or the request is lost. A continuous review policy is adopted to replenish the inventory. Upon two different information levels, i.e. the fully unobservable case and the partially observable case, arriving customers decide whether to join or to balk the system. We investigate the customers’ individually optimal and socially optimal strategies, and further consider the optimal pricing issue that maximises the server’s revenue. Some numerical experiments are carried out to show that the individually optimal joining probability (or threshold) is not always greater than that of socially optimal one. It is observed that, to maximise the server’s revenue, concealing some system information to customers may be more profitable. Conversely, to maximise the social welfare, the customers need more system information. Finally, numerical results in the fully unobservable case illustrate a reasonable phenomenon that the revenue maximum is equal to social optimum in most cases.
Journal: International Journal of Production Research
Pages: 6883-6902
Issue: 22
Volume: 55
Year: 2017
Month: 11
X-DOI: 10.1080/00207543.2017.1363426
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenjie Bi
Author-X-Name-First: Wenjie
Author-X-Name-Last: Bi
Author-Name: Guo Li
Author-X-Name-First: Guo
Author-X-Name-Last: Li
Author-Name: Mengqi Liu
Author-X-Name-First: Mengqi
Author-X-Name-Last: Liu
Title: Dynamic pricing with stochastic reference effects based on a finite memory window
Abstract: 
 Inspired by the latest empirical studies, we propose a new updating model for reference prices by assuming that consumers’ memories are limited and their recall of previous prices obeys a first-order Markov stochastic process. We investigate a dynamic pricing model with stochastic reference effects and finite memory. Consistent with the exponential smoothing model, we indicate that reference effects lead to monotonic convergence of the optimal price path to an expected steady-state price. The steady-state range tends to widen as consumers become loss-averse. The results of our numerical experiments differ from findings of certain models under the assumption of stochastic recall memory of consumers. The optimal price path fluctuates consistently around the steady state instead of remaining constant. The effect of the first price on the memory window and long-term profits decreases as the length of memory window increases.
Journal: International Journal of Production Research
Pages: 3331-3348
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1221160
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Template-Type: ReDIF-Article 1.0
Author-Name: Dunbing Tang
Author-X-Name-First: Dunbing
Author-X-Name-Last: Tang
Author-Name: Qi Wang
Author-X-Name-First: Qi
Author-X-Name-Last: Wang
Author-Name: Inayat Ullah
Author-X-Name-First: Inayat
Author-X-Name-Last: Ullah
Title: Optimisation of product configuration in consideration of customer satisfaction and low carbon
Abstract: 
 Product configuration is one of the key technologies in the environment of mass customisation, and it has been emphasised and concerned by much research. However, previous studies mostly focus on the cost or the customer utility, but ignore the environmental concern which becomes an important design criterion due to the rising awareness of environmental protection. Moreover, various preferences of customers are also not considered. In this paper, we develop a new bi-objective optimisation model with simultaneous consideration of customer satisfaction and the environmental impact in product configuration. Two objectives of our model are the customer satisfaction index (CSI) and greenhouse gas (GHG) emissions of products. The CSI is presented for the evaluation of customer satisfaction and the GHG emission model is developed to assess the environmental impact of the product. Essential constraints, such as selection, cost and compatibility, are also considered in the model. In addition, a two-phase approach is proposed to solve the optimisation model. Finally, the effectiveness of the proposed method is demonstrated through a case study.
Journal: International Journal of Production Research
Pages: 3349-3373
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1231430
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Template-Type: ReDIF-Article 1.0
Author-Name: Guodong Huang
Author-X-Name-First: Guodong
Author-X-Name-Last: Huang
Author-Name: Jie Chen
Author-X-Name-First: Jie
Author-X-Name-Last: Chen
Author-Name: Xiuli Wang
Author-X-Name-First: Xiuli
Author-X-Name-Last: Wang
Author-Name: Yiqun Shi
Author-X-Name-First: Yiqun
Author-X-Name-Last: Shi
Author-Name: Houping Tian
Author-X-Name-First: Houping
Author-X-Name-Last: Tian
Title: From loop structure to policy-making: a CONWIP design framework for hybrid flow shop control in one-of-a-kind production environment
Abstract: 
 A feasible constant work in process (CONWIP) policy can guide developer to better implement CONWIP system. The feasible policy should be selected from alternatives by evaluation. Therefore, how to generate more than one CONWIP alternative policy to evaluate is an inevitable problem in CONWIP practice. From the perspective of loop structure, we propose CONWIP design framework (CDF) which is a systematic design approach to obtain CONWIP alternative policies. The basic concepts and components for CDF are discussed in this paper. Based on CDF, we make 10 CONWIP alternative policies for hybrid flow shop in one-of-a-kind production environment, and these alternative policies are evaluated by simulation. The simulation result implies that (i) the CONWIP alternative policy with robustness has the potential to cope with more fluctuations in high-variety production environment; (ii) a better design for CONWIP policy will be able to enhance the system performance in practice; and (iii) the loop structure can serve as a parameter of CONWIP.
Journal: International Journal of Production Research
Pages: 3374-3391
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1234723
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:12:p:3374-3391




Template-Type: ReDIF-Article 1.0
Author-Name: Shanshan Guo
Author-X-Name-First: Shanshan
Author-X-Name-Last: Guo
Author-Name: H. Sebastian Heese
Author-X-Name-First: H. Sebastian
Author-X-Name-Last: Heese
Title: Product variety and distribution channel structure
Abstract: 
 We consider how a manufacturer’s product variety decision is affected by its distribution strategy. While offering product variety will generally lead to higher demand, it also has negative implications on production costs and demand uncertainty. We investigate how the manufacturer’s optimal product variety decision differs when selling directly to customers (centralised scenario) as compared to selling through a retailer (decentralised scenario). We find that the retailer’s power and the impact of product variety on demand significantly affect the attractiveness of product variety and determine under which distribution strategy the manufacturer should provide a higher level of variety.
Journal: International Journal of Production Research
Pages: 3392-3410
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1240380
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1240380
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:12:p:3392-3410




Template-Type: ReDIF-Article 1.0
Author-Name: Danqin Yang
Author-X-Name-First: Danqin
Author-X-Name-Last: Yang
Author-Name: Tiaojun Xiao
Author-X-Name-First: Tiaojun
Author-X-Name-Last: Xiao
Title: Coordination of a supply chain with loss-averse consumers in service quality
Abstract: 
 We develop a two-period game model to study the coordination mechanism for a supply chain with loss-averse consumers who are assumed to have dwindling sensitivity to service quality gain relative to loss. We find that all-unit quantity discount coupling with service subsidy rate can coordinate the retailer’s price and service quality decisions together in each period. When consumers become more loss-averse in service quality, the coordinated wholesale price in the first period might increase; whereas that in the second period decreases. With Pareto coordination mechanism, larger loss-aversion might weaken the supplier’s bargaining power. We provide managerial insights on how to adjust the coordinated contract when the consumers’ loss-aversion and reference value of service quality level change.
Journal: International Journal of Production Research
Pages: 3411-3430
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1241444
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1241444
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Template-Type: ReDIF-Article 1.0
Author-Name: Ramzi Hammami
Author-X-Name-First: Ramzi
Author-X-Name-Last: Hammami
Author-Name: Yannick Frein
Author-X-Name-First: Yannick
Author-X-Name-Last: Frein
Author-Name: Bouchaib Bahli
Author-X-Name-First: Bouchaib
Author-X-Name-Last: Bahli
Title: Supply chain design to guarantee quoted lead time and inventory replenishment: model and insights
Abstract: 
 Do lead time constraints only lead to re-think and re-optimise the inventory positioning along the supply chain or can they impact on the design of the supply chain itself? To answer such a question, we integrate the lead time constraints in a multi-echelon supply chain design model and challenge the difficulty of combining in the same model the long-term decisions (facility location, supplier selection) with the midterm decisions (inventory placement and replenishment, delivery lead time). The model guarantees the respect of the quoted lead time associated with each customer order and the replenishment of the different stocks (raw materials, intermediate and final products) in the different stages of the supply chain between any pair of consecutive orders. We use the model to investigate the impact of the quoted lead time and customer’s order frequency on supply chain design decisions and costs. Some of our results indicate that the lead time constraints can lead to bringing the sites of manufacturing and distribution close to the demand zone and to select local suppliers in spite of their higher cost.
Journal: International Journal of Production Research
Pages: 3431-3450
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1242799
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1242799
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Template-Type: ReDIF-Article 1.0
Author-Name: Arash Abedi
Author-X-Name-First: Arash
Author-X-Name-Last: Abedi
Author-Name: Weihang Zhu
Author-X-Name-First: Weihang
Author-X-Name-Last: Zhu
Title: An optimisation model for purchase, production and distribution in fish supply chain – a case study
Abstract: 
 This paper presents an optimisation model for spawn purchase, fish culturing production process and harvested fish distribution in a fish supply chain. Due to the complexity and variety of real-world fish supply chains, the model is built based on a case study for a real trout fish farm to illustrate the methodology on how to incorporate influential factors from both warm chain and cold chain. Warm chain mainly considers the biological factors while fish is alive and cold chain mainly considers the economic factors after fish is ready for harvest, harvested, and processed. The model seeks to improve the trout farm production planning to help decision-making on spawn purchase quantity, the best time to harvest fish, and the farming periods. In addition, the model adopts a customer classification method in distribution planning that is able to prioritise the delivery of fresh fish to the most profitable customers. A mixed integer linear programming (MILP) model was developed to maximise the total profit. The experimental results demonstrate that farmers’ total profit can be increased after applying the proposed optimisation strategy, compared to the traditional farming strategy.
Journal: International Journal of Production Research
Pages: 3451-3464
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1242800
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1242800
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:12:p:3451-3464




Template-Type: ReDIF-Article 1.0
Author-Name: Marta Jakowczyk
Author-X-Name-First: Marta
Author-X-Name-Last: Jakowczyk
Author-Name: João Quariguasi Frota Neto
Author-X-Name-First: João
Author-X-Name-Last: Quariguasi Frota Neto
Author-Name: Andrew Gibson
Author-X-Name-First: Andrew
Author-X-Name-Last: Gibson
Author-Name: Luk N. Van Wassenhove
Author-X-Name-First: Luk N.
Author-X-Name-Last: Van Wassenhove
Title: Understanding the market for remanufactured products: what can we learn from online trading and Web search sites?
Abstract: 
 Notwithstanding the interest it elicits from academics and practitioners, relatively little is known about the market for remanufactured products. Research, still in its infancy, has focused almost entirely on what affects willingness to pay, and our understanding of other key marketing questions, such as what drives search intensity for remanufactured products and the number of remanufactured products on offer, is limited. This paper fills this knowledge gap. Focusing on the online market for remanufactured electrical and electronic products, we empirically test whether product-specific and market-specific determinants affect search intensity and number of remanufactured products on offer, that is number of listings. We use as inputs online search traffic, product-specific data collected from various other online sources and relevant eBay listing data. Our analysis supports the hypotheses that search intensity for remanufactured products is associated with search intensity for price and elapsed time since the launch of new counterpart products. Number of remanufactured products listed is associated with number of listings for new counterparts and two product-specific characteristics: presence of moving parts and whether the product is used for personal hygiene. We discuss several implications of our findings for remanufacturers and policy-makers as well as directions for future research.
Journal: International Journal of Production Research
Pages: 3465-3479
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1275872
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1275872
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Template-Type: ReDIF-Article 1.0
Author-Name: Malgorzata Plaza
Author-X-Name-First: Malgorzata
Author-X-Name-Last: Plaza
Title: Cost-effectiveness of audio description production process: comparative analysis of outsourcing and ‘in-house’ methods
Abstract: 
 The need for audio description (AD) is growing rapidly due to the increasing number of people who suffer vision loss. Unfortunately, the producers of movie, shows and other TV programmes view AD as a costly service with no revenue potential. Since cost-effectiveness of AD was never argued, the producers hesitate to expand the service beyond mandatory requirements imposed by the regulatory agencies. This paper develops a cost model and a decision support system that can be used to examine the cost-effectiveness of AD production. AD expansion is examined using a case study, in which the three types of producers: a production studio, an independent film and a broadcaster audio, describe a 30-min TV show. The expansion is analysed under the following conditions: (1) the descriptions are produced by a full-time AD crew instead of being outsourced to a third party, (2) AD production is supported by technology to reduce the time required to record and synchronise narrations and (3) a rich programming mix that includes: shows, movies and other TV programmes is described. The results are promising. For example, if a rich programming mix is described by a broadcaster, AD expansion will become feasible.
Journal: International Journal of Production Research
Pages: 3480-3496
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1282182
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1282182
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:12:p:3480-3496




Template-Type: ReDIF-Article 1.0
Author-Name: Charisios Achillas
Author-X-Name-First: Charisios
Author-X-Name-Last: Achillas
Author-Name: Dimitrios Tzetzis
Author-X-Name-First: Dimitrios
Author-X-Name-Last: Tzetzis
Author-Name: Maria Olga Raimondo
Author-X-Name-First: Maria Olga
Author-X-Name-Last: Raimondo
Title: Alternative production strategies based on the comparison of additive and traditional manufacturing technologies
Abstract: 
 Additive manufacturing technology has been evolving for several years. New material options, better processing speeds and greater autonomy are some of the characteristics of this technology that are still under research. However, in its current state, many commercially available 3D printers are competing with traditional manufacturing techniques in the fabrication of end-use products. In this paper, different additive manufacturing technologies are compared with injection moulding in a real-world case study. The comparison is conducted in terms of lead time and total production cost. From the case under study, it becomes obvious that none of the additive manufacturing technologies examined is yet able to practically replace injection moulding for medium- and high production volumes. However, when considering low-volume production, both rapid tooling and additive manufacturing may offer an alternative that could result into shorter lead times and decreased total production costs. In addition, the introduction of Additive Manufacturing in a producer’s production portfolio can increase flexibility, reduce warehousing costs and assist the company towards the adoption of a mass customisation business strategy.
Journal: International Journal of Production Research
Pages: 3497-3509
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1282645
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1282645
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Template-Type: ReDIF-Article 1.0
Author-Name: Benrong Zheng
Author-X-Name-First: Benrong
Author-X-Name-Last: Zheng
Author-Name: Chao Yang
Author-X-Name-First: Chao
Author-X-Name-Last: Yang
Author-Name: Jun Yang
Author-X-Name-First: Jun
Author-X-Name-Last: Yang
Author-Name: Min Zhang
Author-X-Name-First: Min
Author-X-Name-Last: Zhang
Title: Dual-channel closed loop supply chains: forward channel competition, power structures and coordination
Abstract: 
 This paper examines the effect of forward channel competition and power structure on dual-channel closed loop supply chains (CLSC), which consists of a manufacturer, a retailer and a collector. The manufacturer can either wholesale products to the retailer or directly sell them to the market, the collector undertakes the collection activity of used products. Under different channel power structures, a centralised and three decentralised models are explored under symmetric and asymmetric relative status between direct and retail channels. Through a comprehensive comparison among these models, the result shows that each channel member has an incentive to play the channel leader’s role. Meanwhile, from the total channel system’s perspective, we find that the manufacturer-led or retailer-led model can either be the most effective CLSC under symmetric relative channel status, which depends on the channel substitution rate between two channels. While under asymmetric relative channel status, the numerical result shows that the whole CLSC should select collector-led, manufacturer-led and retailer-led CLSC model in turn with the retail channel’s relative status becoming stronger. Finally, with the benchmark of the centralised decision-making system, we design modified two-part tariff contracts to coordinate dual-channel CLSCs under different channel power structures.
Journal: International Journal of Production Research
Pages: 3510-3527
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1304662
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1304662
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Template-Type: ReDIF-Article 1.0
Author-Name: Cuiqing Jiang
Author-X-Name-First: Cuiqing
Author-X-Name-Last: Jiang
Author-Name: Yao Liu
Author-X-Name-First: Yao
Author-X-Name-Last: Liu
Author-Name: Yong Ding
Author-X-Name-First: Yong
Author-X-Name-Last: Ding
Author-Name: Kun Liang
Author-X-Name-First: Kun
Author-X-Name-Last: Liang
Author-Name: Rui Duan
Author-X-Name-First: Rui
Author-X-Name-Last: Duan
Title: Capturing helpful reviews from social media for product quality improvement: a multi-class classification approach
Abstract: 
 Reviews posted to social media are an effective source of information for helping quality managers to improve product quality. However, because helpful quality-related reviews may involve various aspects of product quality, previous studies confusing these aspects cannot provide targeted information regarding different aspects of product quality and production system improvement. In this paper, we propose a method of multi-class classification for helpful quality-related reviews corresponding to different aspects of product quality and production systems. Furthermore, the efficient and accurate identification of helpful quality-related reviews remains a critical challenge because of the sparseness of such reviews, which significantly influences classifier performance. To address these problems, we develop a model for the identification of helpful reviews called Helpful Quality-related Review Mining (HQRM) that incorporates a multi-class classification architecture and imbalanced data classification methods. The experimental results show that HQRM enables the multi-class classification of helpful quality-related reviews with significantly improved precision, recall and F-measure values.
Journal: International Journal of Production Research
Pages: 3528-3541
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1304664
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1304664
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:12:p:3528-3541




Template-Type: ReDIF-Article 1.0
Author-Name: Wei Zhang
Author-X-Name-First: Wei
Author-X-Name-Last: Zhang
Author-Name: Yongjiang Shi
Author-X-Name-First: Yongjiang
Author-X-Name-Last: Shi
Author-Name: Miying Yang
Author-X-Name-First: Miying
Author-X-Name-Last: Yang
Author-Name: Xinjian Gu
Author-X-Name-First: Xinjian
Author-X-Name-Last: Gu
Author-Name: Renzhong Tang
Author-X-Name-First: Renzhong
Author-X-Name-Last: Tang
Author-Name: Xiaohong Pan
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Pan
Title: Ecosystem evolution mechanism of manufacturing service system driven by service providers
Abstract: 
 To date, research has mainly discussed the definition and classification of producer services. Yet many companies require an integrated solution of products and producer services. The aim of this paper is to propose a model of the ecological evolution of manufacturing service systems (MSS) driven by service providers. This model adopts modular thinking to integrate dispersive producer services into an entire MSS, the process of which forms the ecological evolution of MSS. This paper applies ecological theory to build the ecological evolution mechanism of MSS. In this mechanism, the predator–prey relationship is used as a metaphor for the relationships between manufacturers and service providers in a MSS. A predator–prey model is built to simulate the ecological evolution of MSS. A predation cellular genetic algorithm is adopted to optimise this evolution. The proposed model and algorithm are demonstrated and validated by a case study of MSS in bicycle industry. This study contributes to theory by proposing and clarifying the mechanism for provision of services between businesses. The future research will focus on the application and empirical analysis of this mechanism derived from big data.
Journal: International Journal of Production Research
Pages: 3542-3558
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1305131
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1305131
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Template-Type: ReDIF-Article 1.0
Author-Name: Gionata Carmignani
Author-X-Name-First: Gionata
Author-X-Name-Last: Carmignani
Title: Scrap value stream mapping (S-VSM): a new approach to improve the supply scrap management process
Abstract: 
 In this work, an innovative methodology to improve the Supply Scrap Management Process (SSMP), based on Value Stream Mapping (VSM), is presented. VSM is one of the best tools to map a process and eliminate its critical issues, that produces good results if applied to production processes, but can be ineffective for management processes as the SSMP. Therefore, the main objective of this work is to overcome this limitation. The proposed approach taking the name Scrap Value Stream Mapping (S-VSM) and integrates concepts from VSM and other Lean Production (LP) and World Class Manufacturing tools. It is structured in five steps. The definition of the process borders and the identification of categories of loss through the first four steps of Cost Deployment is the first step. Then, the SSMP is subdivided in its Accounting and Physical Streams and the current state is drawn. Next, wastes and critical issues are analysed and their root causes are determined using some of LP tools. In step four, improvements are proposed and the future state is drawn. Furthermore, potential savings, in terms of €, are estimated. In the last step, a methodology to monitor the effects of implemented improvements is defined. A case study taken from the application of the S-VSM within automotive company is presented.
Journal: International Journal of Production Research
Pages: 3559-3576
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1308574
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1308574
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Template-Type: ReDIF-Article 1.0
Author-Name: Yongxin Liao
Author-X-Name-First: Yongxin
Author-X-Name-Last: Liao
Author-Name: Fernando Deschamps
Author-X-Name-First: Fernando
Author-X-Name-Last: Deschamps
Author-Name: Eduardo de Freitas Rocha Loures
Author-X-Name-First: Eduardo de Freitas Rocha
Author-X-Name-Last: Loures
Author-Name: Luiz Felipe Pierin Ramos
Author-X-Name-First: Luiz Felipe Pierin
Author-X-Name-Last: Ramos
Title: Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal
Abstract: 
 Over the last few years, the fourth industrial revolution has attracted more and more attentions all around the world. In the current literature, there is still a lack of efforts to systematically review the state of the art of this new industrial revolution wave. The aim of this study is to address this gap by investigating the academic progresses in Industry 4.0. A systematic literature review was carried out to analyse the academic articles within the Industry 4.0 topic that were published online until the end of June 2016. In this paper, the obtained results from both the general data analysis of included papers (e.g. relevant journals, their subject areas and categories, conferences, keywords) and the specific data analysis corresponding to four research sub-questions are illustrated and discussed. These results not only summarise the current research activities (e.g. main research directions, applied standards, employed software and hardware), but also indicate existing deficiencies and potential research directions through proposing a research agenda. Findings of this review can be used as the basis for future research in Industry 4.0 and related topics.
Journal: International Journal of Production Research
Pages: 3609-3629
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1308576
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1308576
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Template-Type: ReDIF-Article 1.0
Author-Name: Samira Keivanpour
Author-X-Name-First: Samira
Author-X-Name-Last: Keivanpour
Author-Name: Daoud Ait Kadi
Author-X-Name-First: Daoud
Author-X-Name-Last: Ait Kadi
Title: Modelling end of life phase of the complex products: the case of end of life aircraft
Abstract: 
 There are different approaches to modelling the products at the End of Life (EOL), including closed loop approach, the ladder of lansink and material flow. The sustainability principles and the complexity of the products may affect the choice of modelling type. The life cycle costs, several subsystems and the interaction between design features, construction, technology, suppliers and legislation affect the degree of complexity of the products. Hence, developing appropriate strategies are required for modelling EOL phase of the complex products. This article presents strategies for modelling EOL phase of complex products considering sustainability tools, EOL phase models and the characteristics of these products. An ingenerated approach is proposed to address the four essential aspects of the complex product at the EOL: operational, tactical, strategic and sustainability. The case of aircraft at the EOL is presented to highlight the application of the proposed approach.
Journal: International Journal of Production Research
Pages: 3577-3595
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1308577
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1308577
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Template-Type: ReDIF-Article 1.0
Author-Name: Dayron Antonio Álvarez-Rodríguez
Author-X-Name-First: Dayron Antonio
Author-X-Name-Last: Álvarez-Rodríguez
Author-Name: Julio Elias Normey-Rico
Author-X-Name-First: Julio Elias
Author-X-Name-Last: Normey-Rico
Author-Name: Rodolfo César Costa Flesch
Author-X-Name-First: Rodolfo César Costa
Author-X-Name-Last: Flesch
Title: Model predictive control for inventory management in biomass manufacturing supply chains
Abstract: 
 This paper presents a centralised model predictive control strategy applied to biomass inventory control in sugarcane industries. Sugarcane industries are important renewable energy producers and an adequate inventory control of their feed material (biomass) can improve energy production. Simple linear discrete-time models with dead-time are developed to predict the controlled variable behaviour. Two layers are used in the controller, in the upper one performance is optimised by an linear programming (LP) algorithm and a multivariable generalised predictive controller (GPC) or multivariable generalised predictive controller with dead-time compensation (DTC-GPC) is used in the lower level. Simulation results in general show that the proposed controllers globally optimise the system behaviour and find an optimal ordering amount for keeping stock levels. In cases of plant/model mismatch DTC-GPC can have a significant and positive impact on the control of stock levels adding one more parameter for achieving minimised oscillatory performances (bullwhip effect).
Journal: International Journal of Production Research
Pages: 3596-3608
Issue: 12
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1315191
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1315191
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Template-Type: ReDIF-Article 1.0
Author-Name: Yun Dong
Author-X-Name-First: Yun
Author-X-Name-Last: Dong
Author-Name: Ren Zhao
Author-X-Name-First: Ren
Author-X-Name-Last: Zhao
Title: Solve train stowage planning problem of steel coil using a pointer-based discrete differential evolution
Abstract: 
 Train stowage planning problem of steel coil (TSPP) is to determine loading locations of the coils on train railcars, which is rarely studied, and an important optimisation problem in real iron and steel industry. In this paper, first, according to the actual situations of a steel products transportation department, the problem is formulated as an integer programming (IP) mathematical model in which multiple destination stations, varied stowing modes and different railcar types are considered. Then, on the basis of a general discrete optimisation algorithm framework, i.e. pointer-based discrete differential evolution (PDDE), a novel variant (T-PDDE) is proposed for effectively solving the TSPP. In particular, to deal with the issue of transformation between stowage plan and algorithm individual, a problem-based coding method is designed. To further enhance the algorithm performance, a double levels evolution strategy and an opposite-based local search are developed based on the features of problem. Finally, with the practical and simulative data, extensive comparison experiments are carried out to evaluate the proposed algorithm. The numerical results demonstrate the superiority of T-PDDE on solving TSPP.
Journal: International Journal of Production Research
Pages: 6937-6955
Issue: 22
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2017.1413260
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1413260
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Template-Type: ReDIF-Article 1.0
Author-Name: Zijian He
Author-X-Name-First: Zijian
Author-X-Name-Last: He
Author-Name: Vaneet Aggarwal
Author-X-Name-First: Vaneet
Author-X-Name-Last: Aggarwal
Author-Name: Shimon Y. Nof
Author-X-Name-First: Shimon Y.
Author-X-Name-Last: Nof
Title: Differentiated service policy in smart warehouse automation
Abstract: 
 Smart warehouse automation has emerged as an effective, competitive solution for suppliers and distributors. With the increasing demand for physical storage and distribution services, suppliers and service providers are challenged to respond not only effectively, but with minimal latency. Differentiated service levels for different classes of customer orders have not yet, however, been developed for physical storage and retrieval. In this paper, in the context of smart warehouse automation services, a novel policy, called Differentiated Probabilistic Queuing (DPQ) is developed for servicing customers&#x2019; orders by Automated Guided Vehicles (AGV). Applying the DPQ policy, the average overall latency of each customer order, the mean overall processing time of this customer&#x2019;s orders in the smart warehouse automation system, is characterised under Poisson customer order arrival patterns. The weighted average latency of all customer orders is optimised over the choice of (1) storage assignment and (2) DPQ policy. Due to the existence of two types of variables, Alternating Minimisation method is applied to solve this joint optimisation problem. Compared with a combination of the classical turn-over rate storage assignment method and FCFS policy, the new approach yields 19.64% lower (better) objective function value with statistical significance. Numerical analysis results also indicate, as expected, that when the smart warehouse system resources become more limited, and the price difference among different classes of customer orders increases, the improvement becomes even more significant.
Journal: International Journal of Production Research
Pages: 6956-6970
Issue: 22
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2017.1421789
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421789
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Template-Type: ReDIF-Article 1.0
Author-Name: Sandeep Kumar
Author-X-Name-First: Sandeep
Author-X-Name-Last: Kumar
Author-Name: Bhushan S. Purohit
Author-X-Name-First: Bhushan S.
Author-X-Name-Last: Purohit
Author-Name: Vikas Manjrekar
Author-X-Name-First: Vikas
Author-X-Name-Last: Manjrekar
Author-Name: Vivek Singh
Author-X-Name-First: Vivek
Author-X-Name-Last: Singh
Author-Name: Bhupesh Kumar Lad
Author-X-Name-First: Bhupesh Kumar
Author-X-Name-Last: Lad
Title: Investigating the value of integrated operations planning: A case-based approach from automotive industry
Abstract: 
 During the last decade, many researchers have focused on joint consideration of various operations planning aspects like production scheduling, maintenance scheduling, inventory control, etc. Such joint considerations are becoming increasingly important from the point of view of current advancement in intelligent manufacturing, also known as Industry 4.0. Under the concept of Industry 4.0, advanced data analytics aim to remove human intervention in decision-making. Thus, the managerial level coordination of decisions taken independently by various departments will be out of trend. Therefore, developing an approach that optimises various operations planning decisions simultaneously is essential. Available literature on such joint considerations is more of the exploratory in nature and is limited to simplistic production environments. This necessitates the investigations of value of integrated operations planning for wide range of manufacturing scenarios. Present paper adopts a case-oriented approach to investigate the value of integrated operations planning. First, an integrated approach for simultaneously determining job sequencing, batch-sizing, inventory levels and preventive maintenance schedule is developed. The approach is tested in a complex production environment of an automotive plant and substantial economic improvement was realised. Second, a comprehensive evaluation is performed to study the robustness and implications of proposed approach for various production scenarios. Results of such pervasive performance investigations confirm the value of proposed approach over conventional approaches.
Journal: International Journal of Production Research
Pages: 6971-6992
Issue: 22
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1424367
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424367
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Template-Type: ReDIF-Article 1.0
Author-Name: Vijaya Dixit
Author-X-Name-First: Vijaya
Author-X-Name-Last: Dixit
Author-Name: Priyanka Verma
Author-X-Name-First: Priyanka
Author-X-Name-Last: Verma
Author-Name: Piyush Raj
Author-X-Name-First: Piyush
Author-X-Name-Last: Raj
Author-Name: Mayank Sharma
Author-X-Name-First: Mayank
Author-X-Name-Last: Sharma
Title: Resource and time criticality based block spatial scheduling in a shipyard under uncertainty
Abstract: 
 The block erection area is an important bottleneck resource that determines the throughput and productivity of a shipyard. This study addresses Block Spatial Scheduling (BSS) problem of a shipbuilding project comprising 72 blocks with uncertain erection duration. We adopted priority rules-based simulation approach to overcome the computational complexity of non-deterministic polynomial hard BSS problem. This is one of the earliest studies to introduce resource (space) based criticality index in BSS problem. Four time-based, one resource-based and six combinations of time criticality index (TCI) and resource criticality index (RCI) based priority rules are considered for achieving three objectives: minimisation of expected project duration, minimisation of expected average tardiness of blocks and maximisation of average area utilisation percentage. Seven important implications are derived from results, which can be applied by shipbuilding managers to BSS to increase the productivity of shipyard. Results reveal that priority rule based on TCI&#xD7;RCI and shortest processing time yield the most and the least efficient trade-off, respectively, between time and resource-oriented objectives. Further, a sensitivity analysis, performed by varying degree of uncertainty, reveals negative effect of uncertainty by increasing variation in objectives. Overall, the derived implications underpin the importance of incorporating RCI in BSS context.
Journal: International Journal of Production Research
Pages: 6993-7007
Issue: 22
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1424369
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424369
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Template-Type: ReDIF-Article 1.0
Author-Name: Toni Erfurth
Author-X-Name-First: Toni
Author-X-Name-Last: Erfurth
Author-Name: Julia Bendul
Author-X-Name-First: Julia
Author-X-Name-Last: Bendul
Title: Integration of global manufacturing networks and supply chains: a cross case comparison of six global automotive manufacturers
Abstract: 
 Striving for new business opportunities automotive original&#xA0;equipment manufacturers established overseas plants in emerging markets and global manufacturing networks evolved. In this regard so-called knocked down supply chains have been the key for the establishment of successful overseas operations. Importing all parts required from the original plants in form of easy to be handled kits secures a high product quality and stable supply despite lacking qualification of local workforce and supplier bases. Over time the overseas plants and global manufacturing networks have matured by increasingly taking over value adding processes and integrating local suppliers. However, the supply chain structure and management have not been adapted accordingly and still comprise high inventory buffers and lead times. There is little research on the integrated design of global manufacturing networks and knocked down supply chains. This research aims to contribute to close this research gap by means of a cross-case study with six globally operating OEMs investigating the fit of knocked down supply chains and global manufacturing networks. On the basis of transaction cost theory, we develop an integrated framework to align global manufacturing networks and knocked down supply chain design that can serve as guideline to open logistics performance and cost potentials.
Journal: International Journal of Production Research
Pages: 7008-7030
Issue: 22
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1424370
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424370
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Template-Type: ReDIF-Article 1.0
Author-Name: Renan Spencer Trindade
Author-X-Name-First: Renan Spencer
Author-X-Name-Last: Trindade
Author-Name: Olinto C&#xE9;sar Bassi de Ara&#xFA;jo
Author-X-Name-First: Olinto C&#xE9;sar Bassi
Author-X-Name-Last: de Ara&#xFA;jo
Author-Name: Marcia Helena Costa Fampa
Author-X-Name-First: Marcia Helena Costa
Author-X-Name-Last: Fampa
Author-Name: Felipe Martins M&#xFC;ller
Author-X-Name-First: Felipe Martins
Author-X-Name-Last: M&#xFC;ller
Title: Modelling and symmetry breaking in scheduling problems on batch processing machines
Abstract: 
 Problems of scheduling batch-processing machines to minimise the makespan are widely exploited in the literature, mainly motivated by real-world applications, such as burn-in tests in the semiconductor industry. These problems consist of grouping jobs in batches and scheduling them on machines. We consider problems where jobs have non-identical sizes and processing times, and the total size of each batch cannot exceed the machine capacity. The processing time of a batch is defined as the longest processing time among all jobs assigned to it. Jobs can also have non-identical release times, and in this case, a batch can only be processed when all jobs assigned to it are available. This paper discusses four different versions of batch scheduling problems, considering a single processing machine or parallel processing machines and considering jobs with or without release times. New mixed integer linear programming formulations are proposed as enhancements of formulations proposed in the literature, and symmetry breaking constraints are investigated to reduce the size of the feasible sets. Computational results show that the proposed formulations have a better performance than other models in the literature, being able to solve to optimality instances only considered before to be solved by heuristic procedures.
Journal: International Journal of Production Research
Pages: 7031-7048
Issue: 22
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1424371
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424371
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 7049-7049
Issue: 22
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1505031
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1505031
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Erratum
Journal: International Journal of Production Research
Pages: 7050-7050
Issue: 22
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1513964
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1513964
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Template-Type: ReDIF-Article 1.0
Author-Name: Souheil Ayed
Author-X-Name-First: Souheil
Author-X-Name-Last: Ayed
Author-Name: Zied Hajej
Author-X-Name-First: Zied
Author-X-Name-Last: Hajej
Author-Name: Sadok Turki
Author-X-Name-First: Sadok
Author-X-Name-Last: Turki
Author-Name: Nidhal Rezg
Author-X-Name-First: Nidhal
Author-X-Name-Last: Rezg
Title: FPA method for optimal production planning under availability/degradation machine and subcontracting constraint
Abstract: 
 This work treats an industrial problematic of a manufacturing system M1 subject to random failure and that satisfies a random demand under required service level. To ensure the satisfaction of the demand, it calls up on a second manufacturing system M2 that is a subcontractor and has a stochastic service level. This paper aims to determine an optimal production plan taking into account the degradation of the manufacturing system following its production rate and its availability. The unavailability of the machine M1 is due to the non-negligible preventive and corrective maintenance actions duration. To consider a realistic case of the subcontractor, we consider that is not able to respond to the variation of the demand, and then it assumed that the manufacturer can order a minimum fixed quantity. We then derive an optimal production plan taking into account the degradation of the machine and simultaneously minimising: inventory, degradation and production cost. An algorithm based on finite perturbation analysis is proposed to determine the optimal production plan and the sensitivity study of the availability is presented.
Journal: International Journal of Production Research
Pages: 2135-2148
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1165879
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1165879
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Template-Type: ReDIF-Article 1.0
Author-Name: Kuan Siew Khor
Author-X-Name-First: Kuan Siew
Author-X-Name-Last: Khor
Author-Name: Benjamin T. Hazen
Author-X-Name-First: Benjamin T.
Author-X-Name-Last: Hazen
Title: Remanufactured products purchase intentions and behaviour: Evidence from Malaysia
Abstract: 
 One of the greatest threats to widespread diffusion of closed-loop supply chain (CLSC) practices in support of consumer goods is the lack of consumer acceptance of remanufactured products. Although the preponderance of extant CLSC research historically focused on product reclamation and remanufacturing practices, consumer acceptance of remanufactured products is now receiving more attention. However, significant gaps in the literature remain to include examining actual consumer behaviour in the presence of alternative offerings. Using theory of planned behaviour and data gathered from Malaysia, this research addresses these gaps by examining how consumer attitude, subjective norms and perceived behavioural control with regard to purchasing remanufactured products affect consumer intention to purchase remanufactured consumer electronic products. Then, actual purchase behaviour is compared with purchase intentions to determine if consumers followed through with their intentions. Findings suggest that consumers are most apt to purchase energy-efficient offerings regardless of their original intentions.
Journal: International Journal of Production Research
Pages: 2149-2162
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1194534
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1194534
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Template-Type: ReDIF-Article 1.0
Author-Name: Hossein Beheshti Fakher
Author-X-Name-First: Hossein
Author-X-Name-Last: Beheshti Fakher
Author-Name: Mustapha Nourelfath
Author-X-Name-First: Mustapha
Author-X-Name-Last: Nourelfath
Author-Name: Michel Gendreau
Author-X-Name-First: Michel
Author-X-Name-Last: Gendreau
Title: A cost minimisation model for joint production and maintenance planning under quality constraints
Abstract: 
 In this paper, integrated planning of production, imperfect maintenance and process inspections in a multi-machine system is investigated. This system consists of parallel machines which deteriorate with time and they may shift from a primarily in-control state to a degraded state with a higher defective rate or to a failed state. Maintenance scheduling corresponds to a discrete time age-based imperfect maintenance with a large number of maintenance alternatives. Process inspections are considered to detect the current state of the system. Detecting a deteriorated condition initiates the quality check of the related sub-lots, rework of defective items and a process adjustment that brings the machine in its normal conditions. Production planning includes a capacitated lot-sizing problem with multiple products. We propose a joint approach that coordinates the decisions of the three functions, where the objective function minimises the total cost. Evaluation of costs and interacting factors is presented and two heuristic methods are proposed to solve the problem. The results of the joint model are compared to a non-integrated method and a sensitivity analysis is conducted.
Journal: International Journal of Production Research
Pages: 2163-2176
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1201605
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1201605
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Template-Type: ReDIF-Article 1.0
Author-Name: Rosa Abbou
Author-X-Name-First: Rosa
Author-X-Name-Last: Abbou
Author-Name: Jean Jacques Loiseau
Author-X-Name-First: Jean Jacques
Author-X-Name-Last: Loiseau
Author-Name: Charifa Moussaoui
Author-X-Name-First: Charifa
Author-X-Name-Last: Moussaoui
Title: Robust inventory control of production systems subject to uncertainties on demand and lead times
Abstract: 
 In this paper, we are interested in the controller design for constrained production systems subject to uncertainties on the demand and the production delays. The case study focuses on the inventory regulation problem in production systems which must respond to the customer demands of finite products. Such systems are characterised by the presence of delays due to production processes, the saturation of the input command and the constraints due to the finite capacities of stocks. In our study, we assume that (i) the customer demands are considered to be unknown but bounded by a given value, (ii) both the control input and the inventory output are subject to assigned constraints, and (iii) the production delay is defined with an uncertainty interval. Our model includes two factors that commonly have an impact on the supply chain performances and cause the bullwhip effect: the variability of the customer demand and the uncertainty on the lead time. The proposed approach is based on a saturated predictor-feedback structure, in which the constraints and the physical limitations of the production system are taken into account. The concepts used in this approach are the BIBO-stability and the D$ \mathcal D $-invariance properties. We examine then the bullwhip effect phenomenon, which is an important observation in supply chain management. In order to study the robustness of the control system state feedback, the proposed approach gives necessary and sufficient conditions on the controller parameters, for which the system requirements will be completely met, and permits to ensure the bounds of solutions for the control parameters. The accuracy of the proposed methodology is illustrated through simulation result which demonstrates that the bullwhip effect can be reduced, but not completely eliminated, using a saturated command and a predictor-feedback structure.
Journal: International Journal of Production Research
Pages: 2177-2196
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1214295
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1214295
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Template-Type: ReDIF-Article 1.0
Author-Name: Manuel Díaz-Madroñero
Author-X-Name-First: Manuel
Author-X-Name-Last: Díaz-Madroñero
Author-Name: Josefa Mula
Author-X-Name-First: Josefa
Author-X-Name-Last: Mula
Author-Name: Mariano Jiménez
Author-X-Name-First: Mariano
Author-X-Name-Last: Jiménez
Author-Name: David Peidro
Author-X-Name-First: David
Author-X-Name-Last: Peidro
Title: A rolling horizon approach for material requirement planning under fuzzy lead times
Abstract: 
 This paper proposes a fuzzy multi-objective integer linear programming (FMOILP) approach to model a material requirement planning (MRP) problem with fuzzy lead times. The objective functions minimise the total costs, back-order quantities and idle times of productive resources. Capacity constraints are included by considering overtime resources. Into the crisp MRP multi-objective model, we incorporate the possibility of occurrence of each uncertain lead time using fuzzy numbers. Then FMOILP is transformed into an auxiliary crisp mixed-integer linear programming model by a fuzzy goal programming approach for each fuzzy lead time combination. In order to defuzzify the set of solutions associated with each fuzzy lead time combination, a solution method based on the centre of gravity concept is addressed. Model validation with a numerical example is carried out by a novel rolling horizon procedure where uncertain lead times are updated during each planning period according to the centre of gravity obtained. For illustration purposes, the proposed solution approach is satisfactorily compared to a rolling horizon approach in which lead times are allocated when the possibility of occurrence is established at one.
Journal: International Journal of Production Research
Pages: 2197-2211
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1223382
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1223382
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Template-Type: ReDIF-Article 1.0
Author-Name: Khanh T.P. Nguyen
Author-X-Name-First: Khanh T.P.
Author-X-Name-Last: Nguyen
Author-Name: Thomas Yeung
Author-X-Name-First: Thomas
Author-X-Name-Last: Yeung
Author-Name: Bruno Castanier
Author-X-Name-First: Bruno
Author-X-Name-Last: Castanier
Title: Acquisition of new technology information for maintenance and replacement policies
Abstract: 
 In this paper, we propose the first model that considers the option to acquire information on the profitability of a new technology that is not yet available on the market for asset maintenance and replacement decisions. We consider the uncertainty of future asset characteristics by incorporating information acquisition decisions into a non-stationary Markov decision process framework. Using this framework, we optimise asset maintenance and replacement decisions as well as the optimal timing of new technology adoption. Through mathematical analyses, the monotone properties and convexity of the value function and optimal policy are deduced. Deeper numerical analyses highlight the importance of considering the acquisition of information on future technology when formulating a maintenance and replacement policy for the asset. We also deduce a non-intuitive result: an increase in the arrival probability of new technology does not necessarily make the acquisition of additional information more attractive.
Journal: International Journal of Production Research
Pages: 2212-2231
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1229069
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1229069
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhen Chen
Author-X-Name-First: Zhen
Author-X-Name-Last: Chen
Author-Name: Tangbin Xia
Author-X-Name-First: Tangbin
Author-X-Name-Last: Xia
Author-Name: Ershun Pan
Author-X-Name-First: Ershun
Author-X-Name-Last: Pan
Title: Optimal multi-level classification and preventive maintenance policy for highly reliable products
Abstract: 
 Highly reliable products are widely used in aerospace, automotive, integrated manufacturing and other fields. With increasing market demand and competition, product classification for different segment market segments has become more and more critical. Leading manufacturers are always searching and designing classification policies for highly reliable products. On the other hand, preventive maintenance can improve the operation efficiency of the product, extend the service life and reduce enormous losses brought by failures. These two factors are taken into account by many large enterprises when making sound economical and operational decisions. Therefore, this research proposes a joint multi-level classification and preventive maintenance model (JMCPM model) under age-based maintenance. Different preventive maintenance policies are developed for corresponding level units. Accordingly, the optimal joint policy of multi-level classification and preventive maintenance can be obtained by JMCPM. In this model, degradation-based burn-in is utilised to eliminate defective units and collect degradation data. The degradation data are the basis of classification and can be used to estimate the residual life. Then, for making full use of these data, linear discriminant analysis is employed to design classification rules. The objective of the JMCPM model is to minimise the average cost per unit time by properly choosing the settings of classification and preventive maintenance intervals simultaneously. Finally, a simulation study is carried out for evaluating the performance of the JMCPM model. For an illustration of the proposed model and the methods of inference developed here, a real case involving degradation data from electrical connectors is analysed.
Journal: International Journal of Production Research
Pages: 2232-2250
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1232497
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1232497
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Template-Type: ReDIF-Article 1.0
Author-Name: Lu Chen
Author-X-Name-First: Lu
Author-X-Name-Last: Chen
Author-Name: Boxiao Chen
Author-X-Name-First: Boxiao
Author-X-Name-Last: Chen
Author-Name: Quoc Trung Bui
Author-X-Name-First: Quoc Trung
Author-X-Name-Last: Bui
Author-Name: Minh Hoàng Hà
Author-X-Name-First: Minh Hoàng
Author-X-Name-Last: Hà
Title: Designing service sectors for daily maintenance operations in a road network
Abstract: 
 The problem of designing service sectors in a road network for the organisation of route maintenance activities is addressed in this paper. The decisions involve determining the locations of a set of depots and assigning road segments to the selected depots to form service sectors. Routing operations must be taken into consideration while partitioning service sectors in order to precisely evaluate deadhead and required number of vehicles. The problem is thus formulated as a location-arc routing problem and solved by a branch-and-cut algorithm. A three-stage heuristic algorithm with sector design component is developed to solve the medium- and large-sized problems. The computational experiments demonstrate the effectiveness of the heuristic algorithm, and the superiority of the heuristic algorithm to the exact method in terms of some specific partition evaluation criteria.
Journal: International Journal of Production Research
Pages: 2251-2265
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1233363
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1233363
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Template-Type: ReDIF-Article 1.0
Author-Name: Dingqi Yan
Author-X-Name-First: Dingqi
Author-X-Name-Last: Yan
Author-Name: Qi Zhou
Author-X-Name-First: Qi
Author-X-Name-Last: Zhou
Author-Name: Jianzhou Wang
Author-X-Name-First: Jianzhou
Author-X-Name-Last: Wang
Author-Name: Na Zhang
Author-X-Name-First: Na
Author-X-Name-Last: Zhang
Title: Bayesian regularisation neural network based on artificial intelligence optimisation
Abstract: 
 Stock prediction is generally considered to be challenging and known for its high noise and strong nonlinearities in financial time series analysis. However, current forecasting models ignore the importance of model parameter optimisation and the use of recent data. In this article, a novel forecasting approach with a Bayesian-regularised artificial neural networks (BR-ANN) was proposed. The weight of the proposed model (BR-ANN) is determined by the particle swarm optimisation (PSO) algorithm. Daily market prices and financial technical indicators are utilised as inputs to predict the one day future closing price of the Shanghai (in China) composite index. The Bayesian-regularised network uses a probabilistic nature for the network weights and can reduce the potential for over-fitting and over-training. Our empirical study and the results of our K-line theory analysis indicate that PSO is determined to be an effective algorithm to optimise the parameters of the Bayesian neural network compared with other well-known prediction algorithms. In particular, the PSO model is more reliable than the simple Bayesian regularisation neural network near the local maximum value.
Journal: International Journal of Production Research
Pages: 2266-2287
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1237785
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1237785
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Template-Type: ReDIF-Article 1.0
Author-Name: Khalil Negrichi
Author-X-Name-First: Khalil
Author-X-Name-Last: Negrichi
Author-Name: Maria Di Mascolo
Author-X-Name-First: Maria
Author-X-Name-Last: Di Mascolo
Author-Name: Jean-Marie Flaus
Author-X-Name-First: Jean-Marie
Author-X-Name-Last: Flaus
Title: A model based approach to assess the performance of production systems in degraded mode
Abstract: 
 Nowadays production systems are asked to perform their activities in a high uncertainty environment and to guarantee their performance in this environment. Therefore, they are asked to master risks that are part of their daily activities, to maintain the performance which is considered as their key success factor. Risks may cause serious effects that threaten the production systems and degrade their performance. Nevertheless, we cannot estimate the degradation that a risk may cause to system performance, since risk analysis methods found in the literature do not allow simulating the behaviour of the system in degraded mode. In order to help production systems to assess their performance in risk situations, we propose in this paper a model-based approach that enables assessing the performance of production systems in degraded mode. Our approach is based on function, interaction, structure (FIS) modelling framework that enables modelling complex system and its failures. The resulting model is converted into an executable simulation model based on a new class of Petri Nets (PNs) called predicate-transition, prioritised, synchronous (PTPS) PN. The obtained simulation model is then executed in order to obtain performance indicators in degraded mode. This tool is used during the system design, in order to study the impact of risks on the designed production system performance. It is also used to study an existing production system in order to analyse and optimise its behaviour in degraded mode. In this article, we present our tool and apply it to a special case of production systems which is a hospital sterilisation system.
Journal: International Journal of Production Research
Pages: 2288-2303
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1237788
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1237788
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Template-Type: ReDIF-Article 1.0
Author-Name: Raed Kontar
Author-X-Name-First: Raed
Author-X-Name-Last: Kontar
Author-Name: Shiyu Zhou
Author-X-Name-First: Shiyu
Author-X-Name-Last: Zhou
Author-Name: John Horst
Author-X-Name-First: John
Author-X-Name-Last: Horst
Title: Estimation and monitoring of key performance indicators of manufacturing systems using the multi-output Gaussian process
Abstract: 
 Recently, the estimation and monitoring of manufacturing key performance indicators (KPIs) have drawn significant attention. In this article, a KPI estimation and monitoring method using a multi-output Gaussian process (MGP) is proposed. The Gaussian process (GP) is an effective non-parametric flexible tool for data-driven statistical modelling for various systems. The unique features of the proposed method is that the MGP enjoys the high flexibility and desirable analytical properties of the GP while also capturing the correlation between different KPIs, thus providing better estimation accuracy and error quantification. The advantageous features of the proposed method are demonstrated through a numerical study as well as a case study with real world data in the estimation and monitoring of throughput for a multiclass production operation.
Journal: International Journal of Production Research
Pages: 2304-2319
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1237791
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1237791
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Template-Type: ReDIF-Article 1.0
Author-Name: Anna Martí Bigorra
Author-X-Name-First: Anna
Author-X-Name-Last: Martí Bigorra
Author-Name: Ove Isaksson
Author-X-Name-First: Ove
Author-X-Name-Last: Isaksson
Title: Combining customer needs and the customer’s way of using the product to set customer-focused targets in the House of Quality
Abstract: 
 An increasing number of products are equipped with software and sensors. This suggests that, in order to deliver more customised performance, future products will be developed to accommodate systems that supply information on how these products are used. Today, information on the customer’s way of using a product is seldom factored into product design, but the opportunities for making use of it are increasing dramatically due to the amount of available data that can be logged. The proposed methodology is to formulate Customer Needs at a detailed level to be able to link customer satisfaction with a clear interface to the Design Requirements. These links are obtained by combining information acquired by means of surveys, among other methodologies, as well as usage data from customer products. The method is based on the planning House of Quality and also takes cost and risk into consideration. Risk is estimated using the Analytical Hierarchy Process, whereby a hierarchy of the most relevant customer information is constructed to make designers aware of how customer-focused the design process is. To validate the proposed methodology an illustrative example is presented. Results show that the method provides valuable information that enables the company to remain customer-focused during the whole process but also when strategic decisions on price and product launch are made.
Journal: International Journal of Production Research
Pages: 2320-2335
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1238114
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1238114
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Template-Type: ReDIF-Article 1.0
Author-Name: Mario José Basallo-Triana
Author-X-Name-First: Mario José
Author-X-Name-Last: Basallo-Triana
Author-Name: Jesús Andrés Rodríguez-Sarasty
Author-X-Name-First: Jesús Andrés
Author-X-Name-Last: Rodríguez-Sarasty
Author-Name: Hernán Darío Benitez-Restrepo
Author-X-Name-First: Hernán Darío
Author-X-Name-Last: Benitez-Restrepo
Title: Analogue-based demand forecasting of short life-cycle products: a regression approach and a comprehensive assessment
Abstract: 
 In several industries, global competition, increasing customer expectations and technological innovations tend to accelerate product life-cycles. In this changing environment, traditional forecasting methods tend to be ineffective as a consequence of the transient and highly uncertain demand of short life-cycle products (SLCP), and the scarcity of sales data. To address this challenge, we present a methodology to forecast SLCP demand using time series of similar products referred to as analogies. Linear regression and clustering techniques are used for the selection and weighting of suitable analogies. The proposed methodology is tested against seven analogue-based forecasting methods, including two implementations of non-linear regression methods. In different sets of time series, our methodology attained more accurate forecasts with short processing times compared with state-of-the-art methods. Such results reveal promising applications of combined regression and clustering techniques as simple and effective forecasting tools for supporting replenishment decisions for SLCP.
Journal: International Journal of Production Research
Pages: 2336-2350
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1241443
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1241443
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Template-Type: ReDIF-Article 1.0
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Author-Name: Zih-Huei Wang
Author-X-Name-First: Zih-Huei
Author-X-Name-Last: Wang
Title: Developing a variables multiple dependent state sampling plan with simultaneous consideration of process yield and quality loss
Abstract: 
 Acceptance sampling plans have been utilised predominantly for the inspection of outgoing and incoming lots; these plans provide effective rules to vendors and buyers for making decisions on product acceptance or rejection. Multiple dependent state (MDS) sampling plans have been developed for lot sentencing and are shown to be more efficient than traditional single sampling plans. The decision criteria of MDS sampling plans are based on sample information not only from the current lot but also from preceding lots. In this study, we develop a variables MDS sampling plan for lot sentencing based on the advanced process capability index, which was developed by combining the merits of the yield-based index and loss-based index. The operating characteristic function of the developed plan is derived based on the exact sampling distribution. The determination of plan parameters is formulated as an optimisation model with non-linear constraints, where the objective is to minimise the sample size required for inspection and the constraints are set by the vendor and the buyer to satisfy the desired quality levels and allowable risks. The performance of the developed plan is examined and compared with traditional sampling plans. A step-by-step procedure is provided, and the parameters of the plan under various conditions are tabulated for practical applications.
Journal: International Journal of Production Research
Pages: 2351-2364
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1244360
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1244360
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Template-Type: ReDIF-Article 1.0
Author-Name: Kuen-Suan Chen
Author-X-Name-First: Kuen-Suan
Author-X-Name-Last: Chen
Author-Name: Hsi-Tien Chen
Author-X-Name-First: Hsi-Tien
Author-X-Name-Last: Chen
Author-Name: Tsang-Chuan Chang
Author-X-Name-First: Tsang-Chuan
Author-X-Name-Last: Chang
Title: The construction and application of Six Sigma quality indices
Abstract: 
 Process quality is the primary factor in facilitating product sales. In accordance with the concept of Six Sigma, numerous studies have employed process capability indices for the determination of process quality levels. Unfortunately, existing indices present only a range of quality levels rather than a specific quality level value. This paper aims to propose Six Sigma quality indices for the assessment of quality levels associated with unilateral as well as bilateral specifications. To ensure the reliability in process assessment, we employ the lower confidence limit of the indices to serve as a standard and develop a process quality analysis chart for the simultaneous evaluation of larger-the-better, smaller-the-better and nominal-the-best quality characteristics with the aim of identifying the causes of sub-standard quality. The resulting chart also provides a valuable reference by which to guide efforts aimed at improvement. Finally, we present three cases and numerical experiments to demonstrate the practical applicability of the proposed method.
Journal: International Journal of Production Research
Pages: 2365-2384
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1246763
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1246763
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Template-Type: ReDIF-Article 1.0
Author-Name: Jinho Kim
Author-X-Name-First: Jinho
Author-X-Name-Last: Kim
Author-Name: Myong K. Jeong
Author-X-Name-First: Myong K.
Author-X-Name-Last: Jeong
Author-Name: Elsayed A. Elsayed
Author-X-Name-First: Elsayed A.
Author-X-Name-Last: Elsayed
Title: Monitoring multistage processes with autocorrelated observations
Abstract: 
 In multistage manufacturing processes, autocorrelations within stages over time are prevalent and the classical control charts are often ineffective in monitoring such processes. In this paper, we derive a linear state space model of an autocorrelated multistage process as a vector autoregressive process, and construct novel multivariate control charts, CBAM and Conditional-based MEWMA, for detecting the mean changes in a multistage process based on a projection scheme by incorporating in-control stage information. When in-control stages are unknown, finding in-control stages is a challenging issue due to the autocorrelations over time and the sequential correlations between stages. To overcome this difficulty, we propose a conditional-based selection that chooses stages with strong evidences of in-control stage using the cascading property of multistage processes. The information of selected stages is effectively utilised in obtaining powerful test statistics for detecting a mean change. The performance of the proposed charts is compared with other existing procedures under different scenarios. Both simulation studies and a real example show the effectiveness of the conditional-based charts in detecting a wide range of small mean shifts compared with the other existing control charts.
Journal: International Journal of Production Research
Pages: 2385-2396
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1247996
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1247996
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Template-Type: ReDIF-Article 1.0
Author-Name: Marien A. Graham
Author-X-Name-First: Marien A.
Author-X-Name-Last: Graham
Author-Name: Amitava Mukherjee
Author-X-Name-First: Amitava
Author-X-Name-Last: Mukherjee
Author-Name: Subhabrata Chakraborti
Author-X-Name-First: Subhabrata
Author-X-Name-Last: Chakraborti
Title: Design and implementation issues for a class of distribution-free Phase II EWMA exceedance control charts
Abstract: 
 Distribution-free (nonparametric) control charts can play an essential role in process monitoring when there is dearth of information about the underlying distribution. In this paper, we study various aspects related to an efficient design and execution of a class of nonparametric Phase II exponentially weighted moving average (denoted by NPEWMA) charts based on exceedance statistics. The choice of the Phase I (reference) sample order statistic used in the design of the control chart is investigated. We use the exact time-varying control limits and the median run-length as the metric in an in-depth performance study. Based on the performance of the chart, we outline implementation strategies and make recommendations for selecting this order statistic from a practical point of view and provide illustrations with a data-set. We conclude with a summary and some remarks.
Journal: International Journal of Production Research
Pages: 2397-2430
Issue: 8
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1249428
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1249428
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Template-Type: ReDIF-Article 1.0
Author-Name: Ali Allahverdi
Author-X-Name-First: Ali
Author-X-Name-Last: Allahverdi
Author-Name: Erwin Pesch
Author-X-Name-First: Erwin
Author-X-Name-Last: Pesch
Author-Name: Michael Pinedo
Author-X-Name-First: Michael
Author-X-Name-Last: Pinedo
Author-Name: Frank Werner
Author-X-Name-First: Frank
Author-X-Name-Last: Werner
Title: Scheduling in manufacturing systems: new trends and perspectives
Journal: International Journal of Production Research
Pages: 6333-6335
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2018.1504252
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504252
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:19:p:6333-6335




Template-Type: ReDIF-Article 1.0
Author-Name: Tsung-Chyan Lai
Author-X-Name-First: Tsung-Chyan
Author-X-Name-Last: Lai
Author-Name: Yuri N. Sotskov
Author-X-Name-First: Yuri N.
Author-X-Name-Last: Sotskov
Author-Name: Natalja G. Egorova
Author-X-Name-First: Natalja G.
Author-X-Name-Last: Egorova
Author-Name: Frank Werner
Author-X-Name-First: Frank
Author-X-Name-Last: Werner
Title: The optimality box in uncertain data for minimising the sum of the weighted job completion times
Abstract: 
 An uncertain single-machine scheduling problem is considered, where the processing time of a job can take any real value from a given segment. The criterion is to minimise the total weighted completion time of the n jobs, a weight being associated with each given job. We use the optimality box as a stability measure of the optimal schedule and derive an O(n)-algorithm for calculating the optimality box for a fixed permutation of the given jobs. We investigate properties of the optimality box using blocks of the jobs. If each job belongs to a single block, then the largest optimality box may be constructed in O(nlogn)
$ O(n \log n) $
 time. For the general case, we apply dynamic programming for constructing a job permutation with the largest optimality box. The computational results for finding a permutation with the largest optimality box show that such a permutation is close to an optimal one, which can be determined after completing the jobs when their processing times became known.
Journal: International Journal of Production Research
Pages: 6336-6362
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2017.1398426
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398426
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Template-Type: ReDIF-Article 1.0
Author-Name: Pablo Valledor
Author-X-Name-First: Pablo
Author-X-Name-Last: Valledor
Author-Name: Alberto Gomez
Author-X-Name-First: Alberto
Author-X-Name-Last: Gomez
Author-Name: Paolo Priore
Author-X-Name-First: Paolo
Author-X-Name-Last: Priore
Author-Name: Javier Puente
Author-X-Name-First: Javier
Author-X-Name-Last: Puente
Title: Solving multi-objective rescheduling problems in dynamic permutation flow shop environments with disruptions
Abstract: 
 In multi-objective optimisation problems, optimal decisions need to be made in the presence of trade-offs among conflicting objectives which may sometimes be expressed in different units of measure. This makes it difficult to reduce the problem to a single-objective optimisation. Furthermore, when disruptive changes emerge in manufacturing environments, such as the arrival of new jobs or machine breakdowns, the scheduling system should be adapted by responding quickly. In this paper, we propose a rescheduling architecture for solving the problem based on a predictive-reactive strategy and a new method to calculate the reactive schedule in each rescheduling period. Additionally, we developed a methodology that allows the use of multi-objective performance metrics to evaluate dispatching rules. These rules are applied at a benchmark specifically designed for this paper considering three objective functions: makespan, total weighted tardiness and stability. Three types of disruptions are also considered: arrivals of new jobs, machine breakdowns and variations in job processing times. Results showed that the RANDOM rule provides a better behaviour compared to other evaluated rules and a lower ratio of non-dominated solutions compared to ATC (apparent tardiness cost) and FIFO (first-in-first-out) rules. Moreover, the behaviour of the hypervolume metric depends on the problem dimensions.
Journal: International Journal of Production Research
Pages: 6363-6377
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2018.1468095
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1468095
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Template-Type: ReDIF-Article 1.0
Author-Name: Ronghua Meng
Author-X-Name-First: Ronghua
Author-X-Name-Last: Meng
Author-Name: Yunqing Rao
Author-X-Name-First: Yunqing
Author-X-Name-Last: Rao
Author-Name: Yun Zheng
Author-X-Name-First: Yun
Author-X-Name-Last: Zheng
Author-Name: Dezhong Qi
Author-X-Name-First: Dezhong
Author-X-Name-Last: Qi
Title: Modelling and solving algorithm for two-stage scheduling of construction component manufacturing with machining and welding process
Abstract: 
 This paper focuses on a two-stage machining and welding scheduling problem based on an investigation at a structural metal manufacturing plant, aiming to minimise the total makespan. Several parts processed at Stage one according to classical job-shop scheduling are grouped into a single construction component at the second welding stage. Fabrication of the construction component cannot begin until all comprising parts have been completed at Stage one. This paper establishes a novel mathematic model to minimise the total makespan by mainly considering the dominance relationship between the construction component and the corresponding parts. In order to solve this two-stage problem, we propose an improved harmony search algorithm. A local search method is applied to the best vector at each iteration, so that a more optimal vector can be subsequently realised. The average value, minimum value, relative percentage deviation and standard deviation are discussed in the experimental section, and the proposed local best harmony search algorithm outperforms the genetic algorithm, immune algorithm and harmony search algorithm without local search. Moreover, six optimal solutions are given as Gantt charts, which vividly illustrate that the mathematical model established in this paper can facilitate the development of a better scheduling scheme.
Journal: International Journal of Production Research
Pages: 6378-6390
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2017.1349949
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1349949
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrzej Bo&#x17C;ek
Author-X-Name-First: Andrzej
Author-X-Name-Last: Bo&#x17C;ek
Author-Name: Frank Werner
Author-X-Name-First: Frank
Author-X-Name-Last: Werner
Title: Flexible job shop scheduling with lot streaming and sublot size optimisation
Abstract: 
 Models and optimisation approaches are developed for a flexible job shop scheduling problem with lot streaming and lot sizing of the variable sublots. A two-stage optimisation procedure is proposed. First, the makespan value is minimised with the smallest sublots defined for the problem instance. This makes it possible to shorten the makespan significantly, because each sublot is transferred separately to the next operation of a job. In the second stage, the sizes of the sublots are maximised without increasing the obtained makespan value. In this way, the quantity of sublots and transport activities is limited together with the related manufacturing cost. Two objectives are defined for the second stage. The first one is the maximisation of the sum of the sublot sizes of all operations, the second one is the maximisation of the number of the operations which do not need to be split at all. Mixed-integer linear programming, constraint programming and graph-based models are implemented for the problem. Two optimisation approaches are developed and compared in computational experiments for each stage and objective, one approach is based on a third-party solver, and the second one on an independent own implementation, namely a tabu search and a greedy constructive heuristic.
Journal: International Journal of Production Research
Pages: 6391-6411
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2017.1346322
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346322
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Template-Type: ReDIF-Article 1.0
Author-Name: Renato de Matta
Author-X-Name-First: Renato
Author-X-Name-Last: de Matta
Title: Scheduling a manufacturing process with restrictions on resource availability
Abstract: 
 This paper examines the scheduling of a drug packaging operation which requires assigning resources to production lines during set-up in order to satisfy product specifications. We present mixed integer programming models of the problem and develop a Lagrangian heuristic to solve the models. Real data from a drug company and randomly generated data are used to test the models. Results show the efficacy of our solution approach to find good feasible schedules. We discuss some of the practical benefits and potential issues about the production schedules obtained using the models.
Journal: International Journal of Production Research
Pages: 6412-6429
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2017.1384583
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1384583
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Template-Type: ReDIF-Article 1.0
Author-Name: Durga Prasad
Author-X-Name-First: Durga
Author-X-Name-Last: Prasad
Author-Name: S. C. Jayswal
Author-X-Name-First: S. C.
Author-X-Name-Last: Jayswal
Title: Reconfigurability consideration and scheduling of products in a manufacturing industry
Abstract: 
 Reconfigurable manufacturing system is a new type of manufacturing system which can change its capacity and functionality very easily and quickly whenever required. RMS (reconfigurable manufacturing system) has capacity and functionality exactly what is required. RMS is adjustable to the fluctuating demands and it can be easily upgraded with new process technology. Reconfigurability of a manufacturing system is measured in terms of cost, effort and time. It is the ability of a manufacturing system to be reconfigured quickly with low reconfiguration effort at low cost. In the present work, reconfigurability has been considered in Continental Automotive Components Pvt. Ltd. on the basis of RMS principles. A modified reconfigurable layout has been proposed for an assembly line and scheduling of the products has been done for the criteria reconfiguration effort, profit over cost and due date. Scheduling of the products has been done using the integrated approach of Shannon entropy and RIM (Reference Ideal Method). R program has been written for scheduling. Sensitivity analysis has been conducted for the problem.
Journal: International Journal of Production Research
Pages: 6430-6449
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2017.1334979
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1334979
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehdi Foumani
Author-X-Name-First: Mehdi
Author-X-Name-Last: Foumani
Author-Name: Asghar Moeini
Author-X-Name-First: Asghar
Author-X-Name-Last: Moeini
Author-Name: Michael Haythorpe
Author-X-Name-First: Michael
Author-X-Name-Last: Haythorpe
Author-Name: Kate Smith-Miles
Author-X-Name-First: Kate
Author-X-Name-Last: Smith-Miles
Title: A cross-entropy method for optimising robotic automated storage and retrieval systems
Abstract: 
 In this paper, we consider a robotic automated storage and retrieval system (AS/RS) where a Cartesian robot picks and palletises items onto a mixed pallet for any order. This robotic AS/RS not only retrieves orders in an optimal sequence, but also creates an optimal store ready pallet of any order. Adapting the Travelling Salesman Problem to warehousing, the decision to be made includes finding the optimal sequence of orders, and optimal sequence of items inside each order, that jointly minimise total travel times. In the first phase, as a control problem, we develop an avoidance strategy for the robot (or automatic stacker crane) movement sequence. This approach detects the collision occurrence causing unsafe handling of hazardous items and prevents the occurrence of it by a collision-free robot movement sequence. Due to the complexity of the problem, the second phase is attacked by a Cross-Entropy (CE) method. To evaluate the performance of the CE method, a computational analysis is performed over various test problems. The results obtained from the CE method are compared to those of the optimal solutions obtained using CPLEX. The results indicate high performance of the solution procedure to solve the sequencing problem of robotic AS/RSs.
Journal: International Journal of Production Research
Pages: 6450-6472
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2018.1456692
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1456692
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Boris Sokolov
Author-X-Name-First: Boris
Author-X-Name-Last: Sokolov
Title: Scheduling of recovery actions in the supply chain with resilience analysis considerations
Abstract: 
 Supply chain engineering models with resilience considerations have been mostly focused on disruption impact quantification within one analysis layer, such as supply chain design or planning. Performance impact of disruptions has been typically analysed without scheduling of recovery actions. Taking into account schedule recovery actions and their duration times, this study extends the existing literature to supply chain scheduling and resilience analysis by an explicit integration of the optimal schedule recovery policy and supply chain resilience. In particular, we compute a schedule optimal control policy and analyse the performance of this policy by varying the perturbation vector and representing the outcomes of variations in the form of an attainable set. We propose a scheduling model that considers the coordination of recovery actions in the supply chain. Further, we suggest a resilience index by using the notion of attainable sets. The attainable sets are known in control theory; their calculation is based on the schedule control model results and the minimax regret approach for continuous time parameters given by intervals. We show that the proposed indicator can be used to estimate the impact of disruption and recovery dynamics on the achievement of planned performance in the supply chain.
Journal: International Journal of Production Research
Pages: 6473-6490
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2017.1401747
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401747
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Template-Type: ReDIF-Article 1.0
Author-Name: Changchun Liu
Author-X-Name-First: Changchun
Author-X-Name-Last: Liu
Author-Name: Xi Xiang
Author-X-Name-First: Xi
Author-X-Name-Last: Xiang
Author-Name: Li Zheng
Author-X-Name-First: Li
Author-X-Name-Last: Zheng
Author-Name: Jing Ma
Author-X-Name-First: Jing
Author-X-Name-Last: Ma
Title: An integrated model for multi-resource constrained scheduling problem considering multi-product and resource-sharing
Abstract: 
 This paper studies a multi-resource constrained scheduling problem considering multi-product and resource-sharing in the manufacturing supply chain, in which many independent production units coordinate with a truck resource manager. A mixed integer programming model is formulated to minimise the total system cost and some analytical properties are proposed to tighten the model. A Lagrangian relaxation-based heuristic with several enhancements, e.g. warm startup, approximating solve and parallel computation of subproblems, is proposed to solve the model. Finally, computational experiments are conducted to verify that (i) the proposed method has a better performance in both objective and CPU time than CPLEX, (ii) all three enhancements can help reduce the total computation time and (iii) a certain degree of resource-sharing can help reduce the total cost of the system.
Journal: International Journal of Production Research
Pages: 6491-6511
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2017.1363428
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1363428
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Template-Type: ReDIF-Article 1.0
Author-Name: Weiwei Chen
Author-X-Name-First: Weiwei
Author-X-Name-Last: Chen
Author-Name: Lei Lei
Author-X-Name-First: Lei
Author-X-Name-Last: Lei
Author-Name: Zhengwei Wang
Author-X-Name-First: Zhengwei
Author-X-Name-Last: Wang
Author-Name: Mingfei Teng
Author-X-Name-First: Mingfei
Author-X-Name-Last: Teng
Author-Name: Junming Liu
Author-X-Name-First: Junming
Author-X-Name-Last: Liu
Title: Coordinating supplier selection and project scheduling in resource-constrained construction supply chains
Abstract: 
 In this paper, we study the problem of coordinating supplier selection and project scheduling, motivated by a real-life operational challenge encountered in the construction industry. In particular, we consider a project network consisting of multiple concurrent projects, with the objective of minimising the total tardiness of all projects. These projects are independent in operation but are subject to shared suppliers and the final quality inspection by the same committee, which then leads to the need for project review sequencing. The earliest starting time of each activity in a project depends on the availability of required resources (both renewable and non-renewable), as well as the activity precedence constraints. We formulate this problem as a mixed integer linear programming model, and propose a mathematical programming-based heuristic to solve the model. The heuristic decomposes the model into subproblems, and solves the subproblems through an iterative process. Each subproblem has a much smaller size and can be solved quickly and independently. The information obtained in solving subproblems is used to guide the search process. Numerical examples show the computational effectiveness of the proposed heuristic, and the benefits of coordination.
Journal: International Journal of Production Research
Pages: 6512-6526
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2018.1436782
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1436782
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Mahdi Nasiri
Author-X-Name-First: Mohammad Mahdi
Author-X-Name-Last: Nasiri
Author-Name: Ali Rahbari
Author-X-Name-First: Ali
Author-X-Name-Last: Rahbari
Author-Name: Frank Werner
Author-X-Name-First: Frank
Author-X-Name-Last: Werner
Author-Name: Roya Karimi
Author-X-Name-First: Roya
Author-X-Name-Last: Karimi
Title: Incorporating supplier selection and order allocation into the vehicle routing and multi-cross-dock scheduling problem
Abstract: 
 In the vehicle routing problem with cross-docking (VRPCD), it is assumed that the selected suppliers and the quantity of the products purchased from each supplier are known. This paper presents an MILP model which incorporates supplier selection and order allocation into the VRPCD in a multi-cross-dock system minimising the total costs, including purchasing, transportation, cross-docking, inventory and early/tardy delivery penalty costs. The sensitivity of the model on the key parameters of the objective function is analysed and the supply decisions are evaluated when the coefficients of the distribution cost are changed. A two-stage solution algorithm (TSSA) is proposed and the results of the TSSA for small-sized instances are compared with the exact solutions. Finally, a large-sized real case of an urban freight transport is solved using the TSSA.
Journal: International Journal of Production Research
Pages: 6527-6552
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2018.1471241
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471241
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Template-Type: ReDIF-Article 1.0
Author-Name: Liang Qu
Author-X-Name-First: Liang
Author-X-Name-Last: Qu
Author-Name: Shuguang He
Author-X-Name-First: Shuguang
Author-X-Name-Last: He
Author-Name: Michael B. C. Khoo
Author-X-Name-First: Michael B. C.
Author-X-Name-Last: Khoo
Author-Name: Philippe Castagliola
Author-X-Name-First: Philippe
Author-X-Name-Last: Castagliola
Title: A CUSUM chart for detecting the intensity ratio of negative events
Abstract: 
 This paper developed a single cumulative sum (CUSUM) scheme, called the UCUSUM chart, for simultaneously detecting the size N and time interval T of an event. The new chart used the information of size and frequency of the event and the UCUSUM chart is carried out using the only one statistic U, which contains both T and N; on the other hand, the UCUSUM chart could allocate the detection power to the T shifts and the N shifts. The results present that the UCUSUM chart is significantly powerful compared to other charts which are in the current research with either the time interval T or with the size N. The UCUSUM chart could be applied in many areas including industries and non-industries and the performance of the new chart shows it is much effective in example.
Journal: International Journal of Production Research
Pages: 6553-6567
Issue: 19
Volume: 56
Year: 2018
Month: 10
X-DOI: 10.1080/00207543.2017.1398423
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398423
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Template-Type: ReDIF-Article 1.0
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Author-Name: Robert Gao
Author-X-Name-First: Robert
Author-X-Name-Last: Gao
Author-Name: Andrew Y. C. Nee
Author-X-Name-First: Andrew Y. C.
Author-X-Name-Last: Nee
Title: Sustainable cybernetic manufacturing
Journal: International Journal of Production Research
Pages: 3799-3801
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2019.1598153
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598153
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Template-Type: ReDIF-Article 1.0
Author-Name: Daniel Alejandro Rossit
Author-X-Name-First: Daniel Alejandro
Author-X-Name-Last: Rossit
Author-Name: Fernando Tohmé
Author-X-Name-First: Fernando
Author-X-Name-Last: Tohmé
Author-Name: Mariano Frutos
Author-X-Name-First: Mariano
Author-X-Name-Last: Frutos
Title: Industry 4.0: Smart Scheduling
Abstract: 
 Smart Manufacturing and Industry 4.0 production environments integrate the physical and decisional aspects of manufacturing processes into autonomous and decentralised systems. One of the main aspects in these systems is production planning, in particular scheduling operations on machines. We introduce here a new decision-making schema, Smart Scheduling, intended to yield flexible and efficient production schedules on the fly, taking advantage of the features of these new environments. The ability to face unforeseen and disruptive events is one of the main improvements in our proposed schema, which uses an efficient screening procedure (Tolerance Scheduling) to lessen the need of rescheduling in the face of those events.
Journal: International Journal of Production Research
Pages: 3802-3813
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1504248
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1504248
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Xin Liu
Author-X-Name-First: Xin
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Service-oriented robust parallel machine scheduling
Abstract: 
 Stochastic scheduling optimisation is a hot and challenging research topic with wide applications. Most existing works on stochastic parallel machine scheduling address uncertain processing time, and assume that its probability distribution is known or can be correctly estimated. This paper investigates a stochastic parallel machine scheduling problem, and assumes that only the mean and covariance matrix of the processing times are known, due to the lack of historical data. The objective is to maximise the service level, which measures the probability of all jobs jointly completed before or at their due dates. For the problem, a new distributionally robust formulation is proposed, and two model-based approaches are developed: (1) a sample average approximation method is adapted, (2) a hierarchical approach based on mixed integer second-order cone programming (MI-SOCP) formulation is designed. To evaluate and compare the performance of the two approaches, randomly generated instances are tested. Computational results show that our proposed MI-SOCP-based hierarchical approach can obtain higher solution quality with less computational effect.
Journal: International Journal of Production Research
Pages: 3814-3830
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1497311
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1497311
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Template-Type: ReDIF-Article 1.0
Author-Name: Chengkuan Zeng
Author-X-Name-First: Chengkuan
Author-X-Name-Last: Zeng
Author-Name: Jiafu Tang
Author-X-Name-First: Jiafu
Author-X-Name-Last: Tang
Author-Name: Zhi-Ping Fan
Author-X-Name-First: Zhi-Ping
Author-X-Name-Last: Fan
Title: Auction-based cooperation mechanism for cell part scheduling with transportation capacity constraint
Abstract: 
 This paper addresses cell part scheduling (CPS) problem with transportation capacity constraint. In the problem, parts may need to visit different cells, they have to be transferred by automated guided vehicle (AGV). The objective is to minimise the over-all process make-span. An integer nonlinear programming (INLP) model is formulated to allocate the machines, AGVs and schedule all parts. A reasonable transportation mode is presented, and an auction-based heuristic approach is proposed to solve the problem, which focuses on dealing with cooperation between machines and AGVs during processing and transferring parts. The auction consists of two aspects: auction for AGV and auction for machine. In both auctions, AGVs and machines act as auctioneers respectively, and parts act as bidders. A new improved disjunctive graph model is developed to optimise the feasible solutions obtained by auction-based approach. Numerical experiments were conducted to test the auction-based approach and improved disjunctive graph model. The results demonstrate the effectiveness of proposed auction-based approach and improved disjunctive graph model, also indicate influence of the capacity of AGV on scheduling parts.
Journal: International Journal of Production Research
Pages: 3831-3846
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1513660
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1513660
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Template-Type: ReDIF-Article 1.0
Author-Name: Feng Li
Author-X-Name-First: Feng
Author-X-Name-Last: Li
Author-Name: Lin Zhang
Author-X-Name-First: Lin
Author-X-Name-Last: Zhang
Author-Name: T. W. Liao
Author-X-Name-First: T. W.
Author-X-Name-Last: Liao
Author-Name: Yongkui Liu
Author-X-Name-First: Yongkui
Author-X-Name-Last: Liu
Title: Multi-objective optimisation of multi-task scheduling in cloud manufacturing
Abstract: 
 Cloud manufacturing is a consumer-centric requirement-driven manufacturing paradigm that integrates distributed resources for providing services to consumers in an on-demand manner. Scheduling of multiple tasks is an important technical means for satisfying consumer requirements in cloud manufacturing. However, high individualised requirements and the associated complex task structures complicate the task scheduling in cloud manufacturing. This paper establishes a more comprehensive model for scheduling multiple distinct tasks with complicated manufacturing processes. The hierarchical relationships (a mixture of dependency and independency) of subtasks within tasks are considered. The objectives involve three kinds of time and cost factors, namely processing time, setup time, transfer time and the respective cost. In addition, service quality is also considered into the optimisation objective. Two multi-objective-meta-heuristic algorithms, i.e. ACO-based multi-objective algorithm (MACO) and NSGA-II-based multi-objective algorithm (MGA), are designed to solve the scheduling problem. A detailed analysis of the performance of the two algorithms is performed by applying them to several different scheduling instances. Experimental results indicate that in most cases the MACO algorithm can obtain a more diverse set of Pareto solutions hence offering more alternatives to meet widely different users’ needs.
Journal: International Journal of Production Research
Pages: 3847-3863
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1538579
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1538579
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Template-Type: ReDIF-Article 1.0
Author-Name: Ullah Saif
Author-X-Name-First: Ullah
Author-X-Name-Last: Saif
Author-Name: Zailin Guan
Author-X-Name-First: Zailin
Author-X-Name-Last: Guan
Author-Name: Chuangjian Wang
Author-X-Name-First: Chuangjian
Author-X-Name-Last: Wang
Author-Name: Cong He
Author-X-Name-First: Cong
Author-X-Name-Last: He
Author-Name: Lei Yue
Author-X-Name-First: Lei
Author-X-Name-Last: Yue
Author-Name: Jahanzaib Mirza
Author-X-Name-First: Jahanzaib
Author-X-Name-Last: Mirza
Title: Drum buffer rope-based heuristic for multi-level rolling horizon planning in mixed model production
Abstract: 
 In recent years mixed model production industries are highly interested to apply Industry 4.0 and internet of things. The existing planning and scheduling methods are not efficient enough to make intelligent plans. Therefore, there is a strong need to develop planning and scheduling methods which can timely update the medium level and lower level schedules and can be utilised for Industry 4.0. Drum buffer rope (DBR) is a direct application of theory of constraint, is utilised here to make an efficient plan. Current research proposed a DBR-based heuristic algorithm (DBR-HA) for multi-level planning considering shifting bottleneck resource to make efficient schedule in rolling horizon in mixed model production environment and utilise capacity constraint resource (CCR) at maximum. The proposed DBR-HA identifies the drum, i.e. CCR, and make an efficient schedule on it in each lower level scheduling period and utilise a feedback method to update customer orders in each medium level planning horizon. The proposed method is useful to implement Industry 4.0 in mixed model industries and update their plan and schedule in real time. The performance of the proposed DBR-HA algorithm is measured and compared with the performance of the basic scheduling rules used in the Case Company based on a Case Company problem data. Results indicate that the proposed method is significant to reduce the gap between medium level planning and lower level schedules and gives an efficient medium level plan and lower level schedule in each planning horizon as compared to the other methods.
Journal: International Journal of Production Research
Pages: 3864-3891
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2019.1569272
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1569272
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Template-Type: ReDIF-Article 1.0
Author-Name: Xi Vincent Wang
Author-X-Name-First: Xi Vincent
Author-X-Name-Last: Wang
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Title: Digital twin-based WEEE recycling, recovery and remanufacturing in the background of Industry 4.0
Abstract: 
 The waste electrical and electronic equipment (WEEE) recovery can be categorised into two types, i.e. recycling at the material level and remanufacturing at the component level. However, the WEEE recovery is facing enormous challenges of diversified individuals, lack of product knowledge, distributed location, and so forth. On the other hand, the latest ICT provides new methods and opportunities for industrial operation and management. Thus, in this research digital twin and Industry 4.0 enablers are introduced to the WEEE remanufacturing industry. The goal is to provide an integrated and reliable cyber-avatar of the individual WEEE, thus forming personalised service system. The main contribution presented in this paper is the novel digital twin-based system for the WEEE recovery to support the manufacturing/remanufacturing operations throughout the product’s life cycle, from design to recovery. Meanwhile, the international standard-compliant data models are also developed to support WEEE recovery services with high data interoperability. The feasibility of the proposed system and methodologies is validated and evaluated during implementations in the cloud and cyber-physical system.
Journal: International Journal of Production Research
Pages: 3892-3902
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1497819
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1497819
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Template-Type: ReDIF-Article 1.0
Author-Name: Qiang Liu
Author-X-Name-First: Qiang
Author-X-Name-Last: Liu
Author-Name: Hao Zhang
Author-X-Name-First: Hao
Author-X-Name-Last: Zhang
Author-Name: Jiewu Leng
Author-X-Name-First: Jiewu
Author-X-Name-Last: Leng
Author-Name: Xin Chen
Author-X-Name-First: Xin
Author-X-Name-Last: Chen
Title: Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system
Abstract: 
 Under a mass individualisation paradigm, the individualised design of manufacturing systems is difficult as it involves adaptive integrating both new and legacy machines for the formation of part families with uncertainty. A systematic virtual model mirroring the real world of manufacturing system is essential to bridge the gap between its design and operation. This paper presents a digital twin-driven methodology for rapid individualised designing of the automated flow-shop manufacturing system. The digital twin merges physics-based system modelling and distributed semi-physical simulation to provide engineering solution analysis capabilities and generates an authoritative digital design of the system at pre-production phase. An effective feedbacking of collected decision-support information from the intelligent multi-objective optimisation of the dynamic execution is presented to boost the applicability of the digital twin vision in the designing of AFMS. Finally, a bi-level iterative coordination mechanism is proposed to achieve optimal design performance for required functions of AFMS. A case study is conducted to prove the feasibility and effectiveness of the proposed methodology.
Journal: International Journal of Production Research
Pages: 3903-3919
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1471243
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471243
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Template-Type: ReDIF-Article 1.0
Author-Name: Jinjiang Wang
Author-X-Name-First: Jinjiang
Author-X-Name-Last: Wang
Author-Name: Lunkuan Ye
Author-X-Name-First: Lunkuan
Author-X-Name-Last: Ye
Author-Name: Robert X. Gao
Author-X-Name-First: Robert X.
Author-X-Name-Last: Gao
Author-Name: Chen Li
Author-X-Name-First: Chen
Author-X-Name-Last: Li
Author-Name: Laibin Zhang
Author-X-Name-First: Laibin
Author-X-Name-Last: Zhang
Title: Digital Twin for rotating machinery fault diagnosis in smart manufacturing
Abstract: 
 With significant advancement in information technologies, Digital Twin has gained increasing attention as it offers an enabling tool to realise digitally-driven, cloud-enabled manufacturing. Given the nonlinear dynamics and uncertainty involved during the process of machinery degradation, proper design and adaptability of a Digital Twin model remain a challenge. This paper presents a Digital Twin reference model for rotating machinery fault diagnosis. The requirements for constructing the Digital Twin model are discussed, and a model updating scheme based on parameter sensitivity analysis is proposed to enhance the model adaptability. Experimental data are collected from a rotor system that emulates an unbalance fault and its progression. The data are then input to a Digital Twin model of the rotor system to investigate its ability of unbalance quantification and localisation for fault diagnosis. The results show that the constructed Digital Twin rotor model enables accurate diagnosis and adaptive degradation analysis.
Journal: International Journal of Production Research
Pages: 3920-3934
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1552032
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1552032
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Template-Type: ReDIF-Article 1.0
Author-Name: Fei Tao
Author-X-Name-First: Fei
Author-X-Name-Last: Tao
Author-Name: Fangyuan Sui
Author-X-Name-First: Fangyuan
Author-X-Name-Last: Sui
Author-Name: Ang Liu
Author-X-Name-First: Ang
Author-X-Name-Last: Liu
Author-Name: Qinglin Qi
Author-X-Name-First: Qinglin
Author-X-Name-Last: Qi
Author-Name: Meng Zhang
Author-X-Name-First: Meng
Author-X-Name-Last: Zhang
Author-Name: Boyang Song
Author-X-Name-First: Boyang
Author-X-Name-Last: Song
Author-Name: Zirong Guo
Author-X-Name-First: Zirong
Author-X-Name-Last: Guo
Author-Name: Stephen C.-Y. Lu
Author-X-Name-First: Stephen C.-Y.
Author-X-Name-Last: Lu
Author-Name: A. Y. C. Nee
Author-X-Name-First: A. Y. C.
Author-X-Name-Last: Nee
Title: Digital twin-driven product design framework
Abstract: 
 With the advent of new generation information technologies in industry and product design, the big data-driven product design era has arrived. However, the big data-driven product design mainly places emphasis on the analysis of physical data rather than the virtual models, in other words, the convergence between product physical and virtual space is usually absent. Digital twin, a new emerging and fast growing technology which connects the physical and virtual world, has attracted much attention worldwide recently. This paper presents a new method for product design based on the digital twin approach. The development of product design is briefly introduced first. The framework of digital twin-driven product design (DTPD) is then proposed and analysed. A case is presented to illustrate the application of the proposed DTPD method.
Journal: International Journal of Production Research
Pages: 3935-3953
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1443229
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1443229
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Template-Type: ReDIF-Article 1.0
Author-Name: Göran Adamson
Author-X-Name-First: Göran
Author-X-Name-Last: Adamson
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Author-Name: Philip Moore
Author-X-Name-First: Philip
Author-X-Name-Last: Moore
Title: Feature-based function block control framework for manufacturing equipment in cloud environments
Abstract: 
 The ability to adaptively control manufacturing equipment in cloud environments is becoming increasingly more important. Industry 4.0, supported by Cyber Physical Systems and the concept of on-demand, scalable and pay-for-usage resource-sharing in cloud environments offers many promises regarding effective and flexible manufacturing. For implementing the concept of manufacturing services in a cloud environment, a cloud control approach for the sharing and control of networked manufacturing resources is required. This paper presents a cloud service-based control approach which has a product perspective and builds on the combination of event-driven IEC 61499 Function Blocks and product manufacturing features. Distributed control is realised through the use of a networked control structure of such Function Blocks as decision modules, enabling an adaptive run-time behaviour. The control approach has been developed and implemented as prototype systems for both local and distributed manufacturing scenarios, in both real and virtual applications. An application scenario is presented to demonstrate the applicability of the control approach. In this scenario, Assembly Feature-Function Blocks for adaptive control of robotic assembly tasks have been used.
Journal: International Journal of Production Research
Pages: 3954-3974
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1542178
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1542178
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuanbin Wang
Author-X-Name-First: Yuanbin
Author-X-Name-Last: Wang
Author-Name: Yuan Lin
Author-X-Name-First: Yuan
Author-X-Name-Last: Lin
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Title: IoT-enabled cloud-based additive manufacturing platform to support rapid product development
Abstract: 
 Additive Manufacturing (AM) with its unique capabilities provides a new way of rapid product development. The emerging Cloud Manufacturing paradigm makes it much easier to access various AM resources with minimum investment. Distributed recourses can also be utilised more efficiently. However, the current cloud platforms mainly focus on providing simple 3D printing services, rather than support the customers throughout the product development process, from design, to process planning, and to printing. Therefore, a new cloud platform is proposed to integrate not only hard resources such as 3D printers and materials, but also soft resources such as the know-how and test data to provide supports on printing as well as design and process planning. Internet of Things provides new capabilities to the cloud platform, enabling customers to remotely control and monitor the printing process. The paper also examined the feasibility of Artificial Neural Networks for surface defect detection. The platform is able to work in dynamic and iterative product development processes and reduce development time and cost. An illustrative platform is developed to demonstrate the functionalities.
Journal: International Journal of Production Research
Pages: 3975-3991
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1516905
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1516905
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Template-Type: ReDIF-Article 1.0
Author-Name: Dazhong Wu
Author-X-Name-First: Dazhong
Author-X-Name-Last: Wu
Author-Name: Yupeng Wei
Author-X-Name-First: Yupeng
Author-X-Name-Last: Wei
Author-Name: Janis Terpenny
Author-X-Name-First: Janis
Author-X-Name-Last: Terpenny
Title: Predictive modelling of surface roughness in fused deposition modelling using data fusion
Abstract: 
 To realise high quality, additively manufactured parts, real-time process monitoring and advanced predictive modelling tools are crucial for accelerating quality assurance in additive manufacturing. While previous research has demonstrated the effectiveness of physics- and model-based diagnosis and prognosis for additive manufacturing, very little research has been reported on real-time monitoring and predictive modelling of the surface roughness of additively manufactured parts. This paper presents a data fusion approach to predicting surface roughness in fused deposition modelling (FDM) processes. The predictive models are trained using random forests (RFs), support vector regression (SVR), ridge regression (RR), and least absolute shrinkage and selection operator (LASSO). A real-time monitoring system is developed to monitor the health condition of a FDM machine in real-time using multiple sensors. RFs, SVR, RR, and LASSO are demonstrated on the condition monitoring data collected from these sensors. To integrate the data sources, a feature-level data fusion method is introduced. Experimental results have shown that the predictive models trained by the machine learning algorithms are capable of predicting the surface roughness of additively manufacturing parts with very high accuracy. The prediction accuracy can be further improved using the data fusion method.
Journal: International Journal of Production Research
Pages: 3992-4006
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1505058
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1505058
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Template-Type: ReDIF-Article 1.0
Author-Name: Yulin Wang
Author-X-Name-First: Yulin
Author-X-Name-Last: Wang
Author-Name: Yongping Zhang
Author-X-Name-First: Yongping
Author-X-Name-Last: Zhang
Author-Name: Fei Tao
Author-X-Name-First: Fei
Author-X-Name-Last: Tao
Author-Name: Tingyu Chen
Author-X-Name-First: Tingyu
Author-X-Name-Last: Chen
Author-Name: Ying Cheng
Author-X-Name-First: Ying
Author-X-Name-Last: Cheng
Author-Name: Shunkun Yang
Author-X-Name-First: Shunkun
Author-X-Name-Last: Yang
Title: Logistics-aware manufacturing service collaboration optimisation towards industrial internet platform
Abstract: 
 As a critical enabler for achieving smart manufacturing, the Industrial Internet platform aims to integrate distributed manufacturing services to complete complicated manufacturing tasks. Manufacturing service (MS) collaboration plays an important role in improving manufacturing efficiency and customers’ satisfaction and its optimisation is therefore of great significance. As MSs are geographically distributed, logistics is an essential ingredient that needs to be considered for MS collaboration optimisation. However, only straight-line logistics distances are considered in most of existing studies without considering effects of logistics route selection and complex geographical locations of MSs, thereby resulting in inaccuracy in practical applications. With the aim to overcome these drawbacks, this paper establishes an adjacent matrix-based logistics-aware MS collaboration optimisation (LA-MSCO) model with detailed definitions of time, cost and reliability attributes of logistics. An improved artificial bee colony algorithm with both dimensional self-adaptation and group leader mechanisms, i.e. DSA-GL-ABC, is proposed for solving the LA-MSCO problem. Simulation experiments indicate the better performance of DSA-GL-ABC algorithm in terms of searching capability, convergence speed and solution quality.
Journal: International Journal of Production Research
Pages: 4007-4026
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1543967
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543967
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Template-Type: ReDIF-Article 1.0
Author-Name: Quan Liu
Author-X-Name-First: Quan
Author-X-Name-Last: Liu
Author-Name: Zhihao Liu
Author-X-Name-First: Zhihao
Author-X-Name-Last: Liu
Author-Name: Wenjun Xu
Author-X-Name-First: Wenjun
Author-X-Name-Last: Xu
Author-Name: Quan Tang
Author-X-Name-First: Quan
Author-X-Name-Last: Tang
Author-Name: Zude Zhou
Author-X-Name-First: Zude
Author-X-Name-Last: Zhou
Author-Name: Duc Truong Pham
Author-X-Name-First: Duc Truong
Author-X-Name-Last: Pham
Title: Human-robot collaboration in disassembly for sustainable manufacturing
Abstract: 
 Sustainable manufacturing is a global front-burner issue oriented to the sustainable development of humanity and society. In this context, this paper takes the human-robot collaborative disassembly (HRCD) as the topic on its contribution to economic, environmental and social sustainability. In addition, a detailed enabling systematic implementation for HRCD is presented, combined with a set of advanced technologies such as cyber-physical production system (CPPS) and artificial intelligence (AI), and it involves five aspects which including perception, cognition, decision, execution and evolution aiming at the dynamics, uncertainties and complexities in disassembly. Deep reinforcement learning, incremental learning and transfer learning are also investigated in the systematic approaches for HRCD. The demonstration in the case study contains experiment results of multi-modal perception for robot system and human body in hybrid human-robot collaborative disassembly cell, sequence planning for an HRCD task, distance based safety strategy and motion driven control method, and it manifests high feasibility and effectiveness of the proposed approaches for HRCD and verifies the functionalities of the systematic framework.
Journal: International Journal of Production Research
Pages: 4027-4044
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2019.1578906
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1578906
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Template-Type: ReDIF-Article 1.0
Author-Name: Aitor Ardanza
Author-X-Name-First: Aitor
Author-X-Name-Last: Ardanza
Author-Name: Aitor Moreno
Author-X-Name-First: Aitor
Author-X-Name-Last: Moreno
Author-Name: Álvaro Segura
Author-X-Name-First: Álvaro
Author-X-Name-Last: Segura
Author-Name: Mikel de la Cruz
Author-X-Name-First: Mikel
Author-X-Name-Last: de la Cruz
Author-Name: Daniel Aguinaga
Author-X-Name-First: Daniel
Author-X-Name-Last: Aguinaga
Title: Sustainable and flexible industrial human machine interfaces to support adaptable applications in the Industry 4.0 paradigm
Abstract: 
 The Industry 4.0 paradigm introduced several technologies in the industrial manufacturing landscape, highlighting the Cyber Physical Systems, Internet of Things and Visual Computing as some of the key enabling technologies. The fast paced evolution of the technology has to be reflected in the common ground between the machines and the operators. The introduction of advanced, flexible and adaptable Human Machine Interfaces (HMI) will empower the operators with information and custom tools to be more productive in a safer way. This work presents totally functional hardware and a novel software architecture to build flexible advanced HMI interfaces that will provide adaptable and useful information to the operator of the machines. Industrial protocols are used to receive real-time data. A USB camera can be plugged to enable the utilisation of Computer Vision algorithms. A touch display shows adaptable interfaces composed of (a) 3D interactive graphics, (b) texts and 2D images, (c) the camera feed and (d) user interface controls to enable the interaction with the operators. The results present three use cases: (a) an HMI customised for 3D printers, (b) real-time motor control from the HMI and (c) a digital twin of a robotic arm receiving real-time data from the actual robotic arm. This work present data regarding consumption of the hardware for each use case under different work-load.
Journal: International Journal of Production Research
Pages: 4045-4059
Issue: 12
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2019.1572932
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1572932
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Template-Type: ReDIF-Article 1.0
Author-Name: Xuxia Zou
Author-X-Name-First: Xuxia
Author-X-Name-Last: Zou
Author-Name: Ling Liu
Author-X-Name-First: Ling
Author-X-Name-Last: Liu
Author-Name: Kunpeng Li
Author-X-Name-First: Kunpeng
Author-X-Name-Last: Li
Author-Name: Wenli Li
Author-X-Name-First: Wenli
Author-X-Name-Last: Li
Title: A coordinated algorithm for integrated production scheduling and vehicle routing problem
Abstract: 
 In this paper, the integrated production scheduling and vehicle routing problem is considered for a Make-to-Order manufacturer, who has a single machine for production and limited vehicles with capacity constraints for transportation. The objective is to determine production scheduling and vehicle routing, which are two interacted decisions, to minimise the maximum order delivery time. A property on optimal production sequence is proposed first, based on which backward and forward batching methods are developed and are embedded into a proposed genetic algorithm. The proposed genetic algorithm is capable of providing high-quality solutions by determining the two decisions simultaneously. For comparison purpose, a two-stage algorithm is developed, which decomposes the overall problem into two successively solved sub-problems. The experiments show that the proposed genetic algorithm can provide higher quality solutions than the proposed two-stage algorithm and two published algorithms studying related problems.
Journal: International Journal of Production Research
Pages: 5005-5024
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1378955
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1378955
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Template-Type: ReDIF-Article 1.0
Author-Name: Binay Dash
Author-X-Name-First: Binay
Author-X-Name-Last: Dash
Author-Name: M.S. Gajanand
Author-X-Name-First: M.S.
Author-X-Name-Last: Gajanand
Author-Name: T.T. Narendran
Author-X-Name-First: T.T.
Author-X-Name-Last: Narendran
Title: A model for planning the product portfolio and launch timings under resource constraints
Abstract: 
 Product design is increasingly becoming a critical function in many organisations having significant impact on their performance. It aims at the selection of a near-optimal mix of products and attribute-levels to offer in the target market. The standard product portfolio planning approach has focused on selecting optimum product profiles based on part-worth utility data. However, given that product development happens in multiple stages, combining the product definition decisions with the product development feasibility will provide organisations with a more inclusive and global solution. This paper considers a resource-constrained environment with a multi-stage product development cycle and presents an approach for helping an organisation to select the definitions of products for its product portfolio and the feasible launch timings. The proposed framework will aid product managers and researchers to identify and evaluate alternative product definitions using a Mixed Integer Linear Programming model in order to determine the alternatives which best balance product features and product development.
Journal: International Journal of Production Research
Pages: 5081-5103
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1394588
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394588
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Template-Type: ReDIF-Article 1.0
Author-Name: Cheng-Ju Chuang
Author-X-Name-First: Cheng-Ju
Author-X-Name-Last: Chuang
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Title: Optimal process mean and quality improvement in a supply chain model with two-part trade credit based on Taguchi loss function
Abstract: 
 The two-part trade credit policy is developed to accelerate cash inflow that can avoid bad debt risk in the earlier economic order quantity (EOQ) models allowing only one period of time for delay in payment. Taguchi loss function has proved to be a more realistic function for fitting the actual quality loss cost in economic product quantity (EPQ) model. To minimise quality loss, optimal process mean setting shifts process mean to balance the cost outside the specification limits, quality improvement applies investment to reduce process variation. Supply chain integration has been proved that it can be used to minimise the entire cost more effectively than independent EOQ or EPQ models. This paper improves the earlier studies by incorporating the above research topics that have not been simultaneously discussed before, develops a supply chain model based on the Taguchi loss function, which combines the trade strategy from the retailer’s perspective and the quality adjustments from the supplier’s perspective to maximise total supply chain profit. We find that the trade credit terms definitely affect suppliers and retailers’ optimal decisions, and numerical examples can provide decision references for supply chain managers to set a trade credit policy and control quality.
Journal: International Journal of Production Research
Pages: 5234-5248
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1394591
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394591
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Template-Type: ReDIF-Article 1.0
Author-Name: Maxim A. Bushuev
Author-X-Name-First: Maxim A.
Author-X-Name-Last: Bushuev
Author-Name: Jay R. Brown
Author-X-Name-First: Jay R.
Author-X-Name-Last: Brown
Author-Name: Tatiana Rudchenko
Author-X-Name-First: Tatiana
Author-X-Name-Last: Rudchenko
Title: Improving delivery performance for asymmetric Laplace distributed delivery time in a two-stage supply chain
Abstract: 
 This paper investigates strategies for improving supply chain delivery timeliness when the delivery time follows an asymmetric Laplace distribution. Delivery performance is measured using a cost-based analytical model which evaluates the expected cost for early and late delivery. This paper presents a set of propositions that define the effect of changes to the parameters of the delivery time distribution on the expected penalty cost for untimely delivery when a supplier uses an optimally positioned delivery window to minimise the expected cost of untimely delivery. The scale parameter increases the expected penalty cost, skewness decreases the cost and the location parameter has no effect on the expected penalty cost. The effects are illustrated in a numerical example with real-world supplier data. The results can be used in developing strategies for improving delivery performance from a supplier’s perspective and define how the delivery time distribution parameters can be modified to decrease the expected penalty cost of untimely delivery. The paper proposes a general approach to modelling delivery performance improvement and can be applied to other delivery time distribution forms. The approach can serve as guidance for practitioners undertaking a programme to improve delivery performance.
Journal: International Journal of Production Research
Pages: 5172-5187
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1397790
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1397790
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:15:p:5172-5187




Template-Type: ReDIF-Article 1.0
Author-Name: Miray Öner-Közen
Author-X-Name-First: Miray
Author-X-Name-Last: Öner-Közen
Author-Name: Stefan Minner
Author-X-Name-First: Stefan
Author-X-Name-Last: Minner
Title: Dynamic pricing, leadtime quotation and due date based priority dispatching
Abstract: 
 This study considers a profit-maximising make-to-order manufacturing firm that (i) dynamically quotes a price/leadtime pair to arriving prospective customers who then decide whether or not to place an order by trading off the price and leadtime and (ii) dispatches placed orders. We model the marketing–operations collaboration problem as a Markov decision process to obtain the optimal quotation and dispatching policy numerically. We further investigate the sub-optimality of several sequential approaches. Our numerical results show that sub-optimality is negligible when the tardiness penalty is proportional to tardiness and the customer sensitivities to price and leadtime quotes are similar. However, it is considerable when tardiness of orders is penalised with a fixed cost and the customers differ significantly in their sensitivity to price and leadtime. By joint optimisation, it is possible to make more appealing price/leadtime quotes to customers and at the same time reach a better service level. On the other hand, the joint optimisation can also suggest the lowering of a firm’s service level in order to achieve higher profits.
Journal: International Journal of Production Research
Pages: 5118-5130
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1397791
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1397791
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Template-Type: ReDIF-Article 1.0
Author-Name: Biswajit Sarkar
Author-X-Name-First: Biswajit
Author-X-Name-Last: Sarkar
Author-Name: Chong Zhang
Author-X-Name-First: Chong
Author-X-Name-Last: Zhang
Author-Name: Arunava Majumder
Author-X-Name-First: Arunava
Author-X-Name-Last: Majumder
Author-Name: Mitali Sarkar
Author-X-Name-First: Mitali
Author-X-Name-Last: Sarkar
Author-Name: Yong Won Seo
Author-X-Name-First: Yong Won
Author-X-Name-Last: Seo
Title: A distribution free newsvendor model with consignment policy and retailer’s royalty reduction
Abstract: 
 Reducing the system cost and achieving significant profit are the key factors for every successful business sector. A consignment contract under distribution-free approach may be a fruitful combination to achieve a profitable business. This model deals with a single-period newsvendor problem with a consignment policy. The consignment policy is an agreement between any two parties, named as the consignor and the consignee. Under Stackelberg approach, firms act as leader and follower. Both parties carry some parts of the holding cost instead of one. A new policy for paying the fixed fee to the consignee is introduced. This paper considers no specific probability distribution for customer’s demand except a known mean and standard deviation. An efficient approach is proposed to reduce the retailer’s cost and building a sustainable consignment contract. The solution of this model is obtained using distribution free approach. A comparison between the traditional supply chain policy and the consignment policy is established. The price-sensitivity on demand is analysed. Some numerical examples and graphical representations are given for both traditional and consignment policy. Result proves that consignment policy is dominating over the traditional policy and a significant reduction of retailer’s royalty is found.
Journal: International Journal of Production Research
Pages: 5025-5044
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1399220
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1399220
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Template-Type: ReDIF-Article 1.0
Author-Name: Ina Bräuer
Author-X-Name-First: Ina
Author-X-Name-Last: Bräuer
Author-Name: Udo Buscher
Author-X-Name-First: Udo
Author-X-Name-Last: Buscher
Title: A note on ‘Pricing and ordering decisions in a supply chain with imperfect quality items and inspection under buyback of defective items’
Abstract: 
 Taleizadeh, Noori-daryan, and Tavakkoli-Moghaddam consider pricing and ordering decisions in a three-level supply chain with defective items and inspection processes in their paper published in 2015. They examine three scenarios for defective items at the manufacturer: disposal, rework and selling at a lower price. Unfortunately, this interesting and innovative paper suffers from some shortcomings that are addressed in our note.
Journal: International Journal of Production Research
Pages: 5272-5277
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1399223
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1399223
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Template-Type: ReDIF-Article 1.0
Author-Name: Salma Karray
Author-X-Name-First: Salma
Author-X-Name-Last: Karray
Author-Name: Simon Pierre Sigué
Author-X-Name-First: Simon Pierre
Author-X-Name-Last: Sigué
Title: Joint advertising of complementary products sold through an independent retailer
Abstract: 
 Two game-theoretic models are developed to study the profitability of joint advertising in a context where two manufacturers sell complementary products through an independent retailer and can either advertise separately or jointly. We find that it may not be in the interest of symmetric manufacturers to partner for advertising, especially when joint advertising is less effective than firms’ individual advertising and the degree of advertising complementarity between the two products is high. Conversely, the manufacturers prefer joint advertising to individual advertising programs even if its effectiveness is lower, but both the degrees of price and advertising complementarity are very large. Under these conditions, joint advertising is implemented at the expense of the retailer who suffers from the associated reduced demand for the two products. In such a context, the manufacturers’ advertising partnership mainly reduces advertising costs by mitigating double marginalisation in pricing. The extension to asymmetric manufacturers shows that the weaker manufacturer and the retailer can induce the stronger manufacturer to engage in joint advertising.
Journal: International Journal of Production Research
Pages: 5222-5233
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1399224
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1399224
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Template-Type: ReDIF-Article 1.0
Author-Name: Quanwu Zhao
Author-X-Name-First: Quanwu
Author-X-Name-Last: Zhao
Author-Name: Wei Wang
Author-X-Name-First: Wei
Author-X-Name-Last: Wang
Author-Name: Robert De Souza
Author-X-Name-First: Robert
Author-X-Name-Last: De Souza
Title: A heterogeneous fleet two-echelon capacitated location-routing model for joint delivery arising in city logistics
Abstract: 
 This paper focuses on optimisation issue in designing urban logistics network for joint delivery alliances in parcel delivery industry, explicitly taking into account heterogeneous fleet and practices of joint delivery alliances in China. The objective is to determine the set of Intermediate Depots (IDs) to open and the allocation of city logistics terminals to minimise a total cost comprised of the set-up costs of IDs and the total variable cost of routes under joint delivery. A powerful cooperative approximation heuristic algorithm is developed and a comparative analysis is performed with three published approaches based on the well-known benchmark instances in this field. The results suggest that the proposed method can find good solutions in a reasonable amount of time for most data-sets. The proposed method has also been successfully applied to an industrial case for a joint delivery alliance in Chongqing, China. Comprehensively analysis are conducted between joint delivery and separate delivery, heterogeneous and homogeneous fleets, considering the carbon emissions or not, and demand variations.
Journal: International Journal of Production Research
Pages: 5062-5080
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1401235
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401235
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Template-Type: ReDIF-Article 1.0
Author-Name: Nunzia Carbonara
Author-X-Name-First: Nunzia
Author-X-Name-Last: Carbonara
Author-Name: Roberta Pellegrino
Author-X-Name-First: Roberta
Author-X-Name-Last: Pellegrino
Title: Real options approach to evaluate postponement as supply chain disruptions mitigation strategy
Abstract: 
 The purpose of this paper is to assess the value of postponement as strategy for mitigating supply chain disruptions. To accomplish this objective, we develop a real option computational model that quantifies the value of postponement in mitigating both supply and demand disruptions by taking into account the value of managerial flexibility to decide whether exploiting or not the strategy, if and when disruptions occur, and whenever product differentiation proves valuable based on information available at that time. Numerical experiments show the importance of incorporating an option valuation method when pricing the value of postponement. This ensures managers implement postponement only when it is valuable, thus avoiding burdening the company with its initial sunk costs. By modelling the postponement implementation under different conditions, we identify the situations in which postponement performs better as supply chain disruptions mitigation strategy. We derive the operational configurations, in terms of decoupling point position, and external conditions, in terms of riskiness of the environment, which make the postponement an effective mitigation strategy.
Journal: International Journal of Production Research
Pages: 5249-5271
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1403663
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1403663
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Template-Type: ReDIF-Article 1.0
Author-Name: Belarmino Adenso-Díaz
Author-X-Name-First: Belarmino
Author-X-Name-Last: Adenso-Díaz
Author-Name: Julio Mar-Ortiz
Author-X-Name-First: Julio
Author-X-Name-Last: Mar-Ortiz
Author-Name: Sebastián Lozano
Author-X-Name-First: Sebastián
Author-X-Name-Last: Lozano
Title: Assessing supply chain robustness to links failure
Abstract: 
 Supply chain networks need to respond efficiently to operation disruptions, as one of their aims is to guarantee the on time delivery of products. Hence, robustness has become one of the important issues to consider when designing supply networks. There are alternative ways to measure what robustness means in this context. In this paper, we propose a new metric based on the effect on service level of the collapse of active transportation links. Numerical experiments are carried out to understand how different design factors affect robustness. Robustness under a targeted attack is compared with robustness to random failures. Results show that flow complexity (i.e. the number of potential transportation links between supply network nodes) is the most influential factor affecting supply network and its robustness, as well as the service level that can be maintained after disruptions. Thus, diversification both in supply sources and transportation routes seems to be key to robustness.
Journal: International Journal of Production Research
Pages: 5104-5117
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1419582
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1419582
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Template-Type: ReDIF-Article 1.0
Author-Name: Cátia Barbosa
Author-X-Name-First: Cátia
Author-X-Name-Last: Barbosa
Author-Name: Américo Azevedo
Author-X-Name-First: Américo
Author-X-Name-Last: Azevedo
Title: Hybrid modelling of MTO/ETO manufacturing environments for performance assessment
Abstract: 
 Performance assessment is critical in today’s competitive environments, where companies need to establish trade-offs between key competitive dimensions. The complexity of these environments calls for new approaches to performance assessment. Thus, in this work, we propose a novel conceptual framework for performance assessment in manufacturing environments combining different production strategies. Focus is laid on MTO/ETO combined environments and a three-stage problem analysis is considered. Firstly, a hybrid SD-DES-ABS model approach addresses the needs of a system that handles different types of orders, processes and workforce allocation requirements; secondly, the model results for different demand scenarios are assessed using a one-way ANOVA analysis followed by a Tukey – Kramer’s test, with pairwise comparisons for assessment of significant performance variations under different system operating policies. A full factorial Design of Experiments (DOE) analysis follows, for determining the relevant process parameters influencing the system performance. As an example of application of the proposed framework, we consider the case of an advanced manufacturing company, whose manufacturing environment encompasses combined MTO/ETO production strategies.
Journal: International Journal of Production Research
Pages: 5147-5171
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1421788
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421788
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Template-Type: ReDIF-Article 1.0
Author-Name: Y. Boulaksil
Author-X-Name-First: Y.
Author-X-Name-Last: Boulaksil
Author-Name: A.C.C. van Wijk
Author-X-Name-First: A.C.C.
Author-X-Name-Last: van Wijk
Title: A cash-constrained stochastic inventory model with consumer loans and supplier credits: the case of nanostores in emerging markets
Abstract: 
 We consider a small traditional retailer that is managing its inventory under strict cash constraints, mainly because typically informal loans are offered to customers. These stores are widely present in emerging markets, and we refer to them as nanostores (also called ‘mom-and-pop stores’). As the suppliers require immediate payments for goods delivered, a nanostore can only replenish products to the level for which it has on-hand cash available. To improve delivery efficiency, a supplier might offer a nanostore credit for its replenishments. However, currently, suppliers are often reluctant to do so as these nanostores quickly go bankrupt or disappear, hence defaulting on all outstanding credits. The objective of this paper is to determine when it is beneficial to offer supplier credits. We propose a multi-period, stochastic inventory model, and numerically compare scenarios with and without supplier credits. Our study shows that even in the presence of this risk, suppliers often have good incentives to provide these credits, even if interest is not incurred. For this to hold, the operations of the retailer should be (a little) profitable in the first place, for which we provide analytical conditions.
Journal: International Journal of Production Research
Pages: 4983-5004
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1424368
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424368
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Template-Type: ReDIF-Article 1.0
Author-Name: Elisabetta Raguseo
Author-X-Name-First: Elisabetta
Author-X-Name-Last: Raguseo
Author-Name: Claudio Vitari
Author-X-Name-First: Claudio
Author-X-Name-Last: Vitari
Title: Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects
Abstract: 
 Big data has recently been recognised as one of the most important areas of future technology. It has attracted the attention of many industries, since it has the potential to provide companies with high business value. This paper examines the forms of business value that companies can create from big data analytics investments, the direct impacts it has on the financial performance of a firm, and the mediating effects of market performance and customer satisfaction. Drawing on the resource-based view theory, this study demonstrates that the business value achieved from investments in big data analytics leads to advantages in terms of the financial performance of a firm. The results offer evidence of the existence of a customer satisfaction mediation effect and of the absence of a market performance mediation effect. Theoretical and practical implications are discussed at the end of the paper.
Journal: International Journal of Production Research
Pages: 5206-5221
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1427900
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1427900
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiewu Leng
Author-X-Name-First: Jiewu
Author-X-Name-Last: Leng
Author-Name: Pingyu Jiang
Author-X-Name-First: Pingyu
Author-X-Name-Last: Jiang
Title: Evaluation across and within collaborative manufacturing networks: a comparison of manufacturers’ interactions and attributes
Abstract: 
 Evaluation on collaborative manufacturing network (CMN) structure characteristics has important implications for network operations such as production decision-making, product recovery, creating consensus. Several recent studies suggest that augmenting network structure with nodes’ attributes can provide a more fine-grained understanding of the network. However, there have been few studies to provide a systematic understanding of these effects in a CMN at scale. This gap is bridged using an industrial printing machinery CMN data-set collected on a web-based producing and outsourcing service platform. Novel phenomena with respect to both interaction and attribute metrics across and within the CMNs are observed. Moreover, although many studies employ either interaction or attribute data to study the relative roles of manufacturers in a CMN, relatively little is known about the relationship between these two types of data. This study explores this relationship by comparing two defined metrics (i.e. relational capability and node capability), which evaluate the manufacturers’ interactions and attributes, respectively. We examine to what extent the two metrics of manufacturers correlate with each other, and how possible dissimilarities and similarities can be explained based on the collected industrial CMN data-set. The insights thereby provide a better basis for efficient operations decision-making in CMN.
Journal: International Journal of Production Research
Pages: 5131-5146
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1430903
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1430903
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Template-Type: ReDIF-Article 1.0
Author-Name: Maurício Fontoura Blos
Author-X-Name-First: Maurício Fontoura
Author-X-Name-Last: Blos
Author-Name: Robson Marinho da Silva
Author-X-Name-First: Robson Marinho
Author-X-Name-Last: da Silva
Author-Name: Hui-Ming Wee
Author-X-Name-First: Hui-Ming
Author-X-Name-Last: Wee
Title: A framework for designing supply chain disruptions management considering productive systems and carrier viewpoints
Abstract: 
 With the advent of the global and digital world, the number of geographically dispersed firms throughout the world has increased and the problem of Supply Chain (SC) disruption appeared as a main concern to many industries. In such context, designing disruptions management strategies for a robust SC has become a critical worldwide issue that is still under-explored. Since its design phase, this class of robust and global SC must integrate technologies and agents of production. However, the existing works only consider the Productive Systems (PSs) and the carrier viewpoint must also be considered since goods should be produced and distributed at the right quantity, at the right place and at the right time. In this complex task of designing disruptions management, a formal method must be used to integrate technologies ensuring the compliance of certain requirements, such as: developing collaborative and autonomous models, allowing reuse templates, considering analysis/simulation abilities and facilitating the interaction among engineering practitioners. Therefore, this paper presents a framework to model, analyse, control and monitor the robust and global SC, designing and integrating models with Petri Net, agent-based model techniques for disruptions management and considering both PSs and carrier viewpoints. A case study is investigated and the findings demonstrated the proposed solution supports decisions making for solving problems of design, analysis and control.
Journal: International Journal of Production Research
Pages: 5045-5061
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1442943
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1442943
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Template-Type: ReDIF-Article 1.0
Author-Name: Li-Hao Zhang
Author-X-Name-First: Li-Hao
Author-X-Name-Last: Zhang
Author-Name: Tian Li
Author-X-Name-First: Tian
Author-X-Name-Last: Li
Author-Name: Ti-Jun Fan
Author-X-Name-First: Ti-Jun
Author-X-Name-Last: Fan
Title: Inventory misplacement and demand forecast error in the supply chain: profitable RFID strategies under wholesale and buy-back contracts
Abstract: 
 We investigate RFID adoption strategies under wholesale price and buy-back contracts in a supply chain with one manufacturer and one retailer who faces inventory misplacement and demand forecast error. RFID can alleviate the misplacement problem, and can reduce demand forecast error by shortening order lead time. By a newsvendor model, we characterise the optimal contract terms in the supply chain without and with RFID adoption, respectively. We further analyse how the contract terms depend on RFID-related parameters (e.g. salable rate and demand forecast error). We find that both without and with RFID, the wholesale price contract will lead to the double marginalisation problem, while the buy-back contract can coordinate the supply chain. We show that the supply chain adopts RFID if and only if the tagging cost is below a threshold; the threshold is in negative correlation to the demand forecast error. The supply chain is more willing to adopt RFID under the buy-back contract than under the wholesale price contract. RFID adoption can sometimes lessen the double marginalisation problem under the wholesale price contract, improving the supply chain efficiency. A smaller RFID tagging cost or a reduced forecast error do not necessarily lead to higher supply chain efficiency.
Journal: International Journal of Production Research
Pages: 5188-5205
Issue: 15
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1463110
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1463110
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Th&#xFC;rer
Author-X-Name-First: Matthias
Author-X-Name-Last: Th&#xFC;rer
Author-Name: Nuno O. Fernandes
Author-X-Name-First: Nuno O.
Author-X-Name-Last: Fernandes
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Author-Name: Ting Qu
Author-X-Name-First: Ting
Author-X-Name-Last: Qu
Author-Name: Cong Dong Li
Author-X-Name-First: Cong Dong
Author-X-Name-Last: Li
Title: Centralised . decentralised control decision in card-based control systems: comparing  systems and COBACABANA
Abstract: 
 Kanban systems are simple yet effective means of controlling production. Production control is decentralised or exercised locally on the shop floor, i.e. a downstream station signals to an upstream station that an item is needed. If items are always the same and known, then demands can be satisfied instantaneously from stock; but if items differ and are unknown, demands must first be propagated backwards from station to station before being satisfied. The former is defined as an inventory control problem and the latter as an order control problem. Handling the order control problem via kanban involves a decentralised card acquisition process (during which information is propagated from station to station) that is separated from the actual production process. COBACABANA (control of balance by card-based navigation), an alternative card-based solution, shares kanban&#x2019;s control structure but centralises the card acquisition process. Evaluating the two systems therefore provides a unique opportunity to compare decentralised and centralised control. Using simulation, we demonstrate that it is specifically the centralised card acquisition process that allows COBACABANA to balance the workload across resources and thus to outperform kanban in an order control problem. This has major implications for research and practice.
Journal: International Journal of Production Research
Pages: 322-337
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1425018
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1425018
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Template-Type: ReDIF-Article 1.0
Author-Name: Im&#xE8;ne Benkalai
Author-X-Name-First: Im&#xE8;ne
Author-X-Name-Last: Benkalai
Author-Name: Djamal Rebaine
Author-X-Name-First: Djamal
Author-X-Name-Last: Rebaine
Author-Name: Pierre Baptiste
Author-X-Name-First: Pierre
Author-X-Name-Last: Baptiste
Title: Scheduling flow shops with operators
Abstract: 
 This paper addresses the problem of assigning a number of operators, less than the number of machines, in a flow shop environment. We study two different problems. The first is the assignment of operators subject to a fixed job sequence; the second is on handling simultaneously the assignment of operators and the scheduling of jobs on the machines. We present complexity results and develop a new lower bound. Heuristic algorithms are designed for both problems. An experimental study is then conducted to evaluate the quality of our solving methods. The results show that the appropriate approach depends on the parameters of the problem, including the number of operators. The methods also provided results close to the theoretical lower bound in most of the cases.
Journal: International Journal of Production Research
Pages: 338-356
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1425557
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1425557
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Template-Type: ReDIF-Article 1.0
Author-Name: Xue Xiao
Author-X-Name-First: Xue
Author-X-Name-Last: Xiao
Author-Name: Shufang Wang
Author-X-Name-First: Shufang
Author-X-Name-Last: Wang
Author-Name: Lejun Zhang
Author-X-Name-First: Lejun
Author-X-Name-Last: Zhang
Author-Name: Cheng-zhi Qin
Author-X-Name-First: Cheng-zhi
Author-X-Name-Last: Qin
Title: Complexity analysis of manufacturing service ecosystem: a mapping-based computational experiment approach
Abstract: 
 The trend of servitisation is increasingly affecting manufacturing enterprises. Traditional manufacturing enterprises cannot handle the related challenges of service innovation by themselves. Recently, manufacturing service ecosystem (MSE) has been proposed to support service innovation by facilitating collaboration. The construction and development of MSE need to handle a series of complexities, such as individual complexity, interaction complexity and ecological complexity. However, it is still very difficult to clearly identify the possible effect of various influence factors on MSE evolution, which is necessary analyse the complex dynamic interactive relationship among participants, so as to maintain the sustainable and healthy development of MSE. To change such a situation, this paper proposes a mapping-based computational experiment approach to analyse the evolution of MSE. This approach has three main parts, i.e. model construction of real world, model mapping of computational system and experiment evaluation of various factors of MSE evolution. By adopting the proposed approach, several case studies are conducted to investigate the possible effect of cooperation preference on the MSE evolution in various market environments. The results demonstrate that the proposed approach is effective.
Journal: International Journal of Production Research
Pages: 357-378
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1430906
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1430906
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Template-Type: ReDIF-Article 1.0
Author-Name: Jizhou Zhan
Author-X-Name-First: Jizhou
Author-X-Name-Last: Zhan
Author-Name: Xiangfeng Chen
Author-X-Name-First: Xiangfeng
Author-X-Name-Last: Chen
Author-Name: Qiying Hu
Author-X-Name-First: Qiying
Author-X-Name-Last: Hu
Title: The value of trade credit with rebate contract in a capital-constrained supply chain
Abstract: 
 We investigate the value of an innovative trade credit with rebate contract (TCRC) model in a stylised supply chain. In this supply chain, the capital-abundant manufacturer offers an integrated contract involving trade credit, minimum ordering and sales rebate contract to a capital-constrained retailer. To highlight the value of the TCRC model, we compare it with a traditional trade credit financing (TTCF) model in a &#x2018;selling to the newsvendor model&#x2019;. First, we show that equilibrium strategies exist between the manufacturer and the retailer under the TCRC or TTCF model. Second, this study investigates equilibrium selection between the TCRC and TTCF models for the individual and the supply chain. Finally, we show the manufacturer&#x2019;s pricing policy, wherein the TCRC model outperforms the TTCF model for the players. Furthermore, we conduct a set of numerical experiments to show evidence for theoretical analysis and measure the operation efficiency of the TCRC model for players in the supply chain.
Journal: International Journal of Production Research
Pages: 379-396
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1442946
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1442946
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Template-Type: ReDIF-Article 1.0
Author-Name: Ahmed Awil Abdrahman Ahmed
Author-X-Name-First: Ahmed Awil Abdrahman
Author-X-Name-Last: Ahmed
Author-Name: Yiliu Liu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Liu
Title: Throughput-based importance measures of multistate production systems
Abstract: 
 Many production systems are multistate, with a finite number of performance levels that are between perfect functioning and complete failure. Importance measures are often used in the maintenance planning of complicated systems, to observe the criticalities of components, reveal the system weakness, and thus to guide the allocation of limited maintenance resources. This paper compares several commonly used importance measures for multistate systems, and investigates their effectiveness and limitations with a simple example. These existing measures focus on the states of a system at some moment, while ignoring the dynamic behaviours in the long-term. For a production system, however, its throughput in a certain period, rather than the instantaneous performance, is the system property of interest. Therefore, two new long-term throughput-based importance measures: total throughput importance measure and maintenance effect importance measure are proposed in this paper, to answer the questions about the criticalities of different components and the long-term effects of successful maintenance activities on the throughput of a production system in a certain period. A case study on an offshore production system is conducted, to illustrate how the new importance measures work and what kind of implications can be provided to the maintenance crew.
Journal: International Journal of Production Research
Pages: 397-410
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1442947
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1442947
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:397-410




Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Suresh P. Sethi
Author-X-Name-First: Suresh P.
Author-X-Name-Last: Sethi
Author-Name: Boris Sokolov
Author-X-Name-First: Boris
Author-X-Name-Last: Sokolov
Title: Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications
Abstract: 
 This paper presents a survey on the applications of optimal control to scheduling in production, supply chain and Industry 4.0 systems with a focus on the deterministic maximum principle. The first objective is to derive major contributions, application areas, limitations, as well as research and application recommendations for the future research. The second objective is to explain control engineering models in terms of industrial engineering and production management. To achieve these objectives, optimal control models, qualitative methods of performance analysis and computational methods for optimal control are considered. We provide a brief historic overview and clarify major mathematical fundamentals whereby the control engineering terms are brought into correspondence with industrial engineering and management. The survey allows the grouping of models with only terminal constraints with application to master production scheduling, models with hybrid terminal&#x2013;logical constraints with applications to short term job and flow shop scheduling, and hybrid structural&#x2013;terminal&#x2013;logical constraints with applications to customised assembly systems such as Industry 4.0. Computational algorithms in state, control and adjoint variable spaces are discussed.
Journal: International Journal of Production Research
Pages: 411-432
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1442948
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1442948
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Template-Type: ReDIF-Article 1.0
Author-Name: Farzad Alavifard
Author-X-Name-First: Farzad
Author-X-Name-Last: Alavifard
Title: Modelling default dependence in automotive supply networks using vine-copula
Abstract: 
 This paper presents an intuitive model for default dependencies in supply networks and its application in firms&#x2019; capital management. Modern supply chain networks are characterised by horizontal ties between firms within a particular industry or group, which are sequentially arranged based on vertical ties between firms in different layers. The recognition and accounting of these simultaneous interdependencies is crucial for a more advanced understanding of complex inter-organisational relations. Using the state-of-the art vine-copulae, we model these multidimensional interdependencies in the automotive industry, and capture the default tail dependency between alliance partners. Further, we apply our model to determine the optimal economic capital, such that companies can absorb unexpected losses from defaults in supply chain, while avoiding over-capitalisation. Our findings should spur managers to analyse their supplier networks with respect to default dependencies and to take this phenomenon into consideration when making sourcing decisions.
Journal: International Journal of Production Research
Pages: 433-451
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1443522
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1443522
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:433-451




Template-Type: ReDIF-Article 1.0
Author-Name: Jaakko Peltokorpi
Author-X-Name-First: Jaakko
Author-X-Name-Last: Peltokorpi
Author-Name: Esko Niemi
Author-X-Name-First: Esko
Author-X-Name-Last: Niemi
Title: Effects of group size and learning on manual assembly performance: an experimental study
Abstract: 
 In variable manual assembly production of highly customised products, effective allocation of workers to products is required. To support decision-making here, industrial managers should be aware of the performance effects of the number of workers and learning within individual products. Evidence on such fundamental effects requires laboratory studies with products similar to those in real assembly industries. Because of the lack of such studies, this paper studies experimentally the effects of group size (one to four workers) and learning (up to four repetitions per group) on the performance of product assembly. The product, built for the purpose of the present study, consists of representative elements from real products in the mechanical engineering industry. A total of 68 undergraduate students participated in the experiments. The results from the experiments are in line with the hypotheses that the mean assembly time decreases at a decelerating rate as a function of both group size and repetitions, and that productivity per worker decreases as a function of group size. The results are explained in more detail through the experiences of the participants. Managerial implications and aspects for future research are also discussed.
Journal: International Journal of Production Research
Pages: 452-469
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1444810
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1444810
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:452-469




Template-Type: ReDIF-Article 1.0
Author-Name: Kyungsu Park
Author-X-Name-First: Kyungsu
Author-X-Name-Last: Park
Author-Name: Jingshan Li
Author-X-Name-First: Jingshan
Author-X-Name-Last: Li
Title: Improving productivity of a multi-product machining line at a motorcycle manufacturing plant
Abstract: 
 This paper introduces a case study to improve productivity of a multi-product transmission case machining line at a motorcycle manufacturing plant. First, the manufacturing process is introduced to characterise the production flow. Through structural modelling, such a process is simplified through aggregations and transformed into a two-stage Bernoulli line model with split dedicated machines and finite buffers. Using Markov chain analysis, the system throughput can be estimated. The results are validated by plant data. To improve system productivity, through numerical experiments, we investigate the impacts of increasing machine efficiency, varying demands and implementing different loading policies. Such a study provides a quantitative tool for plant engineers and managers to improve production operations.
Journal: International Journal of Production Research
Pages: 470-487
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1448129
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1448129
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Template-Type: ReDIF-Article 1.0
Author-Name: Yujian Song
Author-X-Name-First: Yujian
Author-X-Name-Last: Song
Author-Name: Jiantong Zhang
Author-X-Name-First: Jiantong
Author-X-Name-Last: Zhang
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: The berth allocation optimisation with the consideration of time-varying water depths
Abstract: 
 Confronting the challenges provided by jumbo container vessels, managers of world-class seaports must take into consideration water depths-related constraints when making the vessel berthing decisions. That is, when the water depths satisfy the requirement of jumbo vessels&#x2019; drafts, these vessels are allowed to sail through the navigation channel. In this paper, we study a tactical berth allocation problem under the consideration of time-varying water depths. For the resolution, we propose an integer programming model, a set partitioning formulation and an improved differential evolutionary algorithm. Computational experiments demonstrate that the set partitioning formulation outperforms the integer programming model and can be applied to solve small- and medium-sized problems. The improved differential evolutionary algorithm is recommended for large-sized problems.
Journal: International Journal of Production Research
Pages: 488-516
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1449975
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1449975
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:488-516




Template-Type: ReDIF-Article 1.0
Author-Name: Gilseung Ahn
Author-X-Name-First: Gilseung
Author-X-Name-Last: Ahn
Author-Name: You-Jin Park
Author-X-Name-First: You-Jin
Author-X-Name-Last: Park
Author-Name: Sun Hur
Author-X-Name-First: Sun
Author-X-Name-Last: Hur
Title: Performance computation methods for composition of tasks with multiple patterns in cloud manufacturing
Abstract: 
 Task composition in cloud manufacturing involves the selection of appropriate services from the cloud manufacturing platform and combining them to process the task with the purpose of achieving its expected performance. Calculation methods for achieving the performance expected by customers when the task has two or more composition patterns (e.g. sequential and switching pattern) are necessary because most tasks have multiple composition patterns in cloud manufacturing. Previous studies, however, have focused only on a single composition pattern. In this paper, we regard a task as a directed acyclic graph, and propose graph-based algorithms to obtain cost, execution time, quality and reliability of a task having multiple composition patterns. In addition, we model the task composition problem by introducing cost and execution time as performance attributes, and quality and reliability as basic attributes in the Kano model. Finally, an experiment to compare the performances of three metaheuristic algorithms (namely, variable neighbourhood search, genetic, and simulated annealing) is conducted to solve the problem. The experimental result shows that the variable neighbourhood search algorithm yields better and more stable solutions than the genetic algorithm and simulated annealing algorithms.
Journal: International Journal of Production Research
Pages: 517-530
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1451664
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1451664
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Template-Type: ReDIF-Article 1.0
Author-Name: Enrique Gerstl
Author-X-Name-First: Enrique
Author-X-Name-Last: Gerstl
Author-Name: Baruch Mor
Author-X-Name-First: Baruch
Author-X-Name-Last: Mor
Author-Name: Gur Mosheiov
Author-X-Name-First: Gur
Author-X-Name-Last: Mosheiov
Title: Scheduling on a proportionate flowshop to minimise total late work
Abstract: 
 We study a scheduling problem to minimise total late work, i.e. each job is penalised according to the duration of its parts scheduled after its due-date. The machine setting is an m-machine proportionate flow shop. Two versions of the problem are studied: (i) the case that total late work refers to the last operation of the job (i.e. the operation performed on the last machine of the flow shop); (ii) the case that total late work refers to all the operations (on all machines). Both versions are known to be NP-hard. We prove a crucial property of an optimal schedule, and consequently introduce efficient pseudo-polynomial dynamic programming algorithms for the two versions. The dynamic programming algorithms are tested numerically and proved to perform well on large size instances.
Journal: International Journal of Production Research
Pages: 531-543
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1456693
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1456693
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:531-543




Template-Type: ReDIF-Article 1.0
Author-Name: Zhen Shang
Author-X-Name-First: Zhen
Author-X-Name-Last: Shang
Author-Name: Songzheng Zhao
Author-X-Name-First: Songzheng
Author-X-Name-Last: Zhao
Author-Name: Yanjun Qian
Author-X-Name-First: Yanjun
Author-X-Name-Last: Qian
Author-Name: Jun Lin
Author-X-Name-First: Jun
Author-X-Name-Last: Lin
Title: Exact algorithms for the feedback length minimisation problem
Abstract: 
 Planning the sequence of interrelated activities of production and manufacturing systems has become a challenging issue due to the existence of cyclic information flows. This study develops efficient exact algorithms for finding an activity sequence with minimum total feedback length in a design structure matrix. First, we present two new properties of the problem. Second, based on the properties, we develop an efficient Parallel Branch-and-Prune algorithm (PBP). Finally, the proposed PBP is further improved by adopting hash functions representing activity sequences, which is referred as hash function-based PBP. Experimental results indicate that the proposed hash function-based PBP can find optimal solutions for problems up to 25 interrelated activities within 1 h, and outperforms existing methods.
Journal: International Journal of Production Research
Pages: 544-559
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1456697
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1456697
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:544-559




Template-Type: ReDIF-Article 1.0
Author-Name: Sergey Kovalev
Author-X-Name-First: Sergey
Author-X-Name-Last: Kovalev
Author-Name: Mikhail Y. Kovalyov
Author-X-Name-First: Mikhail Y.
Author-X-Name-Last: Kovalyov
Author-Name: Gur Mosheiov
Author-X-Name-First: Gur
Author-X-Name-Last: Mosheiov
Author-Name: Enrique Gerstl
Author-X-Name-First: Enrique
Author-X-Name-Last: Gerstl
Title: Semi-V-shape property for two-machine no-wait proportionate flow shop problem with TADC criterion
Abstract: 
 The problem of minimising total absolute deviation of job completion times in a two-machine no-wait proportionate flow shop has been recently studied. It was shown that the LPT (largest processing time first) job sequence is optimal if the number of jobs n does not exceed 7, and that the LPT sequence is not optimal for instances with n&#x2265;8
$ n \ge 8 $
. We prove that there exists an optimal semi-V-shaped job sequence, in which the first job has the largest processing time, a certain number, greater than n&#xA0;/&#xA0;2, of the following jobs appear in the LPT order, and jobs following job with the minimum processing time are sequenced in the SPT (shortest processing time first) order. We also present an O(n3)
$ O(n^3) $
 time dynamic programming algorithm to find the best V-shaped job sequence, in which the jobs on the left of the job with the minimum processing time are sequenced in the LPT order and those on the right of this job are sequenced in the SPT order.
Journal: International Journal of Production Research
Pages: 560-566
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1468097
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1468097
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Template-Type: ReDIF-Article 1.0
Author-Name: Zewen Huang
Author-X-Name-First: Zewen
Author-X-Name-Last: Huang
Author-Name: Zhongshun Shi
Author-X-Name-First: Zhongshun
Author-X-Name-Last: Shi
Author-Name: Leyuan Shi
Author-X-Name-First: Leyuan
Author-X-Name-Last: Shi
Title: Minimising total weighted completion time on batch and unary machines with incompatible job families
Abstract: 
 This paper addresses the problem of scheduling on batch and unary machines with incompatible job families such that the total weighted completion time is minimised. A mixed-integer linear programming model is proposed to solve the problem to optimality for small instances. Tight lower bounds and a 4-approximation algorithm are developed. A constraint programming-based method is also proposed. Numerical results demonstrate that the proposed algorithms can obtain high quality solutions and have a competitive performance. Sensitivity analysis indicates that the performance of the proposed algorithms is also robust on different problem structures.
Journal: International Journal of Production Research
Pages: 567-581
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1470341
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1470341
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:567-581




Template-Type: ReDIF-Article 1.0
Author-Name: Houtian Ge
Author-X-Name-First: Houtian
Author-X-Name-Last: Ge
Author-Name: Stephan Goetz
Author-X-Name-First: Stephan
Author-X-Name-Last: Goetz
Author-Name: Miguel G&#xF3;mez
Author-X-Name-First: Miguel
Author-X-Name-Last: G&#xF3;mez
Author-Name: Richard Gray
Author-X-Name-First: Richard
Author-X-Name-Last: Gray
Author-Name: James Nolan
Author-X-Name-First: James
Author-X-Name-Last: Nolan
Title: Modelling testing mechanism for mitigating genetically modified wheat contamination risks
Abstract: 
 Recent discoveries of genetically modified (GM) wheat growing in farm fields across several U.S. states have renewed public worries about GM wheat contamination if GM wheat is commercialised. There would appear to be a need for research designed to identify reactive risk mitigation strategies to maintain the sustainability of grain supply chains (SCs) before any potential GM wheat contamination undermines their integrity. This research attempts to identify cost-effective testing strategies to mitigate the GM wheat contamination risks. We explicitly model the U.S. wheat supply chain in a realistic manner to embrace complexity inherent in the system. The specification of appropriate wheat handling strategies in the SC is formulated as system optimisation problems and solved using simulation. Once solved for a base scenario, sensitivity analysis is conducted on key variables that influence wheat varietal testing strategies.
Journal: International Journal of Production Research
Pages: 582-598
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1472403
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1472403
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Template-Type: ReDIF-Article 1.0
Author-Name: Marco Marconi
Author-X-Name-First: Marco
Author-X-Name-Last: Marconi
Author-Name: Michele Germani
Author-X-Name-First: Michele
Author-X-Name-Last: Germani
Author-Name: Marco Mandolini
Author-X-Name-First: Marco
Author-X-Name-Last: Mandolini
Author-Name: Claudio Favi
Author-X-Name-First: Claudio
Author-X-Name-Last: Favi
Title: Applying data mining technique to disassembly sequence planning: a method to assess effective disassembly time of industrial products
Abstract: 
 Design for end-of-life and design for disassembly are enabling design strategies for the implementation of business models based on the circular economy paradigm. The paper presents a method for calculating the effective disassembly sequence and time for industrial products. Five steps support designers in defining liaisons and related properties and precedence among components with the aim to calculate the best disassembly sequence and time. The effective disassembly time is computed considering the actual conditions of a product and its components (e.g. deformation, rust and wear) using corrective factors. This aspect represents the main contribution to the state of the art in the field of design for disassembly. The corrective factors are derived from a specific data mining process, based on the observation of real de-manufacturing activities. The proposed approach has been used for calculating the disassembly times of target components in a washing machine and in a coffee machine. The case studies highlight the method reliability of both: definition of time-effective disassembly sequences and assessment of effective disassembly times. In particular, a comparison of experimental tests shows a maximum deviation of &#x2212;6% for the electric motor of the washing machine and &#x2212;3% for the water pump of the coffee machine.
Journal: International Journal of Production Research
Pages: 599-623
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1472404
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1472404
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Template-Type: ReDIF-Article 1.0
Author-Name: Qazi Shaheen Kabir
Author-X-Name-First: Qazi Shaheen
Author-X-Name-Last: Kabir
Author-Name: Yoshinori Suzuki
Author-X-Name-First: Yoshinori
Author-X-Name-Last: Suzuki
Title: Comparative analysis of different routing heuristics for the battery management of automated guided vehicles
Abstract: 
 This paper explores how different routing techniques for the battery management of automated guided vehicles (AGVs) can affect the performance of a system. Four heuristics available in the literature were the basis of this study. Simulation models were developed to investigate how the routing of an AGV towards a battery station can affect the productivity of a manufacturing facility. Results show that the best productivity can be achieved when a routing heuristic tries to jointly minimise the total travel distance and waiting time at a battery station. The gain in productivity, when compared with the highest possible gain theoretically achievable, is quite substantial. It was also found that higher frequency of decision-making (i.e. decisions with smaller time interval) about battery swapping helps to increase the productivity of a system.
Journal: International Journal of Production Research
Pages: 624-641
Issue: 2
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1475761
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1475761
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Template-Type: ReDIF-Article 1.0
Author-Name: Marly Monteiro de Carvalho
Author-X-Name-First: Marly Monteiro de
Author-X-Name-Last: Carvalho
Author-Name: Roque Rabechini Junior
Author-X-Name-First: Roque
Author-X-Name-Last: Rabechini Junior
Title: Impact of risk management on project performance: the importance of soft skills
Abstract: 
 This study aims to elucidate the relationship between risk management and project success, considering the contingent effect of project complexity. This approach also combines aspects of soft and hard skills. This methodological approach involves a literature review to underpin the conceptual framework and a survey for empirical validation, using structural equation modelling. The hypotheses were tested based on a field study involving 263 projects distributed among eight industries. The fieldwork involved interviews with project managers and risk managers and an analysis of internal company documents about the projects’ performance. The structural model presented herein provides a means for correlating the hard and soft sides of risk management with project success, understanding the moderating effect of project complexity. The soft side of risk management appears most prominently and explains 10.7% of the effect on project success. Moreover, the soft side supports the hard side, since we found a significant correlation that explains 25.3% of the effect on the hard side.
Journal: International Journal of Production Research
Pages: 321-340
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.919423
File-URL: http://hdl.handle.net/10.1080/00207543.2014.919423
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:2:p:321-340




Template-Type: ReDIF-Article 1.0
Author-Name: Guojun Zhang
Author-X-Name-First: Guojun
Author-X-Name-Last: Zhang
Author-Name: Yuhao Deng
Author-X-Name-First: Yuhao
Author-X-Name-Last: Deng
Author-Name: Haiping Zhu
Author-X-Name-First: Haiping
Author-X-Name-Last: Zhu
Author-Name: Hui Yin
Author-X-Name-First: Hui
Author-X-Name-Last: Yin
Title: Delayed maintenance policy optimisation based on  control chart
Abstract: 
 Data sharing between statistic process control (SPC) and condition-based maintenance is valuable and the joint optimisation has been studied, mostly focusing on the SPC control chart limits. Traditionally, maintenance is taken as a response to the control chart alarms, as soon as the alarm is released. This may not be a good decision due to the existence of false alarms and the loss of production interruptions. So this paper proposed a delayed maintenance policy. This policy allows a delay time for the detection and maintenance after an alarm. The operational state probabilities during the delayed period are estimated by Bayesian theory, and a Markov model is built for the monitoring–maintenance process. The model is validated by a Tecnomatix-based simulation, and then used to optimise the average delay time as well as the sampling parameters. Numerical results show that the improvements do exist in some cases, but it depends on the production conditions. Suggestions about when to perform delayed maintenance are also given through factorial analysis.
Journal: International Journal of Production Research
Pages: 341-353
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.923948
File-URL: http://hdl.handle.net/10.1080/00207543.2014.923948
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthew Tickle
Author-X-Name-First: Matthew
Author-X-Name-Last: Tickle
Author-Name: Dotun Adebanjo
Author-X-Name-First: Dotun
Author-X-Name-Last: Adebanjo
Author-Name: Robin Mann
Author-X-Name-First: Robin
Author-X-Name-Last: Mann
Author-Name: Francis Ojadi
Author-X-Name-First: Francis
Author-X-Name-Last: Ojadi
Title: Business improvement tools and techniques: a comparison across sectors and industries
Abstract: 
 The purpose of this study was to investigate the awareness, usage, perceived effectiveness and potential future use of improvement tools and techniques via two sets of comparisons: between public and private sector organisations, and between manufacturers and service organisations. The need for the study was driven by the current lack of understanding of the extent of improvement tools and techniques adoption on a global scale. A questionnaire survey of 453 respondents from over 20 countries was conducted and the quantitative data were analysed through use of the IBM SPSS software package. The study’s findings indicated that there are no significant differences between both sets of organisations for the majority of improvement tools and techniques. However, this study has shown that public sector organisations are more likely to adopt some improvement tools and techniques in comparison to their private sector counterparts. Similarly, service organisations are also more likely to adopt some improvement tools and techniques than their manufacturing counterparts. These results contradict the conventional perception that improvement tools and techniques are used more often by the private sector and manufacturing organisations.
Journal: International Journal of Production Research
Pages: 354-370
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.933274
File-URL: http://hdl.handle.net/10.1080/00207543.2014.933274
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Template-Type: ReDIF-Article 1.0
Author-Name: Rameshwar Dubey
Author-X-Name-First: Rameshwar
Author-X-Name-Last: Dubey
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Title: Exploring soft TQM dimensions and their impact on firm performance: some exploratory empirical results
Abstract: 
 The aim of the paper is to study soft total quality management practices and their impacts on firm performance. In the research, the systematic literature review was used. After identifying a research gap, a theoretical framework was developed and research hypotheses were formulated. We have further checked the validity and reliability of measurement items using confirmatory factor analysis. The research framework was tested using multiple linear regressions under the effect of controllable variables (i.e. size of employees, supply uncertainty and demand uncertainty) of firm performance. The research hypotheses are well supported, which is consistent with previous extant literature.
Journal: International Journal of Production Research
Pages: 371-382
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.933909
File-URL: http://hdl.handle.net/10.1080/00207543.2014.933909
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Template-Type: ReDIF-Article 1.0
Author-Name: Amir Hossein Azadnia
Author-X-Name-First: Amir Hossein
Author-X-Name-Last: Azadnia
Author-Name: Muhamad Zameri Mat Saman
Author-X-Name-First: Muhamad Zameri Mat
Author-X-Name-Last: Saman
Author-Name: Kuan Yew Wong
Author-X-Name-First: Kuan Yew
Author-X-Name-Last: Wong
Title: Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process
Abstract: 
 Within supply chains activities, selecting appropriate suppliers based on the sustainability criteria (economic, environmental and social) can help companies move toward sustainable development. Although several studies have recently been accomplished to incorporate sustainability criteria into supplier selection problem, much less attention has been devoted to developing a comprehensive mathematical model that allocates the optimal quantities of orders to suppliers considering lot-sizing problems. In this research, we propose an integrated approach of rule-based weighted fuzzy method, fuzzy analytical hierarchy process and multi-objective mathematical programming for sustainable supplier selection and order allocation combined with multi-period multi-product lot-sizing problem. The mathematical programming model consists of four objective functions which are minimising total cost, maximising total social score, maximising total environmental score and maximising total economic qualitative score. The proposed model is developed based on the parameters achieved through the preprocessing of suppliers’ social, environmental and economic data by a rule-based weighted fuzzy approach and fuzzy analytical hierarchy process. The proficiency and applicability of the proposed approach is illustrated by a case study of packaging films in food industry. Considering sustainability criteria in the proposed model reveals that a higher value of sustainable purchasing is achievable in comparison with a single-objective cost-based model.
Journal: International Journal of Production Research
Pages: 383-408
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.935827
File-URL: http://hdl.handle.net/10.1080/00207543.2014.935827
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Template-Type: ReDIF-Article 1.0
Author-Name: Claudia Neumüller
Author-X-Name-First: Claudia
Author-X-Name-Last: Neumüller
Author-Name: Florian Kellner
Author-X-Name-First: Florian
Author-X-Name-Last: Kellner
Author-Name: Jatinder N.D. Gupta
Author-X-Name-First: Jatinder N.D.
Author-X-Name-Last: Gupta
Author-Name: Rainer Lasch
Author-X-Name-First: Rainer
Author-X-Name-Last: Lasch
Title: Integrating three-dimensional sustainability in distribution centre selection: the process analysis method-based analytic network process
Abstract: 
 In this paper, we propose a combined methodology for the selection of distribution centres (DCs) by integrating and balancing economic, environmental and social sustainability aspects. The analytic network process (ANP) permits to systematically evaluate possible DCs on the basis of a situation-specific decision structure. A systematic development of the decision networks, which is one of the core challenges using the ANP, is supported by the process analysis method which we extend for that purpose. The validity and soundness of the proposed framework are demonstrated by means of a case study. The case study results reveal that omitting aspects of sustainability can lead to unfortunate results.
Journal: International Journal of Production Research
Pages: 409-434
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.939241
File-URL: http://hdl.handle.net/10.1080/00207543.2014.939241
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:2:p:409-434




Template-Type: ReDIF-Article 1.0
Author-Name: A. Ben-Salem
Author-X-Name-First: A.
Author-X-Name-Last: Ben-Salem
Author-Name: A. Gharbi
Author-X-Name-First: A.
Author-X-Name-Last: Gharbi
Author-Name: A. Hajji
Author-X-Name-First: A.
Author-X-Name-Last: Hajji
Title: An Environmental Hedging Point Policy to control production rate and emissions in unreliable manufacturing systems
Abstract: 
 This paper proposes a new Hedging Point Policy (HPP) which integrates environmental concerns into the optimal control of unreliable manufacturing systems. The considered system is composed of a production facility subjects to random failures and producing a product family intended for a given market with stable demand. The manufacturing facility’s operations cause harmful emissions to the environment, and may incur sanctions in the form of an environmental tax imposed by the relevant authorities. Given the significant compromise that must take place between inventory, backlog and taxes costs, the main objective of this paper is to propose a feedback adaptive control policy which provides a better control of the production rate and the emissions generated. Under the HPP category, a new structure called the Environmental Hedging Point Policy (EHPP) is proposed. To illustrate the effectiveness of the proposal, an experimental approach based on simulation modelling, variance analysis and response surface methodology (RSM) is applied. The results show a significant gain in terms of incurred costs compared to those incurred when the system is governed by a classical HPP. An improved version of EHPP is also proposed for systems with high emission rates. Several sensitivity analyses are conducted to illustrate the robustness and effectiveness of the proposed policies.
Journal: International Journal of Production Research
Pages: 435-450
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.946161
File-URL: http://hdl.handle.net/10.1080/00207543.2014.946161
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Erratum
Journal: International Journal of Production Research
Pages: 675-675
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.950450
File-URL: http://hdl.handle.net/10.1080/00207543.2014.950450
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Template-Type: ReDIF-Article 1.0
Author-Name: Wen-Hsien Tsai
Author-X-Name-First: Wen-Hsien
Author-X-Name-Last: Tsai
Author-Name: Tsen-Shu Tsaur
Author-X-Name-First: Tsen-Shu
Author-X-Name-Last: Tsaur
Author-Name: Yu-Wei Chou
Author-X-Name-First: Yu-Wei
Author-X-Name-Last: Chou
Author-Name: Jau-Yang Liu
Author-X-Name-First: Jau-Yang
Author-X-Name-Last: Liu
Author-Name: Jui-Ling Hsu
Author-X-Name-First: Jui-Ling
Author-X-Name-Last: Hsu
Author-Name: Chu-Lun Hsieh
Author-X-Name-First: Chu-Lun
Author-X-Name-Last: Hsieh
Title: Integrating the activity-based costing system and life-cycle assessment into green decision-making
Abstract: 
 The main objective of this study is to develop a model for decision-making associated with the activity-based costing (ABC) system within the life-cycle assessment (LCA) aspects for the electrical and electronic industry. In order to maximise a company’s profits and minimise environmental impact within limited constraints and resources, a mathematical programming model and green optimal manufacturing decisions have been proposed. Our findings provide insight into ‘green businesses’, and are beneficial in terms of environmental management in a competitive industry. The proposed programming model is put forward as a green management tool that provides enterprise advantages and niches, and reaches environmental sustainability goals.
Journal: International Journal of Production Research
Pages: 451-465
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.951089
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951089
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Template-Type: ReDIF-Article 1.0
Author-Name: Khosrow Noshad
Author-X-Name-First: Khosrow
Author-X-Name-Last: Noshad
Author-Name: Anjali Awasthi
Author-X-Name-First: Anjali
Author-X-Name-Last: Awasthi
Title: Supplier quality development: A review of literature and industry practices
Abstract: 
 Managing quality of suppliers is of prime importance in supply chains to minimise costs arising due to poor-quality products and services. Supplier quality development (SQD) is a strategic quality development activity for increasing quality, reliability and efficiency of suppliers. This paper reports results of review on the academic literature and industrial practices on SQD in order to find main concepts, steps, prevalent methodologies, tools and techniques, and best practices. We reviewed 177 papers from years 1980–2013 including 22 company manuals for conducting this study. The proposed review assists readers in developing a better understanding of SQD, involved processes and their key elements, tools and techniques used, challenges in supplier quality management, best practices from academics and industry, and open research problems in SQD that require detailed investigation.
Journal: International Journal of Production Research
Pages: 466-487
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.954679
File-URL: http://hdl.handle.net/10.1080/00207543.2014.954679
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Template-Type: ReDIF-Article 1.0
Author-Name: Weihua Liu
Author-X-Name-First: Weihua
Author-X-Name-Last: Liu
Author-Name: Dong Xie
Author-X-Name-First: Dong
Author-X-Name-Last: Xie
Author-Name: Yang Liu
Author-X-Name-First: Yang
Author-X-Name-Last: Liu
Author-Name: Xiaoyan Liu
Author-X-Name-First: Xiaoyan
Author-X-Name-Last: Liu
Title: Service capability procurement decision in logistics service supply chain: a research under demand updating and quality guarantee
Abstract: 
 Though existing researches have already studied on service quality guarantee and demand updating in a supply chain respectively, there is little attention paid to integrated research on service quality guarantee problem with demand updating. This paper aims to investigate the impacts of demand uncertainty revelation and quality guarantee change cost (GCC) on the optimal decisions of logistics service integrator (LSI) and functional logistics service provider (FLSP) in a logistics service supply chain. At the beginning of the first period, the FLSP first guarantees an initial quality level and the LSI procures service capacity from the FLSP based on the demand prediction. Then the demand information is updated after the first-period demand being satisfied, and the LSI and the FLSP make their optimal decisions based on the renewed demand in the next period. Before the second period, uncertainty complete revelation/uncertainty incomplete revelation (UCR/UIR) and GCC/no guarantee change cost (NGCC) may take place, which will affect the decisions the LSI and the FLSP make. Consequently, four situations are considered: (1) UCR and GCC; (2) UIR and GCC; (3) UCR and NGCC; and (4) UIR and NGCC. In each situation, we derive the optimal decisions of the FLSP and the LSI, and a comparison between the first- and second-period decisions in each situation is conducted. Several managerial insights are concluded, and the most important one is that the LSI is supposed to reduce the procurement quantity and the FLSP is supposed to promise a higher quality defect rate in the case of UIR and NGCC. Furthermore, in case of UIR and GCC, we specify a critical condition in which the LSI and the FLSP insist on the initial decisions of the first period. At last, we conducted numerical analysis and gave a practical example of China Yuantong Express Company to support our conclusions.
Journal: International Journal of Production Research
Pages: 488-510
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.955219
File-URL: http://hdl.handle.net/10.1080/00207543.2014.955219
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Template-Type: ReDIF-Article 1.0
Author-Name: Hongyan Dai
Author-X-Name-First: Hongyan
Author-X-Name-Last: Dai
Author-Name: Mitchell M. Tseng
Author-X-Name-First: Mitchell M.
Author-X-Name-Last: Tseng
Author-Name: Paul H. Zipkin
Author-X-Name-First: Paul H.
Author-X-Name-Last: Zipkin
Title: Design of traceability systems for product recall
Abstract: 
 A product recall is very expensive and a poorly executed recall can be devastating to a company’s reputation. It is, therefore, important to improve the traceability for supply chains to address potential recalls. This paper studies the recall dynamics in a two-stage supply chain with a manufacturer and two suppliers. It is shown that the suppliers would opt-out in improving traceability due to misalignment of incentives, leading to diminishing traceability of the whole supply chain and high product recall liabilities for the manufacturer. To address this problem, this research designs an interest-sharing mechanism by which the recall liability reduction of the manufacturer due to improved traceability can be shared with the suppliers to induce traceability improvement effort. Results show that the interest-sharing mechanism improves not only the economic benefit, but also the traceability for each party. We also provide a systematic framework to choose the design parameters, including the degree of accuracy and level of coding, for the supply chain to realise such benefits.
Journal: International Journal of Production Research
Pages: 511-531
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.955922
File-URL: http://hdl.handle.net/10.1080/00207543.2014.955922
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Template-Type: ReDIF-Article 1.0
Author-Name: Biyu Liu
Author-X-Name-First: Biyu
Author-X-Name-Last: Liu
Author-Name: Martin Holmbom
Author-X-Name-First: Martin
Author-X-Name-Last: Holmbom
Author-Name: Anders Segerstedt
Author-X-Name-First: Anders
Author-X-Name-Last: Segerstedt
Author-Name: Weida Chen
Author-X-Name-First: Weida
Author-X-Name-Last: Chen
Title: Effects of carbon emission regulations on remanufacturing decisions with limited information of demand distribution
Abstract: 
 Policy-makers are developing regulation policies to drive down carbon emissions from industries. Independent remanufacturers (IRs), which remanufacture recycled products/components/parts, must manage and evaluate economic costs generated by the production under future carbon emission regulations. We present three optimisation models to determine the remanufacturing quantity that maximises the total profits under three common carbon emission regulation policies: (a) mandatory carbon emissions capacity, (b) carbon tax and (c) cap and trade. These models include sales revenue, remanufacturing cost, disposal cost, inventory holding cost, shortage cost and carbon emission cost. The max–min approach is used to solve the models, which assume limited information on demand distribution. We investigate how the three regulation policies affect remanufacturing decision-making for IRs and we also solve some numerical examples where we vary the magnitudes of incentives, penalties and stringency of constraints to provide implications to policy-makers. The results indicate that remanufacturers should aim to improve yield rate to maximise the profit irrespective of the implemented carbon emissions policy. Policy-makers should prefer the carbon tax policy, if any of the other two policies must be performed, a remanufacturing discount such as a higher carbon emission cap or lower penalty should be implemented to better promote the development of remanufacturers.
Journal: International Journal of Production Research
Pages: 532-548
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.957875
File-URL: http://hdl.handle.net/10.1080/00207543.2014.957875
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Template-Type: ReDIF-Article 1.0
Author-Name: Awanis Romli
Author-X-Name-First: Awanis
Author-X-Name-Last: Romli
Author-Name: Paul Prickett
Author-X-Name-First: Paul
Author-X-Name-Last: Prickett
Author-Name: Rossitza Setchi
Author-X-Name-First: Rossitza
Author-X-Name-Last: Setchi
Author-Name: Shwe Soe
Author-X-Name-First: Shwe
Author-X-Name-Last: Soe
Title: Integrated eco-design decision-making for sustainable product development
Abstract: 
 This paper presents an integrated eco-design decision-making (IEDM) methodology that is formed using three stages: life cycle assessment, an eco-design process (Eco-Process) model and an enhanced eco-design quality function deployment process. All product sustainability considerations are conducted within a special eco-design house of quality. This brings together the analysis of factors relating to manufacturing processes, product usage and end-of-life strategy. The concentration of environmental considerations in one place insures that product sustainability is central to any design development and that the implications of change are fully identified and justified. The IEDM methodology utilises of a set of Eco-Process parameters and their associated relationships to allow users with complementary knowledge to enter and access information in a timely and controlled manner. They are then able to contribute their expertise to support decisions with the aim of providing more sustainable products. An application of the approach is presented in the context of a case study considering the redesign of a single-use medical forceps. The materials and production methods used are investigated with a view to quantifying their environmental impact. The resulting IEDM methodology can be seen to be widely and easily applicable.
Journal: International Journal of Production Research
Pages: 549-571
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.958593
File-URL: http://hdl.handle.net/10.1080/00207543.2014.958593
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Template-Type: ReDIF-Article 1.0
Author-Name: Gu Pang
Author-X-Name-First: Gu
Author-X-Name-Last: Pang
Author-Name: Fabrizio Casalin
Author-X-Name-First: Fabrizio
Author-X-Name-Last: Casalin
Author-Name: Savvas Papagiannidis
Author-X-Name-First: Savvas
Author-X-Name-Last: Papagiannidis
Author-Name: Luc Muyldermans
Author-X-Name-First: Luc
Author-X-Name-Last: Muyldermans
Author-Name: Ying Kei Tse
Author-X-Name-First: Ying Kei
Author-X-Name-Last: Tse
Title: Price determinants for remanufactured electronic products: a case study on eBay UK
Abstract: 
 In this paper, we analyse the market determinants of price differentials between new and remanufactured products in Electronics using data on purchases made on eBay UK. The empirical analysis is carried out by means of linear regression methods, which are capable of controlling for the presence of collinearity among the explanatory variables. Our empirical results suggest that the seller reputation, length of warranties, proxies of demand and supply of remanufactured products, duration, end day of product listings as well as the availability of return policies are important determinants of price differentials. Most importantly, we find that the seller identity plays an important role, as our empirical results are predominantly driven by transactions carried out by non-manufacturer-approved vendors.
Journal: International Journal of Production Research
Pages: 572-589
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.958594
File-URL: http://hdl.handle.net/10.1080/00207543.2014.958594
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrea Chiarini
Author-X-Name-First: Andrea
Author-X-Name-Last: Chiarini
Author-Name: Emidia Vagnoni
Author-X-Name-First: Emidia
Author-X-Name-Last: Vagnoni
Title: World-class manufacturing by Fiat. Comparison with Toyota Production System from a Strategic Management, Management Accounting, Operations Management and Performance Measurement dimension
Abstract: 
 Toyota Production System (TPS) and the derived lean production have cast a shadow over the models of world-class manufacturing (WCM). Yet, some groups such as Fiat have reinvented WCM. Fiat’s WCM is quickly becoming a sort of alternative to TPS-lean production. By means of semi-structured interviews and a direct observation of the documentation of Fiat’s model, this research wants to find the theoretical elements that underpin the model. The methodology is mainly based on grounded theory. The theoretical elements were coded and classified within four dimensions: strategic management, management accounting, operations management and performance measurement system. The four dimensions and their elements were compared for the first time with the same dimensions of TPS-lean production. Fiat’s WCM seems to have a ‘grand strategy’ focused on quality and cost savings where quality must be reached with no trade-off with other strategies. Safety is pursued above all else and Fiat’s WCM cannot be implemented without this first achievement. A particular system called ‘cost deployment’ measures wastes and losses on processes. The performance measurement system is structured and fosters day-by-day management as well as computer-based management. Furthermore, the performance measurement system is based on a complex and formal auditing and benchmarking process.
Journal: International Journal of Production Research
Pages: 590-606
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.958596
File-URL: http://hdl.handle.net/10.1080/00207543.2014.958596
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaojun Pan
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Pan
Author-Name: Shoude Li
Author-X-Name-First: Shoude
Author-X-Name-Last: Li
Title: Optimal control of a stochastic production–inventory system under deteriorating items and environmental constraints
Abstract: 
 In this paper, we present an optimal control model of a stochastic production–inventory with deteriorating items, emission tax and pollution abatement investment. In our model, the emission tax is levied on the firm’s environmental obsolescence rate of technology rather than the total amount of the environmental externality. Our objective is to apply Hamilton–Jacobi–Bellman (HJB) equation to solve the stochastic production–inventory system with deteriorating items, emission tax and pollution abatement investment; and derive the optimal production rate and pollution abatement investment rate that maximise the objective function value. The results are discussed with some illustrative examples for different demand rate functions, and sensitivity analysis is conducted to study the effect of changing the parameters and coefficients on the objective function value.
Journal: International Journal of Production Research
Pages: 607-628
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.961201
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961201
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Template-Type: ReDIF-Article 1.0
Author-Name: Xianghui Peng
Author-X-Name-First: Xianghui
Author-X-Name-Last: Peng
Author-Name: Victor Prybutok
Author-X-Name-First: Victor
Author-X-Name-Last: Prybutok
Title: Relative effectiveness of the Malcolm Baldrige National Quality Award categories
Abstract: 
 This study fills a critical research gap by assessing the effectiveness of the Malcolm Baldrige National Quality Award (MBNQA) model within a government organisation and by comparing the effectiveness of the categories within the MBNQA model in government to the effectiveness of the categories of the MBNQA model in different industries. This study examines the relative effectiveness of each Baldrige category in the MBNQA 2013–2014 framework to results using data from a municipal government. We tested the hypothesised research model employing partial least squares (structural equation modelling). The results validate the effectiveness of the Baldrige categories and quantitatively support the theoretical foundations of the Baldrige model. Drawing on contingency theory, we explore the commonalities and differences of the effectiveness of Baldrige categories across different industries. The comparisons provide evidence that the Baldrige model has experienced the appropriate adaptations over years. This work discusses theoretical and managerial implications, and suggests future research directions.
Journal: International Journal of Production Research
Pages: 629-647
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.961207
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961207
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Template-Type: ReDIF-Article 1.0
Author-Name: Monika Manglik
Author-X-Name-First: Monika
Author-X-Name-Last: Manglik
Author-Name: Mangey Ram
Author-X-Name-First: Mangey
Author-X-Name-Last: Ram
Title: Behavioural analysis of a hydroelectric production power plant under reworking scheme
Abstract: 
 By high calibre of the fundamental nature of electric power, both of our economic and personal interests, a system is expected to supply as electrical energy as possible with the highest degree of quality and reliability. This research work aimed to evaluate the reliability measures of a hydroelectric power station. The results of this study are deliberate to provide the improved criteria for upcoming proposals, and serves as a basis for generation expansion planning of hydroelectric power stations. This paper presents a Markov-process based mathematical model for a hydroelectric power plant. The important reliability measures have been derived and discussed with the help of failure and repair rates through the analysis. This research gives a clear view of how the hydropower plants are modelled by defining the states under the failure and repair rates.
Journal: International Journal of Production Research
Pages: 648-664
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.962114
File-URL: http://hdl.handle.net/10.1080/00207543.2014.962114
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:2:p:648-664




Template-Type: ReDIF-Article 1.0
Author-Name: Wei-Feng Guo
Author-X-Name-First: Wei-Feng
Author-X-Name-Last: Guo
Author-Name: Jian Zhou
Author-X-Name-First: Jian
Author-X-Name-Last: Zhou
Author-Name: Chih-Lang Yu
Author-X-Name-First: Chih-Lang
Author-X-Name-Last: Yu
Author-Name: Sang-Bing Tsai
Author-X-Name-First: Sang-Bing
Author-X-Name-Last: Tsai
Author-Name: You-Zhi Xue
Author-X-Name-First: You-Zhi
Author-X-Name-Last: Xue
Author-Name: Quan Chen
Author-X-Name-First: Quan
Author-X-Name-Last: Chen
Author-Name: Jiann-Jong Guo
Author-X-Name-First: Jiann-Jong
Author-X-Name-Last: Guo
Author-Name: Po-Yu Huang
Author-X-Name-First: Po-Yu
Author-X-Name-Last: Huang
Author-Name: Chia-Huei Wu
Author-X-Name-First: Chia-Huei
Author-X-Name-Last: Wu
Title: Evaluating the green corporate social responsibility of manufacturing corporations from a green industry law perspective
Abstract: 
 Corporate social responsibility (CSR) refers to corporations exhibiting ethical behaviours towards societal members. This responsibility should be demonstrated towards all stakeholders rather than only stockholders. Corporations should be responsible for the effects that their actions have on stakeholders by assuming a fair and responsible attitude and valuing sustainable development. Corporations that affect their stakeholders must assume their responsibilities by focusing on sustainable development and exhibiting a fair attitude; for example, providing staff members with a positive work environment, introducing green products, sustaining environmental quality, offering satisfactory after-sales services and maintaining positive interaction with the community. Relevant studies that have integrated green production (GP) with CSR evaluation were scarce in the past. Moreover, previous studies regarding standard criteria for CSR evaluation have involved a major shortcoming, in that a majority of these studies have assumed mutual independence and no influencing and causal relationships among CSR criteria. The present study focused on GP and employed a novel decision-making trial and evaluation laboratory method to evaluate and investigate green corporate social responsibility (GCSR) indicators. In addition, the degrees of influence and the causal relationships among GCSR indicators were explored.
Journal: International Journal of Production Research
Pages: 665-674
Issue: 2
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.972525
File-URL: http://hdl.handle.net/10.1080/00207543.2014.972525
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanfeng Xing
Author-X-Name-First: Yanfeng
Author-X-Name-Last: Xing
Author-Name: Min Hu
Author-X-Name-First: Min
Author-X-Name-Last: Hu
Author-Name: He Zeng
Author-X-Name-First: He
Author-X-Name-Last: Zeng
Author-Name: Yansong Wang
Author-X-Name-First: Yansong
Author-X-Name-Last: Wang
Title: Fixture layout optimisation based on a non-domination sorting social radiation algorithm for auto-body parts
Abstract: 
 Auto-body compliant parts are easily deformed during clamping and welding, and fixture layout is very important to the final product quality. However, it is very difficult to design fixture layout because it needs to synchronously satisfy the requirements of assembly tolerance and gravity deformation, which are calculated by finite element analysis. This paper proposes a new method to optimise fixture scheme by a non-domination sorting social radiation algorithm (NSSRA). Firstly, unfeasible nodes are eliminated by four rules according to manufacturing experiences. Afterwards, a few groups are divided based on positions of all feasible nodes. N groups are optimised using NSSRA. Finally, the best fixture layout is generated by selecting the feasible points among the optimal groups in last step. A case study of inner hood is used to illustrate the proposed method, and the results suggest that NSSRA has better efficiency and higher accuracy than NSGA-II.
Journal: International Journal of Production Research
Pages: 3475-3490
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.1003662
File-URL: http://hdl.handle.net/10.1080/00207543.2014.1003662
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Template-Type: ReDIF-Article 1.0
Author-Name: K.K. Starkov
Author-X-Name-First: K.K.
Author-X-Name-Last: Starkov
Author-Name: A.Y. Pogromsky
Author-X-Name-First: A.Y.
Author-X-Name-Last: Pogromsky
Author-Name: I.J.B.F. Adan
Author-X-Name-First: I.J.B.F.
Author-X-Name-Last: Adan
Title: Manufacturing lines under surplus-based control: multiple products and bounded buffers
Abstract: 
 Challenged by the scheduling complexity for production flow processes in industrial facilities, we study the performance of multi-product producing lines. We analyse the performance of multi-product lines that consist a number of machines and bounded buffers with preselected base stock levels. It is assumed that each manufacturing machine in the line is capable of working with several product types, but only operate on one product at a time. The network is operated under a surplus-based production control policy in the presence of perturbations and production demand fluctuations. We derive bounds on the demand tracking accuracy for each product type, regardless its flow direction in the multi-product line. In addition, for a multi-product line with unidirectional product flow, we obtain a quantitative relation between demand tracking accuracy, its inventory levels, numbers of product types, buffer capacity limits and perturbations. The accuracy of the obtained demand tracking bounds is illustrated by numerical simulations. By means of simulation experiments, we show that the obtained results have a valuable meaning and can be used as a reference tool in practice.
Journal: International Journal of Production Research
Pages: 3491-3504
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2015.1012602
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1012602
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Template-Type: ReDIF-Article 1.0
Author-Name: Gun Srijuntongsiri
Author-X-Name-First: Gun
Author-X-Name-Last: Srijuntongsiri
Author-Name: Stanislav S. Makhanov
Author-X-Name-First: Stanislav S.
Author-X-Name-Last: Makhanov
Title: Optimisation of five-axis machining G-codes in the angular space
Abstract: 
 Reducing the kinematic errors is an important problem in five-axis machining. Errors of this type substantially affect the quality of the five-axis manufacturing. In this paper, we propose and analyse a new numerical algorithm to reduce the kinematic errors of a five-axis tool path using minimisation of the variation of the rotation angles. Our algorithm finds the locations of the cutter contact points (CC points) in the angular space and the orientation/location of the target surface relative to the mounting table that minimise the angle variation. We show through the numerical experiments and cutting simulations that the proposed method is efficient and accurate.
Journal: International Journal of Production Research
Pages: 3207-3227
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.965421
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965421
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Template-Type: ReDIF-Article 1.0
Author-Name: Yi-Kuei Lin
Author-X-Name-First: Yi-Kuei
Author-X-Name-Last: Lin
Author-Name: Ping-Chen Chang
Author-X-Name-First: Ping-Chen
Author-X-Name-Last: Chang
Title: Demand satisfaction and decision-making for a PCB manufacturing system with production lines in parallel
Abstract: 
 This paper studies demand satisfaction and decision-making for a printed circuit board (PCB) manufacturing system. A performance indicator, the system reliability, is proposed to evaluate the demand satisfaction. In particular, two important characteristics, (i) multiple production lines in parallel and (ii) multiple repair actions, are considered in this study. The PCB manufacturing system is modelled as a stochastic-flow manufacturing network (SFMN) by the graphical transformation and decomposition techniques. Based on the network-structured SFMN, this paper develops an algorithm to generate all minimal capacity vectors that workstations should provide to satisfy a given demand. In terms of all minimal capacity vectors, the system reliability is derived. In addition, the reliable production policy is determined based on each single minimal capacity vector.
Journal: International Journal of Production Research
Pages: 3193-3206
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.965851
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965851
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Template-Type: ReDIF-Article 1.0
Author-Name: Afrooz Moatari-Kazerouni
Author-X-Name-First: Afrooz
Author-X-Name-Last: Moatari-Kazerouni
Author-Name: Yuvin Chinniah
Author-X-Name-First: Yuvin
Author-X-Name-Last: Chinniah
Author-Name: Bruno Agard
Author-X-Name-First: Bruno
Author-X-Name-Last: Agard
Title: Integration of occupational health and safety in the facility layout planning, part II: design of the kitchen of a hospital
Abstract: 
 Facility layout design has an important effect on the performance of manufacturing systems. It intends to determine relative location of departments and machines within a plant. A good layout design must ensure that a set of criteria and objectives are met and optimised, e.g. area requirements, cost, communication and safety. The most common objective used in facility planning methods is to minimise the transportation cost. However, factors such as the plant safety, flexibility for future design changes, noise and aesthetics must be considered as well. In this paper, a case study is carried out to investigate the safety concerns in facility layout design. In this regard, a facility layout planning methodology, integrating occupational health and safety (OHS) is presented. This methodology considers transportation cost as well as safety in the facility design. By this means, OHS issues are considered at the design stage of the facility. In other words, this research demonstrates the improvements in the layout design by integrating safety aspects.
Journal: International Journal of Production Research
Pages: 3228-3242
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.970711
File-URL: http://hdl.handle.net/10.1080/00207543.2014.970711
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:11:p:3228-3242




Template-Type: ReDIF-Article 1.0
Author-Name: Afrooz Moatari-Kazerouni
Author-X-Name-First: Afrooz
Author-X-Name-Last: Moatari-Kazerouni
Author-Name: Yuvin Chinniah
Author-X-Name-First: Yuvin
Author-X-Name-Last: Chinniah
Author-Name: Bruno Agard
Author-X-Name-First: Bruno
Author-X-Name-Last: Agard
Title: Integrating occupational health and safety in facility layout planning, part I: methodology
Abstract: 
 An influential factor affecting the efficiency of a manufacturing facility is its layout. In a production facility, measure for efficiency can be based on the total cost of transporting the items between different departments and throughout the facility. However, other factors may influence efficiency of the manufacturing facility too. As such are: supporting the organisation's vision through improved material handling, material flow and control; effectively assigning people, equipment, space and energy; minimising capital investment; adaptability and ease of maintenance; as well as providing for employee safety and job satisfaction. By incorporating health and safety measures in the initial design of a facility layout, the organisation may avoid money and manpower loss resulting from industrial accidents. This paper proposes a facility layout planning methodology which integrates the occupational health and safety (OHS) features in the early design of a facility layout. The model considers transportation cost in the facility as well as safety concerns. By this means, the OHS issues are reflected prior to the construction of a facility.
Journal: International Journal of Production Research
Pages: 3243-3259
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.970712
File-URL: http://hdl.handle.net/10.1080/00207543.2014.970712
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Template-Type: ReDIF-Article 1.0
Author-Name: Juan A. Marin-Garcia
Author-X-Name-First: Juan A.
Author-X-Name-Last: Marin-Garcia
Author-Name: Tomas Bonavia
Author-X-Name-First: Tomas
Author-X-Name-Last: Bonavia
Title: Relationship between employee involvement and lean manufacturing and its effect on performance in a rigid continuous process industry
Abstract: 
 This research aims to empirically test the effect of employee involvement on lean manufacturing (LM), and the effect of LM on production outcomes. Employee involvement is operationalised through four related variables: empowerment, training, contingent remuneration and communication. The effects are tested by recording management perceptions in a different industrial sector from those usually studied in previous research – ceramic manufacturers, a highly competitive and internationally successful sector. We obtained data from 101 ceramic tile plants (64% of response rate) in the Valencia region of Spain. This approach is developed using a statistical method called partial least squares. All paths are significant except for contingent remuneration; specifically, relationships were found between empowerment, training, communication and LM, and between LM and performance.
Journal: International Journal of Production Research
Pages: 3260-3275
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.975852
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975852
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Template-Type: ReDIF-Article 1.0
Author-Name: A. Azadeh
Author-X-Name-First: A.
Author-X-Name-Last: Azadeh
Author-Name: M. Rezaei-Malek
Author-X-Name-First: M.
Author-X-Name-Last: Rezaei-Malek
Author-Name: F. Evazabadian
Author-X-Name-First: F.
Author-X-Name-Last: Evazabadian
Author-Name: M. Sheikhalishahi
Author-X-Name-First: M.
Author-X-Name-Last: Sheikhalishahi
Title: Improved design of CMS by considering operators decision-making styles
Abstract: 
 Cell formation is one of the oldest problems in cellular manufacturing systems (CMS) including assigning parts, machines and operators to cells. Cell manufacturing contains a number of cells where each cell is responsible for processing the family of similar parts. Another important aspect of cell formation is worker assignment to cells. Since operators work together in long periods, it is suggested to consider operators’ personal characteristics to increase their satisfaction and the productivity of system. This paper considers decision-making styles of operators (as an index of operator’s personal characteristics) and presents a new mathematical programming model for clustering parts, machines and workers simultaneously. The model includes two objectives; (1) minimization of intracellular movements and cell establishment costs, (2) minimization of decision-making style inconsistency among operators in each cell. The paper applies ε-constraint method for solving the problem and gathering non-dominated solutions such as Pareto optimal solutions. Furthermore, this paper uses common weighted multicriteria decision analysis (MCDA)-data envelopment analysis method to choose the best solution from the candidate Pareto optimal solutions that have been achieved by solving the mathematical model. A real case study is investigated to show the capability of the proposed model to design CMS in the assembly unit. The proposed design assists decision-makers to develop cellular systems with more operators’ satisfaction and productivity.
Journal: International Journal of Production Research
Pages: 3276-3287
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.975860
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975860
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Template-Type: ReDIF-Article 1.0
Author-Name: Maurizio Faccio
Author-X-Name-First: Maurizio
Author-X-Name-Last: Faccio
Author-Name: Mauro Gamberi
Author-X-Name-First: Mauro
Author-X-Name-Last: Gamberi
Author-Name: Francesco Pilati
Author-X-Name-First: Francesco
Author-X-Name-Last: Pilati
Author-Name: Marco Bortolini
Author-X-Name-First: Marco
Author-X-Name-Last: Bortolini
Title: Packaging strategy definition for sales kits within an assembly system
Abstract: 
 Packaging is typically the last task in a production process, especially in an assembly system. If an assembled product is sold as a single unit, its packaging is normally performed by the last workstation, in order to obtain a ready-for-sale product. Moreover, assembled product often comes with its accessories, packaged all together and supplied to the customer as a single unit: a sales kit. Due to the variety of products and accessories, the variety of kits is continuously increasing, requiring a complex definition of the best packaging strategy to adopt. The present paper aims to analyse the packaging problem in a production system, identifying and comparing the packaging strategies. These strategies provide, through a comparison model of total cost functions, a decision-making procedure for operations managers. Through a simulative study, a set of convenience areas for each analysed packaging strategy is derived. The findings from an industrial case study are also reported to validate the proposed methodology.
Journal: International Journal of Production Research
Pages: 3288-3305
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.975862
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975862
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Template-Type: ReDIF-Article 1.0
Author-Name: Kees Jan Roodbergen
Author-X-Name-First: Kees Jan
Author-X-Name-Last: Roodbergen
Author-Name: Iris F.A. Vis
Author-X-Name-First: Iris F.A.
Author-X-Name-Last: Vis
Author-Name: G. Don Taylor
Author-X-Name-First: G. Don
Author-X-Name-Last: Taylor
Title: Simultaneous determination of warehouse layout and control policies
Abstract: 
 In a supply chain’s order fulfilment process, it is often the warehouse that plays a central role in making the right product available to the right customer at the right time. This paper aims to improve warehouse performance by deriving an effective design method for the simultaneous determination of warehouse layout and the warehouse’s control policies. The authors consider layout variables for the warehouse such as the number of primary aisles utilised, the number of cross-aisles and the aisle length under several different design philosophies. Concurrently, control policies such as storage policies and routing are considered. Simulation is utilised to determine the performance of the various resulting scenarios. A screening and selection procedure is employed to reduce the required number of replications while achieving a predetermined precision in identifying the best configuration. The approach is applied for an industrial partner in this research and the results of experimentation are compared to a baseline scenario which describes a proposed new facility in the Netherlands. The results reveal a large potential for performance improvement.
Journal: International Journal of Production Research
Pages: 3306-3326
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.978029
File-URL: http://hdl.handle.net/10.1080/00207543.2014.978029
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:11:p:3306-3326




Template-Type: ReDIF-Article 1.0
Author-Name: Jordi Pereira
Author-X-Name-First: Jordi
Author-X-Name-Last: Pereira
Title: Empirical evaluation of lower bounding methods for the simple assembly line balancing problem
Abstract: 
 The simple assembly line balancing problem (SALBP) is a classical problem that arises in the design of assembly lines. The objective of the SALBP is to divide the assembly work among different workstations of the assembly line in order to maximise the efficiency of the entire line. In this paper, we: (a) put forward different families of lower bounds for the SALBP; (b) introduce new lower bounds; (c) generalise previous results; and (d) analyse the performance of these lower bounding techniques in terms of solution quality using a recently proposed set of instances. An analysis of the results of these bounds leads us to: (1) improve the best-known lower bound for 104 out of the 175 open instances from the benchmark set; (2) identify the areas of applicability of different sources of bounds; and (3) identify possible uses of these bounds in other assembly line balancing problems.
Journal: International Journal of Production Research
Pages: 3327-3340
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.980014
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980014
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Template-Type: ReDIF-Article 1.0
Author-Name: Shih Jia Lee
Author-X-Name-First: Shih Jia
Author-X-Name-Last: Lee
Author-Name: Ek Peng Chew
Author-X-Name-First: Ek Peng
Author-X-Name-Last: Chew
Author-Name: Loo Hay Lee
Author-X-Name-First: Loo Hay
Author-X-Name-Last: Lee
Author-Name: Julius Thio
Author-X-Name-First: Julius
Author-X-Name-Last: Thio
Title: A study on crate sizing problems
Abstract: 
 This paper studies the crate sizing problem to predetermine optimal standard packaging crate sizes for a demand of assorted sizes of products to minimise space and costs. The crate sizing problem is a real world logistics scenario faced by an existing multinational corporation in the applied chemistry industry. Customer demands come in a mix of rolls to be packaged in individual crates and then shipped in shipping containers from plants to customers. Firstly, a linear crate length optimisation model is introduced with the objective to minimise the total loss of extra space inside the crates for a given distribution of customer demands. In order to take inventory costs of crates into consideration, a second problem is introduced to both find the optimal number of crate types and the corresponding lengths such that the total costs of packaging and inventory are minimised. The latter problem is first formulated as a non-linear optimisation model and then solved using dynamic programming approach to balance the trade-off between the number of crate types and the penalty cost for space wastage inside the crates.
Journal: International Journal of Production Research
Pages: 3341-3353
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.980453
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980453
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:11:p:3341-3353




Template-Type: ReDIF-Article 1.0
Author-Name: A. Calleja
Author-X-Name-First: A.
Author-X-Name-Last: Calleja
Author-Name: M.A. Alonso
Author-X-Name-First: M.A.
Author-X-Name-Last: Alonso
Author-Name: A. Fernández
Author-X-Name-First: A.
Author-X-Name-Last: Fernández
Author-Name: I. Tabernero
Author-X-Name-First: I.
Author-X-Name-Last: Tabernero
Author-Name: I. Ayesta
Author-X-Name-First: I.
Author-X-Name-Last: Ayesta
Author-Name: A. Lamikiz
Author-X-Name-First: A.
Author-X-Name-Last: Lamikiz
Author-Name: L.N. López de Lacalle
Author-X-Name-First: L.N.
Author-X-Name-Last: López de Lacalle
Title: Flank milling model for tool path programming of turbine blisks and compressors
Abstract: 
 In this paper, a methodology for complex surface machining based on cutting forces prediction is presented. The work is focused on blade finishing operations. The cutting forces model developed can be applied to three axis and five axis milling cases. For three-axis cases, the chip thickness is calculated according to traditional analytical methods. On the contrary, for five-axis cases the chip thickness is obtained from a geometric method developed in the paper. The cutting forces values can be calculated for the complete toolpath, but the presented model can also provide the programmer information about the cutting forces in a single point of the toolpath. The cutting force model is integrated in the CAM software in order to provide an extra tool that helps the programmer to decide which the optimal milling strategy is, based on the minimum cutting forces. In the last section, results of a case study based on impeller and blisk blades flank milling are discussed. Model predicted forces and real measured forces of flank milling operations are compared for model validation. Applying this methodology, cutting forces can be taken into account as a decisive criterion for optimal tool path selection.
Journal: International Journal of Production Research
Pages: 3354-3369
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.983619
File-URL: http://hdl.handle.net/10.1080/00207543.2014.983619
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:11:p:3354-3369




Template-Type: ReDIF-Article 1.0
Author-Name: A. Azadeh
Author-X-Name-First: A.
Author-X-Name-Last: Azadeh
Author-Name: T. Nazari
Author-X-Name-First: T.
Author-X-Name-Last: Nazari
Author-Name: H. Charkhand
Author-X-Name-First: H.
Author-X-Name-Last: Charkhand
Title: Optimisation of facility layout design problem with safety and environmental factors by stochastic DEA and simulation approach
Abstract: 
 This article presents an integrated computer simulation–stochastic data envelopment analysis (SDEA) approach to deal with the job shop facility layout design problem (JSFLD) with stochastic outputs and safety and environmental factors. Stochastic outputs are defined as non-crisp operational and deterministic inputs. At first, feasible layout alternatives are generated under expert decision. Then, computer simulation network is used for performance modelling of each layout design. The outputs of simulation are average time-in-system, average queue length and average machine utilisation. Finally, SDEA is used with Lingo software for finding the optimum layout alternative amongst all feasible generated alternatives with respect to stochastic, safety and environmental indicators. The integrated approach of this study was more precise and efficient than previous studies with the stated outputs. The results have been verified and validated by principal component analysis. The unique features of this study are the ability of dealing with multiple inputs (including safety) and stochastic (including environmental) outputs. It also uses mathematical programming for optimum layout alternatives. Moreover, it is a practical tool and may be applied in real cases by considering safety and environmental aspects of the manufacturing process within JSFLD problems.
Journal: International Journal of Production Research
Pages: 3370-3389
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.986294
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986294
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:11:p:3370-3389




Template-Type: ReDIF-Article 1.0
Author-Name: R. Kia
Author-X-Name-First: R.
Author-X-Name-Last: Kia
Author-Name: H. Shirazi
Author-X-Name-First: H.
Author-X-Name-Last: Shirazi
Author-Name: N. Javadian
Author-X-Name-First: N.
Author-X-Name-Last: Javadian
Author-Name: R. Tavakkoli-Moghaddam
Author-X-Name-First: R.
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: Designing group layout of unequal-area facilities in a dynamic cellular manufacturing system with variability in number and shape of cells
Abstract: 
 This paper presents a new mixed-integer non-linear programming model for designing the group layout (GL) of unequal-area facilities in a cellular manufacturing system (CMS) under a dynamic environment. There are some features that make the presented model different from the previous studies. These include: (1) manufacturing cells with variable numbers and shapes, (2) machine depot keeping idle machines, (3) machines of unequal-areas, (4) manufacturing cells with rectangle regular shapes established on the continuous shop floor and (5) integration of cell formation and GL as interrelated decisions involved in the design of a CMS in a dynamic environment. The objective function is to minimises the total costs of intra- and inter-cell material handling, machine overhead, machine relocation, machine processing, purchasing machines and forming cells. Since the problem is NP-hard, an efficient simulated annealing (SA) algorithm is developed to solve the presented model. The performance of this model is illustrated by two numerical examples. It is then tested using several test problems with different sizes and settings to verify the computational efficiency of the developed algorithm in comparison to the classical genetic algorithm (GA). The obtained results show that the quality of the solutions obtained by SA is better than GA.
Journal: International Journal of Production Research
Pages: 3390-3418
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.986295
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986295
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Template-Type: ReDIF-Article 1.0
Author-Name: Pâmela M.C. Cortez
Author-X-Name-First: Pâmela M.C.
Author-X-Name-Last: Cortez
Author-Name: Alysson M. Costa
Author-X-Name-First: Alysson M.
Author-X-Name-Last: Costa
Title: Sequencing mixed-model assembly lines operating with a heterogeneous workforce
Abstract: 
 We study the problem of sequencing mixed-model assembly lines operating with a heterogeneous workforce. The practical motivation for this study comes from the context of managing assembly lines in sheltered work centres for the disabled. We propose a general framework in which task execution times are both worker and model dependent. Within this framework, the problem is defined and mathematical mixed-integer models and heuristic procedures are proposed. These include a set of fast constructive heuristics, two local search procedures based on approximate measures using either a solution upper bound or the solution of a linear program and a GRASP metaheuristic. Computational tests with instances adapted from commonly used literature databases are used to validate the proposed approaches. These tests give insight on the quality of the different techniques, which prove to be very efficient both in terms of computational effort and solution quality when compared to other strategies such as a random sampling or the solution of the MIP models using a commercial solver.
Journal: International Journal of Production Research
Pages: 3419-3432
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.987881
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Template-Type: ReDIF-Article 1.0
Author-Name: Christian Franz
Author-X-Name-First: Christian
Author-X-Name-Last: Franz
Author-Name: Achim Koberstein
Author-X-Name-First: Achim
Author-X-Name-Last: Koberstein
Author-Name: Leena Suhl
Author-X-Name-First: Leena
Author-X-Name-Last: Suhl
Title: Dynamic resequencing at mixed-model assembly lines
Abstract: 
 In this paper, we investigate a dynamic resequencing problem covering realistic properties of a mixed-model assembly line. To this end, we present a mathematical model that addresses dynamically supplied blocking information and viable due dates. We developed two different strategies that use a static resequencing algorithm as a subroutine. One strategy integrates each unblocked order immediately into the planned sequence, whereas the other strategy waits for good positions that do not conflict with the due dates. All algorithms construct guaranteed feasible sequences. Using industrial test data, we show that both strategies perform significantly better than a simple method derived from practice. A replanning procedure that tries to improve the current planned sequence whenever computing time suffices yields an additional improvement for both strategies.
Journal: International Journal of Production Research
Pages: 3433-3447
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.993046
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Template-Type: ReDIF-Article 1.0
Author-Name: Mustapha Sali
Author-X-Name-First: Mustapha
Author-X-Name-Last: Sali
Author-Name: Vincent Giard
Author-X-Name-First: Vincent
Author-X-Name-Last: Giard
Title: Optimal stock-out risk when demand is driven by several mixed-model assembly lines in the presence of emergency supply
Abstract: 
 This article focuses on the calculation of the optimal stock-out risk when resorting to emergency supplies is allowed. The studied context is a supply chain where several distant mixed-model assembly lines trigger the demand of a component used for assembly. When the cumulated lead time of a component exceeds the frozen horizon of the material requirement planning (MRP) of at least one of the assembly lines, its demand becomes stochastic. This leads to a mix between production to stock and production to order for the component of interest. The periodic replenishment policy is designed to address demand uncertainty in consistence with MRP information. To prevent stock-out propagation along the supply chain, the emergency supply is used as a last resort. The calculation of the optimal order-up-to-level and its associated optimal stock-out risk are based on a single-period trade-off between holding cost and emergency supply cost (transportation and production).
Journal: International Journal of Production Research
Pages: 3448-3461
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.997398
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Template-Type: ReDIF-Article 1.0
Author-Name: Hossein Neghabi
Author-X-Name-First: Hossein
Author-X-Name-Last: Neghabi
Author-Name: Farhad Ghassemi Tari
Author-X-Name-First: Farhad
Author-X-Name-Last: Ghassemi Tari
Title: An optimal approach for maximizing the number of adjacencies in multi floor layout problem
Abstract: 
 Multi-floor facility layout problem concerns the arrangement of departments on the different floors. In this paper, a new mathematical model is proposed for multi-floor layout with unequal department area. Maximising the number of useful adjacencies among departments is considered as the objective function. The adjacencies are divided into two major categories: horizontal and vertical adjacencies. The horizontal adjacency may be occurred between the departments assigned to same floors while the vertical can be happened between departments assigned to any consecutive floors. A minimum common boundary length (surface area) between any two horizontal (vertical) adjacent departments is specified. The efficiency of the model is demonstrated by six illustrative examples. The proposed model is practical in multi-floor plant where the existence of adjacencies between departments is useful or essential due to possible establishment of conveyor, transferring pipes, lift truck route, etc.
Journal: International Journal of Production Research
Pages: 3462-3474
Issue: 11
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.999957
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Template-Type: ReDIF-Article 1.0
Author-Name: Monideepa Tarafdar
Author-X-Name-First: Monideepa
Author-X-Name-Last: Tarafdar
Author-Name: Sufian Qrunfleh
Author-X-Name-First: Sufian
Author-X-Name-Last: Qrunfleh
Title: Agile supply chain strategy and supply chain performance: complementary roles of supply chain practices and information systems capability for agility
Abstract: 
 The paper examines the mediating effect of supply chain (SC) practices on the relationship between agile supply chain (ASC) strategy and SC performance. It further examines the moderating effect of information systems (IS) capability for agility on this mediated relationship. Using the theoretical lenses of complementarity and the information processing view of the supply chain, we hypothesise that strategic supplier partnership, customer relationship, postponement and lean practices, mediate the relationship between ASC strategy and SC performance. We further hypothesise that IS capability for agility moderates each of these mediated relationships. We empirically test the hypotheses using survey data from members of senior and executive management in the logistics/supply chain functions of 205 firms. The paper contributes to the literature on ASCs by theoretically explaining and empirically demonstrating how SC practices and IS capability for agility act together to effect a positive relationship between ASC strategy and supply chain performance.
Journal: International Journal of Production Research
Pages: 925-938
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1203079
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Template-Type: ReDIF-Article 1.0
Author-Name: K. P. Abdul Nazar
Author-X-Name-First: K. P.
Author-X-Name-Last: Abdul Nazar
Author-Name: V. Madhusudanan Pillai
Author-X-Name-First: V. Madhusudanan
Author-X-Name-Last: Pillai
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 1226-1226
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1206671
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Template-Type: ReDIF-Article 1.0
Author-Name: Robert O. Neidigh
Author-X-Name-First: Robert O.
Author-X-Name-Last: Neidigh
Author-Name: Terry P. Harrison
Author-X-Name-First: Terry P.
Author-X-Name-Last: Harrison
Title: Optimising lot sizing with nonlinear production rates in a multi-product multi-machine environment
Abstract: 
 In a variety of discrete manufacturing environments, it is common to experience a nonlinear production rate. In particular, our interest is in the case of an increasing production rate, where learning creates efficiencies. This leads to greater output per unit time as the process continues. However, the advantages of an increasing production rate may be offset by other factors. For examples, JIT policies typically lead to smaller lot sizes, where the value of an increasing production rate is largely lost. We develop a general model that balances the impact of various competing effects. Our research focuses on determining lot sizes that satisfy demand requirements while minimising production and holding costs. We extend our prior work by developing a multi-product, multi-machine method for modelling and solving this class of production problems. The solution method is demonstrated using the production function from the PR#2 grinding process for a production plant in Carlisle, PA. The solution heuristic provides solution times that are on average only 0.22 to 0.55% above optimum as the solution parameters are varied and the ratio of heuristic solution times to optimal solution times varies from 18.16 to 14.15%.
Journal: International Journal of Production Research
Pages: 939-959
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1207820
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Template-Type: ReDIF-Article 1.0
Author-Name: Martin Epp
Author-X-Name-First: Martin
Author-X-Name-Last: Epp
Author-Name: Simon Wiedemann
Author-X-Name-First: Simon
Author-X-Name-Last: Wiedemann
Author-Name: Kai Furmans
Author-X-Name-First: Kai
Author-X-Name-Last: Furmans
Title: A discrete-time queueing network approach to performance evaluation of autonomous vehicle storage and retrieval systems
Abstract: 
 In this paper, we present a method for performance evaluation of autonomous vehicle storage and retrieval systems (AVS/RSs) with tier-captive single-aisle vehicles. A discrete-time open queueing network approach is applied. The data obtained from the evaluation of the lift and vehicle movements can be used directly as input for the general discrete service time distributions of the queueing network. Furthermore, the approach allows for the computation of the retrieval transaction time distribution as well as of the distribution of the number of transactions waiting to be stored. Consequently, not only expected values and variances but also quantiles of the performance measures can be obtained. Comparison to discrete-event simulation quantifies approximation errors resulting from the decomposition approach in the discrete-time domain. Moreover, the errors obtained by the discrete-time approach are compared to the errors obtained using a continuous-time open queueing network approach. Finally, it will be outlined how the model can be used for designing AVS/RSs according to given system requirements, such as storage capacity, throughput, height and length of the system as well as the 95% quantile of the retrieval transaction time.
Journal: International Journal of Production Research
Pages: 960-978
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1208371
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1208371
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Template-Type: ReDIF-Article 1.0
Author-Name: Wapee Manopiniwes
Author-X-Name-First: Wapee
Author-X-Name-Last: Manopiniwes
Author-Name: Takashi Irohara
Author-X-Name-First: Takashi
Author-X-Name-Last: Irohara
Title: Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response
Abstract: 
 This paper proposes a stochastic linear mixed-integer programming model for integrated decisions in the preparedness and response stages in pre- and post-disaster operations, respectively. We develop a model for integrated decisions that considers three key areas of emergency logistics: facility and stock prepositioning, evacuation planning and relief vehicle planning. To develop a framework for effective relief operations, we consider not only a cost-based but also an equity-based solution approach in our multiple objectives model. Then a normalised weighted sum method is used to parameterise our multiple objective programming model. This paper suggests a compromise between the cost, and the equity of relief victims. The experiments also demonstrate how time restrictions and the availability of relief vehicles impact the two objective functions.
Journal: International Journal of Production Research
Pages: 979-996
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1211340
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1211340
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Template-Type: ReDIF-Article 1.0
Author-Name: Aidin Delgoshaei
Author-X-Name-First: Aidin
Author-X-Name-Last: Delgoshaei
Author-Name: Mohd Khairol Anuar Ariffin
Author-X-Name-First: Mohd Khairol Anuar
Author-X-Name-Last: Ariffin
Author-Name: Ahad Ali
Author-X-Name-First: Ahad
Author-X-Name-Last: Ali
Title: A multi-period scheduling method for trading-off between skilled-workers allocation and outsource service usage in dynamic CMS
Abstract: 
 In this paper, a new method is proposed for short-term period scheduling of dynamic cellular manufacturing systems in a dual resource constrained environment. The aim of this method is to find best production strategy of in-house manufacturing using worker assignment (both temporary and skilled workers) and outsourcing, while part demands are uncertain and can be varied periodically. For this purpose, a multi-period scheduling model has been proposed which is flexible enough to use in real industries. To solve the proposed problem, a number of metaheuristics are developed including Branch and Bound; a hybrid Tabu Search and Simulated Annealing algorithms and a hybrid Ant Colony Optimization and Simulated Annealing algorithms. A Taguchi method (L27 orthogonal optimisation) is used to estimate parameters of the proposed method in order to solve experiments derived from the literature. For evaluating the system imbalance in dynamic market demands, a new measuring index is developed. Our findings indicate that the uncertain market demands affects the part allocating which may induce workstation-load variations that yield to cell-load variation accordingly. To solve this problem, two methods are offered. The results show that promoting staff and using freezing technique are promising ways to reduce system imbalance while confronting with the mentioned condition. The outcomes also show the superiority of the proposed hybrid method in providing solutions with better quality.
Journal: International Journal of Production Research
Pages: 997-1039
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1213445
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213445
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Template-Type: ReDIF-Article 1.0
Author-Name: Seyed Mohammad Khalili
Author-X-Name-First: Seyed Mohammad
Author-X-Name-Last: Khalili
Author-Name: Fariborz Jolai
Author-X-Name-First: Fariborz
Author-X-Name-Last: Jolai
Author-Name: Seyed Ali Torabi
Author-X-Name-First: Seyed Ali
Author-X-Name-Last: Torabi
Title: Integrated production–distribution planning in two-echelon systems: a resilience view
Abstract: 
 Global supply chains are increasingly exposed to operational and disruption risks that threaten their business continuity. This paper presents a novel two-stage scenario-based mixed stochastic-possibilistic programming model for integrated production and distribution planning problem in a two-echelon supply chain over a midterm horizon under risk. Operational risks are handled by introducing imprecise (i.e. possibilistic) parameters while disruption risks are accounted for through stochastic disruption scenarios. The proposed model accounts for the risk mitigation options and recovery of lost capacities in an integrated manner. In the first stage, the structure of the chain and proactive risk mitigation decisions are determined, while the second stage specifies the recovery plan of lost capacities in addition to production and distribution plans. Considering extra capacities in the production facilities, backup routes for transportation links and pre-positioning of emergency inventory in distribution centres are considered as feasible options to improve the resilience level of the supply chain. We propose a new indicator for optimising the resilience level of the chain based on restoration of lost capacities. For the sake of robustness, the expected worst case of the second stage’s objective function is considered by utilising the conditional value at risk (CVaR) measure. The validation and applicability of the proposed model are examined through several numerical experiments.
Journal: International Journal of Production Research
Pages: 1040-1064
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1213446
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213446
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Template-Type: ReDIF-Article 1.0
Author-Name: He-Yau Kang
Author-X-Name-First: He-Yau
Author-X-Name-Last: Kang
Author-Name: Amy H.I. Lee
Author-X-Name-First: Amy H.I.
Author-X-Name-Last: Lee
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Author-Name: Cheng-Han Lee
Author-X-Name-First: Cheng-Han
Author-X-Name-Last: Lee
Title: An efficient method for dynamic-demand joint replenishment problem with multiple suppliers and multiple vehicles
Abstract: 
 How to improve competitive edges to meet rapidly changing market environment and dynamic customer needs is critical for the survival and success of firms these days. A good supply chain and inventory management is a necessity in the intensive competitive market. This paper considers a dynamic-demand joint replenishment problem with multiple vehicle routing. The problem is first formulated as a mixed integer programming model with an objective to minimise total costs, which include ordering cost, purchase cost, production cost, transportation cost and holding cost, under a prerequisite that inventory shortage is prohibited in the system. A particle swarm optimisation model is proposed next to solve large-scale problems which are computationally difficult. A case study of a touch panel manufacturer is presented to examine the practicality of the models.
Journal: International Journal of Production Research
Pages: 1065-1084
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1218564
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1218564
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Template-Type: ReDIF-Article 1.0
Author-Name: Layth C. Alwan
Author-X-Name-First: Layth C.
Author-X-Name-Last: Alwan
Author-Name: Christian H. Weiß
Author-X-Name-First: Christian H.
Author-X-Name-Last: Weiß
Title: INAR implementation of newsvendor model for serially dependent demand counts
Abstract: 
 The classic newsvendor model was developed under the assumption that period-to-period demand is independent over time. In real-life applications, the notion of independent demand is often challenged. In this paper, we propose a dynamic implementation of the newsvendor model based on a class of integer-valued autoregressive (INAR) models when facing correlated discrete demand. Motivated by application, we consider INAR models with underlying Poisson error innovations and with underlying negative-binomial error innovations to accommodate overdispersion scenarios. We numerically compare our proposal with the standard newsvendor solution and with a standard autoregressive-based newsvendor solution. Our results show that an appropriately specified INAR-based newsvendor solution not only outperforms the standard case but also the approximating forecasting approaches. Moreover, even in the presence of autocorrelation, the use of the standard autoregressive model as an approximating approach can lead to increased costs over and above the standard implementation of the newsvendor model based on no forecasting.
Journal: International Journal of Production Research
Pages: 1085-1099
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1218565
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1218565
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:4:p:1085-1099




Template-Type: ReDIF-Article 1.0
Author-Name: Ehsan Khodabandeh
Author-X-Name-First: Ehsan
Author-X-Name-Last: Khodabandeh
Author-Name: Lihui Bai
Author-X-Name-First: Lihui
Author-X-Name-Last: Bai
Author-Name: Sunderesh S. Heragu
Author-X-Name-First: Sunderesh S.
Author-X-Name-Last: Heragu
Author-Name: Gerald W. Evans
Author-X-Name-First: Gerald W.
Author-X-Name-Last: Evans
Author-Name: Thomas Elrod
Author-X-Name-First: Thomas
Author-X-Name-Last: Elrod
Author-Name: Mark Shirkness
Author-X-Name-First: Mark
Author-X-Name-Last: Shirkness
Title: Modelling and solution of a large-scale vehicle routing problem at GE appliances &amp; lighting
Abstract: 
 We consider a special case of the vehicle routing problem where not only each customer has specified delivery time window, but each route has limited time duration. We propose a solution algorithm using network reduction techniques and simulated annealing meta-heuristic. The objective is twofold: minimising the travel time and minimising the total number of vehicles required. The time-window constraint ensures delivery without delay, thus, a potentially higher level of customer satisfaction. The algorithm has helped the transportation planning team at General Electric Appliances &amp; Lighting to significantly reduce the number of required trucks in two real cases, while its performance on randomly generated cases is also efficient when compared to properly selected benchmarking algorithms.
Journal: International Journal of Production Research
Pages: 1100-1116
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1220685
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1220685
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Template-Type: ReDIF-Article 1.0
Author-Name: Daniel Seifert
Author-X-Name-First: Daniel
Author-X-Name-Last: Seifert
Author-Name: Ralf W. Seifert
Author-X-Name-First: Ralf W.
Author-X-Name-Last: Seifert
Author-Name: Olov H.D. Isaksson
Author-X-Name-First: Olov H.D.
Author-X-Name-Last: Isaksson
Title: A test of inventory models with permissible delay in payment
Abstract: 
 Contrary to the long-standing view in the finance literature that firms should maximise payment delays, research in operations management suggests that long payment delays can be suboptimal. In this study, we reconcile these two views by applying a secondary data approach to established operations management theory. Based on a sample of 3383 groups of public US firms from a novel database, we find that our data are consistent with the causal relations and theoretical predictions of the operations management literature. Firm profitability is positively associated with payment delay. Payment delay, in turn, is positively associated with the capital cost difference between buyer and supplier and negatively associated with the price elasticity of demand and the deterioration rate of inventory. However, we do not observe any significant interaction effects between these factors, which raise a number of questions for future research.
Journal: International Journal of Production Research
Pages: 1117-1128
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1224947
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1224947
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Template-Type: ReDIF-Article 1.0
Author-Name: Yongjian Li
Author-X-Name-First: Yongjian
Author-X-Name-Last: Li
Author-Name: Shuiye Niu
Author-X-Name-First: Shuiye
Author-X-Name-Last: Niu
Author-Name: Xiukun Zhao
Author-X-Name-First: Xiukun
Author-X-Name-Last: Zhao
Author-Name: Wen Wang
Author-X-Name-First: Wen
Author-X-Name-Last: Wang
Title: Effect of EPR coefficient policy on the production decision in precious metal accessory recycling
Abstract: 
 This study examines the effect of the extended producer responsibility (EPR) coefficient policy on the production decision between a supplier and a manufacturer in a precious metal accessory recycling supply chain. EPR coefficient is a regulation proposed by the government and enterprises to balance economic profit and EPR behaviour, and refers to the production proportion of recycled products in all serviceable products. Enterprises with a large EPR coefficient have good EPR practice. This study uses the newsvendor model and numerical simulation to study a supply chain system with remanufacturing and reproduction processes. Results show that the optimal recycling mode and the optimal EPR coefficient are always present in precious metal accessory operations. The increasing market demand for recycled products and the improving whole recycling parameters are both effective in enlarging the optimal EPR coefficient. However, the improvement of single or partial recycling parameters (except the market demand parameter) has no effect on the optimal EPR coefficient. The implementation mechanism and applicable conditions of the EPR coefficient policy are also explored. This study indicates that the EPR coefficient policy is an appropriate and effective approach to promote the EPR practice of the Chinese Government.
Journal: International Journal of Production Research
Pages: 1129-1146
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1224948
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1224948
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Template-Type: ReDIF-Article 1.0
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: Nan Li
Author-X-Name-First: Nan
Author-X-Name-Last: Li
Author-Name: S.H. Chung
Author-X-Name-First: S.H.
Author-X-Name-Last: Chung
Author-Name: Mozafar Saadat
Author-X-Name-First: Mozafar
Author-X-Name-Last: Saadat
Title: Management of sustainable manufacturing systems-a review on mathematical problems
Abstract: 
 The ever-growing awareness of environmental protection has significantly influenced the method of manufacturing products. Due to the introduction of new processes, the management of sustainable manufacturing shows different characteristics to those of traditional systems. Sustainable manufacturing systems have attracted a great deal of attention in the past 20 years as an emerging manufacturing approach. Particularly in the last 10 years, the number of papers focusing on the topic of sustainable manufacturing systems’ management has increased rapidly. More and more practical factors have been considered and integrated into this area which makes it more complex, but closer to reality. This paper aims to classify the mathematical problems dealing with the management of sustainable manufacturing systems. More than 100 related papers mainly from 1994 to 2015 have been selected and reviewed and divided into three categories according to the main elements in a manufacturing system: production planning and control, inventory management and control and manufacturing network design. The development of each category is summarised and the corresponding mathematical problems are discussed to provide a general overview of the relevant research fields and identify future research directions.
Journal: International Journal of Production Research
Pages: 1210-1225
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1229067
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1229067
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaohua Han
Author-X-Name-First: Xiaohua
Author-X-Name-Last: Han
Author-Name: Haiyan Wu
Author-X-Name-First: Haiyan
Author-X-Name-Last: Wu
Author-Name: Qianxia Yang
Author-X-Name-First: Qianxia
Author-X-Name-Last: Yang
Author-Name: Jennifer Shang
Author-X-Name-First: Jennifer
Author-X-Name-Last: Shang
Title: Collection channel and production decisions in a closed-loop supply chain with remanufacturing cost disruption
Abstract: 
 Enterprise risk management (ERM) focuses on managing functions of an entire business, with special attention to supply chain uncertainty. Managing supply chain through effective ERM will mitigate firm exposure to risk in operations and ensure the success of the business. We study collection channel and production decisions in a closed-loop supply chain (CLSC) with one dominant manufacturer and one retailer, from the perspective of both firm profit and system robustness. A robust system is desired as only minimal changes in production plan are necessary when facing disruption, and is valuable for enterprise risk reduction. We find that without disruption the indirect (retailer) collection channel achieves higher profit than that of the direct (manufacturer) channel, which is also true under some disruption cases. However, the direct channel is more robust when facing disruption, and generates more profits for manufacturers when the positive disruption is large. We also find that the revenue-sharing contracts are effective in coordinating members of the CLSC. Finally, we conduct numerical studies to validate the models and derive managerial insights.
Journal: International Journal of Production Research
Pages: 1147-1167
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1230684
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1230684
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Template-Type: ReDIF-Article 1.0
Author-Name: Guodong Yu
Author-X-Name-First: Guodong
Author-X-Name-Last: Yu
Author-Name: Fei Li
Author-X-Name-First: Fei
Author-X-Name-Last: Li
Author-Name: Yu Yang
Author-X-Name-First: Yu
Author-X-Name-Last: Yang
Title: Robust supply chain networks design and ambiguous risk preferences
Abstract: 
 In this paper, a robust stochastic optimisation model for regret minimising is proposed for supply chain networks design. The model emphasises the ambiguity lying in both the risk preference and the probability distribution. A duality theory for the model is derived and the random utility functions are identified as the Lagrange multipliers. In addition, a tractable relaxation based on reformulation-linearisation technique is presented for the computational aspects of the model. The numerical experiments show that our regret minimising model can make a well balance between the conservativeness of a pure robust optimisation model and the optimism of risk-neutrality. We also present a case study to demonstrate the applicability of the proposed model.
Journal: International Journal of Production Research
Pages: 1168-1182
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1232499
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1232499
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:4:p:1168-1182




Template-Type: ReDIF-Article 1.0
Author-Name: Ruggero Golini
Author-X-Name-First: Ruggero
Author-X-Name-Last: Golini
Author-Name: Antonella Moretto
Author-X-Name-First: Antonella
Author-X-Name-Last: Moretto
Author-Name: Federico Caniato
Author-X-Name-First: Federico
Author-X-Name-Last: Caniato
Author-Name: Maria Caridi
Author-X-Name-First: Maria
Author-X-Name-Last: Caridi
Author-Name: Matteo Kalchschmidt
Author-X-Name-First: Matteo
Author-X-Name-Last: Kalchschmidt
Title: Developing sustainability in the Italian meat supply chain: an empirical investigation
Abstract: 
 Although sustainable supply chain (SC) management has been widely investigated in recent years, the focus has mainly been on the practices adopted by a single company, so missing the big picture at SC level. This study of the Italian meat industry considers the SC as a whole, identifying the critical points for each stage in terms of economic, environmental and social sustainability. To this end, a first set of case studies was conducted of companies at different stages of the SC before turning to focus on the meat processing stage, which was identified as critical and highly relevant. A second set of case studies analysed how these companies leverage SC management practices to develop sustainable SCs. In so doing, specific attention was paid to drivers and contingent variables that foster the adoption of sustainable practices. The results of the two steps were then merged to illuminate how practices adopted by the meat processors can impact on the whole chain, confirming their pivotal role in driving sustainability. These results provide a holistic view of the phenomenon, encompassing the entire chain from end to end and highlighting the interdependences across various stages of the meat SC.
Journal: International Journal of Production Research
Pages: 1183-1209
Issue: 4
Volume: 55
Year: 2017
Month: 2
X-DOI: 10.1080/00207543.2016.1234724
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1234724
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Template-Type: ReDIF-Article 1.0
Author-Name: Ludwig Dumetz
Author-X-Name-First: Ludwig
Author-X-Name-Last: Dumetz
Author-Name: Jonathan Gaudreault
Author-X-Name-First: Jonathan
Author-X-Name-Last: Gaudreault
Author-Name: André Thomas
Author-X-Name-First: André
Author-X-Name-Last: Thomas
Author-Name: Nadia Lehoux
Author-X-Name-First: Nadia
Author-X-Name-Last: Lehoux
Author-Name: Philippe Marier
Author-X-Name-First: Philippe
Author-X-Name-Last: Marier
Author-Name: Hind El-Haouzi
Author-X-Name-First: Hind
Author-X-Name-Last: El-Haouzi
Title: Evaluating order acceptance policies for divergent production systems with co-production
Abstract: 
 The impacts of using different order acceptance policies in manufacturing sectors are usually well known and documented in the literature. However, for industries facing divergent processes with co-production (i.e. several products produced at the same time from a common raw material), the evaluation, comparison and selection of policies are not trivial tasks. This paper proposes a framework to enable this evaluation. Using a simulation model that integrates a custom-built ERP, we compare and evaluate different order acceptance policies in various market conditions. Experiments are carried out using a case from the forest products industry. Results illustrate how and when different market conditions related to divergent/co-production industries may call for available-to-promise (ATP), capable-to-promise (CTP), and other known strategies. Especially, we show that advanced order acceptance policies like CTP may generate a better income for certain types of market and, conversely to typical manufacturing industries, ATP performs better than other strategies for a specific demand patterns.
Journal: International Journal of Production Research
Pages: 3631-3643
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1193250
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193250
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Neubauer
Author-X-Name-First: Matthias
Author-X-Name-Last: Neubauer
Author-Name: Florian Krenn
Author-X-Name-First: Florian
Author-X-Name-Last: Krenn
Author-Name: Dennis Majoe
Author-X-Name-First: Dennis
Author-X-Name-Last: Majoe
Author-Name: Christian Stary
Author-X-Name-First: Christian
Author-X-Name-Last: Stary
Title: Subject-orientation as design language for integration across organisational control layers
Abstract: 
 Recent research and development in production industry reveals a movement to cyber-physical production systems and Internet of things enabled manufacturing. In this context, ways in which enterprise processes are conceptualised and executed are changing. Decentralising production by applying interlinked cyber-physical production resources breaks up the traditional boundaries between different process abstraction layers. Heterogeneous smart devices and processes at all levels in the industrial control need to interact in such systems. In this paper, requirements from the field of Business Process Management towards the vertical integration of business and production processes are derived. With respect to the identified requirements the eligibility of the Subject-oriented Process Management (S-BPM) approach for vertical process integration is depicted. At the core, the paper investigates the applicability of S-BPM to achieve vertical process integration and reports lessons learnt from two industrial application scenarios. The first scenario aims to encode human properties to adapt workplaces to human needs. The second scenario aims towards supporting the execution and tracking of dynamic production processes.
Journal: International Journal of Production Research
Pages: 3644-3656
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1198058
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1198058
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Template-Type: ReDIF-Article 1.0
Author-Name: Dávid Gyulai
Author-X-Name-First: Dávid
Author-X-Name-Last: Gyulai
Author-Name: András Pfeiffer
Author-X-Name-First: András
Author-X-Name-Last: Pfeiffer
Author-Name: László Monostori
Author-X-Name-First: László
Author-X-Name-Last: Monostori
Title: Robust production planning and control for multi-stage systems with flexible final assembly lines
Abstract: 
 Production planning of final assembly systems is a challenging task, as the often fluctuating order volumes require flexible solutions. Besides, the calculated plans need to be robust against the process-level disturbances and stochastic nature of some parameters like manual processing times or machine availability. In the paper, a simulation-based optimisation method is proposed that utilises lower level shop floor data to calculate robust production plans for final assembly lines of a flexible, multi-stage production system. In order to minimise the idle times when executing the plans, the capacity control that specifies the proper operator–task assignments is also determined. The analysed multi-stage system is operated with a pull strategy, which means that the production at the final assembly lines generates demands for the preceding stages providing the assembled components. In order to guarantee the feasibility of the plans calculated for the final assembly lines, a decomposition approach is proposed to optimise the production plan of preceding stages. By this way, the robust production can be ensured resulting in reduced losses and overall production costs even though the system is exposed to changes and disturbances.
Journal: International Journal of Production Research
Pages: 3657-3673
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1198506
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1198506
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Template-Type: ReDIF-Article 1.0
Author-Name: Daniele Scrimieri
Author-X-Name-First: Daniele
Author-X-Name-Last: Scrimieri
Author-Name: Nikolas Antzoulatos
Author-X-Name-First: Nikolas
Author-X-Name-Last: Antzoulatos
Author-Name: Elkin Castro
Author-X-Name-First: Elkin
Author-X-Name-Last: Castro
Author-Name: Svetan M. Ratchev
Author-X-Name-First: Svetan M.
Author-X-Name-Last: Ratchev
Title: Automated experience-based learning for plug and produce assembly systems
Abstract: 
 This paper presents a self-learning technique for adapting modular automated assembly systems. The technique consists of automatically analysing sensor data and acquiring experience on the changes made on an assembly system to cope with new production requirements or to recover from disruptions. Experience is generalised into operational knowledge that is used to aid engineers in future adaptations by guiding them throughout the process. At each step, applicable changes are presented and ranked based on: (1) similarity between the current context and those in the experience base; (2) estimate of the impact on system performance. The experience model and the self-learning technique reflect the modular structure of the assembly machine and are particularly suitable for plug and produce systems, which are designed to offer high levels of self-organisation and adaptability. Adaptations can be performed and evaluated at different levels: from the smallest pluggable unit to the whole assembly system. Knowledge on individual modules can be reused when modules are plugged into other systems. An experimental evaluation has been conducted on an industrial case study and the results show that, with experience-based learning, adaptations of plug and produce systems can be performed in a shorter time.
Journal: International Journal of Production Research
Pages: 3674-3685
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1207817
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1207817
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhe Yuan
Author-X-Name-First: Zhe
Author-X-Name-Last: Yuan
Author-Name: Haoxuan Xu
Author-X-Name-First: Haoxuan
Author-X-Name-Last: Xu
Author-Name: Yeming (Yale) Gong
Author-X-Name-First: Yeming (Yale)
Author-X-Name-Last: Gong
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Author-Name: Jinlong Zhang
Author-X-Name-First: Jinlong
Author-X-Name-Last: Zhang
Title: Designing public storage warehouses with high demand for revenue maximisation
Abstract: 
 The design of public storage warehouses needs to fit market segments to increase the average revenue in an environment of high demand. This paper presents a revenue model integrated with queuing and price-demand theories to solve the design and pricing problem for public storage warehouses. We consider two demand cases in the model, which are exponential demand and piecewise linear demand. We also develop a solution based on dynamic programming techniques to solve the problem. Using data from a warehouse, we conduct numerical experiments. Results show that our approach can improve the expected revenue of public storage warehouses with high demand by 16.6% on average. We further conduct sensitivity analysis on price, and investigate the relation between revenue and price.
Journal: International Journal of Production Research
Pages: 3686-3700
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1211338
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1211338
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Template-Type: ReDIF-Article 1.0
Author-Name: Stefan Feldmann
Author-X-Name-First: Stefan
Author-X-Name-Last: Feldmann
Author-Name: Birgit Vogel-Heuser
Author-X-Name-First: Birgit
Author-X-Name-Last: Vogel-Heuser
Title: Interdisciplinary product lines to support the engineering in the machine manufacturing domain
Abstract: 
 Current market dynamics force today’s companies to manufacture smaller lot sizes up to individual products. As a consequence, companies need to react to such changes; it is hence inevitable to ensure a correct, reliable and flexible engineering process, which allows for managing the highly variant-rich machines. This article investigates the applicability of interdisciplinary product lines for the engineering in the machine manufacturing domain. Therein, four core aspects are addressed: first, the current practice of companies regarding the management of variants is analysed. Second, the requirements to be fulfilled by an interdisciplinary variant management approach are analysed. Third, an interdisciplinary product line approach is presented that aims at overcoming the challenges. Fourth, the benefits and limitations of the approach are discussed and research gaps that need to be addressed in future works are identified.
Journal: International Journal of Production Research
Pages: 3701-3714
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1211343
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1211343
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Template-Type: ReDIF-Article 1.0
Author-Name: Huan Liu
Author-X-Name-First: Huan
Author-X-Name-Last: Liu
Author-Name: Qiang Liu
Author-X-Name-First: Qiang
Author-X-Name-Last: Liu
Author-Name: Pengpeng Sun
Author-X-Name-First: Pengpeng
Author-X-Name-Last: Sun
Author-Name: Qitong Liu
Author-X-Name-First: Qitong
Author-X-Name-Last: Liu
Author-Name: Songmei Yuan
Author-X-Name-First: Songmei
Author-X-Name-Last: Yuan
Title: The optimal feedrate planning on five-axis parametric tool path with geometric and kinematic constraints for CNC machine tools
Abstract: 
 The optimal feedrate planning on five-axis parametric tool path with multi-constraints remains challenging due to the variable curvature of tool path curves and the nonlinear relationships between the Cartesian space and joint space. The methods for solving this problem are very limited at present. The optimal feedrate associated with a programmed tool path is crucial for high speed and high accuracy machining. This paper presents a novel feedrate optimisation method for feedrate planning on five-axis parametric tool paths with preset multi-constraints including chord error constraint, tangential kinematic constraints and axis kinematic constraints. The proposed method first derives a linear objective function for feedrate optimisation by using a discrete format of primitive continuous objective function. Then, the preset multi-constraints are converted to nonlinear constraint conditions on the decision variables in the linear objective function and are then linearised with an approximation strategy. A linear model for feedrate optimisation with preset multiple constraints is then constructed, which can be solved by well-developed linear programming algorithms. Finally, the optimal feedrate can be obtained from the optimal solution and fitted to the smooth spline curve as the ultimate feedrate profile. Experiments are conducted on two parametric tool paths to verify the feasibility and applicability of the proposed method that show both the planning results and computing efficiency are satisfactory when the number of sampling positions is appropriately determined.
Journal: International Journal of Production Research
Pages: 3715-3731
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1254357
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1254357
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexander Sunk
Author-X-Name-First: Alexander
Author-X-Name-Last: Sunk
Author-Name: Peter Kuhlang
Author-X-Name-First: Peter
Author-X-Name-Last: Kuhlang
Author-Name: Thomas Edtmayr
Author-X-Name-First: Thomas
Author-X-Name-Last: Edtmayr
Author-Name: Wilfried Sihn
Author-X-Name-First: Wilfried
Author-X-Name-Last: Sihn
Title: Developments of traditional value stream mapping to enhance personal and organisational system and methods competencies
Abstract: 
 This paper presents developments of traditional value stream mapping (VSM) related to enhancing system and method competencies of both individuals and organisations. Since systematic immersions in traditional VSM – a highly accepted technique for improving production systems – are necessary, this paper describes from a production research point of view approaches for systematic productivity increases, reduction of lead time and an approach to improve sustainability indicators of value streams. The introduced developments of VSM focus on the entire flow and on details, thus creating synergies for designing and improving value streams, processes and work systems both economically and ecologically. On the one hand, this paper shows how practical approaches respectively rationalisation concepts (Lean principles, VSM, Process Management, short-cyclic improvement routine, Methods-Time Measurement) are used in industry in order to manage and improve processes and value streams. On the other hand, sustainability management can be supported on shop floor with utilisation of VSM. It aims to extend the view on value streams of both researchers and practitioners in sense of system and methods competencies.
Journal: International Journal of Production Research
Pages: 3732-3746
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1272764
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1272764
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Template-Type: ReDIF-Article 1.0
Author-Name: Akash Gupta
Author-X-Name-First: Akash
Author-X-Name-Last: Gupta
Author-Name: Debjit Roy
Author-X-Name-First: Debjit
Author-X-Name-Last: Roy
Author-Name: René de Koster
Author-X-Name-First: René
Author-X-Name-Last: de Koster
Author-Name: Sampanna Parhi
Author-X-Name-First: Sampanna
Author-X-Name-Last: Parhi
Title: Optimal stack layout in a sea container terminal with automated lifting vehicles
Abstract: 
 Container terminal performance is largely determined by its design decisions, which include the number and type of quay cranes, stack cranes, transport vehicles, vehicle travel path and stack layout. We investigate the orientation of the stack layout (parallel or perpendicular to the quayside) on the throughput time performance of the terminals. Previous studies in this area typically use deterministic optimisation, and a few studies use probabilistic travel times and simulation to analyse the effect of stack layout on terminal throughput times. In this research, we capture the stochasticity with an integrated queuing network modelling approach to analyse the performance of container terminals with parallel stack layout using automated lifting vehicles. Using this analytical model, we investigate 1008 parallel stack layout configurations on throughput times and determine the optimal stack layout configuration. We find that, assuming an identical width of the internal transport area, container terminals with parallel stack layout perform better (from 4–12% in terms of container throughput times) than terminals with a perpendicular stack layout.
Journal: International Journal of Production Research
Pages: 3747-3765
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2016.1273561
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1273561
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Template-Type: ReDIF-Article 1.0
Author-Name: Vladimir Polotski
Author-X-Name-First: Vladimir
Author-X-Name-Last: Polotski
Author-Name: Jean-Pierre Kenne
Author-X-Name-First: Jean-Pierre
Author-X-Name-Last: Kenne
Author-Name: Ali Gharbi
Author-X-Name-First: Ali
Author-X-Name-Last: Gharbi
Title: Set-up and production planning in hybrid manufacturing–remanufacturing systems with large returns
Abstract: 
 Hybrid systems that use both raw materials and returned products in the production process are considered. The system contains one facility, and undergoes set-ups each time it switches between two production modes. In particular, we address systems engaged mainly in remanufacturing and having a large percentage of return. This situation is encountered in companies with mature remanufacturing channels. The targeted application area is comprised of hybrid systems that uses leasing as a business model with manufacturing serving to attenuate return uncertainty. To evaluate the system performance, we take into account manufacturing and remanufacturing costs, holding costs in serviceable and return inventories, backlog and set-up costs. Our analysis of hybrid systems with high return levels reveals features that are peculiar to such systems and that differentiate them from systems with lower return rates. We first present analytical solutions for optimal production and set-up schedule, and determine the possible cycle shapes for reliable systems. Optimal policies contain intervals of manufacturing and remanufacturing at maximal rate, and intervals of on-demand and on-return remanufacturing. Failure-prone systems are studied next, using the formalism of stochastic dynamic programming. Optimal policies give rise to the trajectories converging to the patterns similar to the analytically calculated cycles.
Journal: International Journal of Production Research
Pages: 3766-3787
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2017.1293863
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1293863
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Template-Type: ReDIF-Article 1.0
Author-Name: Roberto Luiz Tomelero
Author-X-Name-First: Roberto Luiz
Author-X-Name-Last: Tomelero
Author-Name: João Carlos Espíndola Ferreira
Author-X-Name-First: João Carlos Espíndola
Author-X-Name-Last: Ferreira
Author-Name: Vikas Kumar
Author-X-Name-First: Vikas
Author-X-Name-Last: Kumar
Author-Name: Jose Arturo Garza-Reyes
Author-X-Name-First: Jose Arturo
Author-X-Name-Last: Garza-Reyes
Title: A lean environmental benchmarking (LEB) method for the management of cutting tools
Abstract: 
 Manufacturing companies are striving hard to remain competitive hence, they rely on a number of resources to meet customers’ expectations, among which cutting tools are included. This paper addresses the problems faced in the management of cutting tools activities. Production managers have highlighted the lack of procedures containing metrics and targets that would show them whether their company is able to perform an efficient management, and if it is capable of supporting the deployment process. In this context, this paper presents a novel lean environmental benchmarking (LEB) method for performing a diagnosis of practices and performances to support the implementation of a cutting tool management strategy and/or the effective management of these assets. Strategic, technical and logistical aspects are addressed, particularly, with regard to management focused on lean manufacturing and environmental aspects. Field studies were performed in nine Brazilian companies in the metal-mechanical sector to validate the LEB method proposed. The LEB method helped the participant organisations to clarify the various activities that involved the management of their cutting tools, while the field studies indicated that all nine organisations had a great concern regarding the preservations of the environment, and also an effective utilisation of resources spent for machining components.
Journal: International Journal of Production Research
Pages: 3788-3807
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2017.1293864
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1293864
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Template-Type: ReDIF-Article 1.0
Author-Name: Chenlu Miao
Author-X-Name-First: Chenlu
Author-X-Name-Last: Miao
Author-Name: Gang Du
Author-X-Name-First: Gang
Author-X-Name-Last: Du
Author-Name: Roger J. Jiao
Author-X-Name-First: Roger J.
Author-X-Name-Last: Jiao
Author-Name: Tiebin Zhang
Author-X-Name-First: Tiebin
Author-X-Name-Last: Zhang
Title: Coordinated optimisation of platform-driven product line planning by bilevel programming
Abstract: 
 Product line planning (PLP) aims at an optimal combination of product feature offerings, suggesting itself to be a determinant decision for a company to satisfy diverse customer needs and gain competitive advantages. Fulfilment of planned product lines must make trade-offs between product variety and production costs. To balance the costs of product lines, manufacturers often adopt a product platform configuration (PPC) approach to redesign product and process platforms by adding new modules to the legacy platforms. The PPC is an effective means of providing product variety while controlling the manufacturing costs. The PLP and PPC problems have traditionally been investigated separately in the marketing research and engineering design fields. It is important to coordinate PLP and PPC decisions within a coherent optimisation framework. This paper proposes a bilevel mixed 0–1 nonlinear programming model to formulate coordinated optimisation for platform-driven product line planning. The upper level deals with the PLP problem by maximising the profit of an entire product line, whilst the lower level copes with the multiple product platforms optimisation for the optimal PPC in accordance with the upper level decisions of product line structure. To solve this bilevel programming model, a bilevel genetic algorithm is developed to find the optimal solution. A case study of coordinated optimisation between an automobile line and its product platforms is presented to demonstrate the feasibility and effectiveness of the proposed bilevel programming in comparison with a typical ‘all-in-one’ approach and a non-joint optimisation programming.
Journal: International Journal of Production Research
Pages: 3808-3831
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2017.1294770
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1294770
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Template-Type: ReDIF-Article 1.0
Author-Name: Joachim Lentes
Author-X-Name-First: Joachim
Author-X-Name-Last: Lentes
Author-Name: Nikolas Zimmermann
Author-X-Name-First: Nikolas
Author-X-Name-Last: Zimmermann
Title: amePLM: a platform providing information provision in engineering
Abstract: 
 The procedure for the engineering of products and production systems in manufacturing companies is often distributed over several organisational units. The different units involved in these procedures use their respective methods and tools, resulting in silo-like and distributed information and data sources for engineering. In this paper, the open platform amePLM is introduced. This platform is based on a semantic data model. The ontology as explicitly formulated data model allows an integrated view on data and information available in the systems used along the product lifecycle, and the automatic provision of suitable information to the user. Furthermore, this open approach allows the linking of the solution to existing engineering software systems in the sense of a continuous flow of information.
Journal: International Journal of Production Research
Pages: 3832-3841
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2017.1302617
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1302617
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Template-Type: ReDIF-Article 1.0
Author-Name: Ana Vafadar
Author-X-Name-First: Ana
Author-X-Name-Last: Vafadar
Author-Name: Kevin Hayward
Author-X-Name-First: Kevin
Author-X-Name-Last: Hayward
Author-Name: Majid Tolouei-Rad
Author-X-Name-First: Majid
Author-X-Name-Last: Tolouei-Rad
Title: Sensitivity analysis for justification of utilising special purpose machine tools in the presence of uncertain parameters
Abstract: 
 Decision-makers in manufacturing area frequently face machine tool selection problem under uncertainty due to competitive market changes. Special purpose machines (SPMs), a relatively new class of reconfigurable machine tools, are used to react quickly to changes. Justification of utilising these machines vs. other machine tools requires a technique to investigate the sources of uncertainties. In this work, sensitivity analysis is utilised to investigate the sources of these uncertainties and errors which may reveal new insights for evaluating a machine tool. An illustrative example is provided to show the sensitivity of parameters on the economic performance of SPMs compared to the other alternatives. The results show that this analysis provides additional information and moves the decision closer to the optimum alternative.
Journal: International Journal of Production Research
Pages: 3842-3861
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2017.1308032
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1308032
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenchi Shou
Author-X-Name-First: Wenchi
Author-X-Name-Last: Shou
Author-Name: Jun Wang
Author-X-Name-First: Jun
Author-X-Name-Last: Wang
Author-Name: Peng Wu
Author-X-Name-First: Peng
Author-X-Name-Last: Wu
Author-Name: Xiangyu Wang
Author-X-Name-First: Xiangyu
Author-X-Name-Last: Wang
Author-Name: Heap-Yih Chong
Author-X-Name-First: Heap-Yih
Author-X-Name-Last: Chong
Title: A cross-sector review on the use of value stream mapping
Abstract: 
 Value Stream Mapping (VSM) has become a popular method for lean thinking and implementation in recent years. Previous reviews related to VSM are limited to individual sectors due to varied research objectives. The lack of studies which focus on cross-sector review of VSM studies is impeding the implementation of VSM by both lean researchers and practitioners. The paper aims to determine the-state-of-the-art development of VSM in five sectors, including manufacturing, health care, construction, product development and service sectors. A total of 131 journal articles are reviewed and analysed from the period of 1999–12/2016. The analysis covers the complete implementation cycle of VSM, including metrics for current state map, improvement techniques for future state map, benefits and achievements of VSM application, and critical success factors for VSM implementation. Cross-sector comparisons and investigations are conducted to understand the differences of VSM implementations in various sectors to facilitate VSM development and increase the number of successful VSM implementation. The results suggest that understanding value and waste in a diverse value stream environment and ensuring the suitability and usability of traditional lean metrics/techniques within the different flow settings are central to the VSM development.
Journal: International Journal of Production Research
Pages: 3906-3928
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2017.1311031
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1311031
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohit Goswami
Author-X-Name-First: Mohit
Author-X-Name-Last: Goswami
Author-Name: Yash Daultani
Author-X-Name-First: Yash
Author-X-Name-Last: Daultani
Author-Name: M.K. Tiwari
Author-X-Name-First: M.K.
Author-X-Name-Last: Tiwari
Title: An integrated framework for product line design for modular products: product attribute and functionality-driven perspective
Abstract: 
 The purpose of this research is to facilitate original equipment manufacturers operating in a single market segment to frame their product line design strategy that pertains to offering right product attributes with right attribute level in the right product profile within a market segment. Through this research, we attempt to establish a link between functional level design of product attributes with commercial objectives of the enterprise. Initially, by deriving the functional importance of product attribute levels of individual product attributes within a product profile, demand and functional importance data are generated. Utilising the function-based cost estimating framework and multi-linear regression methodology, we determine the cost and product development time coefficients for respective product attributes. Finally, a mixed integer quadratic programming-based mathematical formulation is developed that includes maximisation of product premium and minimisation of various costs as major objectives under the assumption that manufacturer seeks to offer optimal number of product profiles within the market segment. Employing the commercial solver LINGO, the integrated framework is solved. The entire framework is illustrated using the operator cabin of heavy construction machinery.
Journal: International Journal of Production Research
Pages: 3862-3885
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2017.1314039
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1314039
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Template-Type: ReDIF-Article 1.0
Author-Name: Runliang Dou
Author-X-Name-First: Runliang
Author-X-Name-Last: Dou
Author-Name: Yubo Zhang
Author-X-Name-First: Yubo
Author-X-Name-Last: Zhang
Author-Name: Guofang Nan
Author-X-Name-First: Guofang
Author-X-Name-Last: Nan
Title: Iterative product design through group opinion evolution
Abstract: 
 More and more industrial products have begun to adopt iterative design modes. Opinions collected from all sides in each round of iterations are used as bases to make products that are able to capture the changes of customer demand dynamically and to respond to these changes in a timely manner. In this context, it becomes important for product designers and manufacturers to study the evolution of opinions as well as the product scheme along with design iteration to determine its regularity. This paper integrates the Hegselmann–Krause model into product improvement process, and develops a dynamic model from the view of opinion dynamics. The dynamic model simultaneously converges the evolution of customers’ opinions, professional designers’ opinions and the product scheme. The paper also analyses the interaction mechanism among different opinions as well as the mechanism between opinions and the product scheme. The experimental results determine that the product scheme, customers’ opinions and professional designers’ opinions can demonstrate differently but regular evolution patterns along with the design iteration according to the difference in confidence intervals or the difference caused by tending to adopt a more customer-driven design strategy or a more professional designer-driven design strategy. Finally, reasonable suggestions are provided to help manufacturers make product design strategies.
Journal: International Journal of Production Research
Pages: 3886-3905
Issue: 13
Volume: 55
Year: 2017
Month: 7
X-DOI: 10.1080/00207543.2017.1316020
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1316020
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Template-Type: ReDIF-Article 1.0
Author-Name: Hengxia Gao
Author-X-Name-First: Hengxia
Author-X-Name-Last: Gao
Author-Name: Dandan Wang
Author-X-Name-First: Dandan
Author-X-Name-Last: Wang
Author-Name: Ernesto D. R. Santibanez Gonzalez
Author-X-Name-First: Ernesto D. R.
Author-X-Name-Last: Santibanez Gonzalez
Author-Name: Yanbing Ju
Author-X-Name-First: Yanbing
Author-X-Name-Last: Ju
Title: Optimal stocking strategies for inventory mechanism with a stochastic short-term price discount and partial backordering
Abstract: 
 Price discount is an important research topic in the field of inventory management. The existing research on this topic mainly considers fixed price discount, but ignores the situation in which stochastic short-term price discount may be involved. In this paper, we study an inventory problem considering stochastic short-term price discount and partial backordering. To address this problem, we propose an optimal replenishment and stocking model to maximise the retailers' profit. After that, a cost–benefit analysis-based heuristic method for solving the developed model is presented by considering two scenarios depending on whether a replenishment point belongs to a discount period or not. Furthermore, an algorithm is provided to elicit an optimal ordering policy from multiple solutions derived from the given heuristic solution method. Finally, a real case is offered to demonstrate the application of the proposed model, followed by a sensitivity analysis. The results indicate that a retailer can identify the optimal replenishment policy with the aim of achieving maximal profit in situations where stochastic short-term price discount and partial backordering are considered for certain inventory problems at hand. In addition, sensitivity analysis illustrates a fact that different values of the introduced parameters may influence the optimal replenishment policy.
Journal: International Journal of Production Research
Pages: 7471-7500
Issue: 24
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1567949
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1567949
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiang Wan
Author-X-Name-First: Xiang
Author-X-Name-Last: Wan
Title: What happened to inventory and cost after a vertical integration? A longitudinal analysis considering demand uncertainty
Abstract: 
 This study provides empirical analyses on the changes in inventory and cost of goods sold (COGS) after vertical integration. Theoretical studies suggest contradictory influences of vertical integration on operations due to operational conflicts and coordination improvement: (1) operational conflicts that raise inventory level and COGS and (2) coordination improvement that lowers inventory level and cost. Hence, the changes in inventory and COGS associated with vertical integration become an empirical question. This study applied Econometrics models to analyse proprietary data associated with a vertical integration. The results suggest non-monotonic patterns of changes in inventory level and cost of goods sold. Specifically, when various fixed effects are controlled, inventory and COGS increase first then decrease after vertical integration. Furthermore, increases are amplified while decreases are weakened by higher demand uncertainty. These findings provide managers with a comprehensive understanding of the operational consequences of vertical integration decisions and some implications to managing the benefits associated with vertical integration.
Journal: International Journal of Production Research
Pages: 7501-7519
Issue: 24
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1584414
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1584414
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Template-Type: ReDIF-Article 1.0
Author-Name: Faycal A. Touzout
Author-X-Name-First: Faycal A.
Author-X-Name-Last: Touzout
Author-Name: Lyes Benyoucef
Author-X-Name-First: Lyes
Author-X-Name-Last: Benyoucef
Title: Multi-objective multi-unit process plan generation in a reconfigurable manufacturing environment: a comparative study of three hybrid metaheuristics
Abstract: 
 Low costs, high reactivity and high quality products are necessary criteria for industries to achieve competitiveness in nowadays market. In this context, reconfigurable manufacturing systems (RMSs) have emerged to fulfil these requirements. RMS is one of the latest manufacturing paradigms, where machines components, software or material handling units can be added, removed, modified or interchanged as needed and when imposed by the necessity to react and respond rapidly and cost-effectively to changing. This research work addresses the multi-objective single-product multi-unit process plan generation problem in a reconfigurable manufacturing environment where three hybrid heuristics are proposed and compared namely: repetitive single-unit process plan heuristic (RSUPP), iterated local search on single-unit process plans heuristic (LSSUPP) and archive-based iterated local search heuristic (ABILS). Single-unit process plans are generated using the adapted non-dominated sorting genetic algorithm (NSGA-II). Moreover, in addition to the minimisation of the classical total production cost and the total completion time, the minimisation of the maximum machines exploitation time is considered as a novel optimisation criterion, in order to have high quality products. To illustrate the applicability of the three approaches, examples are presented and the obtained numerical results are analysed.
Journal: International Journal of Production Research
Pages: 7520-7535
Issue: 24
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1635277
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1635277
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei Xing
Author-X-Name-First: Wei
Author-X-Name-Last: Xing
Author-Name: Qing Zhu
Author-X-Name-First: Qing
Author-X-Name-Last: Zhu
Author-Name: Xuan Zhao
Author-X-Name-First: Xuan
Author-X-Name-Last: Zhao
Title: Supply contract design under price volatility and competition
Abstract: 
 This study analyses index-based contract designs and contract equilibria in a competitive setting. We consider a two-echelon supply chain consisting of two manufacturers and a retailer. Each manufacturer procures a commodity in a spot market and uses such a commodity to produce a product. The manufacturers initially choose either an index-based or fixed-price contract. Thereafter, the manufacturer that adopts an index-based contract designs the contract price on the basis of the spot and forward prices of its input commodity. Finally, the two products are sold through the common retailer. Our analysis indicates that an index-based contract provides a manufacturer with a contingent pricing mechanism, thereby enabling the contract price to respond to the spot price of its input commodity. If only one manufacturer adopts an index-based contract, then the contract price is designed to respond positively to the corresponding spot price, while the contract design constantly benefits the designer but may either benefit or hurt the rival and retailer. If both manufacturers adopt an index-based contract, then the contract price may be designed to respond negatively to the corresponding spot price. The reason is that the manufacturer intends to dampen competition by adopting an opposite contract price design. Further study shows that in equilibrium, both manufacturers consistently adopt an index-based contact if the spot prices are positively correlated. However, differentiated contract strategies may be optimal for manufacturers if the correlation is negative.
Journal: International Journal of Production Research
Pages: 7536-7551
Issue: 24
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1678085
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1678085
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Template-Type: ReDIF-Article 1.0
Author-Name: Lin Wang
Author-X-Name-First: Lin
Author-X-Name-Last: Wang
Author-Name: Zhiqiang Lu
Author-X-Name-First: Zhiqiang
Author-X-Name-Last: Lu
Author-Name: Xiaole Han
Author-X-Name-First: Xiaole
Author-X-Name-Last: Han
Title: Joint optimisation of production, maintenance and quality for batch production system subject to varying operational conditions
Abstract: 
 This paper considers the integration problem of production, maintenance and quality for a capacitated lot-sizing production system subject to deterioration. The effects of varying operational conditions from batch to batch on system reliability and product quality are modelled by proportional hazards models, resulting in non-monotonic failure rate and defect rate. After each batch production, imperfect preventive maintenance (PM) is determined to mitigate the system deterioration, and inspection is taken to sort nonconforming items in the finished goods. Once the cumulative number of nonconforming items exceeds a predetermined threshold, an overhaul is performed to renew the system. An integrated model for optimising production plan, PM plan and overhaul strategy is developed to minimise the total cost while satisfying all product demands. A genetic algorithm is proposed to solve the integrated model efficiently. Numerical results validate the rationality of the model with varying operational conditions consideration and its applicability in economic benefits.
Journal: International Journal of Production Research
Pages: 7552-7566
Issue: 24
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1581956
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1581956
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Template-Type: ReDIF-Article 1.0
Author-Name: Lu Zhen
Author-X-Name-First: Lu
Author-X-Name-Last: Zhen
Author-Name: Qiuji Sun
Author-X-Name-First: Qiuji
Author-X-Name-Last: Sun
Author-Name: Kai Wang
Author-X-Name-First: Kai
Author-X-Name-Last: Wang
Author-Name: Xiaotian Zhang
Author-X-Name-First: Xiaotian
Author-X-Name-Last: Zhang
Title: Facility location and scale optimisation in closed-loop supply chain
Abstract: 
 This paper solves a strategic-level decision problem on determining the optimal location of (re)manufacturers and logistics centres with the consideration of facility scales in an integrated closed-loop supply chain network. A two-stage stochastic mixed-integer non-linear programming model is established to minimise the fixed cost and the expected operation costs under uncertain demand and return. We develop an improved tabu search heuristic algorithm to solve the model. We also design a distance-based decision rule to validate the effectiveness of the proposed model. Numerical experiments are conducted to test the performance of the proposed model and the solution method. In addition, sensitivity analysis is provided to investigate the influences of varying inspection locations and recovery rates on the final performance.
Journal: International Journal of Production Research
Pages: 7567-7585
Issue: 24
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1587189
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1587189
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Template-Type: ReDIF-Article 1.0
Author-Name: Nico André Schmid
Author-X-Name-First: Nico André
Author-X-Name-Last: Schmid
Author-Name: Veronique Limère
Author-X-Name-First: Veronique
Author-X-Name-Last: Limère
Title: A classification of tactical assembly line feeding problems
Abstract: 
 Trends like mass-customisation and the increasing number of models produced and parts used on a single assembly line promote interest in the field of assembly line feeding. The assembly line feeding problem (ALFP) deals with the assignment of parts to line feeding policies such as line stocking, boxed-supply, sequencing and kitting (stationary and travelling), and emerged as a research field two and a half decades ago. In order to structure the increasing effort in this field, we provide an extensive review of the literature and organise it from various perspectives. Furthermore, we propose a classification for the ALFP and classify existing literature. The goal of this classification is threefold. Firstly, it should help the reader to get an overview of the problem and most of its related aspects. Secondly, the classification reveals blind spots in academic research. Finally, it enables practitioners to match real-world problems with existing research results. In order to encourage researchers to close the existing gaps, we finalise this paper by pointing out the most important open research fields.
Journal: International Journal of Production Research
Pages: 7586-7609
Issue: 24
Volume: 57
Year: 2019
Month: 12
X-DOI: 10.1080/00207543.2019.1581957
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1581957
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Template-Type: ReDIF-Article 1.0
Author-Name: Ann-Christine Falck
Author-X-Name-First: Ann-Christine
Author-X-Name-Last: Falck
Author-Name: Malin Tarrar
Author-X-Name-First: Malin
Author-X-Name-Last: Tarrar
Author-Name: Sandra Mattsson
Author-X-Name-First: Sandra
Author-X-Name-Last: Mattsson
Author-Name: Lina Andersson
Author-X-Name-First: Lina
Author-X-Name-Last: Andersson
Author-Name: Mikael Rosenqvist
Author-X-Name-First: Mikael
Author-X-Name-Last: Rosenqvist
Author-Name: Rikard Söderberg
Author-X-Name-First: Rikard
Author-X-Name-Last: Söderberg
Title: Assessment of manual assembly complexity: a theoretical and empirical comparison of two methods
Abstract: 
 There are several theoretical methods for assessment of assembly complexity but there are few practically applicable methods. One of the methods, CompleXity Index (CXI), aims at assessing operators’ perception of manual assembly complexity in running production. Another recently developed method, Basic Assembly Complexity (CXB) is intended for predictive assessment of basic manual assembly complexity in early product and production development. Both CXI and CXB aim to improve assembly conditions for operators, reduce assembly-related errors and the costs for corrective measures as well as increase assembly quality although in different ways and at different organisational levels and life cycle stages. The purpose of this study was to compare the two methods to obtain feedback and learn from operators experience in order to develop better predictive assessment criteria. The method comparison showed that about 50% of the CXB assessment approaches were similar to CXI but other covered different aspects. In comparison of the complexity values of the methods no significant results were obtained. However, some CXI issues that were not taken into account in CXB should be considered. CXB and CXI could be used in conjunction but further assessment criteria are probably needed.
Journal: International Journal of Production Research
Pages: 7237-7250
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1330571
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1330571
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Template-Type: ReDIF-Article 1.0
Author-Name: Chuwen Zhang
Author-X-Name-First: Chuwen
Author-X-Name-Last: Zhang
Author-Name: Jonathan F. Bard
Author-X-Name-First: Jonathan F.
Author-X-Name-Last: Bard
Author-Name: Rodolfo Chacon
Author-X-Name-First: Rodolfo
Author-X-Name-Last: Chacon
Title: Controlling work in process during semiconductor assembly and test operations
Abstract: 
 This paper introduces a mid-term planning model for scheduling assembly and test operations aimed at minimising the difference between customer demand and product completions each day. A secondary objective is to maximise daily surplus which is a surrogate for throughput. Typically, semiconductor companies have 1000s of products or devices in their catalogue that can be organised into unique groups of up to a 100 devices each. This simplifies the planning process because it is only necessary to consider the groups as a whole rather than the individual devices when constructing schedules. In all, we developed and tested three related models. Each provides daily production rates at each process step for each device group for up to one month at a time. The models are distinguished by how cycle time is treated. The first takes a steady-state approach and uses Little’s Law to formulate a WIP target constraint based on the average cycle time at each processing step. The second and third include integer and fractional cycle times in the variable definitions. To find solutions, raw production data are analysed in a preprocessing step and then converted to input files in a standard format. FlopC++ from the COIN-OR open source software project is used to write and solve the model. Testing was done using three data-sets from the Taiwan AT facility of a global semiconductor firm. By comparing model output with historical data for 6 device groups and 33 process steps, we were able to realise decreases in shortages of up to 40% per month.
Journal: International Journal of Production Research
Pages: 7251-7275
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1333649
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1333649
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Template-Type: ReDIF-Article 1.0
Author-Name: Pooya Alavian
Author-X-Name-First: Pooya
Author-X-Name-Last: Alavian
Author-Name: Peter Denno
Author-X-Name-First: Peter
Author-X-Name-Last: Denno
Author-Name: Semyon M. Meerkov
Author-X-Name-First: Semyon M.
Author-X-Name-Last: Meerkov
Title: Multi-job production systems: definition, problems, and product-mix performance portrait of serial lines
Abstract: 
 This paper pursues two goals: (a) Define a class of widely used in practice flexible manufacturing systems, referred to as Multi-Job Production (MJP) and formulate industrially motivated problems related to their performance. (b) Provide initial results concerning some of these problems pertaining to analysis of the throughput and bottlenecks of MJP serial lines as functions of the product-mix. In MJP systems, all job-types are processed by the same sequence of manufacturing operations, but with different processing time at some or all machines. To analyse MJP with unreliable machines, we introduce the work-based model of production systems, which is insensitive to whether single- or multi-job manufacturing takes place. Based on this model, we investigate the performance of MJP lines as a function of the product-mix. We show, in particular, that for the so-called conflicting jobs there exists a range of product-mixes, wherein the throughput of MJP is larger than that of any constituent job-type manufactured in a single-job regime. To characterise the global behaviour of MJP lines, we introduce the Product-Mix Performance Portrait, which represents the system properties for all product-mixes and which can be used for operations management. Finally, we report the results of an application at an automotive assembly plant.
Journal: International Journal of Production Research
Pages: 7276-7301
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1338779
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1338779
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Template-Type: ReDIF-Article 1.0
Author-Name: Yaping Ren
Author-X-Name-First: Yaping
Author-X-Name-Last: Ren
Author-Name: Daoyuan Yu
Author-X-Name-First: Daoyuan
Author-X-Name-Last: Yu
Author-Name: Chaoyong Zhang
Author-X-Name-First: Chaoyong
Author-X-Name-Last: Zhang
Author-Name: Guangdong Tian
Author-X-Name-First: Guangdong
Author-X-Name-Last: Tian
Author-Name: Leilei Meng
Author-X-Name-First: Leilei
Author-X-Name-Last: Meng
Author-Name: Xiaoqiang Zhou
Author-X-Name-First: Xiaoqiang
Author-X-Name-Last: Zhou
Title: An improved gravitational search algorithm for profit-oriented partial disassembly line balancing problem
Abstract: 
 Disassembly is indispensable to recycle and remanufacture end-of-life products, and a disassembly line-balancing problem (DLBP) is studied frequently. Recent research on disassembly lines has focused on a complete disassembly for optimising the balancing ability of lines. However, a partial disassembly process is widely applied in the current industry practice, which aims at reusing valuable components and maximising the profit (or minimising the cost). In this paper, we consider a profit-oriented partial disassembly line-balancing problem (PPDLBP), and a mathematical model of this problem is established, which is to achieve the maximisation of profit for dismantling a product in DLBP. The PPDLBP is NP-complete since DLBP is proven to be a NP-complete problem, which is usually handled by a metaheuristics. Therefore, a novel efficient approach based on gravitational search algorithm (GSA) is proposed to solve the PPDLBP. GSA is an optimisation technique that is inspired by the Newtonian gravity and the laws of motion. Also, two different scale cases are used to test on the proposed algorithm, and some comparisons with the CPLEX method, particle swarm optimisation, differential evolution and artificial bee colony algorithms are presented to demonstrate the excellence of the proposed approach.
Journal: International Journal of Production Research
Pages: 7302-7316
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1341066
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1341066
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Template-Type: ReDIF-Article 1.0
Author-Name: Hyung-Won Kim
Author-X-Name-First: Hyung-Won
Author-X-Name-Last: Kim
Author-Name: Dong-Ho Lee
Author-X-Name-First: Dong-Ho
Author-X-Name-Last: Lee
Title: An optimal algorithm for selective disassembly sequencing with sequence-dependent set-ups  in parallel disassembly environment
Abstract: 
 This study considers selective disassembly sequencing in parallel disassembly environment in which two or more components can be removed by a single disassembly operation. The problem is to determine the sequence of disassembly operations to extract multiple target components while satisfying the precedence relations among disassembly operations. The objective is to minimise the sum of sequence-dependent set-up and operation costs. An integer programming model is developed after representing all possible disassembly sequences using an extended process graph, and then an optimal branch and bound algorithm is proposed that incorporates the methods to obtain the lower and upper bounds as well as a dominance property to reduce the search space. To show the performance of the algorithm, computational experiments are done on various random instances, and the results are reported. In particular, it is shown from the test results that the optimal algorithm requires much shorter computation times than a competitive commercial software package. Finally, a case is reported to illustrate the extended process graph and the solution algorithm.
Journal: International Journal of Production Research
Pages: 7317-7333
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1342879
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuchen Li
Author-X-Name-First: Yuchen
Author-X-Name-Last: Li
Title: The type-II assembly line rebalancing problem considering stochastic task learning
Abstract: 
 Assembly lines with non-constant task time attribute are widely studied in the literature. For the SALBP-II assembly line balancing problem, we take account of stochastic task time changes, which is more practical than the deterministic times often assumed in industrial application. An algorithm – ENCORE, which leverages the traditional algorithm SALOME2, is proposed to address the assembly line balancing problem with stochastic task time attribute. Computational and statistical experiments are conducted to show the efficiency of proposed algorithms over traditional methods with regards to the improvement of total production times.
Journal: International Journal of Production Research
Pages: 7334-7355
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1346316
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Template-Type: ReDIF-Article 1.0
Author-Name: Wen Su
Author-X-Name-First: Wen
Author-X-Name-Last: Su
Author-Name: Xiaolei Xie
Author-X-Name-First: Xiaolei
Author-X-Name-Last: Xie
Author-Name: Jingshan Li
Author-X-Name-First: Jingshan
Author-X-Name-Last: Li
Author-Name: Li Zheng
Author-X-Name-First: Li
Author-X-Name-Last: Zheng
Author-Name: Shaw C. Feng
Author-X-Name-First: Shaw C.
Author-X-Name-Last: Feng
Title: Reducing energy consumption in serial production lines with Bernoulli reliability machines
Abstract: 
 This paper is devoted to developing an integrated model to minimise energy consumption while maintaining desired productivity in Bernoulli serial lines with unreliable machines and finite buffers. For small systems, such as three- and four-machine lines with small buffers, exact analysis to optimally allocate production capacity is introduced. For medium size systems (e.g. three- and four-machine lines with larger buffers, or five-machine lines with small buffers), an aggregation procedure to evaluate line production rate is introduced. Using it, optimal allocation of machine efficiency is searched to minimise energy consumption. Insights and allocation principles are obtained through the analyses. Finally, for larger systems, a fast and accurate heuristic algorithm is presented and validated through extensive numerical experiments to obtain optimal allocation of production capacity to minimise energy consumption while maintaining desired productivity.
Journal: International Journal of Production Research
Pages: 7356-7379
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1349948
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Template-Type: ReDIF-Article 1.0
Author-Name: Silviya Valeva
Author-X-Name-First: Silviya
Author-X-Name-Last: Valeva
Author-Name: Mike Hewitt
Author-X-Name-First: Mike
Author-X-Name-Last: Hewitt
Author-Name: Barrett W. Thomas
Author-X-Name-First: Barrett W.
Author-X-Name-Last: Thomas
Title: A matheuristic for workforce planning with employee learning and stochastic demand
Abstract: 
 This paper focuses on the opportunity to direct the development of responsive capacity by recognising that individuals learn through experience when designing workforce plans. We focus on the operations of a product manufacturer that seeks to maximise profit by selling multiple products, while recognising that demands for each product is uncertain. As such, we study a stochastic integer program wherein an organisation can hedge against uncertainty in demand both by holding inventory (at a cost) and building a more responsive production process. Solving this stochastic program presents many computational difficulties, including the fact that quantitative models of human learning are non-linear and the explosion of instance size that result from modelling uncertainty with scenarios. As a result, we propose a matheuristic for this problem and with an extensive computational study demonstrate its ability to produce high-quality solutions in little time.
Journal: International Journal of Production Research
Pages: 7380-7397
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1349950
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Template-Type: ReDIF-Article 1.0
Author-Name: Bahadır Durak
Author-X-Name-First: Bahadır
Author-X-Name-Last: Durak
Author-Name: Dilek Tuzun Aksu
Author-X-Name-First: Dilek
Author-X-Name-Last: Tuzun Aksu
Title: Dynamic programming and mixed integer programming based algorithms for the online glass cutting problem with defects and production targets
Abstract: 
 In flat glass manufacturing, glass products of various dimensions are cut from a glass ribbon that runs continuously on a conveyor belt. Placement of glass products on the glass ribbon is restricted by the defects of varying severity located on the ribbon as well as the quality grades of the products to be cut. In addition to cutting products, a common practice is to remove defective parts of the glass ribbon as scrap glass. As the glass ribbon moves continuously, cutting decisions need to be made within seconds, which makes this online problem very challenging. A simplifying assumption is to limit scrap cuts to those made immediately behind a defect (a cut-behind-fault or CBF). We propose an online algorithm for the glass cutting problem that solves a series of static cutting problems over a rolling horizon. We solve the static problem using two methods: a dynamic programming algorithm (DP) that utilises the CBF assumption and a mixed integer programming (MIP) formulation with no CBF restriction. While both methods improve the process yield substantially, the results indicate that MIP significantly outperforms DP, which suggests that the computational benefit of the CBF assumption comes at a cost of inferior solution quality.
Journal: International Journal of Production Research
Pages: 7398-7411
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1349951
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Template-Type: ReDIF-Article 1.0
Author-Name: F. Tevhide Altekin
Author-X-Name-First: F. Tevhide
Author-X-Name-Last: Altekin
Title: A comparison of piecewise linear programming formulations for stochastic disassembly line balancing
Abstract: 
 Recently, several mathematical programming formulations and solution approaches have been developed for the stochastic disassembly line balancing problem (DLBP). This paper aims at finding optimal solutions for the stochastic DLBP. Two second-order cone programming (SOCP1 and SOCP2) models and five piecewise linear mixed integer programming (PwLP) models are presented. The PwLP formulations involve two specially ordered sets of type 2 (S1 and S2) models and three convex combination (CC1, CC2 and CC3) models. In each modelling category, the latter models strengthen the initial S1 and CC1 models. Our computational analysis of a total 240 instances of ten problems demonstrates that all the seven models can be used to solve practical-sized DLBP problems to optimality using GUROBI. The SOCP2 model and the strengthened S2 and CC2 models lead to lower computation times, compared to SOCP1, S1, CC1 and CC3, respectively. Using the strengthened S2 and CC2 formulations, the CPU times of the CC3 model available in the literature can be reduced by 50 and 40%, respectively. Besides analysing the optimal solutions and the differences of the computation times, we present insights gained from our results.
Journal: International Journal of Production Research
Pages: 7412-7434
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1351639
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Template-Type: ReDIF-Article 1.0
Author-Name: Amos H.C. Ng
Author-X-Name-First: Amos H.C.
Author-X-Name-Last: Ng
Author-Name: Sabry Shaaban
Author-X-Name-First: Sabry
Author-X-Name-Last: Shaaban
Author-Name: Jacob Bernedixen
Author-X-Name-First: Jacob
Author-X-Name-Last: Bernedixen
Title: Studying unbalanced workload and buffer allocation of production systems using multi-objective optimisation
Abstract: 
 Numerous studies have investigated the effects of unbalanced service times and inter-station buffer sizes on the efficiency of discrete part, unpaced production lines. There are two main disadvantages of many of these studies: (1) only some predetermined degree of imbalance and patterns of imbalance have been evaluated against the perfectly balanced configuration, making it hard to form a general conclusion on these factors; (2) only a single objective has been set as the target, which neglects the fact that different patterns of imbalance may outperform with respect to different performance measures. Therefore, the aim of this study is to introduce a new approach to investigate the performance of unpaced production lines by using multiple-objective optimisation. It has been found by equipping multi-objective optimisation with an efficient, equality constraints handling technique, both the optimal pattern and degree of imbalance, as well as the optimal relationship among these factors and the performance measures of a production system can be sought and analysed with some single optimisation runs. The results have illustrated that some very interesting relationships among the key performance measures studied, including system throughput, work-in-process and average buffer level, could only be observed within a truly multi-objective optimisation context. While these results may not be generalised to apply to any production lines, the genericity of the proposed simulation-based approach is believed to be applicable to study any real-world, complex production lines.
Journal: International Journal of Production Research
Pages: 7435-7451
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1362121
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1362121
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Template-Type: ReDIF-Article 1.0
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Alena Otto
Author-X-Name-First: Alena
Author-X-Name-Last: Otto
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Title: Preventing ergonomic risks with integrated planning on assembly line balancing and parts feeding
Abstract: 
 In this paper, we advise to perform assembly line balancing simultaneously with decision-making on parts feeding. Such integrated planning may open additional potential to reduce labour costs. Additional planning flexibility gained with the integrated planning may be used to mitigate ergonomic risks at workplaces. We formulate the integrated assembly line balancing and parts feeding planning problem, propose a mixed-integer model and compare integrated planning to a common hierarchical planning approach in a detailed case study on the assembly of a self-priming pump. Our case study illustrates that workplaces with high ergonomic risks may emerge even in productions that involve handling parts and workpieces of low weights and avoid static and awkward postures. We also show that the proposed integrated planning approach may eliminate excessive ergonomic risks and improve productivity indicators simultaneously.
Journal: International Journal of Production Research
Pages: 7452-7472
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1363427
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1363427
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Template-Type: ReDIF-Article 1.0
Author-Name: H. Mosadegh
Author-X-Name-First: H.
Author-X-Name-Last: Mosadegh
Author-Name: S.M.T. Fatemi Ghomi
Author-X-Name-First: S.M.T.
Author-X-Name-Last: Fatemi Ghomi
Author-Name: G.A. Süer
Author-X-Name-First: G.A.
Author-X-Name-Last: Süer
Title: A control theoretical modelling for velocity tuning of the conveyor belt in a dynamic mixed-model assembly line
Abstract: 
 This paper proposes a control theoretical modelling to study dynamic behaviour of a mixed-model assembly line. First, an open-loop model is developed for the system, then examined via different conveyor’s velocity values. It is realised that the performance of the system is very sensitive to the velocity; therefore, a closed-loop (CL) model is developed taking feedback from the system. By the use of proportional-integral-derivative (PID) controller and SIMULINK, some interesting results are obtained applying CL model: regardless of the sequence of the products in the line, the total work-overload and idleness always equals to zero. Moreover, less working area within the workstation is required. Based on the statistical analysis, it is found that no significant increase in makespan is imposed by CL model. It is also shown that PID controller is robust not only to the disturbances of the velocity, also to the uncertainties in the assembly operation times. These results are supported by many numerical experiments dealing with different test problems, line configurations and sequences. Finally, using a discrete event simulation model, the proposed approach is applied into a seru production mode. Simulation results show that the feedback PID controller can deal with real-world assembly line problems, successfully.
Journal: International Journal of Production Research
Pages: 7473-7495
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1370150
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Template-Type: ReDIF-Article 1.0
Author-Name: Steven Hoedt
Author-X-Name-First: Steven
Author-X-Name-Last: Hoedt
Author-Name: Arno Claeys
Author-X-Name-First: Arno
Author-X-Name-Last: Claeys
Author-Name: Hendrik Van Landeghem
Author-X-Name-First: Hendrik
Author-X-Name-Last: Van Landeghem
Author-Name: Johannes Cottyn
Author-X-Name-First: Johannes
Author-X-Name-Last: Cottyn
Title: The evaluation of an elementary virtual training system for manual assembly
Abstract: 
 Due to the low volume high variety strategies of manufacturing companies, manual assembly operators have a much larger cognitive load than before. The expertise of the operators must be kept up to date at any time. Since the high investment and low flexibility of a real setting to perform a manual assembly training, a virtual replica is introduced in many cases. The aim of this paper is to study the effect of an elementary virtual training for manual assembly tasks. In literature, different studies on the topic can be found; nevertheless, a comparison between the different studies is not possible due to diverse evaluation methods and descriptions. A benchmark for a uniform evaluation of virtual training systems is presented and applied to this experiment. Two groups were submitted to a number of manual assembly tasks. The test group got a virtual training period in advance. A significant learning transfer during that training period was observed. When the first assembly of the reference group is counted as a real training, no significant difference can be found between the virtual and real training. The outcomes of this experiment will be used in future work to compare different virtual training systems and influential factors such as the assembly complexity. Furthermore, the application of virtual training to manual assembly in a mixed-model environment and its industrial usability are topics that still need to be studied.
Journal: International Journal of Production Research
Pages: 7496-7508
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1374572
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1374572
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Template-Type: ReDIF-Article 1.0
Author-Name: Seyed-Esmaeil Moussavi
Author-X-Name-First: Seyed-Esmaeil
Author-X-Name-Last: Moussavi
Author-Name: Morad Mahdjoub
Author-X-Name-First: Morad
Author-X-Name-Last: Mahdjoub
Author-Name: Olivier Grunder
Author-X-Name-First: Olivier
Author-X-Name-Last: Grunder
Title: Productivity improvement through a sequencing generalised assignment in an assembly line system
Abstract: 
 This paper considers the assignment of heterogeneous workers to workstations of an assembly line in order to minimise the total production time. As the structure of the system implies that each of the workstations needs at least one worker, thus the problem can be considered as a generalised assignment problem (GAP). The objective is to perform an efficient human resource planning for a specified horizon consisting of several periods. Hence, we present an extension of the generalised assignment problem, consisting of a set of GAPs (one for each planning period) in which each GAP depends on the previous ones. A mixed integer mathematical model is presented for this sequencing assignment problem. The model is solved by an exact algorithm using Gurobi solver. It is proved that the problem is NP-hard and solving the medium and large size instances is not possible by the exact algorithms. Hence, two matheuristic approaches based on the disaggregated formulation of GAP are proposed. The first approach solves the problem through two sub-problems as the transportation formulation and assignment formulation. The second approach solves the problem by decomposition of the problem into several classical GAPs. The approaches are examined by a total of 27 instances. The results illustrate the efficiency of the proposed algorithms in the computational time and accuracy of the solutions.
Journal: International Journal of Production Research
Pages: 7509-7523
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1378828
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1378828
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Template-Type: ReDIF-Article 1.0
Author-Name: Cláudia Pinho
Author-X-Name-First: Cláudia
Author-X-Name-Last: Pinho
Author-Name: Luis Mendes
Author-X-Name-First: Luis
Author-X-Name-Last: Mendes
Title: IT in lean-based manufacturing industries: systematic literature review and research issues
Abstract: 
 This systematic literature review is the first to explore the role of IT in lean manufacturing contexts, characterising literature on the field, identifying and exploring the main issues approached, and identifying potential future lines of research. Grounded on an accurate screening process, 124 papers were selected for analysis from the SCOPUS and the ISI Web of Knowledge databases. The structured content analysis process highlights five key issues approached in literature: (1) software and technologies used, (2) benefits achieved through applying IT in lean manufacturing, (3) importance of IT integration, (4) IT and lean as complementary or independent options and (5) role of human resources. Despite an apparent scepticism concerning compatibility between IT and lean, claiming that IT may lead to processes’ complexity, extra tasks, resource consuming, among other issues, among other key findings, the review shows that several different IT instruments may boost improvements, acting as a facilitator in developing lean industrial environments, especially when lean-based improvement processes are introduced first, and then IT infrastructures. Because both IT and Lean may require significant investments in terms of managerial attention, employees’ capabilities and financial resources, it is important for management to balance investment decisions. Authors point to several shortcomings in literature which represent significant opportunities for further research: (1) significant lack of integrated comprehensive frameworks, (2) lack of knowledge concerning hybrid manufacturing systems, supply chains as research unit of analysis, how organisations can respond to staff resistance, and role of IT across the distinctive stages of lean maturity.
Journal: International Journal of Production Research
Pages: 7524-7540
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1384585
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1384585
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Template-Type: ReDIF-Article 1.0
Author-Name: Asiye Aydilek
Author-X-Name-First: Asiye
Author-X-Name-Last: Aydilek
Author-Name: Harun Aydilek
Author-X-Name-First: Harun
Author-X-Name-Last: Aydilek
Author-Name: Ali Allahverdi
Author-X-Name-First: Ali
Author-X-Name-Last: Allahverdi
Title: Minimising maximum tardiness in assembly flowshops with setup times
Abstract: 
 This paper addresses a two-stage assembly flowshop scheduling problem with the objective of minimising maximum tardiness where set-up times are considered as separate from processing times. The performance measure of maximum tardiness is important for some scheduling environments, and hence, it should be taken into account while making scheduling decisions for such environments. Given that the problem is strongly NP-hard, different algorithms have been proposed in the literature. The algorithm of Self-Adaptive Differential Evolution (SDE) performs as the best for the problem in the literature. We propose a new hybrid simulated annealing and insertion algorithm (SMI). The insertion step, in the SMI algorithm, strengthens the exploration step of the simulated annealing algorithm at the beginning and reinforces the exploitation step of the simulated annealing algorithm towards the end. Furthermore, we develop several dominance relations for the problem which are incorporated in the proposed SMI algorithm. We compare the performance of the proposed SMI algorithm with that of the best existing algorithm, SDE. The computational experiments indicate that the proposed SMI algorithm performs significantly better than the existing SDE algorithm. More specifically, under the same CPU time, the proposed SMI algorithm, on average, reduces the error of the best existing SDE algorithm over 90%, which indicates the superiority of the proposed SMI algorithm.
Journal: International Journal of Production Research
Pages: 7541-7565
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1387300
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1387300
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Template-Type: ReDIF-Article 1.0
Author-Name: Sebastián Lozano
Author-X-Name-First: Sebastián
Author-X-Name-Last: Lozano
Author-Name: Gabriel Villa
Author-X-Name-First: Gabriel
Author-X-Name-Last: Villa
Author-Name: Ignacio Eguía
Author-X-Name-First: Ignacio
Author-X-Name-Last: Eguía
Title: Data envelopment analysis with multiple modes of functioning. Application to reconfigurable manufacturing systems
Abstract: 
 In principle, data envelopment analysis (DEA) does not consider the possibility, which can occur in practice, of a production system being able to operate in different modes of functioning. In this paper, a new DEA modelling approach is proposed in which the different modes of functioning are taken into account and included in the analysis. The observed input consumption and output production in each mode of functioning is used to derive a mode-specific technology. The overall DEA technology aggregates these mode-specific technologies according to their respective time allocations. The proposed model computes a target operating point for each mode of functioning so that the operation of the overall system is efficient. The proposed approach is applied to assess the technical, cost and allocative efficiency of a reconfigurable manufacturing system. The inputs considered are modules/tools usage, labour and energy consumption. The outputs are the number of units produced of each part type. The production possibility set is determined by previous observations of the system functioning, from which the best practices can be identified. Technical, cost and allocative efficiency scores can be computed. The proposed approach not only generates input cost savings but also lead time reductions.
Journal: International Journal of Production Research
Pages: 7566-7583
Issue: 24
Volume: 55
Year: 2017
Month: 12
X-DOI: 10.1080/00207543.2017.1391418
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1391418
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Template-Type: ReDIF-Article 1.0
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Author-Name: Chen Xu
Author-X-Name-First: Chen
Author-X-Name-Last: Xu
Author-Name: Chao Chen
Author-X-Name-First: Chao
Author-X-Name-Last: Chen
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Big Data Analytics for Physical Internet-based intelligent manufacturing shop floors
Abstract: 
 Physical Internet (PI, π) has been widely used for transforming and upgrading the logistics and supply chain management worldwide. This study extends the PI concept into manufacturing shop floors where typical logistics resources are converted into smart manufacturing objects (SMOs) using Internet of Things (IoT) and wireless technologies to create a RFID-enabled intelligent shop floor environment. In such PI-based environment, enormous RFID data could be captured and collected. This study introduces a Big Data Analytics for RFID logistics data by defining different behaviours of SMOs. Several findings are significant. It is observed that task weight is primarily considered in the logistics decision-making in this case. Additionally, the highest residence time occurs in a buffer with the value of 12.17 (unit of time) which is 40.57% of the total delivery time. That implies the high work-in-progress inventory level in this buffer. Key findings and observations are generated into managerial implications, which are useful for various users to make logistics decisions under PI-enabled intelligent shop floors.
Journal: International Journal of Production Research
Pages: 2610-2621
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2015.1086037
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1086037
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Template-Type: ReDIF-Article 1.0
Author-Name: Ting Qu
Author-X-Name-First: Ting
Author-X-Name-Last: Qu
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Junhao Wang
Author-X-Name-First: Junhao
Author-X-Name-Last: Wang
Author-Name: Zongzhong Wang
Author-X-Name-First: Zongzhong
Author-X-Name-Last: Wang
Author-Name: Huan Fu
Author-X-Name-First: Huan
Author-X-Name-Last: Fu
Author-Name: Congdong Li
Author-X-Name-First: Congdong
Author-X-Name-Last: Li
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: System dynamics analysis for an Internet-of-Things-enabled production logistics system
Abstract: 
 A production logistics system is often subject to high operational dynamics due to large working areas, frequent resource interactions, long operation periods and intensive human involvement. Researchers have applied system dynamics to design the structure of statistically robust systems which accommodate common dynamics. Yet this approach begins to lose its feasibility because dynamics anticipation and statistics are becoming more difficult in ever more competitive markets and adjustments to system structure typically incur high costs. In response, this study explores how a robust information structure can be designed and real-time control schemes for controlling the dynamics inherent to real-life systems applied. Motivated by the wide application of industrial Internet-of-Things (IoT) systems, this paper investigates the typical production logistic execution processes and adopts system dynamics to design cost-effective IoT solutions. The internal and external production logistic processes are first investigated separately. Using sensitivity analysis, the optimal IoT solutions are evaluated and analysed to provide guidance on IoT implementation. Internal and external production logistic processes are then combined into an integrated structure to offer a generic system dynamics approach. This research does not only enhance the use of system dynamics, but also presents a quantitative IoT system analysis approach.
Journal: International Journal of Production Research
Pages: 2622-2649
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1173738
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173738
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Template-Type: ReDIF-Article 1.0
Author-Name: Hoa Tran-Dang
Author-X-Name-First: Hoa
Author-X-Name-Last: Tran-Dang
Author-Name: Nicolas Krommenacker
Author-X-Name-First: Nicolas
Author-X-Name-Last: Krommenacker
Author-Name: Patrick Charpentier
Author-X-Name-First: Patrick
Author-X-Name-Last: Charpentier
Title: Containers monitoring through the Physical Internet: a spatial 3D model based on wireless sensor networks
Abstract: 
 The Physical Internet concept was developed to address the current unsustainability problem of logistic systems. The key elements are the encapsulation and the handling of world-standard smart green modular containers (π-containers) throughout an open global logistic infrastructure. Logistic processes such as partial loading/unloading or splitting/merging of π-containers play an important role for a successful Physical Internet. However, the large variety of transformation processes can introduce desynchronisation between the physical and informational flows, i.e. the real composition of a composite π-container (a set of stacked π-containers) can differ of the information stored in the supply chain management system. To overcome this problem, this paper proposes a system to generate and maintain automatically a virtual three-dimensional layout reflecting the spatial distribution of π-containers. The proposed approach uses smart π-containers equipped with wireless sensor nodes. The relative position of π-containers can be determined by the neighbourhood relationships between the sensor nodes. From this information, a constraint set is formulated in a Constraint Satisfaction Problem where each solution is a potential loading pattern. The methodology is developed and computational experiments are proposed, as a proof-of-concept. The results show that our proposed method yields quick and satisfactory results.
Journal: International Journal of Production Research
Pages: 2650-2663
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1206220
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1206220
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Template-Type: ReDIF-Article 1.0
Author-Name: Dah-Chuan Gong
Author-X-Name-First: Dah-Chuan
Author-X-Name-Last: Gong
Author-Name: Jia-Lun Kang
Author-X-Name-First: Jia-Lun
Author-X-Name-Last: Kang
Author-Name: Gary C. Lin
Author-X-Name-First: Gary C.
Author-X-Name-Last: Lin
Author-Name: T. C. Hou
Author-X-Name-First: T. C.
Author-X-Name-Last: Hou
Title: On an IC wire bonding machine production–inventory problem with time value of money
Abstract: 
 The semiconductor industry in Taiwan has received excellent performance ratings in the past. SinoPac’s statistics in January, 2016 found that two of the top four global packaging and testing companies are from Taiwan, including ASE Group and SPIL. In the IC packaging process, the wire bonding machine requires careful attention. It is also costly at approximately 50% of the equipment investment. Thus, this paper focuses on wire bonding machines’ production problems. According to the on-site interviews, three key control modules are identified, which may change a machine to an out-of-control state and are responsible for 90% of the defective products. A mathematical model is developed to determine the optimal production time of an imperfect production process. Taking the time value of money, the objective is to minimise the total of the set-up cost, inventory cost and the defect cost. Besides applying MacLaurin Series, a math property and an effective solution range are derived to help obtain near-optimal solutions. For the justification of solution quality, the bisection method working on practical data is used. Finally, managerial insights are explored from observed outputs through the changes of various parameters. Moreover, these explorations are confirmed by experts in this field.
Journal: International Journal of Production Research
Pages: 2431-2453
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1213914
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213914
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Template-Type: ReDIF-Article 1.0
Author-Name: Gu Pang
Author-X-Name-First: Gu
Author-X-Name-Last: Pang
Author-Name: Bartosz Gebka
Author-X-Name-First: Bartosz
Author-X-Name-Last: Gebka
Title: Forecasting container throughput using aggregate or terminal-specific data? The case of Tanjung Priok Port, Indonesia
Abstract: 
 We propose a new approach to forecasting total port container throughput: to generate forecasts based on each of the port’s terminals and aggregate them into the total throughput forecast. We forecast the demand for total container throughput at the Indonesia’s largest seaport Tanjung Priok Port, employing SARIMA, the additive and multiplicative Seasonal Holt-Winters (MSHW) and the Vector Error Correction Model (VECM) on the monthly port and individual terminal container throughput time series between 2003 and 2013. The performance of forecasting models is evaluated based on mean absolute error and root mean squared error. Our results show that the MSHW model produces the most accurate forecasts of total container throughput, whereas SARIMA generates the worst in-sample model fit. The VECM provides the best model fits and forecasts for individual terminals. Our results report that the total container throughput forecasts based on modelling the total throughput time series are consistently better than those obtained by combining those forecasts generated by terminal-specific models. The forecasts of total throughput until the end of 2018 provide an essential insight into the strategic decision-making on the expansion of port’s capacity and construction of new container terminals at Tanjung Priok Port.
Journal: International Journal of Production Research
Pages: 2454-2469
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1227102
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1227102
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Template-Type: ReDIF-Article 1.0
Author-Name: Xian Cheng
Author-X-Name-First: Xian
Author-X-Name-Last: Cheng
Author-Name: Shaoyi Liao
Author-X-Name-First: Shaoyi
Author-X-Name-Last: Liao
Author-Name: Zhongsheng Hua
Author-X-Name-First: Zhongsheng
Author-X-Name-Last: Hua
Title: A policy of picking up parcels for express courier service in dynamic environments
Abstract: 
 As a particular logistics service, the express courier service has seen considerable growth recently, which resulted in an unprecedented fierce competition. Besides, the development of information and communication technologies has enabled express company to manage their service. With the purpose of improving service quality and operation efficiency for express company, we focus on the problem of intercity express courier routing in courier-triggered pickup service. A novel pickup policy for courier routing is proposed based on the idea of centrality measures and the nearest-neighbour (NN) policy by considering the un-serviced customer requests as a globally coupled network. This policy enables to dispatch the idle courier to the more central request location, which allows the courier to easily serve the neighbouring requests around the central request location, thus securing both global and local performance. We also propose a simple prototype of real-time fleet management system where the proposed pickup policy is embedded into it. To evaluate the efficiency and practicability of the pickup policy, we conduct comprehensive computational experiments to generate various testing scenarios; moreover, two widely used dispatching policies – NN and first-come-first-served (FCFS) – are considered as the benchmark policy. Results show that the proposed pickup policy significantly outperforms the NN and FCFS policies in terms of waiting time and total service time.
Journal: International Journal of Production Research
Pages: 2470-2488
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1231431
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1231431
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Template-Type: ReDIF-Article 1.0
Author-Name: B.C. Giri
Author-X-Name-First: B.C.
Author-X-Name-Last: Giri
Author-Name: A. Chakraborty
Author-X-Name-First: A.
Author-X-Name-Last: Chakraborty
Author-Name: T. Maiti
Author-X-Name-First: T.
Author-X-Name-Last: Maiti
Title: Consignment stock policy with unequal shipments and process unreliability for a two-level supply chain
Abstract: 
 This paper considers a vendor managed inventory model with consignment stock policy in which a single vendor delivers a single product to a single buyer in unequal-sized shipments. The vendor’s production process may produce some defective items during a production run. The buyer performs a screening process immediately after receiving each delivery from the vendor and the vendor bears the warranty cost of defective item, if any. The buyer either scraps or repairs the defective items by sending them to a repair factory. The average expected profit of the integrated system is derived using renewal reward theorem and a solution procedure is suggested to determine the optimal shipment policy of the vendor. Numerical examples are taken to determine both the equal and unequal shipment policies and compare their relative performances.
Journal: International Journal of Production Research
Pages: 2489-2505
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1233362
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1233362
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Template-Type: ReDIF-Article 1.0
Author-Name: Marko Mladineo
Author-X-Name-First: Marko
Author-X-Name-Last: Mladineo
Author-Name: Ivica Veza
Author-X-Name-First: Ivica
Author-X-Name-Last: Veza
Author-Name: Nikola Gjeldum
Author-X-Name-First: Nikola
Author-X-Name-Last: Gjeldum
Title: Solving partner selection problem in cyber-physical production networks using the HUMANT algorithm
Abstract: 
 The idea of non-hierarchical production networks consisting of autonomous enterprises has been present in scientific community for more than 20 years. Although some global corporations are using their own production networks across continents, they are not similar to the original idea of non-hierarchical production networks in many aspects. It seems that this idea waited for production systems to acquire proper information and communications technology (ICT) or new industrial platforms, like Industry 4.0. The result is a new type of production network called Cyber-Physical Production Network (CPPN). The CPPN is, from ICT point of view, ready to act as non-hierarchical production networks consisting of autonomous production systems with many automated processes. One of the most important processes of the CPPN is a selection of optimal partners (enterprises) to be part of a new virtual enterprise, created inside production network. An optimisation problem emerges in this process, and it is called Partner Selection Problem (PSP). It is non-polynomial-hard combinatorial problem. Since metaheuristic algorithms are well-proven in solving that kind of problem, a specially designed metaheuristic algorithm derived from ant colony optimisation and named the HUMANT (HUManoid ANT) algorithm is used in this paper. It is multi-objective optimisation algorithm that successfully solves different instances of PSP with two, three, four or more objectives.
Journal: International Journal of Production Research
Pages: 2506-2521
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1234084
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1234084
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Template-Type: ReDIF-Article 1.0
Author-Name: Rafael Diaz
Author-X-Name-First: Rafael
Author-X-Name-Last: Diaz
Author-Name: Erika Marsillac
Author-X-Name-First: Erika
Author-X-Name-Last: Marsillac
Title: Evaluating strategic remanufacturing supply chain decisions
Abstract: 
 Accurately evaluating strategic commitments to remanufacturing requires a comprehensive understanding and consideration of the simultaneous effect of uncertainty on supply and demand. This paper presents a model that supports improved remanufacturing decision-making under stochastic demand and supply components and various cost factor considerations. The model is formulated as a newsvendor model extension that considers the simultaneous effects of probabilistic supply and demand. This characterisation assesses the effects of critical operational constraints on several strategic performance measures including cost, revenue and profit. The paper employs a Monte Carlo approach to assess the performance and extent of engagement in strategic remanufacturing supply chain operations, and illustrates results via a case study application. Results indicate that the technique can assist decision-makers in strategically determining the potential of future engagements in remanufacturing activities, and extends research findings by theoretically examining strategic decision-making for remanufacturing activity.
Journal: International Journal of Production Research
Pages: 2522-2539
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1239848
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1239848
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Template-Type: ReDIF-Article 1.0
Author-Name: Tingying Wu
Author-X-Name-First: Tingying
Author-X-Name-Last: Wu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Zhen Yang
Author-X-Name-First: Zhen
Author-X-Name-Last: Yang
Author-Name: Zhili Zhou
Author-X-Name-First: Zhili
Author-X-Name-Last: Zhou
Author-Name: Wei Zhou
Author-X-Name-First: Wei
Author-X-Name-Last: Zhou
Title: Lagrangean relaxation and hybrid simulated annealing tabu search procedure for a two-echelon capacitated facility location problem with plant size selection
Abstract: 
 In this paper, we study a two-echelon capacitated facility location problem with plant size selection (TECFLP-PSS). Given a set of potential sites for plants, each of which is associated with several possible sizes and corresponding unit production costs, a set of potential sites for capacitated depots and a set of customers with demands, the TECFLP-PSS aims to optimise the plant locations and sizes, the depot locations and the product flows from the opened plants to the opened depots and then to the end customers under single-source constraints. The objective is to satisfy all customers’ demands with a minimum total cost of facility opening, production and transportation. We develop a mixed integer programming model and propose a Lagrangean relaxation approach combined with new valid inequalities and core problem to achieve tight lower and upper bounds for this problem. We then improve the upper bound with a hybrid simulated annealing tabu search procedure. Computational experiments on benchmarks and randomly generated instances are conducted to validate the effectiveness and efficiency of the proposed method.
Journal: International Journal of Production Research
Pages: 2540-2555
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1240381
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1240381
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianchang Fan
Author-X-Name-First: Jianchang
Author-X-Name-Last: Fan
Author-Name: Debing Ni
Author-X-Name-First: Debing
Author-X-Name-Last: Ni
Author-Name: Xiaowo Tang
Author-X-Name-First: Xiaowo
Author-X-Name-Last: Tang
Title: Product quality choice in two-echelon supply chains under post-sale liability: insights from wholesale price contracts
Abstract: 
 This paper considers a two-echelon supply chain consisting of an upstream manufacturer (M) and a downstream Retailer (R) who transact intermediate products via a wholesale price contract. The supply chain provides an experience good to unit-demand consumers. M is liable for the harm caused by its products in a low quality state. A two-stage game model is built to describe how the supply chain operates. With the equilibrium and under certain assumptions, this paper finds that (1) in spite that post-sale product liability positively affects the wholesale price, M’s quality level, the contracted quantity and supply chain members’ profitability are independent of it; (2) when liability-related factors and M’s quality improvement efficiency change, the wholesale price serves as a medium for M and R to mutually share the ex ante expected liability cost, the demand loss caused by the ex ante expected consumer harm and the ex ante quality-improving cost; (3) in response to changes in liability-related factors, the quality performance is in conflict with the financial performance for both M and R, but this conflict disappears in the presence of a change in quality improvement efficiency. Managerial insights are also discussed.
Journal: International Journal of Production Research
Pages: 2556-2574
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1240382
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1240382
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Template-Type: ReDIF-Article 1.0
Author-Name: Chongqi Wu
Author-X-Name-First: Chongqi
Author-X-Name-Last: Wu
Author-Name: Kunpeng Li
Author-X-Name-First: Kunpeng
Author-X-Name-Last: Li
Author-Name: Tianqin Shi
Author-X-Name-First: Tianqin
Author-X-Name-Last: Shi
Title: Supply chain coordination with two-part tariffs under information asymmetry
Abstract: 
 Supply chain coordination literature indicates that two-part tariff contracts cannot coordinate a supply chain with a supplier and a retailer under information asymmetry, but can coordinate the channel under full information, while leaving the retailer zero profit. Motivated by the practice of Costco Business Centres, we incorporate customer heterogeneity, near-saturated retail market and asymmetric information into a stylised model. The retailer has the knowledge of customer heterogeneity while the supplier does not. The supplier, on the other hand, designs a menu of two-part tariffs for the retailer to choose from. We have found that two-part tariffs can coordinate the supply chain under asymmetric information, while leaving the retailer a positive profit. In addition, a one-size-fits-all two-part tariff can coordinate the supply chain at equilibrium, i.e. there is no need for the supplier to design different two-part tariffs for the retailer who may possess different types of information.
Journal: International Journal of Production Research
Pages: 2575-2589
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1240383
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1240383
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:9:p:2575-2589




Template-Type: ReDIF-Article 1.0
Author-Name: Gyusun Hwang
Author-X-Name-First: Gyusun
Author-X-Name-Last: Hwang
Author-Name: Jeongcheol Lee
Author-X-Name-First: Jeongcheol
Author-X-Name-Last: Lee
Author-Name: Jinwoo Park
Author-X-Name-First: Jinwoo
Author-X-Name-Last: Park
Author-Name: Tai-Woo Chang
Author-X-Name-First: Tai-Woo
Author-X-Name-Last: Chang
Title: Developing performance measurement system for Internet of Things and smart factory environment
Abstract: 
 To cope with large fluctuations in the demand of a commodity, it is necessary for the manufacturing system to have rapid reactive ability. This requirement may be secured by performance measurement. Although manufacturing companies have used information systems to manage performance, there has been the difficulty of capturing real-time data to depict real situations. The recent development and application of the Internet of Things (IoT) has enabled the resolution of this problem. In demonstration of the functionality of IoT, we developed an IoT-based performance model consistent with the ISA-95 and ISO-22400 standards, which define manufacturing processes and performance indicator formulas. The development comprised three steps: (1) Selection of the Key Performance Indicators of the Overall Equipment Effectiveness (OEE), and the development of an IoT-based production performance model, (2) Implementation of the IoT-based architecture and performance measurement process using Business Process Modelling and (3) Validation of the proposed model through virtual factory simulation. We investigated the effect of the IoT-workability on the OEE, based on the final results of the simulation, both for the planned and actual productions. The simulation results showed that the proposed model represented the timestamp data acquired by IoT and captured the entire production process, thus enabling the determination of real-time performance indicators.
Journal: International Journal of Production Research
Pages: 2590-2602
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1245883
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1245883
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Template-Type: ReDIF-Article 1.0
Author-Name: Imen Ben Mohamed
Author-X-Name-First: Imen
Author-X-Name-Last: Ben Mohamed
Author-Name: Walid Klibi
Author-X-Name-First: Walid
Author-X-Name-Last: Klibi
Author-Name: Olivier Labarthe
Author-X-Name-First: Olivier
Author-X-Name-Last: Labarthe
Author-Name: Jean-Christophe Deschamps
Author-X-Name-First: Jean-Christophe
Author-X-Name-Last: Deschamps
Author-Name: Mohamed Zied Babai
Author-X-Name-First: Mohamed Zied
Author-X-Name-Last: Babai
Title: Modelling and solution approaches for the interconnected city logistics
Abstract: 
 Achieving a sustainable delivery of goods in urban areas has become a challenging task for service providers and logistics managers. Under this context, the physical internet (PI) Manifesto offers through its emergent concept of interconnected city logistics (ICL) a solution toward a more sustainable transportation of PI containers within cities. In this article, we explore the operational urban transportation problem of PI containers under ICL considerations. For this variant, built on the multiplicity of urban logistics centres and their interconnection, a comprehensive modelling approach is proposed to include key features such as multiple time periods, multi-zone urban coverage, heterogeneous fleets, multi-trip and multi-hub pickups, and delivery constraints. In order to deal with solvability issues encountered with realistic instances of the problem, a heuristic solution approach is developed. This is done with the objective to come up with solutions offering the best trade-offs between economic and ecological attributes within a short computational time. To validate the approach, a realistic set of instances is built with data inspired from city freight movements in an urban area in France. Using these experiments, the solvability of the model and the performance of our heuristic approach are discussed and managerial insights are derived.
Journal: International Journal of Production Research
Pages: 2664-2684
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1267412
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1267412
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanyan Yang
Author-X-Name-First: Yanyan
Author-X-Name-Last: Yang
Author-Name: Shenle Pan
Author-X-Name-First: Shenle
Author-X-Name-Last: Pan
Author-Name: Eric Ballot
Author-X-Name-First: Eric
Author-X-Name-Last: Ballot
Title: Innovative vendor-managed inventory strategy exploiting interconnected logistics services in the Physical Internet
Abstract: 
 Traditional supply chain networks are often designed in the interests of a company. Once the network has been defined, the storage and distribution of goods are usually fixed and restricted within the network. This is assumed to be an inherent limit of current inventory control research. Instead of specialised hierarchical storage networks, this paper proposes an innovative vendor-managed inventory strategy exploiting the Physical Internet (PI), which is an open, universal, interconnected logistics system. In such a system, facilities and means of transport are shared and can be allocated according to demands of users. As a result, the PI allows users to stock anywhere in the network and also provides open multisourcing options for orders with on-demand warehousing services within the PI. Inventory decisions can be made dynamically by each player to minimise networkwide inventory levels. A non-linear, simulation-based optimisation model was developed for the vendors’ inventory decision-making when confronted with stochastic demands. A metaheuristic using simulated annealing was applied to solve the problem, and then, the optimised inventory decisions were validated using simulation. The results suggest that the proposed PI inventory model can reduce the total logistics cost while maintaining a comparable or better level of end customers’ services.
Journal: International Journal of Production Research
Pages: 2685-2702
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1275871
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1275871
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehran Fazili
Author-X-Name-First: Mehran
Author-X-Name-Last: Fazili
Author-Name: Uday Venkatadri
Author-X-Name-First: Uday
Author-X-Name-Last: Venkatadri
Author-Name: Pemberton Cyrus
Author-X-Name-First: Pemberton
Author-X-Name-Last: Cyrus
Author-Name: Mahdi Tajbakhsh
Author-X-Name-First: Mahdi
Author-X-Name-Last: Tajbakhsh
Title: Physical Internet, conventional and hybrid logistic systems: a routing optimisation-based comparison using the Eastern Canada road network case study
Abstract: 
 The Physical Internet (PI) logistics system is an innovative logistics concept that has been gathering a lot of attention lately. This system consists of open, modular and shared containers and transit hubs to move goods globally. The purpose of this paper is to compare the performance of PI with regard to the conventional (CO) logistics system in order to quantify the advantages and disadvantages of PI from a truck and driver routing perspective with an explicit constraint on maximum return time for drivers. The comparison presented in this work is carried out through Monte-Carlo simulation within a sequential three-phase optimisation framework. Based on our analysis, PI reduces driving distance (and time), GHG (greenhouse gas) emissions and the social cost of truck driving. On the other hand, it increases the number of container transfers within the PI logistics centres. This insight is a contribution of the paper and reinforces the current literature on PI. The other main contribution of the paper is a validation of the claim that the number of drivers who can go back home at the end of a work day remains consistently high in PI, regardless of the traffic level.
Journal: International Journal of Production Research
Pages: 2703-2730
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2017.1285075
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1285075
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:9:p:2703-2730




Template-Type: ReDIF-Article 1.0
Author-Name: Shenle Pan
Author-X-Name-First: Shenle
Author-X-Name-Last: Pan
Author-Name: Eric Ballot
Author-X-Name-First: Eric
Author-X-Name-Last: Ballot
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Author-Name: Benoit Montreuil
Author-X-Name-First: Benoit
Author-X-Name-Last: Montreuil
Title: Physical Internet and interconnected logistics services: research and applications
Journal: International Journal of Production Research
Pages: 2603-2609
Issue: 9
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2017.1302620
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1302620
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Template-Type: ReDIF-Article 1.0
Author-Name: Ivan Svetunkov
Author-X-Name-First: Ivan
Author-X-Name-Last: Svetunkov
Author-Name: Fotios Petropoulos
Author-X-Name-First: Fotios
Author-X-Name-Last: Petropoulos
Title: Old dog, new tricks: a modelling view of simple moving averages
Abstract: 
 Simple moving average (SMA) is a well-known forecasting method. It is easy to understand and interpret and easy to use, but it does not have an appropriate length selection mechanism and does not have an underlying statistical model. In this paper, we show two statistical models underlying SMA and demonstrate that the automatic selection of the optimal length of the model can easily be done using this finding. We then evaluate the proposed model on a real data-set and compare its performance with other popular simple forecasting methods. We find that SMA performs better both in terms of point forecasts and prediction intervals in cases of normal and cumulative values.
Journal: International Journal of Production Research
Pages: 6034-6047
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2017.1380326
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1380326
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Template-Type: ReDIF-Article 1.0
Author-Name: Ernest Benedito
Author-X-Name-First: Ernest
Author-X-Name-Last: Benedito
Author-Name: Albert Corominas
Author-X-Name-First: Albert
Author-X-Name-Last: Corominas
Title: Embodying decisions on work shifts into strategic manufacturing capacity planning
Abstract: 
 In spite of the obvious impact that decisions on workforce planning have on the capacity of a production system, they are rarely mentioned in strategic capacity planning literature. This paper analyses the implications of embodying decisions on work shifts in strategic capacity planning and proposes a mathematical programming model that allows treating any type of relationship between the intensity in the use of the production equipment and maintenance and variable production costs. A computational experiment shows that the model can be solved in acceptable computing times for moderate values of the number of types of equipment and of work shifts. Using the model, the optimal solutions for diverse scenarios are presented and compared with those obtained under the assumption that the work shifts must be kept invariable over the entire horizon.
Journal: International Journal of Production Research
Pages: 6135-6146
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2017.1421325
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421325
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Template-Type: ReDIF-Article 1.0
Author-Name: Haijun Wang
Author-X-Name-First: Haijun
Author-X-Name-Last: Wang
Author-Name: Shanling Li
Author-X-Name-First: Shanling
Author-X-Name-Last: Li
Author-Name: Jianwen Luo
Author-X-Name-First: Jianwen
Author-X-Name-Last: Luo
Title: Optimal markdown pricing for holiday basket with customer valuation
Abstract: 
 We consider a problem in which a retailer who plans to sell holiday basket during a holiday and needs to determine an optimal markdown price for remaining inventory after the holiday. The retailer also needs to determine an optimal inventory level to maximise the total expected profit during and after the holiday. We assume customers’ total intended spending on the holiday basket is a random variable that is realised during the holiday and customers purchase the holiday basket based on their valuations. We formulate the problem as a two-stage stochastic programming model with the first-stage decision determining an optimal inventory level and the second stage determining an optimal markdown price based on remaining inventory and the realisation of customers’ total intended spending. We show that we can derive a unique optimal markdown price corresponding to the realisation of customers’ total intended spending. At last, we provide numerical results to illustrate the impact of holiday price of the basket, the highest customer valuation as well as the salvage value of the basket, all of which affect the retailer’s decision on markdown price.
Journal: International Journal of Production Research
Pages: 5982-5996
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1427902
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1427902
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Template-Type: ReDIF-Article 1.0
Author-Name: Hye-Young Joo
Author-X-Name-First: Hye-Young
Author-X-Name-Last: Joo
Author-Name: Yong-Won Seo
Author-X-Name-First: Yong-Won
Author-X-Name-Last: Seo
Author-Name: Hokey Min
Author-X-Name-First: Hokey
Author-X-Name-Last: Min
Title: Examining the effects of government intervention on the firm’s environmental and technological innovation capabilities and export performance
Abstract: 
 Considering our living environments directly affect the quality of our daily lives, many believe that the environment should only be safeguarded by the mighty hands of the government instead of leaving the environmental stewardship in the hands of profit-making private enterprises. As such, the government often intervenes with the way private enterprises conduct business through many different forms of environmental regulations and business incentives. However, the efficiency and effectiveness of such government intervention are still unknown and unclear at best. Many sceptics still think that economic growth and environmental protection are in conflict with each other and subsequently the firm’s environmental performance and export performance cannot be achieved simultaneously even with active government intervention over the firm’s environmental management. To clarify this misconception, this paper aims to examine whether government intervention leads to the affected firm’s both environmental and export performance (export sales performance). In addition, it investigates whether government intervention enhances the firm’s environmental and technological innovation capabilities and thus makes the firm more competitive in the global marketplace. In so doing, this paper verifies the ecological modernisation theory and institutional theory using the empirical analysis of the survey data obtained from the Korean manufacturing industry.
Journal: International Journal of Production Research
Pages: 6090-6111
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1430902
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1430902
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Template-Type: ReDIF-Article 1.0
Author-Name: Songyue Zheng
Author-X-Name-First: Songyue
Author-X-Name-Last: Zheng
Author-Name: Yi Liu
Author-X-Name-First: Yi
Author-X-Name-Last: Liu
Author-Name: Yuan Li
Author-X-Name-First: Yuan
Author-X-Name-Last: Li
Author-Name: Liang Wang
Author-X-Name-First: Liang
Author-X-Name-Last: Wang
Title: Conjunct roles of client and vendor control in offshore-outsourced project performance
Abstract: 
 This study explores the conjunct roles of a series of formal and informal control mechanisms exerted, respectively, by client and vendor in offshore-outsourced project performance. Using a sample of 203 offshore projects executed by vendors in China, the results indicate that client process control enhances (or complements) the effect of vendor outcome control, yet impairs (or substitutes) the effect of vendor process control. Conversely, client outcome control enhances (or complements) the effect of vendor process control, yet impairs (or substitutes) the effect of vendor outcome control. Further, for the two informal control mechanisms, the results indicate that client relational control enhances (or complements) the effects of both vendor process and outcome control, whereas vendor clan control only enhances (or complements) the effect of client outcome control on offshore-outsourced project performance. These findings not only contribute new insights for the organisational control and the outsourcing literature, but also provide managerial guidance for client and vendor managers on how to exert and fine-tune their control mechanisms to promote project performance.
Journal: International Journal of Production Research
Pages: 6240-6258
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1433340
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1433340
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiang Chu
Author-X-Name-First: Xiang
Author-X-Name-Last: Chu
Author-Name: Qiuyan Zhong
Author-X-Name-First: Qiuyan
Author-X-Name-Last: Zhong
Author-Name: Xue Li
Author-X-Name-First: Xue
Author-X-Name-Last: Li
Title: Reverse channel selection decisions with a joint third-party recycler
Abstract: 
 In recent years, Internet-based firms have been increasingly engaged in recycling used products, taking advantage of economies of scale by serving a number of manufacturers. However, most studies on the recycling channel of remanufacturing to date only consider the case of a single manufacturer in a closed-loop supply chain. To address this gap, we develop a Stackelberg game model and show that the joint third-party (J3P) collection mode serving multiple manufacturers may outperform individual retailer- and manufacturer-managed modes, as opposed to existing findings considering a single manufacturer. It is optimal for manufacturers to authorise a large-scale J3P to collect used products. In addition, we show that the J3P can design a two-part tariff contract for the manufacturers to overcome the double marginalisation and collective action problems in decentralised supply chains. Our results provide guidance for enterprises and the government on recycling decisions in the era of a network economy.
Journal: International Journal of Production Research
Pages: 5969-5981
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1442944
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1442944
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Template-Type: ReDIF-Article 1.0
Author-Name: Alireza Faraz
Author-X-Name-First: Alireza
Author-X-Name-Last: Faraz
Author-Name: Nada Sanders
Author-X-Name-First: Nada
Author-X-Name-Last: Sanders
Author-Name: Zach Zacharia
Author-X-Name-First: Zach
Author-X-Name-Last: Zacharia
Author-Name: Markus Gerschberger
Author-X-Name-First: Markus
Author-X-Name-Last: Gerschberger
Title: Monitoring type B buyer–supplier relationships
Abstract: 
 The ability to monitor supplier performance is a critical capability for maintaining strong buyer–supplier relationships. Monitoring type B suppliers is especially challenging as they are not as clearly defined as either type A, with strong strategic partnerships, or type C, with little partnership. This research develops a non-parametric multivariate Hoteling’s T
2 control chart to capture the in-control state of a dyadic relationship (Phase I), and show how it would be developed based on survey data of buyer–supplier relationship attributes. Modelling the satisfactory level of dyadic relationship performance is very useful for identifying when the relationship begins to move away from the desired state. We then use the designed control chart to monitor the relationship between dyads over time to determine if any unusual behaviour has occurred (Phase II) and illustrate its implementation through a case study from the auto industry. This research illustrates how supply chain managers can secure and improve their supply chain performance by monitoring and maintaining strong relationships with their partners. The proposed method extends the existing SPC tools to effectively manage Type B buyer–supplier relationships.
Journal: International Journal of Production Research
Pages: 6225-6239
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1444285
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1444285
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Template-Type: ReDIF-Article 1.0
Author-Name: Luiza Ribeiro Alves Cunha
Author-X-Name-First: Luiza Ribeiro Alves
Author-X-Name-Last: Cunha
Author-Name: Ana Paula Santos Delfino
Author-X-Name-First: Ana Paula Santos
Author-X-Name-Last: Delfino
Author-Name: Kamila Almeida dos Reis
Author-X-Name-First: Kamila Almeida
Author-X-Name-Last: dos Reis
Author-Name: Adriana Leiras
Author-X-Name-First: Adriana
Author-X-Name-Last: Leiras
Title: Economic production quantity (EPQ) model with partial backordering and a discount for imperfect quality batches
Abstract: 
 Economic production quantity (EPQ) models are traditionally used in operations management. Despite the large number of papers that describe the models, the classic EPQ model does not consider either imperfect quality batches or shortages. However, some industries may be able to sell imperfect items for a lower price, reducing the total production cost. This paper proposes an EPQ model with partial backordering and discount for imperfect quality batches and an algorithm that returns optimal values for the problem. From a numerical example, it is possible to analyse how the changes in the variables affect each part of the total cost function, which provides a useful tool for strategic decision-making. We conclude that it is better to sell imperfect items as soon as possible because the savings in holding costs results in a total cost reduction. It is more profitable for the producer to have planned shortages considering that some costumers are willing to wait. Furthermore, the reduction of the goodwill cost does not necessarily reduce the total cost.
Journal: International Journal of Production Research
Pages: 6279-6293
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1445878
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1445878
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Template-Type: ReDIF-Article 1.0
Author-Name: Boray Huang
Author-X-Name-First: Boray
Author-X-Name-Last: Huang
Author-Name: Andy Wu
Author-X-Name-First: Andy
Author-X-Name-Last: Wu
Author-Name: David Chiang
Author-X-Name-First: David
Author-X-Name-Last: Chiang
Title: Supporting small suppliers through buyer-backed purchase order financing
Abstract: 
 This paper considers a creditworthy buyer who has two supplies: a low-cost but capital-constrained unreliable SME (small and medium-sized enterprise), and a high-cost but reliable backup source. The buyer may consider a novel financing mechanism named BPOF (buyer-backed purchase order financing) for supporting the SME indirectly. Under the BPOF scheme, the buyer provides partial or full guarantee to share the bank’s financing risk thus facilitate the SME’s loan application. To balance the risk with the benefit due to BPOF, we specify the conditions under which BPOF works and identify the properties of the buyer’s optimal strategy for sourcing and guaranteeing jointly. Generally speaking, a rational buyer’s guarantee should positively correlate to her product margins and the suppliers’ reliability. Finally, we claim when the risk-adjusted wholesale price is sufficiently low, dual financing (BPOF and subsidy) should be suggested.
Journal: International Journal of Production Research
Pages: 6066-6089
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1454614
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1454614
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Template-Type: ReDIF-Article 1.0
Author-Name: Stefania Boscari
Author-X-Name-First: Stefania
Author-X-Name-Last: Boscari
Author-Name: Thomas Bortolotti
Author-X-Name-First: Thomas
Author-X-Name-Last: Bortolotti
Author-Name: Torbjørn H. Netland
Author-X-Name-First: Torbjørn H.
Author-X-Name-Last: Netland
Author-Name: Nick Rich
Author-X-Name-First: Nick
Author-X-Name-Last: Rich
Title: National culture and operations management: a structured literature review
Abstract: 
 National culture has received a substantial amount of interest in the operations management literature. We present the first structured review of articles studying national culture in operations management. Our search returned 51 papers published in ten leading journals between 2000 and 2017. We sort and analyse the papers according to three focus areas of operations management (strategy, execution and improvement). We also analyse the papers according to whether they address the relevance of national culture, the impact of national culture or the actions managers can use to manage or mitigate the effects of national culture. We find that national culture appears as a relevant variable in all focus areas of operations management research but that the direction and strength of its impact remain undetermined. Only a handful of papers address how managers can actively deal with challenges related to national culture. We propose a research agenda and a guiding framework for future research.
Journal: International Journal of Production Research
Pages: 6314-6331
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1461275
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1461275
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Template-Type: ReDIF-Article 1.0
Author-Name: Sricharan Chirra
Author-X-Name-First: Sricharan
Author-X-Name-Last: Chirra
Author-Name: Dinesh Kumar
Author-X-Name-First: Dinesh
Author-X-Name-Last: Kumar
Title: Analysis of SCF under sales promotional schemes: an application of interpretive structural modelling approach
Abstract: 
 In the competitive market of today, supply chain flexibility (SCF) plays crucial way to address various supply chain uncertainties. But, in diverse situations, the supply chain needs different types of flexibilities. This paper analyses the flexibility of an automobile supply chain under sales promotional schemes (SPS) to meet the demand uncertainty. Taking the opinion of supply chain experts from automobile original equipment manufacturers (OEM’s), 14 SCF strategies have been identified and then using interpretive structural modelling (ISM) on the conducted survey, their interrelationships are established and a hierarchical model is developed. MICMAC analysis is done to classify the strategies into four categories viz. autonomous, dependent, linkage and independent strategies, which are based on their driving and dependence powers. Sensitivity analysis has been conducted to check the stability of the model. The thorough exposition of the model presents a handful of insights to supply chain managers to know the most important strategies affecting each other. The study helps in bridging the SCF with SPS, a huge gap existing in the literature.
Journal: International Journal of Production Research
Pages: 6015-6033
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1463474
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1463474
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Template-Type: ReDIF-Article 1.0
Author-Name: Ammar Mohamed Aamer
Author-X-Name-First: Ammar Mohamed
Author-X-Name-Last: Aamer
Title: Outsourcing in non-developed supplier markets: a lean thinking approach
Abstract: 
 The benefits organisations can gain from outsourcing include cost savings and higher levels of innovation. On the other hand, outsourcing drawbacks include potential operations and performance issues such as capability and capacity problems. Some large organisations are pursuing the practice of outsourcing, more specifically, targeting global outsourcing from developing and low-wage countries. However, the perception of expected cost saving benefits when outsourcing to low-wage countries does not always reflect reality. A number of companies have failed to achieve the expected cost savings in sourcing from low-wage countries due to operational-level capability. The objective of this study is to develop an extended evaluation method that takes into account operational-level influence factors, in addition to the procurement factors, in the context of non-developed supplier markets. Our extended evaluation method of potential suppliers addressed the paradigm of ‘standard industry recipes’, by encompassing operational-level influence factors and integrating supplier value stream analysis into the evaluation and selection process of outsourcing. A survey was distributed to 369 international manufacturers. Operational levels were categorised into seven latent constructs: Customer Service/Sales, Purchasing, Production Planning and Control, Manufacturing Engineering, Shop Floor and Quality Control, Receiving and Shipping. Structural Equation Modelling (SEM) confirmed the seven constructs, but measuring items were reduced from 39 to 23 significant observed measuring items, compromising the supplier selection framework. Our proposed framework will help practitioners make better informed decisions in outsourcing from non-developed supplier markets.
Journal: International Journal of Production Research
Pages: 6048-6065
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1465609
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1465609
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingxian Chen
Author-X-Name-First: Jingxian
Author-X-Name-Last: Chen
Author-Name: Liang Liang
Author-X-Name-First: Liang
Author-X-Name-Last: Liang
Author-Name: Dong-qing Yao
Author-X-Name-First: Dong-qing
Author-X-Name-Last: Yao
Title: Pre-positioning of relief inventories: a multi-product newsvendor approach
Abstract: 
 Inventory pre-positioning is critical to quickly and efficiently responding to potential disasters. This paper considers a NPO (a relief agent) that requires stockpiling multiple products for responding multiple potential disaster events. By employing the multi-product newsvendor (MPNV) approach, this paper establishes a multiple relief materials’ storage model that aims to minimise the expected total cost of the NPO. Our model acknowledges that the occurrence of a disaster, the demand after a disaster and the donation after a disaster are uncertain. Given the no-budget constraint, this paper shows the implicit conditions that determine the optimal solutions; for the case with a budget constraint, the paper develops a two-binary iterative approach to solve the model with a budget constraint. Numerical examples are conducted to investigate the impacts of model parameters. The paper further proposes a flexible storage policy, in which the NPO and the supplier jointly stockpile relief materials. The optimal solution of the case with the flexible stockpiling policy is also characterised. Moreover, this paper shows the policy implementation can simultaneously increase the performance of the NPO and the supplier; and both players of the supply chain prefer that the supplier solely holds all inventory.
Journal: International Journal of Production Research
Pages: 6294-6313
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1470342
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1470342
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Template-Type: ReDIF-Article 1.0
Author-Name: Gunjan Yadav
Author-X-Name-First: Gunjan
Author-X-Name-Last: Yadav
Author-Name: Sachin Kumar Mangla
Author-X-Name-First: Sachin Kumar
Author-X-Name-Last: Mangla
Author-Name: Sunil Luthra
Author-X-Name-First: Sunil
Author-X-Name-Last: Luthra
Author-Name: Suresh Jakhar
Author-X-Name-First: Suresh
Author-X-Name-Last: Jakhar
Title: Hybrid BWM-ELECTRE-based decision framework for effective offshore outsourcing adoption: a case study
Abstract: 
 The present study seeks to develop a decision framework of enabler to help managers in offshore outsourcing adoption by focusing on the relevant enablers and their intensities. A hybrid Best Worst Method (BWM) – ELimination and Choice Expressing REality approach is used to test the applicability of developed offshore outsourcing focused enabler’s across four automotive business organisations in India and the adoption score of framework among case organisations is evaluated too. The intensity of offshore outsourcing focused enablers is analysed through BWM and the ranking of organisations and adoption index scores are computed through ELimination and Choice Expressing REality method. The developed framework possesses high adoption rate in offshore outsourcing initiatives across the case organisations. Findings of the study reveal that among the main enablers; managerial and strategic enabler holds the highest weight followed by technological enablers and organisational enablers. This study further presents the sensitivity analysis to check the robustness of developed framework by conducting experiments in different conditions. This research work will facilitate managers and professionals involved in practising offshore outscoring initiatives and results in higher cost advantages on labour and raw material, increased economies of scale, and higher sustainable business development.
Journal: International Journal of Production Research
Pages: 6259-6278
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1472406
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1472406
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Template-Type: ReDIF-Article 1.0
Author-Name: Ashley Y. Metcalf
Author-X-Name-First: Ashley Y.
Author-X-Name-Last: Metcalf
Author-Name: Marco Habermann
Author-X-Name-First: Marco
Author-X-Name-Last: Habermann
Author-Name: Timothy D. Fry
Author-X-Name-First: Timothy D.
Author-X-Name-Last: Fry
Author-Name: James K. Stoller
Author-X-Name-First: James K.
Author-X-Name-Last: Stoller
Title: The impact of quality practices and employee empowerment in the performance of hospital units
Abstract: 
 Healthcare is a unique services environment with increasing demand for services coupled with widely diverse patient needs. In addition, hospitals are under increased pressure to provide quality care yet simultaneously decrease associated costs. This study examines how the use of quality practices and employee empowerment impact hospital unit outcomes. Specifically, the sociotechnical theory is used to explain the relationship of quality practices and employee empowerment in respiratory care services. Utilising data from 101 different hospital units, survey responses from managers and physicians within the same hospital units are used to test the impact on quality and cost of care performance metrics via path modelling. The results show the social side of improvement programs, i.e. employee empowerment, may be a critical component to true quality improvement in hospital units. Furthermore, while respiratory care managers feel that employee empowerment reduces costs of patient care, physicians felt that there was no impact on costs. The implications of these findings and differing perspectives are discussed.
Journal: International Journal of Production Research
Pages: 5997-6014
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1475763
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1475763
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Template-Type: ReDIF-Article 1.0
Author-Name: Mehdi Sharifyazdi
Author-X-Name-First: Mehdi
Author-X-Name-Last: Sharifyazdi
Author-Name: Kaustubh Anil Navangul
Author-X-Name-First: Kaustubh Anil
Author-X-Name-Last: Navangul
Author-Name: Amir Gharehgozli
Author-X-Name-First: Amir
Author-X-Name-Last: Gharehgozli
Author-Name: Marianne Jahre
Author-X-Name-First: Marianne
Author-X-Name-Last: Jahre
Title: On- and offshore prepositioning and delivery mechanism for humanitarian relief operations
Abstract: 
 Traditionally, international humanitarian organisations have used on-demand dispatch of disaster relief goods from regional logistics units (RLUs) for sudden onset disaster response. This paper investigates the improvements in efficiency and resilience of disaster relief operations by combining the existing method of onshore prepositioning of relief items in RLUs with offshore prepositioning of relief items on-board vessels and at seaport terminals. The problem is formulated as a linear programming model that incorporates different logistical costs, including inventory cost, replenishment cost, and transportation cost, to find the best combination of disaster relief methods. At the tactical level, the model determines how much and where disaster relief items need to be prepositioned. At the operational level, the model addresses how much and by which mode of transport the disaster relief items need to be transported to disaster points. The model is tested on 16 major disasters in Southeast Asia. The main finding is that offshore prepositioning can contribute to cost reduction and resilience without compromising on the speed or the scale of the response. The results also suggest that the benefits depend on the duration of the disaster emergency period and the ratio of offshore storage cost to onshore storage cost.
Journal: International Journal of Production Research
Pages: 6164-6182
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1477260
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1477260
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:18:p:6164-6182




Template-Type: ReDIF-Article 1.0
Author-Name: Zied Hajej
Author-X-Name-First: Zied
Author-X-Name-Last: Hajej
Author-Name: Nidhal Rezg
Author-X-Name-First: Nidhal
Author-X-Name-Last: Rezg
Author-Name: Ali Gharbi
Author-X-Name-First: Ali
Author-X-Name-Last: Gharbi
Title: Quality issue in forecasting problem of production and maintenance policy for production unit
Abstract: 
 In this study, we consider an unreliable deteriorating production system that produces conforming and non-conforming products to satisfy a random demand under a given service level and during a finite horizon. The production system is subjected to a failure-prone machine. The quality of the produced products is affected by the machine deterioration since the rate of defectives increases as the deterioration increases. Preventive maintenance actions can be piloted on the production system to reduce the influence of deterioration and the defective rate. A joint control policy is based on a stochastic production and maintenance planning problem with goals to determine, firstly, the economic plan of production and secondly, the optimal maintenance strategy. The proposed jointly optimisation minimises the total cost of production, inventory, maintenance and defectives. A failure rate and quality relationship are defined to show the influence of the production rates variation on the failures rate as well as on the defective rate. A numerical example and an industrial case study are adopted to illustrate the proposed approach and a sensitivity analysis to validate the jointly optimisation.
Journal: International Journal of Production Research
Pages: 6147-6163
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1478150
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1478150
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Template-Type: ReDIF-Article 1.0
Author-Name: Timm Ziarnetzky
Author-X-Name-First: Timm
Author-X-Name-Last: Ziarnetzky
Author-Name: Lars Mönch
Author-X-Name-First: Lars
Author-X-Name-Last: Mönch
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Title: Rolling horizon, multi-product production planning with chance constraints and forecast evolution for wafer fabs
Abstract: 
 In this paper, we study production planning models for semiconductor wafer fabrication facilities (wafer fabs) that consider both safety stocks at the finished goods inventory level and workload-dependent lead times. The evolution of demand forecasts over time follows the multiplicative Martingale Model of Forecast Evolution (MMFE) for multiple products and is incorporated into the planning models via shortfall-based chance constraints, permitting the simultaneous determination of production quantities and safety stocks. We study two variants of this formulation, one that considers forecast updates and one that does not. A planning model with workload-dependent lead times that does not consider safety stocks is used for comparison. The performance of the planning models is assessed in a rolling horizon environment using a simulation model of a scaled-down wafer fab. We find that the chance-constrained model with forecast updates outperforms the one without forecast updates with respect to expected service level and profit. Both chance-constrained models outperform the model without safety stocks. These results indicate that considering forecast evolution in production planning models can lead to improved performance by exploiting the advance demand information provided by the forecast updates.
Journal: International Journal of Production Research
Pages: 6112-6134
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1478461
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1478461
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian-Gang Peng
Author-X-Name-First: Jian-Gang
Author-X-Name-Last: Peng
Author-Name: Guang Xia
Author-X-Name-First: Guang
Author-X-Name-Last: Xia
Author-Name: Bao-Qun Sun
Author-X-Name-First: Bao-Qun
Author-X-Name-Last: Sun
Author-Name: Shao-Jie Wang
Author-X-Name-First: Shao-Jie
Author-X-Name-Last: Wang
Title: Systematical decision-making approach for quality function deployment based on uncertain linguistic term sets
Abstract: 
 A systematical decision-making approach is constructed for quality function deployment (QFD) in uncertain linguistic situations. The mathematical expression and operation of linguistic terms play important roles in the proposed approach in terms of customer requirements (CRs) and design requirements (DRs) in QFD. First, hesitant fuzzy linguistic term sets are designed to conveniently express uncertain linguistic terms and compute with words after the data derived from customers are pretreated and integrated in the decision-making process. Second, the tolerance deviation is defined to restrict innovatively the deviation range of fuzzy linguistic terms in the assessment stage of relative importance for CRs. Third, information entropy is originally designed to determine the final importance of DRs. Moreover, an empirical study on the research project called vortex recoil hydraulic retarder is conducted to demonstrate the performance of the systematical decision-making approach. The proposed approach can be applied to a wide variety of new product development problems in uncertainty settings.
Journal: International Journal of Production Research
Pages: 6183-6200
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1478462
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1478462
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Template-Type: ReDIF-Article 1.0
Author-Name: Hongfu Huang
Author-X-Name-First: Hongfu
Author-X-Name-Last: Huang
Author-Name: Yong He
Author-X-Name-First: Yong
Author-X-Name-Last: He
Author-Name: Dong Li
Author-X-Name-First: Dong
Author-X-Name-Last: Li
Title: Coordination of pricing, inventory, and production reliability decisions in deteriorating product supply chains
Abstract: 
 In this article, we study a two-level supply chain model for deteriorating items, in which the supplier’s production system is unreliable and the retailer’s demand is price-sensitive. The supplier’s production line may randomly shift from the in-control state to the out-of-control state. When the production line is in the out-of-control state, a proportion of the produced products will have bad quality. To mitigate the out-of-control risks, the supplier can improve the production line reliability by investing in high-quality machines, highly skilled workers, or advanced maintenance technologies. We start with the study of pricing and inventory problems concerning endogenous reliability in the integrated and decentralised scenario. To better illustrate the proposed models, two applicable algorithms are designed to determine the optimal production reliability, ordering quantity, and prices. Then, a cooperative reliability investment and revenue-sharing contract is proposed to coordinate the supply chain. Numerical examples and sensitivity analysis of the equilibrium strategies and coordinating results on key system parameters (e.g. deterioration rate, production rate, etc.) are given to verify the effectiveness of the contract, and meanwhile get some managerial insights.
Journal: International Journal of Production Research
Pages: 6201-6224
Issue: 18
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1480070
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1480070
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Template-Type: ReDIF-Article 1.0
Author-Name: Xu Luo
Author-X-Name-First: Xu
Author-X-Name-Last: Luo
Author-Name: Yongmin Yang
Author-X-Name-First: Yongmin
Author-X-Name-Last: Yang
Author-Name: Zhexue Ge
Author-X-Name-First: Zhexue
Author-X-Name-Last: Ge
Author-Name: Xisen Wen
Author-X-Name-First: Xisen
Author-X-Name-Last: Wen
Author-Name: Fengjiao Guan
Author-X-Name-First: Fengjiao
Author-X-Name-Last: Guan
Title: Maintainability-based facility layout optimum design of ship cabin
Abstract: 
 Maintainability of a mechanical system is one of the system design parameters that has a great impact in terms of ease of maintenance. In this paper, a methodology of facility layout optimum design for maintainability of a ship cabin is presented as a way to improve the efficiency and quality of maintainability design. The maintenance operating space, amount of hoisting, balance of cabin, distance requirement and personnel movement distance are all taken into account, and treated as objective functions. The mechanical functional constraints and some important layout experience are also considered and formulated as constraints. Thus, the mathematical model for maintainability layout combinatorial optimisation is constructed. According to the characteristics of maintainability-based facility layout problem, the particle swarm optimisation algorithm developed by Eberhart and Kennedy is modified to enhance the computational efficiency and solution accuracy. A hybrid position updating method is used to solve the optimisation problem with both continuous and discrete variables. The dynamic neighbourhood structure, dynamic inertia weight and adaptive mutation mode are modified to effectively solve the optimisation problem with multiple peak values. Finally, the methodology proposed is illustrated by simulation case and engineering application, and the results suggest that the methodology is effective.
Journal: International Journal of Production Research
Pages: 677-694
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.919416
File-URL: http://hdl.handle.net/10.1080/00207543.2014.919416
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:677-694




Template-Type: ReDIF-Article 1.0
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: Mohamad Y. Jaber
Author-X-Name-First: Mohamad Y.
Author-X-Name-Last: Jaber
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Title: Incorporating human factors in order picking planning models: framework and research opportunities
Abstract: 
 Order picking (OP) activities, essential to logistics operations, are laborious and time-intensive. Humans are central actors in the OP process and determine both OP effectiveness and efficiency. Many researchers have developed models for planning OP activities and increasing the efficiencies of such systems by suggesting different warehouse layouts, OP routes or storage assignments. These studies have, however, ignored workers’ characteristics, or human factors, suggesting that they cannot be substantiated, which led to only partially realistic results. This paper proposes a conceptual framework for integrating human factors into planning models of OP activities and hypothesises that doing so improves the performance of an OP system and workers’ welfare. The framework is based on a systematic literature review that synthesises findings documented in the OP and human factors literature. The results of the paper may assist researchers and practitioners in designing OP systems by developing planning models that help in enhancing performance and reducing long-term costs caused by work-related inefficiencies.
Journal: International Journal of Production Research
Pages: 695-717
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.919424
File-URL: http://hdl.handle.net/10.1080/00207543.2014.919424
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:695-717




Template-Type: ReDIF-Article 1.0
Author-Name: Mohsen Elhafsi
Author-X-Name-First: Mohsen
Author-X-Name-Last: Elhafsi
Author-Name: Li Zhi
Author-X-Name-First: Li
Author-X-Name-Last: Zhi
Author-Name: Herve Camus
Author-X-Name-First: Herve
Author-X-Name-Last: Camus
Author-Name: Etienne Craye
Author-X-Name-First: Etienne
Author-X-Name-Last: Craye
Title: An assemble-to-order system with product and components demand with lost sales
Abstract: 
 This paper studies a single end product assemble-to-order system serving both the demand of the end product and the individual components. Demands are assumed to form independent Poisson streams with different rates. Unsatisfied demand, both for the end product and for components, is assumed lost and thus incurs a per unit lost sale penalty. The end product is assembled from K distinct components each produced on a different production facility (or procured from independent suppliers). Production lead times are non-identical and are assumed to be independent and exponentially distributed. Produced components are held in stock in anticipation of future demands. The goal is to determine the optimal component production and inventory allocation policy. The optimal policy is characterised using a Markov Decision Process model. It is shown that, in addition to the state-dependent threshold type, the optimal policy exhibits counter-intuitive features which have not been observed in systems without components demand. In particular, for certain combinations of system parameters, the optimal inventory allocation policy switches priority as the inventory level of components changes. Furthermore, for a particular component k, as the inventory level of other components increases, the desirability of satisfying Component k demand decreases. Finally, because in general the optimal policy is fairly complicated and is difficult to obtain numerically, due to the curse of dimensionality of dynamic programming, three heuristic policies are proposed. Extensive numerical experiments indicate that the three heuristics perform very well compared to the optimal policy.
Journal: International Journal of Production Research
Pages: 718-735
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.920547
File-URL: http://hdl.handle.net/10.1080/00207543.2014.920547
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:718-735




Template-Type: ReDIF-Article 1.0
Author-Name: Talip Kellegöz
Author-X-Name-First: Talip
Author-X-Name-Last: Kellegöz
Author-Name: Bilal Toklu
Author-X-Name-First: Bilal
Author-X-Name-Last: Toklu
Title: A priority rule-based constructive heuristic and an improvement method for balancing assembly lines with parallel multi-manned workstations 
Abstract: 
 Assembly lines of big-size products such as buses, trucks and helicopters are very different from the lines studied in the literature. These products’ manufacturing processes have a lot of tasks most of which have long task times. Since traditional assembly line models including only one worker in each station (i.e. simple assembly lines) or at most two workers (two-sided assembly lines) may not be suitable for manufacturing these type of products, they need much larger shop floor for a number of stations and long product flow times. In this study, an assembly line balancing problem (ALBP) with parallel multi-manned stations is considered. Following the problem definition, a mixed integer programming formulation is developed. A detailed study of priority rules for simple ALBPs is also presented, and a new efficient constructive heuristic algorithm based on priority rules is proposed. In order to improve solutions found by the constructive heuristic, a genetic algorithm-based solution procedure is also presented. Benchmark instances in the literature are solved by using the proposed mathematical programming formulation. It has been seen that only some of the small-size instances can be solved optimally by this way. So the efficiency of the proposed heuristic method is verified in small-size instances whose optimal solutions are found. For medium- and big-size instances, heuristics’ results and CPU times are demonstrated. A comparative evaluation with a branch and bound algorithm that can be found in the literature is also carried out, and results are presented.
Journal: International Journal of Production Research
Pages: 736-756
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.920548
File-URL: http://hdl.handle.net/10.1080/00207543.2014.920548
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:736-756




Template-Type: ReDIF-Article 1.0
Author-Name: Xianhao Xu
Author-X-Name-First: Xianhao
Author-X-Name-Last: Xu
Author-Name: Guwen Shen
Author-X-Name-First: Guwen
Author-X-Name-Last: Shen
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Wei Huang
Author-X-Name-First: Wei
Author-X-Name-Last: Huang
Title: Travel time analysis for the double-deep dual-shuttle AS/RS
Abstract: 
 Comparing with traditional single-deep single-shuttle automated storage/retrieval systems, double-deep dual-shuttle AS/RS have the advantages of high space utilisation and more efficient, since less number of aisles and less empty travel of S/R machine. This warehousing systems have been developed for use in factories and distribution centres. In this paper, we first develop analytical models of quadruple command cycle to estimate the performance of such system, then taking the single shuttle and dual command cycle as the benchmark model, the potential improvement by dual shuttle has been analyzed, the results show that the efficiency of the system has a significant improvement using dual shuttle S/R machine. In addition, we have extended the proposed travel time to a special case that the double empty storage locations will take place and some management insights are given.
Journal: International Journal of Production Research
Pages: 757-773
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.921351
File-URL: http://hdl.handle.net/10.1080/00207543.2014.921351
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:757-773




Template-Type: ReDIF-Article 1.0
Author-Name: A. Baykasoglu
Author-X-Name-First: A.
Author-X-Name-Last: Baykasoglu
Author-Name: L. Gorkemli
Author-X-Name-First: L.
Author-X-Name-Last: Gorkemli
Title: Agent-based dynamic part family formation for cellular manufacturing applications
Abstract: 
 One of the main critique on cellular manufacturing and its algorithms is their inability to handle dynamics events, especially dynamic changes in part spectrum. Unfortunately, there are not many efforts in the literature to overcome this problem. Agent oriented computing provides a marvellous opportunity to handle dynamic problems and to provide effective solutions, if carefully and intelligently implemented. In this paper, we have proposed a novel agent-based clustering algorithm for part family formation in cellular manufacturing by considering dynamic demand changes. However, it is not easy to directly compare the performance of the proposed algorithm with the literature results as there is no benchmark for dynamic cell formation problems. We attempt to compare the performance of the present algorithm on static test problems by dynamically introducing parts in these data-sets to our algorithm. Many results have been presented on these static data-sets by utilising several heuristics, meta-heuristics and optimisation-based algorithms. Although the proposed algorithm is not an optimisation-based algorithm and its operation is directed to handle dynamic changes in the problem domain through negotiation, we have shown that it has ability to provide very good results which are comparable to the best known solutions.
Journal: International Journal of Production Research
Pages: 774-792
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.924634
File-URL: http://hdl.handle.net/10.1080/00207543.2014.924634
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:774-792




Template-Type: ReDIF-Article 1.0
Author-Name: Anurag Tiwari
Author-X-Name-First: Anurag
Author-X-Name-Last: Tiwari
Author-Name: Pei-Chann Chang
Author-X-Name-First: Pei-Chann
Author-X-Name-Last: Chang
Author-Name: M.K. Tiwari
Author-X-Name-First: M.K.
Author-X-Name-Last: Tiwari
Author-Name: Nevin John Kollanoor
Author-X-Name-First: Nevin John
Author-X-Name-Last: Kollanoor
Title: A Pareto block-based estimation and distribution algorithm for multi-objective permutation flow shop scheduling problem
Abstract: 
 Multi-objective flow shop scheduling plays a key role in real-life scheduling problem which attract the researcher attention. The primary concern is to find the best sequence for flow shop scheduling problem. Estimation of Distribution Algorithms (EDAs) has gained sufficient attention from the researchers and it provides prominent results as an alternate of traditional evolutionary algorithms. In this paper, we propose the pareto optimal block-based EDA using bivariate model for multi-objective flow shop scheduling problem. We apply a bivariate probabilistic model to generate block which have the better diversity. We employ the non-dominated sorting technique to filter the solutions. To check the performance of proposed approach, we test it on the benchmark problems available in OR-library and then we compare it with non-dominated sorting genetic algorithm-II (NSGA-II). Computational results show that pareto optimal BBEDA provides better result and better convergence than NSGA-II.
Journal: International Journal of Production Research
Pages: 793-834
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.933273
File-URL: http://hdl.handle.net/10.1080/00207543.2014.933273
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:793-834




Template-Type: ReDIF-Article 1.0
Author-Name: S. Ahn
Author-X-Name-First: S.
Author-X-Name-Last: Ahn
Author-Name: K. Yoon
Author-X-Name-First: K.
Author-X-Name-Last: Yoon
Author-Name: J. Park
Author-X-Name-First: J.
Author-X-Name-Last: Park
Title: A best-first branch and bound algorithm for the pallet-loading problem
Abstract: 
 In this study, we proposed an optimal algorithm for the pallet-loading problem (PLP). The PLP involves determining a loading pattern that can load the most identical boxes with rectangular shapes onto a large rectangular pallet. A new branch and bound algorithm, including a sub-algorithm that cheques the feasibility of the solutions, was proposed to solve a relaxed mathematical model, which did not consider the exact position of the boxes. Because the algorithm constructed the layout row-by-row and used effective branching strategies and improved bounds, it found a solution very quickly. Whenever a solution was obtained for the relaxed problem, another branch and bound algorithm (as a sub-algorithm) was used to check whether the solution obtained was feasible and to determine the resulting layout. The branching strategies in the sub-algorithm used the solution from the relaxation problem to quickly find the layout of the solution. The computational results demonstrated the superiority of the proposed algorithm. The algorithm proposed in this study solved all three million problems presented with an area ratio bound of less than 101 boxes in a minute, except for one. Solutions to all of the problems were obtained within 90 s, while other existing exact algorithms required more than an hour for some problems.
Journal: International Journal of Production Research
Pages: 835-849
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.935824
File-URL: http://hdl.handle.net/10.1080/00207543.2014.935824
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Template-Type: ReDIF-Article 1.0
Author-Name: Chieh-Yuan Tsai
Author-X-Name-First: Chieh-Yuan
Author-X-Name-Last: Tsai
Author-Name: Sheng-Hsiang Huang
Author-X-Name-First: Sheng-Hsiang
Author-X-Name-Last: Huang
Title: A data mining approach to optimise shelf space allocation in consideration of customer purchase and moving behaviours
Abstract: 
 A good shelf space allocation strategy can help customers easily find product items and dramatically increase store profit. Previous studies generally relied on the space elasticity formula to optimise space allocation models, but space elasticity requires estimates of many parameters, resulting in high costs and frequent errors in the mathematical models. In this study, a three-stage data mining method is proposed for solving the shelf space allocation problem with consideration of both customer purchase and moving behaviours. In the first stage, the customer’s purchasing behaviour is derived from records of previous transactions, while moving behaviour is collected through radio frequency identification systems. In the second stage, the A priori algorithm is applied to obtain frequent product association rules from purchase transactions. In addition, the UMSPL algorithm is adopted to derive high-utility mobile sequential patterns from customer mobile transaction sequences. In the third stage, all product items are classified as either major, minor or trivial according to a set of criteria. A Location preference evaluation procedure is then developed to calculate location preference if a minor item is placed at a given section of the store. Based on the location preference matrix, minor items are reassigned to optimal shelves. The experimental results show the proposed method can reassign items to suitable shelves and dramatically increase cross-selling opportunities for major and minor items.
Journal: International Journal of Production Research
Pages: 850-866
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.937011
File-URL: http://hdl.handle.net/10.1080/00207543.2014.937011
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Template-Type: ReDIF-Article 1.0
Author-Name: Naga Vamsi Krishna Jasti
Author-X-Name-First: Naga Vamsi Krishna
Author-X-Name-Last: Jasti
Author-Name: Rambabu Kodali
Author-X-Name-First: Rambabu
Author-X-Name-Last: Kodali
Title: Lean production: literature review and trends
Abstract: 
 The purpose of this paper is to perform the analysis of literature review of lean production (LP). The analysis involved studying 546 research articles published from 1988 to 2011 in selected 24 operations research journals. The articles are classified by: time distribution of articles, research methodology, research stream, authorship patterns, sector-wise focus, popular elements in lean literature, focus of the articles on lean waste, and implementation status and performance measurement of various existing frameworks/models. Then, the suggestions for the future scope of research possibilities and development are identified. The study provides a taxonomical and integrated review of articles, puts up perspective into the conceptualisation and various critical parameters for research. The findings include: increase in empirical approach research articles, need of applying lean principles in the field of product development and enterprise level areas, need of more interregional research collaborations, need of lean elements as group instead of individual element, need of avoiding seven lean wastes instead of specific waste and lack of testing and validation of the proposed frameworks/models by researchers. The study results shall help researchers, academicians and professionals to focus on the growth, pertinence and research developments in the LP system field.
Journal: International Journal of Production Research
Pages: 867-885
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.937508
File-URL: http://hdl.handle.net/10.1080/00207543.2014.937508
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:867-885




Template-Type: ReDIF-Article 1.0
Author-Name: M. Güray Güler
Author-X-Name-First: M. Güray
Author-X-Name-Last: Güler
Title: Coordinating decentralised assembly systems with random yield and random demand
Abstract: 
 We study coordination of assembly systems with random supplier yields and random customer demand. We propose four contracts which are combinations of well-known contracts in the literature and show that the contracts can coordinate the chain under forced compliance. Our contracts have less payment schemes than the existing contracts given for coordination of assembly systems in the literature. We show that arbitrary profit allocation between the levels of the supply chain (the manufacturer or the suppliers) is possible. We also provide sufficient conditions which enable arbitrary profit allocation among the suppliers and illustrate the profit allocation with numerical examples.
Journal: International Journal of Production Research
Pages: 886-896
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.939240
File-URL: http://hdl.handle.net/10.1080/00207543.2014.939240
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:886-896




Template-Type: ReDIF-Article 1.0
Author-Name: Gökçe Candan
Author-X-Name-First: Gökçe
Author-X-Name-Last: Candan
Author-Name: Harun Resit Yazgan
Author-X-Name-First: Harun Resit
Author-X-Name-Last: Yazgan
Title: Genetic algorithm parameter optimisation using Taguchi method for a flexible manufacturing system scheduling problem
Abstract: 
 The flexible manufacturing system (FMS) scheduling problem is one of the most difficult NP-hard combinatorial optimisation problems. The exact solution of an FMS scheduling problem cannot be found within a reasonable amount of time, even for small size problems. Therefore, a metaheuristic algorithm is required to solve such a problem. The objective of this study is to develop a genetic algorithm (GA) approach to minimise makespan of the scheduling problem. A Taguchi orthogonal array is proposed instead of a full factorial experimental design for determining the parameters of the GA. The effects of the GA parameters on the minimum makespan values are determined and an analysis of variance is performed to investigate significance factors on the results.
Journal: International Journal of Production Research
Pages: 897-915
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.939244
File-URL: http://hdl.handle.net/10.1080/00207543.2014.939244
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Template-Type: ReDIF-Article 1.0
Author-Name: Ehsan Ardjmand
Author-X-Name-First: Ehsan
Author-X-Name-Last: Ardjmand
Author-Name: Gary Weckman
Author-X-Name-First: Gary
Author-X-Name-Last: Weckman
Author-Name: Namkyu Park
Author-X-Name-First: Namkyu
Author-X-Name-Last: Park
Author-Name: Pooya Taherkhani
Author-X-Name-First: Pooya
Author-X-Name-Last: Taherkhani
Author-Name: Manjeet Singh
Author-X-Name-First: Manjeet
Author-X-Name-Last: Singh
Title: Applying genetic algorithm to a new location and routing model of hazardous materials
Abstract: 
 Nowadays – particularly in systems dealing with hazardous materials (HAZMAT) – in addition to minimising the cost of operations in facility location and routing problems, the risk of these operations is considered an important objective. In this paper, a new mathematical model for the location and routing in facilities and disposal sites is proposed. Also, the risk and cost of transporting goods from facilities to customers is considered. The model minimises weighted sum of the cost and risk by answering these questions: (1) where to open the facilities which produce HAZMAT; (2) where to open disposal sites; (3) to which facilities every customer should be assigned; (4) to which disposal site each facility should be assigned; (5) which route a facility should choose to serve the customers; and (6) which route a facility should choose to reach a disposal site. A novel GA is applied to solve the mathematical model. The results show the robustness of GA in terms of finding high-quality non-dominated solutions and running time.
Journal: International Journal of Production Research
Pages: 916-928
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.942010
File-URL: http://hdl.handle.net/10.1080/00207543.2014.942010
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Template-Type: ReDIF-Article 1.0
Author-Name: Peng Yang
Author-X-Name-First: Peng
Author-X-Name-Last: Yang
Author-Name: Lixin Miao
Author-X-Name-First: Lixin
Author-X-Name-Last: Miao
Author-Name: Zhaojie Xue
Author-X-Name-First: Zhaojie
Author-X-Name-Last: Xue
Author-Name: Lei Qin
Author-X-Name-First: Lei
Author-X-Name-Last: Qin
Title: Optimal storage rack design for a multi-deep compact AS/RS considering the acceleration/deceleration of the storage and retrieval machine
Abstract: 
 This paper explores the optimal storage rack design for a multi-deep compact Automated Storage and Retrieval System (AS/RS) considering the acceleration and deceleration of storage and retrieval (S/R) machine. The expected travel time under the single-command cycle and dual-command cycle for a random storage strategy is derived. Based on the travel time, the general models we propose calculate the optimal ratio between three dimensions that minimises the travel time under different speed profile scenarios. From the result, it is proven that the optimal storage rack design model in the constant speed situation can be treated as a special case of the model considering the acceleration and deceleration of S/R machine. Finally, this study investigates the effect of speed profile of S/R machine and fixing dimensions by various numerical experiments.
Journal: International Journal of Production Research
Pages: 929-943
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.942441
File-URL: http://hdl.handle.net/10.1080/00207543.2014.942441
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Template-Type: ReDIF-Article 1.0
Author-Name: Niloofar Shoaardebili
Author-X-Name-First: Niloofar
Author-X-Name-Last: Shoaardebili
Author-Name: Parviz Fattahi
Author-X-Name-First: Parviz
Author-X-Name-Last: Fattahi
Title: Multi-objective meta-heuristics to solve three-stage assembly flow shop scheduling problem with machine availability constraints
Abstract: 
 In this paper, a three-stage assembly flow shop scheduling problem with machine availability constraints is taken into account. Two objectives of minimising total weighted completion times (flow time) and minimising sum of weighted tardiness and earliness are simultaneously considered. To describe this problem, a mathematical model is presented. The problem is generalisation of three-machine flow shop scheduling problem and two-stage assembly flow shop scheduling problem. Since these problems are known to be NP-hard, the considered problem is also strongly NP-hard. Therefore, two multi-objective meta-heuristics are presented to efficiently solve this problem in a reasonable amount of time. Comprehensive computational experiments are performed to illustrate the performance of the presented algorithms.
Journal: International Journal of Production Research
Pages: 944-968
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.948575
File-URL: http://hdl.handle.net/10.1080/00207543.2014.948575
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Template-Type: ReDIF-Article 1.0
Author-Name: Ramesh Bollapragada
Author-X-Name-First: Ramesh
Author-X-Name-Last: Bollapragada
Author-Name: Saravanan Kuppusamy
Author-X-Name-First: Saravanan
Author-X-Name-Last: Kuppusamy
Author-Name: Uday S. Rao
Author-X-Name-First: Uday S.
Author-X-Name-Last: Rao
Title: Component procurement and end product assembly in an uncertain supply and demand environment
Abstract: 
 In this paper, we examine a multi-product, multi-component, procurement and assembly problem with both supply and demand uncertainties. We explicitly model the uncertainty using a stochastic program that facilitates procurement and assembly decisions. We present a stochastic linear programming model of the problem which we solve using its deterministic equivalent with a finite number of scenarios. We show that the systems performance, i.e. total cost, depends on the order lead time, L, and the assembly lead time Q, only through their sum L+Q$ L+Q $. We illustrate the impact of L+Q$ L+Q $ on system performance with numerical experiments. Also, we illustrate that, in some cases, increasing supplier capacity can worsen system performance. In addition, we identify the key cost drivers that need attention from managers in the manufacturing industry, when there is limited knowledge of future demand and component availability.
Journal: International Journal of Production Research
Pages: 969-982
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.951522
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951522
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:3:p:969-982




Template-Type: ReDIF-Article 1.0
Author-Name: Ningxuan Kang
Author-X-Name-First: Ningxuan
Author-X-Name-Last: Kang
Author-Name: Li Zheng
Author-X-Name-First: Li
Author-X-Name-Last: Zheng
Author-Name: Jingshan Li
Author-X-Name-First: Jingshan
Author-X-Name-Last: Li
Title: Analysis of multi-product manufacturing systems with arbitrary processing times
Abstract: 
 Multi-product systems with finite buffers and sequence-dependent set-up times are quite common in modern manufacturing industry. In practice, the distribution of machine processing time could be arbitrary, while in existing literature it is often assumed to follow an exponential distribution. In this paper, we develop an analytical method to study the multi-product manufacturing systems with non-exponential processing times. An embedded Markov chain model is constructed and two approximation methods, Gamma estimation and linear approximation, are proposed. The model is validated with high accuracy by numerical experiments and practical data from an automotive assembly system.
Journal: International Journal of Production Research
Pages: 983-1001
Issue: 3
Volume: 53
Year: 2015
Month: 2
X-DOI: 10.1080/00207543.2014.952363
File-URL: http://hdl.handle.net/10.1080/00207543.2014.952363
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Template-Type: ReDIF-Article 1.0
Author-Name: Stanislav Chankov
Author-X-Name-First: Stanislav
Author-X-Name-Last: Chankov
Author-Name: Marc-Thorsten Hütt
Author-X-Name-First: Marc-Thorsten
Author-X-Name-Last: Hütt
Author-Name: Julia Bendul
Author-X-Name-First: Julia
Author-X-Name-Last: Bendul
Title: Influencing factors of synchronization in manufacturing systems
Abstract: 
 Manufacturing systems exhibit two types of synchronisation phenomena: logistics and physics. Previous research has established synchronisation measures for both types and has shown that they are related to the due date performance. However, there is a lack of knowledge about the factors triggering synchronisation emergence as well as a holistic understanding of synchronisation effects on logistics performance. Thus, this research aims to further explore the relation between synchronisation, its influencing factors and its effect on logistics performance. Based on a profound literature review, we derive first hypotheses on the cause-and-effect-relationships between structural and dynamic properties of a manufacturing system and the emergence of logistics and physics synchronisation as well as logistics performance. By conducting a discrete-event simulation study on diverse manufacturing system types (line, flow shop and job shop production), we are able to test these hypotheses. We conclude that manufacturing network architecture as a structural property as well as processing time variability and system workload as dynamic properties may be exploited for an advanced and synchronisation-oriented manufacturing system design.
Journal: International Journal of Production Research
Pages: 4781-4801
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1400707
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1400707
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Template-Type: ReDIF-Article 1.0
Author-Name: Haichao Wang
Author-X-Name-First: Haichao
Author-X-Name-Last: Wang
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Author-Name: Youlong Lv
Author-X-Name-First: Youlong
Author-X-Name-Last: Lv
Author-Name: Xiaolong Zhang
Author-X-Name-First: Xiaolong
Author-X-Name-Last: Zhang
Author-Name: Guoqiang Guo
Author-X-Name-First: Guoqiang
Author-X-Name-Last: Guo
Author-Name: Wei Qin
Author-X-Name-First: Wei
Author-X-Name-Last: Qin
Author-Name: Xiaoxi Wang
Author-X-Name-First: Xiaoxi
Author-X-Name-Last: Wang
Title: Tool path optimisation method for large thin-wall part of spacecraft
Abstract: 
 Roughing tool path of panel machining, which is a bottleneck of spacecraft production, should be optimised rapidly to shorten process time. This problem has a large solution space, and surface quality should be taken into account. The decision variables are cavity machining order, feed point and cutting direction of each cavity. Our problem is presented as an asymmetric general travelling salesman problem (AGTSP). A cluster optimisation-based hybrid max–tmin ant system (CO-HMMAS) is proposed, which solves two sub-problems as a whole. The oriented pheromone and dynamic heuristic information calculating methods are designed. We analyse the differences between one-stage and two-stage AGTSP local search heuristics and combine CO-HMMAS with them properly. An improved Global 3-opt heuristic suitable for both symmetric and asymmetric cases is proposed with sharply reduced time complexity. Comparison experiments verified that, two-stage local search heuristics decrease solution error significantly and rapidly when the error is great, and one-stage ones improve a near-optimal solution costing much more computing time. Benchmarks tests show that, CO-HMMAS outperforms the state-of-the-art algorithm on several technical indexes. Experiments on typical panels reveal that all algorithm improvements are effective, and CO-HMMAS can obtain a better tool path than the best algorithm within less CPU time.
Journal: International Journal of Production Research
Pages: 4925-4940
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1401239
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401239
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenyu Zhang
Author-X-Name-First: Wenyu
Author-X-Name-Last: Zhang
Author-Name: Yushu Yang
Author-X-Name-First: Yushu
Author-X-Name-Last: Yang
Author-Name: Shuai Zhang
Author-X-Name-First: Shuai
Author-X-Name-Last: Zhang
Author-Name: Dejian Yu
Author-X-Name-First: Dejian
Author-X-Name-Last: Yu
Author-Name: Yacheng Li
Author-X-Name-First: Yacheng
Author-X-Name-Last: Li
Title: Correlation-aware manufacturing service composition model using an extended flower pollination algorithm
Abstract: 
 Due to the emergence of cloud computing technology, many services with the same functionalities and different non-functionalities occur in cloud manufacturing system. Thus, manufacturing service composition optimisation is becoming increasingly important to meet customer demands, where this issue involves multi-objective optimisation. In this study, we propose a new manufacturing service composition model based on quality of service as well as considerations of crowdsourcing and service correlation. To address the problem of multi-objective optimisation, we employ an extended flower pollination algorithm (FPA) to obtain the optimal service composition solution, where it not only utilises the adaptive parameters but also integrates with genetic algorithm (GA). A case study was conducted to illustrate the practicality and effectiveness of the proposed method compared with GA, differential evolution algorithm, and basic FPA.
Journal: International Journal of Production Research
Pages: 4676-4691
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1402137
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1402137
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Template-Type: ReDIF-Article 1.0
Author-Name: Seokho Kang
Author-X-Name-First: Seokho
Author-X-Name-Last: Kang
Author-Name: Eunji Kim
Author-X-Name-First: Eunji
Author-X-Name-Last: Kim
Author-Name: Jaewoong Shim
Author-X-Name-First: Jaewoong
Author-X-Name-Last: Shim
Author-Name: Wonsang Chang
Author-X-Name-First: Wonsang
Author-X-Name-Last: Chang
Author-Name: Sungzoon Cho
Author-X-Name-First: Sungzoon
Author-X-Name-Last: Cho
Title: Product failure prediction with missing data
Abstract: 
 In production data, missing values commonly appear for several reasons including changes in measurement and inspection items, sampling inspections, and unexpected process events. When applied to product failure prediction, the incompleteness of data should be properly addressed to avoid performance degradation in prediction models. Well-known approaches for missing data treatment, such as elimination and imputation, would not perform well under usual scenarios in production data, including high missing rate, systematic missing and class imbalance. To address these limitations, here we present a method for predictive modelling with missing data by considering the characteristics of production data. It builds multiple prediction models on different complete data subsets derived from the original data-set, each of which has different coverage of instances and input variables. These models are selectively used to make predictions for new instances with missing values. We demonstrate the effectiveness of the proposed method through a case study using actual data-sets from a home appliance manufacturer.
Journal: International Journal of Production Research
Pages: 4849-4859
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1407883
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1407883
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Template-Type: ReDIF-Article 1.0
Author-Name: Yan-Lai Li
Author-X-Name-First: Yan-Lai
Author-X-Name-Last: Li
Author-Name: Yin-Feng Du
Author-X-Name-First: Yin-Feng
Author-X-Name-Last: Du
Author-Name: Kwai-Sang Chin
Author-X-Name-First: Kwai-Sang
Author-X-Name-Last: Chin
Title: Determining the importance ratings of customer requirements in quality function deployment based on interval linguistic information
Abstract: 
 Quality function deployment (QFD) is a customer-oriented tool and is widely applied to design and improve products and services. Determining the importance ratings (IRs) of customer requirements (CRs) is an essential step in QFD application and will affect the quality of product design and improvement. In this study, a group decision-making method is proposed to obtain realistic IRs. Low-carbon environment is considered in recognising CRs. Interval linguistic information (ILI) is used to express the vague evaluations in product improvement. In addition, an interval linguistic weighted arithmetic averaging operator, a normalised formula, and an expected value operator are integrated to deal with evaluation matrices expressed by ILI. A relationship matrix is used reversely to acquire accurate basic IRs (BIRs). The improved cosine method based on ILI is also employed to derive BIRs. The modified entropy method based on ILI is proposed to determine a competitive priority rating (CPR) of a CR. The final IR of every CR can be obtained by integrating its BIR and CPR. Finally, a practical product improvement of turbine engine is provided to illustrate the validity and feasibility of the proposed approach.
Journal: International Journal of Production Research
Pages: 4692-4708
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1417650
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1417650
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexander G. Chentsov
Author-X-Name-First: Alexander G.
Author-X-Name-Last: Chentsov
Author-Name: Pavel A. Chentsov
Author-X-Name-First: Pavel A.
Author-X-Name-Last: Chentsov
Author-Name: Alexander A. Petunin
Author-X-Name-First: Alexander A.
Author-X-Name-Last: Petunin
Author-Name: Alexander N. Sesekin
Author-X-Name-First: Alexander N.
Author-X-Name-Last: Sesekin
Title: Model of megalopolises in the tool path optimisation for CNC plate cutting machines
Abstract: 
 We consider the issues of tool path optimisation under constraints and formulate a mathematical problem of visiting megalopolises. The megalopolises model is the result of the discretisation of the tool path problem for CNC plate cutting machines. The order of visits is subject to precedence constraints. In addition, the cost functions depend on the set of pending tasks. The quality criterion is a variety of the additive criterion. The problem is established within the dynamic programming framework, however, a heuristic is proposed and implemented to solve practical problems of large dimensionality.
Journal: International Journal of Production Research
Pages: 4819-4830
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2017.1421784
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421784
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:14:p:4819-4830




Template-Type: ReDIF-Article 1.0
Author-Name: Huan Jin
Author-X-Name-First: Huan
Author-X-Name-Last: Jin
Author-Name: Mike Hewitt
Author-X-Name-First: Mike
Author-X-Name-Last: Hewitt
Author-Name: Barrett W. Thomas
Author-X-Name-First: Barrett W.
Author-X-Name-Last: Thomas
Title: Workforce grouping and assignment with learning-by-doing and knowledge transfer
Abstract: 
 We consider a workforce allocation problem in which workers learn both by performing a job and by observing the performance of and interacting with co-located colleagues. As a result, an organisation can benefit from both effectively assigning individuals to jobs and grouping workers into teams. A challenge often faced when solving workforce allocation models that recognise learning is that learning curves are non-linear. To overcome this challenge, we identify properties of an optimal solution to a non-linear programme for grouping workers into teams and assigning the resulting teams to sets of jobs. With these properties identified, we reformulate the non-linear programme to a mixed integer programme that can be solved in much less time. We analyse (near-)optimal solutions to this model to derive managerial insights.
Journal: International Journal of Production Research
Pages: 4968-4982
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1424366
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424366
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:14:p:4968-4982




Template-Type: ReDIF-Article 1.0
Author-Name: Siavash H. Khajavi
Author-X-Name-First: Siavash H.
Author-X-Name-Last: Khajavi
Author-Name: Gege Deng
Author-X-Name-First: Gege
Author-X-Name-Last: Deng
Author-Name: Jan Holmström
Author-X-Name-First: Jan
Author-X-Name-Last: Holmström
Author-Name: Pasi Puukko
Author-X-Name-First: Pasi
Author-X-Name-Last: Puukko
Author-Name: Jouni Partanen
Author-X-Name-First: Jouni
Author-X-Name-Last: Partanen
Title: Selective laser melting raw material commoditization: impact on comparative competitiveness of additive manufacturing
Abstract: 
 The paper analyses the impact of cheaper metal powder supplies on the comparative competitiveness of additive manufacturing (AM). By utilising two case studies, we compare the economic impact of an innovative titanium extraction method on Selective Laser Melting (SLM) and conventional methods of machining and casting. A switch-over analysis identifies the production quantities above which conventional manufacturing is more cost competitive than additive manufacturing. This analysis is performed for current raw material as well as cheaper raw material supply. The results illustrate the improved comparative competitiveness of SLM as the titanium supply is commoditised and more readily available in powder form. The responsiveness of the supply chain is improved as the switch-over point between SLM and conventional methods increases. Moreover, as the raw material supply chain for titanium is transformed through the use of this novel extraction method, the manufacturing supply chain is simplified.
Journal: International Journal of Production Research
Pages: 4874-4896
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1436781
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1436781
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:14:p:4874-4896




Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoguang Sun
Author-X-Name-First: Xiaoguang
Author-X-Name-Last: Sun
Author-Name: Rémy Houssin
Author-X-Name-First: Rémy
Author-X-Name-Last: Houssin
Author-Name: Jean Renaud
Author-X-Name-First: Jean
Author-X-Name-Last: Renaud
Author-Name: Mickaël Gardoni
Author-X-Name-First: Mickaël
Author-X-Name-Last: Gardoni
Title: Towards a human factors and ergonomics integration framework in the early product design phase: Function-Task-Behaviour
Abstract: 
 Considering the existing methodologies’ hysteresis and cost of the human factors and ergonomics (HF/E) integration in the design phase, this paper attempts to develop a time-saving, less expensive and standard approach for designers to integrate the HF/E from the early design phase. In this study, the HF/E information is embodied by a user manual, which will be continuously improved with the refinement of design. A Function-Task-Behaviour framework is proposed to restate the design process, which involves three steps: (1) Functional specification involves function definition and decomposition according to initial user manual and other requirements; (2) Embodiment refers to conducting task definition and planning to achieve the intended function. SysML is used for task definition and PERT method is applied for task planning; (3) Detailed design refers to the interactions analysis between user’s behaviour and product’s behaviour in the work area. A case study is shown at the end of this paper to illustrate the feasibility of the proposed method in integrating the HF/E from the early design phase to improve the final performance of both product and user.
Journal: International Journal of Production Research
Pages: 4941-4953
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1437287
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1437287
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:14:p:4941-4953




Template-Type: ReDIF-Article 1.0
Author-Name: Chanduraj Pious Kapse
Author-X-Name-First: Chanduraj Pious
Author-X-Name-Last: Kapse
Author-Name: Anil Kumar
Author-X-Name-First: Anil
Author-X-Name-Last: Kumar
Author-Name: Manoj Kumar Dash
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Dash
Author-Name: Edmundas Kazimieras Zavadskas
Author-X-Name-First: Edmundas Kazimieras
Author-X-Name-Last: Zavadskas
Author-Name: Sunil Luthra
Author-X-Name-First: Sunil
Author-X-Name-Last: Luthra
Title: Developing textile entrepreneurial inclination model by integrating experts mining and ISM-MICMAC
Abstract: 
 The Indian textile industry is lacking in an entrepreneurial inclination of a skilled young generation; because of this, the industry is facing a challenge to achieve sustainable development and growth. To overcome this problem, the goal of this work is to build an entrepreneurial inclination model in the context of the textile industry. For achieving this goal, a combined approach of an extensive literature review and experts mining has been used to establish the entrepreneurial inclination factors in phased of the study. In the second phase, an Interpretive Structural Modelling with Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) has been applied to build a structural model and to find the driving force factors and dependence power. The results show that effective entrepreneurship courses, institutional policy, training and internship, institutional corporation and the involvement of institutional heads play a very significant role in encouraging youth towards entrepreneurship. The outcomes of the study can help both the government and academic institutes to draw up effective policy and develop an entrepreneurial culture which can help to create more entrepreneurs in the textile field.
Journal: International Journal of Production Research
Pages: 4709-4728
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1443523
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1443523
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:14:p:4709-4728




Template-Type: ReDIF-Article 1.0
Author-Name: Der-Chiang Li
Author-X-Name-First: Der-Chiang
Author-X-Name-Last: Li
Author-Name: Qi-Shi Shi
Author-X-Name-First: Qi-Shi
Author-X-Name-Last: Shi
Author-Name: Ming-Da Li
Author-X-Name-First: Ming-Da
Author-X-Name-Last: Li
Title: Using an attribute conversion approach for sample generation to learn small data with highly uncertain features
Abstract: 
 Accelerating new product development has become an important marketing strategy for manufacturers who are competing globally. However, this may lead to the small data learning issue. Although machine learning algorithms are used to extract knowledge from training samples, algorithms may not output satisfactory predictions when training sizes are small. This paper provides a real case of a TFT-LCD (thin film transistor liquid crystal display) maker when a new strengthened cover glass is developed using chemical processes. With very little prior experience about the processes involved, engineers attempted to improve the yield rates by determining the parameters from a few pilot-run data. However, owing to the fact that the processes were different from those required to make TFT-LCD panels, the highly uncertain characteristics of the processes led to the use of two virtual sample generation (VSG) approaches, bootstrap aggregating (bagging) and the synthetic minority over-sampling technique, from which unsatisfactory results were obtained. Accordingly, this study was used to develop a systematic VSG method based on fuzzy theory to tackle the learning issue. The experimental results show that support vector regressions built with training sets containing the proposed samples present more precise predictions and thus can help engineers infer more correct manufacturing parameters.
Journal: International Journal of Production Research
Pages: 4954-4967
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1444813
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1444813
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Template-Type: ReDIF-Article 1.0
Author-Name: Lea Hannola
Author-X-Name-First: Lea
Author-X-Name-Last: Hannola
Author-Name: Alexander Richter
Author-X-Name-First: Alexander
Author-X-Name-Last: Richter
Author-Name: Shahper Richter
Author-X-Name-First: Shahper
Author-X-Name-Last: Richter
Author-Name: Alexander Stocker
Author-X-Name-First: Alexander
Author-X-Name-Last: Stocker
Title: Empowering production workers with digitally facilitated knowledge processes – a conceptual framework
Abstract: 
 Recent digital advancements, including social software, mobile technologies and augmented reality, offer promising opportunities to empower knowledge workers in their production environment by leveraging their knowledge processes, decision-making skills and social interaction practices. This paper proposes a conceptual framework for empowering workers in industrial production environments with digitally facilitated knowledge management processes. The framework explores four concrete facets of digital advancements that apply to a wide range of knowledge processes and production strategies in manufacturing companies. Each of these advancements are capable of supporting one specific facet of the individual knowledge management processes of workers; knowledge transfer, discovery, acquisition and sharing. The study contributes to the production research community by aligning emerging digital technologies and current trends in advanced manufacturing environments to benefit workers and improve job satisfaction, efficiency and productivity. The paper also contains suggestions about developing innovative solutions for production environments that support workers with digital technologies for flexible production.
Journal: International Journal of Production Research
Pages: 4729-4743
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1445877
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1445877
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Template-Type: ReDIF-Article 1.0
Author-Name: Huimeng Zheng
Author-X-Name-First: Huimeng
Author-X-Name-Last: Zheng
Author-Name: Weidong Liu
Author-X-Name-First: Weidong
Author-X-Name-Last: Liu
Author-Name: Chengdi Xiao
Author-X-Name-First: Chengdi
Author-X-Name-Last: Xiao
Title: Structural relationship model for design defect and influencing factors in the concurrent design process
Abstract: 
 Concurrent design is a systematic approach that aims to help developers consider all elements related to the product life cycle, including quality, cost, schedule and user requirement. This approach is challenging because designers conduct these elements manually in the design process. In addition, studies on the formation mechanism of design defects are limited. To minimise the difficulties of product designers and prevent design defects, a structural relationship model is presented for the concurrent design process. The structural relationship model, which incorporates design defects, design process and influencing factors, is marked through polychromatic sets. The interval analytic hierarchy process is used to determine the weight of each influencing factor. Furthermore, a brief model instruction for concurrent design is proposed to guarantee the model application’s validity. The proposed method enables designers to concentrate on functionality and performance design, and the findings are expected to be theoretically and practically useful for preventing and controlling defects in concurrent design.
Journal: International Journal of Production Research
Pages: 4897-4924
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1447704
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1447704
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Template-Type: ReDIF-Article 1.0
Author-Name: R. Anthony Inman
Author-X-Name-First: R. Anthony
Author-X-Name-Last: Inman
Author-Name: Kenneth W. Green
Author-X-Name-First: Kenneth W.
Author-X-Name-Last: Green
Title: Lean and green combine to impact environmental and operational performance
Abstract: 
 We assess the antecedent link between lean and green practices and assess the combined impact of lean and green practices on both environmental and operational performance. A lean and green practices performance model is proposed that incorporates lean and green practices as antecedents to both environmental and operational performance. Structural equation modelling was used to analyse data collected from a sample of 182 manufacturing managers in U.S. plants. We found that lean manufacturing practices are positively associated with environmental performance and operational performance and that green supply chain management practices are positively associated with environmental performance and environmental performance is positively associated with operational performance. No support was found for the idea that green supply chain management practices are positively associated with operational performance. While lean practices were found to directly affect environmental performance, the indirect effect of lean practices on environmental performance through green practices is stronger, indicating complementarity.
Journal: International Journal of Production Research
Pages: 4802-4818
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1447705
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1447705
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Template-Type: ReDIF-Article 1.0
Author-Name: Shuangshuang Li
Author-X-Name-First: Shuangshuang
Author-X-Name-Last: Li
Author-Name: Xintian Liu
Author-X-Name-First: Xintian
Author-X-Name-Last: Liu
Author-Name: Yansong Wang
Author-X-Name-First: Yansong
Author-X-Name-Last: Wang
Author-Name: Xiaolan Wang
Author-X-Name-First: Xiaolan
Author-X-Name-Last: Wang
Title: Hidden quality cost function of a product based on the cubic approximation of the Taylor expansion
Abstract: 
 The-Nominal-The-Best (N-type) loss function is established based on the Taylor expansion. Results become more accurate as more Taylor expansion items are retained. N-type loss function neglects terms with powers higher than two, which inevitably leads to a certain deviation between the calculated result and the true value. In this paper, Taylor expansion is retained to the third-order, and the quality loss function is extended to three items. The quality loss coefficients of each item are determined, and the asymmetric piecewise cubic quality loss function is established. The deviation between the cubic and quadratic functions is evaluated. The formula for calculating the hidden quality cost of a product is derived by choosing an appropriate density distribution function and using process capability. Two cases are utilised to analyse and discuss the quality loss and hidden quality cost of a product using the cubic quality loss and quadratic quality loss functions. This paper provides a more accurate approach for the study of product quality management.
Journal: International Journal of Production Research
Pages: 4762-4780
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1465607
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1465607
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Template-Type: ReDIF-Article 1.0
Author-Name: Chao Zhang
Author-X-Name-First: Chao
Author-X-Name-Last: Zhang
Author-Name: Guanghui Zhou
Author-X-Name-First: Guanghui
Author-X-Name-Last: Zhou
Author-Name: Qi Lu
Author-X-Name-First: Qi
Author-X-Name-Last: Lu
Author-Name: Fengtian Chang
Author-X-Name-First: Fengtian
Author-X-Name-Last: Chang
Title: Generating significant subassemblies from 3D assembly models for design reuse
Abstract: 
 Significant subassemblies are defined as the reusable regions of pre-existing 3D assembly models. A significant subassembly has great significances for design reuse as it aggregates abundant knowledge in a vivid 3D CAD model and enables designers to reuse existing mature designs from a high-level perspective. Consequently, this paper contributes to significant subassembly generation from pre-existing 3D assembly models for design reuse. The paper first gives an explicit definition of significant subassemblies and further explores the multilevel knowledge embedded in these significant subassemblies. Based on the above definition and multilevel knowledge, a knowledge-based approach is then proposed for significant subassembly generation, which includes three phases: (1) identifying candidate subassemblies with high cohesion inside and low coupling outside using the Markov clustering process; (2) removing normal candidate subassemblies with low reusability and less information, and generating filtered subassemblies using the proposed assembly frequency – inverse mean subassembly frequency based scheme; and (3) determining significant subassemblies by measuring the complexity of the filtered subassemblies. Finally, a computer numerical control honing machine model is taken as an application example to demonstrate the effectiveness of the proposed approach.
Journal: International Journal of Production Research
Pages: 4744-4761
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1465608
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1465608
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Template-Type: ReDIF-Article 1.0
Author-Name: Lin Lin
Author-X-Name-First: Lin
Author-X-Name-Last: Lin
Author-Name: Bin Luo
Author-X-Name-First: Bin
Author-X-Name-Last: Luo
Author-Name: ShiSheng Zhong
Author-X-Name-First: ShiSheng
Author-X-Name-Last: Zhong
Title: Multi-objective decision-making model based on CBM for an aircraft fleet with reliability constraint
Abstract: 
 Modern production management patterns, in which multi-unit (e.g. an aircraft fleet) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision-making. To schedule a good maintenance plan, not only does the individual aircraft maintenance have to be considered, but also the maintenance of the other aircraft in fleet have to be taken into account. Condition-based maintenance (CBM) is a maintenance scheme which recommends maintenance decisions according to equipment status collected by condition monitor over a period of time. Evaluating risk is necessary for scheduling appropriate maintenance, avoiding aircraft losses and maintaining the repairable components at a high-reliable state. In this paper, a novel two-models-fusion framework is proposed to predict the reliability of aircraft structures subjected to fatigue loads. Furthermore, we established a fleet maintenance decision-making model based on CBM for the maintenance of fatigue structures. The model concentrates on both minimising fleet maintenance cost and maximising fleet availability, overcoming the shortcomings of traditional fleet CBM research, which has simply focused on one or the other of these parameters. Finally, a case study regarding a fleet of 10 aircraft is conducted, and the results indicated that the proposed model efficiently generates outcomes that meet the schedule requirements.
Journal: International Journal of Production Research
Pages: 4831-4848
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1467574
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1467574
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Template-Type: ReDIF-Article 1.0
Author-Name: Sylvester A. Aye
Author-X-Name-First: Sylvester A.
Author-X-Name-Last: Aye
Author-Name: P. Stephan Heyns
Author-X-Name-First: P. Stephan
Author-X-Name-Last: Heyns
Title: Prognostics of slow speed bearings using a composite integrated Gaussian process regression model
Abstract: 
 Prognostics of manufacturing systems enables improved maintenance scheduling and cost reduction through reduced downtime, improved allocation of maintenance resources and reduced consequential costs of breakdowns. Prognostics are necessary for predictive maintenance of bearings in manufacturing systems. The findings show that in general the composite integrated GPR models perform better than the simple mean simple covariance GPR models, irrespective of whether the training or test sets are dependent or independent. In this investigation the Affine Mean GPR (AMGPR) was found to be the most effective prognostic model for prognostics of slow speed bearings on both dependent and independent data samples.
Journal: International Journal of Production Research
Pages: 4860-4873
Issue: 14
Volume: 56
Year: 2018
Month: 7
X-DOI: 10.1080/00207543.2018.1470340
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1470340
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Template-Type: ReDIF-Article 1.0
Author-Name: Mario Fargnoli
Author-X-Name-First: Mario
Author-X-Name-Last: Fargnoli
Author-Name: Nicolas Haber
Author-X-Name-First: Nicolas
Author-X-Name-Last: Haber
Author-Name: Tomohiko Sakao
Author-X-Name-First: Tomohiko
Author-X-Name-Last: Sakao
Title: PSS modularisation: a customer-driven integrated approach
Abstract: 
 The shift from product ownership to integrated solutions (Product-Service Systems (PSSs)) is expected to lead to a higher customer satisfaction in many cases compared to providing products and services separately. PSS providers are required to add more value to the products they offer, as well as to augment and diversify the services related to these products. To deal with this complex task, this paper proposes a practical methodology to support manufacturers in designing services related to the proper functioning of their products fulfilling customers’ needs and expectations. This approach is based on the synergic use of Quality Function Deployment for PSS (QFDforPSS), Axiomatic Design (AD) and the service blueprint tools, providing a correlation between the customers’ expectations, the PSS components and the PSS modules. The methodology was verified by means of a service modularisation for PSS at a company operating in the biomedical sector. While the proposed approach needs to be validated through further studies in different contexts, its positive results in reducing both the risk of overdesigning and the possibility of creating design conflicts can contribute practically to the scientific knowledge on the development of integrated solutions.
Journal: International Journal of Production Research
Pages: 4061-4077
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1481302
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1481302
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammed Hichame Benbitour
Author-X-Name-First: Mohammed Hichame
Author-X-Name-Last: Benbitour
Author-Name: Evren Sahin
Author-X-Name-First: Evren
Author-X-Name-Last: Sahin
Author-Name: Yves Dallery
Author-X-Name-First: Yves
Author-X-Name-Last: Dallery
Title: The use of rush deliveries in periodic review assemble-to-order systems
Abstract: 
 We calculate optimal safety stock in a periodic review (T,S) assemble-to-order system having multiple components and multiple finished goods (FGs). Customer orders for FGs arrive according to independent Poisson processes, and cannot be neither backlogged nor lost. In case of potential component stock-out, the studied system uses rush deliveries from suppliers. For this setting, approximate expressions of the optimal safety stock that minimise the sum of inventory holding and rush ordering costs are developed. Exact optimal safety stocks are calculated using Discrete Event Simulation, and compared numerically to the approximate expressions. The model is applied to a first-tier automotive supplier and yields to a significant reduction in terms of inventory holding and rush ordering costs. A sensitivity analysis on relevant system parameters such as components demand, assembly coefficients and unit rush ordering cost is conducted.
Journal: International Journal of Production Research
Pages: 4078-4097
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1505059
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1505059
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Template-Type: ReDIF-Article 1.0
Author-Name: Claver Diallo
Author-X-Name-First: Claver
Author-X-Name-Last: Diallo
Author-Name: Uday Venkatadri
Author-X-Name-First: Uday
Author-X-Name-Last: Venkatadri
Author-Name: Abdelhakim Khatab
Author-X-Name-First: Abdelhakim
Author-X-Name-Last: Khatab
Author-Name: Zhuojun Liu
Author-X-Name-First: Zhuojun
Author-X-Name-Last: Liu
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Title: Optimal joint selective imperfect maintenance and multiple repairpersons assignment strategy for complex multicomponent systems
Abstract: 
 This paper addresses the joint selective maintenance and repairperson assignment problem (JSM–RAP) for complex multicomponent systems. The systems perform consecutive missions separated by scheduled finite duration breaks and are imperfectly maintained during the breaks. Current selective maintenance (SM) models usually assume that only one repair channel is available or that the repairperson assignment optimisation can be done at a subsequent stage. Using a generalised reliability function for k-out-of-n systems, we formulate the JSM–RAP for multicomponent systems more complex than the series-parallel systems commonly used in previous SM models. Two nonlinear formulations and their corresponding binary integer programming models are then proposed and optimally solved. Numerical experiments show the added value of the proposed approach and highlight the benefit of jointly carrying out the selection of the components to be maintained, the maintenance level to be performed and the assignment of the maintenance tasks to repairpersons. It is also shown that the flexibility provided by mixed skill cohorts of repairpersons over uniform cohorts can yield higher performance levels when the skillsets are significantly different.
Journal: International Journal of Production Research
Pages: 4098-4117
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1505060
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1505060
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:13:p:4098-4117




Template-Type: ReDIF-Article 1.0
Author-Name: Xiongbing Li
Author-X-Name-First: Xiongbing
Author-X-Name-Last: Li
Author-Name: Zhiping Liu
Author-X-Name-First: Zhiping
Author-X-Name-Last: Liu
Author-Name: Fulin Wang
Author-X-Name-First: Fulin
Author-X-Name-Last: Wang
Author-Name: Bing Yi
Author-X-Name-First: Bing
Author-X-Name-Last: Yi
Author-Name: Yongfeng Song
Author-X-Name-First: Yongfeng
Author-X-Name-Last: Song
Title: Combining physical shell mapping and reverse-compensation optimisation for spiral machining of free-form surfaces
Abstract: 
 Machining of free-form surfaces has an important role in industrial manufacturing, but conventional tool-path generation strategies for free-form surfaces machining have the drawbacks of serious flattening distortion and poor tool-path continuity. Therefore, a novel method is developed to generate a spiral tool path for the machining of free-form surfaces by improving surface-flattening distortion and tool-path continuity. First, physical shell mapping is presented to flatten a free-form surface into a plane, which takes stretching energy, bending energy, and global energy into account. Then, the spatial spiral polyline is rounded to generate a spiral path by proposing reverse-compensation optimisation. Therefore, the free-form surfaces can be quickly flattened with less distortion, remaining free of overlap, and can in addition be machined at high speed along a C2 continuous spiral tool path. Further, the flattening error, tool-path length, mean curvature, mean scallop-height error of the spiral path, machining time and surface roughness are obviously reduced. Finally, simulation results are given to show the effectiveness and feasibility of the presented strategy.
Journal: International Journal of Production Research
Pages: 4118-4131
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1512763
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1512763
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Template-Type: ReDIF-Article 1.0
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Xiaoyi Man
Author-X-Name-First: Xiaoyi
Author-X-Name-Last: Man
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: A two-stage stochastic programming for single yard crane scheduling with uncertain release times of retrieval tasks
Abstract: 
 Nowadays maritime transportation has become the mainstream of the global logistics, and the operational efficiency of container terminals plays a critical role in maritime transportation. As one of the most important terminal operational issues, yard crane scheduling that handles both storage and retrieval tasks has caught a lot of interest. However, the uncertainty on the release times of retrieval tasks, as one common phenomenon in daily operations, has been ignored in the literature. This paper investigates single yard crane scheduling to minimise the expected total tardiness of tasks, and focus on the case with uncertain release times of retrieval tasks. A two-stage stochastic programming model is proposed, and the sample average approximation (SAA) approach is applied to solve small instances of the problem. For large-scale instances, a genetic algorithm (GA) and a rule-based heuristic are developed. To evaluate the performances of the solution methods, numerical experiments with 300 instances are implemented. Computational results show that the rule-based heuristic outperforms both GA and SAA in terms of solution quality and running time.
Journal: International Journal of Production Research
Pages: 4132-4147
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1516903
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1516903
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Template-Type: ReDIF-Article 1.0
Author-Name: Niels De Smet
Author-X-Name-First: Niels
Author-X-Name-Last: De Smet
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Author-Name: Bram Desmet
Author-X-Name-First: Bram
Author-X-Name-Last: Desmet
Title: Optimising installation (R,Q) policies in distribution networks with stochastic lead times: a comparative analysis of guaranteed- and stochastic service models
Abstract: 
 This paper studies two modelling approaches to the multi-echelon inventory optimisation problem in a distribution network with stochastic demands and lead times. It compares the performance of a novel guaranteed-service model (GSM), using an installation (R, Q) inventory control policy, with a stochastic service model (SSM) considering ordering, holding and flexibility costs. From both cycle service level and fill rate perspectives, our numerical analysis of the 1-warehouse 2-retailer network shows that cost difference between both models is driven by the internal service level at the warehouse. The GSM outperforms the SSM for over 80% of the simulated instances and realises an average total cost improvement of approximately 10%. This analysis goes against earlier results that showed a relatively low-cost difference between the two approaches, and demonstrates that it is worthwhile to evaluate competing models for multi-echelon inventory optimisation in real-world supply chains with batch ordering and variable lead times.
Journal: International Journal of Production Research
Pages: 4148-4165
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1518606
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518606
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:13:p:4148-4165




Template-Type: ReDIF-Article 1.0
Author-Name: Pietro De Giovanni
Author-X-Name-First: Pietro
Author-X-Name-Last: De Giovanni
Title: A feature fatigue supply chain game with cooperative programs and ad-hoc facilitators
Abstract: 
 In this paper, we analyze a manufacturer's decisions to invest in technology to increase the number of product features and make its business more economically appealing. High number of features can lead to an overspecified product that entails a feature fatigue effect. More specifically, consumers show a decreasing willingness to purchase a good, due to its complexity. The manufacturer sells through a retailer, which in turn invests in some store facilitators efforts. The manufacturer can decrease the feature fatigue effect by implementing either a cooperative program or an ad-hoc facilitator. Our results reveal that the manufacturer, as the chain leader, makes decisions according to the program's efficiency, while considering the revenue sharing rule. When the share is low, the manufacturer's decision is always based on efficiency; otherwise, high sharing parameters sponsor the implementation of an ad-hoc facilitator. We identify a region of parameters in which firms have divergent preferences, resulting that the feature fatigue mitigation is a short term objective. The results also reveal a trade-off between profits and feature fatigue. An ad-hoc facilitator guarantees large profits, even without fully solving the feature fatigue issue. Instead, a support program increases mitigates the feature fatigue effect, while worsening the firms' profits.
Journal: International Journal of Production Research
Pages: 4166-4186
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1519264
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1519264
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:13:p:4166-4186




Template-Type: ReDIF-Article 1.0
Author-Name: Alessio Ishizaka
Author-X-Name-First: Alessio
Author-X-Name-Last: Ishizaka
Author-Name: Arijit Bhattacharya
Author-X-Name-First: Arijit
Author-X-Name-Last: Bhattacharya
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Rob Dekkers
Author-X-Name-First: Rob
Author-X-Name-Last: Dekkers
Author-Name: Vijay Pereira
Author-X-Name-First: Vijay
Author-X-Name-Last: Pereira
Title: Outsourcing and offshoring decision making
Journal: International Journal of Production Research
Pages: 4187-4193
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2019.1603698
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1603698
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:13:p:4187-4193




Template-Type: ReDIF-Article 1.0
Author-Name: Ananya Bhattacharya
Author-X-Name-First: Ananya
Author-X-Name-Last: Bhattacharya
Author-Name: Prakash J. Singh
Author-X-Name-First: Prakash J.
Author-X-Name-Last: Singh
Title: Antecedents of agency problems in service outsourcing
Abstract: 
 As outsourcing of services has grown in popularity, agency problems such as adverse selection and moral hazard have become more prevalent, leading to increased contracting costs. In this paper, we focus on how adverse selection and performance ambiguity arise in service outsourcing arrangements. We used agency theory as a theoretical lens to propose a mediated model where two antecedents, information asymmetry and goals compatibility, directly affect performance ambiguity, and indirectly through adverse selection. This model was tested empirically with dyadic data on 50 matched pair service outsourcing arrangements between organisations in Australia. Results show that information asymmetry impacts performance ambiguity through adverse selection, whereas goals compatibility affects performance ambiguity directly, without influencing adverse selection. These results suggest that the two agency problems are differentially affected by the antecedents of service outsourcing. The theoretical and practical contributions of this study are a better understanding of how different agency problems arise and how they can be controlled in service outsourcing in particular and in service production context more generally.
Journal: International Journal of Production Research
Pages: 4194-4210
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1506179
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1506179
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Template-Type: ReDIF-Article 1.0
Author-Name: Manfredi Bruccoleri
Author-X-Name-First: Manfredi
Author-X-Name-Last: Bruccoleri
Author-Name: Giovanni Perrone
Author-X-Name-First: Giovanni
Author-X-Name-Last: Perrone
Author-Name: Erica Mazzola
Author-X-Name-First: Erica
Author-X-Name-Last: Mazzola
Author-Name: Robert Handfield
Author-X-Name-First: Robert
Author-X-Name-Last: Handfield
Title: The magnitude of a product recall: offshore outsourcing vs. captive offshoring effects
Abstract: 
 The escalation in product recalls in recent years is attributed to the rise of globalisation and associated challenges of offshoring. Extant SCM research suggests that product recalls have a significant negative impact on financial performance, but gaps exist relative to the managerial actions to minimise their impact. Recall response strategies have become more important in the press, given that a single recall may result in the mandatory withdrawal of millions of products from the market, with firms incurring enormous logistics costs and brand damage. In this study, we address this gap in the research, and using a measure of product recall defined as the volume of products withdrawn from the market due to product quality failure. We explore the scale of the recall in the context of pharmaceutical sector global sourcing strategies, exploring whether the variation in global sourcing decisions not only increases the likelihood of a recall, but also influences the capability to minimise the total cost of recall. Our results suggest that offshore outsourcing and captive offshoring have opposite effects in terms of their influence on the magnitude of product recall. We summarise the implications through a compelling set of insights for future global sourcing strategy research themes.
Journal: International Journal of Production Research
Pages: 4211-4227
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1533652
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1533652
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Template-Type: ReDIF-Article 1.0
Author-Name: Shanthi Gopalakrishnan
Author-X-Name-First: Shanthi
Author-X-Name-Last: Gopalakrishnan
Author-Name: Haisu Zhang
Author-X-Name-First: Haisu
Author-X-Name-Last: Zhang
Title: The link between vendor certification and growth in IT outsourcing: a tale of two stories
Abstract: 
 There has been a great deal of ambiguity and complexity in the relationship between vendor certification and vendor growth in the outsourcing context. In this study, the authors build a competitive mediation model, where they examine both the direct and the indirect effects of vendor certification on vendor growth. Using a combination of primary data (i.e. survey) and secondary data from a sample of 120 IT vendors in India, they find that vendor certification directly helps with vendor growth but it hurts vendor innovation and therefore indirectly hinders vendor growth. They further explore the moderating role of the number of major clients. Results demonstrate that an increase in the number of major clients does not moderate the positive relationship between certification and growth; however, it weakens the negative relationship between certification and innovation. Therefore, a large client base seems to attenuate the dark side of certification in organisational innovation activities.
Journal: International Journal of Production Research
Pages: 4228-4243
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2019.1599459
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1599459
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Template-Type: ReDIF-Article 1.0
Author-Name: Carsten Hansen
Author-X-Name-First: Carsten
Author-X-Name-Last: Hansen
Author-Name: Carlos Mena
Author-X-Name-First: Carlos
Author-X-Name-Last: Mena
Author-Name: Emel Aktas
Author-X-Name-First: Emel
Author-X-Name-Last: Aktas
Title: The role of political risk in service offshoring entry mode decisions
Abstract: 
 This research investigates the effect of political risk on the offshore service industry. The study empirically examines how an extended political risk definition, operationalised into a model consisting of 12 political risk variables, helps predict location decisions across offshoring entry modes and activity types. The research focuses on captive offshoring and offshore outsourcing entry modes, and Information Technology Outsourcing (ITO), Business Process Outsourcing (BPO) and Knowledge Process Outsourcing (KPO) activity types. The research indicated that political risk factors accounted for 38% of the variability in offshore outsourcing flows, implying that concerns about service disruptions and/or cost implications of external uncertainties feature as a key factor in supplier selection and location decisions. The findings further confirm a positive relationship between institutional and regulatory factors in host locations, and the flow of offshoring activities with a high knowledge content. The research contributes to enhancing the explanatory ability of Transaction Cost Economics by re-operationalising the concept of political risk in the context of both offshore outsourcing and captive offshoring. For practitioners, these findings provide a clear indication of the political risks that can affect service offshoring decisions; for policymakers, they highlight the importance of strengthening institutional and regulatory factors to attract investment.
Journal: International Journal of Production Research
Pages: 4244-4260
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1518601
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518601
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Template-Type: ReDIF-Article 1.0
Author-Name: Alessio Ishizaka
Author-X-Name-First: Alessio
Author-X-Name-Last: Ishizaka
Author-Name: Cristina López
Author-X-Name-First: Cristina
Author-X-Name-Last: López
Title: Cost-benefit AHPSort for performance analysis of offshore providers
Abstract: 
 The performance of a company is largely affected by that of its providers as they are a direct factor that determines product prices, flexibility and quality. It is, therefore, important to measure their performance. Several aspects need to be measured but traditional multi-criteria decision methods (MCDM) do not benchmark but only rank providers. Multi-criteria decision sorting methods are well indicated to benchmark activities into classes. In this paper, we present a modification of the AHPSort sorting method, where cost and benefit criteria are kept separate for a better and easier comparison. A case study in the aerospace industry will illustrate the efficacy of the new Cost-Benefit AHPSort method. The results will help managers to make specific decisions concerning their current offshore providers. They will also give valuable feedback for providers in order to improve their performance. Additionally, the findings enable a definition of benchmarking that will support future evaluations.
Journal: International Journal of Production Research
Pages: 4261-4277
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1509393
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1509393
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Template-Type: ReDIF-Article 1.0
Author-Name: Harpreet Kaur
Author-X-Name-First: Harpreet
Author-X-Name-Last: Kaur
Author-Name: Surya Prakash Singh
Author-X-Name-First: Surya Prakash
Author-X-Name-Last: Singh
Author-Name: Abhijit Majumdar
Author-X-Name-First: Abhijit
Author-X-Name-Last: Majumdar
Title: Modelling joint outsourcing and offshoring decisions
Abstract: 
 Offshoring and outsourcing have emerged as two most essential and important strategies for the manufacturing firms globally. This has happened due to the relentless forces of competition and globalisation, which has forced modern manufacturing firms to disaggregate themselves and reach for foreign investments, technological inputs through collaboration and cooperation among markets and partners. Outsourcing and offshoring simultaneously has potential to help the firm to meet three strategic goals i.e. ‘efficiency’ through cost minimisation; ‘exploration’ through an access to the right and technologically capable firm vendors/ Suppliers/ players; and ‘exploitation’ from development of global markets. Both outsourcing and offshoring have grown to a great extent either by the number of companies involved or by the number of multiple nations are involved. Hence, addressing both offshoring and outsourcing strategies together can provides value to the supply chain in economical and efficient way. Therefore, this paper is an attempt to model joint outsourcing and offshoring decision integrated with fuzzy-MCDM approaches using fuzzy data to optimise total cost through right selection of suppliers to meet demand of global markets, thus, achieving efficiency, exploration and exploitation. The model addresses qualitative and quantitative criteria in joint decisions and is also illustrated to show the cost effectiveness.
Journal: International Journal of Production Research
Pages: 4278-4309
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1471245
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471245
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Template-Type: ReDIF-Article 1.0
Author-Name: Kulwant S. Pawar
Author-X-Name-First: Kulwant S.
Author-X-Name-Last: Pawar
Author-Name: Fahian Anisul Huq
Author-X-Name-First: Fahian Anisul
Author-X-Name-Last: Huq
Author-Name: Ahmad Khraishi
Author-X-Name-First: Ahmad
Author-X-Name-Last: Khraishi
Author-Name: Janat Shah
Author-X-Name-First: Janat
Author-X-Name-Last: Shah
Title: Contextualisation of the complexity in the selection of developing country outsourcees by developed country outsourcers
Abstract: 
 Outsourcing research has recognised that selecting the right offshore supplier (outsourcee) in low-cost distant developing countries is complex, but central to outsourcing success. More specifically, the combination of outsourcee contextual internal factors (e.g. capabilities) with outsourced-to country contextual external factors (e.g. political, legal, economic, socio-cultural) as two fundamental and interconnected decisions firms make when outsourcing remains an underexplored research gap. Therefore, through a rigorous three-tier qualitative approach we, firstly, develop a contextual Environmental Separation Index (ESI) decision tool to help outsourcing firms in making more informed decisions when selecting outsourcees and outsourcing locations. Secondly, we operationalise the ESI as intuitive and easy to use decision tool, yet with a provision to deliver a truly context proof outsourcee selection decision. Thirdly, we adopt a complexity theory lens to explain that narrowing the contextual outsourcer–outsourcee gap facilitates a mind-set shift in outsourcing relationships from hierarchies to networks and from controlling to empowering developing country outsourcees. We show from a complexity theory perspective how contextual separation gaps between developed country outsourcers and developing country outsourcees can be an effective way to grasp the evolutionary path of outsourcing relationships.
Journal: International Journal of Production Research
Pages: 4310-4332
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2018.1529444
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1529444
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Template-Type: ReDIF-Article 1.0
Author-Name: Chun-Chin Wei
Author-X-Name-First: Chun-Chin
Author-X-Name-Last: Wei
Author-Name: Yung-Lung Cheng
Author-X-Name-First: Yung-Lung
Author-X-Name-Last: Cheng
Author-Name: Kuo-Liang Lee
Author-X-Name-First: Kuo-Liang
Author-X-Name-Last: Lee
Title: How to select suitable manufacturing information system outsourcing projects by using TOPSIS method
Abstract: 
 Modern business management depends on information technology (IT) deeply. However, most companies, especially manufacturing, are not good at IT. But IT is very important and complex to the manufacturing industry. Numerous manufacturing now outsource their information system (IS) projects to Information Service Providers (ISP) instead of developing in-house. This work classifies the critical objectives for selecting manufacturing information system outsourcing projects into benefit-related objectives and cost-related objectives and then formulates a goal programming (GP) model. Interactions between manufacturing information system projects and availability of scarce resources are also considered into constraints of the model. However, because of the incommensurability and conflicting nature of these objectives, the GP model becomes complex. The method called ‘technique for order preference by similarity to ideal solution’ (TOPSIS) and the fuzzy set theory are employed to simplify the complex GP solving process and reflect the preferences of managers. A case study of a TV assembly company in Taiwan illustrates the feasibility of the proposed model.
Journal: International Journal of Production Research
Pages: 4333-4350
Issue: 13
Volume: 57
Year: 2019
Month: 7
X-DOI: 10.1080/00207543.2019.1572930
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1572930
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:13:p:4333-4350




Template-Type: ReDIF-Article 1.0
Author-Name: Yoram Koren
Author-X-Name-First: Yoram
Author-X-Name-Last: Koren
Author-Name: Wencai Wang
Author-X-Name-First: Wencai
Author-X-Name-Last: Wang
Author-Name: Xi Gu
Author-X-Name-First: Xi
Author-X-Name-Last: Gu
Title: Value creation through design for scalability of reconfigurable manufacturing systems
Abstract: 
 Rapid and cost-effective scalability of the throughput of manufacturing systems is an invaluable feature for the management of manufacturing enterprises. System design for scalability allows the enterprise to build a manufacturing system to supply the current demand, and upgrade its throughput in the future, in a cost-effective manner, to meet possible higher market demand in a timely manner. To possess this capability, the manufacturing system must be designed at the outset for future expansions in its throughput to enable growths in supply exactly when needed by the market. A mathematical method that maximises the system throughput after reconfiguration is proposed, and an industrial case is presented to validate the method. The paper offers a set of principles for system design for scalability to guide designers of modern manufacturing systems.
Journal: International Journal of Production Research
Pages: 1227-1242
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1145821
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1145821
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Template-Type: ReDIF-Article 1.0
Author-Name: Mariagrazia Dotoli
Author-X-Name-First: Mariagrazia
Author-X-Name-Last: Dotoli
Author-Name: Alexander Fay
Author-X-Name-First: Alexander
Author-X-Name-Last: Fay
Author-Name: Marek Miśkowicz
Author-X-Name-First: Marek
Author-X-Name-Last: Miśkowicz
Author-Name: Carla Seatzu
Author-X-Name-First: Carla
Author-X-Name-Last: Seatzu
Title: Advanced control in factory automation: a survey
Abstract: 
 This paper provides a survey of the main advanced control techniques currently adopted in factory automation. In particular, it focuses on five classes of control approaches, namely: model-based control, control based on computational intelligence, adaptive control, discrete event systems-based control and finally event-triggered and self-triggered control. A particular focus is put on the most significant and recent contributions in these areas with attention to their application in the factory automation domain. Finally, open issues, challenges and the requirements of further research efforts for each class are pointed out.
Journal: International Journal of Production Research
Pages: 1243-1259
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1173259
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173259
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:5:p:1243-1259




Template-Type: ReDIF-Article 1.0
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Title: Human factors in order picking: a content analysis of the literature
Abstract: 
 Order picking (OP) is one of the most labour- and time-intensive processes in internal logistics. Over the last decades, researchers have developed various mathematical planning models that help to increase the efficiency of OP systems, for example, by optimising storage assignments or by specifying routes for the order pickers that minimise travel distance in the warehouse. Human characteristics that are often a major determinant of OP system performance have, however, widely been ignored in this stream of research. This paper systematically evaluates the literature on manual OP systems and conducts a content analysis to gain insights into how human factors (HF) have been considered and discussed in the scientific literature. The results of the analysis indicate that management-oriented efficiency criteria dominated prior research on OP, and that there is a clear lack of attention to HF in the design and management of OP systems. This poses an opportunity for research and design of manual OP systems.
Journal: International Journal of Production Research
Pages: 1260-1276
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1186296
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1186296
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:5:p:1260-1276




Template-Type: ReDIF-Article 1.0
Author-Name: Claver Diallo
Author-X-Name-First: Claver
Author-X-Name-Last: Diallo
Author-Name: Uday Venkatadri
Author-X-Name-First: Uday
Author-X-Name-Last: Venkatadri
Author-Name: Abdelhakim Khatab
Author-X-Name-First: Abdelhakim
Author-X-Name-Last: Khatab
Author-Name: Sriram Bhakthavatchalam
Author-X-Name-First: Sriram
Author-X-Name-Last: Bhakthavatchalam
Title: State of the art review of quality, reliability and maintenance issues in closed-loop supply chains with remanufacturing
Abstract: 
 The design of reverse logistics and remanufacturing processes and the recovery of end-of-life products have been well-studied in the literature. Quality, reliability, maintenance and warranty for recovered products and the remanufacturing activities that extend their life are integral issues in reverse logistics. This paper reviews recent and relevant literature on these issues in closed-loop supply chains, with a focus on remanufactured or second-hand products. The published literature is first classified into domain areas of research and practice. The wide array of mathematical tools and techniques used in the literature are then identified and mapped. Finally, the findings are summarised and the main research gaps are highlighted.
Journal: International Journal of Production Research
Pages: 1277-1296
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1200152
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1200152
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:5:p:1277-1296




Template-Type: ReDIF-Article 1.0
Author-Name: Alfred Theorin
Author-X-Name-First: Alfred
Author-X-Name-Last: Theorin
Author-Name: Kristofer Bengtsson
Author-X-Name-First: Kristofer
Author-X-Name-Last: Bengtsson
Author-Name: Julien Provost
Author-X-Name-First: Julien
Author-X-Name-Last: Provost
Author-Name: Michael Lieder
Author-X-Name-First: Michael
Author-X-Name-Last: Lieder
Author-Name: Charlotta Johnsson
Author-X-Name-First: Charlotta
Author-X-Name-Last: Johnsson
Author-Name: Thomas Lundholm
Author-X-Name-First: Thomas
Author-X-Name-Last: Lundholm
Author-Name: Bengt Lennartson
Author-X-Name-First: Bengt
Author-X-Name-Last: Lennartson
Title: An event-driven manufacturing information system architecture for Industry 4.0
Abstract: 
 Future manufacturing systems need to be more flexible, to embrace tougher and constantly changing market demands. They need to make better use of plant data, ideally utilising all data from the entire plant. Low-level data should be refined to real-time information for decision-making, to facilitate competitiveness through informed and timely decisions. The Line Information System Architecture (LISA), is presented in this paper. It is an event-driven architecture featuring loose coupling, a prototype-oriented information model and formalised transformation services. LISA is designed to enable flexible factory integration and data utilisation. The focus of LISA is on integration of devices and services on all levels, simplifying hardware changes and integration of new smart services as well as supporting continuous improvements on information visualisation and control. The architecture has been evaluated on both real industrial data and industrial demonstrators and it is also being installed at a large automotive company. This article is an extended and revised version of the paper presented at the 2015 IFAC Symposium on Information Control in Manufacturing (INCOM 2015). The paper has been restructured in regards to the order and title of the chapters, and additional information about the integration between devices and services aspects have been added. The introduction and the general structure of the paper now better highlight the contributions of the paper and the uniqueness of the framework.
Journal: International Journal of Production Research
Pages: 1297-1311
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1201604
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1201604
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Template-Type: ReDIF-Article 1.0
Author-Name: Samira Keivanpour
Author-X-Name-First: Samira
Author-X-Name-Last: Keivanpour
Author-Name: Daoud Ait-Kadi
Author-X-Name-First: Daoud
Author-X-Name-Last: Ait-Kadi
Author-Name: Christian Mascle
Author-X-Name-First: Christian
Author-X-Name-Last: Mascle
Title: Automobile manufacturers’ strategic choice in applying green practices: joint application of evolutionary game theory and fuzzy rule-based approach
Abstract: 
 Satisfying the end-of-life vehicle (ELV) legislations is essential for business activities in some markets. However, with the lack of similar regulations for the treatment of ELV, automotive manufacturers follow different green practices. These practices can be a complex task such as an eco-design strategy or issuing a guideline or manual for the end-of-life phase of the product. Each of these practices also has different impacts on the other players in the market. Several factors contribute to manufacturers’ gain as a result of applying green practices. The uncertainties in these features and the absence of data availability raise the difficulty in the manufacturers’ profit estimation. This paper proposes a new approach to analysing automotive manufacturers’ strategic choice in applying ELV practices considering the competitive advantages of performing these practices and the interaction between players. A joint application of evolutionary game theory and fuzzy rule-based approach is proposed to analyse the strategic behaviour of automotive manufacturers. The proposed model provides a simulation environment for testing the interaction of the different market factors and players’ action. The experimental design highlights the validity of the model and its implications. The result reveals that when we have two populations of players including the market leader in recycling initiatives and market reader; the market elements such as ‘elasticity of demand to price’ and ‘loyalty of consumers to market leader’ play an essential role in determining the stable strategy of the game.
Journal: International Journal of Production Research
Pages: 1312-1335
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1203077
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1203077
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Template-Type: ReDIF-Article 1.0
Author-Name: Emanuele Dovere
Author-X-Name-First: Emanuele
Author-X-Name-Last: Dovere
Author-Name: Sergio Cavalieri
Author-X-Name-First: Sergio
Author-X-Name-Last: Cavalieri
Author-Name: Stefano Ierace
Author-X-Name-First: Stefano
Author-X-Name-Last: Ierace
Title: RFId systems for moveable asset management: an assessment model
Abstract: 
 Management of moveable assets is a key issue in most industrial manufacturing companies. With the increasing complexity of production systems characterised by numerous and heterogeneous machining centres, it becomes quite hard to carry out an effective and cost-efficient management model of the tools and fixtures needed for ensuring a correct and timely execution of the planned production cycles. A prerequisite for a proper management of moveable assets is the adoption of identification systems to support the traceability and data collection of the most relevant pieces of information along the life cycle of an asset. The aim of this paper was to provide an assessment model for evaluating the benefits and costs related to the adoption of RFId tags as identifications systems for moveable assets, and in particular in managing machinery tools in a production premise. In order to present a practical example of applicability of the model, an industrial application is reported with an in-depth analysis of the potential benefits and issues derived from the implementation of RFId tags.
Journal: International Journal of Production Research
Pages: 1336-1349
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1207818
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1207818
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:5:p:1336-1349




Template-Type: ReDIF-Article 1.0
Author-Name: SangJe Cho
Author-X-Name-First: SangJe
Author-X-Name-Last: Cho
Author-Name: Hong-Bae Jun
Author-X-Name-First: Hong-Bae
Author-X-Name-Last: Jun
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Heuristic algorithms for maximising the total profit of end-of-life computer remanufacturing
Abstract: 
 Recently the optimisation of end-of-life (EOL) computer remanufacturing has been highlighted since a big amount of used computers have been disposed of every year. Each part inspected after disassembling EOL computers can have various EOL options such as reuse, repair, reconditioning and so on. Depending on EOL options, recovered values and costs of parts will be different. Hence, in order to maximise the profit of remanufactured computers, it is important to develop the method as to how to decide the EOL options of computer parts. To this end, this study deals with a decision-making problem to select the best EOL option policy of the computer parts for maximising the total profit of computer remanufacturing considering its incurred costs and demand of remanufactured computers during multiple production periods. In particular, to maximise the total profit, the conditional repair option is newly proposed. To resolve the problem, a genetic search algorithm and an ant colony search algorithm have been developed. Computational experiments have carried out to evaluate the algorithms and the proposed conditional repair option.
Journal: International Journal of Production Research
Pages: 1350-1367
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1211341
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1211341
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:5:p:1350-1367




Template-Type: ReDIF-Article 1.0
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Nikolai Guschinsky
Author-X-Name-First: Nikolai
Author-X-Name-Last: Guschinsky
Title: Decision support for design of reconfigurable rotary machining systems for family part production
Abstract: 
 To remain competitive in currently unpredictable markets, the enterprises must adapt their manufacturing systems to frequent market changes and high product variety. Reconfigurable manufacturing systems (RMSs) promise to offer a rapid and cost-effective response to production fluctuations under the condition that their configuration is attentively studied and optimised. This paper presents a decision support tool for designing reconfigurable machining systems to be used for family part production. The objective is to elaborate a cost-effective solution for production of several part families. This design issue is modelled as a combinatorial optimisation problem. An illustrative example and computational experiments are discussed to reveal the application of the proposed methodology. Insight gained would be useful to the decision-makers managing the configuration of manufacturing systems for diversified products.
Journal: International Journal of Production Research
Pages: 1368-1385
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1213451
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213451
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Template-Type: ReDIF-Article 1.0
Author-Name: Laura Macchion
Author-X-Name-First: Laura
Author-X-Name-Last: Macchion
Author-Name: Rosanna Fornasiero
Author-X-Name-First: Rosanna
Author-X-Name-Last: Fornasiero
Author-Name: Andrea Vinelli
Author-X-Name-First: Andrea
Author-X-Name-Last: Vinelli
Title: Supply chain configurations: a model to evaluate performance in customised productions
Abstract: 
 This paper describes an approach used to evaluate the performance of different supply chain configurations in customised contexts. Based on historical data collected from the supply chain of a shoe producer, different configurations are evaluated based on a discrete-event simulation by highlighting the performance of the supply chain (in terms of supply chain order lead-time and inventory volume) when the production switched from standard production (characterised by batches of large quantities of the same product) to customised production (characterised by a small of series batches with high product variability). The simulation approach relies on experimentation through executable configurations, which enables the creation of different scenarios, and is then applied to the case of an actual firm in the footwear industry. The managerial implications of these findings are discussed.
Journal: International Journal of Production Research
Pages: 1386-1399
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1221161
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1221161
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:5:p:1386-1399




Template-Type: ReDIF-Article 1.0
Author-Name: Tomás S. Harrington
Author-X-Name-First: Tomás S.
Author-X-Name-Last: Harrington
Author-Name: Mark A. Phillips
Author-X-Name-First: Mark A.
Author-X-Name-Last: Phillips
Author-Name: Jagjit Singh Srai
Author-X-Name-First: Jagjit Singh
Author-X-Name-Last: Srai
Title: Reconfiguring global pharmaceutical value networks through targeted technology interventions
Abstract: 
 Targeting a series of advanced manufacturing technology (AMT) ‘interventions’ provides the potential for significant step changes across the pharmaceutical value chain, from early stage ‘system discovery’ and clinical trials, through to novel service supply models. This research explores future value network configurations which, when aligned with disruptive shifts in technology (process and digital), may enable alternative routes to medicines production and the delivery of additional value to ‘end-users’, i.e. patients and health care providers. We draw on a categorisation of AMTs that may enable a shift from the traditional ‘batch’ and centralised manufacturing paradigm of ‘make-to-stock’, towards more re-distributed ‘continuous’ manufacturing and ‘make-to-order’ models. Despite reported benefits in the academic literature (e.g. reduced footprints, improved quality, enhanced flexibility and inventory savings), current adoption rates of continuous technologies in this sector remain low (c. 5%). This paper presents new data sources, in our study of AMT adoption in a global pharmaceutical context – assessing the barriers to implementation, and the pathways to delivering future continuous manufacturing scenarios. Our findings capture the high level of disparity in viewpoints, highlighting the uncertainties and transformational challenges ahead – in terms of opportunity areas, technological readiness and a future vision for the sector, as a whole.
Journal: International Journal of Production Research
Pages: 1471-1487
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1221541
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1221541
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Template-Type: ReDIF-Article 1.0
Author-Name: Ahmed M. Deif
Author-X-Name-First: Ahmed M.
Author-X-Name-Last: Deif
Author-Name: Hoda A. ElMaraghy
Author-X-Name-First: Hoda A.
Author-X-Name-Last: ElMaraghy
Title: Variety and volume dynamic management for value creation in changeable manufacturing systems
Abstract: 
 In today’s uncertain market and continuously evolving technology, managing manufacturing systems are more complex than ever. This paper studies the dynamics of managing variety and volume to enhance value creation in manufacturers implementing system-level advanced and automated manufacturing technology (AAMT). The demand is composed of heterogeneous customers who make purchasing decisions depending on the variety levels and lead times of the firm’s product offerings. The cost structure adopted calculates profit as the difference between customer value creation rate (VCR) and costs associated with the process of creating this value. Reported results contribute to the variety and volume management literature by offering analytical clarity of factors affecting product platforms and capacity scalability management for systems with AAMT. In addition, insightful answers to the trade-offs between profit maximising market coverage and investments, smoothing demand policies and system stability for this type of environment are presented. Furthermore, the value of market information in deciding the industrial technology investment and also the impact of product life cycle on the same investment is captured.
Journal: International Journal of Production Research
Pages: 1516-1529
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1222088
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1222088
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Template-Type: ReDIF-Article 1.0
Author-Name: Mahesh Mani
Author-X-Name-First: Mahesh
Author-X-Name-Last: Mani
Author-Name: Brandon M. Lane
Author-X-Name-First: Brandon M.
Author-X-Name-Last: Lane
Author-Name: M. Alkan Donmez
Author-X-Name-First: M. Alkan
Author-X-Name-Last: Donmez
Author-Name: Shaw C. Feng
Author-X-Name-First: Shaw C.
Author-X-Name-Last: Feng
Author-Name: Shawn P. Moylan
Author-X-Name-First: Shawn P.
Author-X-Name-Last: Moylan
Title: A review on measurement science needs for real-time control of additive manufacturing metal powder bed fusion processes
Abstract: 
 Additive manufacturing technologies are increasingly used in the development of new products. However, variations in part quality in terms of material properties, dimensional tolerances, surface roughness and defects limit its broader acceptance. Process control today based on heuristics and experimental data yields limited improvement in part quality. In an effort to identify the needed measurement science for real-time closed-loop control of additive manufacturing (AM) processes, this paper presents a literature review on the current AM control schemes, process measurements and modelling and simulation methods as it applies to the powder bed fusion process, though results from other processes are reviewed where applicable. We present our research findings to identify the correlations between process parameters, process signatures and product quality. We also present research recommendations on the key control issues to serve as a technical basis for standards development in this area. Complimentary details to this paper with summary tables, range of values, preliminary correlations and correlation figures can be accessed from a National Institute of Standards and Technology Report (http://nvlpubs.nist.gov/nistpubs/ir/2015/NIST.IR.8036.pdf). This paper is developed based on the report.
Journal: International Journal of Production Research
Pages: 1400-1418
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1223378
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1223378
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Template-Type: ReDIF-Article 1.0
Author-Name: Mojtaba Khorram Niaki
Author-X-Name-First: Mojtaba
Author-X-Name-Last: Khorram Niaki
Author-Name: Fabio Nonino
Author-X-Name-First: Fabio
Author-X-Name-Last: Nonino
Title: Additive manufacturing management: a review and future research agenda
Abstract: 
 Based on the phenomenal changes that additive manufacturing (AM) has brought to industries and markets, managerial approaches should be re-examined and developed to take advantage of emerging opportunities. This revolutionary technology is dramatically changing business and innovation models, shrinking supply chains and altering the global economy. For example, 3D printing shifts production locations closer to customers and leads to free-form product design as well as sustainable manufacturing. Several studies have been conducted on AM technology, but the research stream on AM management is still developing, with studies dispersed in journals across different research areas. Our study presents both systematic and quantitative analyses of the literature, including co-citation analysis, factor analysis and multidimensional scaling, to explore the structure of the AM research domains in the scope of management, business and economics. We found eight main research streams: AM technology selection, supply chain, product design and production cost models, environmental aspects, strategic challenges, manufacturing systems, open-source innovation and business models and economics. Finally, based on the results of our in-depth analysis of the literature, we found nine promising future research directions.
Journal: International Journal of Production Research
Pages: 1419-1439
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1229064
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1229064
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Template-Type: ReDIF-Article 1.0
Author-Name: Yao Li
Author-X-Name-First: Yao
Author-X-Name-Last: Li
Author-Name: Guozhu Jia
Author-X-Name-First: Guozhu
Author-X-Name-Last: Jia
Author-Name: Yang Cheng
Author-X-Name-First: Yang
Author-X-Name-Last: Cheng
Author-Name: Yuchen Hu
Author-X-Name-First: Yuchen
Author-X-Name-Last: Hu
Title: Additive manufacturing technology in spare parts supply chain: a comparative study
Abstract: 
 Additive Manufacturing (AM) technology has the potential to significantly improve supply chain dynamics. The purpose of this paper is to investigate the impact of AM on spare parts supply chain. Three supply chain scenarios are investigated in this paper, namely conventional supply chain, centralised AM-based supply chain and distributed AM-based supply chain. Based on system dynamics simulations, this paper specifically compares three supply chain scenarios, in terms of total variable cost and carbon emission. The results show the spare part supply chain utilising AM is indeed superior to the traditional one in sustainable performance. It is also expected that AM can facilitate the spare parts supply chain to achieve more economic benefits along with its development. To our knowledge, this paper is one of the early studies that explores the impact of AM on supply chain performance and quantitatively examines the superiority of utilising AM in spare parts supply chain. Some suggestions are also provided to help managers adopting AM in their spare parts supply chains.
Journal: International Journal of Production Research
Pages: 1498-1515
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1231433
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1231433
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Template-Type: ReDIF-Article 1.0
Author-Name: Moustafa Gadalla
Author-X-Name-First: Moustafa
Author-X-Name-Last: Gadalla
Author-Name: Deyi Xue
Author-X-Name-First: Deyi
Author-X-Name-Last: Xue
Title: Recent advances in research on reconfigurable machine tools: a literature review
Abstract: 
 A recent trend in research on reconfigurable manufacturing systems is the development of reconfigurable machine tools (RMTs). A RMT can be used as a group of machines through change of its configuration to satisfy different manufacturing requirements. A literature review is provided in this paper to demonstrate the state-of-the-art advances and challenges on research and development of RMTs from the perspectives of architecture design, configuration design and optimisation, and system integration and control. In architecture design, semi-open and open architectures based on modular design approach are often selected to allow different modules of the machine to be added and removed. In configuration design and optimisation, operations of reconfiguration processes are analysed and optimised to achieve variety of configurations with the minimum reconfiguration effort. In system integration and control, transfers of motion, energy and data among different modules of the RMT are carried out. The challenges in research on RMTs are also discussed.
Journal: International Journal of Production Research
Pages: 1440-1454
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1237795
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1237795
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Template-Type: ReDIF-Article 1.0
Author-Name: Lilian Adriana Borges
Author-X-Name-First: Lilian Adriana
Author-X-Name-Last: Borges
Author-Name: Kim Hua Tan
Author-X-Name-First: Kim Hua
Author-X-Name-Last: Tan
Title: Incorporating human factors into the AAMT selection: a framework and process
Abstract: 
 Human factors such as employee morale and workers skills greatly influence the successful adoption of automated and advanced manufacturing technologies. For newly industrialised countries, the evaluation of these factors before technology selection is particularly paramount. Countries such as Brazil are in the critical early stages of technology adoption and low rates of secondary education and scarcity of technicians reinforce the importance of assessing human factors before the actual technology implementation. Although methods have been proposed to evaluate intangible aspects, the lack of a structured approach to identify and quantify human factors still constitutes a major hurdle. The paper describes a framework and process to assist managers in identifying and evaluating human factors in the selection. The approach was tested in eight companies in Brazil. The results indicated that the main advantages of the proposed approach are: (a) provide a comprehensive justification of technology adoption by identifying and quantifying intangible aspects; and (b) supply a practical process to be incorporated into the selection decision-making process.
Journal: International Journal of Production Research
Pages: 1459-1470
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1259668
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1259668
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Template-Type: ReDIF-Article 1.0
Author-Name: Yunguang Long
Author-X-Name-First: Yunguang
Author-X-Name-Last: Long
Author-Name: Jieyi Pan
Author-X-Name-First: Jieyi
Author-X-Name-Last: Pan
Author-Name: Qinghui Zhang
Author-X-Name-First: Qinghui
Author-X-Name-Last: Zhang
Author-Name: Yingjie Hao
Author-X-Name-First: Yingjie
Author-X-Name-Last: Hao
Title: 3D printing technology and its impact on Chinese manufacturing
Abstract: 
 For both developed and developing countries, manufacturing plays a crucial role in international competition. There is a growing consensus that 3D printing (3DP) technologies will revolutionise the development of global manufacturing. Although considerable research has previously been conducted to define the technological and economic benefits of 3DP on global manufacturing, minimal research has linked 3DP with Chinese manufacturing (CM). Therefore, to address this research gap and to investigate 3DP’s potential impact on alleviating CM’s development issues, this paper explores the definition, characteristics and mainstream technologies of 3DP, presents the current situation and the main problems of CM, and analyses the potential impact of 3DP on the development of CM. Then, this study introduces the current 3DP promotion and industrialisation situation in China as well as the issues with promoting 3DP in CM.
Journal: International Journal of Production Research
Pages: 1488-1497
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2017.1280196
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1280196
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Template-Type: ReDIF-Article 1.0
Author-Name: Sami Farooq
Author-X-Name-First: Sami
Author-X-Name-Last: Farooq
Author-Name: Yang Cheng
Author-X-Name-First: Yang
Author-X-Name-Last: Cheng
Author-Name: Rikke Vestergaard Matthiesen
Author-X-Name-First: Rikke
Author-X-Name-Last: Vestergaard Matthiesen
Author-Name: John Johansen
Author-X-Name-First: John
Author-X-Name-Last: Johansen
Author-Name: Chris O’Brien
Author-X-Name-First: Chris
Author-X-Name-Last: O’Brien
Title: Management of automation and advanced manufacturing technology (AAMT) in the context of global manufacturing
Journal: International Journal of Production Research
Pages: 1455-1458
Issue: 5
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2017.1296205
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1296205
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Juan Ding
Author-X-Name-First: Ming Juan
Author-X-Name-Last: Ding
Author-Name: Booi H. Kam
Author-X-Name-First: Booi H.
Author-X-Name-Last: Kam
Author-Name: Jia Ying Zhang
Author-X-Name-First: Jia Ying
Author-X-Name-Last: Zhang
Author-Name: Ferry Jie
Author-X-Name-First: Ferry
Author-X-Name-Last: Jie
Title: Effects of human resource management practices on logistics and supply chain competencies – evidence from China logistics service market
Abstract: 
 The Chinese logistics service market is a vibrant and highly contested arena. The industry, however, has been characterised as operationally inefficient in comparison with those of the developed economies. Shortage of logistics human resources and lack of logistics expertise have been identified as two of the key contributory factors. Based on responses from 76 Chinese logistics service providers to a survey conducted in 2010, this study explores whether, and how, four sets of human resource management (HRM) practices contribute to nurturing three logistics and supply chain (L&amp;SC) competencies in the Chinese logistics service market. Results from a hierarchical multiple regression analysis show that not all HRM practices were equally effective in building L&amp;SC competencies. While training and development, and recruitment and selection were significant in contributing to nurturing the three L&amp;SC competencies, both performance management and reward management did not. These findings suggest that conventional HRM practices designed to reward individual performance may not be suited to nurturing team-based L&amp;SC competencies in the Chinese context. The implications of these findings were discussed and directions for further studies offered.
Journal: International Journal of Production Research
Pages: 2885-2903
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.946569
File-URL: http://hdl.handle.net/10.1080/00207543.2014.946569
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:2885-2903




Template-Type: ReDIF-Article 1.0
Author-Name: Vijaya Dixit
Author-X-Name-First: Vijaya
Author-X-Name-Last: Dixit
Author-Name: Rajiv Srivastava K.
Author-X-Name-First: Rajiv
Author-X-Name-Last: Srivastava K.
Author-Name: Atanu Chaudhuri
Author-X-Name-First: Atanu
Author-X-Name-Last: Chaudhuri
Title: Project network-oriented materials management policy for complex projects: a Fuzzy Set Theoretic approach
Abstract: 
 This work devises a materials management policy integrated with project network characteristics of complex projects. It proposes a relative quantitative measure, overall criticality (OC), for prioritisation of items based on penalty incurred due to their non-availability. In complex projects, practicing managers find it difficult to measure OC of items because of the subjective factors and intractable nature of penalties involved. However, using their experience, they can linguistically identify the antecedents and relate them to consequent OC. This work adopts Fuzzy Set Theory to capture managerial tacit knowledge which provides them enough flexibility to provide information in real form. Computed OC values can be used for items prioritisation and as shortage cost coefficient in inventory models. The revised materials management policy was applied to a shipbuilding project. OC values were analysed to justify the importance of incorporating project network characteristics and potential cost savings were calculated.
Journal: International Journal of Production Research
Pages: 2904-2920
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.948971
File-URL: http://hdl.handle.net/10.1080/00207543.2014.948971
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Template-Type: ReDIF-Article 1.0
Author-Name: Shanshan Ma
Author-X-Name-First: Shanshan
Author-X-Name-Last: Ma
Author-Name: Jie Lin
Author-X-Name-First: Jie
Author-X-Name-Last: Lin
Author-Name: Wei Xing
Author-X-Name-First: Wei
Author-X-Name-Last: Xing
Author-Name: Xuan Zhao
Author-X-Name-First: Xuan
Author-X-Name-Last: Zhao
Title: Advance booking discount in the presence of spot market
Abstract: 
 We consider a risk-neutral firm that can procure raw material via long-term contract as well as in spot market, using the material as a one-to-one input to produce a seasonal product and selling it in the customer market. The firm can use the advance booking discount (ABD) program to entice customers to place their orders prior to the selling season. The ABD program provides an opportunity for the firm to update its understanding of the regular demand and spot price. We separately analyse two cases: (NI) no information updating and (IU) information updating cases. In each case, we derive the optimal discount pricing strategy and corresponding expected profit of the firm. By comparing them, we investigate the value of information updating obtained from the pre-committed order. Among others, our study finds that if the product has a relatively high profit margin, or a low profit margin where the raw material spot price is more sensitive to the trading volume, it is optimal for the firm to implement the discount strategy. The optimal discount coefficient in the IU case is never lower than in the NI case. We further find that the optimal discount coefficient in the NI case decreases in spot market volatility; however, it increases in spot market volatility if and only if the firm’s market share is larger than half of the total market demand in the IU case.
Journal: International Journal of Production Research
Pages: 2921-2936
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.961204
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961204
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Template-Type: ReDIF-Article 1.0
Author-Name: Shukai Li
Author-X-Name-First: Shukai
Author-X-Name-Last: Li
Author-Name: Jianxiong Zhang
Author-X-Name-First: Jianxiong
Author-X-Name-Last: Zhang
Author-Name: Wansheng Tang
Author-X-Name-First: Wansheng
Author-X-Name-Last: Tang
Title: Joint dynamic pricing and inventory control policy for a stochastic inventory system with perishable products
Abstract: 
 This paper considers the joint dynamic pricing and inventory control policy for a stochastic inventory system with perishable products. The inventory system, with random disturbance, is modelled as a continuous-time stochastic differential equation. Combined dynamic pricing and production control, a stochastic dynamic optimisation problem that maximises the total discounted profit is developed. By applying the stochastic optimal control method, we formulate the problem of finding the optimal joint dynamic pricing and production schedule as the problem of solving a Hamilton–Jacobi–Bellman (HJB) equation. It is shown that the optimal dynamic pricing and production rate take the linear feedback form of the inventory level, which allows the decision-maker to effectively adjust the strategies as time evolves. In addition, to highlight the advantage of the joint dynamic pricing and production strategy, the case of the optimal production with static price is considered. Numerical examples are given to illustrate the validness of the theoretical results.
Journal: International Journal of Production Research
Pages: 2937-2950
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.961206
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961206
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Template-Type: ReDIF-Article 1.0
Author-Name: Fu-Hsiang Chen
Author-X-Name-First: Fu-Hsiang
Author-X-Name-Last: Chen
Title: Application of a hybrid dynamic MCDM to explore the key factors for the internal control of procurement circulation
Abstract: 
 Decisions related to the internal control measurement of procurement circulation are inherently multiple criteria decision-making problems and are strategically important to enterprises. Although efforts have been made to discover systematic methods for enhancing purchasing performance, the criteria have been assumed to be independent, which is not actually the case. Most conventional decision models cannot capture the complex interrelationships the criteria. Here, we propose a workable hybrid dynamic multiple criteria decision-making (HDMCDM) method to solve the problems arising from the complex dynamics in the real world. The relationship between the criteria and the criteria weights for the HDMCDM are developed by combining the decision-making trial and evaluation laboratory (DEMATEL) method with the fundamental concept of the analytic network process (ANP), the DEMATEL-based ANP (DANP). VlseKriterijumska Optimizacija I Kompromisno Resenje is then used to aggregate the performance gaps with the weights obtained from the DANP. The results obtained for a specific company show that the four dimensions of internal control of procurement circulation have a mutual influence relationship, with the dimension of ‘receiving and storage’ demonstrating the greatest influence and ‘recorded liabilities’ the least. Empirical analysis helps to improve the scores for achieving the aspiration levels for each factor.
Journal: International Journal of Production Research
Pages: 2951-2969
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.961210
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961210
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:2951-2969




Template-Type: ReDIF-Article 1.0
Author-Name: Guanqun Ni
Author-X-Name-First: Guanqun
Author-X-Name-Last: Ni
Author-Name: Yinfeng Xu
Author-X-Name-First: Yinfeng
Author-X-Name-Last: Xu
Author-Name: Jiuping Xu
Author-X-Name-First: Jiuping
Author-X-Name-Last: Xu
Author-Name: Yucheng Dong
Author-X-Name-First: Yucheng
Author-X-Name-Last: Dong
Title: Optimal decisions for fixed-price group-buying business originated in China: a game theoretic perspective
Abstract: 
 In this paper, we study a new group-buying mechanism originated in China where the new mechanism adopts a fixed group price rather than a dynamic pricing mechanism. We employ a sensitive parameter α$ \alpha $, reflecting the initial customer’s seeking and communication cost and formulate this new group-buying business as a game model. First, we formulate the basic model as a Stackelberg game where the website is the leader and the seller is the follower. Our result shows that the group-buying mechanism is more efficient when the value of α$ \alpha $ is smaller, and there is also an upper bound for α$ \alpha $ to adopt group-buying mechanism. Second, we establish three other group-buying game structures by considering different market power between the website and the seller. By comparing the maximum revenues and optimal decisions obtained under different market structures, some interesting and valuable managerial insights are established such that when to adopt a group-buying mechanism or a non-group-buying mechanism and how to make a decision optimally based on adopted mechanism.
Journal: International Journal of Production Research
Pages: 2995-3005
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.965350
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965350
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:2995-3005




Template-Type: ReDIF-Article 1.0
Author-Name: Varun Gupta
Author-X-Name-First: Varun
Author-X-Name-Last: Gupta
Author-Name: Bo He
Author-X-Name-First: Bo
Author-X-Name-Last: He
Author-Name: Suresh P. Sethi
Author-X-Name-First: Suresh P.
Author-X-Name-Last: Sethi
Title: Contingent sourcing under supply disruption and competition
Abstract: 
 With the increasing awareness of the serious consequences of supply disruption risk, firms adopt various kinds of strategies to mitigate it. We consider a supply chain in which two suppliers sell components to two competing manufacturers producing and selling substitutable products. Supplier U is unreliable and cheap, while Supplier R is reliable and expensive. Firm C uses a contingent dual-sourcing strategy and Firm S uses a single-sourcing strategy. We study the implications of the contingent sourcing strategy under competition and in the presence of a possible supply disruption. The time of the occurrence of the supply disruption is uncertain and exogenous, but the procurement time of components is in the control of the firms. We show that supply disruption and procurement times jointly impact the firms’ buying decisions. We characterise the firms’ optimal order quantities and their expected profits under different cases. Subsequently, through numerical computations, we obtain additional managerial insights. Finally, as extensions, we study the impact endogenizing equilibrium sourcing strategies of asymmetric and symmetric firms, and of capacity reservation by Firm C with Supplier R to mitigate disruption.
Journal: International Journal of Production Research
Pages: 3006-3027
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.965351
File-URL: http://hdl.handle.net/10.1080/00207543.2014.965351
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Template-Type: ReDIF-Article 1.0
Author-Name: Dominik Eckstein
Author-X-Name-First: Dominik
Author-X-Name-Last: Eckstein
Author-Name: Matthias Goellner
Author-X-Name-First: Matthias
Author-X-Name-Last: Goellner
Author-Name: Constantin Blome
Author-X-Name-First: Constantin
Author-X-Name-Last: Blome
Author-Name: Michael Henke
Author-X-Name-First: Michael
Author-X-Name-Last: Henke
Title: The performance impact of supply chain agility and supply chain adaptability: the moderating effect of product complexity
Abstract: 
 Even though research has suggested that supply chain agility and supply chain adaptability are distinct capabilities, little is known about their performance effects and about the contextual conditions under which they are effective. Based on a sample of 143 German firms, we empirically investigate the effects of supply chain agility and supply chain adaptability on cost performance and operational performance using hierarchical regression analysis. We ground our investigation in the dynamic capabilities view and contingency theory. We find that supply chain agility and supply chain adaptability positively affect both cost performance and operational performance. We further find evidence for a mediating role of supply chain agility in the links between supply chain adaptability and performance. Product complexity positively moderates the links between supply chain adaptability and cost performance, and supply chain adaptability and operational performance. The results contribute to the literature by offering a more nuanced understanding of the performance implications of supply chain agility and supply chain adaptability, thereby addressing the crucial question of why their benefits may or may not materialise under varying levels of product complexity.
Journal: International Journal of Production Research
Pages: 3028-3046
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.970707
File-URL: http://hdl.handle.net/10.1080/00207543.2014.970707
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Template-Type: ReDIF-Article 1.0
Author-Name: Hadi Sahebi
Author-X-Name-First: Hadi
Author-X-Name-Last: Sahebi
Author-Name: Stefan Nickel
Author-X-Name-First: Stefan
Author-X-Name-Last: Nickel
Author-Name: Jalal Ashayeri
Author-X-Name-First: Jalal
Author-X-Name-Last: Ashayeri
Title: Joint venture formation and partner selection in upstream crude oil section: goal programming application
Abstract: 
 In the past three decades, the magnitude of business dynamics has increased rapidly due to increased complexity, uncertainty and risk of international projects. This fact made it increasingly tough to ‘go alone’ into the international projects. As a consequence, companies with diverse strengths and weaknesses cooperatively bid for joint ventures (JV) formation. Joint venture is also a well-established aspect of the crude oil industry, specifically in the upstream segment. Making decision on the optimal form of JVs is still a challenging problem. In addition, the success of a JV is intertwined with the accuracy of the partner selection phase. Therefore, this paper formulates a multi-criteria mathematical model to select the best partners and form an optimal JV for undertaking oilfield projects. The lexicographic goal programming technique is employed to minimise undesirable deviations from diverse goals such as resources needs (technological and expertise), budgetary requirements, time, etc. The model is validated with a real-life-based example and provides insightful views on alternative formats of cooperation.
Journal: International Journal of Production Research
Pages: 3047-3061
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.970708
File-URL: http://hdl.handle.net/10.1080/00207543.2014.970708
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:3047-3061




Template-Type: ReDIF-Article 1.0
Author-Name: Umit S. Bititci
Author-X-Name-First: Umit S.
Author-X-Name-Last: Bititci
Author-Name: Patrizia Garengo
Author-X-Name-First: Patrizia
Author-X-Name-Last: Garengo
Author-Name: Aylin Ates
Author-X-Name-First: Aylin
Author-X-Name-Last: Ates
Author-Name: Sai S. Nudurupati
Author-X-Name-First: Sai S.
Author-X-Name-Last: Nudurupati
Title: Value of maturity models in performance measurement
Abstract: 
 Over the last 20 years, the field of performance measurement (PM) has evolved from measurement to management. Investigations demonstrated the relevance of PM in management of organisations’ results. Although maturity model concept was widely used, the value of maturity models in PM has not been purposefully investigated. To address this gap, this research formulated three research questions: (1) How do maturity models in the field of performance measurement and management (PM&amp;M) add value in practice? (2) How do such maturity models compliment and/or replicate the value added by an expert? (3) How do maturity models contribute to the development of the organisation’s PM&amp;M practices? Using a predefined research protocol, 12 European manufacturing organisations and independent experts were engaged in conducting two separate studies: (1) the experts conducted reviews with 12 companies using a standard business review format; (2) research team adopted one of the available maturity models and facilitated self-assessments with the management teams of the same 12 companies. Results from both the studies were compared and high levels of congruence were identified. The analysis demonstrates that the maturity models with certain characteristics, promote organisational learning as well as enabling efficient and effective assessment of the performance management practices of the organisations.
Journal: International Journal of Production Research
Pages: 3062-3085
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.970709
File-URL: http://hdl.handle.net/10.1080/00207543.2014.970709
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Template-Type: ReDIF-Article 1.0
Author-Name: ShiJie Ye
Author-X-Name-First: ShiJie
Author-X-Name-Last: Ye
Author-Name: Zhi Xiao
Author-X-Name-First: Zhi
Author-X-Name-Last: Xiao
Author-Name: Guangfu Zhu
Author-X-Name-First: Guangfu
Author-X-Name-Last: Zhu
Title: Identification of supply chain disruptions with economic performance of firms using multi-category support vector machines
Abstract: 
 From a practical perspective, a novel method using multi-category support vector machines (MC-SVM) is proposed to identify supply chain disruptions (SCD). With the data related to economic performance from quarter statements and individual announcements published by the listed firms, the variables of MC-SVM are constructed firstly. Secondly, MC-SVM is used for matching the portfolios of firms, which helps the map from economic performance to SCD by applying MC-SVM again. Finally, a case study is given to testify the ability of proposed method with the data from the listed firms in China.
Journal: International Journal of Production Research
Pages: 3086-3103
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.974838
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974838
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:3086-3103




Template-Type: ReDIF-Article 1.0
Author-Name: Hassan Shavandi
Author-X-Name-First: Hassan
Author-X-Name-Last: Shavandi
Author-Name: Siavash Valizadeh Khaki
Author-X-Name-First: Siavash
Author-X-Name-Last: Valizadeh Khaki
Author-Name: Majid Khedmati
Author-X-Name-First: Majid
Author-X-Name-Last: Khedmati
Title: Parallel importation and price competition in a duopoly supply chain
Abstract: 
 Nowadays, diversion of products distribution from authorised channels to the gray markets is one of the main challenges of manufacturers. Suppose an international supplier distributes the products in several countries with different prices. In parallel importation, there are unauthorised distributers who supply products with a lower price and import them to a higher price market. The problem of parallel importation considering a manufacturer and a competitor is analysed using the game theory approach in this article. We investigate the pricing strategy for manufacturers and the effect of unauthorised distributer on price, market share and profit. We also investigate the performance of different policies in a numerical study and show managerial insights.
Journal: International Journal of Production Research
Pages: 3104-3119
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.974841
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974841
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:3104-3119




Template-Type: ReDIF-Article 1.0
Author-Name: Y.T. Chen
Author-X-Name-First: Y.T.
Author-X-Name-Last: Chen
Author-Name: F.T.S. Chan
Author-X-Name-First: F.T.S.
Author-X-Name-Last: Chan
Author-Name: S.H. Chung
Author-X-Name-First: S.H.
Author-X-Name-Last: Chung
Title: An integrated closed-loop supply chain model with location allocation problem and product recycling decisions
Abstract: 
 Environmental pollutions caused by improper abandoned cartridges increase dramatically nowadays. In Hong Kong, due to abundant quantity of cartridges being used, producers have to optimise their forward and reverse networks to maximise the recycling rate and their profits. In this paper, a comprehensive closed-loop supply chain (CLSC) model is established. This model contains eight partners in CLSC and describes the existing cartridge recycling situation in Hong Kong. In the literatures, many CLSC models were established and studied, but few of them analysed the delivery activity for different kinds of materials extracted from the used products and also, few papers studied the situation that used products are classified into good and poor quality. In this model, delivery activities of different materials are considered and the used cartridges are classified into good-quality ones and poor-quality ones. Producers will have different methods to process them. This problem is formulated into an Integer programming model. Since both delivery routes and delivery quantities problems are known to be NP hard, a novel modified two-stage genetic algorithm (GA) is proposed. A new two-stage encoding algorithm in the proposed GA reinforces the genetic searching ability in tackling this kind of problem. As the model is new in literature, we used Integer Programming to solve the testing instances and benchmark with the proposed algorithm. The results show that a near-optimal solution can be obtained by the proposed GA in a much shorter computational time.
Journal: International Journal of Production Research
Pages: 3120-3140
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.975849
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975849
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Template-Type: ReDIF-Article 1.0
Author-Name: Pan Zhang
Author-X-Name-First: Pan
Author-X-Name-Last: Zhang
Author-Name: Yu Xiong
Author-X-Name-First: Yu
Author-X-Name-Last: Xiong
Author-Name: Zhongkai Xiong
Author-X-Name-First: Zhongkai
Author-X-Name-Last: Xiong
Title: Coordination of a dual-channel supply chain after demand or production cost disruptions
Abstract: 
 Coordinating a dual-channel supply chain could not only achieve the integrated profit of the supply chain but also alleviate the channel conflict. Although some researches addressed this area, there is scant literature to discuss the coordination issue in the situations of disruption. To fill this void, we utilise a contract with a wholesale price, a direct channel’s price and a lump sum fee to coordinate a dual-channel supply chain under the cases of demand disruptions and production cost disruptions. After deriving the optimal contract for each case, we find that the manufacturer can achieve coordination of the disrupted supply chain by adjusting the parameters of the coordination contract used in a normal environment. We also show that after disruptions, there exists a contract adjustment benefit zone, in which both the manufacturer and the retailer can benefit from the adjustment of coordination contract when demand increases or production cost decreases. A further analysis of the production and distribution strategies in the coordinated dual-channel supply chain after disruptions suggests that the adjustment of the total production and sales of each channel depends heavily on the level of disruptions and the degree of consumers’ loyalty to both channels.
Journal: International Journal of Production Research
Pages: 3141-3160
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.975853
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975853
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:3141-3160




Template-Type: ReDIF-Article 1.0
Author-Name: Yuming Xiao
Author-X-Name-First: Yuming
Author-X-Name-Last: Xiao
Title: Flexibility measure analysis of supply chain
Abstract: 
 This paper is intended to explore a new method of measuring supply chain flexibility from two dimensions (resources and time) when the supply chain is coordinated. Under the assumptions that the node enterprises’ marginal costs increase with their outputs, firstly this paper analyses the coordination problem of a supply chain with buyback contract, then formulates the resource allocation with the entropy concept in the case of supply chain coordination, puts forward the concepts of resource output elasticity and time output elasticity, analyses the resources’ dynamic matching problem from the two dimensions of resource and time in order to respond to the change of market demand. Finally, based on the above discussion, this paper proposes a method of measuring supply chain flexibility by integrating the resource flexibility and time flexibility. The method not only considers the resources and time required to respond the market’s change, but also takes into account the coordination relationship between the node enterprises.
Journal: International Journal of Production Research
Pages: 3161-3174
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.975864
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975864
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:3161-3174




Template-Type: ReDIF-Article 1.0
Author-Name: John Miltenburg
Author-X-Name-First: John
Author-X-Name-Last: Miltenburg
Title: Changes in manufacturing facility-, network-, and strategy-types at the Michelin North America Company from 1950 to 2014
Abstract: 
 Large manufacturing firms operate networks of facilities which they design to achieve particular manufacturing strategies. Facilities, networks and strategies are of several distinct types. The facility-, network- and strategy-types used by a firm depend on the competitive environment in which a firm operates. This paper examines the facility-, network- and strategy-types used by the Michelin North America Company during the period from 1950 to 2014. The examination shows how three changes in the competitive environment (changes in tariffs and government industrial policy, the 1964 Canada – United States Automotive Trade Agreement, and the 1996 North American Free Trade Agreement) triggered significant changes in these types. The examination produces insights into categorisations of facility-, network- and strategy-types that are useful for understanding how large firms operate, how we can predict what changes large firms will make to their facilities, network and strategy and how stakeholders such as employees, suppliers and governments can manage the risks of working with large firms.
Journal: International Journal of Production Research
Pages: 3175-3191
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.975865
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975865
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:3175-3191




Template-Type: ReDIF-Article 1.0
Author-Name: Nima Hamta
Author-X-Name-First: Nima
Author-X-Name-Last: Hamta
Author-Name: M. Akbarpour Shirazi
Author-X-Name-First: M.
Author-X-Name-Last: Akbarpour Shirazi
Author-Name: S.M.T. Fatemi Ghomi
Author-X-Name-First: S.M.T.
Author-X-Name-Last: Fatemi Ghomi
Author-Name: Sara Behdad
Author-X-Name-First: Sara
Author-X-Name-Last: Behdad
Title: Supply chain network optimization considering assembly line balancing and demand uncertainty
Abstract: 
 In supply chain optimisation problems, determining the location, number and capacity of facilities is concerned as strategic decisions, while mid-term and short-term decisions such as assembly policy, inventory levels and scheduling are considered as the tactical and operational decision levels. This paper addresses the optimisation of strategic and tactical decisions in the supply chain network design (SCND) under demand uncertainty. In this respect, a two-stage stochastic programming model is developed in which strategic location decisions are made in the first-stage, while the second-stage contains SCND problem and the assembly line balancing as a tactical decision. In the solution scheme, the combination of sample average approximation and Latin hypercube sampling methods is utilised to solve the developed two-stage mixed-integer stochastic programming model. Finally, computational experiments on randomly generated problem instances are presented to demonstrate the performance and power of developed model in handling uncertainty. Computational experiments showed that stochastic model yields better results compared with deterministic model in terms of objective function value, i.e. the sum of the first-stage costs and the expected second-stage costs. This issue proved that uncertainty would be a significant and fundamental element of developed model and improve the quality of solutions.
Journal: International Journal of Production Research
Pages: 2970-2994
Issue: 10
Volume: 53
Year: 2015
Month: 5
X-DOI: 10.1080/00207543.2014.978030
File-URL: http://hdl.handle.net/10.1080/00207543.2014.978030
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:2970-2994




Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Selected surveys on cutting edge problems in Production Research
Journal: International Journal of Production Research
Pages: 4621-4626
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2019.1639372
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1639372
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Template-Type: ReDIF-Article 1.0
Author-Name: Jersone Tasso Moreira Silva
Author-X-Name-First: Jersone Tasso Moreira
Author-X-Name-Last: Silva
Author-Name: Jose Humberto Ablanedo-Rosas
Author-X-Name-First: Jose Humberto
Author-X-Name-Last: Ablanedo-Rosas
Author-Name: Dennys Eduardo Rossetto
Author-X-Name-First: Dennys Eduardo
Author-X-Name-Last: Rossetto
Title: A longitudinal literature network review of contributions made to the academy over the past 55 years of the IJPR
Abstract: 
 The International Journal of Production Research (IJPR) first issue was published in 1961. This year commemorates the journal’s 55th year anniversary. In celebration of its anniversary, this article aims to comprehensively review the journals overall existence (1961–2017), per decade, by a longitudinal analysis of the literature through a main path analysis, and a bibliometric and social network overview. This paper differentiates from previous IJPR’s studies conducted by focusing on the journal’s social network analysis (SNA) by decades and overall period. This research article classiﬁes leading bibliographic material by using the total number of publications, citations, authors per work, country, author’s afﬁliation, funding agencies, keywords, co-authorship and the top-10 cited papers (with objectives and contributions), over the previous five decades. In conjunction with utilising SNA, major findings indicate remarkable improvement on authors’ publication due to a strong social network. Furthermore, the results suggest that the improvement of Asian universities on the IJPR is not only a result of a strong social network among authors, but also an active support from national research funding agencies. The collaboration between researchers appears to be evidently rising by an increasing percentage of articles penned by three or more authors and the average number of authors per article published. The main path analysis identifies the 30 milestone papers which constitute the backbone of the knowledge published in the overall IJPR history.
Journal: International Journal of Production Research
Pages: 4627-4653
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1484953
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1484953
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian (Jeff) Guan
Author-X-Name-First: Jian (Jeff)
Author-X-Name-Last: Guan
Author-Name: Andrew S. Manikas
Author-X-Name-First: Andrew S.
Author-X-Name-Last: Manikas
Author-Name: Lynn H. Boyd
Author-X-Name-First: Lynn H.
Author-X-Name-Last: Boyd
Title: The International Journal of Production Research at 55: a content-driven review and analysis
Abstract: 
 The articles published in the International Journal of Production Research (IJPR) since inception have made a significant contribution to operations management (OM) research, firmly establishing IJPR as one of the most important outlets for OM research. This paper uses a text mining technique called Latent Semantic Analysis to identify the core areas of research published in IJPR since inception, and reveals how the focus on topics has evolved over time. The data consist of the abstracts of all articles published in IJPR from the inception of the journal through December 2015. The study identifies 16 core areas of research and provides a detailed analysis of how these core areas have evolved over time. The results from this data-driven analysis of 55 years of research in IJPR not only provide a comprehensive examination of past research in the journal but also important insights into the evolution of key areas of research in operations management.
Journal: International Journal of Production Research
Pages: 4654-4666
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2017.1296979
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1296979
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4654-4666




Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Manikas
Author-X-Name-First: Andrew
Author-X-Name-Last: Manikas
Author-Name: Lynn Boyd
Author-X-Name-First: Lynn
Author-X-Name-Last: Boyd
Author-Name: Qinghua Pang
Author-X-Name-First: Qinghua
Author-X-Name-Last: Pang
Author-Name: Jian (Jeff) Guan
Author-X-Name-First: Jian (Jeff)
Author-X-Name-Last: Guan
Title: An analysis of research methods in IJPR since inception
Abstract: 
 Production research as an academic field has experienced tremendous growth in the last few decades. The progress in production research and operations management (OM) research is due in no small part to the increasing sophistication and availability of research methods in this field. This paper explores the role of research methods in OM publications through an analysis of the entire corpus of research as represented in a leading OM journal, the International Journal of Production Research (IJPR). This paper reports on a study of all 8653 academic article abstracts published in IJPR since inception to identify the research methods used to both generate and analyse data over the 55 years from the journal’s inception in 1961 through 2015. The study classifies articles using a 6 × 6 typology on the dimensions of data generation and data analysis and provides a summary of the use of research methods and the evolution of their use over time. For example, mathematical modelling has become the dominant method for data generation while experiments have become less popular. Though meta-heuristics and optimisation remain the most popular methods for data analysis, data mining methods have gained pained popularity, comparable to statistical methods.
Journal: International Journal of Production Research
Pages: 4667-4675
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2017.1362122
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1362122
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4667-4675




Template-Type: ReDIF-Article 1.0
Author-Name: Qingfeng Wang
Author-X-Name-First: Qingfeng
Author-X-Name-Last: Wang
Author-Name: Xu Sun
Author-X-Name-First: Xu
Author-X-Name-Last: Sun
Title: The international journal of production research in the past, the present and the future: a bibliometric analysis
Abstract: 
 The growing importance and rising influence of the IJPR in its fields of research is mirrored in its ever-growing number of citations, its large number of authors and author affiliated countries/regions and institutions. By comparing the IJPR with its top peer journals, we have demonstrated an ever-improving status of the IJPR over the years when measured against the performance of the top peer journals in the same period. We have looked into the possible future for the IJPR by providing some suggestions which aim to partially address the areas for improvement identified for the journal.
Journal: International Journal of Production Research
Pages: 4676-4691
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1543974
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543974
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4676-4691




Template-Type: ReDIF-Article 1.0
Author-Name: Rodrigo Romero-Silva
Author-X-Name-First: Rodrigo
Author-X-Name-Last: Romero-Silva
Author-Name: Erika Marsillac
Author-X-Name-First: Erika
Author-X-Name-Last: Marsillac
Title: Trends and topics in IJPR from 1961 to 2017: a statistical history
Abstract: 
 This paper studies the history of the International Journal of Production Research (IJPR) by analysing the topics that have received the most attention in each of the journal’s publication years. Text mining exposed for scrutiny the most frequently mentioned and cited terms contained in the titles, abstracts and keywords of IJPR papers. Analyses suggest that the triad of scheduling/optimisation/simulation and supply-chain-related topics have been IJPR’s mainstays, but valuable opportunities remain for relevant topics that have not yet been concurrently and frequently studied. Results also show that terms related to sustainability and risk management topics have gained recent relevance. In addition, IJPR appears to complement its modelling technique focus with empirical methodological approaches to provide a well-balanced perspective, since the ‘case study’ term is common. Finally, a linear relationship is found between the number of papers that have covered certain topics and the number of citations those topics have received, highlighting which topics had fewer or more citations than expected, given the number of papers that covered those topics. IJPR stands as one of the most prestigious and established journals in its field and the results from this study indicate the evolving interests of the field for over half a century.
Journal: International Journal of Production Research
Pages: 4692-4718
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1551638
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1551638
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohamed Ben-Daya
Author-X-Name-First: Mohamed
Author-X-Name-Last: Ben-Daya
Author-Name: Elkafi Hassini
Author-X-Name-First: Elkafi
Author-X-Name-Last: Hassini
Author-Name: Zied Bahroun
Author-X-Name-First: Zied
Author-X-Name-Last: Bahroun
Title: Internet of things and supply chain management: a literature review
Abstract: 
 This paper explores the role of Internet of Things (IoT) and its impact on supply chain management (SCM) through an extensive literature review. Important aspects of IoT in SCM are covered including IoT definition, main IoT technology enablers and various SCM processes and applications. We offer several categorisation of the extant literature, such as based on methodology, industry sector and focus on a classification based on major supply chain processes. In addition, a bibliometric analysis of the literature is also presented. We find that most studies have focused on conceptualising the impact of IoT with limited analytical models and empirical studies. In addition, most studies have focused on the delivery supply chain process and the food and manufacturing supply chains. Areas of future SCM research that can support IoT implementation are also identified.
Journal: International Journal of Production Research
Pages: 4719-4742
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2017.1402140
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1402140
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Template-Type: ReDIF-Article 1.0
Author-Name: Ana Beatriz Lopes de Sousa Jabbour
Author-X-Name-First: Ana Beatriz Lopes
Author-X-Name-Last: de Sousa Jabbour
Author-Name: Charbel Jose Chiappetta Jabbour
Author-X-Name-First: Charbel Jose
Author-X-Name-Last: Chiappetta Jabbour
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Marcelo Wilson Furlan Matos Alves
Author-X-Name-First: Marcelo Wilson
Author-X-Name-Last: Furlan Matos Alves
Author-Name: Daniela Andriani Ribeiro
Author-X-Name-First: Daniela Andriani
Author-X-Name-Last: Ribeiro
Title: Decarbonisation of operations management – looking back, moving forward: a review and implications for the production research community
Abstract: 
 This paper systematically analyses the vital motivations, drivers and barriers to the adoption of low-carbon operations management practices in response to climate change, highlighting the implications for the International Journal of Production Research (IJPR)’s community, which has contributed significantly to discussion of and research into sustainable production. Based on a thorough review of key articles on low-carbon operations management published in a number of prestigious journals, seven propositions for future research are suggested. Additionally, a unique classification of the barriers to and motivations for low-carbon production is put forward. These areas, which deserve further investigation, are (a) economic issues, (b)  policy, (c) technology, (d) governance and (e) the market. The research agenda proposed for low-carbon production and operations may prove useful to the production research community in planning future developments and research projects, increasing knowledge and designing teaching modules on the topic. The study concludes by shedding light on the main research opportunities that IJPR’s community will encounter.
Journal: International Journal of Production Research
Pages: 4743-4765
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2017.1421790
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421790
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Template-Type: ReDIF-Article 1.0
Author-Name: S.P. Leo Kumar
Author-X-Name-First: S.P.
Author-X-Name-Last: Leo Kumar
Title: Knowledge-based expert system in manufacturing planning: state-of-the-art review
Abstract: 
 In this paper, an effort has been made for intense review on Knowledge-Based Expert System (KB-ES) applications in manufacturing planning. Uniqueness of the present review work is addressed in terms of analysis on published review articles and their review gap. Research works exemplified between 1981 and 2016 were reviewed in terms of ES application in handling product variety, execution of process planning activities, machining, tool selection, tool design, welding, advanced manufacturing, product development. A statistical analysis was carried out in relation with number of publications, domain-specific area and their percentage contribution. It was inferred that, most of the work focused on ES applications related to tool design and machining apart from execution of various process planning activities. Future research can focus on the development frame-based, object oriented-based, ontology-based knowledge representation in order to develop robust system in decision-making for handling complex engineering problem. ES applications can be extended to field of micro fabrication, machine tool development and integrated system development from design to manufacturing.
Journal: International Journal of Production Research
Pages: 4766-4790
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1424372
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424372
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4766-4790




Template-Type: ReDIF-Article 1.0
Author-Name: M. Hasni
Author-X-Name-First: M.
Author-X-Name-Last: Hasni
Author-Name: M.S. Aguir
Author-X-Name-First: M.S.
Author-X-Name-Last: Aguir
Author-Name: M.Z. Babai
Author-X-Name-First: M.Z.
Author-X-Name-Last: Babai
Author-Name: Z. Jemai
Author-X-Name-First: Z.
Author-X-Name-Last: Jemai
Title: Spare parts demand forecasting: a review on bootstrapping methods
Abstract: 
 Accurate demand forecasts are essential to the inventory control of spare parts. There is a plethora of statistical methods developed in the academic literature to deal with the forecasting of spare parts demand. These methods belong to the parametric and the non-parametric approaches. Within the second approach, the bootstrapping methods are the most considered ones. Despite that bootstrapping methods have shown a good empirical performance in comparison with their parametric counterparts, none of the available studies highlight the necessity to bring together its related state of knowledge and critically review the relevant research advancements. The present paper bridges this gap by reviewing the literature that deals with the bootstrapping approach and by discussing some of its statistical properties. This yields a better understanding of its framework, and hence, retrieves more robust explanations of the observed mixed-performances of the available bootstrap-based forecasting methods. This paper reviews as well the service level models associated with the bootstrapping approach with an emphasis on the fill rate models.
Journal: International Journal of Production Research
Pages: 4791-4804
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1424375
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424375
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4791-4804




Template-Type: ReDIF-Article 1.0
Author-Name: Eren Özceylan
Author-X-Name-First: Eren
Author-X-Name-Last: Özceylan
Author-Name: Can B. Kalayci
Author-X-Name-First: Can B.
Author-X-Name-Last: Kalayci
Author-Name: Aşkıner Güngör
Author-X-Name-First: Aşkıner
Author-X-Name-Last: Güngör
Author-Name: Surendra M. Gupta
Author-X-Name-First: Surendra M.
Author-X-Name-Last: Gupta
Title: Disassembly line balancing problem: a review of the state of the art and future directions
Abstract: 
 The disassembly line balancing (DLB) problem assigns the set of tasks to each workstation for each product to be disassembled and aims at attaining several objectives, such as minimising the number of workstations, ensuring similar idle time at each workstation and removing hazardous parts/highly demanded components at the earliest moments possible. Over the past two decades, the DLB problem and its variants have grown ever more popular for researchers and practitioners of environmentally conscious manufacturing. Yet, the problem characteristics and assumptions vary widely and there is no literature review to classify the existing articles accordingly. Hence, a comprehensive literature review of recent and state-of-the-art papers is vital to draw a framework of the past, and to shed light on future directions. To do so, 116 studies published in proceedings and journals since 1999 are selected and reviewed. The papers are then analysed and categorised to construct a useful foundation of past research. Finally, trends and gaps in the literature are identified to clarify and to suggest future research opportunities.
Journal: International Journal of Production Research
Pages: 4805-4827
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1428775
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1428775
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Template-Type: ReDIF-Article 1.0
Author-Name: Yong-Hong Kuo
Author-X-Name-First: Yong-Hong
Author-X-Name-Last: Kuo
Author-Name: Andrew Kusiak
Author-X-Name-First: Andrew
Author-X-Name-Last: Kusiak
Title: From data to big data in production research: the past and future trends
Abstract: 
 Data have been utilised in production research in meaningful ways for decades. Recent years have offered data in larger volumes and improved quality collected from diverse sources. The state-of-the-art data research in production and the emerging methodologies are discussed. The review of the literature suggests that production research enabled by data has shifted from that based on analytical models to data-driven. Manufacturing and data envelopment analysis have been the most popular application areas of data-driven methodologies. The research published to date indicates that data mining is becoming a dominant methodology in production research. Future trends and opportunities for data-driven production research are presented.
Journal: International Journal of Production Research
Pages: 4828-4853
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1443230
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1443230
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Template-Type: ReDIF-Article 1.0
Author-Name: Yongkui Liu
Author-X-Name-First: Yongkui
Author-X-Name-Last: Liu
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Author-Name: Xi Vincent Wang
Author-X-Name-First: Xi Vincent
Author-X-Name-Last: Wang
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Author-Name: Lin Zhang
Author-X-Name-First: Lin
Author-X-Name-Last: Zhang
Title: Scheduling in cloud manufacturing: state-of-the-art and research challenges
Abstract: 
 For the past eight years, cloud manufacturing as a new manufacturing paradigm has attracted a large amount of research interest worldwide. The aim of cloud manufacturing is to deliver on-demand manufacturing services to consumers over the Internet. Scheduling is one of the critical means for achieving the aim of cloud manufacturing. Thus far, about 158 articles have been published on scheduling in cloud manufacturing. However, research on scheduling in cloud manufacturing faces numerous challenges. Thus, there is an urgent need to ascertain the current status and identify issues and challenges to be addressed in the future. Covering articles published on the subject over the past eight years, this article aims to provide a state-of-the-art literature survey on scheduling issues in cloud manufacturing. A detailed statistical analysis of the literature is provided based on the data gathered from the Elsevier’s Scopus abstract and citation database. Typical characteristics of scheduling issues in cloud manufacturing are systematically summarised. A comparative analysis of scheduling issues in cloud manufacturing and other scheduling issues such as cloud computing scheduling, workshop scheduling and supply chain scheduling is also carried out. Finally, future research issues and challenges are identified.
Journal: International Journal of Production Research
Pages: 4854-4879
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1449978
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1449978
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Rezaei-Malek
Author-X-Name-First: Mohammad
Author-X-Name-Last: Rezaei-Malek
Author-Name: Mehrdad Mohammadi
Author-X-Name-First: Mehrdad
Author-X-Name-Last: Mohammadi
Author-Name: Jean-Yves Dantan
Author-X-Name-First: Jean-Yves
Author-X-Name-Last: Dantan
Author-Name: Ali Siadat
Author-X-Name-First: Ali
Author-X-Name-Last: Siadat
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: A review on optimisation of part quality inspection planning in a multi-stage manufacturing system
Abstract: 
 In multi-stage manufacturing systems, optimisation of part quality inspection planning (PQIP) problem means to determine the optimal time, place and extent of inspection activities for assessing the significant quality characteristics of products while maximising the system efficiency. An inspection activity is capable of detecting the produced defects partially and accordingly prevents further processing of them in downstream and more importantly avoids them to reach customers. In this paper, the existing researches on the optimisation of the part quality inspection are surveyed from the viewpoint of the considered production system characteristics; the applied modelling approaches and solution methodologies. This review found that although numerous works have been already done on the PQIP, the development of multi-objective optimisation frameworks considering real production constraints under parameters uncertainty is necessary. Also, by the Industry 4.0 trend, the creation of integrated models aiming to plan the inspection, maintenance and production activities simultaneously, seems to be an important potential future research direction.
Journal: International Journal of Production Research
Pages: 4880-4897
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1464231
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1464231
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4880-4897




Template-Type: ReDIF-Article 1.0
Author-Name: Bin Shen
Author-X-Name-First: Bin
Author-X-Name-Last: Shen
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Stefan Minner
Author-X-Name-First: Stefan
Author-X-Name-Last: Minner
Title: A review on supply chain contracting with information considerations: information updating and information asymmetry
Abstract: 
 Supply chain contracting and the use of information are undoubtedly two critical and influential areas in modern supply chain management. However, relatively little is known about supply chain contracting mechanisms with different information settings. To fill this gap, we review and classify the related supply chain contracting literature into three categories with respect to different kinds of information considerations, namely (i) demand information updating, (ii) supply information updating and (iii) information asymmetry. We report the publication trend and classify the commonly studied supply chain contracts with the use of information such as pricing contracts, commitment contracts and menu of contracts. We discuss how contracting and the use of information influence each other in the supply chain. Moreover, we review the major application areas of information usage and report the historical development of major related topics. Finally, we propose several important future research directions.
Journal: International Journal of Production Research
Pages: 4898-4936
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1467062
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1467062
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4898-4936




Template-Type: ReDIF-Article 1.0
Author-Name: Nima Kazemi
Author-X-Name-First: Nima
Author-X-Name-Last: Kazemi
Author-Name: Nikunja Mohan Modak
Author-X-Name-First: Nikunja Mohan
Author-X-Name-Last: Modak
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Title: A review of reverse logistics and closed loop supply chain management studies published in IJPR: a bibliometric and content analysis
Abstract: 
 Reverse Logistics and Closed Loop Supply Chain Management (RL&CLSCM) are universally recognised as two environmentally friendly practices that could help in greening conventional supply chains. The popularity of these fields of research has led to the evolution of a vast number of publications in the literature. Various journals have so far contributed to the advancement of the field, with the International Journal of Production of Research (IJPR) being one of the most prominent contributed journals. To celebrate the 55th volume anniversary of IJPR, this review study aims to investigate the studies in the area of RL&CLSCM published in IJPR. The paper presents a thorough bibliometric and content analysis of 94 studies that were published in IJPR from 2000 until July 2017. The studies initially underwent a rigorous bibliometric and mapping analysis that helped to identify their characteristics. Subsequently, the contents of the sample papers were evaluated thoroughly. The content analysis led to classification of the papers into two main categories and sub-categories, and then to rigorous identification of the papers’ attributes. The bibliometric and content analysis disclosed several research gaps that remain to be addressed in IJPR.
Journal: International Journal of Production Research
Pages: 4937-4960
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1471244
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471244
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoguang Sun
Author-X-Name-First: Xiaoguang
Author-X-Name-Last: Sun
Author-Name: Rémy Houssin
Author-X-Name-First: Rémy
Author-X-Name-Last: Houssin
Author-Name: Jean Renaud
Author-X-Name-First: Jean
Author-X-Name-Last: Renaud
Author-Name: Mickaël Gardoni
Author-X-Name-First: Mickaël
Author-X-Name-Last: Gardoni
Title: A review of methodologies for integrating human factors and ergonomics in engineering design
Abstract: 
 The requirements of Human Factors and Ergonomics (HF/E) in engineering design must be satisfied, including usability, safety, reliability, and operability in the workplace and work environment. This study presents a review of the methodologies for integrating HF/E information in engineering design. The primary purpose of this review is to identify and summarise the current research in this field, thereby giving the recommendations of future research. The focus is on the interaction design between the system (product) and its user (human), including the design of a complex machine, equipment, system, and simple product. Publications in this field between 1982 and 2017 were reviewed from two aspects: (1) the stage of HF/E information integration in engineering design, including conceptual design, embodiment, and detailed design, and (2) the category of the HF/E, including physical ergonomics, cognitive ergonomics, and organisational ergonomics. The benefits and limitations of the reviewed design methodologies were stated in their respective sections. A critical analysis of the research topics from these two aspects was performed with comparison summarising the applicability of these methodologies for researchers and designers. The suggestions for future research were also offered according to the main findings.
Journal: International Journal of Production Research
Pages: 4961-4976
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1492161
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1492161
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4961-4976




Template-Type: ReDIF-Article 1.0
Author-Name: Amina Chelly
Author-X-Name-First: Amina
Author-X-Name-Last: Chelly
Author-Name: Imen Nouira
Author-X-Name-First: Imen
Author-X-Name-Last: Nouira
Author-Name: Yannick Frein
Author-X-Name-First: Yannick
Author-X-Name-Last: Frein
Author-Name: Atidel B. Hadj-Alouane
Author-X-Name-First: Atidel B.
Author-X-Name-Last: Hadj-Alouane
Title: On The consideration of carbon emissions in modelling-based supply chain literature: the state of the art, relevant features and research gaps
Abstract: 
 This review paper provides the operations management (OM) community with an exhaustive analysis of the mathematical models developed for the problem of low-carbon supply chain management (LCSCM). Our paper belongs to the green supply chain management (GSCM) reviews but is distinguished by its specific interest in analysing research works on supply chain (SC) management regarding the reduction of carbon emissions and its related constraints. To facilitate our benchmarking of the 83 selected papers, we adopt a literature classification based on the logistic decisions studied within the developed models. We distinguish three categories of logistic decisions: operational management, technology investment and SC design coordination. Companies are currently facing great external pressures from governments and their conscientious customers to reduce their overall emissions. We analyse how these environmental constraints, which we believe are key drivers for low-carbon emissions management, have been incorporated into mathematical models. Analysing these external pressures in terms of concern about carbon emissions constitutes our main contribution through this literature review. In addition, companies are facing a challenge to reduce their carbon emissions, which are mainly generated from production, transport and storage activities. Consequently, the modelling of carbon emissions remains a crucial task when addressing the LCSCM problem. We suggest analysing the techniques used thus far to approximate those carbon emissions. Furthermore, to illustrate our literature classification and the features of the LCSCM problem, we provide the framework on which we based our analysis of the selected literature. We discuss the modelling aspects of this problem to highlight the limits of the existing literature and consequently suggest recommendations for future research. We believe that this issue will continue to be one of the top concerns of the OM community within the GSCM field as it continues to gain importance among business leaders, and political and social actors.
Journal: International Journal of Production Research
Pages: 4977-5004
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1497310
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1497310
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Template-Type: ReDIF-Article 1.0
Author-Name: Dorothea Calmels
Author-X-Name-First: Dorothea
Author-X-Name-Last: Calmels
Title: The job sequencing and tool switching problem: state-of-the-art literature review, classification, and trends
Abstract: 
 The job sequencing and tool switching problem is a combinatorial optimisation problem that appears in various industries, mainly in the manufacturing sector. Although tool switching is only part of a much larger decision-making process in manufacturing systems, it has a major impact on the overall performance of the system by affecting the total set-up time as well as the machine and tool utilisation. Over the past few decades, various approaches have been applied to tool switching problems. This study provides a comprehensive review of the literature on the job sequencing and tool switching problem. Studies are identified and compared through a structured literature review and classified according to a new framework which allows the identification of problem perspectives and solution methods. The results show that current research does not fully exploit real-world situations and studies are often limited to a single-machine and uniform tool size and set-up time. Finally, this literature review summarises the current research results and provides directions for future research.
Journal: International Journal of Production Research
Pages: 5005-5025
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1505057
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1505057
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:5005-5025




Template-Type: ReDIF-Article 1.0
Author-Name: Michel Stella Ravelomanantsoa
Author-X-Name-First: Michel Stella
Author-X-Name-Last: Ravelomanantsoa
Author-Name: Yves Ducq
Author-X-Name-First: Yves
Author-X-Name-Last: Ducq
Author-Name: Bruno Vallespir
Author-X-Name-First: Bruno
Author-X-Name-Last: Vallespir
Title: A state of the art and comparison of approaches for performance measurement systems definition and design
Abstract: 
 To control their enterprises in a complex environment, decision-makers need to measure their enterprise regularly to perpetuate. For that, they use a specific set of performance indicators grouped in a coherent system named performance measurement systems (PMS). Such systems are generally defined and implemented using different methods. As business performance measurement appeared from the 1900s, a large number of approaches developed by researchers and practitioners have appeared since those years until today. They were not designed for the same purpose and on the same basis and each of them has advantages and disadvantages to measure optimally the performance. So, decision-makers have difficulties to choose among these methods the most appropriate to their needs when they want to design and implement their customised PMS. The objective of this paper is to present the main concepts that approaches are based on, to present a state of the art as exhaustive as possible of the approaches and methods themselves and to make a comparison between them in order to allow decision-makers to choose among them the one or a combination of several ones which would efficiently suit to their needs to reach their global objective of PMS design and implementation.
Journal: International Journal of Production Research
Pages: 5026-5046
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1506178
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1506178
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Template-Type: ReDIF-Article 1.0
Author-Name: Mariagrazia Dotoli
Author-X-Name-First: Mariagrazia
Author-X-Name-Last: Dotoli
Author-Name: Alexander Fay
Author-X-Name-First: Alexander
Author-X-Name-Last: Fay
Author-Name: Marek Miśkowicz
Author-X-Name-First: Marek
Author-X-Name-Last: Miśkowicz
Author-Name: Carla Seatzu
Author-X-Name-First: Carla
Author-X-Name-Last: Seatzu
Title: An overview of current technologies and emerging trends in factory automation
Abstract: 
 In this paper we provide an overview of recent theoretical approaches and technologies that respond to the fundamental challenges of modern factory automation. We classify these major methods and technologies into several groups and, for seven of them - namely: vertical integration of factory automation systems; distributed and decentralised control, smart sensors and actuators in factories; networked control systems and wireless sensors and actuators; autonomy and self-organisation of factories; advanced sensing for factory automation; semantic models of factories; engineering methods of factory automation systems - we report recent research contributions and formulate open technical problems in the domain of modern factory automation.
Journal: International Journal of Production Research
Pages: 5047-5067
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1510558
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1510558
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Template-Type: ReDIF-Article 1.0
Author-Name: Lucas Martins Ikeziri
Author-X-Name-First: Lucas Martins
Author-X-Name-Last: Ikeziri
Author-Name: Fernando Bernardi de Souza
Author-X-Name-First: Fernando Bernardi de
Author-X-Name-Last: Souza
Author-Name: Mahesh C. Gupta
Author-X-Name-First: Mahesh C.
Author-X-Name-Last: Gupta
Author-Name: Paula de Camargo Fiorini
Author-X-Name-First: Paula
Author-X-Name-Last: de Camargo Fiorini
Title: Theory of constraints: review and bibliometric analysis
Abstract: 
 This paper presents a bibliometric analysis of the Theory of Constraints (TOC) research i.e. a total of 1009 journal articles published since 1984. From a bibliometric point of view, the state of the art was mapped and research gaps in the scientific literature identified, creating opportunities for future research. The Production area leads in number of publications, and applications in the Process of Ongoing Improvement in general have been receiving less attention from academics. It is also worth noting that the International Journal of Production Research has the highest concentration of published works on TOC. The results show that TOC is in continuous development with a trend of growth and therefore demands additional inquiry. The main contributions of this work are: (a) presenting a comprehensive historical review and bibliometric analysis on TOC in a manner not yet illustrated in the literature; (b) addressing potential implications and directions for the IJPR community on TOC research; and (c) offering avenues for future research on how to advance the extant literature of TOC.
Journal: International Journal of Production Research
Pages: 5068-5102
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1518602
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518602
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Template-Type: ReDIF-Article 1.0
Author-Name: Paola Cocca
Author-X-Name-First: Paola
Author-X-Name-Last: Cocca
Author-Name: Filippo Marciano
Author-X-Name-First: Filippo
Author-X-Name-Last: Marciano
Author-Name: Marco Alberti
Author-X-Name-First: Marco
Author-X-Name-Last: Alberti
Author-Name: Debora Schiavini
Author-X-Name-First: Debora
Author-X-Name-Last: Schiavini
Title: Leanness measurement methods in manufacturing organisations: a systematic review
Abstract: 
 The interest of lean companies in tools to monitor and control their lean implementation process, i.e. their leanness level, is continuously increasing. A multitude of diverse approaches have been proposed in the literature for that purpose. In order to provide some guidance both to practitioners interested in selecting a tool and academics aiming at developing a new approach, a systematic review of the methods to measure leanness in manufacturing organisations is carried out. Thirty-one methods are identified and critically analysed based on a set of comparative dimensions. The main strengths and weaknesses of each approach are highlighted. In particular, this paper’s results show that only less than a third of the methods are able to assess leanness in a complete way, taking into consideration both the degree of lean practices adoption and the performance outcomes resulting from implementation. In order to contribute to the reinforcement of a unifying view of the leanness concept, a new leanness definition is developed. Some further gaps in the literature are pointed out, providing directions for future research.
Journal: International Journal of Production Research
Pages: 5103-5118
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1521016
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521016
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience
Abstract: 
 This study suggests a new approach to supply chain (SC) disruption risk management where SC behaviour is less dependent on the certainty of our knowledge about the environment and its changes. The unpredictability of the occurrence of disruption and its magnitude suggests that designing SCs with a low need for ‘certainty’ may be as important, if not more so, than predetermined disruption control strategies. In this setting, this study calls for the development of a new perspective in SC disruption management, i.e. low-certainty-need (LCN) SCs. A number of principles and concepts is derived in recent, relevant literature to structure the characteristics of the LCN framework and its management. Structural variety, process flexibility, and parametrical redundancy are identified as key LCN SC characteristics that ensure efficient disruption resistance as well as recovery resource allocation. Two efficiency capabilities of the LCN SC are shown, i.e. low need for uncertainty consideration in planning decisions and low need for recovery coordination efforts based on a combination of lean and resilient elements. The results allow the identification of an LCN SC framework, concepts and technologies for its implementation as well as missing themes and new research questions which contribute to a better understanding of SC disruption risks. Special focus is directed on the digital technology usage in the LCN framework implementation.
Journal: International Journal of Production Research
Pages: 5119-5136
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1521025
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521025
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Template-Type: ReDIF-Article 1.0
Author-Name: David Bogataj
Author-X-Name-First: David
Author-X-Name-Last: Bogataj
Author-Name: Marija Bogataj
Author-X-Name-First: Marija
Author-X-Name-Last: Bogataj
Title: NPV approach to material requirements planning theory – a 50-year review of these research achievements
Abstract: 
 The Material Requirements Planning (MRP) Theory celebrates 50 years of its development. Because delays are Inevitable, Grubbström developed a theory where delays are calculated in the space of complex variables. Using his approach to evaluate time and exposure to risk in complex production-inventory systems is much easier when dealing with multiple delays. Working in the space of complex variables, which describe production flows and cash flows associated with items, it is easier to derive the NPV of activities in the system. This approach allows for a better evaluation of the impacts on the exposure to risks and rescheduling. We presented the development of this theory since 1967 when Grubbström published his first economic article on Laplace Transforms in production and investments. We discuss possible directions for further progress towards age management, environmental sustainability and closed-loop control, risk evaluation, and agile rescheduling in the framework of Industry 4.0. The overview includes the canon of Grubbström’s work to be used as a reference for researchers, who are aware of the importance of correct and accurate timing for the economic evaluation of technical systems. It also underlines an open question: Can this approach support the development of more transparent and resilient financial systems for financing global inventories?
Journal: International Journal of Production Research
Pages: 5137-5153
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1524167
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1524167
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Template-Type: ReDIF-Article 1.0
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Yahaya Y. Yusuf
Author-X-Name-First: Yahaya Y.
Author-X-Name-Last: Yusuf
Author-Name: Ezekiel O. Adeleye
Author-X-Name-First: Ezekiel O.
Author-X-Name-Last: Adeleye
Author-Name: Thanos Papadopoulos
Author-X-Name-First: Thanos
Author-X-Name-Last: Papadopoulos
Author-Name: Dharma Kovvuri
Author-X-Name-First: Dharma
Author-X-Name-Last: Kovvuri
Author-Name: Dan’Asabe G. Geyi
Author-X-Name-First: Dan’Asabe G.
Author-X-Name-Last: Geyi
Title: Agile manufacturing: an evolutionary review of practices
Abstract: 
 Academics and practitioners have long acknowledged the importance of agile manufacturing and related supply chains in achieving firm sustainable competitiveness. However, limited, if any, research has focused on the evolution of practices within agile manufacturing supply chains and how these are related to competitive performance objectives. To address this gap, we reviewed the literature on an agile manufacturing drawing on the evolution of manufacturing agility, attributes of agile manufacturing, the drivers of agile manufacturing, and the identification of the enabling competencies deployable for agile manufacturing. Our thesis is that agile manufacturing is at the centre of achieving a sustainable competitive advantage, especially in light of current unprecedented market instability coupled with complex customer requirements. In this regard, the emphasis which agile manufacturing places on responsive adaptability would counter the destabilising influence of competitive pressures on organisations performance criteria. We have identified five enabling competencies as the agility enablers and practices of agile manufacturing, that is, transparent customisation, agile supply chains, intelligent automation, total employee empowerment and technology integration, and further explored their joint deployment to create positive multiplier effects. Future research directions were also provided with respect to the operationalisation of the five identified enablers and the potential for emergent technologies of big data, blockchain, and Internet of Things to shape future agile manufacturing practices.
Journal: International Journal of Production Research
Pages: 5154-5174
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1530478
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530478
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Template-Type: ReDIF-Article 1.0
Author-Name: Afshin Jamshidi
Author-X-Name-First: Afshin
Author-X-Name-Last: Jamshidi
Author-Name: Farzad Jamshidi
Author-X-Name-First: Farzad
Author-X-Name-Last: Jamshidi
Author-Name: Daoud Ait-Kadi
Author-X-Name-First: Daoud
Author-X-Name-Last: Ait-Kadi
Author-Name: Amar Ramudhin
Author-X-Name-First: Amar
Author-X-Name-Last: Ramudhin
Title: A review of priority criteria and decision-making methods applied in selection of sustainable city logistics initiatives and collaboration partners
Abstract: 
 Sustainable city logistics plans could significantly affect the quality of life in the urban environment. Evaluating sustainable city logistics initiatives such as urban distribution centres, congestion pricing, delivery timing and access restrictions is a complex problem since several subjective and objective criteria and constraints should be taken into account. On the other hand, collaboration partner selection in the context of the city logistics planning plays an important role in achieving operational efﬁciency under municipal freight regulations such as access, sizing and timing restrictions. This study identifies and reviews the applied criteria/sub-criteria, and multi-criteria decision-making techniques for sustainable city logistics initiatives selection and also collaboration partner selection problems and presents an insight into common criteria/sub-criteria and suitable multi-criteria decision-making techniques for future researches. The results of this literature review reveals that the recent papers aim at considering simultaneously technical, social, environmental and economic criteria by using analytical hierarchy process (AHP) method in the selection of sustainable city logistics initiatives. This result in collaboration partner selection section aims at considering simultaneously quality and cost criteria by using AHP method.
Journal: International Journal of Production Research
Pages: 5175-5193
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1540892
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1540892
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Template-Type: ReDIF-Article 1.0
Author-Name: Yasamin Eslami
Author-X-Name-First: Yasamin
Author-X-Name-Last: Eslami
Author-Name: Michele Dassisti
Author-X-Name-First: Michele
Author-X-Name-Last: Dassisti
Author-Name: Mario Lezoche
Author-X-Name-First: Mario
Author-X-Name-Last: Lezoche
Author-Name: Hervé Panetto
Author-X-Name-First: Hervé
Author-X-Name-Last: Panetto
Title: A survey on sustainability in manufacturing organisations: dimensions and future insights
Abstract: 
 Manufacturing organisations are facing the urge to adopt new strategies like sustainability to be able to respond to the market and customer’s demand for sustainable products due to the scarcity of the natural resources or government policies. To serve this purpose, the main questions risen are ‘How sustainability is defined through its dimensions?’ and ‘what sub-dimensions can denominate sustainable manufacturing?’ Focusing on the questions, this study is cantered by a systematic literature review based on sustainability, its dimensions and sub-dimensions to investigate sustainability in manufacturing and the domains on which manufacturers can act on to be more ‘sustainable’. Although the literature is more focused on the three traditional dimensions of sustainability namely: environmental, economic and social, a more detailed look through the dimensions is needed to help manufacturing organisations sketch their own sustainable strategies on more specific issues. The study of the dimensions led to a hierarchy of importance for the traditional three, in which environmental dimension of sustainability showed to be conspicuous. Therefore, the dimension was chosen for the further analysis conducted by Formal Concept Analysis (FCA) on its sub-dimensions to explore the trends in their combination by manufacturers while trying to reach sustainability.
Journal: International Journal of Production Research
Pages: 5194-5214
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1544723
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1544723
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Template-Type: ReDIF-Article 1.0
Author-Name: Timothy Sprock
Author-X-Name-First: Timothy
Author-X-Name-Last: Sprock
Author-Name: Conrad Bock
Author-X-Name-First: Conrad
Author-X-Name-Last: Bock
Author-Name: Leon F. McGinnis
Author-X-Name-First: Leon F.
Author-X-Name-Last: McGinnis
Title: Survey and classification of operational control problems in discrete event logistics systems (DELS)
Abstract: 
 This paper reviews and classifies literature on operational control of discrete event logistics systems (DELS). Operational control manipulates the flow of items through a DELS. Each control problem addressed in the surveyed literature is classified based on the control decision that the analysis model is formulated to support. These control decisions are defined by abstract functional definitions focussing on analysis model inputs, outputs, and variables. This classification of control problems shows that five kinds of atomic control decisions are needed to cover the literature, either by themselves or in combination. Standard functional definitions of operational control decisions enable discovery and interoperability of decision-support analysis models.
Journal: International Journal of Production Research
Pages: 5215-5238
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2018.1553314
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1553314
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Template-Type: ReDIF-Article 1.0
Author-Name: Isabel Mundi
Author-X-Name-First: Isabel
Author-X-Name-Last: Mundi
Author-Name: M. M. E. Alemany
Author-X-Name-First: M. M. E.
Author-X-Name-Last: Alemany
Author-Name: Raúl Poler
Author-X-Name-First: Raúl
Author-X-Name-Last: Poler
Author-Name: Vicente S. Fuertes-Miquel
Author-X-Name-First: Vicente S.
Author-X-Name-Last: Fuertes-Miquel
Title: Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model
Abstract: 
 Lack of homogeneity in the product (LHP) appears in some production processes that confer heterogeneity in the characteristics of the products obtained. Supply chains with this issue have to classify the product in different homogeneous subsets, whose quantity is uncertain during the production planning process. This paper proposes a generic framework for reviewing in a unified way the literature about production planning models dealing with LHP uncertainty. This analysis allows the identification of similarities among sectors to transfer solutions between them and gaps existing in the literature for further research. The results of the review show: (1) sectors affected by LHP inherent uncertainty, (2) the inherent LHP uncertainty types modelled, and (3) the approaches for modelling LHP uncertainty most widely employed. Finally, we suggest a conceptual model reflecting the aspects to be considered when modelling the production planning in sectors with LHP in an uncertain environment.
Journal: International Journal of Production Research
Pages: 5239-5283
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2019.1566665
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566665
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Template-Type: ReDIF-Article 1.0
Author-Name: Maria Pia Ciano
Author-X-Name-First: Maria Pia
Author-X-Name-Last: Ciano
Author-Name: Rossella Pozzi
Author-X-Name-First: Rossella
Author-X-Name-Last: Pozzi
Author-Name: Tommaso Rossi
Author-X-Name-First: Tommaso
Author-X-Name-Last: Rossi
Author-Name: Fernanda Strozzi
Author-X-Name-First: Fernanda
Author-X-Name-Last: Strozzi
Title: How IJPR has addressed ‘lean’: a literature review using bibliometric tools
Abstract: 
 The aim of this study is to investigate the body of literature on lean published by the International Journal of Production Research (IJPR), which has been interested in the subject since its dawn. This review adopted a dynamic and quantitative bibliometric method composed of the keywords co-occurrence network and keywords burst detection. The analyses performed on keywords co-occurrence networks highlighted how research in IJPR has addressed research on lean over time and allowed a comparison with the consolidated research streams in literature. The burst detection completed the analysis highlighting the trends and most recent research areas characterising IJPR publications. The outcomes of this study reflected the evergreen relevance of lean; indeed, the latest research trajectories identified in IJPR stressed its link with the increasingly topical issues concerning industry 4.0, sustainability and remanufacturing. The analysis recognised in ‘lean Six Sigma’, and specifically in its support to the service sector, an under-considered topic, hence a scope that offers room for further study, in accordance with IJPR objectives.
Journal: International Journal of Production Research
Pages: 5284-5317
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2019.1566667
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566667
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Daneshvar Kakhki
Author-X-Name-First: Mohammad
Author-X-Name-Last: Daneshvar Kakhki
Author-Name: Vidyaranya B. Gargeya
Author-X-Name-First: Vidyaranya B.
Author-X-Name-Last: Gargeya
Title: Information systems for supply chain management: a systematic literature analysis
Abstract: 
 Information systems (IS) impact supply chain management (SCM) on processes such as planning, sourcing, and delivering, and at levels ranging from tactical operations to organisational strategy. The vast scope of IS and SCM relationships have resulted in diverse and disintegrated research on the topic. This paper offers a systematic literature analysis at the intersection of supply chain and information systems (SCIS), aiming to provide a classification for existing areas of research. This research is based on an analysis of more than 1500 articles published in peer-reviewed journals over the past four decades to classify topics and methods and to identify major trends and distinguish important research themes. The classification of the literature has identified major clusters of research in SCIS, and suggestions are made for future research in each of the identified clusters. In general, the findings point out that there is a dearth of research on topics such as ‘impact of IT on vertical disintegration of supply chains,’ ‘implications of new technologies for supply chains,’ and ‘concerns related to trust, governance, ownership, privacy, and security of data in supply chains.’ This work provides both researchers and practitioners with an insightful description of the current state of research in SCIS and related future trends in research and practice.
Journal: International Journal of Production Research
Pages: 5318-5339
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2019.1570376
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1570376
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Template-Type: ReDIF-Article 1.0
Author-Name: Shenle Pan
Author-X-Name-First: Shenle
Author-X-Name-Last: Pan
Author-Name: Damien Trentesaux
Author-X-Name-First: Damien
Author-X-Name-Last: Trentesaux
Author-Name: Eric Ballot
Author-X-Name-First: Eric
Author-X-Name-Last: Ballot
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Horizontal collaborative transport: survey of solutions and practical implementation issues
Abstract: 
 Horizontal collaboration has been considered as effective practice for sustainable logistics and freight transport and it has gained increased attention in recent years. This paper aims to provide a survey of the development of horizontal collaborative transport (HCT) over the past ten years, to identify research trends and gaps, then to propose some research opportunities. The paper also aims to provide guidelines to logistics companies who wish to embark on HCT, to help them choose which HCT solution to implement. To provide a comprehensive and structured review, the paper follows the methodology for Systematic Literature Review proposed in the literature. A total of 120 scientific papers published between 2007 and 2017 were reviewed. A survey framework based on two axes – HCT solutions and implementation issues – is developed to analyse and position the papers. The results show that, regarding HCT solutions, carrier alliance and flow controller collaboration were the most frequently studied. But recent innovative solutions such as pooling and physical internet are also gaining increased attention. Regarding implementation issues, the focus of the literature has been on the development of decision-making models, including transport planning, lane exchange, and gain sharing. Conversely, managerial and technological issues have received less attention.
Journal: International Journal of Production Research
Pages: 5340-5361
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2019.1574040
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1574040
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Template-Type: ReDIF-Article 1.0
Author-Name: Ilenia Zennaro
Author-X-Name-First: Ilenia
Author-X-Name-Last: Zennaro
Author-Name: Serena Finco
Author-X-Name-First: Serena
Author-X-Name-Last: Finco
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Alessandro Persona
Author-X-Name-First: Alessandro
Author-X-Name-Last: Persona
Title: Big size highly customised product manufacturing systems: a literature review and future research agenda
Abstract: 
 The paper presents a systematic literature review on big size product manufacturing systems in MTO and ETO environments. In particular, the analysis is focused on highly customised, big and heavy products, calling for highly engineering solutions. This kind of products are characterised by low-volume demand, complex material bills, need of more than one worker in the same workstation (caused by the component dimensions and complexity), multi-skilled human resources and large floor space requirements. The analysis involved 587 research articles published from 1981 to 2017 from 118 international journals in the area of production research and operation management. Finally, 160 papers have been individuated and clustered in three main research topic area: specification processes and product design, production planning and control, project portfolio management. Results indicate that research focused on optimising and managing a large-size product manufacturing system is gaining growing attention in the last ten years. However, product/process design, production planning and control and project management techniques still lack innovations and ad hoc methods, capable to take into consideration both in-house part feeding problems, both ergonomics issues present in this kind of manufacturing environments.
Journal: International Journal of Production Research
Pages: 5362-5385
Issue: 15-16
Volume: 57
Year: 2019
Month: 8
X-DOI: 10.1080/00207543.2019.1582819
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1582819
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Template-Type: ReDIF-Article 1.0
Author-Name: Abdolreza Roshani
Author-X-Name-First: Abdolreza
Author-X-Name-Last: Roshani
Author-Name: Davide Giglio
Author-X-Name-First: Davide
Author-X-Name-Last: Giglio
Title: Simulated annealing algorithms for the multi-manned assembly line balancing problem: minimising cycle time
Abstract: 
 Multi-manned assembly lines are often designed to produce big-sized products, such as automobiles and trucks. In this type of production lines, there are multi-manned workstations where a group of workers simultaneously performs different operations on the same individual product. One of the problems, that managers of such production lines usually encounter, is to produce the optimal number of items using a fixed number of workstations, without adding new ones. In this paper, such a class of problems, namely, the multi-manned assembly line balancing problem is addressed, with the objective of minimising the cycle time. A mixed-integer mathematical programming formulation is proposed for the considered problem. This model has the primary objective of minimising the cycle time for a given number of workstations and the secondary objective of minimising the total number of workers. Since the addressed problem is NP-hard, two meta-heuristic approaches based on the simulated annealing algorithm have been developed: ISA and DSA. ISA solves the problem indirectly while DSA solves it directly. The performance of the two algorithms are tested and compared on a set of test problems taken from the literature. The results show that DSA outperforms ISA in term of solution quality and computational time.
Journal: International Journal of Production Research
Pages: 2731-2751
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1181286
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1181286
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Template-Type: ReDIF-Article 1.0
Author-Name: Koichi Nakade
Author-X-Name-First: Koichi
Author-X-Name-Last: Nakade
Title: Effect of worker sequence on cycle time in a U-shaped line with chase mode
Abstract: 
 In this paper, a U-shaped line with multiple machines is considered, where each of multiple heterogeneous workers is allocated to one of machines as his/her starting position along the line. The chase mode is assumed, in which workers deal with all tasks and walk around on the same route. Periodicity of cycle time of a U-shaped line in chase mode is discussed, where periodicity means that time necessary for each worker to walk around is cyclic and depends on the order of worker’s sequence. When it is periodic, the overall cycle time on the output of products becomes greater than the fundamental cycle time of the system, which is the maximum among total task times on workers and machines divided by the number of workers. It is shown that if there are just two workers then there is no periodicity of cycle time. Examples for three worker case show that the order of workers on the line sometimes highly influences on the length and periodicity of cycle time. The sufficient conditions under which there is no periodicity are derived for three or more worker cases.
Journal: International Journal of Production Research
Pages: 2752-2763
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1190472
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1190472
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Template-Type: ReDIF-Article 1.0
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Alessandro Persona
Author-X-Name-First: Alessandro
Author-X-Name-Last: Persona
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Title: Additional effort estimation due to ergonomic conditions in order picking systems
Abstract: 
 Within a warehouse, the picking activity often relies on human operators. Therefore, when designing and evaluating a manual picking system, it is important to consider that, besides the high flexibility the pickers are able to warrant, they inevitably require an additional effort due to their ergonomic working conditions. In this paper, the authors propose a new model to consider such additional effort, starting from the concepts of human availability and rest allowance. The new method allows the evaluation of the current configuration of a certain warehouse, considering two different operative situations (directly employed operators and indirectly employed ones). Moreover, it makes it possible to estimate and to understand the benefits that can be achieved by introducing some ergonomic improvements. The proposed procedure has also been applied to a real industrial case study.
Journal: International Journal of Production Research
Pages: 2764-2774
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1190879
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1190879
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Template-Type: ReDIF-Article 1.0
Author-Name: Ignacio Eguia
Author-X-Name-First: Ignacio
Author-X-Name-Last: Eguia
Author-Name: Jose Carlos Molina
Author-X-Name-First: Jose Carlos
Author-X-Name-Last: Molina
Author-Name: Sebastian Lozano
Author-X-Name-First: Sebastian
Author-X-Name-Last: Lozano
Author-Name: Jesus Racero
Author-X-Name-First: Jesus
Author-X-Name-Last: Racero
Title: Cell design and multi-period machine loading in cellular reconfigurable manufacturing systems with alternative routing
Abstract: 
 This paper deals with the design and loading of Cellular Reconfigurable Manufacturing Systems in the presence of alternative routing and multiple time periods. These systems consist of multiple reconfigurable machining cells, each of which has Reconfigurable Machine Tools and Computer Numerical Control (CNC) machines. Each reconfigurable machine has a library of feasible auxiliary machine modules for achieving particular operational capabilities, while each CNC machine has an automatic tool changer and a tool magazine of a limited capacity. The proposed approach consists of two phases: the machine cell design phase which involves the grouping of machines into machine cells, and the cell loading phase that determines the routing mix and the tool and module allocation. In this paper, the cell design problem is modelled as an Integer Linear Programming formulation, considering the multiple process plans of each part type as if they were separate part types. Once the manufacturing cells are formed, a Mixed Integer Linear Programming model is developed for the cell loading problem, considering multi-period demands for the part types, and minimising transportation and holding costs while keeping the machine and cell utilisations in each period, and the system utilisation across periods, approximately balanced. An illustrative problem and experimental results are presented.
Journal: International Journal of Production Research
Pages: 2775-2790
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1193673
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193673
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Template-Type: ReDIF-Article 1.0
Author-Name: Theodor Freiheit
Author-X-Name-First: Theodor
Author-X-Name-Last: Freiheit
Author-Name: Wei Li
Author-X-Name-First: Wei
Author-X-Name-Last: Li
Title: The effect of work content imbalance and its interaction with scheduling method on sequential flow line performance
Abstract: 
 Uneven workflow in serial flow lines is common when job work content varies. Unfortunately, work content imbalance between stations or between jobs degrades system performance. The effect of this imbalance can be mitigated by proper job sequencing. In this paper, we uncouple the influence of station-to-station and job-to-job imbalance within a set of jobs, introducing metrics to quantify the degree of imbalance, and determine their impact on line performance. We then examine the sensitivity of several scheduling methods at different problem scales and processing time variance levels, and compare the sensitivity to process time stability radii. Within the case studies explored, we determine that greater station imbalance can degrade solution quality regardless of problem scale and variance level. Greater job imbalance can either improve or diminish solution quality (i.e. relative performance from a given scheduling method), but less than station imbalance. Scheduling methods that sequence jobs based on the sums of processing times, e.g. SPT, can benefit from greater station imbalance. Scheduling methods that sequence jobs based on idle time between stations, e.g. the state-space heuristic, are more sensitive to station imbalance, but can also benefit from job imbalance. Finally, we conclude that job sequence has a greater impact on solution quality than stability radii.
Journal: International Journal of Production Research
Pages: 2791-2805
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1194536
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1194536
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Template-Type: ReDIF-Article 1.0
Author-Name: Shraga Shoval
Author-X-Name-First: Shraga
Author-X-Name-Last: Shoval
Author-Name: Mahmoud Efatmaneshnik
Author-X-Name-First: Mahmoud
Author-X-Name-Last: Efatmaneshnik
Author-Name: Michael J. Ryan
Author-X-Name-First: Michael J.
Author-X-Name-Last: Ryan
Title: Assembly sequence planning for processes with heterogeneous reliabilities
Abstract: 
 Stochasticity in assembly processes is often associated with the processing time and availability of machinery, tools and manpower, however in this paper it is determined by probability of an assembly task successful completion which here is referred to as task reliability. We present a mathematical model for optimising the expected assembly cost, and consider two scenarios: the first a situation where a failure of one assembly task requires rework of that task alone; second a situation in which a failure in the midst of the process requires resumption of previously completed tasks. In the worst case scenario the assembly process must restart from the beginning. We show that the first scenario is insensitive to sequencing unless there are set-up costs. In the second scenario the process is sensitive to tasks’ sequence. We present a heuristic that argues for accomplishing more uncertain tasks (with less reliability) earlier in the process to decrease the expected cost of assembly, and show that in a mutually dependent assembly process, when tasks’ reliabilities are similar, the cheaper tasks should be executed earlier in the process.
Journal: International Journal of Production Research
Pages: 2806-2828
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1213449
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213449
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Template-Type: ReDIF-Article 1.0
Author-Name: Luiza Zeltzer
Author-X-Name-First: Luiza
Author-X-Name-Last: Zeltzer
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Author-Name: Veronique Limère
Author-X-Name-First: Veronique
Author-X-Name-Last: Limère
Title: Workload balancing and manufacturing complexity levelling in mixed-model assembly lines
Abstract: 
 To effectively react and meet the current ever growing demand for individualised motor vehicles, built to customer specific requirements, automotive industry has accelerated its transition towards mass-customisation. As a result, the number of new model introductions has drastically increased over the past three decades. To cope with this intensified customisation, the current automotive assembly platforms are designed to assemble a wide range of relatively different models, and are turned into mixed-model assembly lines (MMALs). This implies that the set of tasks to be performed on each workstation is no longer stable but varies highly with the model-mix. As a consequence, the manufacturing complexity increases at the workstations and throughout the whole assembly system. This paper proposes a method to monitor manufacturing complexity at each workstation while the MMAL is being balanced. An entropy-based quantitative measure of complexity, which incorporates the variability of each task duration, is developed. This measure is used to monitor the manufacturing complexity level at each workstation. An integrated mixed-line balancing and complexity monitoring heuristic is proposed, to determine workload balance solutions, in which manufacturing complexity is levelled throughout the workstations composing the line. This procedure is tested on a real data-set provided by an automotive manufacturer. The results are reported and thoroughly discussed.
Journal: International Journal of Production Research
Pages: 2829-2844
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1213452
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213452
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Template-Type: ReDIF-Article 1.0
Author-Name: Dennis Kolberg
Author-X-Name-First: Dennis
Author-X-Name-Last: Kolberg
Author-Name: Joshua Knobloch
Author-X-Name-First: Joshua
Author-X-Name-Last: Knobloch
Author-Name: Detlef Zühlke
Author-X-Name-First: Detlef
Author-X-Name-Last: Zühlke
Title: Towards a lean automation interface for workstations
Abstract: 
 Methods and principles of Lean Production have become the major concepts to create highly efficient processes since the early 1990s. Due to its high effectiveness by reducing complexity and focusing on value-adding tasks, the Lean concept is still successful. Nevertheless, its changeability to produce highly customised products is limited. Industry 4.0 describes the vision of a smart production which can meet these future market requirements. Enablers are innovative information and communication technologies and the integration of all production entities into a common digital network. Lean Automation is the application of Industry 4.0 technologies to Lean Production methods in order to combine benefits from both domains. First proprietary Lean Automation solutions exist, but to enhance changeability in production, a common, unified communication interface is required. This paper presents the ongoing work towards an interface for digitising Lean Production methods using Cyber Physical Systems.
Journal: International Journal of Production Research
Pages: 2845-2856
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1223384
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1223384
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Template-Type: ReDIF-Article 1.0
Author-Name: H. Mosadegh
Author-X-Name-First: H.
Author-X-Name-Last: Mosadegh
Author-Name: S.M.T. Fatemi Ghomi
Author-X-Name-First: S.M.T.
Author-X-Name-Last: Fatemi Ghomi
Author-Name: G.A. Süer
Author-X-Name-First: G.A.
Author-X-Name-Last: Süer
Title: Heuristic approaches for mixed-model sequencing problem with stochastic processing times
Abstract: 
 Despite many pioneering efforts and works over the past decades, stochastic events have not been studied extensively in mixed-model assembly lines thus far. For a mixed-model sequencing problem with stochastic processing times, this paper aims to minimise expected total work overload. It also focuses on the most critical workstation of the line. In practice, this assumption is useful when the whole or a big portion of the assembly line is considered as a single station. In order to tackle the problem, a dynamic programming (DP) algorithm as well as two greedy heuristics from the literature is employed. However, it is realised that the DP cannot guarantee the optimal sequence neither for stochastic nor deterministic problems. It is because the calculation of work overload is involved in a recursive procedure that affects the states’ value functions. Therefore, by the use of network representation, the problem is modelled as a shortest path problem and a new heuristic, inspired by Dijkstra’s algorithm is developed to deal with it. Numerical results show that the proposed method outperforms other algorithms strongly. Finally, some discussion is provided about why one should consider stochastic parameters and why the proposed heuristic performs well in this regard.
Journal: International Journal of Production Research
Pages: 2857-2880
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1223897
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1223897
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Template-Type: ReDIF-Article 1.0
Author-Name: Federico Trigos
Author-X-Name-First: Federico
Author-X-Name-Last: Trigos
Author-Name: Eduardo Manuel López
Author-X-Name-First: Eduardo Manuel
Author-X-Name-Last: López
Title: A vulcanising decision planning as a particular one-dimensional cutting stock problem with limited part-related tooling in make-to-order industrial environments
Abstract: 
 A specialised case of the classical one-dimensional cutting stock problem (1D-CSP) with six main additional features is adapted in this paper to model and solve planning unit operations with limited resources in the make-to-order industrial environment, generating a new decision-making problem. The objective is to satisfy demand using the minimum number of manufacturing cycles. Although there is a large number of applications, this paper proposes a decision model directed at the vulcanising operation during the manufacturing of rubber curved hoses in the automotive industry. Because each vulcanising cycle (VC) uses a considerable amount of resources, the need to minimise the total number of VCs is of importance due to its direct relationship with lead time and productivity. An integer-programming model based on a network optimisation formulation is proposed to solve the problem to optimality and allows for construction of the mathematical model. In addition, due to the limited capacity of computers to solve large instances, a heuristic is developed to obtain near-optimal solutions. Scheduling issues are found in the optimal solution of the integer-programming model, but the heuristic overcomes such obstacles. Numerical experiments demonstrate the efficiency of the heuristic.
Journal: International Journal of Production Research
Pages: 2881-2896
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1227100
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1227100
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Template-Type: ReDIF-Article 1.0
Author-Name: Elif Elcin Gunay
Author-X-Name-First: Elif Elcin
Author-X-Name-Last: Gunay
Author-Name: Ufuk Kula
Author-X-Name-First: Ufuk
Author-X-Name-Last: Kula
Title: A stochastic programming model for resequencing buffer content optimisation in mixed-model assembly lines
Abstract: 
 In mixed-model assembly lines, smooth operation of the assembly line depends on adherence to the scheduled sequence. However, during production process, this sequence is altered both intentionally and uninstentionally. A major source of unintentional sequence alteration in automobile plants is the paint defects. A post-paint resequencing buffer, located before the final assembly is used to restore the altered sequence. Restoring the altered sequence back to the scheduled sequence requires three distinct operations in this buffer: Changing the positions (i.e. resequencing) of vehicles, inserting spare vehicles in between difficult models and replacing spare vehicles with paint defective vehicles. We develop a two-stage stochastic model to determine the optimal number of spare vehicles from each model-colour type to be placed into the Automated Storage and Retrieval System resequencing buffer that maximises the scheduled sequence achievement ratio (SSAR). The model contributes to the literature by explicitly considering above three distinct operations and random nature of paint defect occurrences. We use sample average approximation algorithm to solve the model. We provide managerial insights on how paint entrance sequence, defect rate and buffer size affect the SSAR. A value of stochastic solution shows that the model significantly outperforms its deterministic counterpart.
Journal: International Journal of Production Research
Pages: 2897-2912
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1227101
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1227101
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingyang Zhou
Author-X-Name-First: Jingyang
Author-X-Name-Last: Zhou
Author-Name: Peter E.D. Love
Author-X-Name-First: Peter E.D.
Author-X-Name-Last: Love
Author-Name: Kok Lay Teo
Author-X-Name-First: Kok Lay
Author-X-Name-Last: Teo
Author-Name: Hanbin Luo
Author-X-Name-First: Hanbin
Author-X-Name-Last: Luo
Title: An exact penalty function method for optimising QAP formulation in facility layout problem
Abstract: 
 A quadratic assignment problem (QAP), which is a combinatorial optimisation problem, is developed to model the problem of locating facilities with material flows between them. The aim of solving the QAP formulation for a facility layout problem (FLP) is to increase a system’s operating efficiency by reducing material handling costs, which can be measured by interdepartmental distances and flows. The QAP-formulated FLP can be viewed as a discrete optimisation problem, where the quadratic objective function is optimised with respect to discrete decision variables subject to linear equality constraints. The conventional approach for solving this discrete optimisation problem is to use the linearisation of the quadratic objective function whereby additional discrete variables and constraints are introduced. The adoption of the linearisation process can result in a significantly increased number of variables and constraints; solving the resulting problem can therefore be challenging. In this paper, a new approach is introduced to solve this discrete optimisation problem. First, the discrete optimisation problem is transformed into an equivalent nonlinear optimisation problem involving only continuous decision variables by introducing quadratic inequality constraints. The number of variables, however, remains the same as the original problem. Then, an exact penalty function method is applied to convert this transformed continuous optimisation problem into an unconstrained continuous optimisation problem. An improved backtracking search algorithm is then developed to solve the unconstrained optimisation problem. Numerical computation results demonstrate the effectiveness of the proposed new approach.
Journal: International Journal of Production Research
Pages: 2913-2929
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1229068
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1229068
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Template-Type: ReDIF-Article 1.0
Author-Name: Jihee Han
Author-X-Name-First: Jihee
Author-X-Name-Last: Han
Author-Name: Yoonho Seo
Author-X-Name-First: Yoonho
Author-X-Name-Last: Seo
Title: Mechanism to minimise the assembly time with feeder assignment for a multi-headed gantry and high-speed SMT machine
Abstract: 
 This paper proposes the development of a mechanism to minimise the assembly time for a multi-headed gantry and high-speed surface mounting technology machine by determining the component assignment to feeder slots. Since a gantry moves long distances in order to pick components, place them on the board and then return them to the feeder slots, we classified the overall assembly time according to the different movements of a gantry. The overall assembly time is then minimised by presenting a new heuristic for the feeder assignment, consisting of Nearest Component Allocation (NCA) and Globally Updated Assignment (GUA). NCA contains information about how each component type locates closely to others on the board. Using the solution from NCA, the component distance function calculates the most representative distance between component types. Then, GUA is applied to improve the NCA solution. The experiments consist of several printed circuit boards with numbers of component types and points to be placed. Highlights of this paper are that: a classification of the gantry movements is proposed based on the average speed; a heuristic NCA-GUA for feeder assignment is developed by considering the placements on the board; the computational time is greatly reduced by NCA-GUA without degrading the solution quality; and a decision process for nozzle assignment is proposed to minimise the overall assembly time. The results show how NCA and GUA affect the final results, and how this mechanism leads to better performance than a genetic algorithms or 2-opt swap search. This comparison proves that our method provides competitive and effective solutions in terms of minimising the overall assembly time.
Journal: International Journal of Production Research
Pages: 2930-2949
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1229071
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1229071
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Template-Type: ReDIF-Article 1.0
Author-Name: Nikolas Antzoulatos
Author-X-Name-First: Nikolas
Author-X-Name-Last: Antzoulatos
Author-Name: Elkin Castro
Author-X-Name-First: Elkin
Author-X-Name-Last: Castro
Author-Name: Lavindra de Silva
Author-X-Name-First: Lavindra
Author-X-Name-Last: de Silva
Author-Name: André Dionisio Rocha
Author-X-Name-First: André Dionisio
Author-X-Name-Last: Rocha
Author-Name: Svetan Ratchev
Author-X-Name-First: Svetan
Author-X-Name-Last: Ratchev
Author-Name: José Barata
Author-X-Name-First: José
Author-X-Name-Last: Barata
Title: A multi-agent framework for capability-based reconfiguration of industrial assembly systems
Abstract: 
 Rapidly changing market requirements and shorter product lifecycles demand assembly systems that are able to cope with frequently changing resources, resource capabilities and product specifications. This paper presents a multi-agent framework that can adapt an assembly system in order to cope with such changes. The focus of this work is on the ability to plug resources (such as PLCs) into and out of the system, and dynamically aggregate resource capabilities to form more complex ones as resources are plugged in. In addition, an implementation of the framework on an industrial assembly system is discussed, and some insights are provided into some of the key features that product specification languages ought to have to be useful in real world assembly systems, and into the added value of using the proposed framework.
Journal: International Journal of Production Research
Pages: 2950-2960
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1243268
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1243268
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Template-Type: ReDIF-Article 1.0
Author-Name: Yihai He
Author-X-Name-First: Yihai
Author-X-Name-Last: He
Author-Name: Linbo Wang
Author-X-Name-First: Linbo
Author-X-Name-Last: Wang
Author-Name: Yi Wei
Author-X-Name-First: Yi
Author-X-Name-Last: Wei
Author-Name: Zhenzhen He
Author-X-Name-First: Zhenzhen
Author-X-Name-Last: He
Title: Optimisation of burn-in time considering the hidden loss of quality deviations in the manufacturing process
Abstract: 
 The burn-in test time is an important parameter of the complex batch processing machine scheduling problem. The omission of the loss of quality deviations in manufacturing generates a non-comprehensive and imperfect result in the optimisation of burn-in time, which hinders the identification of proactive and economical optimisation strategies to prevent infant failure in manufacturing. To solve this problem, this study visualises and quantifies for the first time the hidden loss caused by quality deviations in manufacturing and uses it as a newly added constraint to optimise the burn-in time. Firstly, a quality loss model composed of visible yield loss and warranty costs related to measurable but undetectable reliability vulnerabilities is defined. Secondly, the loss effects of growing defects are measured during the burn-in test, and the optimal burn-in time expressed by the proposed quality loss model is traded off between the additional burn-in cost and the decreased quality loss for an acceptable low infant failure rate. Finally, the effectiveness of the proposed optimisation approach is demonstrated using actual data from a control board with a high infant failure rate. Results show that the proposed method can systematically combine the fundamental loss of quality deviations in the optimisation of burn-in time, which supplements the commonly used optimality criteria, with the upstream loss of quality deviations in the form of manufacturing defects.
Journal: International Journal of Production Research
Pages: 2961-2977
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1262081
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1262081
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Template-Type: ReDIF-Article 1.0
Author-Name: Kuo-Ching Ying
Author-X-Name-First: Kuo-Ching
Author-X-Name-Last: Ying
Author-Name: Yi-Ju Tsai
Author-X-Name-First: Yi-Ju
Author-X-Name-Last: Tsai
Title: Minimising total cost for training and assigning multiskilled workers in  production systems
Abstract: 
 This paper investigates the multiskilled worker training and assignment (MWT&amp;A) problem of the seru production system (SPS), which is a new type of assembly line configured as multiple assembly cells, or so-called serus. The configuration of the SPS emphasises production efficiency and flexibility, achieved by multiskilled workers (MWs) able to cope with the demand of high-variety and low-volume manufacturing. Well-arranged and trained MWs are viewed as a critical factor when it comes to enhancing the performance of SPSs. This paper studies the MWT&amp;A problem in the SPS with the aim of minimising the total cost, specifically, the workers’ training cost and the balance cost of processing times of the MWs in serus. This study provides an applicable mathematical programming model and designs a two-phase heuristic, named the SAIG algorithm, to effectively and efficiently solve this problem. The performance of the proposed algorithm is demonstrated by a comparison with the state-of-the-art heuristic through a series of computational experiments.
Journal: International Journal of Production Research
Pages: 2978-2989
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2016.1277594
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1277594
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Template-Type: ReDIF-Article 1.0
Author-Name: Yang Yu
Author-X-Name-First: Yang
Author-X-Name-Last: Yu
Author-Name: Wei Sun
Author-X-Name-First: Wei
Author-X-Name-Last: Sun
Author-Name: Jiafu Tang
Author-X-Name-First: Jiafu
Author-X-Name-Last: Tang
Author-Name: Ikou Kaku
Author-X-Name-First: Ikou
Author-X-Name-Last: Kaku
Author-Name: Junwei Wang
Author-X-Name-First: Junwei
Author-X-Name-Last: Wang
Title: Line- conversion towards reducing worker(s) without increasing makespan: models, exact and meta-heuristic solutions
Abstract: 
 Compared with the traditional assembly line, seru production can reduce worker(s) and decrease makespan. However, when the two objectives are considered simultaneously, Pareto-optimal solutions may save manpower but increase makespan. Therefore, we formulate line-seru conversion towards reducing worker(s) without increasing makespan and develop exact and meta-heuristic algorithms for the different scale instances. Firstly, we analyse the distinct features of the model. Furthermore, according to the feature of the solution space, we propose two exact algorithms to solve the small to medium-scale instances. The first exact algorithm searches the solution space from more workers to fewer workers. The second exact algorithm searches the solution space from fewer workers to more workers. The two exact algorithms search a part of solution space to obtain the optimal solution of reducing worker(s) without increasing makespan. According to the variable length of the feasible solutions, we propose a variable-length encoding heuristic algorithm for the large-scale instances. Finally, we use the extensive experiments to evaluate the performance of the proposed algorithms and to investigate some managerial insights on when and how to reduce worker(s) without increasing makespan by line-seru conversion.
Journal: International Journal of Production Research
Pages: 2990-3007
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2017.1284359
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1284359
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Template-Type: ReDIF-Article 1.0
Author-Name: Abdelhakim Khatab
Author-X-Name-First: Abdelhakim
Author-X-Name-Last: Khatab
Author-Name: EL Houssaine Aghezzaf
Author-X-Name-First: EL Houssaine
Author-X-Name-Last: Aghezzaf
Author-Name: Claver Diallo
Author-X-Name-First: Claver
Author-X-Name-Last: Diallo
Author-Name: Imene Djelloul
Author-X-Name-First: Imene
Author-X-Name-Last: Djelloul
Title: Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations
Abstract: 
 This paper deals with the selective maintenance problem for a multi-component system performing consecutive missions separated by scheduled breaks. To increase the probability of successfully completing its next mission, the system components are maintained during the break. A list of potential imperfect maintenance actions on each component, ranging from minimal repair to replacement is available. The general hybrid hazard rate approach is used to model the reliability improvement of the system components. Durations of the maintenance actions, the mission and the breaks are stochastic with known probability distributions. The resulting optimisation problem is modelled as a non-linear stochastic programme. Its objective is to determine a cost-optimal subset of maintenance actions to be performed on the components given the limited stochastic duration of the break and the minimum system reliability level required to complete the next mission. The fundamental concepts and relevant parameters of this decision-making problem are developed and discussed. Numerical experiments are provided to demonstrate the added value of solving this selective maintenance problem as a stochastic optimisation programme.
Journal: International Journal of Production Research
Pages: 3008-3024
Issue: 10
Volume: 55
Year: 2017
Month: 5
X-DOI: 10.1080/00207543.2017.1290295
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1290295
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Template-Type: ReDIF-Article 1.0
Author-Name: Bahman Naderi
Author-X-Name-First: Bahman
Author-X-Name-Last: Naderi
Author-Name: Ahmed Azab
Author-X-Name-First: Ahmed
Author-X-Name-Last: Azab
Author-Name: Katayoun Borooshan
Author-X-Name-First: Katayoun
Author-X-Name-Last: Borooshan
Title: A realistic multi-manned five-sided mixed-model assembly line balancing and scheduling problem with moving workers and limited workspace
Abstract: 
 The assembly line balancing problem can completely vary from one production line to the other. This paper deals with a realistic assembly line for the automotive industry inspired by Fiat Chrysler Automotive in North America and Parskhodro in Iran (both large-scale automotive companies). This problem includes some specific requirements that have not been studied in the literature. For example, the assembly line is five-sided, and workers can move along these sides. Due to the limited workspace, all the sides cannot work simultaneously at one station. First, a mixed integer linear programming model is proposed for the problem. Then, the model is improved to have a tighter linear relaxation. Moreover, an effective logic-based Benders’ decomposition algorithm is developed. After careful analysis of problem’s structure, three propositions are introduced. The master problem is well restricted by eight valid inequalities. Two different sub-problem types are defined to extract more information from the master problem’s solution. In this case, the algorithm adds effective cuts that reduce the solution space to the extent possible at each iteration. Thus, the number of iterations is significantly cut down. The performance of the model and algorithm, as well as improvement made on both, is evaluated.
Journal: International Journal of Production Research
Pages: 643-661
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1476786
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1476786
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Izadikhah
Author-X-Name-First: Mohammad
Author-X-Name-Last: Izadikhah
Author-Name: Majid Azadi
Author-X-Name-First: Majid
Author-X-Name-Last: Azadi
Author-Name: Vahid Shokri Kahi
Author-X-Name-First: Vahid
Author-X-Name-Last: Shokri Kahi
Author-Name: Reza Farzipoor Saen
Author-X-Name-First: Reza
Author-X-Name-Last: Farzipoor Saen
Title: Developing a new chance constrained NDEA model to measure the performance of humanitarian supply chains
Abstract: 
 Data envelopment analysis (DEA) is a method for measuring performance of decision making units (DMUs). Conventional DEA models view DMUs as black boxes. Network DEA (NDEA) models have been developed to overcome this shortfall. This paper develops a new NDEA model based on modified enhanced Russell measure model. This paper measures performance of humanitarian supply chains (HSCs) by an NDEA model. Capabilities of the proposed model are addressed by theorems. However, in the real world, there might be stochastic data. This paper presents a stochastic version of the proposed NDEA model to measure the performance of HSCs. We analyse main properties of our model. We present a case study to demonstrate the applicability of the proposed model.
Journal: International Journal of Production Research
Pages: 662-682
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1480840
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1480840
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingui Xie
Author-X-Name-First: Jingui
Author-X-Name-Last: Xie
Author-Name: Ning Wang
Author-X-Name-First: Ning
Author-X-Name-Last: Wang
Author-Name: Runkang Ding
Author-X-Name-First: Runkang
Author-X-Name-Last: Ding
Author-Name: Jinchen Guo
Author-X-Name-First: Jinchen
Author-X-Name-Last: Guo
Author-Name: Ling Xin
Author-X-Name-First: Ling
Author-X-Name-Last: Xin
Author-Name: Jian Liu
Author-X-Name-First: Jian
Author-X-Name-Last: Liu
Title: Association learning of Chinese herbal medicines and disease treatment efficacy
Abstract: 
 Patients with rheumatoid arthritis (RA) usually suffer from great pain. It is difficult to cure RA thoroughly. Among various treatment methods, the Chinese herbal medicine is attracting more and more attention. The aim of this study is to analyse the associations between the herbs and the effectively improved laboratory indexes used to evaluate the treatment efficacy. The data was collected from the First Hospital Affiliated to Anhui University of Chinese Medicine. The definition of effectively improved laboratory indexes was proposed. The association rules learning was applied to identify associations between the herbs and the effectively improved key laboratory indexes. Core herbs and their combination patterns were discovered from large-scale prescriptions. Our results were also validated by relevant traditional Chinese medicine theory and physicians' clinical experience, which indicated the applicability and reliability of our method in studying the effectiveness of herbal medicines.
Journal: International Journal of Production Research
Pages: 683-702
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1480841
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1480841
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Template-Type: ReDIF-Article 1.0
Author-Name: Lei Zhang
Author-X-Name-First: Lei
Author-X-Name-Last: Zhang
Author-Name: Xuening Chu
Author-X-Name-First: Xuening
Author-X-Name-Last: Chu
Author-Name: Hansi Chen
Author-X-Name-First: Hansi
Author-X-Name-Last: Chen
Author-Name: Bo Yan
Author-X-Name-First: Bo
Author-X-Name-Last: Yan
Title: A data-driven approach for the optimisation of product specifications
Abstract: 
 In order to develop the profit-maximising, market share-maximising or cost-minimising bundle of product engineering specifications with proper performance levels, an optimisation model driven by operating data is proposed. The operating data are input as the sources to conduct the optimisation and a data-based customer satisfaction function can be formed. Then, a customer choice model developed from the customer satisfaction is constructed to estimate the customer choice probability. The expected market share (EMS) then can be derived from the choice probability. After all, a multi-objective model is constructed to maximise the EMS and minimise the total engineering cost. The candidate Pareto-optimal solutions can be obtained by solving the optimisation model. Then a membership function is defined to select the optimal solution from the Pareto-optimal solutions. A case study for optimising the smartphone’s specifications is conducted to demonstrate the effectiveness of the newly developed approach. Compared with the commonly used Conjoint Analysis (CA) method in determining the most desired levels for product specifications, the proposed data-driven method can avoid the situation where the user’s preferences are irrational, making the proposed method be more practical in measuring customer preferences than the utility-based model.
Journal: International Journal of Production Research
Pages: 703-721
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1480843
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1480843
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Template-Type: ReDIF-Article 1.0
Author-Name: Fateme Marandi
Author-X-Name-First: Fateme
Author-X-Name-Last: Marandi
Author-Name: S.M.T. Fatemi Ghomi
Author-X-Name-First: S.M.T.
Author-X-Name-Last: Fatemi Ghomi
Title: Integrated multi-factory production and distribution scheduling applying vehicle routing approach
Abstract: 
 This paper introduces a new integrated multi-factory production and distribution scheduling problem in supply chain management. This supply chain consists of a number of factories joined together in a network configuration. The factories produce intermediate or finished products and supply them to other factories or to end customers that are distributed in various geographical zones. The problem consists of finding a production schedule together with a vehicle routing solution simultaneously to minimise the sum of tardiness cost and transportation cost. A mixed-integer programming model is developed to tackle the small-sized problems using CPLEX, optimally. Due to the NP-hardness, to deal with medium- and large-sized instances, this paper develops a novel Improved Imperialist Competitive Algorithm (IICA) employing a local search based on simulated annealing algorithm. Performance of the proposed IICA is compared with the optimal solution and also with four variants of population-based metaheuristics: Imperialist Competitive Algorithm, Genetic Algorithm, Particle Swarm Optimisation (PSO), and Improved PSO. Based on the computational results, it is statistically shown that quality of the IICA’s solutions is the same as optimal ones solving small problems. It also outperforms other algorithms in finding near-optimal solutions dealing with medium and large instances in a reasonably short running time.
Journal: International Journal of Production Research
Pages: 722-748
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1481301
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1481301
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Template-Type: ReDIF-Article 1.0
Author-Name: Jens Buergin
Author-X-Name-First: Jens
Author-X-Name-Last: Buergin
Author-Name: Philippe Blaettchen
Author-X-Name-First: Philippe
Author-X-Name-Last: Blaettchen
Author-Name: Juri Kronenbitter
Author-X-Name-First: Juri
Author-X-Name-Last: Kronenbitter
Author-Name: Katharina Molzahn
Author-X-Name-First: Katharina
Author-X-Name-Last: Molzahn
Author-Name: Yannick Schweizer
Author-X-Name-First: Yannick
Author-X-Name-Last: Schweizer
Author-Name: Caroline Strunz
Author-X-Name-First: Caroline
Author-X-Name-Last: Strunz
Author-Name: Manuel Almagro
Author-X-Name-First: Manuel
Author-X-Name-Last: Almagro
Author-Name: Frank Bitte
Author-X-Name-First: Frank
Author-X-Name-Last: Bitte
Author-Name: Stephan Ruehr
Author-X-Name-First: Stephan
Author-X-Name-Last: Ruehr
Author-Name: Marcello Urgo
Author-X-Name-First: Marcello
Author-X-Name-Last: Urgo
Author-Name: Gisela Lanza
Author-X-Name-First: Gisela
Author-X-Name-Last: Lanza
Title: Robust assignment of customer orders with uncertain configurations in a production network for aircraft manufacturing
Abstract: 
 Production of multi-variant products in a network requires the assignment of customer orders to locations and periods. This is a highly complex planning task, as requirements of procurement, production, distribution, and sales have to be considered. Providing customers with the flexibility of configuring their ordered products after order assignment further increases the complexity of the planning task by taking uncertainty into account. Therefore, a robust optimisation model, using scenarios representing potential customer-specific order configurations, is introduced. By providing enough flexibility to handle maximum work overload caused by the potential order configurations at locations, a robust assignment of orders can be guaranteed in order to avoid undesirable situations causing delays and additional costs. Therefore, the mid-term adjustments of the flexibility limits are enabled by the changeability of workforce supply by making use of external workers. An industrial application of the model in manufacturing of the Airbus A320 Family of aircrafts is presented. The costs for offering configuration flexibility to customers are quantified by the expected value of perfect information. The explicit consideration of configuration uncertainty through the use of scenarios is discussed based on the value of the stochastic solution in comparison to the results attained by simplistically using the expected value.
Journal: International Journal of Production Research
Pages: 749-763
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1482018
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1482018
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Template-Type: ReDIF-Article 1.0
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Euan Kidd
Author-X-Name-First: Euan
Author-X-Name-Last: Kidd
Author-Name: Arnab Bhattacharjee
Author-X-Name-First: Arnab
Author-X-Name-Last: Bhattacharjee
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Sustainable procurement performance of large enterprises across supply chain tiers and geographic regions
Abstract: 
 Sustainable procurement is steering today’s supply chains towards responsible business practices. This research aims to examine the trend in the sustainability performance of large enterprises for supplier selection across supply chain tiers and geographic locations. Secondary data on 83 global, large enterprises discussing sustainable procurement practices are analysed using hierarchical multiple regression analysis. Dynamic capabilities view and stakeholder theory are utilised to develop the hypotheses. The results show that sustainable procurement performance for large enterprises varies across supply chain tiers and increases in the direction of the end customer. Due to standardisation of regulations and dynamic capabilities of global, large enterprises, no significant difference is observed across geographic regions.
Journal: International Journal of Production Research
Pages: 764-778
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1482431
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1482431
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Template-Type: ReDIF-Article 1.0
Author-Name: Hojat Rezaei Soufi
Author-X-Name-First: Hojat
Author-X-Name-Last: Rezaei Soufi
Author-Name: S. Ali Torabi
Author-X-Name-First: S. Ali
Author-X-Name-Last: Torabi
Author-Name: Navid Sahebjamnia
Author-X-Name-First: Navid
Author-X-Name-Last: Sahebjamnia
Title: Developing a novel quantitative framework for business continuity planning
Abstract: 
 Today’s competitive and turbulent environment persuades every organisation to implement a business continuity management system (BCMS) for dealing with disruptive incidents such as earthquake, flood, and terrorist attacks. Within a BCMS, effective and efficient business continuity plans (BCPs) must be provided to ensure the continuity of organisation’s key products. This study develops a novel approach to select the most appropriate BCPs which can meet the business continuity key measures. First, a risk assessment process is conducted to define the disruptive incidents for which the organisation should have suitable BCPs. Then, two different possibilistic programming models including hard and soft BCP selection models are developed to determine appropriate BCPs under epistemic uncertainty of input data. These models aim to maximise the resilience level of the organisation while minimising the establishment cost of selected BCPs.‏ Finally, a real case study is provided whose results demonstrate the applicability and usefulness of the proposed approach.
Journal: International Journal of Production Research
Pages: 779-800
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1483586
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1483586
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:3:p:779-800




Template-Type: ReDIF-Article 1.0
Author-Name: Niki Kousi
Author-X-Name-First: Niki
Author-X-Name-Last: Kousi
Author-Name: Spyridon Koukas
Author-X-Name-First: Spyridon
Author-X-Name-Last: Koukas
Author-Name: George Michalos
Author-X-Name-First: George
Author-X-Name-Last: Michalos
Author-Name: Sotiris Makris
Author-X-Name-First: Sotiris
Author-X-Name-Last: Makris
Title: Scheduling of smart intra – factory material supply operations using mobile robots
Abstract: 
 This paper presents the design and prototype implementation of a service-based control system responsible for the material supply operations planning and coordination in assembly lines. The material supply processes are carried out by autonomous mobile units that are responsible for the transportation of the consumables from the warehouse to the production stations. The plan generation based on time and inventory level driven criteria is automatically carried out by a web-based software that can also distribute the derived plan to the autonomous mobile units. The proposed system was implemented on a case inspired by an actual production line from the automotive assembly sector. Discrete event simulation has been employed for the investigated production system, to derive the specifications for the mobile units (e.g. number of boxes that can carry simultaneously) that may serve the system efficiently. The results indicate that the proposed architecture integrated with the discussed mobile assistant units may provide high quality solutions with respect to the end user criteria.
Journal: International Journal of Production Research
Pages: 801-814
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1483587
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1483587
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:3:p:801-814




Template-Type: ReDIF-Article 1.0
Author-Name: Hasan Şahin
Author-X-Name-First: Hasan
Author-X-Name-Last: Şahin
Author-Name: Bayram Topal
Author-X-Name-First: Bayram
Author-X-Name-Last: Topal
Title: Examination of effect of information sharing on businesses performance in the supply chain process
Abstract: 
 Nowadays, supply chain management (SCM) has become one of the focal points of competition. The importance of information sharing in SCM is gradually increasing in terms of improving the business performance. In this study, an attempt to determine the effect of information sharing in the supply chain process (SCP) on cost, financial and business performance, in general, was made. The attempt was made by means of a measuring tool which is based on a theoretical approach. For this purpose, the structural equation model (SEM) was established by taking into account the supply chain structure, SCP, supply chain flexibility, environmental uncertainties and information sharing latent structures in businesses and the cost and financial performance indicators. In this study, differently from most other studies, two performance variables were included, and the model was created by defining these variables, which could be measured with more than one indicator, as latent variables. For this purpose, the data obtained from a questionnaire study performed on large firms within the scope of ISO 1000 were used. An attempt to reveal the factors affecting the cost and financial performance of businesses in SCM was made in the study. As a result of the analyses performed, the proposed SEM model was tested by taking into account various compliance criteria, and the validity and reliability of the model were determined.
Journal: International Journal of Production Research
Pages: 815-828
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1484954
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1484954
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Boris Sokolov
Author-X-Name-First: Boris
Author-X-Name-Last: Sokolov
Title: The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics
Abstract: 
 The impact of digitalisation and Industry 4.0 on the ripple effect and disruption risk control analytics in the supply chain (SC) is studied. The research framework combines the results from two isolated areas, i.e. the impact of digitalisation on SC management (SCM) and the impact of SCM on the ripple effect control. To the best of our knowledge, this is the first study that connects business, information, engineering and analytics perspectives on digitalisation and SC risks. This paper does not pretend to be encyclopedic, but rather analyses recent literature and case-studies seeking to bring the discussion further with the help of a conceptual framework for researching the relationships between digitalisation and SC disruptions risks. In addition, it emerges with an SC risk analytics framework. It analyses perspectives and future transformations that can be expected in transition towards cyber-physical SCs. With these two frameworks, this study contributes to the literature by answering the questions of (1) what relations exist between big data analytics, Industry 4.0, additive manufacturing, advanced trace & tracking systems and SC disruption risks; (2) how digitalisation can contribute to enhancing ripple effect control; and (3) what digital technology-based extensions can trigger the developments towards SC risk analytics.
Journal: International Journal of Production Research
Pages: 829-846
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1488086
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1488086
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:3:p:829-846




Template-Type: ReDIF-Article 1.0
Author-Name: Xiaolin Wang
Author-X-Name-First: Xiaolin
Author-X-Name-Last: Wang
Author-Name: Min Xie
Author-X-Name-First: Min
Author-X-Name-Last: Xie
Author-Name: Lishuai Li
Author-X-Name-First: Lishuai
Author-X-Name-Last: Li
Title: On optimal upgrade strategy for second-hand multi-component systems sold with warranty
Abstract: 
 Reliability improvement strategies such as upgrade, reconditioning and remanufacturing have been extensively adopted by dealers of second-hand systems to improve the system reliability and reduce the warranty servicing cost. However, most existing studies on this topic do not consider the multi-component structures of complex second-hand systems, and either treat them as black-box systems by ignoring their internal structures or simply deal with individual components. In this paper, a new upgrade model is developed for complex second-hand systems sold with a non-renewing free repair/replacement warranty, by explicitly considering their multi-component configurations. Two types of components, i.e. repairable and non-repairable components, are taken into account. During the upgrade process, non-repairable components can be upgraded only by replacement (if necessary), while repairable ones may be imperfectly upgraded with various degrees. The main objective of the dealer is to determine which components to upgrade and the corresponding upgrade degrees, to minimise the total expected servicing cost. In view of the problem structure, a marginal analysis based algorithm is presented. It is shown that the proposed upgrade strategy contains the ‘no upgrade’ strategy and the ‘component-level perfect upgrade/replacement’ strategy as special cases, and outperforms them. Finally, several extensions of the proposed upgrade model are discussed.
Journal: International Journal of Production Research
Pages: 847-864
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1488087
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1488087
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:3:p:847-864




Template-Type: ReDIF-Article 1.0
Author-Name: Parisa Dolati Neghabadi
Author-X-Name-First: Parisa
Author-X-Name-Last: Dolati Neghabadi
Author-Name: Karine Evrard Samuel
Author-X-Name-First: Karine
Author-X-Name-Last: Evrard Samuel
Author-Name: Marie-Laure Espinouse
Author-X-Name-First: Marie-Laure
Author-X-Name-Last: Espinouse
Title: Systematic literature review on city logistics: overview, classification and analysis
Abstract: 
 City logistics is one of the significant branches of supply chain management, dealing with the logistics and transportation activities in urban areas. This research area has recently appropriated an exponential growth of publications. This paper presents a bibliometric analysis along with a systematic literature review to organise the results of surveying more than 370 papers and research works published since 2010. We identify the top contributing research topics. The most common keywords used in the city logistics literature are referred to in order to propose six research categories identifying the main innovative research perspectives.
Journal: International Journal of Production Research
Pages: 865-887
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1489153
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1489153
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:3:p:865-887




Template-Type: ReDIF-Article 1.0
Author-Name: Melih Çelik
Author-X-Name-First: Melih
Author-X-Name-Last: Çelik
Author-Name: Haldun Süral
Author-X-Name-First: Haldun
Author-X-Name-Last: Süral
Title: Order picking in parallel-aisle warehouses with multiple blocks: complexity and a graph theory-based heuristic
Abstract: 
 In this paper, we consider the order picking problem (OPP), which constitutes one of the special cases of the Steiner travelling salesperson problem and addresses the costliest operation in a warehouse. Given a list of items to be picked and their locations in the warehouse layout, the OPP aims to find the shortest route that starts from a depot point, picks all the items in the list, and returns to the depot. This paper fills two important gaps regarding the OPP. First, to the best of our knowledge, we present the first complexity results on the problem. Second, we propose a heuristic approach that makes use of its graph-theoretic properties. Computational experiments on randomly generated instances show that the heuristic not only outperforms its state-of-the-art counterparts in the literature, but it is also robust in terms of changing problem parameters.
Journal: International Journal of Production Research
Pages: 888-906
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1489154
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1489154
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:3:p:888-906




Template-Type: ReDIF-Article 1.0
Author-Name: Henrik Jaldell
Author-X-Name-First: Henrik
Author-X-Name-Last: Jaldell
Title: Measuring productive performance using binary and ordinal output variables: the case of the Swedish fire and rescue services
Abstract: 
 Fire protection is an example of a complex production process. This study measures efficiency by constructing binary and ordinal output variables from information on residential fires in Sweden about how a fire spreads from when the fire and rescue brigade arrives to when a fire is suppressed. The motivations behind this study are that there are only a few studies trying to estimate production efficiency for fire and rescue services, that data on a more detailed level is interesting for some public services, and there is a need to be able to measure efficiency differences even if only a binary or ordinal output variable is available. Using a logit random parameter model, the random effects are interpreted as efficiency differences. The conclusions are that fire and rescue services with a more flexible fire organisation with first response persons, working in collaboration with other municipalities and with larger populations are more efficient.
Journal: International Journal of Production Research
Pages: 907-917
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1489159
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1489159
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:3:p:907-917




Template-Type: ReDIF-Article 1.0
Author-Name: Tsui-Ping Chung
Author-X-Name-First: Tsui-Ping
Author-X-Name-Last: Chung
Author-Name: Zhen Xue
Author-X-Name-First: Zhen
Author-X-Name-Last: Xue
Author-Name: Tong Wu
Author-X-Name-First: Tong
Author-X-Name-Last: Wu
Author-Name: Stephen C. Shih
Author-X-Name-First: Stephen C.
Author-X-Name-Last: Shih
Title: Minimising total completion time on single-machine scheduling with new integrated maintenance activities
Abstract: 
 A single-machine scheduling problem with new maintenance activities is examined in this paper. In the scheduling literature, it is often assumed that the interval between maintenance activities is fixed or within a specified time frame. However, this assumption may not hold true in many real-world situations, such as the maintenance activities in wafer manufacturing of semiconductor. Before the wafer manufacturing process starts, it is imperative that the wafers go through a number of cleaning operations to avoid contamination. Using a cleaning agent as the main material of wafer cleaning, the contamination will be dissolved and removed from wafer surface. In case of contamination being accumulated substantial and going beyond a permitted value, the cleaning agent is highly likely to damage the wafer surfaces. Thus, the interval between maintenance activities in the wafer manufacturing process is deemed irregular. The objective function of the proposed problem is to minimise total completion time. Addressing the problem, a binary integer programming model is formulated in this paper. Furthermore, with the research problem being NP-hard, a heuristic based on two special properties is proposed to address the problem. To evaluate and validate the proposed heuristic, a new lower bound is further developed. Extensive experiments have been conducted showing that the proposed heuristic efficiently yields a near-optimal solution with an average percentage error of 15.4 from lower bound.
Journal: International Journal of Production Research
Pages: 918-930
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1496294
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1496294
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Author-Name: Paolo Renna
Author-X-Name-First: Paolo
Author-X-Name-Last: Renna
Title: Workload control in dual-resource constrained high-variety shops: an assessment by simulation
Abstract: 
 Workload Control (WLC) seeks to align capacity with demand, where capacity is typically assumed to be restricted by a single constraint – machine capacity. In practice, however, shops are often restricted by dual resource constraints: labour and machines. This study, therefore, uses simulation to investigate the performance of WLC in Dual Resource Constrained (DRC) high-variety shops with fully interchangeable labour. By considering several environmental factors and different labour assignment and dispatching rules, it is demonstrated that the order release function of WLC maintains its positive impact on performance in a DRC shop under different staffing levels. The positive effect of considering labour availability at release, as proposed in previous research, could not, however, be confirmed. Thus, the original release method can be applied if labour is fully interchangeable. In terms of labour assignment, we show that a distinct assignment pattern that differs between upstream and downstream stations improves performance if the routing is directed. Meanwhile, dispatching plays a less important role but creates important interaction effects with the assignment rule. Finally, the results suggest that increasing the service rate is a better response to the reduction in capacity that results from labour absenteeism than lowering the input frequency of work.
Journal: International Journal of Production Research
Pages: 931-947
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1497313
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1497313
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Template-Type: ReDIF-Article 1.0
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Alessandro Persona
Author-X-Name-First: Alessandro
Author-X-Name-Last: Persona
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Valentina Visentin
Author-X-Name-First: Valentina
Author-X-Name-Last: Visentin
Title: A model for rest allowance estimation to improve tasks assignment to operators
Abstract: 
 Manual activities are still present in production systems, such as order picking in warehouses, material handling in production systems, loading and unloading of work centres. Many scientific contributions have widely demonstrated production system efficiency is strictly linked to the operator wellbeing. In fact, activities at different pace and duration imply different productivity but also different effects on the fatigue accumulation acquired by the operators, with consequently required resting period. It is necessary to integrate operator fatigue and recovery analysis into traditional decision support models for the design and management of production systems.This paper aims to present an analytical model for setting the time necessary for operators to recover from the performed activity. According to previous research, the exponential trend of fatigue accumulation and recovery alleviation is studied. The energy expenditure rate, predicted with heart rate monitoring, is used to model the fatigue/recovery level, varying the physiological factors of the operators and the characteristics of the analysed manual activities. The model is limited to the activities where the whole body is used rather than a specific part stressed continuously. Finally, it is applied to optimise the scheduling of activities among operators in a manual order picking system. It is demonstrated that its use improves performance in terms of productivity.
Journal: International Journal of Production Research
Pages: 948-962
Issue: 3
Volume: 57
Year: 2019
Month: 2
X-DOI: 10.1080/00207543.2018.1497816
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1497816
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhaolin (Erick) Li
Author-X-Name-First: Zhaolin (Erick)
Author-X-Name-Last: Li
Author-Name: Qiang Lu
Author-X-Name-First: Qiang
Author-X-Name-Last: Lu
Author-Name: Masoud Talebian
Author-X-Name-First: Masoud
Author-X-Name-Last: Talebian
Title: Online versus bricks-and-mortar retailing: a comparison of price, assortment and delivery time
Abstract: 
 The popularity of online retailing has created great opportunities and challenges for retailers. A key challenge faced by many retailers is the choice between the clicks, the bricks-and-mortar, and the bricks-and-clicks strategies. In this paper, we develop a comprehensive framework for selecting the appropriate distribution channel given assortment, logistics and consumer characteristics. Under the traditional bricks-and-mortar retail model, the retailer displays and sells the assortment in a physical store, whereas under the online retail model, the retailer accepts orders online and delivers the products offline. The traditional retailer jointly determines the breadth, the depth and the price of the assortment, whereas the online retailer jointly determines the breadth and price of the assortment and the delivery time. After deriving the joint optimal solution for the traditional and the online retailers, we compare their performance. We analytically and numerically examine how inventory cost, delivery cost and consumer behaviours could affect the optimal distribution strategy and customer service.
Journal: International Journal of Production Research
Pages: 3823-3835
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.973074
File-URL: http://hdl.handle.net/10.1080/00207543.2014.973074
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3823-3835




Template-Type: ReDIF-Article 1.0
Author-Name: Ruggero Golini
Author-X-Name-First: Ruggero
Author-X-Name-Last: Golini
Author-Name: Matteo Kalchschmidt
Author-X-Name-First: Matteo
Author-X-Name-Last: Kalchschmidt
Title: Designing an expert system to support competitiveness through global sourcing
Abstract: 
 Performing global sourcing – which is defined as the amount of purchases made by a plant outside its continent of origin – effectively is highly complicated because of several concurring variables (e.g. number of suppliers, supplied goods, and the location of the buyer and supplier, among other factors). However, the findings available in literature – which are often focused on few variables – can be difficult to be applied by managers to take decisions in this domain. Because of this limitation, we built an expert system (called global sourcing expert system [GSES]) to suggest what type of supply management (e.g. supplier base management, supplier selection and supplier integration) practices are most suitable given the level of global sourcing, strategy and other characteristics of the company. To build the theoretical grounding of the GSES, we performed a deep literature review to identify the highest number of variables that can be related to a global sourcing strategy. Next, we built the GSES exploiting data from the International Manufacturing Strategy Survey (IMSS) as a knowledge base. This data-set is composed of 725 companies surveyed in 2009 in the assembly manufacturing industries (ISIC code range 28–35) distributed across 19 countries. Finally, the system was validated by means of simulations and five real cases to verify that the expert system was actually usable by practitioners and provided robust insights. The paper also includes a detailed description of how the tool is built to allow future replications.
Journal: International Journal of Production Research
Pages: 3836-3855
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.974842
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974842
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3836-3855




Template-Type: ReDIF-Article 1.0
Author-Name: Jie Yang
Author-X-Name-First: Jie
Author-X-Name-Last: Yang
Author-Name: Kee Hung Lai
Author-X-Name-First: Kee Hung
Author-X-Name-Last: Lai
Author-Name: Jifu Wang
Author-X-Name-First: Jifu
Author-X-Name-Last: Wang
Author-Name: Rupak Rauniar
Author-X-Name-First: Rupak
Author-X-Name-Last: Rauniar
Author-Name: Hongming Xie
Author-X-Name-First: Hongming
Author-X-Name-Last: Xie
Title: Strategic alliance formation and the effects on the performance of manufacturing enterprises from supply chain perspective
Abstract: 
 This study examines the antecedents of strategic alliance formation in manufacturing firms in China, the alliance effect on innovation capability and dyadic quality performance, and how these two organisational capabilities are related to the supply chain performance of Chinese manufacturing enterprises in Shanghai. We perform a series of statistical techniques including logistic regression analysis, multivariate analysis of variance (MANOVA) and multiple regression analysis for assessing the hypothesised relationships. Our findings indicate that relational stability and effective communication are significant antecedent factors influencing strategic alliance formation among Chinese manufacturing enterprises. Such alliance formation is found to benefit innovation capability and dyadic quality performance, which are significant contributors to the supply chain performance of Chinese manufacturers. We provide important theoretical and practical implications on these antecedents and consequences of strategic alliance formation leading to supply chain performance in the Chinese manufacturing context.
Journal: International Journal of Production Research
Pages: 3856-3870
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.974843
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974843
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3856-3870




Template-Type: ReDIF-Article 1.0
Author-Name: Ruth Sagron
Author-X-Name-First: Ruth
Author-X-Name-Last: Sagron
Author-Name: Dean Grosbard
Author-X-Name-First: Dean
Author-X-Name-Last: Grosbard
Author-Name: Gad Rabinowitz
Author-X-Name-First: Gad
Author-X-Name-Last: Rabinowitz
Author-Name: Israel Tirkel
Author-X-Name-First: Israel
Author-X-Name-Last: Tirkel
Title: Approximation of single-class queueing networks with downtime-induced traffic variability
Abstract: 
 Queuing networks have been used with partial success for analytical modelling of manufacturing systems. In this paper, we consider a tandem system with high traffic variability caused by downtime events in the first queue. We propose improved approximation for departure variability in order to predict the waiting duration at the bottleneck queue located last in the line. We demonstrate that existing methods do not properly approximate such systems and provide some reasons and insights. Thus, a new decomposition method which employs the variability function principles is proposed. We differentiate between two components of the departure variability in multi-class systems: the ‘within-class effect’ – the variability caused by the class’ own inter-arrival and service time distributions – and the ‘between-class effect’ – the variability caused by interactions with other classes. Our analysis shows that the first effect can be approximated by existing multi-class decomposition methods, while the second effect requires a new development. Our proposed approximation for between-class effect is based on simulating a proper sub-system. The method enables modelling different policies of downtimes (e.g. FCFS, Priority). Numerical experiments show relative errors much smaller vs. existing procedures.
Journal: International Journal of Production Research
Pages: 3871-3887
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.974845
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974845
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3871-3887




Template-Type: ReDIF-Article 1.0
Author-Name: Chao Ou-Yang
Author-X-Name-First: Chao
Author-X-Name-Last: Ou-Yang
Author-Name: Hsin-Jung Cheng
Author-X-Name-First: Hsin-Jung
Author-X-Name-Last: Cheng
Author-Name: Yeh-Chun Juan
Author-X-Name-First: Yeh-Chun
Author-X-Name-Last: Juan
Title: An Integrated mining approach to discover business process models with parallel structures: towards fitness improvement
Abstract: 
 Process mining (PM) is a technique to extract a process model from an event log to represent the process behaviour recorded in that event log. A mined process model with high fitness means that it can reflect most of the process behaviour recorded in the event log. Previous studies have shown that the mined model with high fitness can be used in process improvement, such as fraud detection, continuous process improvement and benchmarking. Genetic process mining (GPM) is a famous PM approach, which can simultaneously identify several process structures from event logs. However, GPM cannot effectively discover parallel structures from event logs. This study proposes a PM approach based on integration of GPM, particle swarm optimisation and differential evolution to find process models with high fitness for event logs involving multiple parallel structures. The results show that the proposed approach does indeed lead to improvement in gaining process models with high fitness for event logs involving multiple parallel structures.
Journal: International Journal of Production Research
Pages: 3888-3916
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.974847
File-URL: http://hdl.handle.net/10.1080/00207543.2014.974847
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3888-3916




Template-Type: ReDIF-Article 1.0
Author-Name: Gang Wang
Author-X-Name-First: Gang
Author-X-Name-Last: Wang
Author-Name: Ratna Babu Chinnam
Author-X-Name-First: Ratna Babu
Author-X-Name-Last: Chinnam
Author-Name: Ibrahim Dogan
Author-X-Name-First: Ibrahim
Author-X-Name-Last: Dogan
Author-Name: Yan Jia
Author-X-Name-First: Yan
Author-X-Name-Last: Jia
Author-Name: Melvin Houston
Author-X-Name-First: Melvin
Author-X-Name-Last: Houston
Author-Name: James Ockers
Author-X-Name-First: James
Author-X-Name-Last: Ockers
Title: Focused factories: a Bayesian framework for estimating non-product related investment
Abstract: 
 Focused factories are one of the new manufacturing trends for automotive suppliers. A key requirement for these suppliers is the ability to accurately estimate both product and non-product related investment in these facilities to quote profitable business. We propose a systematic Bayesian framework to estimate non-product related investment in focused factories. Our approach incorporates uncertainty in the activity-based costing method and applies Monte Carlo simulation process to generate distributions of investment for the cost centres, and for the different project phases in setting up a facility. A Bayesian-updating procedure is introduced to improve parameter estimations as new information becomes available with experience in setting up these facilities. Our approach is deployed at a leading global automotive tier-one supplier, Visteon Corporation. The efficacy of the Visteon-focused factory cost model is validated using subject matter experts as well as by comparing the model results with estimates from the typical current process.
Journal: International Journal of Production Research
Pages: 3917-3933
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.975373
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975373
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3917-3933




Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Thomas
Author-X-Name-First: Andrew
Author-X-Name-Last: Thomas
Author-Name: Duc Truong Pham
Author-X-Name-First: Duc Truong
Author-X-Name-Last: Pham
Author-Name: Mark Francis
Author-X-Name-First: Mark
Author-X-Name-Last: Francis
Author-Name: Ron Fisher
Author-X-Name-First: Ron
Author-X-Name-Last: Fisher
Title: Creating resilient and sustainable manufacturing businesses – a conceptual fitness model
Abstract: 
 Over recent years, UK manufacturing industry has experienced turbulence in its business performance. Lower cost products, and responsive and flexible processes, are now essential in order for a company to capture new markets and to become economically resilient. Business resiliency is a term used frequently to describe a company’s ability to adapt and cope with disturbance. This has led to the generation of many frameworks and models aimed at guiding companies towards improved business performance. However, these frameworks are primarily strategic in nature and do not necessarily focus on creating resilience at an operational level in manufacturing companies. The authors employ a mixed research approach initially undertaking a literature review and then a screening survey in to 25 manufacturing companies in order to identify the key business resiliency techniques employed. Following this, a focus group goes on to detail a new manufacturing resiliency model called the fit operational model. The model’s effectiveness is then assessed and adjusted as a result of being implemented in a subject company.
Journal: International Journal of Production Research
Pages: 3934-3946
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.975850
File-URL: http://hdl.handle.net/10.1080/00207543.2014.975850
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3934-3946




Template-Type: ReDIF-Article 1.0
Author-Name: Giuliano Almeida Marodin
Author-X-Name-First: Giuliano
Author-X-Name-Last: Almeida Marodin
Author-Name: Tarcisio Abreu Saurin
Author-X-Name-First: Tarcisio Abreu
Author-X-Name-Last: Saurin
Title: Managing barriers to lean production implementation: context matters
Abstract: 
 As the barriers to lean production implementation (LPI) are influenced by the context, the search for generalisable barriers, relationships, priorities and control measures is to some extent elusive. This study introduces a framework for managing barriers to LPI in specific companies, which is comprised of five stages: (i) description of the context; (ii) identification of the barriers; (iii) analysis of the influence of the context on the barriers; (iv) analysis of the relationships among the barriers using interpretive structural modelling – this sets a basis for prioritising the barriers; and (v) a feedback meeting to discuss the results of data collection, which also informs on the development of an action plan to control the barriers. The use of the framework is illustrated by a case study of a manufacturing plant. Data collection involved interviews, observations and document analysis. A follow-up visit to the company was conducted 18 months after the initial data collection, in order to identify changes in the context. The framework is a contribution in terms of prescriptive theory related to LPI, and is also a means for the generation of data for developing descriptive theory related to the barriers to LPI.
Journal: International Journal of Production Research
Pages: 3947-3962
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.980454
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980454
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3947-3962




Template-Type: ReDIF-Article 1.0
Author-Name: Steven Peters
Author-X-Name-First: Steven
Author-X-Name-Last: Peters
Title: Optimal investment policies in premature manufacturing technologies
Abstract: 
 Mass customisation, increasing complexity and variety of new products as well as ongoing global competition force companies to use innovative manufacturing technologies. However, the way from a new and premature manufacturing technology towards its application in series production at the level of operational excellence is challenging. Recent examples in the automotive industry, such as alternative powertrains and new body concepts for lightweight design, have shown the necessity to integrate production research into the very early phase of product development – going far beyond established approaches of simultaneous engineering. This paper presents an optimisation method which enables companies to find the best point in time to start investing in a new premature manufacturing technology during product development. Therefore, a dynamic and stochastic model is used based on a Markovian decision process. Finally, the method is applied in an example of a manufacturing technology for the automotive industry.
Journal: International Journal of Production Research
Pages: 3963-3974
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.980455
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980455
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Template-Type: ReDIF-Article 1.0
Author-Name: Fiorenzo Franceschini
Author-X-Name-First: Fiorenzo
Author-X-Name-Last: Franceschini
Author-Name: Maurizio Galetto
Author-X-Name-First: Maurizio
Author-X-Name-Last: Galetto
Author-Name: Domenico Maisano
Author-X-Name-First: Domenico
Author-X-Name-Last: Maisano
Author-Name: Luca Mastrogiacomo
Author-X-Name-First: Luca
Author-X-Name-Last: Mastrogiacomo
Title: Prioritisation of engineering characteristics in QFD in the case of customer requirements orderings
Abstract: 
 Quality Function Deployment is an effective tool to orient the design of a product and related production processes towards the real exigencies of the end-user. Its first phase – the house of quality – is aimed at translating customer requirements (CRs) into engineering characteristics (ECs) of the product of interest, also determining an ECs’ prioritisation. All of the techniques proposed for tackling this problem are based on the assumption that the importance of each CR is expressed on interval or ratio scales (i.e. cardinal scales). To this end, customer evaluations – naturally expressed on ordinal scales – are artfully turned into numbers. This study introduces a novel technique – denominated as ordinal prioritisation method – that can be applied to prioritise ECs. The method addresses the problem of the prioritisation of ECs when the importance of CRs is given on an ordinal scale. The description of the method is supported by some application examples.
Journal: International Journal of Production Research
Pages: 3975-3988
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.980457
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980457
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3975-3988




Template-Type: ReDIF-Article 1.0
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme Luz
Author-X-Name-Last: Tortorella
Author-Name: Giuliano Almeida Marodin
Author-X-Name-First: Giuliano Almeida
Author-X-Name-Last: Marodin
Author-Name: Flávio Sanson Fogliatto
Author-X-Name-First: Flávio Sanson
Author-X-Name-Last: Fogliatto
Author-Name: Rogério Miorando
Author-X-Name-First: Rogério
Author-X-Name-Last: Miorando
Title: Learning organisation and human resources management practices: an exploratory research in medium-sized enterprises undergoing a lean implementation
Abstract: 
 Despite the fact that Lean Manufacturing (LM) implementation has been widely discussed in the literature, a reduced number of works focus on medium-sized enterprises (MEs). Such gap becomes more evident when searching for works exploring the dimensions of learning organisation (DLO) that surround LM implementation in MEs. This paper aims at assessing DLO maturity and the importance of human resources management (HRM) practices in MEs that are starting LM implementation. We verify the applicability of a method for assessing maturity levels of DLO and HRM practices in seven different MEs. The method was originally conceived for large enterprises well advanced in the lean implementation process; it combines concepts of HRM and organisational learning with lean implementation roadmaps. Adapting the method for application in MEs allows such companies to anticipate and minimise organisational learning problems by conducting appropriate HRM practices, leading to a more effective LM implementation. We conclude that the method is a suitable diagnostic tool for MEs, indicating which phases of the lean roadmap are better prepared to be implemented.
Journal: International Journal of Production Research
Pages: 3989-4000
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.980462
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980462
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3989-4000




Template-Type: ReDIF-Article 1.0
Author-Name: Prakash J. Singh
Author-X-Name-First: Prakash J.
Author-X-Name-Last: Singh
Author-Name: Frank Wiengarten
Author-X-Name-First: Frank
Author-X-Name-Last: Wiengarten
Author-Name: Alka A. Nand
Author-X-Name-First: Alka A.
Author-X-Name-Last: Nand
Author-Name: Teresa Betts
Author-X-Name-First: Teresa
Author-X-Name-Last: Betts
Title: Beyond the trade-off and cumulative capabilities models: alternative models of operations strategy
Abstract: 
 Organisations are expected to develop sound strategies relating to their core operations capabilities of cost efficiency, quality, delivery, flexibility and innovation, to gain and maintain competitive advantage. However, there is a paucity of specific models that can be used to explain and predict how organisations combine and use these capabilities. Previous research has primarily focused on the ‘trade-off’ and the ‘cumulative capabilities’ models. In this study, data from an international sample of 1438 manufacturing plants are used to explore other models that organisations are using in addition to the two predominant models. This analysis shows that, in practice, the trade-off model is not used, but the cumulative capabilities model is used extensively. Further, our proposed new models, the ‘threshold’, ‘average’ and ‘multiple’, are prevalent in many plants. Also, a small proportion of the plants have in place the ‘uncompetitive’ model. In terms of relative effectiveness, there are no significant differences between the models with respect to several measures of operational performance. Overall, this study provides empirical evidence that there are other operations strategy models beyond the trade-off and cumulative capabilities dichotomy that organisations deploy.
Journal: International Journal of Production Research
Pages: 4001-4020
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.983277
File-URL: http://hdl.handle.net/10.1080/00207543.2014.983277
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Template-Type: ReDIF-Article 1.0
Author-Name: Hong-Bin Yan
Author-X-Name-First: Hong-Bin
Author-X-Name-Last: Yan
Author-Name: Tieju Ma
Author-X-Name-First: Tieju
Author-X-Name-Last: Ma
Title: A fuzzy group decision making approach to new product concept screening at the fuzzy front end
Abstract: 
 Efficient new product concept screening plays an important role in new product development (NPD). Due to the inherent complexity, incompleteness and ambiguity in NPD, fuzzy approaches have been widely developed and used for new product concept screening. Because of the group behaviours (diversity of gate-team members and senior management’s preference), the new product concept screening is typical group decision-making problem. Moreover, it is usually more efficient to conduct the screening evaluation in a gate-team and make a screening decision outside the gate-team by senior management. Therefore, it is necessary to provide a result with a high degree of flexibility and credibility so as to better support the senior management to make a screening decision in NPD. Existing fuzzy approaches neglect these two issues. Towards this end, a three-stage fuzzy group decision-making approach is proposed to assist the senior management perform new product concept screening. A case study is borrowed from the literature to illustrate our proposed approach. Our approach is compared with two existing techniques from theoretical and empirical perspectives. The results show that the proposed approach can capture the group behaviours and present a relatively realistic and informative result which gives the senior management a high degree of flexibility and credibility in new product concept screening.
Journal: International Journal of Production Research
Pages: 4021-4049
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.986297
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986297
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Template-Type: ReDIF-Article 1.0
Author-Name: T.C. Wong
Author-X-Name-First: T.C.
Author-X-Name-Last: Wong
Author-Name: Alan H.S. Chan
Author-X-Name-First: Alan H.S.
Author-X-Name-Last: Chan
Title: A neural network-based methodology of quantifying the association between the design variables and the users’ performances
Abstract: 
 User performance is highly correlated with design variables of a system. Such association can be described as display–control relationship. In this study, a neural network-based methodology is proposed to identify and quantify the association among design variables (inputs) and to compute their relative influences (RIs) on the two performance measures (outputs) of user response time and response accuracy, using artificial neural network, generalised regression neural network, support vector regression (SVR), multiple linear regression and response surface model. Based on the results of the comparison, it is found that neural network-based methods are more reliable than SVR-based methods in computing the RI of design variables. As a result of our analysis, the best option for optimising each of the measures is suggested. Some useful observations about the design of man–machine systems are also presented, discussed and visualised. In the study of man–machine systems, quantitative methods are seldom adopted for examining the mappings between various displays and controls under a variety of operating conditions. The major contribution of this study is to provide some insights into the usefulness of quantitative methods in evaluating man–machine design in terms of display–control compatibility and to extract explanatory information from renowned black box systems such as neural networks.
Journal: International Journal of Production Research
Pages: 4050-4067
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.988886
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988886
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Template-Type: ReDIF-Article 1.0
Author-Name: Wiljeana J. Glover
Author-X-Name-First: Wiljeana J.
Author-X-Name-Last: Glover
Author-Name: Jennifer A. Farris
Author-X-Name-First: Jennifer A.
Author-X-Name-Last: Farris
Author-Name: Eileen M. Van Aken
Author-X-Name-First: Eileen M.
Author-X-Name-Last: Van Aken
Title: The relationship between continuous improvement and rapid improvement sustainability
Abstract: 
 While rapid improvement efforts, e.g. Kaizen events, and continuous improvement efforts, i.e. kaizen, remain popular approaches to operational excellence, it is rare that organisations fully sustain change from these initiatives. The impact of both Kaizen events and kaizen may be substantially lower, if not entirely eliminated, after significant time has elapsed from initial implementation of changes. In this paper, we examine how having a continuous improvement culture can support rapid improvement sustainability via an examination of the impact of Kaizen events several months after implementation. Employing a dynamic capabilities perspective and using the institutionalisation of planned change framework, we empirically examine this relationship via a field study of 65 Kaizen events in eight manufacturing organisations. In short, we find that the extent to which work area employees exhibit peer learning, as well as awareness and responsibility both inside and outside of their work area, and the extent to which changes are accepted are significantly related to the perceived impact of Kaizen events several months after implementation. This research adds to current understanding of Kaizen events and kaizen, providing evidence to guide the use of Kaizen events and to inform areas for future research.
Journal: International Journal of Production Research
Pages: 4068-4086
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.991841
File-URL: http://hdl.handle.net/10.1080/00207543.2014.991841
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Template-Type: ReDIF-Article 1.0
Author-Name: Luis Mendes
Author-X-Name-First: Luis
Author-X-Name-Last: Mendes
Author-Name: José Machado
Author-X-Name-First: José
Author-X-Name-Last: Machado
Title: Employees’ skills, manufacturing flexibility and performance: a structural equation modelling applied to the automotive industry
Abstract: 
 The issue of manufacturing flexibility (MF) is gaining growing importance in production/operations management, mainly due to the changing nature of competition, and in such a context, the efficient use of resources may be a major concern and challenge for manufacturing strategy in many industries, particularly in the capital intensive automotive industry. Building on the foundation laid by previous researches on flexibility concerns, the objective of this study is to gain further insights on the nature of the linkage between employees’ skills and MF, as well as its impact on business performance. Moving toward such purpose, a structural equation modelling is applied to data collected from 144 manufacturing firms in the automotive industry from several countries. Findings provide evidences that workforce’ skills may foster MF as an effective approach to cope with uncertain environments and turbulent markets. More precisely, results show that employees’ skills directly influence new product, volume and mix flexibility, which in turn directly influence business performance. Moreover, findings revealed that MF mediates partially the relationship between employees’ skills and business performance.
Journal: International Journal of Production Research
Pages: 4087-4101
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.993772
File-URL: http://hdl.handle.net/10.1080/00207543.2014.993772
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Template-Type: ReDIF-Article 1.0
Author-Name: Ramy Harik
Author-X-Name-First: Ramy
Author-X-Name-Last: Harik
Author-Name: Wissam EL Hachem
Author-X-Name-First: Wissam
Author-X-Name-Last: EL Hachem
Author-Name: Khaled Medini
Author-X-Name-First: Khaled
Author-X-Name-Last: Medini
Author-Name: Alain Bernard
Author-X-Name-First: Alain
Author-X-Name-Last: Bernard
Title: Towards a holistic sustainability index for measuring sustainability of manufacturing companies
Abstract: 
 Competition from low wage countries and the adoption of free market strategies have forced manufacturing firms to recognise and implement productivity enhancement strategies. This research defines a holistic sustainability index embedding several performance indices. The aim of this study was to establish a relevant framework that would assess the current situation of an industry through aggregation of environmental, social, economical as well as manufacturing variables. The proposition has its roots in trends and gaps in the sustainability literature of manufacturing industries and is based on the analytic hierarchy process (AHP) method. A list of indicators measuring the industry performance based on an AHP scoring methodology is proposed. The next stages include grouping industries according to common deficiencies across the four dimensions and establishing a cooperation framework. The food manufacturing industry is the main target in this study and will benefit from adopting sustainable long-term policies. By recognising the importance of social–environmental sustainability and taking the initiative to pursue it, profits will grow as a positive effect of such policies. The added value is twofold: (1) coupling all sustainability dimensions, often addressed in silos and (2) integrating manufacturing indicators which enable the analysis of interrelationships with sustainability.
Journal: International Journal of Production Research
Pages: 4117-4139
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.993773
File-URL: http://hdl.handle.net/10.1080/00207543.2014.993773
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanlong Cao
Author-X-Name-First: Yanlong
Author-X-Name-Last: Cao
Author-Name: Kui Zhao
Author-X-Name-First: Kui
Author-X-Name-Last: Zhao
Author-Name: Jiangxin Yang
Author-X-Name-First: Jiangxin
Author-X-Name-Last: Yang
Author-Name: Wei Xiong
Author-X-Name-First: Wei
Author-X-Name-Last: Xiong
Title: Constructing the integrated strategic performance indicator system for manufacturing companies
Abstract: 
 The performance indicator system based on balanced scorecard (BSC) is the vertical breakdown proceeding from the strategy, it neglects considering the collaborative relationship between the upstream and downstream departments. This paper proposes a design method of company integrated strategic performance indicator system based on BSC and the ‘suppliers-input-process-output-customers’ model (SIPOC). First, the strategy map and BSC are adopted to develop the company-level key performance indicators (KPIs), which are gradually broken down to different departments and forming department KPIs. Then, the common performance indicators (CPIs) are determined based on the SIPOC process analysis; thus, achieving the synergy between different departments. Finally, the departmental performance indicators system can be constructed by composing KPIs and CPIs together. While achieving the strategic vertical breakdown, this method can bring about the synergy between departments in horizontal operation. Also, a case study from a manufacturing company is performed to verify the feasibility of the method.
Journal: International Journal of Production Research
Pages: 4102-4116
Issue: 13
Volume: 53
Year: 2015
Month: 7
X-DOI: 10.1080/00207543.2014.994715
File-URL: http://hdl.handle.net/10.1080/00207543.2014.994715
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuri N. Sotskov
Author-X-Name-First: Yuri N.
Author-X-Name-Last: Sotskov
Author-Name: Omid Gholami
Author-X-Name-First: Omid
Author-X-Name-Last: Gholami
Title: Mixed graph model and algorithms for parallel-machine job-shop scheduling problems
Abstract: 
 Heuristic algorithms are developed to solve the parallel-machine job-shop problems FJ|ri|Φ$ FJ|r_i|\Phi $, where the criterion Φ$ \Phi $ is the minimisation of the makespan, Φ=Cmax$ \Phi =C_{\max } $, or the sum of completion times, Φ=∑Ci$ \Phi =\sum C_i $. The developed algorithms include sequencing and assigning stages. At the sequencing stage, the job-shop problem J|ri|Φ$ J|r_i|\Phi $ is solved, where job Ji∈J$ J_i \in \mathcal{J} $ is available for processing from time ri$ r_i $. The problem J|ri|Φ$ J|r_i|\Phi $ is modelled by a mixed graph G=(O,A,E)$ G=(\mathcal{O}, A, E) $, where the vertices O$ \mathcal{O} $ are the operations to be processed. The precedence constraints on the set O$ \mathcal{O} $ are determined by the arc set A$ A $. The resource constraints are determined by the edge set E$ E $. In order to resolve a conflict arising between two operations processed on the same machine, the algorithm should substitute a conflict edge from the set E$ E $ by an arc incident to the same vertices from the set O$ \mathcal{O} $. The resulting digraph Gt=(O,A⋃At,∅)$ G_t=(\mathcal{O}, A \bigcup A_t, \varnothing ) $ determines a heuristic solution to the problem J|ri|Φ$ J|r_i|\Phi $, where all machines are different. The digraph Gt$ G_t $ determines a semi-active schedule for the problem FJ|ri|Φ$ FJ|r_i|\Phi $. A mixed graph model is used for solving the problem FJ|ri|Φ$ FJ|r_i|\Phi $, which allows a scheduler to construct an efficient schedule via deleting some arcs from the set At$ A_t $ in the digraph Gt$ G_t $ or (and) via changing orientations of the arcs. Several heuristics have been developed to transform the digraph Gt$ G_t $ into a new digraph as a proper answer for the problem FJ|ri|Φ$ FJ|r_i|\Phi $. The developed algorithms have been tested on the benchmark instances. It is demonstrated how these algorithms may be used for solving a train timetabling problem.
Journal: International Journal of Production Research
Pages: 1549-1564
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2015.1075666
File-URL: http://hdl.handle.net/10.1080/00207543.2015.1075666
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Template-Type: ReDIF-Article 1.0
Author-Name: Christos Zikopoulos
Author-X-Name-First: Christos
Author-X-Name-Last: Zikopoulos
Title: Remanufacturing lotsizing with stochastic lead-time resulting from stochastic quality of returns
Abstract: 
 In the current paper, we model the duration of recovery of used products as a variable that depends on each unit’s quality. Because of the uncertainty related to returned units’ quality, the necessary time for the recovery of a lot is a random variable. We provide analytical expressions for the optimisation of recovery planning decisions under different assumptions regarding quality and demand characteristics. In addition, through an extensive numerical study, we examine the impact of the different parameters on the necessity to consider explicitly the stochastic nature of recovery lead-time. Moreover, we discuss the advisability of establishing procedures for the classification of returns according to their quality condition. As our findings indicate, overlooking quality uncertainty can increase related costs considerably because of poor process coordination. Furthermore, ignoring variability may result in undue overestimation of the efficiency of lot-sizing policies. On the other hand, the establishment of quality assessment procedures is worthwhile only when the stochastic behaviour of quality cannot be taken into account explicitly.
Journal: International Journal of Production Research
Pages: 1565-1587
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1150616
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1150616
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Template-Type: ReDIF-Article 1.0
Author-Name: Simon Thevenin
Author-X-Name-First: Simon
Author-X-Name-Last: Thevenin
Author-Name: Nicolas Zufferey
Author-X-Name-First: Nicolas
Author-X-Name-Last: Zufferey
Author-Name: Jean-Yves Potvin
Author-X-Name-First: Jean-Yves
Author-X-Name-Last: Potvin
Title: Makespan minimisation for a parallel machine scheduling problem with preemption and job incompatibility
Abstract: 
 In this paper, an extension of the graph colouring problem is introduced to model a parallel machine scheduling problem with job incompatibility. To get closer to real-world applications, where the number of machines is limited and jobs have different processing times, each vertex of the graph requires multiple colours and the number of vertices with the same colour is bounded. In addition, several objectives related to scheduling are considered: makespan, number of pre-emptions and summation over the jobs’ throughput times. Different solution methods are proposed, namely, two greedy heuristics, two tabu search methods and an adaptive memory algorithm. The latter uses multiple recombination operators, each one being designed for optimising a subset of objectives. The most appropriate operator is selected dynamically at each iteration, depending on its past performance. Experiments show that the proposed algorithm is effective and robust, while providing high-quality solutions on benchmark instances for the graph multi-colouring problem, a simplification of the considered problem.
Journal: International Journal of Production Research
Pages: 1588-1606
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1181285
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1181285
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Template-Type: ReDIF-Article 1.0
Author-Name: Gabriela N. Maschietto
Author-X-Name-First: Gabriela N.
Author-X-Name-Last: Maschietto
Author-Name: Yassine Ouazene
Author-X-Name-First: Yassine
Author-X-Name-Last: Ouazene
Author-Name: Martín G. Ravetti
Author-X-Name-First: Martín G.
Author-X-Name-Last: Ravetti
Author-Name: Maurício C. de Souza
Author-X-Name-First: Maurício C.
Author-X-Name-Last: de Souza
Author-Name: Farouk Yalaoui
Author-X-Name-First: Farouk
Author-X-Name-Last: Yalaoui
Title: Crane scheduling problem with non-interference constraints in a steel coil distribution centre
Abstract: 
 This article deals with a parallel machine scheduling problem subject to non-interference constraints. This situation often appears at logistic centres, such as depots, warehouses and stockyards. The analyzed scenario is based on a real case at a distribution centre of steel coils, where two cranes using the same rail must load dispatching trucks. We analyze this case by modelling the situation through a parallel machine perspective and considering two mechanisms to deal with the machine interference, R2|intf|∑wjCj$ R2 | \ { intf} \ | \sum w_jC_{j} $. In the first approach, the machine interference is dealt by scheduling whole trucks. In the second one, we schedule the trucks and the coils within. The proposed mathematical models are able to solve small and medium instances, thus, we develop two genetic algorithms to solve real size instances, allowing the analysis of different storage policies. Results show that the genetic approach is able to find near-optimal solutions independently of the policy, with solutions gap ranging from 10 to 2.1%.
Journal: International Journal of Production Research
Pages: 1607-1622
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1193249
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193249
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Template-Type: ReDIF-Article 1.0
Author-Name: Niloy J. Mukherjee
Author-X-Name-First: Niloy J.
Author-X-Name-Last: Mukherjee
Author-Name: Subhash C. Sarin
Author-X-Name-First: Subhash C.
Author-X-Name-Last: Sarin
Author-Name: Sanchit Singh
Author-X-Name-First: Sanchit
Author-X-Name-Last: Singh
Title: Lot streaming in the presence of learning in sublot-attached setup times and processing times
Abstract: 
 Lot streaming is the process of splitting a production lot into sublots, and then processing the sublots on different machines in an overlapping manner. In this paper, we study the use of lot streaming for processing a lot in a two-machine flow shop when a sublot-attached setup time is incurred before the processing of each sublot. The objective is to determine number of sublots and sublot sizes and minimize makespan. We also consider the case when the effect of learning is observed in processing times, sublot-attached setup times, or, both. We present closed-form expressions for optimal sublot sizes and efficient search schemes to determine optimal number of sublots.
Journal: International Journal of Production Research
Pages: 1623-1639
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1200760
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1200760
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Template-Type: ReDIF-Article 1.0
Author-Name: Oussama Masmoudi
Author-X-Name-First: Oussama
Author-X-Name-Last: Masmoudi
Author-Name: Alice Yalaoui
Author-X-Name-First: Alice
Author-X-Name-Last: Yalaoui
Author-Name: Yassine Ouazene
Author-X-Name-First: Yassine
Author-X-Name-Last: Ouazene
Author-Name: Hicham Chehade
Author-X-Name-First: Hicham
Author-X-Name-Last: Chehade
Title: Lot-sizing in a multi-stage flow line production system with energy consideration
Abstract: 
 In this paper, a single-item capacitated lot-sizing problem in a flow-shop system with energy consideration is studied. The planning horizon is defined by a set of periods where each one is characterised by a length, an allowed maximal power, an electricity price, a power price and a demand. The objective is to determine the quantities to be produced by each machine at each period while minimising the production cost in terms of electrical, inventory, set-up and power required costs. For medium- and large-scale problems, lot-sizing problems are hard to solve. Therefore, in this study, two heuristics are developed to solve this problem in a reasonable time. To evaluate the performances of these heuristics, computational experiments are presented and numerical results are discussed and analysed.
Journal: International Journal of Production Research
Pages: 1640-1663
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1206670
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1206670
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Template-Type: ReDIF-Article 1.0
Author-Name: Nour El Houda Tellache
Author-X-Name-First: Nour El Houda
Author-X-Name-Last: Tellache
Author-Name: Mourad Boudhar
Author-X-Name-First: Mourad
Author-X-Name-Last: Boudhar
Title: Two-machine flow shop problem with unit-time operations and conflict graph
Abstract: 
 This paper addresses the problem of scheduling, on a two-machine flow shop, a set of unit-time operations subject to the constraints that some conflicting jobs cannot be scheduled simultaneously on different machines. In the context of our study, these conflicts are modelled by general graphs. The problem of minimising the maximum completion time (makespan) is known to be NP-hard in the strong sense. We propose a mixed-integer linear programming (MILP) model. Then, we develop a branch and bound algorithm based on new lower and upper bound procedures. We further provide a computer simulation to measure the performance of the proposed approaches. The computational results show that the branch and bound algorithm outperforms the MILP model and can solve instances of size up to 20,000 jobs.
Journal: International Journal of Production Research
Pages: 1664-1679
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1206672
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1206672
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Template-Type: ReDIF-Article 1.0
Author-Name: Gaia Nicosia
Author-X-Name-First: Gaia
Author-X-Name-Last: Nicosia
Author-Name: Andrea Pacifici
Author-X-Name-First: Andrea
Author-X-Name-Last: Pacifici
Title: Scheduling assembly tasks with caterpillar precedence constraints on dedicated machines
Abstract: 
 In this work, we address the problem of scheduling a set of n non-preemptive tasks on m dedicated machines in order to minimise the makespan. For each task deterministic processing times and a specific processing machine are given, moreover a set of precedence constraints among the tasks are known. We present a heuristic and some lower bounds on the minimum makespan for a relevant case in manufacturing applications, namely when the precedence constraints form a caterpillar graph. A caterpillar is a directed tree consisting of a single directed path and leaf nodes each of which is incident to the directed path by exactly one incoming arc. A number of computational experiments are also performed in order to test the performance of the proposed solution algorithm.
Journal: International Journal of Production Research
Pages: 1680-1691
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1220686
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1220686
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Template-Type: ReDIF-Article 1.0
Author-Name: Luca Zeppetella
Author-X-Name-First: Luca
Author-X-Name-Last: Zeppetella
Author-Name: Elisa Gebennini
Author-X-Name-First: Elisa
Author-X-Name-Last: Gebennini
Author-Name: Andrea Grassi
Author-X-Name-First: Andrea
Author-X-Name-Last: Grassi
Author-Name: Bianca Rimini
Author-X-Name-First: Bianca
Author-X-Name-Last: Rimini
Title: Optimal production scheduling with customer-driven demand substitution
Abstract: 
 This paper deals with the production scheduling problem with customer-driven demand substitution. We consider a manufacturing system in a make-to-stock environment which is potentially able to produce a large variety of product options (the so-called long-term product assortment) but, for reasons of capacity and operative limitations, only a subset of those options can be available in stock at the same time (the so-called short-term product assortment). In such a context, typical of fields where high-variety strategies are applied, the first-choice option of the customer could be unavailable at a certain instant of time. In that case, if production is planned by taking demand substitution issues into consideration, other options which are good substitutes will be available, thus increasing the probability that the customer chooses to substitute. The paper proposes two mixed-integer linear programming models (for both the lost sale case and the backorder case) for optimising the production schedule by jointly considering (i) capacity and production constraints, and costs on one hand, (ii) and demand substitution issues on the other hand. An extensive experimental analysis has allowed us to evaluate the models’ behaviour in a variety of operative scenarios and to draw some concluding remarks.
Journal: International Journal of Production Research
Pages: 1692-1706
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1223895
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1223895
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Template-Type: ReDIF-Article 1.0
Author-Name: Kuo-Ching Ying
Author-X-Name-First: Kuo-Ching
Author-X-Name-Last: Ying
Author-Name: Shih-Wei Lin
Author-X-Name-First: Shih-Wei
Author-X-Name-Last: Lin
Author-Name: Chung-Cheng Lu
Author-X-Name-First: Chung-Cheng
Author-X-Name-Last: Lu
Title: Effective dynamic dispatching rule and constructive heuristic for solving single-machine scheduling problems with a common due window
Abstract: 
 This study addresses the single-machine scheduling problem with a common due window (CDW) that has a constant size and position. The objective is to minimise the total weighted earliness–tardiness penalties for jobs completed out of the CDW. To determine a schedule as close to optimum as possible, this study develops a dynamic dispatching rule and an effective constructive heuristic. The better performance of the proposed heuristic is demonstrated by comparing the results of it with those of a state-of-the-art greedy heuristic on a well-known benchmark problem set. In addition, we incorporate the constructive heuristic into a best-so-far meta-heuristic to examine the benefit of the proposed heuristic. The results show that the best known solutions in 144 out of the 250 benchmark instances are improved.
Journal: International Journal of Production Research
Pages: 1707-1719
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1224949
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1224949
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Template-Type: ReDIF-Article 1.0
Author-Name: Ahmed Kouider
Author-X-Name-First: Ahmed
Author-X-Name-Last: Kouider
Author-Name: Hacène Ait Haddadène
Author-X-Name-First: Hacène
Author-X-Name-Last: Ait Haddadène
Author-Name: Samia Ourari
Author-X-Name-First: Samia
Author-X-Name-Last: Ourari
Author-Name: Ammar Oulamara
Author-X-Name-First: Ammar
Author-X-Name-Last: Oulamara
Title: Mixed graph colouring for unit-time scheduling
Abstract: 
 We consider the job shop scheduling problem with unit-time operations and the makespan criterion. This problem is reduced to finding an optimal colouring of a special class of mixed graph, where its partial graph without edges represents the union of maximal directed paths and its partial graph without arcs represents the union of maximal cliques. As the problem is known to be NP-hard, both exact and heuristic methods are proposed to solve it. This study is carried out in three steps. First, a new lower and upper bounds for the mixed chromatic number are proposed. Afterwards, a colour-indexed mathematical model using the proposed bounds is developed. Then, a tabu search using a dynamic neighbourhood structure is adapted for solving large instances. Computational experiments conducted on several modified benchmarks show the efficiency and effectiveness of the proposed resolution methods.
Journal: International Journal of Production Research
Pages: 1720-1729
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1224950
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1224950
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Template-Type: ReDIF-Article 1.0
Author-Name: Batoul Mahvash
Author-X-Name-First: Batoul
Author-X-Name-Last: Mahvash
Author-Name: Anjali Awasthi
Author-X-Name-First: Anjali
Author-X-Name-Last: Awasthi
Author-Name: Satyaveer Chauhan
Author-X-Name-First: Satyaveer
Author-X-Name-Last: Chauhan
Title: A column generation based heuristic for the capacitated vehicle routing problem with three-dimensional loading constraints
Abstract: 
 This paper addresses an integrated problem of vehicle routing and three-dimensional loading with additional practical constraints such as stability, fragility and LIFO. A column generation (CG) technique-based heuristic is proposed to handle this problem. To generate new columns in CG technique, first, an elementary shortest path problem is solved to find routes with negative reduced cost. Then an extreme point-based heuristic method is employed to verify feasibility of obtained routes in terms of loading and other constraints. To speed up the CG technique, fast column generation is also performed by applying an efficient heuristic pricing method. The CG technique, tested on the benchmark instances, outperforms the efficient tabu search method developed in the literature in terms of solution quality and computation time.
Journal: International Journal of Production Research
Pages: 1730-1747
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1231940
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1231940
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Template-Type: ReDIF-Article 1.0
Author-Name: Chang Wook Kang
Author-X-Name-First: Chang Wook
Author-X-Name-Last: Kang
Author-Name: Misbah Ullah
Author-X-Name-First: Misbah
Author-X-Name-Last: Ullah
Author-Name: Biswajit Sarkar
Author-X-Name-First: Biswajit
Author-X-Name-Last: Sarkar
Author-Name: Iftikhar Hussain
Author-X-Name-First: Iftikhar
Author-X-Name-Last: Hussain
Author-Name: Rehman Akhtar
Author-X-Name-First: Rehman
Author-X-Name-Last: Akhtar
Title: Impact of random defective rate on lot size focusing work-in-process inventory in manufacturing system
Abstract: 
 Literature has focused inventory models with intensive emphasis on imperfect production processes in recent past. However, the work-in-process-based inventory models have been ignored, relatively, in general and the impact of random defects in the form of reworkable and non-reworkable defect rate on lot size and total cost function in particular. This paper develops mathematical models for work-in-process-based inventory by incorporating the effect of random defects rate on lot size and expected total cost function. Our proposed models assume that defective products produced during the production process follow random distributions. Defective products, either in the form of reworkable or rejected production units, follow four types of distribution density functions: uniform, triangular, double triangular and beta distribution. Mathematical models are derived for optimum lot size based on minimization of expected total cost function through the analytical optimization approach. Numerical examples and detailed sensitivity analysis are carried to illustrate and compare the proposed models at different levels of distribution functions’ parameters.
Journal: International Journal of Production Research
Pages: 1748-1766
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1235295
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Template-Type: ReDIF-Article 1.0
Author-Name: Guanlian Xiao
Author-X-Name-First: Guanlian
Author-X-Name-Last: Xiao
Author-Name: Ming Dong
Author-X-Name-First: Ming
Author-X-Name-Last: Dong
Author-Name: Jing Li
Author-X-Name-First: Jing
Author-X-Name-Last: Li
Author-Name: Liya Sun
Author-X-Name-First: Liya
Author-X-Name-Last: Sun
Title: Scheduling routine and call-in clinical appointments with revisits
Abstract: 
 This paper studies the problem of clinical appointment scheduling when taking revisits into account. We consider two classes of patients: (1) routine patients who have made an appointment weeks in advance and (2) same-day patients who call in at the very beginning of the day, before the first clinical consultation begins. After the first appointment and consultation, patients might need an additional examination and a second consultation to confirm their health status. This paper aims to create an advanced scheduling method for both routine patients and same-day patients to optimise the expected weighted sum of three performance measures: patients’ waiting time, physician’s idle time and overtime. A stochastic programme model is constructed and solved by sample average approximation and benders’ decomposition. Numerical tests show that revisits significantly affect the three performance measures; to improve the hospital system’s operation management, both scheduling of appointment times and daily workload plans are taken into account.
Journal: International Journal of Production Research
Pages: 1767-1779
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1237789
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Template-Type: ReDIF-Article 1.0
Author-Name: Anthony John Walker
Author-X-Name-First: Anthony John
Author-X-Name-Last: Walker
Author-Name: Glen Bright
Author-X-Name-First: Glen
Author-X-Name-Last: Bright
Title: Modeling arrival-to-departure sequence disorder in flow-controlled manufacturing systems
Abstract: 
 Flow control policies, such as clear the largest buffer first, have been used extensively in mediating server access between multiple job-arrival processes within manufacturing systems requiring significant set-up times between job types. Although the stability and performance characteristics of clearing policies have been studied, how these clearing policies affect the growth in arrival-to-departure sequence disorder across a machine or workcell is still an area for further research. In this paper, a closed-form model is formulated that characterises the steady-state average arrival-to-departure sequence disorder experienced by jobs processed through a stable flow controlled manufacturing system. Specifically addressed are the effects of upstream sequence disorder on the work-in-process of a downstream assembly process. A simulation study is used to validate the model’s accuracy and applicability in predicting steady-state average arrival-to-departure sequence disorder. A simulation study of an assembly process shows that by balancing upstream steady-state average sequence disorder, downstream work-in-process can be minimised while under a logical component grouping constraint.
Journal: International Journal of Production Research
Pages: 1780-1790
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1238524
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1238524
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiang Wu
Author-X-Name-First: Xiang
Author-X-Name-Last: Wu
Author-Name: Kanjian Zhang
Author-X-Name-First: Kanjian
Author-X-Name-Last: Zhang
Author-Name: Ming Cheng
Author-X-Name-First: Ming
Author-X-Name-Last: Cheng
Title: Computational method for optimal machine scheduling problem with maintenance and production
Abstract: 
 This paper considers an optimal scheduling problem of maintenance and production for a machine. Firstly, the problem is formulated as a stochastic switched impulsive optimal control problem. However, there exists the stochastic disturbance in this model. Thus, it is difficult to solve the problem by conventional optimisation techniques. To overcome this difficulty, the stochastic switched impulsive optimal control problem is transformed into a deterministic switched impulsive optimal control problem with continuous state inequality constraints. Then, by combining a time-scaling transformation, a second-order smoothing technique and a penalty function method, an improved Newton algorithm is developed for solving this problem. Convergence results indicate that the algorithm is globally convergent with quadratic rate. Finally, two numerical examples are provided to illustrate the effectiveness of the developed algorithm.
Journal: International Journal of Production Research
Pages: 1791-1814
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1245451
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1245451
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Template-Type: ReDIF-Article 1.0
Author-Name: Onur Ozturk
Author-X-Name-First: Onur
Author-X-Name-Last: Ozturk
Author-Name: Mehmet A. Begen
Author-X-Name-First: Mehmet A.
Author-X-Name-Last: Begen
Author-Name: Gregory S. Zaric
Author-X-Name-First: Gregory S.
Author-X-Name-Last: Zaric
Title: A branch and bound algorithm for scheduling unit size jobs on parallel batching machines to minimize makespan
Abstract: 
 In this paper, we present a branch and bound algorithm for the parallel batch scheduling of jobs having different processing times, release dates and unit sizes. There are identical machines with a fixed capacity and the number of jobs in a batch cannot exceed the machine capacity. All batched jobs are processed together and the processing time of a batch is given by the greatest processing time of jobs in that batch. We compare our method to a mixed integer program as well as a method from the literature that is capable of optimally solving instances with a single machine. Computational experiments show that our method is much more efficient than the other two methods in terms of solution time for finding the optimal solution.
Journal: International Journal of Production Research
Pages: 1815-1831
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2016.1253889
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1253889
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Template-Type: ReDIF-Article 1.0
Author-Name: Wafaa Labbi
Author-X-Name-First: Wafaa
Author-X-Name-Last: Labbi
Author-Name: Mourad Boudhar
Author-X-Name-First: Mourad
Author-X-Name-Last: Boudhar
Author-Name: Ammar Oulamara
Author-X-Name-First: Ammar
Author-X-Name-Last: Oulamara
Title: Scheduling two identical parallel machines with preparation constraints
Abstract: 
 In this paper, we consider the problem of scheduling a set of n jobs on two identical machines with preparation constraints. Each job requires before its execution a set of resources and a non-negligible preparation time. The objective is to minimise the makespan. This problem is NP-hard. We prove the NP-hardness of two specific cases where in the first case preparation times take only three values, whereas in the second case preparation times and the release dates take only two values, respectively. Then, we present some special cases and heuristic algorithms along with an experimental study.
Journal: International Journal of Production Research
Pages: 1531-1548
Issue: 6
Volume: 55
Year: 2017
Month: 3
X-DOI: 10.1080/00207543.2014.978032
File-URL: http://hdl.handle.net/10.1080/00207543.2014.978032
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Template-Type: ReDIF-Article 1.0
Author-Name: Bin Dan
Author-X-Name-First: Bin
Author-X-Name-Last: Dan
Author-Name: Shuguang Zhang
Author-X-Name-First: Shuguang
Author-X-Name-Last: Zhang
Author-Name: Maosen Zhou
Author-X-Name-First: Maosen
Author-X-Name-Last: Zhou
Title: Strategies for warranty service in a dual-channel supply chain with value-added service competition
Abstract: 
 This paper studies a dual-channel supply chain composed of a manufacturer and a retailer. The manufacturer and the retailer sell homogeneous durable goods bundled with warranty service that is provided by the manufacturer, and they compete for customers by offering free value-added service. Both the warranty and value-added services can affect the purchasing behaviour of customers. We examine the warranty service decision of the manufacturer and the value-added service competition between the manufacturer and the retailer. Three types of warranty service strategies that can affect the value-added service competition are proposed. By analysing the equilibriums of the value-added service level decisions of the manufacturer and the retailer, we find that when the manufacturer increases its warranty service level, the value-added service competition will be weakened, and when the warranty service level is high enough, there is no value-added service competition. In addition, we examine the optimal warranty service strategy and warranty service level of the manufacturer under different conditions, and we find that the stronger the manufacturer’s bargaining power is, or the stronger the value-added service competition intensity is, the more motivation the manufacturer has to provide a high warranty service level. Numerical examples reveal that differentiation strategy in value-added service may hurt the profits of the manufacturer, the retailer and the entire supply chain.
Journal: International Journal of Production Research
Pages: 5677-5699
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2017.1377355
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1377355
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Template-Type: ReDIF-Article 1.0
Author-Name: Yann Jaegler
Author-X-Name-First: Yann
Author-X-Name-Last: Jaegler
Author-Name: Anicia Jaegler
Author-X-Name-First: Anicia
Author-X-Name-Last: Jaegler
Author-Name: Patrick Burlat
Author-X-Name-First: Patrick
Author-X-Name-Last: Burlat
Author-Name: Samir Lamouri
Author-X-Name-First: Samir
Author-X-Name-Last: Lamouri
Author-Name: Damien Trentesaux
Author-X-Name-First: Damien
Author-X-Name-Last: Trentesaux
Title: The ConWip production control system: a systematic review and classification
Abstract: 
 In the past decade, a growing body of literature has investigated the CONstant Work In Progress (ConWip) production control system (PCS). In view of the current industrial challenges entailing adaptability, product customisation, decreasing leadtimes and customer satisfaction, ConWip seems to be an effective and adaptive PCS for manufacturers. This paper aims to update the last ConWip systematic review that dates back to 2003 and to provide a guide for understanding through an original classification method. This method enables the differentiation of papers that concentrate on ConWip sizing, performance and context as well as a comparison with other PCSs. In addition to providing a key to interpreting the research approaches, the criteria considered answers questions on how to implement, how to optimise and why and when to use ConWip. Finally, the most relevant research avenues are highlighted to provide future lines of research.
Journal: International Journal of Production Research
Pages: 5736-5757
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2017.1380325
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1380325
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Template-Type: ReDIF-Article 1.0
Author-Name: Emel Arikan
Author-X-Name-First: Emel
Author-X-Name-Last: Arikan
Author-Name: Lena Silbermayr
Author-X-Name-First: Lena
Author-X-Name-Last: Silbermayr
Title: Risk pooling via unidirectional inventory transshipments in a decentralized supply chain
Abstract: 
 We study risk pooling via unidirectional lateral transshipments between two locations under local decision-making. Unidirectional transshipments can be applicable when cost structures and/or capabilities differ between locations, and it is also a common practice in dual channel supply chains with online and offline sales channels. We show that such a system cannot be coordinated only with varying transshipment prices. The transshipment receiver orders more and the transshipment giver orders less than the respective optimal centralised order quantities. In order to remove this discrepancy, we suggest horizontal coordination mechanisms by introducing a leftover subsidy for the location providing the transshipments or a shortage subsidy for the location receiving transshipments as well as a combination of shortage and leftover subsidy. Further, we evaluate the impact of network structure by comparing the equilibrium order quantities and profits under the uni- and bidirectional systems as well as a system without transshipments. Since demand correlation is a critical aspect in risk pooling we provide a detailed numerical study to discuss its impact on our findings.
Journal: International Journal of Production Research
Pages: 5593-5610
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2017.1394586
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394586
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:17:p:5593-5610




Template-Type: ReDIF-Article 1.0
Author-Name: Tongdan Jin
Author-X-Name-First: Tongdan
Author-X-Name-Last: Jin
Author-Name: Tianqin Shi
Author-X-Name-First: Tianqin
Author-X-Name-Last: Shi
Author-Name: Taeho Park
Author-X-Name-First: Taeho
Author-X-Name-Last: Park
Title: The quest for carbon-neutral industrial operations: renewable power purchase versus distributed generation
Abstract: 
 Integrating renewable energy into the manufacturing facility is the ultimate key to realising carbon-neutral operations. Although many firms have taken various initiatives to reduce the carbon footprint of their facilities, there are few quantitative studies focused on cost analysis and supply reliability of integrating intermittent wind and solar power. This paper aims to fill this gap by addressing the following question: shall we adopt power purchase agreement (PPA) or onsite renewable generation to realise the eco-economic benefits? We tackle this complex decision-making problem by considering two regulatory options: government carbon incentives and utility pricing policy. A stochastic programming model is formulated to search for the optimal mix of onsite and offsite renewable power supply. The model is tested extensively in different regions under various climatic conditions. Three findings are obtained. First, in a long term onsite generation and PPA can avoid the price volatility in the spot or wholesale electricity market. Second, at locations where the wind speed is below 6 m/s, PPA at $70/MWh is preferred over onsite wind generation. Third, compared to PPA and wind generation, solar generation is not economically competitive unless the capacity cost is down below $1.5 M/MW.
Journal: International Journal of Production Research
Pages: 5723-5735
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2017.1394593
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1394593
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Template-Type: ReDIF-Article 1.0
Author-Name: Xinbao Liu
Author-X-Name-First: Xinbao
Author-X-Name-Last: Liu
Author-Name: Shaojun Lu
Author-X-Name-First: Shaojun
Author-X-Name-Last: Lu
Author-Name: Jun Pei
Author-X-Name-First: Jun
Author-X-Name-Last: Pei
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Title: A hybrid VNS-HS algorithm for a supply chain scheduling problem with deteriorating jobs
Abstract: 
 This paper investigates a coordinated scheduling problem in a two stage supply chain where parallel-batching machine, deteriorating jobs and transportation coordination are considered simultaneously. During the production stage, jobs are processed by suppliers and there exists one parallel-batching machine in each supplier. The actual processing time of a job depends on its starting time and normal processing time. The normal processing time of a batch is equal to the largest normal processing time among all jobs in its batch. During the transportation stage, the jobs are then delivered to the manufacturer. Since suppliers are distributed in different locations, the transportation time between each supplier and the manufacturer is different. Based on some structural properties of the studied problem, an optimal algorithm for minimising makespan on a single supplier is presented. This supply chain scheduling problem is proved to be NP-hard, and a hybrid VNS-HS algorithm combining variable neighbourhood search (VNS) with harmony search (HS) is proposed to find a good solution in reasonable time. Finally, some computational experiments are conducted and the results demonstrate the effectiveness and efficiency of the proposed VNS-HS.
Journal: International Journal of Production Research
Pages: 5758-5775
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2017.1418986
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1418986
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Template-Type: ReDIF-Article 1.0
Author-Name: Debadyuti Das
Author-X-Name-First: Debadyuti
Author-X-Name-Last: Das
Title: Sustainable supply chain management in Indian organisations: an empirical investigation
Abstract: 
 The present work is an attempt to investigate the adoption of sustainable supply chain management (SSCM) practices amongst manufacturing and process based organisations in India and its impact on organisational performance encompassing all three dimensions of sustainability. SSCM practices conceived in the present study include environmental management practices (EMP), socially inclusive practices for employees (SPE), socially inclusive practices for community (SPC), operations practices (OP) and supply chain integration (SCI) which were treated as exogenous variables. Organisational performance considered in this study includes five dimensions, namely environmental performance (EPR), employee-centred social performance (ESP), community-centred social performance (CSP), operations performance (OPR) and competitiveness, which were regarded as endogenous variables. The analysis was carried out with the help of structural equation modelling considering natural logarithm of manpower as a control variable. Few major findings are mentioned. EMP does not have any significant association with OPR, nor does it result in competitiveness. However, when jointly mediated through both EPR and OPR, EMP leads to competitiveness. SPC has significant negative association with competitiveness, when only direct relationship is considered. However, indirect relationship between SPC and competitiveness shows significant positive association when mediated through CSP. The resultant total effect between SPC and competitiveness turns out to be insignificant. Further, OPR fully mediates the relationship between OP and competitiveness. Managerial implications of the findings are discussed.
Journal: International Journal of Production Research
Pages: 5776-5794
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2017.1421326
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421326
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhanguo Zhu
Author-X-Name-First: Zhanguo
Author-X-Name-Last: Zhu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Author-Name: Wei Zhou
Author-X-Name-First: Wei
Author-X-Name-Last: Zhou
Author-Name: Selwyn Piramuthu
Author-X-Name-First: Selwyn
Author-X-Name-Last: Piramuthu
Title: Recent advances and opportunities in sustainable food supply chain: a model-oriented review
Abstract: 
 Faced with the challenges associated with sustainably feeding the world’s growing population, the food industry is increasingly relying on operations research (OR) techniques to achieve economic, environmental and social sustainability. It is therefore important to understand the context-specific model-oriented applications of OR techniques in the sustainable food supply chain (SFSC) domain. While existing food supply chain reviews provide an excellent basis for this process, the explicit consideration of sustainability from a model-oriented perspective along with a structured outline of relevant SFSC research techniques are missing in extant literature. We attempt to fill this gap by reviewing 83 related scientific journal publications that utilise mathematical modelling techniques to address issues in SFSC. To this end, we first identify the salient dimensions that include economic, environmental and social issues in SFSC. We then review the models and methods that use these dimensions to solve issues that arise in SFSC. We identify some of the main challenges in analytical modelling of SFSC as well as future research directions.
Journal: International Journal of Production Research
Pages: 5700-5722
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1425014
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1425014
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen Wang
Author-X-Name-First: Chen
Author-X-Name-Last: Wang
Author-Name: Zhe Yin
Author-X-Name-First: Zhe
Author-X-Name-Last: Yin
Title: Using backup supply with responsive pricing to mitigate disruption risk for a risk-averse firm
Abstract: 
 We consider a risk-averse firm’s sourcing problem with two suppliers: a dedicated one and a backup one. The dedicated supplier charges a lower wholesale price, but faces potential disruption risk. The backup supplier is assumed to be perfectly reliable, but charges a higher wholesale price. To mitigate the disruption risk, the firm uses a joint backup supply and responsive pricing strategy. We consider three common backup strategies between the firm and the backup supplier: advance purchase, reservation and contingency purchase. We derive under what conditions each strategy could be optimal. The results show that the thresholds that determine the optimal backup supply strategy are affected by the risk aversion level. When the risk aversion level is not extremely high, the firm should choose among the three backup suppliers by considering the disruption probability and the reservation fee. Firms with a higher risk aversion level tend to rely more on ex-ante preventive efforts (i.e. reservation or advance purchase strategies). When the risk aversion level is extremely high, the firm never considers the contingency purchase strategy, even for a low-probability disruption event. Additionally, market conditions yield non-negligible influences on the firm’s strategic choices due to the existence of risk aversion.
Journal: International Journal of Production Research
Pages: 5660-5676
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1427901
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1427901
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Template-Type: ReDIF-Article 1.0
Author-Name: Baofeng Huo
Author-X-Name-First: Baofeng
Author-X-Name-Last: Huo
Author-Name: Minhao Gu
Author-X-Name-First: Minhao
Author-X-Name-Last: Gu
Author-Name: Zhiqiang Wang
Author-X-Name-First: Zhiqiang
Author-X-Name-Last: Wang
Title: Supply chain flexibility concepts, dimensions and outcomes: an organisational capability perspective
Abstract: 
 Due to the increasing uncertainty and diversity in supply chains (SCs), companies are aiming to develop their SC flexibility, which we define as the capability of a company, both internally and externally in conjunction with its key suppliers and customers, to respond to uncertainties and customer expectations without excessive costs, time and performance losses. SC flexibility has three dimensions – internal, supplier and customer flexibility. This study investigates how SC flexibility improves operational and financial performance from the organisational capability perspective. The conceptual model is empirically tested using data collected from 216 companies in China. Our findings suggest that only customer and internal flexibility contribute to operational performance directly, while supplier flexibility contributes to operational performance only indirectly through internal flexibility. The three dimensions of SC flexibility have no direct impacts on financial performance. We further identify complementarities between supplier and customer flexibility and tradeoffs between supplier and internal flexibility. However, no synergy effect is found for internal and customer flexibility on operational performance. This study provides a framework to understand SC flexibility from the organisational capability perspective and identifies the inter-relationships among the three dimensions of SC flexibility and operational and financial performance.
Journal: International Journal of Production Research
Pages: 5883-5903
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1456694
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1456694
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Template-Type: ReDIF-Article 1.0
Author-Name: Sirish Kumar Gouda
Author-X-Name-First: Sirish Kumar
Author-X-Name-Last: Gouda
Author-Name: Haritha Saranga
Author-X-Name-First: Haritha
Author-X-Name-Last: Saranga
Title: Sustainable supply chains for supply chain sustainability: impact of sustainability efforts on supply chain risk
Abstract: 
 Supply chain managers across the globe are finding it difficult to manage the increasingly complex supply chains despite adopting a variety of risk mitigation strategies. Firms on the other hand have also been adopting various kinds of environmental and social sustainability practices in recent times to reduce carbon footprint and improve their image on the social front. However, very few studies in the extant literature have examined the impact of sustainability practices on supply chain risk. We address this important gap in literature by empirically testing this relationship, using primary data from six manufacturing sectors and 21 different countries including developed as well as emerging markets across the globe. Our findings indicate that risk mitigation strategies do not always reduce the actual supply chain risk experienced by firms, whereas sustainability efforts help reduce supply chain risk, especially in emerging market contexts. In addition, we find that, while reactive risk mitigation strategies on their own fail to reduce supply chain risk, they are effective when used in conjunction with sustainability efforts. We also find that preventive risk mitigation efforts are only effective in mature supply chains such as the OECD countries.
Journal: International Journal of Production Research
Pages: 5820-5835
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1456695
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1456695
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Template-Type: ReDIF-Article 1.0
Author-Name: Narain Gupta
Author-X-Name-First: Narain
Author-X-Name-Last: Gupta
Author-Name: Goutam Dutta
Author-X-Name-First: Goutam
Author-X-Name-Last: Dutta
Author-Name: Manoj K. Tiwari
Author-X-Name-First: Manoj K.
Author-X-Name-Last: Tiwari
Title: An integrated decision support system for strategic supply chain optimisation in process industries: the case of a zinc company
Abstract: 
 We introduce a menu-driven user-friendly decision support system (DSS) for supply chain planning based on optimisation. The DSS is based on a multi-source (supplier), multi-destination (warehouse) network having multiple manufacturing facilities, with multiple materials and multiple storage areas. This integrated supply chain model performs multiple period planning. The use of this DSS requires little knowledge of management sciences tools. We discuss the need for an integrated approach towards supply chain modelling for the process industry. We present the integrated model in the form of a database structure. We validate the model with the real data of a zinc company and demonstrate the impact of optimisation in terms of percentage improvement. The result shows that it is possible to improve unit contribution to profit from 1.89 to 4.66%.
Journal: International Journal of Production Research
Pages: 5866-5882
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1456698
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1456698
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Template-Type: ReDIF-Article 1.0
Author-Name: Akram Chibani
Author-X-Name-First: Akram
Author-X-Name-Last: Chibani
Author-Name: Xavier Delorme
Author-X-Name-First: Xavier
Author-X-Name-Last: Delorme
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Henri Pierreval
Author-X-Name-First: Henri
Author-X-Name-Last: Pierreval
Title: Dynamic optimisation for highly agile supply chains in e-procurement context
Abstract: 
 In the conditions of an increased worldwide competition, supply chains are struggling to respond to an increasingly volatile and complex environment. With technological advances, current practices to build efficient supply chains have changed. Companies are seeking to use internet in order to cope with the flexible and dynamic nature of logistics networks. The purpose of this article is to address the flexible dynamic e-procurement context under asynchronous and repetitive variations over time. The supply chain considered is composed of two levels (buyer–suppliers) operating in highly agile environment. The questions facing the buyer is how many units of product should be purchased and from which supplier in response to variation in term of price and capacity. Because of this highly changing environment characterised by frequent changes in a short time, most of the classical optimisation approaches seem inadequate to address these problems. Recently, dynamic optimisation has been proposed to deal with such problems. However, we have no knowledge of its application in a supply chain context. We suggest a dynamic genetic approach which is applied to an e-procurement context in aim to optimise the procurement process during time.
Journal: International Journal of Production Research
Pages: 5904-5929
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1458164
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1458164
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Template-Type: ReDIF-Article 1.0
Author-Name: Tülin İnkaya
Author-X-Name-First: Tülin
Author-X-Name-Last: İnkaya
Author-Name: Dieter Armbruster
Author-X-Name-First: Dieter
Author-X-Name-Last: Armbruster
Author-Name: Hongmin Li
Author-X-Name-First: Hongmin
Author-X-Name-Last: Li
Author-Name: Karl G. Kempf
Author-X-Name-First: Karl G.
Author-X-Name-Last: Kempf
Title: Product variety strategies for vertically differentiated products in a two-stage supply chain
Abstract: 
 In this paper, we study how the presence of coordination, competition and cost structures affect the product variety and pricing decisions in a two-stage supply chain. We consider vertically differentiated industries. Products reach the end customers via assembly companies positioned in the middle-tier between the producers and end customers. The assembly operations incur bill-of-materials (BOM) cost, which includes the cost of raw materials and components as well as the cost of producing, managing and synchronising supply, storage and distribution of these materials and components. We consider three coordination scenarios in the supply chain, and compare an uncoordinated supply chain with a horizontal and a vertical coordination scenario using the Nash equilibria of a multi-leader Stackelberg game between the producers and assembly companies. For exogenously given quality levels, we show that producers and assembly companies should either differentiate their product offering, or offer the high-end product only depending on the BOM cost. In addition, the uncoordinated scenario helps reduce the intensity of competition in the supply chain. For endogenous quality levels, partial product-differentiation equilibrium can emerge. Numerical experiments are performed to illustrate the impacts of BOM cost and quality levels on the equilibrium.
Journal: International Journal of Production Research
Pages: 5930-5944
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1461271
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1461271
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Template-Type: ReDIF-Article 1.0
Author-Name: Armin Jabbarzadeh
Author-X-Name-First: Armin
Author-X-Name-Last: Jabbarzadeh
Author-Name: Behnam Fahimnia
Author-X-Name-First: Behnam
Author-X-Name-Last: Fahimnia
Author-Name: Fatemeh Sabouhi
Author-X-Name-First: Fatemeh
Author-X-Name-Last: Sabouhi
Title: Resilient and sustainable supply chain design: sustainability analysis under disruption risks
Abstract: 
 Resilience to disruptions and sustainability are both of paramount importance to supply chains. However, the interactions between the two have not been thoroughly explored in the academic literature. We attempt to contribute to this area by presenting a hybrid methodology for the design of a sustainable supply network that performs resiliently in the face of random disruptions. A stochastic bi-objective optimisation model is developed that utilises a fuzzy c-means clustering method to quantify and assess the sustainability performance of the suppliers. The proposed model determines outsourcing decisions and resilience strategies that minimise the expected total cost and maximise the overall sustainability performance in disruptions. Important managerial insights and practical implications are obtained from the model implementation in a case study of plastic pipe industry.
Journal: International Journal of Production Research
Pages: 5945-5968
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1461950
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1461950
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Template-Type: ReDIF-Article 1.0
Author-Name: Ritesh Ojha
Author-X-Name-First: Ritesh
Author-X-Name-Last: Ojha
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Author-Name: Umit S. Bititci
Author-X-Name-First: Umit S.
Author-X-Name-Last: Bititci
Title: Bayesian network modelling for supply chain risk propagation
Abstract: 
 Supply chain risk propagation is a cascading effect of risks on global supply chain networks. The paper attempts to measure the behaviour of risks following the assessment of supply chain risk propagation. Bayesian network theory is used to analyse the multi-echelon network faced with simultaneous disruptions. The ripple effect of node disruption is evaluated using metrics like fragility, service level, inventory cost and lost sales. Developed risk exposure and resilience indices support in assessing the vulnerability and adaptability of each node in the supply chain network. The research provides a holistic measurement approach for predicting the complex behaviour of risk propagation for improved supply chain risk management.
Journal: International Journal of Production Research
Pages: 5795-5819
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1467059
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1467059
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Template-Type: ReDIF-Article 1.0
Author-Name: Sabari R. Prasanna
Author-X-Name-First: Sabari R.
Author-X-Name-Last: Prasanna
Author-Name: Ira Haavisto
Author-X-Name-First: Ira
Author-X-Name-Last: Haavisto
Title: Collaboration in humanitarian supply chains: an organisational culture framework
Abstract: 
 The purpose of this study was to determine the impact that institutional logics and, more specifically, organisational culture can have on humanitarian supply chain (HSC) collaboration. A framework was developed that explicates buyer–supplier collaboration in a humanitarian setting. Twenty-nine semi-structured interviews were conducted with buyers and suppliers. The data indicated that in a HSC, collaborative outcomes, such as new product development, inventory management, and product/service delivery, are influenced by the buyers’ and suppliers’ organisational cultures. Based on suppliers’ characteristics, they can be classified as humanitarian suppliers, commercial suppliers, and humanitarian and commercial suppliers. These groups have distinct organisational cultures. An unexpected finding is that suppliers that serve commercial buyers primarily claim to have encountered no issues in supply chain collaboration with humanitarian buyers, although they have different types of organisational cultures. The factors that lead to successful collaboration are identified as trust, commitment, information sharing and mutual respect. Simultaneously, dominant institutional logics are observed in the dyadic relationship.
Journal: International Journal of Production Research
Pages: 5611-5625
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1475762
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1475762
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Template-Type: ReDIF-Article 1.0
Author-Name: Fangzhou Sun
Author-X-Name-First: Fangzhou
Author-X-Name-Last: Sun
Author-Name: Maichel M. Aguayo
Author-X-Name-First: Maichel M.
Author-X-Name-Last: Aguayo
Author-Name: Rahul Ramachandran
Author-X-Name-First: Rahul
Author-X-Name-Last: Ramachandran
Author-Name: Subhash C. Sarin
Author-X-Name-First: Subhash C.
Author-X-Name-Last: Sarin
Title: Biomass feedstock supply chain design – a taxonomic review and a decomposition-based methodology
Abstract: 
 In this paper, we present a taxonomic review of the literature devoted to the use of operations research approaches for the design and operation of biomass feedstock supply chains (BFSCs). A total of 185 publications that have appeared from 1989 to 2017 are classified based on (1) the embedded optimisation subproblems; (2) the modelling methodologies used for their formulations; and (3) the methods employed for their solution. Our objective of using this classification scheme is to highlight the presence of some useful substructures in a BFSC problem that can, then, be exploited in developing its solution procedure. We illustrate this idea on some generic BFSC problems and present a Dantzig–Wolfe decomposition-based methodology for developing customised approaches to effectively tackle these difficult and large-sized BFSC problems. Finally, we suggest several promising future research directions.
Journal: International Journal of Production Research
Pages: 5626-5659
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1475766
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1475766
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Template-Type: ReDIF-Article 1.0
Author-Name: Kalpit Patne
Author-X-Name-First: Kalpit
Author-X-Name-Last: Patne
Author-Name: Nagesh Shukla
Author-X-Name-First: Nagesh
Author-X-Name-Last: Shukla
Author-Name: Senevi Kiridena
Author-X-Name-First: Senevi
Author-X-Name-Last: Kiridena
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Solving closed-loop supply chain problems using game theoretic particle swarm optimisation
Abstract: 
 In this paper, we propose a closed-loop supply chain network configuration model and a solution methodology that aim to address several research gaps in the literature. The proposed solution methodology employs a novel metaheuristic algorithm, along with the popular gradient descent search method, to aid location-allocation and pricing-inventory decisions in a two-stage process. In the first stage, we use an improved version of the particle swarm optimisation (PSO) algorithm, which we call improved PSO (IPSO), to solve the location-allocation problem (LAP). The IPSO algorithm is developed by introducing mutation to avoid premature convergence and embedding an evolutionary game-based procedure known as replicator dynamics to increase the rate of convergence. The results obtained through the application of IPSO are used as input in the second stage to solve the inventory-pricing problem. In this stage, we use the gradient descent search method to determine the selling price of new products and the buy-back price of returned products, as well as inventory cycle times for both product types. Numerical evaluations undertaken using problem instances of different scales confirm that the proposed IPSO algorithm performs better than the comparable traditional PSO, simulated annealing (SA) and genetic algorithm (GA) methods.
Journal: International Journal of Production Research
Pages: 5836-5853
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1478149
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1478149
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Template-Type: ReDIF-Article 1.0
Author-Name: George J. Kyparisis
Author-X-Name-First: George J.
Author-X-Name-Last: Kyparisis
Author-Name: Christos Koulamas
Author-X-Name-First: Christos
Author-X-Name-Last: Koulamas
Title: Competition in two-tier serial and assembly supply chains with general consumer utility functions
Abstract: 
 We consider two-tier serial supply chains with multiple entrants at each tier and investigate the existence of an equilibrium under a general consumer utility function corresponding to a general inverse price-demand function. In the case of a polynomial inverse price-demand function, we obtain closed-form expressions for the equilibrium prices, the production quantities and the profits of the supply chain entrants. We conclude that the quantity of finished goods supplied to the market, the maximum total operating profit accrued by all supply chain entrants, and the elasticity of the (imputed) demand are all sensitive to the elasticity of slope of the polynomial inverse price-demand function. We then extend our analysis to two-tier assembly supply chains and conclude that most of our results extend to them as well.
Journal: International Journal of Production Research
Pages: 5854-5865
Issue: 17
Volume: 56
Year: 2018
Month: 9
X-DOI: 10.1080/00207543.2018.1478463
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1478463
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Template-Type: ReDIF-Article 1.0
Author-Name: Christos Koulamas
Author-X-Name-First: Christos
Author-X-Name-Last: Koulamas
Author-Name: S.S. Panwalkar
Author-X-Name-First: S.S.
Author-X-Name-Last: Panwalkar
Title: The two-stage no-wait/blocking proportionate super shop scheduling problem
Abstract: 
 We analyze the ‘no-wait’ proportionate two-stage super shop scheduling problem with the objective of minimising the maximum job completion time (makespan). The existing simple sorting procedures for the open shop and the job shop do not work on the super shop. We show that the problem is still solvable in  $ \hbox{O}({{n^3}} ) $ O(n3) time using a procedure based on dynamic programming (DP). A unique feature of this procedure is that the state variable is defined based on the number of jobs; thus, reducing the complexity to polynomial. The same procedure solves the super shop problem with the blocking constraint. We also consider the case of machine dominance and show that the problem can be solved in linear  $ \hbox{O}(n ) $ O(n) time. Finally, we highlight the differences between the super shop with ‘no-wait’ and ‘synchronous’ processing modes via a numerical example.
Journal: International Journal of Production Research
Pages: 2956-2965
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1518603
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1518603
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Template-Type: ReDIF-Article 1.0
Author-Name: Yangyang Zang
Author-X-Name-First: Yangyang
Author-X-Name-Last: Zang
Author-Name: Kaibo Wang
Author-X-Name-First: Kaibo
Author-X-Name-Last: Wang
Title: Robust profile alignment based on penalised-spline smoothing
Abstract: 
 In quality engineering practice, profiles that are used for quality monitoring or evaluation are sometimes unaligned due to engineering constraints. In such cases, profiles have to be registered (aligned) through shifting, time warping or coordinate alignment such that samples are comparable and easy to handle. Among the different registration algorithms, time warping, or alignment of profiles with unequal lengths, is a challenging task. In quality engineering, a typical phenomenon observed in profile alignment is that neighbours of an aligned pair have a high possibility of being similar, which means that a large jump in a warping path is less likely. In this article, a penalised-spline smoothing method is proposed for profile alignment to handle this problem. The newly proposed nonparametric alignment strategy attempts to capture the smoothness and spatially correlated features of warping shifts, and is proven more robust than existing algorithms. A dynamic programming algorithm is developed to obtain the optimal path. Both simulation studies and a real example demonstrate the effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 2966-2983
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1519263
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1519263
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Template-Type: ReDIF-Article 1.0
Author-Name: Hasan Al Hasan
Author-X-Name-First: Hasan
Author-X-Name-Last: Al Hasan
Author-Name: Christelle Guéret
Author-X-Name-First: Christelle
Author-X-Name-Last: Guéret
Author-Name: David Lemoine
Author-X-Name-First: David
Author-X-Name-Last: Lemoine
Author-Name: David Rivreau
Author-X-Name-First: David
Author-X-Name-Last: Rivreau
Title: Surgical case scheduling with sterilising activity constraints
Abstract: 
 In this paper, we study a real scheduling problem which consists in scheduling a set of elective surgical cases requiring surgical instruments and tools in several operating rooms. The objectives are to minimise the overtime of the surgical unit staff, the number of operating rooms used and the number of instruments processed in emergency in the sterilising unit while respecting the current level of service represented by the total number of patients operated per month at the orthopaedic surgery unit. This research was performed in collaboration with the University Hospital of Angers in France (CHU Angers), which has also provided historical data for the experiments. We propose a mixed integer linear programming model for the problem which is solved in a lexicographic fashion. We also propose a robust formulation to deal with the uncertain surgery durations. Both the deterministic and robust formulations are then compared over a set of instances provided by the CHU. The solutions obtained are competitive in terms of number of operating rooms and significantly improve those implemented operationally at the CHU in terms of overtime and emergencies at the sterilising unit.
Journal: International Journal of Production Research
Pages: 2984-3002
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1521015
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521015
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen Chen
Author-X-Name-First: Chen
Author-X-Name-Last: Chen
Author-Name: Lee Kong Tiong
Author-X-Name-First: Lee Kong
Author-X-Name-Last: Tiong
Author-Name: I-Ming Chen
Author-X-Name-First: I-Ming
Author-X-Name-Last: Chen
Title: Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system
Abstract: 
 In this article, scheduling problem of a space-constrained AGV-based prefabricated bathroom units (PBU) manufacturing system is addressed. Space becomes a key resource to this manufacturing system because a very large space is required to accommodate the settling units as well as the queues. Although line balancing helps to reduce the queues, the system is still prone to deadlock due to limited space. Hence, in order to prevent deadlock situations, the production start times of PBUs have to be controlled. A genetic algorithm is proposed with the objective to decide operation for each workstation and to choose a start time for each PBU. The project duration is minimised while satisfying precedence relations and resource availabilities. A rule-based simulation approach is used to estimate the fitness value of every GA chromosomes. At last, the experiment based on data from an industrial project shows that the proposed algorithm has the potential to guide the real practice.
Journal: International Journal of Production Research
Pages: 3003-3019
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1521532
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1521532
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Template-Type: ReDIF-Article 1.0
Author-Name: Melissa Shahgholi Zadeh
Author-X-Name-First: Melissa
Author-X-Name-Last: Shahgholi Zadeh
Author-Name: Yalda Katebi
Author-X-Name-First: Yalda
Author-X-Name-Last: Katebi
Author-Name: Ali Doniavi
Author-X-Name-First: Ali
Author-X-Name-Last: Doniavi
Title: A heuristic model for dynamic flexible job shop scheduling problem considering variable processing times
Abstract: 
 In real scheduling problems, unexpected changes may occur frequently such as changes in task features. These changes cause deviation from primary scheduling. In this article, a heuristic model, inspired from Artificial Bee Colony algorithm, is proposed for a dynamic flexible job-shop scheduling (DFJSP) problem. This problem consists of n jobs that should be processed by m machines and the processing time of jobs deviates from estimated times. The objective is near-optimal scheduling after any change in tasks in order to minimise the maximal completion time (Makespan). In the proposed model, first, scheduling is done according to the estimated processing times and then re-scheduling is performed after determining the exact ones considering machine set-up. In order to evaluate the performance of the proposed model, some numerical experiments are designed in small, medium and large sizes in different levels of changes in processing times and statistical results illustrate the efficiency of the proposed algorithm.
Journal: International Journal of Production Research
Pages: 3020-3035
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1524165
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1524165
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3020-3035




Template-Type: ReDIF-Article 1.0
Author-Name: Carlos Otero-Palencia
Author-X-Name-First: Carlos
Author-X-Name-Last: Otero-Palencia
Author-Name: René Amaya–Mier
Author-X-Name-First: René
Author-X-Name-Last: Amaya–Mier
Author-Name: Ruben Yie-Pinedo
Author-X-Name-First: Ruben
Author-X-Name-Last: Yie-Pinedo
Title: A stochastic joint replenishment problem considering transportation and warehouse constraints with gainsharing by Shapley Value allocation
Abstract: 
 The purpose of this paper is to introduce a heuristic approach that uses a capacitated inventory model as means for identifying a collaborative agreement between different buyers jointly replenishing multiple items from multiple vendors, thus attaining economies of scale while reducing by sharing fixed procurement and operational costs. The proposed approach is denominated Stochastic Collaborative Joint Replenishment Problem (S-CJRP) and consists of two stages. The first stage determines a cost-efficient replenishment frequency for each collaborating company in all possible coalition arrangements. To accomplish the former, an extension of the known Joint Replenishment Problem (JRP) considering real-life capacity constraints, such as stochastic demand assuming normal distribution, finite storage and transport, is solved via genetic algorithms delivering a suitable coalition. In a second stage, the Shapley Value function is established to assess and allocate the potential gains achieved by colluding in the first stage, determining a fair share distribution among players that increases the viability of such coalition. Several scenarios from a simulated numerical study illustrate average cost savings of 32.3%. 28.2% and 32.7% for 3, 4 and 5 players, respectively, considering up to 30 items for the proposed collaboration, in all cases consistently exhibiting cost reduction and increasing the proposal feasibility.
Journal: International Journal of Production Research
Pages: 3036-3059
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1526418
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1526418
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Template-Type: ReDIF-Article 1.0
Author-Name: Xu Zheng
Author-X-Name-First: Xu
Author-X-Name-Last: Zheng
Author-Name: Shengchao Zhou
Author-X-Name-First: Shengchao
Author-X-Name-Last: Zhou
Author-Name: Huaping Chen
Author-X-Name-First: Huaping
Author-X-Name-Last: Chen
Title: Ant colony optimisation algorithms for two-stage permutation flow shop with batch processing machines and nonidentical job sizes
Abstract: 
 This paper focuses on minimising the maximum completion time for the two-stage permutation flow shop scheduling problem with batch processing machines and nonidentical job sizes by considering blocking, arbitrary release times, and fixed setup and cleaning times. Two hybrid ant colony optimisation algorithms, one based on job sequencing (JHACO) and the other based on batch sequencing (BHACO), are proposed to solve this problem. First, max-min pheromone restriction rules and a local optimisation rule are embedded into JHACO and BHACO, respectively, to avoid trapping in local optima. Then, an effective lower bound is estimated to evaluate the performances of the different algorithms. Finally, the Taguchi method is adopted to investigate and optimise the parameters for JHACO and BHACO. The performances of the proposed algorithms are compared with that of CPLEX on small-scale instances and those of a hybrid genetic algorithm (HGA) and a hybrid discrete differential evolution (HDDE) algorithm on full-scale instances. The computational results demonstrate that BHACO outperforms JHACO, HDDE and HGA in terms of solution quality. Besides, JHACO strikes a balance between solution quality and run time.
Journal: International Journal of Production Research
Pages: 3060-3079
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1529445
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1529445
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Template-Type: ReDIF-Article 1.0
Author-Name: Shengkai Chen
Author-X-Name-First: Shengkai
Author-X-Name-Last: Chen
Author-Name: Shuiliang Fang
Author-X-Name-First: Shuiliang
Author-X-Name-Last: Fang
Author-Name: Renzhong Tang
Author-X-Name-First: Renzhong
Author-X-Name-Last: Tang
Title: A reinforcement learning based approach for multi-projects scheduling in cloud manufacturing
Abstract: 
 This paper discussed the multi-projects scheduling problem in Cloud Manufacturing system, where each of the projects is a set of interrelated tasks, and these projects need to be scheduled timely and carefully. However, scheduling massive projects can be challenging due to the uneven distribution of the services and the uncertain arrival of projects. Therefore, we (1) established a dual-objectives optimisation model to minimise both the total makespan and the logistical distance; (2) proposed a Reinforcement Learning based Assigning Policy (RLAP) approach to obtain non-dominated solution set; (3) designed a dynamic state representing an algorithm for agents to determine their decision environment when using RLAP. Experiment results show that RLAP can adjust the distribution of service load according to the nearby tasks, and the schedule quality is improved by  $ 32.1\% $ 32.1% and  $ 5.7\% $ 5.7% compared with NSGA-II and Q-learning, respectively. Besides, the RLAP method has the ability to schedule stochastically arriving projects.
Journal: International Journal of Production Research
Pages: 3080-3098
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1535205
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1535205
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Template-Type: ReDIF-Article 1.0
Author-Name: Lohithaksha M. Maiyar
Author-X-Name-First: Lohithaksha M.
Author-X-Name-Last: Maiyar
Author-Name: SangJe Cho
Author-X-Name-First: SangJe
Author-X-Name-Last: Cho
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Author-Name: Klaus-Dieter Thoben
Author-X-Name-First: Klaus-Dieter
Author-X-Name-Last: Thoben
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Optimising online review inspired product attribute classification using the self-learning particle swarm-based Bayesian learning approach
Abstract: 
 Bowing to the burgeoning needs of online consumers, exploitation of social media content for extrapolating buyer-centric information is gaining increasing attention of researchers and practitioners from service science, data analytics, machine learning and associated domains. The current paper aims to identify the structural relationship between product attributes and subsequently prioritise customer preferences with respect to these attributes while exploiting textual social media data derived from fashion blogs in Germany. A Bayesian Network Structure Learning model with the K2score maximisation objective is formulated and solved. A self-tailored metaheuristic approach that combines self-learning particle swarm optimisation (SLPSO) with the K2 algorithm (SLPSOK2) is employed to decipher the highest scored structures. The proposed approach is implemented on small, medium and large size instances consisting of 9 fashion attributes and 18 problem sets. The results obtained by SLPSOK2 are compared with the particle swarm optimisation/K2score, Genetic Algorithm/K2 score and ant colony optimisation/K2 score. Results verify that SLPSOK2 outperforms its hybrid counterparts for the tested cases in terms of computational time and solution quality. Furthermore, the study reveals that psychological satisfaction, historical revival, seasonal information and facts and figure-based reviews are major components of information in fashion blogs that influence the customers.
Journal: International Journal of Production Research
Pages: 3099-3120
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1535724
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1535724
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Template-Type: ReDIF-Article 1.0
Author-Name: Gurkan Ozturk
Author-X-Name-First: Gurkan
Author-X-Name-Last: Ozturk
Author-Name: Ozan Bahadir
Author-X-Name-First: Ozan
Author-X-Name-Last: Bahadir
Author-Name: Aydin Teymourifar
Author-X-Name-First: Aydin
Author-X-Name-Last: Teymourifar
Title: Extracting priority rules for dynamic multi-objective flexible job shop scheduling problems using gene expression programming
Abstract: 
 In this paper, two new approaches are proposed for extracting composite priority rules for scheduling problems. The suggested approaches use simulation and gene expression programming and are able to evolve specific priority rules for all dynamic scheduling problems in accordance with their features. The methods are based on the idea that both the proper design of the function and terminal sets and the structure of the gene expression programming approach significantly affect the results. In the first proposed approach, modified and operational features of the scheduling environment are added to the terminal set, and a multigenic system is used, whereas in the second approach, priority rules are used as automatically defined functions, which are combined with the cellular system for gene expression programming. A comparison shows that the second approach generates better results than the first; however, all of the extracted rules yield better results than the rules from the literature, especially for the defined multi-objective function consisting of makespan, mean lateness and mean flow time. The presented methods and the generated priority rules are robust and can be applied to all real and large-scale dynamic scheduling problems.
Journal: International Journal of Production Research
Pages: 3121-3137
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1543964
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543964
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3121-3137




Template-Type: ReDIF-Article 1.0
Author-Name: G. M. Komaki
Author-X-Name-First: G. M.
Author-X-Name-Last: Komaki
Author-Name: Shaya Sheikh
Author-X-Name-First: Shaya
Author-X-Name-Last: Sheikh
Author-Name: Behnam Malakooti
Author-X-Name-First: Behnam
Author-X-Name-Last: Malakooti
Title: Flow shop scheduling problems with assembly operations: a review and new trends
Abstract: 
 The past few years have witnessed a resurgence of interest in assembly flow shop scheduling as evidenced by increasing number of published articles in this field. A basic assembly flow shop consists of two types of stages: fabrication or machining stage and assembly stage. Machining and assembly stages are composed of either one or a set of machines that are working in parallel. Final products have hierarchical assembly structure with several components and assembly operation(s). The components need to be processed in the machining stage(s) and then assembled based on hierarchical assembly structure. The goal is to find the sequence of jobs that optimises certain objectives. Assembly flow shop scheduling problem has several interesting derivatives and applications in various manufacturing and service industries. This paper provides a consolidated survey of assembly flow shop models with their solution methodology. Finally, the paper concludes by presenting some problems receiving less attention and proposes several salient research opportunities.
Journal: International Journal of Production Research
Pages: 2926-2955
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1550269
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1550269
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:2926-2955




Template-Type: ReDIF-Article 1.0
Author-Name: Hadi Moradi
Author-X-Name-First: Hadi
Author-X-Name-Last: Moradi
Author-Name: Shahram Shadrokh
Author-X-Name-First: Shahram
Author-X-Name-Last: Shadrokh
Title: A robust scheduling for the multi-mode project scheduling problem with a given deadline under uncertainty of activity duration
Abstract: 
 The problem of this paper deals with the multi-mode project scheduling problem under uncertainty of activity duration where only the renewable resources are taken into account and a given deadline has to be met at the cost of recruiting additional resources. A heuristic algorithm is employed to solve this problem, and to maintain the robustness of the baseline schedule, the concept of critical chain project management (CCPM) is applied in which a new definition to resource buffer is considered. A simulation methodology is used to determine the size and location of resource buffers in the schedules in which three different buffer sizes and three different uncertainty levels are considered. Results and analysis of the simulation outcomes illustrate that resource buffers are useful and should be simulated by the CCPM schedules, as they help to decrease the total duration of the project during implementation and meet the deadline of the project with more assurance.
Journal: International Journal of Production Research
Pages: 3138-3167
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1552371
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1552371
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3138-3167




Template-Type: ReDIF-Article 1.0
Author-Name: Bing Wang
Author-X-Name-First: Bing
Author-X-Name-Last: Wang
Author-Name: Xiaozhi Wang
Author-X-Name-First: Xiaozhi
Author-X-Name-Last: Wang
Author-Name: Hanxin Xie
Author-X-Name-First: Hanxin
Author-X-Name-Last: Xie
Title: Bad-scenario-set robust scheduling for a job shop to hedge against processing time uncertainty
Abstract: 
 This paper proposed two robust scheduling formulations in real manufacturing systems based on the concept of bad scenario set to hedge against processing time uncertainty, which is described by discrete scenarios. Two proposed robust scheduling formulations are applied to an uncertain job-shop scheduling problem with the makespan as the performance criterion. The united-scenario neighbourhood (UN) structure is constructed based on bad scenario set for the scenario job-shop scheduling problem. A tabu search (TS) algorithm with the UN structure is developed to solve the proposed robust scheduling problem. An extensive experiment was conducted. The computational results show that the first robust scheduling formulation could be preferred to the second one for the discussed problem. It is also verified that the obtained robust solutions could hedge against the processing time uncertainty through decreasing the number of bad scenarios and the degree of performance degradation on bad scenarios. Moreover, the computational results demonstrate that the developed TS algorithm is competitive for the proposed robust scheduling formulations.
Journal: International Journal of Production Research
Pages: 3168-3185
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2018.1555650
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1555650
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3168-3185




Template-Type: ReDIF-Article 1.0
Author-Name: Xinyu Sun
Author-X-Name-First: Xinyu
Author-X-Name-Last: Sun
Author-Name: Xin-Na Geng
Author-X-Name-First: Xin-Na
Author-X-Name-Last: Geng
Title: Single-machine scheduling with deteriorating effects and machine maintenance
Abstract: 
 In this paper, the single-machine scheduling problems with deteriorating effects and a machine maintenance are studied. In this circumstance, the deterioration rates of the jobs during the machining process are the same which reduces the production efficiency. The actual processing time of the job is a linearly increasing function of the starting time. In this process, the machine only performs a maintenance activity, and the maintenance time is a fixed value. After the maintenance work is completed, the machine will be restored to the initial state, and the deterioration of the job will be start again. The goal is to determine the optimal schedule in order to minimise the maximum completion time (i.e. the makespan) and the sum of job completion times. We prove that both problems are polynomial time solvable, and we also provide the corresponding algorithms.
Journal: International Journal of Production Research
Pages: 3186-3199
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1566675
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566675
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3186-3199




Template-Type: ReDIF-Article 1.0
Author-Name: Jing-jing Wang
Author-X-Name-First: Jing-jing
Author-X-Name-Last: Wang
Author-Name: Ling Wang
Author-X-Name-First: Ling
Author-X-Name-Last: Wang
Title: Decoding methods for the flow shop scheduling with peak power consumption constraints
Abstract: 
 The permutation flow shop scheduling problem (PFSP) is of wide application backgrounds and plays an important role in the manufacturing systems. With the serious energy concerns in manufacturing enterprises, peak power consumption is considered one of the significant issues. For the PFSP with peak power consumption constraints (PFSPP), the real-time power consumption cannot exceed a given peak power at any time. Since the classical first-come first-serve scheduling method is not suitable for the PFSPP, this paper addresses the decoding methods to obtain feasible schedules based on the permutation encoding scheme. First, an earliest processing rule (EPR) is designed to determine the starting time of each operation, satisfying the power consumption constraints. Then, five decoding methods based on EPR are proposed to determine the suitable priority between the operations to yield feasible schedules with high quality. After analysing the complexity of the proposed decoding methods and comparing the performances via extensive numerical tests, some suggestions are provided for solving the PFSPP with different scales and power constraints.
Journal: International Journal of Production Research
Pages: 3200-3218
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1571252
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1571252
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3200-3218




Template-Type: ReDIF-Article 1.0
Author-Name: Tsui-Ping Chung
Author-X-Name-First: Tsui-Ping
Author-X-Name-Last: Chung
Author-Name: Feng Chen
Author-X-Name-First: Feng
Author-X-Name-Last: Chen
Title: A complete immunoglobulin-based artificial immune system algorithm for two-stage assembly flowshop scheduling problem with part splitting and distinct due windows
Abstract: 
 This paper considers a two-stage assembly flowshop scheduling problem with distinct due windows to minimise the sum of weighted earliness and tardiness. There are several identical parallel machines which produce parts in the first stage. When the required parts are available, a single assembly machine can group these parts into products in the second stage. It is assumed that a part can be split into sub-parts which can be processed independently on the parallel machines in the first stage. Setup is also considered. A mathematical model is established to describe and define the proposed problem. A new decoding method is developed by extending an existing decoding method. Two novel operators, named part splitting (PS) and optimal idle time insertion (ITI), are incorporated into the decoding procedure for improving the quality of the solution. A rule named Priority of Earliness and Tardiness (PET) and a Complete Immunoglobulin-based Artificial Immune System (C-IAIS) algorithm are proposed for solving the problem. To evaluate PET and C-IAIS algorithm, several existing algorithms are used in the experiments. Computational results show that C-IAIS algorithm performs better than other algorithms for solving the proposed problem.
Journal: International Journal of Production Research
Pages: 3219-3237
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1577565
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1577565
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Template-Type: ReDIF-Article 1.0
Author-Name: Wanzhe Hu
Author-X-Name-First: Wanzhe
Author-X-Name-Last: Hu
Author-Name: Zhong Zheng
Author-X-Name-First: Zhong
Author-X-Name-Last: Zheng
Author-Name: Xiaoqiang Gao
Author-X-Name-First: Xiaoqiang
Author-X-Name-Last: Gao
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Title: An improved method for the hot strip mill production scheduling problem
Abstract: 
 In most research on the hot strip mill production scheduling problem (HSMPSP) arising in the steel industry, it is accepted that a schedule with lower penalty caused by jumps of width, hardness, and gauge will result in lower roller wear, so it is regarded as a better schedule. However, based on the analysis of production processes, it is realised that rolling each coil also cause roller wear. In order to assessing the roller wear associated with production scheduling more precisely, it is necessary to consider it as another factor besides those jumps, especially when complicated constraints are involved. In this paper, an improved method is proposed to quantify the expected wear of the rollers done by those jumps and rolling processes. Then the HSMPSP whose objective is to maximise the total length of all scheduled coils is formulated as a team orienteering problem with time windows and additional production constraints. A heuristic method combining an improved Ant Colony Extended algorithm with local search procedures dedicated to HSMPSP is developed. Finally, computational results on instances generated based on production data from an integrated steel mill in China indicate that the proposed algorithm is a promising solution specific to HSMPSP.
Journal: International Journal of Production Research
Pages: 3238-3254
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1579932
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1579932
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3238-3254




Template-Type: ReDIF-Article 1.0
Author-Name: Hamid Safarzadeh
Author-X-Name-First: Hamid
Author-X-Name-Last: Safarzadeh
Author-Name: Farhad Kianfar
Author-X-Name-First: Farhad
Author-X-Name-Last: Kianfar
Title: Job shop scheduling with the option of jobs outsourcing
Abstract: 
 Incorporating outsourcing in scheduling is addressed by several researchers recently. However, this scope is not investigated thoroughly, particularly in the job shop environment. In this paper, a new job shop scheduling problem is studied with the option of jobs outsourcing. The problem objective is to minimise a weighted sum of makespan and total outsourcing cost. With the aim of solving this problem optimally, two solution approaches of combinatorial optimisation problems, i.e. mathematical programming and constraint programming are examined. Furthermore, two problem relaxation approaches are developed to obtain strong lower bounds for some large scale problems for which the optimality is not proven by the applied solution techniques. Using extensive numerical experiments, the performance of the solution approaches is evaluated. Moreover, the effect the objectives's weights in the objective function on the performance of the solution approaches is also investigated. It is concluded that constraint programming outperforms mathematical programming significantly in proving solution optimality, as it can solve small and medium size problems optimally. Moreover, by solving the relaxed problems, one can obtain good lower bounds for optimal solutions even in some large scale problems.
Journal: International Journal of Production Research
Pages: 3255-3272
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1579934
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1579934
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3255-3272




Template-Type: ReDIF-Article 1.0
Author-Name: Mehmet Ertem
Author-X-Name-First: Mehmet
Author-X-Name-Last: Ertem
Author-Name: Feristah Ozcelik
Author-X-Name-First: Feristah
Author-X-Name-Last: Ozcelik
Author-Name: Tugba Saraç
Author-X-Name-First: Tugba
Author-X-Name-Last: Saraç
Title: Single machine scheduling problem with stochastic sequence-dependent setup times
Abstract: 
 In this study, we consider stochastic single machine scheduling problem. We assume that setup times are both sequence dependent and uncertain while processing times and due dates are deterministic. In the literature, most of the studies consider the uncertainty on processing times or due dates. However, in the real-world applications (i.e. plastic moulding industry, appliance assembly, etc.), it is common to see varying setup times due to labour or setup tools availability. In order to cover this fact in machine scheduling, we set our objective as to minimise the total expected tardiness under uncertain sequence-dependent setup times. For the solution of this NP-hard problem, several heuristics and some dynamic programming algorithms have been developed. However, none of these approaches provide an exact solution for the problem. In this study, a two-stage stochastic-programming method is utilised for the optimal solution of the problem. In addition, a Genetic Algorithm approach is proposed to solve the large-size problems approximately. Finally, the results of the stochastic approach are compared with the deterministic one to demonstrate the value of the stochastic solution.
Journal: International Journal of Production Research
Pages: 3273-3289
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1581383
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1581383
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3273-3289




Template-Type: ReDIF-Article 1.0
Author-Name: Sungbum Jun
Author-X-Name-First: Sungbum
Author-X-Name-Last: Jun
Author-Name: Seokcheon Lee
Author-X-Name-First: Seokcheon
Author-X-Name-Last: Lee
Author-Name: Hyonho Chun
Author-X-Name-First: Hyonho
Author-X-Name-Last: Chun
Title: Learning dispatching rules using random forest in flexible job shop scheduling problems
Abstract: 
 In this paper, we address the flexible job-shop scheduling problem (FJSP) with release times for minimising the total weighted tardiness by learning dispatching rules from schedules. We propose a random-forest-based approach called Random Forest for Obtaining Rules for Scheduling (RANFORS) in order to extract dispatching rules from the best schedules. RANFORS consists of three phases: schedule generation, rule learning with data transformation, and rule improvement with discretisation. In the schedule generation phase, we present three solution approaches that are widely used to solve FJSPs. Based on the best schedules among them, the rule learning with data transformation phase converts them into training data with constructed attributes and generates a dispatching rule with inductive learning. Finally, the rule improvement with discretisation improves dispatching rules with a genetic algorithm by discretising continuous attributes and changing parameters for random forest with the aim of minimising the average total weighted tardiness. We conducted experiments to verify the performance of the proposed approach and the results showed that it outperforms the existing dispatching rules. Moreover, compared with the other decision-tree-based algorithms, the proposed algorithm is effective in terms of extracting scheduling insights from a set of rules.
Journal: International Journal of Production Research
Pages: 3290-3310
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1581954
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1581954
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3290-3310




Template-Type: ReDIF-Article 1.0
Author-Name: Reza Ramezanian
Author-X-Name-First: Reza
Author-X-Name-Last: Ramezanian
Author-Name: Mohammad Mahdi Vali-Siar
Author-X-Name-First: Mohammad Mahdi
Author-X-Name-Last: Vali-Siar
Author-Name: Mahdi Jalalian
Author-X-Name-First: Mahdi
Author-X-Name-Last: Jalalian
Title: Green permutation flowshop scheduling problem with sequence-dependent setup times: a case study
Abstract: 
 Increasing global energy consumption, large variations in its cost and the environmental degradation effects are good reasons for the manufacturing industries to become greener. Green shop floor scheduling is increasingly becoming a vital factor in the sustainable manufacturing. In this paper, a green permutation flowshop scheduling problem with sequence-dependent setup times is studied. Two objectives are considered including minimisation of makespan as a measure of service level and minimisation of total energy consumption as a measure of environmental sustainability. We extend a bi-objective mixed-integer linear programming model to formulate the stated problem. We develop a constructive heuristic algorithm to solve the model. The constructive heuristic algorithm includes iterated greedy (CHIG) and local search (CHLS) algorithms. We develop an efficient energy-saving method which decreases energy consumption, on average, by about 15%. To evaluate the effectiveness of the constructive heuristic algorithm, we compare it with the famous augmented ϵ-constraint method using various small-sized and large-sized problems. The results confirm that the heuristic algorithm obtains high-quality non-dominated solutions in comparison with the augmented ϵ-constraint method. Also, they show that the CHIG outperforms the CHLS. Finally, this paper follows a case-study, with in-depth analysis of the model and the constructive heuristic algorithm.
Journal: International Journal of Production Research
Pages: 3311-3333
Issue: 10
Volume: 57
Year: 2019
Month: 5
X-DOI: 10.1080/00207543.2019.1581955
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1581955
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3311-3333




Template-Type: ReDIF-Article 1.0
Author-Name: Borja Ramis Ferrer
Author-X-Name-First: Borja
Author-X-Name-Last: Ramis Ferrer
Author-Name: Jose Luis Martinez Lastra
Author-X-Name-First: Jose Luis
Author-X-Name-Last: Martinez Lastra
Title: Towards the encapsulation and decentralisation of OKD-MES services within embedded devices
Abstract: 
 Traditionally, the resources of embedded devices which are employed for process control at shop floors were resource constrained. However, advances in embedded system technologies permit the enhancement of the processing and storage capabilities of embedded devices. Therefore, semantic descriptions of manufacturing systems can now be hosted and computed at the device level. This fact permits the creation of a decentralised solution for controlling processes at the lowest level of the manufacturing enterprises and the reduction in the time and effort requirements for the configuration and information exchange. The eScop project presented the Open Knowledge-Driven Manufacturing Execution System (OKD-MES) solution, which enables monitoring and controlling production systems openly and allows runtime re-configurability of interconnected industrial equipment and services. This research work presents how part of the OKD-MES functionality can be handled at lower level. More precisely, the OKD-MES representation and management of knowledge can be decentralised and handled at the shop floor level, where the industrial machines are connected to devices that are capable of controlling the execution of processes. The main objective of this paper is to describe a decentralised vision for the OKD-MES framework, which is a centric solution in terms of knowledge management. Moreover, the article also discusses some of the advantages to be gained from decentralising the management of knowledge model semantic descriptions.
Journal: International Journal of Production Research
Pages: 1286-1298
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1328141
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1328141
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Template-Type: ReDIF-Article 1.0
Author-Name: Rajesh Piplani
Author-X-Name-First: Rajesh
Author-X-Name-Last: Piplani
Author-Name: Alvin Wei Hern Ang
Author-X-Name-First: Alvin Wei Hern
Author-X-Name-Last: Ang
Title: Performance comparison of multiple product kanban control systems
Abstract: 
 Kanban control systems have been around for decades and have been used to control work-in-process of manufacturing systems. Lately many variations of the basic control system have been developed; however, much of the work in the development and comparison of control systems has focused on a single-stage manufacturing system producing a single product type. In this research, we present procedures for optimising multiple product kanban control systems, namely Base Stock, Traditional Kanban Control System and Extended Kanban Control System (both dedicated and shared type). We then conduct a detailed simulation study to compare the performance of the systems using a common total cost measure. Numerical results show that the dedicated and shared-extended kanban control systems outperform the other two systems. The study also shows that in spite of their different schematics and contrary to conventional wisdom, the performance of dedicated and shared-extended kanban control systems doesn’t differ much.
Journal: International Journal of Production Research
Pages: 1299-1312
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1332436
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1332436
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Template-Type: ReDIF-Article 1.0
Author-Name: Ye Shi
Author-X-Name-First: Ye
Author-X-Name-Last: Shi
Author-Name: Xiaolong Guo
Author-X-Name-First: Xiaolong
Author-X-Name-Last: Guo
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Title: Dynamic warehouse size planning with demand forecast and contract flexibility
Abstract: 
 This paper develops a dynamic warehouse planning model incorporating demand forecast and contract flexibility, and addresses how demand forecast and contract flexibility affect warehouse size planning. In this model, a manager announces a nominal size of the warehouse space to rent before the planning horizon begins (strategic decision), and determines the ordering quantity and actual warehouse size during the horizon (operational decision). In particular, the manager can adjust the actual warehouse size within a range according to dynamically updating demand forecast during the horizon, which reflects the contract flexibility. We start with the characterisation of the operational decision. For any given nominal size, we show the monotonicity of optimal inventory replenishment and warehousing decisions w.r.t. demand forecast and contract flexibility. However, this monotonicity does not necessarily hold for the strategic choice of the nominal size. Finally, a case study is presented to investigate the interaction between demand forecast information and contract flexibility. We find that the value of demand forecast can be enhanced as the contract flexibility improves. However, more forecasted demands do not imply higher value of contract flexibility.
Journal: International Journal of Production Research
Pages: 1313-1325
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1336680
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1336680
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Template-Type: ReDIF-Article 1.0
Author-Name: Tiffany Bayley
Author-X-Name-First: Tiffany
Author-X-Name-Last: Bayley
Author-Name: Haldun Süral
Author-X-Name-First: Haldun
Author-X-Name-Last: Süral
Author-Name: James H. Bookbinder
Author-X-Name-First: James H.
Author-X-Name-Last: Bookbinder
Title: A hybrid Benders approach for coordinated capacitated lot-sizing of multiple product families with set-up times
Abstract: 
 We examine a coordinated capacitated lot-sizing problem for multiple product families, where demand is deterministic and time-varying. The problem considers set-up and holding costs, where capacity constraints limit the number of individual item and family set-up times and the amount of production in each period. Using a strong reformulation and relaxing the demand constraints, we improve both the upper and lower bounds using a combination of Benders decomposition and an evolutionary algorithm, followed by subgradient optimisation. Through computational experiments, we show that our method consistently achieves better bounds, reducing the duality gap compared to other single-family methods studied in the literature.
Journal: International Journal of Production Research
Pages: 1326-1344
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1338778
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1338778
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1326-1344




Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoyun Xiong
Author-X-Name-First: Xiaoyun
Author-X-Name-Last: Xiong
Author-Name: Dujuan Wang
Author-X-Name-First: Dujuan
Author-X-Name-Last: Wang
Author-Name: T.C. Edwin Cheng
Author-X-Name-First: T.C.
Author-X-Name-Last: Edwin Cheng
Author-Name: Chin-Chia Wu
Author-X-Name-First: Chin-Chia
Author-X-Name-Last: Wu
Author-Name: Yunqiang Yin
Author-X-Name-First: Yunqiang
Author-X-Name-Last: Yin
Title: Single-machine scheduling and common due date assignment with potential machine disruption
Abstract: 
 This paper studies a single-machine due date assignment and scheduling problem in a disruptive environment, where a machine disruption may occur at a particular time that will last for a period of time with a certain probability, and the job due dates are determined by the decision-maker using the popular common due date assignment method. The goal is to determine jointly the optimal job sequence and the common due date so as to minimise the expected value of an integrated cost function that includes the earliness, tardiness and due date assignment costs. We analyse the computational complexity status of various cases of the problem, and develop pseudo-polynomial-time solution algorithms, randomised adaptive search algorithms, and fully polynomial-time approximation schemes for them, if viable. Finally, we conduct extensive numerical testing to assess the performance of the proposed algorithms.
Journal: International Journal of Production Research
Pages: 1345-1360
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1346317
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346317
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Template-Type: ReDIF-Article 1.0
Author-Name: Peng Zhang
Author-X-Name-First: Peng
Author-X-Name-Last: Zhang
Author-Name: Youlong Lv
Author-X-Name-First: Youlong
Author-X-Name-Last: Lv
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Title: An improved imperialist competitive algorithm based photolithography machines scheduling
Abstract: 
 Abstract: Photolithography machine is one of the most expensive equipment in semiconductor manufacturing system, and as such is often the bottleneck for processing wafers. This paper focuses on photolithography machines scheduling with the objective of total completion time minimisation. In contrast to classic parallel machines scheduling, it is characterised by dynamical arrival wafers, re-entrant process flows, dedicated machine constraints and auxiliary resources constraints. We propose an improved imperialist competitive algorithm (ICA) within the framework of a rolling horizon strategy for the problem. We develop a variable time interval-based rolling horizon strategy to decide the scheduling point. We address the global optimisation in every local scheduling by proposing a mixed cost function. Moreover, an adaptive assimilation operator and a sociopolitical competition operator are used to prevent premature convergence of ICA to local optima. A chaotic sequence-based local search method is presented to accelerate the rate of convergence. Computational experiments are carried out comparing the proposed algorithm with ILOG CPLEX, dispatching rules and meta-heuristic algorithms in the literature. It is observed that the algorithm proposed shows an excellent behaviour on cycle time minimisation while with a good on time delivery rate and machine utilisation rate.
Journal: International Journal of Production Research
Pages: 1017-1029
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1346320
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1346320
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Template-Type: ReDIF-Article 1.0
Author-Name: Manuel Mateo
Author-X-Name-First: Manuel
Author-X-Name-Last: Mateo
Author-Name: Jacques Teghem
Author-X-Name-First: Jacques
Author-X-Name-Last: Teghem
Author-Name: Daniel Tuyttens
Author-X-Name-First: Daniel
Author-X-Name-Last: Tuyttens
Title: A bi-objective parallel machine problem with eligibility, release dates and delivery times of the jobs
Abstract: 
 The scheduling of parallel machines is a well-known problem in many companies. Nevertheless, not always all the jobs can be manufactured in any machine and the eligibility appears. Based on a real-life problem, we present a model which has m parallel machines with different level of quality from the highest level for the first machine till the lowest level for the last machine. The set of jobs to be scheduled on these m parallel machines are also distributed among these m levels: one job from a level can be manufactured in a machine of the same or higher level but a penalty, depending on the level, appears when a job is manufactured in a machine different from the highest level i.e. different from the first machine. Besides, there are release dates and delivery times associated to each job. The tackled problem is bi-objective with the criteria: minimisation of the final date – i.e. the maximum for all the jobs of their completion time plus the delivery time – and the minimisation of the total penalty generated by the jobs. In a first step, we analyse the sub-problem of minimisation of the final date on a single machine for jobs with release dates and delivery times. Four heuristics and an improvement algorithm are proposed and compared on didactic examples and on a large set of instances. In a second step an algorithm is proposed to approximate the set of efficient solutions and the Pareto front of the bi-objective problem. This algorithm contains two phases: the first is a depth search phase and the second is a backtracking phase. The procedure is illustrated in detail on an instance with 20 jobs and 3 machines. Then extensive numerical experiments are realised on two different sets of instances, with 20, 30 and 50 jobs, 3 or 4 machines and various values of penalties. Except for the case of 50 jobs, the results are compared with the exact Pareto front.
Journal: International Journal of Production Research
Pages: 1030-1053
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1351634
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1351634
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Template-Type: ReDIF-Article 1.0
Author-Name: Lionel Dupont
Author-X-Name-First: Lionel
Author-X-Name-Last: Dupont
Author-Name: Christophe Bernard
Author-X-Name-First: Christophe
Author-X-Name-Last: Bernard
Author-Name: Faiza Hamdi
Author-X-Name-First: Faiza
Author-X-Name-Last: Hamdi
Author-Name: Faouzi Masmoudi
Author-X-Name-First: Faouzi
Author-X-Name-Last: Masmoudi
Title: Supplier selection under risk of delivery failure: a decision-support model considering managers’ risk sensitivity
Abstract: 
 This paper studies the problem of supplier selection and order allocation in a retail supply chain (comprising suppliers, a central purchasing unit and outlets) under disruption risk. The final demand is deterministic. Suppliers are located in different geographic areas, and supplies are subject to a positive probability of disruption. Different capacity and failure probabilities for each supplier are considered. Our analysis focuses on the insurance versus profitability trade-off faced by a supply manager who buys from suppliers for the outlets. Instead of determining optimal decisions given an objective function and the risk sensitivity of the decision-maker, we use a mixed integer linear programming approach to provide decision-making support that shows a supply manager the ‘elasticity of (expected) losses versus (expected) profits’. Under this model, and depending on the profit-and-loss targets, a supply manager of known risk sensitivity (i.e. risk aversion and loss aversion) can make better decisions when choosing suppliers. Moreover, taking into account, the impact of the share of fixed costs that must be covered by the operation, we consider the net values of expected profit and loss. We discuss the potential influence of the level of the firm’s fixed costs on the supply strategy. In particular, we show how the minimum value of the gross margin needed for the strategy’s profitability affects that strategy. A numerical application is conducted to illustrate the contribution of our decision-making support mechanism, and several managerial insights are obtained.
Journal: International Journal of Production Research
Pages: 1054-1069
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1364442
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1364442
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Template-Type: ReDIF-Article 1.0
Author-Name: Afshin Jamshidi
Author-X-Name-First: Afshin
Author-X-Name-Last: Jamshidi
Author-Name: Daoud Ait-kadi
Author-X-Name-First: Daoud
Author-X-Name-Last: Ait-kadi
Author-Name: Angel Ruiz
Author-X-Name-First: Angel
Author-X-Name-Last: Ruiz
Author-Name: Mohamed Larbi Rebaiaia
Author-X-Name-First: Mohamed Larbi
Author-X-Name-Last: Rebaiaia
Title: Dynamic risk assessment of complex systems using FCM
Abstract: 
 Analysing risk of today’s complex systems is challenging due to the complex and dynamic nature of systems. The current risk analysis tools are not able to take the complex interactions among risks into account and therefore they can’t predict the behaviour of risks accurately. In an attempt to overcome this shortcoming, this paper proposes an integrated generalised decision support tool using fuzzy cognitive maps for dynamic risk assessment of complex systems. The proposed approach has the ability to prioritise risk factors and more importantly predict and analysis the influences of each individual risk factor/risk set on the other risks or on the outcomes of complex and critical systems by taking into account probability of occurrence and consequences of risks and also considering the complex dependencies between risk factors. These features could provide practitioners with realistic results in critical industries and able them to manage risks more efficiently.
Journal: International Journal of Production Research
Pages: 1070-1088
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1370148
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1370148
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1070-1088




Template-Type: ReDIF-Article 1.0
Author-Name: H. Cherkaoui
Author-X-Name-First: H.
Author-X-Name-Last: Cherkaoui
Author-Name: K.T. Huynh
Author-X-Name-First: K.T.
Author-X-Name-Last: Huynh
Author-Name: A. Grall
Author-X-Name-First: A.
Author-X-Name-Last: Grall
Title: Quantitative assessments of performance and robustness of maintenance policies for stochastically deteriorating production systems
Abstract: 
 Over the last few decades, many efforts have been invested in improving the economic performances of maintenance policies for stochastically deteriorating production systems. However, with the development of complex production systems, maintenance managers are interested not only in cost saving, but also in how to trustworthily plan and allocate the required maintenance budget. In this context, the robustness of maintenance policies which is related to the maintenance cost variability from a renewal cycle to another plays a pivotal role. This research deals with a quantitative approach to jointly assess the economic performance and robustness of some representatives of two most well-known classes of maintenance policies: time-based and condition-based maintenance. To this end, we first propose a new cost criterion which combines the long-run expected cost rate and standard deviation of maintenance cost per renewal cycle. Then, we develop and compare the associated mathematical cost models of the considered maintenance policies on the basis of the Gamma degradation process and the theory of stochastic renewal processes. The comparison results under different situations of maintenance costs and system characteristics show that the optimal configuration of maintenance policies gives the best compromise between the performance and robustness, and is mostly affected by the system downtime. Under this aspect, the condition-based maintenance remains more profitable than the time-based maintenance. Still, maintenance managers could implement condition-based maintenance policies that efficiently control the downtime to maximise the maintenance effectiveness of production systems from both performance and robustness viewpoints.
Journal: International Journal of Production Research
Pages: 1089-1108
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1370563
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1370563
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Template-Type: ReDIF-Article 1.0
Author-Name: Robin Hanson
Author-X-Name-First: Robin
Author-X-Name-Last: Hanson
Author-Name: Lars Medbo
Author-X-Name-First: Lars
Author-X-Name-Last: Medbo
Author-Name: Majeed Assaf
Author-X-Name-First: Majeed
Author-X-Name-Last: Assaf
Author-Name: Patrik Jukic
Author-X-Name-First: Patrik
Author-X-Name-Last: Jukic
Title: Time efficiency and physical workload in manual picking from large containers
Abstract: 
 A common task in both trade and manufacturing, manual picking from large containers often involves considerable physical workload, as well as low efficiency and varying picking times. With quantitative evidence from an industrial setting, the paper provides detailed insights into how physical workload and picking time vary in picking from large containers. Components at a short horizontal distance from the picker and at the top instead of the bottom of the pallet are associated with shorter picking time and lower physical workload. Moreover, pallets tilted 45° towards the picker are associated with picking times that are significantly shorter on average and display smaller variations than horizontal pallets. The effects that the tilting of the pallets has on physical workload differs depending on component characteristics and from which section of the containers picking was performed. In the study, the greatest values of physical workload were observed for the tilted pallets.
Journal: International Journal of Production Research
Pages: 1109-1117
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1371352
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1371352
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1109-1117




Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Moeuf
Author-X-Name-First: Alexandre
Author-X-Name-Last: Moeuf
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Author-Name: Samir Lamouri
Author-X-Name-First: Samir
Author-X-Name-Last: Lamouri
Author-Name: Simon Tamayo-Giraldo
Author-X-Name-First: Simon
Author-X-Name-Last: Tamayo-Giraldo
Author-Name: Rodolphe Barbaray
Author-X-Name-First: Rodolphe
Author-X-Name-Last: Barbaray
Title: The industrial management of SMEs in the era of Industry 4.0
Abstract: 
 Industry 4.0 provides new paradigms for the industrial management of SMEs. Supported by a growing number of new technologies, this concept appears more flexible and less expensive than traditional enterprise information systems such as ERP and MES. However, SMEs find themselves ill-equipped to face these new possibilities regarding their production planning and control functions. This paper presents a literature review of existing applied research covering different Industry 4.0 issues with regard to SMEs. Papers are classified according to a new framework which allows identification of the targeted performance objectives, the required managerial capacities and the selected group of technologies for each selected case. Our results show that SMEs do not exploit all the resources for implementing Industry 4.0 and often limit themselves to the adoption of Cloud Computing and the Internet of Things. Likewise, SMEs seem to have adopted Industry 4.0 concepts only for monitoring industrial processes and there is still absence of real applications in the field of production planning. Finally, our literature review shows that reported Industry 4.0 projects in SMEs remained cost-driven initiatives and there in still no evidence of real business model transformation at this time.
Journal: International Journal of Production Research
Pages: 1118-1136
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1372647
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1372647
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1118-1136




Template-Type: ReDIF-Article 1.0
Author-Name: Dimitris Mourtzis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Mourtzis
Author-Name: Sophia Fotia
Author-X-Name-First: Sophia
Author-X-Name-Last: Fotia
Author-Name: Nikoletta Boli
Author-X-Name-First: Nikoletta
Author-X-Name-Last: Boli
Author-Name: Ekaterini Vlachou
Author-X-Name-First: Ekaterini
Author-X-Name-Last: Vlachou
Title: An approach for the modelling and quantification of PSS customisation
Abstract: 
 A Product–Service System (PSS) is a dynamic and multidimensional system that is comprised of products, services, a large network of stakeholders and all necessary supporting infrastructures, aiming towards becoming continuously competitive, satisfying customer needs and improving environmental aspects. The design of such a system and its evaluation throughout the lifecycle are challenging tasks owing to their inherent complexity, which becomes even greater when the aspect of customisation is considered. Nevertheless, the literature work regarding the customisation of PSS is scarce. Towards bridging this gap, the present work proposes a framework for PSS customisation, including the main steps that are required for a successful PSS customisation. For each step in the framework, which has been collected from the literature, PSS approaches have been provided, and could be used in the execution of each step. Next, the present study introduces a method for: (i) the modular representation of PSS based on vector analysis, and then (ii) the quantification of the PSS customisation degree.
Journal: International Journal of Production Research
Pages: 1137-1153
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1378956
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1378956
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1137-1153




Template-Type: ReDIF-Article 1.0
Author-Name: Paul Hahn-Woernle
Author-X-Name-First: Paul
Author-X-Name-Last: Hahn-Woernle
Author-Name: Willibald A. Günthner
Author-X-Name-First: Willibald A.
Author-X-Name-Last: Günthner
Title: Power-load management reduces energy-dependent costs of multi-aisle mini-load automated storage and retrieval systems
Abstract: 
 For economic and ecological reasons, the interest in the energy demand of material-handling systems is rising. As a result, the operators of these systems increasingly pay attention to the energy demand and the costs resulting from it. The energy demand of automated warehouses, with multi-aisle automated storage and retrieval systems, is volatile with uncontrolled power-peaks. These power-peaks result in high energy and hardware costs. In this paper, the effect of a power-load management on the throughput of the material-handling systems is investigated. We assume that the peaks of energy consumption can be significantly reduced by delaying tasks, without having an impact on the throughput. The goal is to find out the interdependence between the electrical power-limits of the power-load management (mean power demand in a period and maximum power demand) and the throughput of the warehouse. The results show that, with a maximum power-limit and a mean power-limit, the peaks in energy consumption can be avoided with only a slight loss of throughput. Load management is an effective method to reduce the energy peaks of an automated warehouse, thereby lowering the costs of automated warehouses.
Journal: International Journal of Production Research
Pages: 1269-1285
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1395487
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1395487
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1269-1285




Template-Type: ReDIF-Article 1.0
Author-Name: Massimo Paolucci
Author-X-Name-First: Massimo
Author-X-Name-Last: Paolucci
Author-Name: Davide Anghinolfi
Author-X-Name-First: Davide
Author-X-Name-Last: Anghinolfi
Author-Name: Flavio Tonelli
Author-X-Name-First: Flavio
Author-X-Name-Last: Tonelli
Title: Field services design and management of natural gas distribution networks: a class of vehicle routing problem with time windows approach
Abstract: 
 Service operations management of metropolitan gas networks at operational level implies the optimisation of decisions related to logistic activities, taking into account multi-objectives and operational constraints. This paper proposes a metaheuristic approach for the operational planning of the daily logistic activities based on vehicle routing with time window model. Experimental results for a real planning case in a gas distribution network demonstrate the approach effectiveness.
Journal: International Journal of Production Research
Pages: 1154-1170
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1398425
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398425
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Template-Type: ReDIF-Article 1.0
Author-Name: T.A. Makarovskikh
Author-X-Name-First: T.A.
Author-X-Name-Last: Makarovskikh
Author-Name: A.V. Panyukov
Author-X-Name-First: A.V.
Author-X-Name-Last: Panyukov
Author-Name: E.A. Savitskiy
Author-X-Name-First: E.A.
Author-X-Name-Last: Savitskiy
Title: Mathematical models and routing algorithms for economical cutting tool paths
Abstract: 
 Resource-efficient technologies for cutting sheet materials allow for the contours of cut-off details to be overlapped. This includes the Intermittent Cutting Problem and the Endpoint Cutting Problem. This paper reviews mathematical models of such resource-efficient cutting processes and suggests algorithms for defining the cutter route under technological constraints. As soon as a cutting plan is given, optimisation with shortening the total length of idle passes. No information of the detail shape is required to define the sequence of detail cutting. This is why all curves without self-intersections and contiguities that are a constituent part of detail boundaries may be interpreted as edges of the plane graph G, and all points of intersection and contiguity may be interpreted as vertices of the graph G. Up to homeomorphism, plane graph G can be represented by a list of edges e∈E(G)$ e\in E(G) $ with incident vertices v1(e),v2(e)$ v_1(e),\, v_2(e) $ and faces f1(e),f2(e)$ f_1(e),\, f_2(e) $. This allows the restrictions of the planed cutter trajectory to be formalised in terms of graph theory. A series of algorithms for constructing the permitted route in the plane graph G as an image of the cutting plan is suggested. The constructed route for the graph G can be interpreted as a tool trajectory for the cutting plan which is the inverse image of graph G.
Journal: International Journal of Production Research
Pages: 1171-1188
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1401746
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401746
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Template-Type: ReDIF-Article 1.0
Author-Name: Chandra Ade Irawan
Author-X-Name-First: Chandra Ade
Author-X-Name-Last: Irawan
Author-Name: Negar Akbari
Author-X-Name-First: Negar
Author-X-Name-Last: Akbari
Author-Name: Dylan F. Jones
Author-X-Name-First: Dylan F.
Author-X-Name-Last: Jones
Author-Name: David Menachof
Author-X-Name-First: David
Author-X-Name-Last: Menachof
Title: A combined supply chain optimisation model for the installation phase of offshore wind projects
Abstract: 
 This paper proposes a combined model for port selection and supply chain optimisation for the installation phase of an offshore wind farm. Two strategic models are proposed where the first model, based on Analytical Hierarchy Process (AHP), aims to select the most suitable installation port. The second model is developed using Integer Linear Programming (ILP) in order to determine the optimal transportation schedule of the components from suppliers to the chosen installation port. The proposed models are evaluated for the West Gabbard (UK) offshore wind farm located in southern part of the North Sea. According to the computational results, the AHP model chooses port of Oostende, Belgium as the most suitable installation port for this offshore wind farm whereas the proposed supply chain model shows that the total transportation cost makes up 9% of total supply chain cost.
Journal: International Journal of Production Research
Pages: 1189-1207
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1403661
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1403661
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1189-1207




Template-Type: ReDIF-Article 1.0
Author-Name: Antonio Casimiro Caputo
Author-X-Name-First: Antonio Casimiro
Author-X-Name-Last: Caputo
Author-Name: Pacifico Marcello Pelagagge
Author-X-Name-First: Pacifico Marcello
Author-X-Name-Last: Pelagagge
Author-Name: Paolo Salini
Author-X-Name-First: Paolo
Author-X-Name-Last: Salini
Title: Selection of assembly lines feeding policies based on parts features and scenario conditions
Abstract: 
 This paper explores the impact of parts features, i.e. unit size and cost, as well as scenario variables on the total delivery cost of materials to assembly lines workstations, according to different materials feeding processes (kitting, line storage and just-in-time delivery). After building cost models based on parts features explicitation, a sensitivity and parametric analysis is carried out in order to justify the cost-effectiveness of each feeding policy and understand whether economic break-even points exist among available feeding alternatives on the basis of the values assumed by relevant attributes of parts. This allows to map areas where each feeding policy is more convenient and also allows a quick method to choose the best feeding policy for each part on an economic basis.
Journal: International Journal of Production Research
Pages: 1208-1232
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1407882
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1407882
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1208-1232




Template-Type: ReDIF-Article 1.0
Author-Name: Tarik Zouadi
Author-X-Name-First: Tarik
Author-X-Name-Last: Zouadi
Author-Name: Alice Yalaoui
Author-X-Name-First: Alice
Author-X-Name-Last: Yalaoui
Author-Name: Mohamed Reghioui
Author-X-Name-First: Mohamed
Author-X-Name-Last: Reghioui
Title: Hybrid manufacturing/remanufacturing lot-sizing and supplier selection with returns, under carbon emission constraint
Abstract: 
 This paper addresses a lot-sizing problem in manufacturing/remanufacturing systems. The studied system is a single manufacturing line where both regular manufacturing and returns remanufacturing processes are carried out, with different set-up costs for each process. We consider also a returns collection phase from customers/distributors with deterministic returns quantities at each period of the planning horizon. The environmental aspect is assumed in this study by considering a carbon emission constraint for the manufacturing, remanufacturing and transportation activities. A mixed integer programming model to minimise the management cost and meet the customer’s needs under different manufacturing constraints is proposed. Otherwise, An adaptation of the well-known Silver and Meal (SM) heuristic and two hybrid method approaches (HM1 and HM2) providing approximates solutions are developed. The mixed integer model was tested on Cplex (Software optimizer), and the obtained results were compared with the ones provided by the adapted heuristic SM and the hybrid methods. The numerical analyses show that hybrid methods provide good-quality solutions in a moderate computational time. The proposed model establishes a collegial and an integrated process that sets values, goals, decisions and priorities along the considered supply chain while taking into account the environmental aspect.
Journal: International Journal of Production Research
Pages: 1233-1248
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1412524
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412524
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Template-Type: ReDIF-Article 1.0
Author-Name: Elisa Gebennini
Author-X-Name-First: Elisa
Author-X-Name-Last: Gebennini
Author-Name: Luca Zeppetella
Author-X-Name-First: Luca
Author-X-Name-Last: Zeppetella
Author-Name: Andrea Grassi
Author-X-Name-First: Andrea
Author-X-Name-Last: Grassi
Author-Name: Bianca Rimini
Author-X-Name-First: Bianca
Author-X-Name-Last: Rimini
Title: Optimal job assignment considering operators’ walking costs and ergonomic aspects
Abstract: 
 The paper deals with the problem of assigning jobs to operators in contexts where the operators are not fixed on a single position, but rotate, by travelling on foot, between different stations. The objective is to jointly consider the need for minimising the operators’ walking costs, expressed as both unproductive times and physiological costs, and the ergonomic risk of the scheduled jobs and their combinations. A new optimisation-based methodology is presented by developing a systematic procedure for input data analysis and an original mixed-integer linear programming model which minimises the cost of walking (or the total metabolic cost) by considering workplace safety and physiological needs. Finally, the proposed optimisation approach has been applied to a case study from the plastic industry. The obtained results allow to draw some interesting conclusions about the impact of ergonomic aspects on the optimal assignment of jobs to operators. Moreover, the importance of reducing unproductive times (i.e. walking times) and, if possible, improving the design of manual tasks (e.g. lifting operations) is highlighted by showing that even small ergonomic investments may lead to significant cost savings.
Journal: International Journal of Production Research
Pages: 1249-1268
Issue: 3
Volume: 56
Year: 2018
Month: 2
X-DOI: 10.1080/00207543.2017.1414327
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1414327
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Template-Type: ReDIF-Article 1.0
Author-Name: Chenglong Li
Author-X-Name-First: Chenglong
Author-X-Name-Last: Li
Author-Name: Amitava Mukherjee
Author-X-Name-First: Amitava
Author-X-Name-Last: Mukherjee
Author-Name: Qin Su
Author-X-Name-First: Qin
Author-X-Name-Last: Su
Author-Name: Min Xie
Author-X-Name-First: Min
Author-X-Name-Last: Xie
Title: Optimal design of a distribution-free quality control scheme for cost-efficient monitoring of unknown location
Abstract: 
 Traditionally, a cost-efficient control chart for monitoring product quality characteristic is designed using prior knowledge regarding the process distribution. In practice, however, the functional form of the underlying process distribution is rarely known a priori. Therefore, the nonparametric (distribution-free) charts have gained more attention in the recent years. These nonparametric schemes are statistically designed either with a fixed in-control average run length or a fixed false alarm rate. Robust and cost-efficient designs of nonparametric control charts especially when the true process location parameter is unknown are not adequately addressed in literature. For this purpose, we develop an economically designed nonparametric control chart for monitoring unknown location parameter. This work is based on the Wilcoxon rank sum (hereafter WRS) statistic. Some exact and approximate procedures for evaluation of the optimal design parameters are extensively discussed. Simulation results show that overall performance of the exact procedure based on bootstrapping is highly encouraging and robust for various continuous distributions. An approximate and simplified procedure may be used in some situations. We offer some illustration and concluding remarks.
Journal: International Journal of Production Research
Pages: 7259-7273
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1173254
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173254
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Template-Type: ReDIF-Article 1.0
Author-Name: Mansour Rached
Author-X-Name-First: Mansour
Author-X-Name-Last: Rached
Author-Name: Zied Bahroun
Author-X-Name-First: Zied
Author-X-Name-Last: Bahroun
Author-Name: Jean-Pierre Campagne
Author-X-Name-First: Jean-Pierre
Author-X-Name-Last: Campagne
Title: Decentralised decision-making with information sharing vs. centralised decision-making in supply chains
Abstract: 
 In recent years, implementing coordination mechanisms in decentralised supply chains to reduce the well-known negative effects of decentralisation, such as the ‘bullwhip effect’, has become a considerable challenge. Furthermore, with the dramatic developments in information and communication technologies, real-time information sharing has become increasingly easier to implement. In this work, we study a mono-product divergent supply chain composed of a supplier, a warehouse, retailers and customers in the context of decentralised and centralised decisions. The main objective of this study is to compare a decentralised supply chain combined with different scenarios of simultaneous upstream and downstream information sharing vs. a centralised supply chain. A mathematical model is developed to compare the logistics costs in the two decision contexts. The experimental results clearly show that the simultaneous sharing of customer demand and supplier-warehouse lead time information in a decentralised supply chain yields nearly equivalent logistics costs as the centralised supply chain context. However, the main beneficiary of the sharing is the warehouse, which receives approximately two-thirds of the benefit. Thus, incentives and revenue sharing contracts should be implemented to motivate and balance the benefits between supply chain partners.
Journal: International Journal of Production Research
Pages: 7274-7295
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1173255
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173255
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Template-Type: ReDIF-Article 1.0
Author-Name: S. Moodleah
Author-X-Name-First: S.
Author-X-Name-Last: Moodleah
Author-Name: E.J. Bohez
Author-X-Name-First: E.J.
Author-X-Name-Last: Bohez
Author-Name: S.S. Makhanov
Author-X-Name-First: S.S.
Author-X-Name-Last: Makhanov
Title: Five-axis machining of STL surfaces by adaptive curvilinear toolpaths
Abstract: 
 We propose a new framework for toolpath generation for five-axis machining of part surfaces represented by the StereoLithography (STL) format. The framework is based on flattening the STL part and generation of adaptive curvilinear toolpaths. The corresponding cost functions, designed to represent the accuracy and the efficiency of the toolpath, are scalar functions, such as the curvature, kinematic error, rotation angles, machining strip or material removal rate or a vector field when the tool moves along a curvilinear path partly or even entirely aligned with directions considered to be optimal. The adaptive toolpath exploits grid generation methods and biased space-filling curves, combined with adaptation to the boundary and the domain decomposition. The proposed methodology of the adaptive curvilinear toolpath (ACT) has been tested on a variety of STL surfaces, including a case study of STL dental parts. Machining crowns/implants for four basic types of human teeth, molar, premolar, canine and incisor, has been considered and analysed. The reference methods are the standard iso-parametric path, MasterCam toolpath, and advanced methods of NX9 (former UG). The experiments show that there is no universal sequence of steps applicable to every surface. However, a correct choice of the tools available within the proposed ACT-framework always leads to a substantial improvement of the toolpath, in terms of its length and the machining time.
Journal: International Journal of Production Research
Pages: 7296-7329
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1176265
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1176265
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Template-Type: ReDIF-Article 1.0
Author-Name: Ana Vafadar
Author-X-Name-First: Ana
Author-X-Name-Last: Vafadar
Author-Name: Majid Tolouei-Rad
Author-X-Name-First: Majid
Author-X-Name-Last: Tolouei-Rad
Author-Name: Kevin Hayward
Author-X-Name-First: Kevin
Author-X-Name-Last: Hayward
Title: New cost model for feasibility analysis of utilising special purpose machine tools
Abstract: 
 Special purpose machine tools (SPMs) have been widely used to perform drilling-related operations in high volume production including within automotive component industries. The first step in designing and manufacturing a SPM is a feasibility analysis. Since SPMs have relatively higher investment cost than other machine tools, this task must be performed before any investment on the preparation of detailed design. The present paper explores an economic feasibility analysis strategy which aims to make logical decision by assessing the strengths and limitations of an SPM in comparison with other machine tools. The mathematical product cost model for SPMs is proposed for estimating important economic factors and then financial indicators are calculated to evaluate the SPM’s economic performance. A case study is used to examine the proposed model and results are compared with other machine tools. The proposed model provides a decision support approach for selecting an SPM for manufacturing a given part from an economic perspective.
Journal: International Journal of Production Research
Pages: 7330-7344
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1181283
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1181283
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:24:p:7330-7344




Template-Type: ReDIF-Article 1.0
Author-Name: Nicola Bateman
Author-X-Name-First: Nicola
Author-X-Name-Last: Bateman
Author-Name: Lee Philp
Author-X-Name-First: Lee
Author-X-Name-Last: Philp
Author-Name: Harry Warrender
Author-X-Name-First: Harry
Author-X-Name-Last: Warrender
Title: Visual management and shop floor teams – development, implementation and use
Abstract: 
 This research investigates the use of visual management, specifically communications boards in a British lock manufacturing company. The research explores the design, implementation and use of communications boards over two years. The purpose of the research was to bring design principles from the graphic design and cognitive psychology into a previously informal process and to develop Visual Management (VM) principles to guide the design of the board. The research findings have acted as a proof of process for the introduction of VM theory into the design of communications boards and provide evidence that the VM principles improved the design of the board. This enabled Team Leaders to better engage in problem-solving and continuous improvement with their teams.
Journal: International Journal of Production Research
Pages: 7345-7358
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1184349
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1184349
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcos Calle
Author-X-Name-First: Marcos
Author-X-Name-Last: Calle
Author-Name: Pedro L. González-R
Author-X-Name-First: Pedro L.
Author-X-Name-Last: González-R
Author-Name: Henri Pierreval
Author-X-Name-First: Henri
Author-X-Name-Last: Pierreval
Title: Impact of the customer demand on order fulfilment strategies based on floating decoupling point: a simulation analysis
Abstract: 
 Order Fulfilment Strategies have become more and more popular, thanks to their capability of improving the delivery times and reducing the inventory levels. Among the postponement strategies of Mass Customisation are the Virtual Build-To-Order (VBTO) and i-Virtual Build-To-Order (i-VBTO) systems which are two systems with the ability to serve customers from anywhere in the inventory (Work-in-Process and Finished Goods Inventory) showing an interesting potential of adaptation to the variability of the demand. This study is aimed at testing the suitability of the basis of the i-VBTO system against the VBTO system through the study of the influence of characteristics of demand that are common in real environments. Regarding the contribution of this work, some weaknesses of the VBTO system can be highlighted (e.g. under certain demand conditions it loses the efficiency), and some benefits of the i-VBTO system (e.g. it turns out to be more robust and stable regarding changes in demand than the VBTO system).
Journal: International Journal of Production Research
Pages: 7359-7373
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1186295
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1186295
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Template-Type: ReDIF-Article 1.0
Author-Name: Vishal Ashok Bhosale
Author-X-Name-First: Vishal Ashok
Author-X-Name-Last: Bhosale
Author-Name: Ravi Kant
Author-X-Name-First: Ravi
Author-X-Name-Last: Kant
Title: An integrated ISM fuzzy MICMAC approach for modelling the supply chain knowledge flow enablers
Abstract: 
 The aim of this study is to identify supply chain knowledge flow enablers (SCKFEs) to inspect interrelationships among these enablers and classify these enablers into driving power and dependence power using an integrated interpretive structural modelling (ISM) and fuzzy Matriced Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) methodology. While the ISM methodology analyses the interactions among the SCKFEs, fuzzy MICMAC analysis is employed to obtain insights into the dependencies among the SCKFEs. A total of 34 SCKFEs were identified through the literature review and expert opinion. As an example, an Indian manufacturing organisation is selected that is willing to adopt the successful knowledge flow for improving supply chain (SC) performance to overcome the intense competition among the SC versus SC. The research shows SCKFEs having high driving power and low dependence have strategic importance because of their driving nature, while the SCKFEs having high dependence and low driving power are more performance orientated. Therefore, it is the responsibility of SC executives to address the high driving power SCKFEs for the enhancement of SC performance. This categorisation provides a useful tool to top management to differentiate between independent and dependent SCKFEs and their mutual relationships, helping them focus on those key SCKFEs that are most significant. This gives a clear picture to SC practitioners and decision-makers about number of SCKFEs, interrelationship and dependencies existing among them.
Journal: International Journal of Production Research
Pages: 7374-7399
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1189102
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1189102
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Template-Type: ReDIF-Article 1.0
Author-Name: Thawatchai Jitpaiboon
Author-X-Name-First: Thawatchai
Author-X-Name-Last: Jitpaiboon
Author-Name: Qiannong Gu
Author-X-Name-First: Qiannong
Author-X-Name-Last: Gu
Author-Name: Dothang Truong
Author-X-Name-First: Dothang
Author-X-Name-Last: Truong
Title: Evolution of competitive priorities towards performance improvement: a meta-analysis
Abstract: 
 Competitive priorities are critical operational dimensions that a business process must possess to satisfy its internal and external customers. The process of defining competitive priorities is evolving and changing over time according to a new business paradigm. Therefore, it is the right time to revisit the critical dimensions of competitive priority. The purpose of this study is threefold: (1) to identify and revise the critical dimensions of competitive priority; (2) to assess the quality of competitive priority measures across studies based on different criteria; (3) to confirm the relationship between several competitive priorities and organisational performance. The results show the different effects that competitive priorities have on organisational performance. Cost and quality priorities show evidence of strong effect size compared to the others.
Journal: International Journal of Production Research
Pages: 7400-7420
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1190878
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1190878
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Handle: RePEc:taf:tprsxx:v:54:y:2016:i:24:p:7400-7420




Template-Type: ReDIF-Article 1.0
Author-Name: C.L. Hu
Author-X-Name-First: C.L.
Author-X-Name-Last: Hu
Author-Name: X. Liu
Author-X-Name-First: X.
Author-X-Name-Last: Liu
Author-Name: Y.K. Hua
Author-X-Name-First: Y.K.
Author-X-Name-Last: Hua
Title: A bi-objective robust model for emergency resource allocation under uncertainty
Abstract: 
 Emergency resource allocation constitutes one of the most critical elements of response operations in the field of emergency management. This paper addresses an emergency resource allocation problem which involves multiple competing affected areas and one relief resource centre under supply shortage and uncertainty in the post-disaster phase. In humanitarian situations, both the efficiency and fairness of an allocation policy have a considerable influence on the effectiveness of emergency response operations. Thus, we formulate a bi-objective robust emergency resource allocation (BRERA) model which tries to maximise efficiency as well as fairness under different sources of uncertainties. To obtain decision-makers’ most preferred allocation policy, we propose a novel emergency resource allocation decision method which consists of three steps: (1) develop a bi-objective heuristic particle swarm optimisation algorithm to search the Pareto frontier of the BRERA model; (2) select a coefficient to measure fairness; and (3) establish a decision method based on decision-makers’ preference restricted by the fairness coefficient. Finally, a real case study taken from the 5 December 2008 Wenchuan Earthquake demonstrates the effectiveness of the proposed method through numerical results. The solution and model robustness are also analysed.
Journal: International Journal of Production Research
Pages: 7421-7438
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1191692
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1191692
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Template-Type: ReDIF-Article 1.0
Author-Name: C. Vasanthakumar
Author-X-Name-First: C.
Author-X-Name-Last: Vasanthakumar
Author-Name: S. Vinodh
Author-X-Name-First: S.
Author-X-Name-Last: Vinodh
Author-Name: K. Ramesh
Author-X-Name-First: K.
Author-X-Name-Last: Ramesh
Title: Application of interpretive structural modelling for analysis of factors influencing lean remanufacturing practices
Abstract: 
 The contemporary manufacturing scenario witnesses the adoption of lean remanufacturing concepts in a concerted manner. Lean remanufacturing is a newly evolved manufacturing process concerned with manufacturing and remanufacturing of products to effectively utilise available energy and resources, while reducing wastes in the process and thereby increasing efficiency. The advantages include process streamlining coupled with end-of-life decisions. A structural model needs to be developed to clarify the interrelationships among factors influencing lean remanufacturing practices. In this study, interpretive structural modelling method has been used to develop the structural model depicting interrelationships and most dominant and least dominant factors. Twenty factors are being identified based on expert opinion from 35 Indian automotive component remanufacturing organisations. The identified most dominant factors include a strong top management commitment with proper strategy selection, long-term vision and participation and a strong understanding of the current product and process designs. MICMAC analysis has been conducted to categorise the factors. The inferences based on the study have been derived. The novel aspect of this study is that it presents the development of structural model to identify the most dominant factors influencing the implementation of lean remanufacturing principles.
Journal: International Journal of Production Research
Pages: 7439-7452
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1192300
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1192300
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Template-Type: ReDIF-Article 1.0
Author-Name: Der-Chiang Li
Author-X-Name-First: Der-Chiang
Author-X-Name-Last: Li
Author-Name: I-Hsiang Wen
Author-X-Name-First: I-Hsiang
Author-X-Name-Last: Wen
Author-Name: Wen-Chih Chen
Author-X-Name-First: Wen-Chih
Author-X-Name-Last: Chen
Title: A novel data transformation model for small data-set learning
Abstract: 
 In most highly competitive manufacturing industries, the sample sizes are usually very small in pilot runs, in order to quickly launch new products. However, it is always difficult for engineers to improve the quality in mass production runs based on the limited data obtained in this way. Past research has demonstrated that adding artificial samples can be an effective approach when learning with small data-sets. However, a prior analysis of the data is needed to deduce the appropriate sample distributions within which the artificial samples are generated. Johnson transformation is one of the well-known models that can be applied to bring data close to a normal distribution with the satisfaction of certain statistical assumptions. The sample size required for such data transformation methods is usually large, and this thus motivates the efforts of the current study to develop a new method which is suitable for small data-sets. Accordingly, this research proposes the small Johnson Data Transformation method to transform small raw data to normal distributions to generate virtual samples. When compared with four other methods, the results obtained with a real small data-set drawn from the Film Transistor Liquid Crystal Display industry in Taiwan demonstrate that the proposed method is able to effectively improve the forecasting ability with small sample sizes.
Journal: International Journal of Production Research
Pages: 7453-7463
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1192301
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1192301
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Template-Type: ReDIF-Article 1.0
Author-Name: Rob Goedhart
Author-X-Name-First: Rob
Author-X-Name-Last: Goedhart
Author-Name: Marit Schoonhoven
Author-X-Name-First: Marit
Author-X-Name-Last: Schoonhoven
Author-Name: Ronald J.M.M. Does
Author-X-Name-First: Ronald J.M.M.
Author-X-Name-Last: Does
Title: Correction factors for Shewhart  and  control charts to achieve desired unconditional ARL
Abstract: 
 In this paper we derive correction factors for Shewhart control charts that monitor individual observations as well as subgroup averages. In practice, the distribution parameters of the process characteristic of interest are unknown and, therefore, have to be estimated. A well-known performance measure within Statistical Process Monitoring is the expectation of the average run length (ARL), defined as the unconditional ARL. A practitioner may want to design a control chart such that, in the in-control situation, it has a certain expected ARL. However, accurate correction factors that lead to such an unconditional ARL are not yet available. We derive correction factors that guarantee a certain unconditional in-control ARL. We use approximations to derive the factors and show their accuracy and the performance of the control charts – based on the new factors – in out-of-control situations. We also evaluate the variation between the ARLs of the individually estimated control charts.
Journal: International Journal of Production Research
Pages: 7464-7479
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1193251
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193251
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Template-Type: ReDIF-Article 1.0
Author-Name: Laureen Grandguillaume
Author-X-Name-First: Laureen
Author-X-Name-Last: Grandguillaume
Author-Name: Sylvain Lavernhe
Author-X-Name-First: Sylvain
Author-X-Name-Last: Lavernhe
Author-Name: Christophe Tournier
Author-X-Name-First: Christophe
Author-X-Name-Last: Tournier
Title: A tool path patching strategy around singular point in 5-axis ball-end milling
Abstract: 
 In 5-axis high-speed milling, large incoherent movements of rotary axes around the singular point are known to be a problem. Correction methods found in the literature deal mostly with the collision that may happen between the tool and the part but not with the feedrate slowdowns which affect surface quality and machining productivity. The method proposed in this paper addresses both geometrical and productivity issues by modifying the tool axes orientation while respecting maximum velocity, acceleration and jerk of the machine tool axes. The aim is to detect these behaviours and replace the considered portion of the tool path by a patch curve respecting kinematical constraints of the machine tool. Compared to previous works, the inserted patch curve is not constrained to pass through the singularity but respect tangential constraints to ensure the monotony of the tool path and is also connected with the rest of the tool path to ensure a continuity up to the third derivative in order to fulfil jerk limitations. For that purpose, the initial articular positions of the rotary axes around the singular point are fitted with B-spline curves, modified and finally discretised for linear interpolation. Experimental investigations on a test part are carried out to show the efficiency of the method in terms of feedrate and surface quality.
Journal: International Journal of Production Research
Pages: 7480-7490
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1196835
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1196835
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Template-Type: ReDIF-Article 1.0
Author-Name: Mou-Yuan Liao
Author-X-Name-First: Mou-Yuan
Author-X-Name-Last: Liao
Title: Markov chain Monte Carlo in Bayesian models for testing gamma and lognormal S-type process qualities
Abstract: 
 The process capability index Cpu is widely used to measure S-type process quality. Many researchers have presented adaptive techniques for assessing the true Cpu assuming normality. However, the quality characteristic is often abnormal, and the derived techniques based on the normality assumption could mislead the manager into making uninformed decisions. Therefore, this study provides an alternative method for assessing Cpu of non-normal processes. The Markov chain Monte Carlo, an emerging popular statistical tool, is integrated into Bayesian models to seek the empirical posterior distributions of specific gamma and lognormal parameters. Afterwards, the lower credible interval bound of Cpu can be derived for testing the non-normal process quality. Simulations show that the proposed method is adaptive and has good performance in terms of coverage probability.
Journal: International Journal of Production Research
Pages: 7491-7503
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1198055
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1198055
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Template-Type: ReDIF-Article 1.0
Author-Name: K.P. Tran
Author-X-Name-First: K.P.
Author-X-Name-Last: Tran
Author-Name: P. Castagliola
Author-X-Name-First: P.
Author-X-Name-Last: Castagliola
Author-Name: G. Celano
Author-X-Name-First: G.
Author-X-Name-Last: Celano
Title: The performance of the Shewhart-RZ control chart in the presence of measurement error
Abstract: 
 Recent literature about quality control has investigated the continuous surveillance of the ratio of two normal random variables under the assumption of no measurement error. However, in practice, measurement errors always exist in quality control applications and may considerably affect the performance of control charts. In this paper, the performance of the Shewhart-RZ control chart is investigated in the presence of a measurement error and modelled by a linear covariate error model. Several figures and tables are generated and commented to show the statistical performance of the Shewhart-RZ control chart for different sources of the measurement error. Two examples illustrate the use of this chart on a quality control problem simulated from the food industry and a real industrial case from a plant treating batteries for recyclement.
Journal: International Journal of Production Research
Pages: 7504-7522
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1198507
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1198507
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Template-Type: ReDIF-Article 1.0
Author-Name: Moacir Godinho Filho
Author-X-Name-First: Moacir
Author-X-Name-Last: Godinho Filho
Author-Name: Gilberto Miller Devós Ganga
Author-X-Name-First: Gilberto Miller Devós
Author-X-Name-Last: Ganga
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Title: Lean manufacturing in Brazilian small and medium enterprises: implementation and effect on performance
Abstract: 
 The main objective of this paper is to investigate the degree to which lean manufacturing (LM) practices are being implemented within Brazilian small and medium enterprises (SMEs), by defining what LM means, in the view of SMEs in Brazil. In addition, the paper investigates the relationship between LM implementation and performance of such companies. The research method used in this paper comprised of an exploratory survey using the partial least-square method with the structural equation modelling technique (PLS-SEM). The results show that the companies studied used practices in a fragmented manner, without a holistic view of LM, which is considered to be one of the most important parts of this approach. Only the constructs of statistical process control, total productive maintenance and employee involvement are being implemented as an integrated approach for Brazilian SMEs. These companies do not take other important constructs such as customer involvement, continuous flow, pull production, set-up time reduction, supplier development and supplier feedback into consideration as part of LM systems, despite using some practices in a dispersed manner. Concerning performance, the present study shows that even in a fragmented way, the implementation of these LM practices help these companies to achieve improvement in operational performance.
Journal: International Journal of Production Research
Pages: 7523-7545
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1201606
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1201606
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Editorial Board
Journal: International Journal of Production Research
Pages: (ebi)-(ebi)
Issue: 24
Volume: 54
Year: 2016
Month: 12
X-DOI: 10.1080/00207543.2016.1254947
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1254947
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Template-Type: ReDIF-Article 1.0
Author-Name: Yingcong Wang
Author-X-Name-First: Yingcong
Author-X-Name-Last: Wang
Author-Name: Renbin Xiao
Author-X-Name-First: Renbin
Author-X-Name-Last: Xiao
Author-Name: Huimin Wang
Author-X-Name-First: Huimin
Author-X-Name-Last: Wang
Title: A flexible labour division approach to the polygon packing problem based on space allocation
Abstract: 
 This paper deals with the two-dimensional satellite module polygon packing problem. Based on the duality of material and space, it regards the polygon packing problem as a space allocation problem, which involves allocating the container space to the given polygons reasonably and efficiently. Ant colony’s labour division is essentially a kind of task allocation. Using this task allocation to achieve the space allocation in polygon packing problems, a flexible labour division approach (FLD) is proposed based on the response threshold model. According to the characteristics of space allocation in polygon packing problems, FLD designs three actions for polygons to occupy the container space. With the interaction between environmental stimulus and response threshold, each polygon takes an appropriate action to complete the space allocation and a layout that meets the requirements of satellite module layout is obtained. The results of standard test instances demonstrate the effectiveness of FLD when compared with self-organisation emergence algorithm. Moreover, experiments on the general polygon packing problem also show that FLD is competitive with other existing algorithms.
Journal: International Journal of Production Research
Pages: 3025-3045
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1229070
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1229070
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Template-Type: ReDIF-Article 1.0
Author-Name: Pierre Baptiste
Author-X-Name-First: Pierre
Author-X-Name-Last: Baptiste
Author-Name: Reinhard Bürgy
Author-X-Name-First: Reinhard
Author-X-Name-Last: Bürgy
Author-Name: Alain Hertz
Author-X-Name-First: Alain
Author-X-Name-Last: Hertz
Author-Name: Djamal Rebaine
Author-X-Name-First: Djamal
Author-X-Name-Last: Rebaine
Title: Online heuristics for unloading boxes off a gravity conveyor
Abstract: 
 This paper addresses the problem of minimising the number of moves to unload a set of boxes off a gravity conveyor by a forklift. If the input data are known in advance, the problem is efficiently solvable with a dynamic programming approach. However, this method is rarely applicable in practice for two reasons. First, the problem generally occurs in a real-time environment where the input data are revealed over time. Second, computing devices are in most cases not available in forklifts or gravity conveyors for decision-making. Online approaches that can easily be applied by human operators are therefore sought in practice. With this in mind, we first propose some intuitive approaches and analyse their performance through an extensive experimental study. The results show that these approaches are quite inefficient as they average between 14.7 and 59.3% above the optimum. A less intuitive but still simple approach is then designed that consistently produces good results with an average gap of 6.1% to the optimum.
Journal: International Journal of Production Research
Pages: 3046-3057
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1229073
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1229073
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Template-Type: ReDIF-Article 1.0
Author-Name: Huasheng Yang
Author-X-Name-First: Huasheng
Author-X-Name-Last: Yang
Author-Name: Vincent Low
Author-X-Name-First: Vincent
Author-X-Name-Last: Low
Author-Name: Canrong Zhang
Author-X-Name-First: Canrong
Author-X-Name-Last: Zhang
Author-Name: Li Zheng
Author-X-Name-First: Li
Author-X-Name-Last: Zheng
Author-Name: Lixin Miao
Author-X-Name-First: Lixin
Author-X-Name-Last: Miao
Title: Behaviour perception-based disruption models for the parallel machine capacitated lot-sizing and scheduling problem
Abstract: 
 Capacitated lot-sizing and scheduling problem under disruption environment is a frequently encountered problem in manufacturing industry. This paper focuses on dealing with the case that the disruption is caused by machine breakdowns. Such case frequently arises during the process of the execution of a planned schedule. As a result, a reschedule needs to be applied, and then the decision-maker naturally may compare the reschedule results with the original one. Rather than from the conventional cost-saving perspective, this paper makes comparison from the attitude or the human behaviour perception of decision-makers towards the deviation from the original schedule. A non-linear mixed integer programming model is constructed with the objective of minimising the negative deviation based on the Prospect Theory, a psychologically more accurate description of decision-making. The non-linear term introduced by the Prospect Theory is approximately linearised by a series of piecewise linear segments. Then, an MIP-based fix-and-optimise algorithm is proposed to solve the approximated MIP problem. In numerical experiments, the impacts of several key factors of the proposed model and algorithm are explored. Two adjustment policies are compared, and the trade-off between cost saving and minimisation of the human behaviour perception deviation of decision-makers is discussed as well.
Journal: International Journal of Production Research
Pages: 3058-3072
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1234083
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1234083
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Template-Type: ReDIF-Article 1.0
Author-Name: Guo-Sheng Liu
Author-X-Name-First: Guo-Sheng
Author-X-Name-Last: Liu
Author-Name: Hai-Dong Yang
Author-X-Name-First: Hai-Dong
Author-X-Name-Last: Yang
Author-Name: Ming-Bao Cheng
Author-X-Name-First: Ming-Bao
Author-X-Name-Last: Cheng
Title: A three-stage decomposition approach for energy-aware scheduling with processing-time-dependent product quality
Abstract: 
 Due to increasing concerns about energy and environmental demands, decision-makers in industrial companies have developed awareness about energy use and energy efficiency when engaging in short-term production scheduling and planning. This paper studied a flow-shop scheduling problem consisting of a series of processing stages and one final quality check stage with the aim of minimising energy consumption. In particular, the product quality in the problem depends on its processing time at each stage, and the energy consumption is related to the processing speed, equipment state and product quality. A novel three-stage decomposition approach is presented to solve the proposed energy-aware scheduling (EAS) problem. The decomposition approach can drastically reduce the search space and provide reliable solutions for the EAS problem. The numerical experiments show that the computational results can achieve an optimality gap of less than 4% when compared to the global optimal solutions. The parameter analysis demonstrates the managerial implications of the proposed problem. For example, increasing the number of alternative processing speeds or relaxing the delivery date will increase energy efficiency. The energy-saving potential is illustrated by comparing the scheduling results using the proposed approach and human experience.
Journal: International Journal of Production Research
Pages: 3073-3091
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1241446
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1241446
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Template-Type: ReDIF-Article 1.0
Author-Name: Dae-Kyu Kim
Author-X-Name-First: Dae-Kyu
Author-X-Name-Last: Kim
Author-Name: Hyun-Jung Kim
Author-X-Name-First: Hyun-Jung
Author-X-Name-Last: Kim
Author-Name: Tae-Eog Lee
Author-X-Name-First: Tae-Eog
Author-X-Name-Last: Lee
Title: Optimal scheduling for sequentially connected cluster tools with dual-armed robots and a single input and output module
Abstract: 
 We examine a cyclic scheduling problem of sequentially connected cluster tools with a single input and output module, which includes multi-cluster tools and linear cluster tools. Every component tool has a dual-armed robot, and chambers are parallelised for a long process step. An intermediate buffer between each pair of adjacent component tools has a limited capacity, and all processed wafers should return to the input and output module. To examine the scheduling problem, we first compute workloads of the process steps and robots to obtain a lower bound on the tool cycle time. We then identify a rule of assigning the chambers to the process steps that makes the tool cycle time independent of the order of using the parallel chambers. We also propose a simple robot task sequence which is modified from the well-known swap sequence for each component tool. We prove that the modified swap sequence is optimal when one of the process steps, not a robot, is the bottleneck. We also present a scheduling strategy which controls robot task timings to deal with interference of wafer flows between each pair of adjacent component tools. Finally, we perform numerical experiments to show the performance of the proposed sequence.
Journal: International Journal of Production Research
Pages: 3092-3109
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1243819
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1243819
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei Li
Author-X-Name-First: Wei
Author-X-Name-Last: Li
Author-Name: Theodor Freiheit
Author-X-Name-First: Theodor
Author-X-Name-Last: Freiheit
Author-Name: Enming Miao
Author-X-Name-First: Enming
Author-X-Name-Last: Miao
Title: A lever concept integrated with simple rules for flow shop scheduling
Abstract: 
 The development of more efficient and better performing priority dispatching rules (PDRs) for production scheduling is relevant to modern flow shop scheduling practice because they are simple, easy to apply and have low computational complexity, especially for large-scale problems. While the current research trend in scheduling is towards finding superior solutions through meta-heuristics, they are computationally expensive and many meta-heuristics also use PDRs to generate starting points. In this paper, we analyse the properties of flow shop scheduling problems to minimise maximum completion time, and generate a new dominance rule that is complementary to Szwarc’s rule. These dominance rules indicate that a weighting factor should be included in sequencing to account for the possibility that a single job’s processing time can generate idle time repeatedly within a flow line. Two new PDRs with a leveraged weighting factor are proposed to minimise makespan and average completion time. Computational results on Taillard’s benchmark problems and on historical operating room data show that the proposed PDRs perform much better than established PDRs without an increase in computational complexity.
Journal: International Journal of Production Research
Pages: 3110-3125
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1246762
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1246762
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Template-Type: ReDIF-Article 1.0
Author-Name: Deming Lei
Author-X-Name-First: Deming
Author-X-Name-Last: Lei
Author-Name: Youlian Zheng
Author-X-Name-First: Youlian
Author-X-Name-Last: Zheng
Author-Name: Xiuping Guo
Author-X-Name-First: Xiuping
Author-X-Name-Last: Guo
Title: A shuffled frog-leaping algorithm for flexible job shop scheduling with the consideration of energy consumption
Abstract: 
 Flexible job shop scheduling problem (FJSP) has been extensively investigated and objectives are often related to time. Energy-related objective should be considered fully in FJSP with the advent of green manufacturing. In this study, FJSP with the minimisation of workload balance and total energy consumption is considered and the conflicting between two objectives is analysed. A shuffled frog-leaping algorithm (SFLA) is proposed based on a three-string coding approach. Population and a non-dominated set are used to construct memeplexes according to tournament selection and the search process of each memeplex is done on its non-dominated member. Extensive experiments are conducted to test the search performance of SFLA and computational results show the conflicting between two objectives of FJSP and the promising advantages of SFLA on the considered FJSP.
Journal: International Journal of Production Research
Pages: 3126-3140
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1262082
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1262082
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhenyou Wang
Author-X-Name-First: Zhenyou
Author-X-Name-Last: Wang
Author-Name: Cai-Min Wei
Author-X-Name-First: Cai-Min
Author-X-Name-Last: Wei
Author-Name: Linhui Sun
Author-X-Name-First: Linhui
Author-X-Name-Last: Sun
Title: Solution algorithms for the number of tardy jobs minimisation scheduling with a time-dependent learning effect
Abstract: 
 This paper deals with a single-machine scheduling problem with a time-dependent learning effect. The goal is to determine the job sequence that minimise the number of tardy jobs. Two dominance properties, two heuristic algorithms and a lower bound to speed up the search process of the branch-and-bound algorithm are proposed. Computational experiments show that the branch-and-bound algorithm can solve instances up to 18 jobs in a reasonable amount of time, and the proposed heuristic algorithm MFLA performs effectively and efficiently
Journal: International Journal of Production Research
Pages: 3141-3148
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1264642
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1264642
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Template-Type: ReDIF-Article 1.0
Author-Name: Chao-Tang Tseng
Author-X-Name-First: Chao-Tang
Author-X-Name-Last: Tseng
Author-Name: Cheng-Hsiung Lee
Author-X-Name-First: Cheng-Hsiung
Author-X-Name-Last: Lee
Author-Name: Yuan-Shyi Peter Chiu
Author-X-Name-First: Yuan-Shyi Peter
Author-X-Name-Last: Chiu
Author-Name: Wei-Te Lu
Author-X-Name-First: Wei-Te
Author-X-Name-Last: Lu
Title: A discrete electromagnetism-like mechanism for parallel machine scheduling under a grade of service provision
Abstract: 
 We consider the problem of minimising total weighted tardiness on identical parallel machines with grade of service eligibility. Due to the essential complexity of the problem, we apply an electromagnetism-like mechanism (EM), which is a novel metaheuristic, to solve the problem. In the proposed EM, the particle is redesigned to represent a valid assignment of jobs to machines. A distance measure between particles, called ‘1A2B’ distance, is proposed by the concept of a number guessing game. Then, the new attraction and repulsion operators are developed to move a particle to the new particle. To verify the proposed EM, computational experiments are conducted to make a comparison with a recent genetic algorithm (GA). The results show that the proposed EM has a good performance and outperforms the GA for the considered problem.
Journal: International Journal of Production Research
Pages: 3149-3163
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1265683
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1265683
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Template-Type: ReDIF-Article 1.0
Author-Name: Enrique Gerstl
Author-X-Name-First: Enrique
Author-X-Name-Last: Gerstl
Author-Name: Gur Mosheiov
Author-X-Name-First: Gur
Author-X-Name-Last: Mosheiov
Title: Single machine scheduling problems with generalised due-dates and job-rejection
Abstract: 
 We study single machine scheduling problems. Generalised due dates are assumed, i.e. job due dates are specified according to the positions of the jobs in the sequence, rather than their identity. Thus, assuming that due dates are numbered in a non-decreasing order, the jth due date refers to the job assigned to the jth position. In addition, we allow the option of job rejection, i.e. not all jobs must be processed. In this case, the scheduler is penalised for each rejected job, and the total rejection cost becomes part of the objective function. Two objective functions are considered: maximum tardiness plus rejection cost, and total tardiness plus rejection cost. Both problems are proved to be NP-hard. Pseudo-polynomial dynamic programmes and efficient heuristics are introduced and tested numerically.
Journal: International Journal of Production Research
Pages: 3164-3172
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1266055
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1266055
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Template-Type: ReDIF-Article 1.0
Author-Name: Sicheng Zhang
Author-X-Name-First: Sicheng
Author-X-Name-Last: Zhang
Author-Name: Tak Nam Wong
Author-X-Name-First: Tak Nam
Author-X-Name-Last: Wong
Title: Flexible job-shop scheduling/rescheduling in dynamic environment: a hybrid MAS/ACO approach
Abstract: 
 In real-world manufacturing, disruptions are often encountered during the execution of a predetermined schedule, leading to the degradation of its optimality and feasibility. This study presents a hybrid approach for flexible job-shop scheduling/rescheduling problems under dynamic environment. The approach, coined as ‘HMA’ is a combination of multi-agent system (MAS) negotiation and ant colony optimisation (ACO). A fully distributed MAS structure has been constructed to support the solution-finding process by negotiation among the agents. The features of ACO are introduced into the negotiation mechanism in order to improve the performance of the schedule. Experimental studies have been carried out to evaluate the performance of the approach for scheduling and rescheduling under different types of disruptions. Different rescheduling policies are compared and discussed. The results have shown that the proposed approach is a competitive method for flexible job-shop scheduling/rescheduling for both schedule optimality and computation efficiency.
Journal: International Journal of Production Research
Pages: 3173-3196
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1267414
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1267414
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianyu Long
Author-X-Name-First: Jianyu
Author-X-Name-Last: Long
Author-Name: Zhong Zheng
Author-X-Name-First: Zhong
Author-X-Name-Last: Zheng
Author-Name: Xiaoqiang Gao
Author-X-Name-First: Xiaoqiang
Author-X-Name-Last: Gao
Title: Dynamic scheduling in steelmaking-continuous casting production for continuous caster breakdown
Abstract: 
 In the steelmaking-continuous casting (SCC) production process, machine breakdown is one of the most common disturbances which may make the current schedule unrealisable. Existing rescheduling models for machine breakdown only employ one constraint that charges cannot be processed on this machine in its failure period. However, this method is effective for steelmaking furnace breakdown and refining furnace breakdown but invalid for continuous caster breakdown. Due to the production characteristics of continuous caster, reallocating a casting order and a continuous caster for each unfinished charge on the broken down continuous caster is necessary before making a new schedule. Different reallocation strategies have different impacts on charge’s processing time and processing stage route in the dynamic scheduling process. Therefore, SCC dynamic scheduling for the continuous caster breakdown is different from the other machines. In this paper, the impacts of these strategies are studied, and a dynamic scheduling model which can be used to generate a new schedule for each strategy is built. To obtain a high-quality solution in acceptable computational time for this model with NP-hard feature, a hybrid algorithm featuring a genetic algorithm combined with a general variable neighbourhood search is developed based on the problem-specific characteristics. Computational experiments on practical production data show that the proposed rescheduling method is effective for SCC dynamic scheduling with continuous caster breakdown.
Journal: International Journal of Production Research
Pages: 3197-3216
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1268277
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1268277
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Template-Type: ReDIF-Article 1.0
Author-Name: Cheng Zhang
Author-X-Name-First: Cheng
Author-X-Name-Last: Zhang
Author-Name: Zhongshun Shi
Author-X-Name-First: Zhongshun
Author-X-Name-Last: Shi
Author-Name: Zewen Huang
Author-X-Name-First: Zewen
Author-X-Name-Last: Huang
Author-Name: Yifan Wu
Author-X-Name-First: Yifan
Author-X-Name-Last: Wu
Author-Name: Leyuan Shi
Author-X-Name-First: Leyuan
Author-X-Name-Last: Shi
Title: Flow shop scheduling with a batch processor and limited buffer
Abstract: 
 This paper addresses flow shop scheduling problem with a batch processor followed by a discrete processor. Incompatible job families and limited buffer size are considered, and the objective is to determine a schedule such that the total completion time is minimised. Flexible buffer service policy is designed, and a greedy heuristic together with the worst-case analysis is developed. We also propose a hybrid method involving a Differential Evolution algorithm. Moreover, two tight lower bounds are provided to measure the performances of the proposed algorithms. Numerical results demonstrate that the proposed algorithms are capable of providing high-quality solutions for large-scale problems within a reasonable computational time.
Journal: International Journal of Production Research
Pages: 3217-3233
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2016.1268730
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1268730
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Template-Type: ReDIF-Article 1.0
Author-Name: Weibo Liu
Author-X-Name-First: Weibo
Author-X-Name-Last: Liu
Author-Name: Yan Jin
Author-X-Name-First: Yan
Author-X-Name-Last: Jin
Author-Name: Mark Price
Author-X-Name-First: Mark
Author-X-Name-Last: Price
Title: New scheduling algorithms and digital tool for dynamic permutation flowshop with newly arrived order
Abstract: 
 The permutation flowshop scheduling problem has been widely studied under static environment by assuming machines and jobs are available at the time of zero. However, in reality, new orders arrive at production systems randomly, which leads to sheer complexity in scheduling due to the dynamic changes given various constraints of resources. Previous studies simply attach new orders directly after the existing schedule. Recent study shows mixing jobs of old and new orders could result in better scheduling solutions. But the heuristic algorithms are still lacking to implement the job mixing policy. To address this problem, a novel scheduling strategy is herein proposed by integrating match-up strategy and real-time strategy (MR) in order to make use of the remaining time before the old order due date. Based on the new MR strategy, eleven new heuristics are introduced with ten existing and one new priority rules. Computational results illustrate the effectiveness of the new heuristics. A digital tool is developed for ease of application of these heuristics, and it is validated by case studies.
Journal: International Journal of Production Research
Pages: 3234-3248
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1285077
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1285077
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Template-Type: ReDIF-Article 1.0
Author-Name: Amir Jalilvand-Nejad
Author-X-Name-First: Amir
Author-X-Name-Last: Jalilvand-Nejad
Author-Name: Rasoul Shafaei
Author-X-Name-First: Rasoul
Author-X-Name-Last: Shafaei
Author-Name: Hamid Shahriari
Author-X-Name-First: Hamid
Author-X-Name-Last: Shahriari
Title: A Genco self-scheduling problem with correlated prices using a new robust optimization approach
Abstract: 
 In this research, a self-scheduling problem for a power generation company (Genco), participating in a day-ahead power market is studied. A robust optimisation approach is followed to tackle uncertainty on the market prices. Due to the existing correlations among hourly market prices and in order to enhance the value of the objective function in an uncertain environment, a new robust optimisation approach is developed and presented to prevent over-conservative solutions. A couple of polyhedral uncertainty sets are applied to protect the optimal solution solely against any correlated perturbation. In addition two robust self-scheduling models are formulated under these uncertainty sets. The results of this study justify the performance of the proposed models compared to those of the existing robust self-scheduling model applied for conventional polyhedral uncertainty set.
Journal: International Journal of Production Research
Pages: 3249-3265
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1288944
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1288944
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Template-Type: ReDIF-Article 1.0
Author-Name: Jae-Min Yu
Author-X-Name-First: Jae-Min
Author-X-Name-Last: Yu
Author-Name: Rong Huang
Author-X-Name-First: Rong
Author-X-Name-Last: Huang
Author-Name: Dong-Ho Lee
Author-X-Name-First: Dong-Ho
Author-X-Name-Last: Lee
Title: Iterative algorithms for batching and scheduling to minimise the total job tardiness in two-stage hybrid flow shops
Abstract: 
 This study considers the batching and scheduling problem in two-stage hybrid flow shops in which each job with a distinct due-date is processed through two serial production stages, each of which has identical machines in parallel. Under the fundamental trade-off that large batch sizes with less frequent changeovers may reduce setup costs and hence increase machine utilisation, while small batch sizes may reduce job flow times and hence improve scheduling performance, the problem is to determine the number of batches, the batch compositions, the allocation of batches to the parallel machines at each stage, and the sequence of the batches allocated to each machine for the objective of minimising the total job tardiness. A mixed integer programming model is developed for the reduced problem in which the number of batches is given, and then, three iterative algorithms are proposed in which batching and scheduling are done repeatedly until a good solution is obtained. To show the performance of the algorithms, computational experiments were done on a number of test instances, and the results are reported. In particular, we show that the number of batches decreases as the ratio of the batch setup time to the job processing time increases.
Journal: International Journal of Production Research
Pages: 3266-3282
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1304661
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1304661
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian Chao Luo
Author-X-Name-First: Jian Chao
Author-X-Name-Last: Luo
Author-Name: Ke Yi Xing
Author-X-Name-First: Ke Yi
Author-X-Name-Last: Xing
Author-Name: Meng Chu Zhou
Author-X-Name-First: Meng Chu
Author-X-Name-Last: Zhou
Author-Name: Xiao Ling Li
Author-X-Name-First: Xiao Ling
Author-X-Name-Last: Li
Author-Name: Xin Nian Wang
Author-X-Name-First: Xin Nian
Author-X-Name-Last: Wang
Title: Scheduling of deadlock and failure-prone automated manufacturing systems via hybrid heuristic search
Abstract: 
 This work focuses on the scheduling problem of deadlock and failure-prone automated manufacturing systems, and presents a new scheduling method by combining a robust supervisory control policy and hybrid heuristic search. It aims to minimise makespan, i.e. the completion time of the last part. Based on the extended reach ability graph of the system, it establishes a new heuristic function and two dispatching rules to guide the search process for a schedule. By embedding a robust supervisory control policy into the search process, it develops a polynomial robust dynamic window search algorithm. Failure and repair events of unreliable resources may occur during the execution of a schedule obtained by the proposed algorithm and may make the schedule infeasible. To reduce the influence caused by them and ensure all parts to be finished, this work proposes two event-driven strategies. The first one suspends the execution of the parts requiring failed resources and those to be started until all failed resources are repaired and permits only those parts that have already been processed on working machines to be completed. The second one invokes the proposed algorithm to obtain a new schedule at the vertex generated after a resource failure or repair event and executes the new schedule. Both strategies are effective while the latter performs better at the expense of more computation.
Journal: International Journal of Production Research
Pages: 3283-3293
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1306132
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1306132
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:11:p:3283-3293




Template-Type: ReDIF-Article 1.0
Author-Name: Michele E. Pfund
Author-X-Name-First: Michele E.
Author-X-Name-Last: Pfund
Author-Name: John W. Fowler
Author-X-Name-First: John W.
Author-X-Name-Last: Fowler
Title: Extending the boundaries between scheduling and dispatching: hedging and rescheduling techniques
Abstract: 
 While deterministic scheduling models have been well studied, the use of these models is not well documented in manufacturing environments. Previous research has indicated that deterministic scheduling approaches quickly lose their advantage compared to dispatching rules when processing time uncertainty is present. This research presents the case of a Printed Wiring Board Manufacturer’s drilling operation, which is a group of unrelated parallel machines. The manufacturer wishes to minimise makespan, number of late jobs, total overtime, average machine finishing time and machine utilisation when stochastic uncertainty is present. While deterministic scheduling has been shown to be a good solution approach when processing time variability is low, this research attempts to extend the boundaries in which scheduling is useful by investigating job and machine hedges as well as periodic and event driven rescheduling policies. The success of the approach is evaluated using a simulation model to evaluate the performance over a number of sequential schedules under various distributional assumptions.
Journal: International Journal of Production Research
Pages: 3294-3307
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1306133
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1306133
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:11:p:3294-3307




Template-Type: ReDIF-Article 1.0
Author-Name: Adil Baykasoğlu
Author-X-Name-First: Adil
Author-X-Name-Last: Baykasoğlu
Author-Name: Fatma S. Karaslan
Author-X-Name-First: Fatma S.
Author-X-Name-Last: Karaslan
Title: Solving comprehensive dynamic job shop scheduling problem by using a GRASP-based approach
Abstract: 
 There are many dynamic events like new order arrivals, machine breakdowns, changes in due dates, order cancellations, arrival of urgent orders etc. that makes static scheduling approaches very difficult. A dynamic scheduling strategy should be adopted under such production circumstances. In the present study an event driven dynamic job shop scheduling mechanism under machine capacity constraints is proposed. The proposed method makes use of the greedy randomised adaptive search procedure (GRASP) by also taking into account orders due dates and sequence-dependent set-up times. Moreover, order acceptance/rejection decision and Order Review Release mechanism are integrated with scheduling decision in order to meet customer due date requirements while attempting to execute capacity adjustments. We employed a goal programming-based logic which is used to evaluate four objectives: mean tardiness, schedule unstability, makespan and mean flow time. Benchmark problems including number of orders, number of machines and different dynamic events are generated. In addition to event-driven rescheduling strategy, a periodic rescheduling strategy is also devised and both strategies are compared for different problems. Experimental studies are performed to evaluate effectiveness of the proposed method. Obtained results have proved that the proposed method is a feasible approach for rescheduling problems under dynamic environments.
Journal: International Journal of Production Research
Pages: 3308-3325
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1306134
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1306134
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Template-Type: ReDIF-Article 1.0
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Author-Name: B.M.T. Lin
Author-X-Name-First: B.M.T.
Author-X-Name-Last: Lin
Title: Demonstrating Johnson’s algorithm via resource-constrained scheduling
Abstract: 
 The celebrated Johnson’s algorithm to solve the two-machine flowshop scheduling problem to minimise the makespan plays a prominent role in scheduling research. In using resource-constrained scheduling to interpret Johnson’s algorithm in teaching scheduling theory and operations management, we have received positive student feedback on the perceived intuition. We demonstrate this idea and show that the resource-constrained scheduling concept also helps simplify the proofs of some classical scheduling results.
Journal: International Journal of Production Research
Pages: 3326-3330
Issue: 11
Volume: 55
Year: 2017
Month: 6
X-DOI: 10.1080/00207543.2017.1314040
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1314040
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Handle: RePEc:taf:tprsxx:v:55:y:2017:i:11:p:3326-3330




Template-Type: ReDIF-Article 1.0
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Rameshwar Dubey
Author-X-Name-First: Rameshwar
Author-X-Name-Last: Dubey
Author-Name: Samuel Fosso Wamba
Author-X-Name-First: Samuel
Author-X-Name-Last: Fosso Wamba
Author-Name: Thanos Papadopoulos
Author-X-Name-First: Thanos
Author-X-Name-Last: Papadopoulos
Author-Name: Benjamin T. Hazen
Author-X-Name-First: Benjamin T.
Author-X-Name-Last: Hazen
Author-Name: Eric W.T. Ngai
Author-X-Name-First: Eric W.T.
Author-X-Name-Last: Ngai
Title: Bridging humanitarian operations management and organisational theory
Abstract: 
 The aim of the editorial note is to introduce the scope of this special issue (SI). We explain our editorial approach and provide a brief summary of eight articles included in the SI following multiple rounds of reviews. Finally, we outline future research questions which stemmed out of the discussions of this SI.
Journal: International Journal of Production Research
Pages: 6735-6740
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1551958
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1551958
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Template-Type: ReDIF-Article 1.0
Author-Name: Michael Naor
Author-X-Name-First: Michael
Author-X-Name-Last: Naor
Author-Name: Asoke Dey
Author-X-Name-First: Asoke
Author-X-Name-Last: Dey
Author-Name: Susan Meyer Goldstein
Author-X-Name-First: Susan
Author-X-Name-Last: Meyer Goldstein
Author-Name: Yitzhak Rosen
Author-X-Name-First: Yitzhak
Author-X-Name-Last: Rosen
Title: Civilian-military pooling of health care resources in Haiti: a theory of complementarities perspective
Abstract: 
 The 2010 Haiti earthquake brought attention to the global need for rapid deployment of disaster relief health care services. In such large-scale disasters, a variety of international organisations provide temporary services until the damaged local health care system recovers. However, the disaster environment can pose operational and temporal challenges that may impede the effectiveness of relief services, and research is needed to provide both theory and methods for improving coordination and collaboration among relief organisations. This study investigates opportunities and barriers for relief organisations to pool complementary resources originating from multiple countries, by examining five case studies that represent the breadth of organizational types, including charter (civilian, military, university-affiliated and public/private), facility type (primary, secondary, and tertiary care), and duration of stay. The study yields a set of research propositions that chart avenues for future studies in this emerging field of research at the intersection of health care humanitarian operations and organisation theory.
Journal: International Journal of Production Research
Pages: 6741-6757
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2017.1355121
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1355121
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:21:p:6741-6757




Template-Type: ReDIF-Article 1.0
Author-Name: Yogesh K. Dwivedi
Author-X-Name-First: Yogesh K.
Author-X-Name-Last: Dwivedi
Author-Name: Mahmud Akhter Shareef
Author-X-Name-First: Mahmud Akhter
Author-X-Name-Last: Shareef
Author-Name: Bhasker Mukerji
Author-X-Name-First: Bhasker
Author-X-Name-Last: Mukerji
Author-Name: Nripendra P. Rana
Author-X-Name-First: Nripendra P.
Author-X-Name-Last: Rana
Author-Name: Kawaljeet Kaur Kapoor
Author-X-Name-First: Kawaljeet Kaur
Author-X-Name-Last: Kapoor
Title: Involvement in emergency supply chain for disaster management: a cognitive dissonance perspective
Abstract: 
 An integrated process, interlinked operation and interoperable communication network amongst operating agencies are critical for developing an effective disaster management supply chain. The traditional managerial problems observed across disaster management operations are: non-cooperation among members, disrupted chain of commands, misuse of relief items, lack of information sharing, mistrust and lack of coordination. This study aims to understand the issues affiliated with negative attitude towards disaster management operations using theory of cognitive dissonance. A qualitative investigation was undertaken across 64 districts in Bangladesh. Five constructs were examined for their influences on attitude and behavioural intention of members participating in government emergency supply chain for disaster management. The results indicate that administrative conflict, political biasness and professional growth have significant effects on attitude. Impact of insecurity is non-significant on attitude. This research offers substantial theoretical contribution to the cognitive dissonance theory in the context of disaster management supply chain.
Journal: International Journal of Production Research
Pages: 6758-6773
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2017.1378958
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1378958
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Template-Type: ReDIF-Article 1.0
Author-Name: Sameer Prasad
Author-X-Name-First: Sameer
Author-X-Name-Last: Prasad
Author-Name: R.P. Sundarraj
Author-X-Name-First: R.P.
Author-X-Name-Last: Sundarraj
Author-Name: Jasmine Tata
Author-X-Name-First: Jasmine
Author-X-Name-Last: Tata
Author-Name: Nezih Altay
Author-X-Name-First: Nezih
Author-X-Name-Last: Altay
Title: Action-research-based optimisation model for health care behaviour change in rural India
Abstract: 
 In this research, we utilise a multi-method braided approach for a real-world health care intervention in rural India. We first use action research to conceptually underpin the role of self-help groups, disease profiles and appropriate interventions in health care behaviour change and improvement. Action research is then coupled with a non-linear integer-programming-based simulation to determine how health care resources need to be distributed over time, disease type and groups. The action research provides specific research questions and distributional forms needed for the optimisation analysis, while the non-linear integer-programming simulation provides specific recommendations on where and when to distribute resources. External validity of the study is ensured by the adoption of recommendations in the field as part of the action research. Findings from this research have important policy implications. For example, it identifies the value of continuous embedded interventions as opposed to periodic ones and the importance of flexibility in terms of which community groups and disease types to serve over time. This research also provides an important bridge between the operations research, health care in developing nations, organisational theory and humanitarian operations bodies of knowledge.
Journal: International Journal of Production Research
Pages: 6774-6792
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2017.1414329
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1414329
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:21:p:6774-6792




Template-Type: ReDIF-Article 1.0
Author-Name: Saileshsingh Gunessee
Author-X-Name-First: Saileshsingh
Author-X-Name-Last: Gunessee
Author-Name: Nachiappan Subramanian
Author-X-Name-First: Nachiappan
Author-X-Name-Last: Subramanian
Author-Name: Samuel Roscoe
Author-X-Name-First: Samuel
Author-X-Name-Last: Roscoe
Author-Name: Jothibasu Ramanathan
Author-X-Name-First: Jothibasu
Author-X-Name-Last: Ramanathan
Title: The social preferences of local citizens and spontaneous volunteerism during disaster relief operations
Abstract: 
 Existing studies on disaster relief operations pay limited attention to acts of spontaneous volunteerism by local citizens in the aftermath of disasters. The purpose of this paper is to explore how social preferences motivate citizens to help during post-disaster situations; above and beyond their own self-regarding interests. The paper begins by synthesising the literature on social preferences from the field of behavioural economics and social psychology with the discourse surrounding behavioural operations management and humanitarian operations management. By doing so, we identify the motivators, enablers and barriers of local citizen response during disaster relief operations. These factors inform a theoretical framework of the social preferences motivating spontaneous volunteerism in post-disaster situations. We evidence facets of the framework using archival and unstructured data retrieved from Twitter feeds generated by local citizens during the floods that hit Chennai, India in 2015. Our model highlights the importance of individual-level action during disaster relief operations and the enabling role of social media as a coordination mechanism for such efforts.
Journal: International Journal of Production Research
Pages: 6793-6808
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2017.1414330
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1414330
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:21:p:6793-6808




Template-Type: ReDIF-Article 1.0
Author-Name: Rajesh Kumar Singh
Author-X-Name-First: Rajesh Kumar
Author-X-Name-Last: Singh
Author-Name: Ayush Gupta
Author-X-Name-First: Ayush
Author-X-Name-Last: Gupta
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Title: Analysing the interaction of factors for resilient humanitarian supply chain
Abstract: 
 Emergencies and disasters place an exceptional demand on the managerial skills of the humanitarian aid community. Most of the developing countries lack in such kind of resilience and effective humanitarian supply chain. Therefore, the purpose of this paper is to identify and analyse the factors to develop the resilience in the humanitarian supply chain. Based on the literature review, total 12 factors related to resilient humanitarian supply chain have been identified. Some of these factors are process oriented and some are result oriented. Interpretive structural modelling with Fuzzy MICMAC analysis is used to develop structural relationships among these factors and to find the driving and the dependence power of these factors. Government support, strategy and capacity planning; and continuous assessment of project progress have emerged as the major drivers for the development of resilient humanitarian supply chain. By managing these driving factors, humanitarian aid programme can be made resilient and agile. The findings will be useful for the humanitarian aid agencies to develop effective and sustainable aid relief programme.
Journal: International Journal of Production Research
Pages: 6809-6827
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1424373
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424373
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:21:p:6809-6827




Template-Type: ReDIF-Article 1.0
Author-Name: Paul D. Larson
Author-X-Name-First: Paul D.
Author-X-Name-Last: Larson
Author-Name: Cyril Foropon
Author-X-Name-First: Cyril
Author-X-Name-Last: Foropon
Title: Process improvement in humanitarian operations: an organisational theory perspective
Abstract: 
 Contingency theory suggests the best way to organise and lead an organisation, or to make decisions, depends upon internal and external situational factors, e.g. organisational size, operational scope and environmental uncertainty. Humanitarian organisations use various process management tools, including codes of conduct and standards. Large non-governmental organisations (NGOs) seem especially attracted to standards. The purpose of this paper is to advance our understanding of process improvement techniques, with a focus on standards, in use by humanitarian NGOs. Content analysis is the method employed in this study. A sample of humanitarian NGO annual reports and web pages is studied to describe the NGOs and determine their approaches to process improvement. The sample contains a mix of NGOs based on their location (France or Canada), organisational size and scope of operations (development aid, disaster relief, etc.). Contingency theory is useful in linking contingency factors to process improvement approaches. NGO size, operational scope and organisational culture factors are linked to use of standards. This is one of the first (if not the first study) to adopt contingency theory in an investigation of process improvement approaches among humanitarian NGOs. It focuses on a managerial issue of great relevance &#x2013; process improvement in humanitarian operations.
Journal: International Journal of Production Research
Pages: 6828-6841
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1424374
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1424374
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Template-Type: ReDIF-Article 1.0
Author-Name: N. Nurmala
Author-X-Name-First: N.
Author-X-Name-Last: Nurmala
Author-Name: Jelle de Vries
Author-X-Name-First: Jelle
Author-X-Name-Last: de Vries
Author-Name: Sander de Leeuw
Author-X-Name-First: Sander
Author-X-Name-Last: de Leeuw
Title: Cross-sector humanitarian&#x2013;business partnerships in managing humanitarian logistics: an empirical verification
Abstract: 
 Cross-Sector humanitarian&#x2013;business partnerships in managing humanitarian logistics comprise a key discussion topic in literature, yet empirical validations of these partnerships are lacking to date. This paper aims to develop a typological framework for humanitarian&#x2013;business partnerships in managing humanitarian logistics and to empirically verify this typology with a data-set using content analysis. The results show that the amounts of partnerships developed between the business sector and the humanitarian sector in managing humanitarian logistics is still limited and these partnerships are not widely publicised. The research furthermore shows that financial contributions comprise the most common type of resource delivered by the business sector when it comes to partnerships with the humanitarian sector focused on managing humanitarian logistics. It is also interesting to note that the majority of partnerships in our sample are dyadic in nature, managed by a single humanitarian organisation and a single business corporation. Furthermore, we find that most of the partnerships target support for natural disaster emergency relief operations and mainly focus on disaster response.
Journal: International Journal of Production Research
Pages: 6842-6858
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1449977
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1449977
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Template-Type: ReDIF-Article 1.0
Author-Name: Xin Yao
Author-X-Name-First: Xin
Author-X-Name-Last: Yao
Author-Name: Ruting Huang
Author-X-Name-First: Ruting
Author-X-Name-Last: Huang
Author-Name: Malin Song
Author-X-Name-First: Malin
Author-X-Name-Last: Song
Author-Name: Nishikant Mishra
Author-X-Name-First: Nishikant
Author-X-Name-Last: Mishra
Title: Pre-positioning inventory and service outsourcing of relief material supply chain
Abstract: 
 Service outsourcing is very common in a commercial supply chain, and in humanitarian relief area, the transportation service is usually outsourced. To practice relief supply more effectively, it seems essential to enlarge outsourcing from shipping to more areas, and private enterprises could play a vital role. This paper examines the optimal pre-disaster order quantity of a certain relief commodity, based on a two-stage coordinated approach. Our findings show that the delay cost, shortage penalty cost, risk of supply shortage, salvage value, expected perishable rate, unit inventory cost and reactive price have significant impacts on the optimal amount of propositioned inventory. Moreover, the outsourcing strategies differ by types of relief commodities. For perishable supplies, proactive or reactive outsourcing would improve the benefits of buyer and supplier simultaneously. As for imperishable supplies, it is better to combine proactive insourcing approach and reactive outsourcing strategy. In view of some supplies whose monitoring cost is high, the insourcing approach is much better than the outsourcing approach.
Journal: International Journal of Production Research
Pages: 6859-6871
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1495853
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1495853
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Template-Type: ReDIF-Article 1.0
Author-Name: Pingping Feng
Author-X-Name-First: Pingping
Author-X-Name-Last: Feng
Author-Name: Ya Liu
Author-X-Name-First: Ya
Author-X-Name-Last: Liu
Author-Name: Feng Wu
Author-X-Name-First: Feng
Author-X-Name-Last: Wu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Two heuristics for coordinating production planning and transportation planning
Abstract: 
 In this study, a coordinated production and transportation planning problem is addressed. A fleet of heterogeneous vehicles is considered. The transportation costs consist of two terms: a term represents the fixed cost for each vehicle used and another term for the variable cost which is the marginal transportation cost times the transportation quantity. The problem is formulated as a mixed-integer linear programming model (MILP) and a Non-Linear Programming model (NLP). The problem is unsolvable when the size increases beyond a certain magnitude. Therefore, two heuristics are developed. One of them is a decomposition-based heuristic (termed DBH). It combines solutions by decomposing the original problem into production and transportation subproblems and iteratively improves the combined solutions. The other heuristic is based on Lagrangian relaxation (called LRBH). The performance of these heuristics is evaluated by comparing their results with optimal solutions for small-sized instances and with Lagrangian-relaxation-based lower bounds for medium- or large-sized instances. The results indicate that although these heuristics use distinct mechanisms, they are both efficient and have comparable performances. The average cost gap for DBH as well as LRBH is around 0.79%$ 0.79\% $ compared with optimal solutions. They are 4.43 and 4.53%$ 4.53\% $, respectively, when compared with Lagrangian-relaxation-based lower bounds.
Journal: International Journal of Production Research
Pages: 6872-6889
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2017.1351631
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1351631
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Template-Type: ReDIF-Article 1.0
Author-Name: Hadi Moheb-Alizadeh
Author-X-Name-First: Hadi
Author-X-Name-Last: Moheb-Alizadeh
Author-Name: Robert Handfield
Author-X-Name-First: Robert
Author-X-Name-Last: Handfield
Title: An integrated chance-constrained stochastic model for efficient and sustainable supplier selection and order allocation
Abstract: 
 Effective allocation of scarce resources across supply chain environments is an emerging issue, as enterprises face shortfalls in raw materials, human labour, budgetary resources, equipment, energy and capacity. We consider these related objectives in designing efficient and sustainable supply networks using a multi-objective mixed-integer non-linear programming (MINLP) model for efficient and sustainable supplier selection and order allocation with stochastic demand. Our approach considers sustainability dimensions including economic, environmental and social responsibility, but also seeks to design the most efficient supply network given constraints of the supply market. Enterprise efficiency is assessed using a bi-objective data envelopment analysis (DEA) whose inputs include raw materials, current expenses and labour force capacity. The resulting model is non-convex because of the presence of bilinear terms in DEA-related constraints, so we introduce a multi-stage solution procedure that first uses piecewise McCormick envelopes (PCM) to linearise the bilinear terms. Next, we introduce a set of valid inequalities in order to improve solution time of the problem whose dimension significantly increases after being linearised. We then exploit chance constrained programming approaches to deal with stochastic demand. Finally, a single aggregated objective function is derived using a fuzzy multi-objective programming approach. A manufacturing case study demonstrates the validity of the proposed approach, and its effectiveness in designing a supply network that addresses the &#x2018;triple bottom line&#x2019; of people, profit and planet that comprises many sustainability initiatives in an efficient manner.
Journal: International Journal of Production Research
Pages: 6890-6916
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2017.1413258
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1413258
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Template-Type: ReDIF-Article 1.0
Author-Name: Ilaria De Sanctis
Author-X-Name-First: Ilaria
Author-X-Name-Last: De Sanctis
Author-Name: Joaqu&#xED;n Ordieres Mer&#xE9;
Author-X-Name-First: Joaqu&#xED;n
Author-X-Name-Last: Ordieres Mer&#xE9;
Author-Name: Filippo Emanuele Ciarapica
Author-X-Name-First: Filippo Emanuele
Author-X-Name-Last: Ciarapica
Title: Resilience for lean organisational network
Abstract: 
 In the literature, when lean is associated with resilience the focus is mainly on developing leaner and more resilient supply chains underrating the importance of organisations as communicating entities. Although people are the heart of a company, their impact on resilience is only marginally considered in the literature. In this study, we address these gaps by developing and testing a model that can calculate the resilience of a lean organisation while considering the organisational topology as well as the learning capacity and attitudes of its workforce. The proposed methodology consists of four macro-steps: identification of a Lean Structural Network (LSN), modelling of nodes, nodes characterisation and analysis of Resilience. A case study is used to explain the proposed model to assess the resilience of the intrinsic structure of a company against two major effects: (a) unexpected shortages in key performance indicators; (b) replacement of a process owner with another having different individual characteristics (different learning curve and attitude). The results show that the proposed methodology allows quantification and prediction of the local and global impacts of unexpected (i.e. failures or other disruptions) and expected events (i.e. cross-training, personnel relocation) in companies under the LSN paradigm.
Journal: International Journal of Production Research
Pages: 6917-6936
Issue: 21
Volume: 56
Year: 2018
Month: 11
X-DOI: 10.1080/00207543.2018.1457810
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1457810
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Template-Type: ReDIF-Article 1.0
Author-Name: Chao Chen
Author-X-Name-First: Chao
Author-X-Name-Last: Chen
Author-Name: Shenle Pan
Author-X-Name-First: Shenle
Author-X-Name-Last: Pan
Author-Name: Zhu Wang
Author-X-Name-First: Zhu
Author-X-Name-Last: Wang
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Title: Using taxis to collect citywide E-commerce reverse flows: a crowdsourcing solution
Abstract: 
 The popularity of round-the-clock online shopping urges the rapid growth of e-commerce, which substantially generates additional parcels for the distribution on the forward side. On the other hand, collecting the returned goods on the revere side is also increasingly becoming a preoccupation, particularly in the crowd and dense metropolitan areas. Inspired by the concepts of Crowdsourcing and Physical Internet, we propose an innovative solution to collect the e-commerce returned goods from final consumption points back to retailers. As an alternative to traditional ways, this solution delivers the returned goods and passengers in an integrated way by leveraging the extra loading capacity and constant mobility provided by taxis that are already reserved to transport passengers. Thus, it could simultaneously migrate the negative economical, environmental and social impacts of reverse flows management. To address the issue of the returned goods collection, we first conduct the qualitative and quantitative study, and further investigate the feasibility and viability of the solution based on three real-world datasets, which consist of locations of shops, a road network and a large-scale trajectory data generated by over 7000 taxis in a month in the city of Hangzhou, China. Three collection strategies are proposed and evaluated. Experimental results generate several useful insights into the implementability and managerial issues of the proposed solution.
Journal: International Journal of Production Research
Pages: 1833-1844
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1173258
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1173258
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Template-Type: ReDIF-Article 1.0
Author-Name: Roba W. Salem
Author-X-Name-First: Roba W.
Author-X-Name-Last: Salem
Author-Name: Mohamed Haouari
Author-X-Name-First: Mohamed
Author-X-Name-Last: Haouari
Title: A simulation-optimisation approach for supply chain network design under supply and demand uncertainties
Abstract: 
 We investigate a three-echelon stochastic supply chain network design problem. The problem requires selecting suppliers, determining warehouses locations and sizing, as well as the material flows. The objective is to minimise the total expected cost. An important feature of the investigated problem is that both the supply and the demand are uncertain. We solve this problem using a simulation-optimisation approach that is based on a novel hedging strategy that aims at capturing the randomness of the uncertain parameters. To determine the optimal hedging parameters, the search process is guided by particle swarm optimisation procedure. We present the results of extensive computational experiments that were conducted on a large set of instances and that provide evidence that the proposed hedging strategy constitutes an effective viable solution approach.
Journal: International Journal of Production Research
Pages: 1845-1861
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1174788
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1174788
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Template-Type: ReDIF-Article 1.0
Author-Name: Mariagrazia Dotoli
Author-X-Name-First: Mariagrazia
Author-X-Name-Last: Dotoli
Author-Name: Nicola Epicoco
Author-X-Name-First: Nicola
Author-X-Name-Last: Epicoco
Author-Name: Marco Falagario
Author-X-Name-First: Marco
Author-X-Name-Last: Falagario
Title: A fuzzy technique for supply chain network design with quantity discounts
Abstract: 
 This paper proposes a hierarchical technique for Supply Chain Network (SCN) efficiency maximisation under uncertainty composed of three steps. The first step extends a previous fuzzy cross-efficiency Data Envelopment Analysis approach, originally intended for suppliers’ selection, in order to evaluate and rank all the actors in each SCN stage under conflicting nondeterministic criteria. Afterwards, a fuzzy linear integer programming model is stated and solved for each pair of subsequent SCN stages to determine the quantities required from each stakeholder to maximise the overall SCN efficiency while satisfying the estimated demand and respecting the nodes capacity. Finally, a heuristics is applied to limit the exchange of small quantities in the SCN, in which the trade is not economically convenient according to quantity discounts. An illustrative example from the literature shows the technique effectiveness.
Journal: International Journal of Production Research
Pages: 1862-1884
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1178408
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1178408
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Template-Type: ReDIF-Article 1.0
Author-Name: Alejandro Gutierrez-Alcoba
Author-X-Name-First: Alejandro
Author-X-Name-Last: Gutierrez-Alcoba
Author-Name: Roberto Rossi
Author-X-Name-First: Roberto
Author-X-Name-Last: Rossi
Author-Name: Belen Martin-Barragan
Author-X-Name-First: Belen
Author-X-Name-Last: Martin-Barragan
Author-Name: Eligius M.T. Hendrix
Author-X-Name-First: Eligius M.T.
Author-X-Name-Last: Hendrix
Title: A simple heuristic for perishable item inventory control under non-stationary stochastic demand
Abstract: 
 In this paper, we study the single-item single-stocking location non-stationary stochastic lot sizing problem for a perishable product. We consider fixed and proportional ordering cost, holding cost and penalty cost. The item features a limited shelf life, therefore we also take into account a variable cost of disposal. We derive exact analytical expressions to determine the expected value of the inventory of different ages. We also discuss a good approximation for the case in which the shelf-life is limited. To tackle this problem, we introduce two new heuristics that extend Silver’s heuristic and compare them to an optimal Stochastic Dynamic Programming policy in the context of a numerical study. Our results demonstrate the effectiveness of our approach.
Journal: International Journal of Production Research
Pages: 1885-1897
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1193248
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1193248
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Template-Type: ReDIF-Article 1.0
Author-Name: Der-Chiang Li
Author-X-Name-First: Der-Chiang
Author-X-Name-Last: Li
Author-Name: Wu-Kuo Lin
Author-X-Name-First: Wu-Kuo
Author-X-Name-Last: Lin
Author-Name: Liang-Sian Lin
Author-X-Name-First: Liang-Sian
Author-X-Name-Last: Lin
Author-Name: Chien-Chih Chen
Author-X-Name-First: Chien-Chih
Author-X-Name-Last: Chen
Author-Name: Wen-Ting Huang
Author-X-Name-First: Wen-Ting
Author-X-Name-Last: Huang
Title: The attribute-trend-similarity method to improve learning performance for small datasets
Abstract: 
 Small data-set learning problems are attracting more attention because of the short product lifecycles caused by the increasing pressure of global competition. Although statistical approaches and machine learning algorithms are widely applied to extract information from such data, these are basically developed on the assumption that training samples can represent the properties of the whole population. However, as the properties that the training samples contain are limited, the knowledge that the learning algorithms extract may also be deficient. Virtual sample generation approaches, used as a kind of data pretreatment, have proved their effectiveness when handling small data-set problems. By considering the relationships among attributes in the value generation procedure, this research proposes a non-parametric process to learn the trend similarities among attributes, and then uses these to estimate the corresponding ranges that attribute values may be located in when other attribute values are given. The ranges of the attribute values of the virtual samples are then stepwise estimated using the triangular membership functions (MFs) built to represent the attribute sample distributions. In the experiment, two real cases are examined with four modelling tools, including the M5′ model tree (M5′), multiple linear regression, support vector regression and back-propagation neural network. The results show that the forecasting accuracies of the four modelling tools are improved when training sets contain virtual samples. In addition, the outcomes of the proposed procedure show significantly smaller predictive errors than those of other approaches.
Journal: International Journal of Production Research
Pages: 1898-1913
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1213447
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213447
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Template-Type: ReDIF-Article 1.0
Author-Name: Omid Sanei Bajgiran
Author-X-Name-First: Omid
Author-X-Name-Last: Sanei Bajgiran
Author-Name: Masoumeh Kazemi Zanjani
Author-X-Name-First: Masoumeh
Author-X-Name-Last: Kazemi Zanjani
Author-Name: Mustapha Nourelfath
Author-X-Name-First: Mustapha
Author-X-Name-Last: Nourelfath
Title: Forest harvesting planning under uncertainty: a cardinality-constrained approach
Abstract: 
 Harvesting planning (HP) is a key tactical decision in lumber supply chains. Harvesting areas in the forests are divided into different blocks with different types and quantities of raw materials (logs). Predicting the availability of raw materials in each block along with log demand is impossible in this industry. Hence, incorporating uncertainty into the HP problem is essential in order to obtain robust plans that do not drastically fluctuate in the presence of future perturbations in the forest and log market. In this paper, we propose a robust harvesting planning model formulated based on cardinality-constrained method. The latter provides some insights into the adjustment of the level of robustness of the harvesting plan over the planning horizon and protection against uncertainty. An extensive set of experiments based on Monte-Carlo simulation is also conducted in order to better validate the proposed robust optimisation approach.
Journal: International Journal of Production Research
Pages: 1914-1929
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1213915
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1213915
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Template-Type: ReDIF-Article 1.0
Author-Name: M. Reza Abdi
Author-X-Name-First: M. Reza
Author-X-Name-Last: Abdi
Author-Name: Ashraf Labib
Author-X-Name-First: Ashraf
Author-X-Name-Last: Labib
Title: RMS capacity utilisation: product family and supply chain
Abstract: 
 The paper contributes to development of RMS through linkage with external stakeholders such as customers and suppliers of parts/raw materials to handle demand fluctuations that necessitate information sharing across the supply chain tiers. RMS is developed as an integrated supply chain hub for adjusting production capacity using a hybrid methodology of decision trees and Markov analysis. The proposed Markov Chain model contributes to evaluate and monitor system reconfigurations required due to changes of product families with consideration of the product life cycles. The simulation findings indicate that system productivity and financial performance in terms of the profit contribution of product-process allocation will vary over configuration stages. The capacity of an RMS with limited product families and/or limited model variants becomes gradually inoperative whilst approaching upcoming configuration stages due to the end of product life cycles. As a result, reconfiguration preparation is suggested quite before ending life cycle of an existing product in process, for switching from a product family to a new/another product family in the production range, subject to its present demand. The proposed model is illustrated through a simplified case study with given product families and transition probabilities.
Journal: International Journal of Production Research
Pages: 1930-1956
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1229066
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1229066
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Template-Type: ReDIF-Article 1.0
Author-Name: Yi-Kuei Lin
Author-X-Name-First: Yi-Kuei
Author-X-Name-Last: Lin
Author-Name: Cheng-Fu Huang
Author-X-Name-First: Cheng-Fu
Author-X-Name-Last: Huang
Author-Name: Yi-Chieh Liao
Author-X-Name-First: Yi-Chieh
Author-X-Name-Last: Liao
Author-Name: Chih-Ching Yeh
Author-X-Name-First: Chih-Ching
Author-X-Name-Last: Yeh
Title: System reliability for a multistate intermodal logistics network with time windows
Abstract: 
 Network structures have been diffusely adopted in logistics systems, where the most critical target is completing the delivery within the promised timeframe. This paper focuses on a single commodity in a multistate intermodal logistics network (MILN) with transit stations and routes to involve three parameters: a route’s capacity, delivery time and time window. There is a carrier along each route whose number of available containers is multistate because the containers can be occupied by other customers. The delivery time consisting of the service time, travel time and waiting time varies with the number of containers and vehicle type. The arrival time at the transit station should be within the time window, the interval between the earliest and latest acceptable arrival times. This paper evaluates the system reliability, the probability that the MILN can successfully deliver sufficient amount of the commodity to meet market demand via several transit stations under the delivery time threshold and time windows. The system reliability can be treated as a delivery performance index and is evaluated with a proposed algorithm in terms of minimal paths. A practical case of scooter parts distribution between Taiwan and China is presented to emphasise the management implications of system reliability.
Journal: International Journal of Production Research
Pages: 1957-1969
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1247997
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1247997
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Template-Type: ReDIF-Article 1.0
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Title: A portfolio approach to supply chain disruption management
Abstract: 
 A new, computationally efficient portfolio approach to supplier selection in the presence of supply chain disruption risks is proposed, where the selection of supply portfolios for parts is combined with production scheduling of finished products. Unlike most of reported research on the supply chain risk management which focuses on the risk mitigation decisions taken prior to a disruption, the proposed portfolio approach combines decisions made before, during and after the disruption. The two decision-making approaches are considered: an integrated approach with the perfect information about the future disruption scenarios, and a hierarchical approach with no such information available. In the integrated approach, which accounts for all potential disruption scenarios, the primary supply portfolio that will hedge against all scenarios is determined along with the recovery supply portfolio and production schedule for each scenario. In the hierarchical approach, first the primary supply portfolio is determined, and then, when a primary supplier is hit by a disruption, the recovery supply portfolio is selected. For the integrated and the hierarchical decision-making, mixed integer programming models are developed with the two risk-neutral conflicting objectives that account for both time and cost of recovery: minimising expected cost or maximising expected service level. The findings indicate that for both objectives, the integrated decision-making selects a more diversified primary supply portfolio than the hierarchical approach and when all primary suppliers are shutdown by disruption, a single sourcing recovery portfolio is usually selected.
Journal: International Journal of Production Research
Pages: 1970-1991
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1249432
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1249432
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Template-Type: ReDIF-Article 1.0
Author-Name: Fabien Mahut
Author-X-Name-First: Fabien
Author-X-Name-Last: Mahut
Author-Name: Joanna Daaboul
Author-X-Name-First: Joanna
Author-X-Name-Last: Daaboul
Author-Name: Matthieu Bricogne
Author-X-Name-First: Matthieu
Author-X-Name-Last: Bricogne
Author-Name: Benoît Eynard
Author-X-Name-First: Benoît
Author-X-Name-Last: Eynard
Title: Product-Service Systems for servitization of the automotive industry: a literature review
Abstract: 
 Nowadays companies are facing several transformations of their activities, empowered and pulled by technological and social evolutions over the few past decades. As competitiveness is a leitmotiv in the market economy paradigm, it is necessary to improve activities through excellence and new offers. In a focus on the consumers’ needs, the limits between tangible and intangible offer are challenged through new kind of offers merging products and service under one common offer. Manufacturing companies, and more precisely the automotive industry, endeavour to integrate new constraints of sustainability, economic globalisation and new ways of consumption made possible with this new kind of offerings. This supports the opportunity to change consumption offers, historically driven by production and consumption of tangible assets. The paper explores a key concept to operate this shift towards a new type of offer gathering products and service into an integrated bundle entitled product-service system (PSS). This paper proposes a review of PSS definitions, methodologies and its applications to clarify the contribution of the literature in enabling its adoption. Requirements to adopt PSS are extracted from case studies and methodologies for servitization are evaluated as means to overcome barriers of PSS adoption. A specific focus is given on the automotive industry.
Journal: International Journal of Production Research
Pages: 2102-2120
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1252864
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1252864
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Template-Type: ReDIF-Article 1.0
Author-Name: Qinyun Li
Author-X-Name-First: Qinyun
Author-X-Name-Last: Li
Author-Name: Stephen M. Disney
Author-X-Name-First: Stephen M.
Author-X-Name-Last: Disney
Title: Revisiting rescheduling: MRP nervousness and the bullwhip effect
Abstract: 
 We study the material requirements planning (MRP) system nervousness problem from a dynamic, stochastic and economic perspective in a two-echelon supply chain under first-order auto-regressive demand. MRP nervousness is an effect where the future order forecasts, given to suppliers so that they may plan production and organise their affairs, exhibits extreme period-to-period variability. We develop a measure of nervousness that weights future forecast errors geometrically over time. Near-term forecast errors are weighted higher than distant forecast errors. Focusing on replenishment policies for high volume items, we investigate two methods of generating order call-offs and two methods of creating order forecasts. For order call-offs, we consider the traditional order-up-to (OUT) policy and the proportional OUT policy (POUT). For order forecasts, we study both minimum mean square error (MMSE) forecasts of the demand process and MMSE forecasts coupled with a procedure that accounts for the known future influence of the POUT policy. We show that when retailers use the POUT policy and account for its predictable future behaviour, they can reduce the bullwhip effect, supply chain inventory costs and the manufacturer’s MRP nervousness.
Journal: International Journal of Production Research
Pages: 1992-2012
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1261196
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1261196
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Template-Type: ReDIF-Article 1.0
Author-Name: Francesco Paolo Appio
Author-X-Name-First: Francesco Paolo
Author-X-Name-Last: Appio
Author-Name: Antonella Martini
Author-X-Name-First: Antonella
Author-X-Name-Last: Martini
Author-Name: Silvia Massa
Author-X-Name-First: Silvia
Author-X-Name-Last: Massa
Author-Name: Stefania Testa
Author-X-Name-First: Stefania
Author-X-Name-Last: Testa
Title: Collaborative network of firms: antecedents and state-of-the-art properties
Abstract: 
 The concept of collaborative networks has attracted considerable attention, especially in two knowledge domains: innovation and operation management. Although collaborative networks have evolved into many forms, their central role in triggering debates has not gone unnoticed. In this paper, we aim to contribute to these debates through a bibliometric review of a decade of research on collaborative networks (2002–2015). By using a combination of document co-citation and bibliographic coupling analyses, we unveil the origins and evolution of collaborative networks over time by analysing the references from the most important academic contributions. Our goal is threefold: first, to systematise the state of the art in the Input-Process-Output (IPO) framework; second, to elucidate the antecedents of the research field on collaborative networks (research streams originating from the field, main authors and journals) by organising them in six thematic clusters; and third, to show how the antecedents shaped the IPO framework. While ‘collaborative networks’ used to belong to two distinct domains, the research agendas seem to converge because of the interactions between their most active authors. As such, cross-fertilisation occurs with the International Journal of Production Research, which plays a central role in this process.
Journal: International Journal of Production Research
Pages: 2121-2134
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1262083
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1262083
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Template-Type: ReDIF-Article 1.0
Author-Name: Behzad Zahiri
Author-X-Name-First: Behzad
Author-X-Name-Last: Zahiri
Author-Name: Mir Saman Pishvaee
Author-X-Name-First: Mir Saman
Author-X-Name-Last: Pishvaee
Title: Blood supply chain network design considering blood group compatibility under uncertainty
Abstract: 
 This paper addresses the design of a blood supply chain (SC) network considering blood group compatibility. To this aim, a bi-objective mathematical programming model is developed which minimises the total cost as well as the maximum unsatisfied demand. Due to uncertain nature of some input parameters, two novel robust possibilistic programming models are proposed based on credibility measure. The data of a real case study are then used to illustrate the applicability and performance of the proposed models as well as validating the proposed robust possibilistic programming approach. The obtained results show the superiority of the developed models and significant cost savings compared to current existed blood SC network.
Journal: International Journal of Production Research
Pages: 2013-2033
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1262563
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1262563
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Template-Type: ReDIF-Article 1.0
Author-Name: Mustafa Çimen
Author-X-Name-First: Mustafa
Author-X-Name-Last: Çimen
Author-Name: Chris Kirkbride
Author-X-Name-First: Chris
Author-X-Name-Last: Kirkbride
Title: Approximate dynamic programming algorithms for multidimensional flexible production-inventory problems
Abstract: 
 An important issue in the manufacturing and supply chain literature concerns the optimisation of inventory decisions. Single-product inventory problems are widely studied and have been optimally solved under a variety of assumptions and settings. However, as systems become more complex, inventory decisions become more complicated for which the methods/approaches for optimising single inventory systems are incapable of deriving optimal policies. Manufacturing process flexibility provides an example of such a complex application area. Decisions involving the interrelated product inventories and production facilities form a highly multidimensional, non-decomposable system for which optimal policies cannot be readily obtained. We propose the methodology of approximate dynamic programming (ADP) to overcome the computational challenge imposed by this multidimensionality. Incorporating a sample backup simulation approach, ADP develops policies by utilising only a fraction of the computations required by classical dynamic programming. However, there are few studies in the literature that optimise production decisions in a stochastic, multi-factory, multi-product inventory system of this complexity. This paper aims to explore the feasibility and relevancy of ADP algorithms for this application. We present the results from numerical experiments that establish the strong performance of policies developed via temporal difference ADP algorithms in comparison to optimal policies and to policies derived from a deterministic approximation of the problem.
Journal: International Journal of Production Research
Pages: 2034-2050
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1264643
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1264643
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Template-Type: ReDIF-Article 1.0
Author-Name: Carsten Hansen
Author-X-Name-First: Carsten
Author-X-Name-Last: Hansen
Author-Name: Carlos Mena
Author-X-Name-First: Carlos
Author-X-Name-Last: Mena
Author-Name: Heather Skipworth
Author-X-Name-First: Heather
Author-X-Name-Last: Skipworth
Title: Exploring political risk in offshoring engagements
Abstract: 
 This research focuses on the analysis of political risk in the context of offshoring decisions. The study uses the Repertory Grid Technique, which entails a series of semi-structured interviews exploring key political risk experiences across offshoring engagements. The research extends the spectrum of political risk analysis in the context of offshoring engagements, and explores the varied impact of political risk across business activity types. The research identifies five key political risks affecting offshoring engagements and highlights the moderating effect of specific offshoring activity types Business Process Outsourcing, Information Technology Outsourcing or Knowledge Process Outsourcing on political risk implications. The research explores the conditioning effect of activity specific exposure to political risk and enhances the explanatory ability of the Transaction Cost Economics constructs, offering a novel operationalisation of the political risk component of external uncertainty. From a practical perspective, the research highlights the need for developing managerial tools to improve monitoring and identification of risks. The key practical contribution is the development of differentiated political risk typologies that can capture the nuances of external risks in offshoring, allowing for more accurate risk assessment of offshoring decisions.
Journal: International Journal of Production Research
Pages: 2051-2067
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1268278
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1268278
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiao Fu
Author-X-Name-First: Xiao
Author-X-Name-Last: Fu
Author-Name: Ming Dong
Author-X-Name-First: Ming
Author-X-Name-Last: Dong
Author-Name: Guanghua Han
Author-X-Name-First: Guanghua
Author-X-Name-Last: Han
Title: Coordinating a trust-embedded two-tier supply chain by options with multiple transaction periods
Abstract: 
 Trust widely works in supply chain practices and deeply affects supply chain decisions. Full trust in transactions and inaccurate demand forecasts are most likely to lead to biased decisions and low supply chain performances. Therefore, we propose a trust updating model to quantify decision-maker’s trust. The model presents the variation of trust over time and is helpful to evaluate decision-maker’s trust level in each transaction. In the model, a coordination mechanism with contract is designed to mitigate each supply chain partner’s ordering risk. Optimal order strategies of both manufactures and retailers in a supply chain under a bidirectional option contract are analysed in this paper. We find the manufacturer’s optimal production quantity is positively affected by penalty price in the contract and its bounds are given by simulation analysis. Our findings in this paper indicate that the proposed coordination mechanism with bidirectional option contract is profitable to all supply chain partners in long-term transactions. Meanwhile, the coordination mechanism helps the supply chain partners to catch up with marketing fluctuations and enhances the supply chain trust and partnerships. Finally, some simulation experiments are employed to obtain more observations.
Journal: International Journal of Production Research
Pages: 2068-2082
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1269970
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1269970
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: Simulation-based ripple effect modelling in the supply chain
Abstract: 
 In light of low-frequency/high-impact disruptions, the ripple effect has recently been introduced into academic literature on supply chain management. The ripple effect in the supply chain results from disruption propagation from the initial disruption point to the supply, production and distribution networks. While optimisation modelling dominates this research field, the potential of simulation modelling still remains under-explored. The objective of this study is to reveal research gaps that can be closed with the help of simulation modelling. First, recent literature on both optimisation and simulation modelling is analysed. Second, a simulation model for multi-stage supply chain design with consideration of capacity disruptions and experimental results is presented in order to depict major areas of simulation application to the ripple effect modelling. Based on both literature analysis and the modelling example, managerial insights and future research areas are identified in regard to simulation modelling application to the ripple effect analysis in the supply chain. The paper concludes by summarising the most important insights and outlining a future research agenda.
Journal: International Journal of Production Research
Pages: 2083-2101
Issue: 7
Volume: 55
Year: 2017
Month: 4
X-DOI: 10.1080/00207543.2016.1275873
File-URL: http://hdl.handle.net/10.1080/00207543.2016.1275873
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Template-Type: ReDIF-Article 1.0
Author-Name: Kostas Selviaridis
Author-X-Name-First: Kostas
Author-X-Name-Last: Selviaridis
Author-Name: Finn Wynstra
Author-X-Name-First: Finn
Author-X-Name-Last: Wynstra
Title: Performance-based contracting: a literature review and future research directions
Abstract: 
 This paper aims to provide a review and synthesis of the performance-based contracting (PBC) literature across academic disciplines. It also seeks to examine how the operations and supply management (OSM) discipline in particular relates to PBC studies in other study fields. The research is based on a systematic literature review of 241 peer-reviewed articles across disciplines, published between 1985 and 2014. A classification framework of PBC research is proposed, addressing key aspects of PBC design and management: performance specification and evaluation, the design of incentives and their impact on supplier behaviour and risks allocation depending also on the risk attitudes of buyers and suppliers. The comparative analysis of literature by discipline helps identify current empirical and theoretical limitations of relevant OSM studies. The paper concludes that future OSM research should expand its theoretical framework and empirical focus to better understand PBC design and management. Eight specific suggestions for future OSM research are offered, e.g. examining the potential of PBC as means for managing sustainability and innovation goals of supply chains. The paper helps advance OSM research in this area by providing a structured overview of definitions, theories, conceptual frames, methods and empirical studies from other disciplines.
Journal: International Journal of Production Research
Pages: 3505-3540
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.978031
File-URL: http://hdl.handle.net/10.1080/00207543.2014.978031
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Template-Type: ReDIF-Article 1.0
Author-Name: L.X. Cui
Author-X-Name-First: L.X.
Author-X-Name-Last: Cui
Title: Towards optimal configuration of a manufacturer’s supply network with demand flexibility
Abstract: 
 Demand flexibility exhibits the degree to which customers are often willing to compromise on product features or performance levels for budgetary (reflected in price) or schedule (reflected in delivery) reasons. It is essential for a manufacturer to map demand flexibility into the supply side and investigate its impact on supply network configuration to maximise its total profit. This paper is among the first contributions that seek to address the challenge of optimal configuration of a manufacturer’s supply network that consists of raw material suppliers and contract manufacturers, considering demand flexibility and commonality among different product families. A new mixed integer programming model is developed to describe the characteristics of this problem. The objective was to maximise the manufacturer’s total profit subject to various operating constraints of the supply chain. In view of the complexity and non-deterministic polynomial-time (NP)-hard nature of the problem, a hybrid constraint programming and simulated annealing algorithm is proposed to solve the problem optimally. Extensive numerical studies are conducted to validate the effectiveness of the proposed model and the hybrid algorithm.
Journal: International Journal of Production Research
Pages: 3541-3560
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.980011
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980011
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Template-Type: ReDIF-Article 1.0
Author-Name: Simone Zanoni
Author-X-Name-First: Simone
Author-X-Name-Last: Zanoni
Author-Name: Mohamad Y. Jaber
Author-X-Name-First: Mohamad Y.
Author-X-Name-Last: Jaber
Title: A two-level supply chain with consignment stock agreement and stock-dependent demand
Abstract: 
 This paper presents a vendor-managed inventory (VMI) with consignment stock (CS) policy applied to the integrated vendor–buyer system, where the demand at the buyer side is stock dependent. Under the VMI with CS, the vendor manufactures a product and delivers it in batches of equal sizes to the buyer: although the goods are in the warehouse of the buyer, they remain to be the property of the vendor until the buyer registers a withdrawal. The products delivered are presented to the end customers in a display area and the demand is assumed to be positively dependent on the number of items displayed. Moreover, the model proposed considers that the product display area is replenished once its inventory level hits a given minimum. The paper investigates and compares different policies that may be adopted to exploit the advantages offered by the consignment stock agreement when stock dependent demand at the buyer side is considered.
Journal: International Journal of Production Research
Pages: 3561-3572
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.980012
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980012
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Template-Type: ReDIF-Article 1.0
Author-Name: Kaida Qin
Author-X-Name-First: Kaida
Author-X-Name-Last: Qin
Author-Name: Frank Youhua Chen
Author-X-Name-First: Frank Youhua
Author-X-Name-Last: Chen
Author-Name: Lijun Ma
Author-X-Name-First: Lijun
Author-X-Name-Last: Ma
Title: Cutting down the travel distance of put systems at Kunming International Flower Auction Market
Abstract: 
 At Kunming International Flower Auction Market (KIFA), about 2.5 million cut flowers traded in 10,000 transactions need to be distributed daily to buyers in its distribution area. Small lots and many buyers per trolley are two distinctive features at KIFA and the identities of the buyers and their demands are not known in advance. The growing transaction volume has recently increased the distribution workforce and the buyers’ waiting time. In this paper, we introduce a modified class-based location policy using KIFA’s historical data to improve its current put system performance. We use the closest-open location method in each class area, which improves the put system performance at KIFA. We examine the effects of the distribution area shape and the number of blocks in each class area on performance measures, and find that KIFA’s put system performance can be further improved.
Journal: International Journal of Production Research
Pages: 3573-3585
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.980013
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980013
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Template-Type: ReDIF-Article 1.0
Author-Name: Gülşen Aydın Keskin
Author-X-Name-First: Gülşen Aydın
Author-X-Name-Last: Keskin
Title: Using integrated fuzzy DEMATEL and fuzzy C: means algorithm for supplier evaluation and selection
Abstract: 
 Decision-making techniques are used to help evaluate the current suppliers’ aim at classifying performance of individual suppliers against desired levels of performance, so as to design suitable plans to increase the performance and capabilities of suppliers. In this study, an integrated model is introduced and proposed for increasing the supplier selection and evaluation quality. The methodology is composed of two steps. The first stage is fuzzy decision-making trial and evaluation laboratory method in which the interactions between the evaluation criteria and the criteria weight have been computed. At the second stage, performances of suppliers are assessed using both the criteria weights obtained at the first stage and fuzzy c-means clustering algorithm by classifying the vendors according to their performances. Obtained results show that the proposed model is very well suited as a decision-making tool for supplier selection decisions.
Journal: International Journal of Production Research
Pages: 3586-3602
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.980461
File-URL: http://hdl.handle.net/10.1080/00207543.2014.980461
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Template-Type: ReDIF-Article 1.0
Author-Name: J. Sicilia
Author-X-Name-First: J.
Author-X-Name-Last: Sicilia
Author-Name: M. González-De-la-Rosa
Author-X-Name-First: M.
Author-X-Name-Last: González-De-la-Rosa
Author-Name: J. Febles-Acosta
Author-X-Name-First: J.
Author-X-Name-Last: Febles-Acosta
Author-Name: D. Alcaide-López-de-Pablo
Author-X-Name-First: D.
Author-X-Name-Last: Alcaide-López-de-Pablo
Title: Optimal inventory policies for uniform replenishment systems with time-dependent demand
Abstract: 
 This study develops an analysis of lot size inventory systems where the replenishment rate is uniform and demand follows a power demand pattern. Shortages are not allowed. Holding cost, replenishing cost and purchasing cost are considered in inventory system control. The objective of the study is to find the economic production quantity that minimises total inventory cost per unit of time. We conclude that optimal inventory policies depend on the demand pattern index chosen to represent customer demand. Theoretical results are illustrated with a business case study. A sensitivity analysis is proposed to describe the optimal policy behaviour.
Journal: International Journal of Production Research
Pages: 3603-3622
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.983618
File-URL: http://hdl.handle.net/10.1080/00207543.2014.983618
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei Liu
Author-X-Name-First: Wei
Author-X-Name-Last: Liu
Author-Name: Shiji Song
Author-X-Name-First: Shiji
Author-X-Name-Last: Song
Author-Name: Bing Li
Author-X-Name-First: Bing
Author-X-Name-Last: Li
Author-Name: Cheng Wu
Author-X-Name-First: Cheng
Author-X-Name-Last: Wu
Title: A periodic review inventory model with loss-averse retailer, random supply capacity and demand
Abstract: 
 This paper studies a periodic review inventory model with random supply capacity and demand, where the retailer is loss-averse. For the single-period problem, it is shown that the retailer will not order unless the initial inventory level is less than a critical value, and the order-up-to level is generally not a constant. Moreover, the critical value and optimal order quantity are only dependent on the random demand and independent on the random capacity. We also investigate the impacts of loss aversion, price and cost on the optimal order quantity and maximum expected utility. Then a dynamic programming approach is used to analyse the retailer’s ordering policy in the multi-period case. In each period, if the initial inventory level is above a given value, an order will not be placed. Otherwise, the upper bound on the optimal order quantity is given. The numerical experiments are conducted to illustrate the optimal ordering policies.
Journal: International Journal of Production Research
Pages: 3623-3634
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.985391
File-URL: http://hdl.handle.net/10.1080/00207543.2014.985391
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Template-Type: ReDIF-Article 1.0
Author-Name: Yen-Ting Lin
Author-X-Name-First: Yen-Ting
Author-X-Name-Last: Lin
Author-Name: Ying-Ju Chen
Author-X-Name-First: Ying-Ju
Author-X-Name-Last: Chen
Title: Competitive outsourcing: choosing between value-added services and key component supplying capability
Abstract: 
 We examine outsourcing strategies of two competing firms. Each of the firms outsources product manufacturing to one of the two manufacturers. In addition to product manufacturing, the first manufacturer also produces a key component that is required by every product. On the other hand, the second manufacturer provides additional services that enhance product value. We characterise the firms’ equilibrium choice of outsourced manufacturers. We demonstrate that difference in the manufacturers’ operational advantages can result in asymmetric outsourcing decisions for ex-ante symmetric firms. Firm profitability can be Pareto improved when the manufacturer who produces the key component gains first-mover advantage. Moreover, that manufacturer can benefit from the entrance of a competitor in the key component market. Finally, even though the firms select their outsourced manufacturers based on self-interest, the resulting equilibrium outsourcing scenario can be the one that also maximises profitability of the manufacturers and the entire supply chain.
Journal: International Journal of Production Research
Pages: 3635-3650
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.985394
File-URL: http://hdl.handle.net/10.1080/00207543.2014.985394
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Template-Type: ReDIF-Article 1.0
Author-Name: Leandro C. Coelho
Author-X-Name-First: Leandro C.
Author-X-Name-Last: Coelho
Author-Name: Gilbert Laporte
Author-X-Name-First: Gilbert
Author-X-Name-Last: Laporte
Title: An optimised target-level inventory replenishment policy for vendor-managed inventory systems
Abstract: 
 In vendor-managed inventory (VMI) systems the supplier is responsible for replenishing customers and for deciding when and how much to deliver. One of two inventory policies is typically employed by the supplier. The first one, called the maximum level (ML) policy, gives full freedom to the supplier to deliver any quantity as long as it respects customer inventory capacities. The alternative, which is more constrained, is called the order-up-to (OU) policy. It states that the supplier has to bring the customer inventory up to its maximum capacity level upon delivery. We propose a new tactical policy in the context of VMI systems, called optimised target-level (OTL), under which when the supplier visits a customer, the quantity delivered is such that the final inventory will always be at the same customer-dependent OTL. We perform a computational evaluation of this new policy against both traditional strategies on benchmark instances. We show that it yields lower costs and inventory levels than the OU policy, and is only marginally more expensive than the ML policy, while being easier to implement.
Journal: International Journal of Production Research
Pages: 3651-3660
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.986299
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986299
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:12:p:3651-3660




Template-Type: ReDIF-Article 1.0
Author-Name: José Crispim
Author-X-Name-First: José
Author-X-Name-Last: Crispim
Author-Name: Nazaré Rego
Author-X-Name-First: Nazaré
Author-X-Name-Last: Rego
Author-Name: Jorge Pinho de Sousa
Author-X-Name-First: Jorge
Author-X-Name-Last: Pinho de Sousa
Title: Stochastic partner selection for virtual enterprises: a chance-constrained approach
Abstract: 
 A virtual enterprise (VE) is a temporary organisation that pools the core competencies of its member enterprises in order to exploit fast-changing market opportunities. Making successful collaborative partnerships is, in this context, a major challenge in today’s competitive business environments. The success of such a ‘virtual’ organisation is strongly dependent on its composition, and the selection of partners becomes therefore a crucial issue. This problem is particularly difficult because of the uncertainties related to information, market dynamics, customer expectations and technology speed-up, with a strongly stochastic decision-making context. In this paper, a chance-constrained approach to rank alternative VE configurations in business environments with uncertainty, and vague and random information, is proposed. This approach is based on a two-stage model: a chance-constraint multi-objective directional Tabu Search metaheuristic, complemented by a 2-tuple fuzzy linguistic representation model. Preliminary computational results clearly demonstrate the potential of the approach for practical application.
Journal: International Journal of Production Research
Pages: 3661-3677
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.986301
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986301
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Template-Type: ReDIF-Article 1.0
Author-Name: Fuguo Zhao
Author-X-Name-First: Fuguo
Author-X-Name-Last: Zhao
Author-Name: Desheng Dash Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Dash Wu
Author-Name: Liang Liang
Author-X-Name-First: Liang
Author-X-Name-Last: Liang
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Cash flow risk in dual-channel supply chain
Abstract: 
 This paper focuses on multi-period cash flow risk which is measured by the SD in dual-channel supply chain. The manufacturer offers a consignment contract to the retailer, exposing cash flow risk due to the payment delay. We analyze cash inflows, outflows, and netflows of each member in dual-channel supply chain. We also examine different influencing factors on the preference of cash flows in dual-channel supply chain and then provide some managerial implications to deal with cash flow risk.
Journal: International Journal of Production Research
Pages: 3678-3691
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.986302
File-URL: http://hdl.handle.net/10.1080/00207543.2014.986302
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:12:p:3678-3691




Template-Type: ReDIF-Article 1.0
Author-Name: Meimei Zheng
Author-X-Name-First: Meimei
Author-X-Name-Last: Zheng
Author-Name: Yan Shu
Author-X-Name-First: Yan
Author-X-Name-Last: Shu
Author-Name: Kan Wu
Author-X-Name-First: Kan
Author-X-Name-Last: Wu
Title: On optimal emergency orders with updated demand forecast and limited supply
Abstract: 
 This study analyses a two-stage newsvendor system with a regular and an emergency order. The emergency order can be placed at a later time based on a more accurate demand forecast. However, the unit cost for the emergency order is higher, and the quantity is limited. To maximise the expected profit, a retailer should determine both regular and emergency order quantities by considering the demand forecast updating, ordering cost and quantity constraint. Using dynamic programming, optimal ordering quantities are derived, and properties of the optimal solutions are obtained. Numerical experiments are carried out to illustrate the effect of the emergency order on the ordering decisions and expected profit. Some managerial insights are gained from the numerical results.
Journal: International Journal of Production Research
Pages: 3692-3719
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.987882
File-URL: http://hdl.handle.net/10.1080/00207543.2014.987882
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Template-Type: ReDIF-Article 1.0
Author-Name: Shailesh Kulkarni
Author-X-Name-First: Shailesh
Author-X-Name-Last: Kulkarni
Author-Name: Subramaniam Ponnaiyan
Author-X-Name-First: Subramaniam
Author-X-Name-Last: Ponnaiyan
Author-Name: Hakan Tarakci
Author-X-Name-First: Hakan
Author-X-Name-Last: Tarakci
Title: Optimal ordering decisions under two returns policies
Abstract: 
 To avoid stockouts and maintain product availability, retailers typically carry excess units and subsequently incur higher cost. In case of style/fashion goods, demand forecasting is extremely difficult due to short selling cycles. The purpose of this study was to minimise the cost of excess stocking without compromising product availability. To achieve these conflicting objectives, our study includes two ordering instances and two returns policies. The time between orders subsequently helps resolve demand uncertainty. Existing studies consider only one type of returns policy, that is, returns on the entire purchase quantity; whereas our study considers two types of returns policies: returns on the first order size and returns on the entire purchase quantity. This study also includes models for the retailer and the supply chain system. Analytical and numerical insights into our study enable the retailer to select his appropriate returns policies to maximise his as well as system’s expected profits. We also show that perfect coordination of partners will help them improve their profits considerably.
Journal: International Journal of Production Research
Pages: 3720-3734
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.988883
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988883
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Template-Type: ReDIF-Article 1.0
Author-Name: Erbao Cao
Author-X-Name-First: Erbao
Author-X-Name-Last: Cao
Author-Name: Xiushuai Zhou
Author-X-Name-First: Xiushuai
Author-X-Name-Last: Zhou
Author-Name: Kevin Lϋ
Author-X-Name-First: Kevin
Author-X-Name-Last: Lϋ
Title: Coordinating a supply chain under demand and cost disruptions
Abstract: 
 In this paper, we investigate the coordination of a supply chain consisting of one manufacturer and n Bertrand competing retailers under disruptions of market demand and production cost. We present a coordination model of a supply chain under normal scenarios. Our findings demonstrate that the coordination scheme designed for the initial production plan should be revised when disruptions of market demand and production cost occur. To resolve this issue, we consider the possible deviation costs caused by disruptions and propose optimal decision models for different disruptions under centralised decision-making. We present an improved revenue-sharing contract model to coordinate the decentralised supply chain under disruptions. The proposed models are then further analysed through numerical examples.
Journal: International Journal of Production Research
Pages: 3735-3752
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.988885
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988885
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Template-Type: ReDIF-Article 1.0
Author-Name: Shaofu Du
Author-X-Name-First: Shaofu
Author-X-Name-Last: Du
Author-Name: Jiaang Zhu
Author-X-Name-First: Jiaang
Author-X-Name-Last: Zhu
Author-Name: Huifang Jiao
Author-X-Name-First: Huifang
Author-X-Name-Last: Jiao
Author-Name: Wuyi Ye
Author-X-Name-First: Wuyi
Author-X-Name-Last: Ye
Title: Game-theoretical analysis for supply chain with consumer preference to low carbon
Abstract: 
 This paper focuses on the impact of consumers’ preference to low carbon in the emission-concerned supply chain. In an emission-concerned supply chain, the consumers are assumed to prefer to low-carbon products. In an emission sensitive market, emission reduction not only brings the higher production costs but also stimulates the inverse demand function. Therefore, this may be an opportunity for players of the supply chain to coordinate their two objectives: environmental pressure (to reduce carbon emissions for environment protection) and profit-seeking, which intuitively seem to be contradictory. In order to address this research focus, a novel emission-sensitive demand function is adopted, and an emission -sensitive cost function is introduced explicitly to capture the deviation production cost caused by emission reduction. Then the decision-making of each member in the emission-concerned supply chain is investigated. We find that the decision-maker of the supply chain will choose different emission reduction strategies for different cases. An inspiring result shows that the channel profit as well as the emission reduction increase in the consumers’ preference to low-carbon consumption simultaneously in particular cases. Moreover, several emission-concerned contracts are designed to coordinate the channel. Another finding is that the manufacturer’s optimal carbon emissions per unit product keeps the same as the centralised channel, no matter whether the supply chain is coordinated or not. Furthermore, the further discussion reveals that less eco-friendly production than the traditional, if lack of external regulation as well as internal moral self-discipline, might be chosen under some specific conditions.
Journal: International Journal of Production Research
Pages: 3753-3768
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.988888
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988888
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Template-Type: ReDIF-Article 1.0
Author-Name: Reza Zanjirani Farahani
Author-X-Name-First: Reza Zanjirani
Author-X-Name-Last: Farahani
Author-Name: Hannaneh Rashidi Bajgan
Author-X-Name-First: Hannaneh
Author-X-Name-Last: Rashidi Bajgan
Author-Name: Behnam Fahimnia
Author-X-Name-First: Behnam
Author-X-Name-Last: Fahimnia
Author-Name: Mohamadreza Kaviani
Author-X-Name-First: Mohamadreza
Author-X-Name-Last: Kaviani
Title: Location-inventory problem in supply chains: a modelling review
Abstract: 
 A location-inventory problem (LIP) aims to integrate strategic supply chain design decisions with tactical and operational inventory management decisions. This study provides an extensive review of the existing literature of LIP modelling. A mathematical model is presented for a basic LIP, which can be further developed to incorporate additional features for use in real-world scenarios. We also discuss the evolution of LIP modelling literature over the past three decades and provide summary tables outlining characteristics of the published works including key modelling attributes and objective function cost components. Additional classifications are completed based on the solution methods adopted and real-world applications investigated. Our observations provide important insights and identify potential directions for future research in the field.
Journal: International Journal of Production Research
Pages: 3769-3788
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.988889
File-URL: http://hdl.handle.net/10.1080/00207543.2014.988889
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoyan Zhu
Author-X-Name-First: Xiaoyan
Author-X-Name-Last: Zhu
Author-Name: Sila Cetinkaya
Author-X-Name-First: Sila
Author-X-Name-Last: Cetinkaya
Title: A stochastic inventory model for an immediate liquidation and price-promotion decision under price-dependent demand
Abstract: 
 We consider a periodic review stochastic inventory system where the current on-hand inventory exceeds the maximum supply needs in the future. Consequently, one must make an immediate inventory liquidation decision on the liquidation quantity and promotional price with the goal of maximising the overall profit where the demand during the liquidation period (DDLP) is a random variable whose distribution depends on the promotional price. We develop a price-dependent DDLP model and an inventory model for optimising the liquidation quantity and unit promotional price. The model is applicable for general distributions of the DDLP and regular demand (i.e. demand during the future periods following the promotion period). We also investigate four special cases where the DDLP and regular demand are assumed to be either exponential or uniform random variables. The two models that assume the exponential distribution for regular demand can be examined analytically and simplified using the mathematical properties we derive. The additional two models that assume the uniform distribution for regular demand do not have closed-form expressions but can be solved numerically. Some numerical examples are presented for further elaboration of the models and to demonstrate their practical use.
Journal: International Journal of Production Research
Pages: 3789-3809
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.990233
File-URL: http://hdl.handle.net/10.1080/00207543.2014.990233
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:12:p:3789-3809




Template-Type: ReDIF-Article 1.0
Author-Name: Nadjib Brahimi
Author-X-Name-First: Nadjib
Author-X-Name-Last: Brahimi
Author-Name: Tarik Aouam
Author-X-Name-First: Tarik
Author-X-Name-Last: Aouam
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Title: Integrating order acceptance decisions with flexible due dates in a production planning model with load-dependent lead times
Abstract: 
 We consider a tactical planning problem, which integrates production planning decisions together with order acceptance decisions, while taking into account the dependency between workload and lead times. The proposed model determines which orders to accept and in which period they should be produced, so that they can be delivered to the customer within the acceptable flexible due dates. When the number of accepted orders increases, the workload and production lead time also increase, and this may result in the possibility of missing customer due dates. This problem is formulated as a mixed integer linear programme for which two relax-and-fix heuristic solution methods are proposed. The first one decomposes the problem based on time periods, while the second decomposes it based on orders. The performances of these heuristics are compared with that of a state-of-the-art commercial solver. Our results show that the time-based relax-and-fix heuristic outperforms the order-based relax-and-fix heuristic, and the solver solution as it yields better integrality gaps for much less CPU effort.
Journal: International Journal of Production Research
Pages: 3810-3822
Issue: 12
Volume: 53
Year: 2015
Month: 6
X-DOI: 10.1080/00207543.2014.993045
File-URL: http://hdl.handle.net/10.1080/00207543.2014.993045
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Template-Type: ReDIF-Article 1.0
Author-Name: Bertrand Hellion
Author-X-Name-First: Bertrand
Author-X-Name-Last: Hellion
Author-Name: Fabien Mangione
Author-X-Name-First: Fabien
Author-X-Name-Last: Mangione
Author-Name: Bernard Penz
Author-X-Name-First: Bernard
Author-X-Name-Last: Penz
Title: Stability contracts between supplier and retailer: a new lot sizing model
Abstract: 
 This work explores the relationship between decision-makers in a company and their suppliers using stability contracts. This relationship can be modelled as a capacitated multi-machine lot sizing problem with minimum order quantity and dynamic time windows, where orders are represented by production levels. Both the amount and the frequency of orders are constrained, the first by upper and lower bounding and the second by dynamic time windows. A mathematical model is provided and an experimental analysis is conducted. A cost study highlights that using proper stability contracts in certain condition can reduce the storage cost of the retailer, improving the whole supply chain efficiency. Conclusions are given leading to insight for decision-makers and contract designers.
Journal: International Journal of Production Research
Pages: 1-12
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.919419
File-URL: http://hdl.handle.net/10.1080/00207543.2014.919419
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Template-Type: ReDIF-Article 1.0
Author-Name: Abhishek Chakraborty
Author-X-Name-First: Abhishek
Author-X-Name-Last: Chakraborty
Author-Name: A.K. Chatterjee
Author-X-Name-First: A.K.
Author-X-Name-Last: Chatterjee
Author-Name: Arqum Mateen
Author-X-Name-First: Arqum
Author-X-Name-Last: Mateen
Title: A vendor-managed inventory scheme as a supply chain coordination mechanism
Abstract: 
 In this paper, we have considered a vendor-managed inventory (VMI) arrangement in a supply chain (SC), where the buyer imposes a penalty for shipments exceeding an upper limit. We have shown as how the industry practice of VMI under penalty can be used as a SC coordination mechanism. The vendor can influence the buyer to increase the batch size without making the buyer worse off. We also discuss how such a penalty scheme may be derived. Further, we have established the equivalence of VMI under deterministic demand with that of quantity discount models, thus highlighting the need to incorporate both cooperation and coordination perspectives while analysing SC collaboration mechanisms.
Journal: International Journal of Production Research
Pages: 13-24
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.921350
File-URL: http://hdl.handle.net/10.1080/00207543.2014.921350
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Template-Type: ReDIF-Article 1.0
Author-Name: Xumei Zhang
Author-X-Name-First: Xumei
Author-X-Name-Last: Zhang
Author-Name: Xiaopeng Han
Author-X-Name-First: Xiaopeng
Author-X-Name-Last: Han
Author-Name: Xiangyu Liu
Author-X-Name-First: Xiangyu
Author-X-Name-Last: Liu
Author-Name: Ru Liu
Author-X-Name-First: Ru
Author-X-Name-Last: Liu
Author-Name: Jinzhong Leng
Author-X-Name-First: Jinzhong
Author-X-Name-Last: Leng
Title: The pricing of product and value-added service under information asymmetry: a product life cycle perspective
Abstract: 
 Facing fierce competition in the global manufacturing industry, manufacturers have begun developing value-added services to increase their competitiveness. One type of sales strategy that has become prevalent is for companies to offer consumers, a relatively low price for value-added services when consumers buy the services simultaneously with the product and a relatively high price for the same value-added services in the future. Considering the degree of information asymmetry about service quality and the changes of it in a product life cycle, this paper examines the pricing of product and value-added service. Four types of pricing strategies are proposed that depend on the time that consumers choose to buy the value-added service. In addition, the results of our study show that a manufacturer choosing a pricing strategy should consider the degree of information asymmetry and consumers’ initial expectations regarding the value-added service quality. When consumers’ initial expectations regarding the value-added service quality are high, the manufacturer should choose one of the four pricing strategies that encourage consumers to buy the service simultaneously with the product. When consumers’ initial expectations regarding the value-added service quality are low, the optimal strategy for the manufacturer depends on the difference in the degree of information asymmetry.
Journal: International Journal of Production Research
Pages: 25-40
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.922707
File-URL: http://hdl.handle.net/10.1080/00207543.2014.922707
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Template-Type: ReDIF-Article 1.0
Author-Name: M. Fattahi
Author-X-Name-First: M.
Author-X-Name-Last: Fattahi
Author-Name: M. Mahootchi
Author-X-Name-First: M.
Author-X-Name-Last: Mahootchi
Author-Name: S.M. Moattar Husseini
Author-X-Name-First: S.M.
Author-X-Name-Last: Moattar Husseini
Author-Name: E. Keyvanshokooh
Author-X-Name-First: E.
Author-X-Name-Last: Keyvanshokooh
Author-Name: F. Alborzi
Author-X-Name-First: F.
Author-X-Name-Last: Alborzi
Title: Investigating replenishment policies for centralised and decentralised supply chains using stochastic programming approach
Abstract: 
 In this paper, a multiple period replenishment problem based on (s, S) policy is investigated for a supply chain (SC) comprising one retailer and one manufacturer with uncertain demand. Novel mixed-integer linear programming (MILP) models are developed for centralised and decentralised decision-making modes using two-stage stochastic programming. To compare these decision-making modes, a Monte Carlo simulation is applied to the optimization models’ policies. To deal with demand uncertainty, scenarios are generated using Latin Hypercube Sampling method and their number is reduced by a scenario reduction technique. In large test problems, where CPLEX solver is not able to reach an optimal solution in the centralised model, evolutionary strategies (ES) and imperialist competitive algorithm (ICA) are applied to find near optimal solutions. Sensitivity analysis is conducted to show the performance of the proposed mathematical models. Moreover, it is demonstrated that both ES and ICA provide acceptable solutions compared to the exact solutions of the MILP model. Finally, the main parameters affecting difference between profits of centralised and decentralised SCs are investigated using the simulation method.
Journal: International Journal of Production Research
Pages: 41-69
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.922710
File-URL: http://hdl.handle.net/10.1080/00207543.2014.922710
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Template-Type: ReDIF-Article 1.0
Author-Name: Hefu Liu
Author-X-Name-First: Hefu
Author-X-Name-Last: Liu
Author-Name: Weiling Ke
Author-X-Name-First: Weiling
Author-X-Name-Last: Ke
Author-Name: Kwok Kee Wei
Author-X-Name-First: Kwok Kee
Author-X-Name-Last: Wei
Author-Name: Zhengsheng Hua
Author-X-Name-First: Zhengsheng
Author-X-Name-Last: Hua
Title: Influence of power and trust on the intention to adopt electronic supply chain management in China
Abstract: 
 Electronic supply chain management (eSCM) has become a popular Web-based seamless supply chain process. Given that Chinese firms are important parts of global supply chains, it is imperative to investigate factors that would affect eSCM adoption in China. In this study, we examine the impact of three power sources – non-mediated, coercive-mediated and reward-mediated power – on the three dimensions of trust – competence, goodwill and contractual – and their influence in turn on a firm’s eSCM adoption intention in China. We collected data through a survey of 131 manufacturing and service firms in China. Our results show that non-mediated power is positively associated with competence and goodwill trust but negatively related to contractual trust. Coercive-mediated power only negatively affects competence and goodwill trust. Reward-mediated power does not affect any type of trust significantly. The results also provide empirical support for the positive effects of competence and contractual trust on the intention to adopt eSCM. This paper contributes knowledge about the power–trust relationship in China from a supply chain perspective and presents a multi-dimensional explanation of the relationships between power, trust and intention to adopt eSCM.
Journal: International Journal of Production Research
Pages: 70-87
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.922711
File-URL: http://hdl.handle.net/10.1080/00207543.2014.922711
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Template-Type: ReDIF-Article 1.0
Author-Name: Salma Karray
Author-X-Name-First: Salma
Author-X-Name-Last: Karray
Author-Name: Saman Hassanzadeh Amin
Author-X-Name-First: Saman Hassanzadeh
Author-X-Name-Last: Amin
Title: Cooperative advertising in a supply chain with retail competition
Abstract: 
 This research assesses the effects of cooperative (coop) advertising in a channel with competing retailers considering both advertising and pricing as decision variables. We develop a game-theoretic model and provide equilibrium solutions for two games. In Game 1, the manufacturer and the retailers do not use cooperative advertising (status quo); and in Game 2, coop advertising is implemented. We also obtain optimal solutions for the case where the channel is coordinated. Contrary to the results provided for one-manufacturer, one-retailer channels, we find that coop advertising may not be profitable for the retailers or for the channel, especially when the market is characterised by low levels of price competition and high advertising competition between retailers. Although it benefits the manufacturer, the total effect of cooperative advertising on the channel profit might be negative under such conditions. The results also show that coop advertising stimulates retailers’ spending but may result in lower advertising expenditures than for a fully coordinated channel. Finally, when coop advertising benefits the entire channel, it does not fully achieve results from vertical integration.
Journal: International Journal of Production Research
Pages: 88-105
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.925602
File-URL: http://hdl.handle.net/10.1080/00207543.2014.925602
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:1:p:88-105




Template-Type: ReDIF-Article 1.0
Author-Name: Seung Ho Yoo
Author-X-Name-First: Seung Ho
Author-X-Name-Last: Yoo
Author-Name: DaeSoo Kim
Author-X-Name-First: DaeSoo
Author-X-Name-Last: Kim
Author-Name: Myung-Sub Park
Author-X-Name-First: Myung-Sub
Author-X-Name-Last: Park
Title: Pricing and return policy under various supply contracts in a closed-loop supply chain
Abstract: 
 This study investigates pricing and return policies under various supply contracts in a closed-loop supply chain in which a supplier has more bargaining power than a retailer. We develop integrated supply contract models based on the principal–agent paradigm. Specifically, the supplier with more bargaining power devises a supply contract, acting as a Stackelberg leader. Then, given the contract offer, the retailer decides on pricing and return policies which affect consumers’ demand and return behaviours. We look into three commonly used supply contracts, i.e. wholesale price, buy-back and quantity discount contracts. The main purpose of this study is to explore how each supply contract affects the retailer’s decision on pricing and return policies, which in turn influence the profits of the entire supply chain and of its members. In doing so, we focus on investigating which contract coordinates the supply chain involving the retailer’s moral hazard. Through analytic comparison of contracts and extensive numerical analyses, we present numerous propositions to enrich the body of knowledge in the closed-loop supply chain and to provide meaningful decision guidelines to the practice.
Journal: International Journal of Production Research
Pages: 106-126
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.932927
File-URL: http://hdl.handle.net/10.1080/00207543.2014.932927
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:1:p:106-126




Template-Type: ReDIF-Article 1.0
Author-Name: Hubert Pun
Author-X-Name-First: Hubert
Author-X-Name-Last: Pun
Author-Name: H. Sebastian Heese
Author-X-Name-First: H. Sebastian
Author-X-Name-Last: Heese
Title: Controlling a supplier’s subcontracting decisions through contractual enforcement or economic incentives
Abstract: 
 Suppliers often subcontract part of their workload to other suppliers, and manufacturers might suffer severe consequences if they do not anticipate their suppliers’ incentives to subcontract. In this paper, we study the case where a manufacturer outsources two tasks to a top-tier supplier. The manufacturer must decide whether it should design a contract that enforces that the different tasks are completed by the appropriate suppliers, and when it is preferable to use economic incentives to manipulate the top-tier supplier’s subcontracting behaviour. We find that when the cost difference between suppliers of different tiers is small and the correlation between the risks associated with the two tasks is minimal, the manufacturer can benefit from designing a contract that ensures the preferred subcontracting behaviour, if the cost of enforcing such a contract is not too high. However, when such enforcement cost is substantial, the manufacturer might be better off manipulating the top-tier supplier’s economic incentives.
Journal: International Journal of Production Research
Pages: 127-140
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.939242
File-URL: http://hdl.handle.net/10.1080/00207543.2014.939242
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Template-Type: ReDIF-Article 1.0
Author-Name: Debabrata Das
Author-X-Name-First: Debabrata
Author-X-Name-Last: Das
Author-Name: Pankaj Dutta
Author-X-Name-First: Pankaj
Author-X-Name-Last: Dutta
Title: Design and analysis of a closed-loop supply chain in presence of promotional offer
Abstract: 
 Closed-loop supply chain (CLSC) has been an area of increasing attention during the last decade due to its economic impact, strict legislations and social awareness. Profitability of any remanufacturing process is mainly driven by the effective and efficient acquisition of used products. In this paper, a market-driven recovery framework is proposed to acquire the used products from consumers by taking into account their buying patterns as well as the willingness to accept a promotional offer. The proposed framework is integrated with an optimisation model for a multi-period CLSC to maximise the overall profit of the system by determining the optimal discount amount along with the decision of finding optimal manufacturing, remanufacturing and disposal quantity. The findings of the study provide several insights to the decision-makers that lead to better performance of the entire closed-loop system. The analysis suggests a trade-off among manufacturing/remanufacturing cost, penalty cost for not fulfilling the legislation criterion and collection cost due to the employment of promotional offer. Sensitivity analysis is performed to observe the effect of various important parameters on the system’s performance. Finally, a comparative study has been conducted to examine the performance of the CLSC with vs. without promotional offer.
Journal: International Journal of Production Research
Pages: 141-165
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.942007
File-URL: http://hdl.handle.net/10.1080/00207543.2014.942007
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Template-Type: ReDIF-Article 1.0
Author-Name: Desirée Knoppen
Author-X-Name-First: Desirée
Author-X-Name-Last: Knoppen
Author-Name: Melek Akın Ateş
Author-X-Name-First: Melek Akın
Author-X-Name-Last: Ateş
Author-Name: Alistair Brandon-Jones
Author-X-Name-First: Alistair
Author-X-Name-Last: Brandon-Jones
Author-Name: Davide Luzzini
Author-X-Name-First: Davide
Author-X-Name-Last: Luzzini
Author-Name: Erik van Raaij
Author-X-Name-First: Erik
Author-X-Name-Last: van Raaij
Author-Name: Finn Wynstra
Author-X-Name-First: Finn
Author-X-Name-Last: Wynstra
Title: A comprehensive assessment of measurement equivalence in operations management
Abstract: 
 This paper provides a comprehensive framework for treating equivalence both prior to data collection and during subsequent analyses, and assesses the extent to which equivalence is considered in survey research in six leading empirical Operations Management (OM) journals (Decision Sciences, International Journal of Operations &amp; Production Management, International Journal of Production Research, Journal of Operations Management, Management Science and Production and Operations Management). Measurement equivalence of latent variables in survey data is an important condition that should be met in order to meaningfully pool and/or compare data stemming from apparently heterogeneous sub-groups. We assess 465 survey articles from a six-year period from 2006 to 2011 and document these articles in relation to the four main stages of our comprehensive framework: identifying sources of heterogeneity; maximising equivalence prior to data collection; testing measurement equivalence after data collection; and dealing with partial and non-equivalence. We conclude that pooling of data from heterogeneous sub-groups is common practice in OM, but that awareness and testing of equivalence remains limited. Given these findings, we further elaborate the best practices detected in those few OM studies that do address equivalence in some way. We conclude that to improve the quality of OM survey research, authors, editors and reviewers should pay greater attention to equivalence, and we provide a pragmatic checklist of measurement equivalence issues across the four stages.
Journal: International Journal of Production Research
Pages: 166-182
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.944629
File-URL: http://hdl.handle.net/10.1080/00207543.2014.944629
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Template-Type: ReDIF-Article 1.0
Author-Name: Kai Fu Yuan
Author-X-Name-First: Kai Fu
Author-X-Name-Last: Yuan
Author-Name: Shi Hua Ma
Author-X-Name-First: Shi Hua
Author-X-Name-Last: Ma
Author-Name: Bo He
Author-X-Name-First: Bo
Author-X-Name-Last: He
Author-Name: Yang Gao
Author-X-Name-First: Yang
Author-X-Name-Last: Gao
Title: Inventory decision-making models for a closed-loop supply chain system with different decision-making structures
Abstract: 
 A closed-loop supply chain system with two types of decision-making structures is investigated. The system includes a retailer, a manufacturer, a supplier and a collector, in which the demand of the retailer is fulfilled either by newly manufactured products or by remanufactured products which are as good as the new ones in function and quality. We extend the work of Yuan and Gao [2010. “Inventory Decision-making Models for a Closed-loop Supply Chain System.” International Journal of Production Research 48 (20), 6155–6187.] to the partly centralised decision-making (PCD) structure which consists of A and B type decision-making structures. The system profit-maximisation models are derived and the solution procedures are presented to determine the optimal system policies of A and B type decision-making structures under the (1, R) and (P, 1) polices by the elimination theory. Through the comparative analysis on eight decision-making structures and sensitivity analysis on the return rate, we get the following results: (1) the variation of decision-making structure doesn’t change the choice of the manufacturer policy type on manufacturing and remanufacturing operations for a given return rate; (2) CD structure and CC structure in Yuan and Gao (2010) are two extreme cases of the PCD structure, and the maximum system profits of B type decision-making structure are greater than those of A type decision-making structure; (3) CD system is not the worst decision-making structure to maximise the system profit for specific manufacturer policy type; (4) the maximum system profit of CC system is always greater than those of other decision-making structures; (5) the coordination of different members in the system has various effect on the system profit; (6) B type decision-making structure has more striking effect on the profits of the manufacturer and the retailer than A type decision-making structure, the coordination of the manufacturer and the retailer is the key to maximise the system profit; and (7) for given decision-making structures and manufacturer policy type, the maximum system profit rises with the increase of the return rate.
Journal: International Journal of Production Research
Pages: 183-219
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.946160
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Template-Type: ReDIF-Article 1.0
Author-Name: M. Guajardo
Author-X-Name-First: M.
Author-X-Name-Last: Guajardo
Author-Name: M. Rönnqvist
Author-X-Name-First: M.
Author-X-Name-Last: Rönnqvist
Title: Cost allocation in inventory pools of spare parts with service-differentiated demand classes
Abstract: 
 Holding inventory of spare parts is critical to assure safety and production. In order to save costs, different producers may collaborate through an inventory pool. We consider an inventory pool of spare parts, subject to a service level constraint, where the members of the pool may have different target service levels, so that they represent different demand classes. The pool is implemented either by round-up or rationing policies. The members should agree on how to share the costs. Based on cooperative game theory concepts, we show the important effects that different targets can have in the core stability for this problem. We perform a computational study in a large number of instances, providing insights on the emptiness of the core and the performance of seven allocation methods. We also propose the novel Minimum Deviation from Service Level Referential Cost Method (MIND). This method looks for a stable allocation such that the maximum difference between a cost allocated to a player and its service level referential cost is minimised. The MIND allocation is the solution to a linear programming model and is core guaranteed, in the sense that if the core is not empty, the allocation belongs to the core.
Journal: International Journal of Production Research
Pages: 220-237
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.948577
File-URL: http://hdl.handle.net/10.1080/00207543.2014.948577
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Template-Type: ReDIF-Article 1.0
Author-Name: R. Rajesh
Author-X-Name-First: R.
Author-X-Name-Last: Rajesh
Author-Name: V. Ravi
Author-X-Name-First: V.
Author-X-Name-Last: Ravi
Author-Name: R. Venkata Rao
Author-X-Name-First: R.
Author-X-Name-Last: Venkata Rao
Title: Selection of risk mitigation strategy in electronic supply chains using grey theory and digraph-matrix approaches
Abstract: 
 Supply chains are becoming more lengthy and complex due to globalisation and vertical integrations. In this context, adopting proactive approaches is needed for dealing with changing risks and vulnerabilities for securing supply chain systems. Supply chain risks are interlinked and thus, one mitigation strategy can reduce many of other supply chain risks. For example, aggregate or pooling demand reduces forecast risks, capacity risks and inventory risks. Also, some of the risk mitigation strategies have negative influences over certain supply chain risks as adding capacity has a negative influence on capacity risks. Twelve major supply chain risk categories and 21 risk mitigation strategies with typical focus on electronics manufacturing supply chains have been identified. A combination of grey theory and digraph-matrix methodologies has been used for quantifying various supply chain risk mitigation strategies and this approach is not seen in literature till date. The proposed model was also tested taking a case study of an Indian electronics manufacturing company. Obtained results were also subject to sensitivity analysis. The net positive influence values of risk mitigation strategies proposed in this research could effectively be used by top management for ascertaining their risk mitigation strategies for better management of supply chains as a whole.
Journal: International Journal of Production Research
Pages: 238-257
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.948579
File-URL: http://hdl.handle.net/10.1080/00207543.2014.948579
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Template-Type: ReDIF-Article 1.0
Author-Name: Jie Wei
Author-X-Name-First: Jie
Author-X-Name-Last: Wei
Author-Name: Jing Zhao
Author-X-Name-First: Jing
Author-X-Name-Last: Zhao
Title: Pricing and remanufacturing decisions in two competing supply chains
Abstract: 
 This paper considers the pricing and remanufacturing decisions in a duopoly market with two competing supply chains, which compete at both manufacturer and retailer levels. There are one manufacturer and one retailer in each supply chain, one manufacturer produces the new product directly from raw material, while the other manufacturer has incorporated a remanufacturing process for used product into the original production system. Based on different industry organisation structures and the chain members’ competing forms, five game decision models are established to explore the chain members’ optimal strategies on price and/or remanufacturing, and the corresponding equilibrium solutions are obtained. Finally, we carry out the sensitivity analysis through numerical studies of some key parameters for examining their influences on the pricing decisions and chain members’ maximum profits. On the basis of comparison and analysis, some managerial insights are derived.
Journal: International Journal of Production Research
Pages: 258-278
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.951088
File-URL: http://hdl.handle.net/10.1080/00207543.2014.951088
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:1:p:258-278




Template-Type: ReDIF-Article 1.0
Author-Name: M.Z. Babai
Author-X-Name-First: M.Z.
Author-X-Name-Last: Babai
Author-Name: T. Ladhari
Author-X-Name-First: T.
Author-X-Name-Last: Ladhari
Author-Name: I. Lajili
Author-X-Name-First: I.
Author-X-Name-Last: Lajili
Title: On the inventory performance of multi-criteria classification methods: empirical investigation
Abstract: 
 A number of multi-criteria inventory classification (MCIC) methods have been proposed in the academic literature. However, most of this literature focuses on the development and the comparison of ranking methods of stock keeping units (SKUs) in an inventory system without any interest in the original and most important goal of this exercise which is the combined service-cost inventory performance. Moreover, to the best of our knowledge these MCIC methods have never been compared in an empirical study. Such an investigation constitutes the objective of this paper. We first present the inventory performance evaluation method that we illustrate based on an example commonly used in the relevant literature which consists of 47 SKUs. Then, we present the empirical investigation that is conducted by means of a large data-set consisting of more than 9086 SKUs and coming from a retailer in the Netherlands that sells do-it-yourself products. The results of the empirical investigation show that the MCIC methods that impose a descending ranking of the criteria, with a dominance of the annual dollar usage and the unit cost criteria, have the lowest combined cost-service performance efficiency.
Journal: International Journal of Production Research
Pages: 279-290
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.952791
File-URL: http://hdl.handle.net/10.1080/00207543.2014.952791
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Template-Type: ReDIF-Article 1.0
Author-Name: Ping Su
Author-X-Name-First: Ping
Author-X-Name-Last: Su
Author-Name: Shuguang Liu
Author-X-Name-First: Shuguang
Author-X-Name-Last: Liu
Title: Dual sourcing in managing operational and disruption risks in contract manufacturing
Abstract: 
 We study a US OEM that outsources its production to two contract manufacturers, a local manufacturer (e.g. in the US or Mexico) and a foreign manufacturer (e.g. in China). The local manufacturer is relatively reliable, but low margin. The foreign manufacturer offers high margin, but is subject to disruption risks. Both manufacturers experience some level of operational uncertainties, and the operational risks can be positively or negatively correlated. Disruption risks are modelled as a Poisson jump process at a random magnitude, and operational risks are modelled as correlated stochastic diffusion processes. We develop a stochastic dynamic programming formulation to characterise the OEM’s optimal capital allocation decision to contract manufacturers, and provide the necessary and sufficient conditions for each optimal decision. The objective of our study is to investigate how dual sourcing balances the risks and opportunities, when the OEM bears disruption risks and correlated operational risks. We find that the two manufacturers can be substitutes or complements to each other. Risk of disruption renders the unreliable foreign manufacturer less attractive, but has a moderating effect on the allocation to the local manufacturer. We also provide managerial implications of our study.
Journal: International Journal of Production Research
Pages: 291-306
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.957876
File-URL: http://hdl.handle.net/10.1080/00207543.2014.957876
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Handle: RePEc:taf:tprsxx:v:53:y:2015:i:1:p:291-306




Template-Type: ReDIF-Article 1.0
Author-Name: Ruey-Chyn Tsaur
Author-X-Name-First: Ruey-Chyn
Author-X-Name-Last: Tsaur
Title: Green product pricing decision analysis with application to personal computers
Abstract: 
 This paper focuses on the pricing of reused personal computers that are discarded and sold on the secondary market. We first extract the main components affecting the performance of a reused computer. We then use quality function deployment to compare the weights of the main components against what reusable computer customers require. Third, we use TOPSIS to rank the selected reused computers. Finally, we price every reused computer according to relative monopoly power and perform an accumulated depreciation analysis on each one at various sale periods. The results show that each reused computer can be easily evaluated and priced on the secondary market.
Journal: International Journal of Production Research
Pages: 307-320
Issue: 1
Volume: 53
Year: 2015
Month: 1
X-DOI: 10.1080/00207543.2014.961202
File-URL: http://hdl.handle.net/10.1080/00207543.2014.961202
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen-Yang Xu
Author-X-Name-First: Chen-Yang
Author-X-Name-Last: Xu
Author-Name: Jing-Rong Li
Author-X-Name-First: Jing-Rong
Author-X-Name-Last: Li
Author-Name: Qing-Hui Wang
Author-X-Name-First: Qing-Hui
Author-X-Name-Last: Wang
Author-Name: Guang-Hua Hu
Author-X-Name-First: Guang-Hua
Author-X-Name-Last: Hu
Title: Contour parallel tool path planning based on conformal parameterisation utilising mapping stretch factors
Abstract: 
 Parameterisation-based methods for planning tool paths on mesh surfaces have been developing for years. The issue of existing mapping deformation which results in machining error has not been sufficiently addressed. And it still needs particular 3D geometric operations when planning iso-scallop tool path. To handle these, an effective approach to directly generating the iso-scallop paths on the parametric domain utilising anisotropic mapping stretch factors is proposed. The conformal parameterisation algorithm, Angle Based Flattening, is first implemented for the mapping between the spatial mesh and the planar mesh. Then a general method to convert 3D path parameters into 2D, which involves the direction mapping and length mapping based on the mapping deformation analysis, is presented. After that, a non-uniform offsetting method is proposed for retrieving the valid 2D offset paths. Finally, the iso-scallop paths on the parametric domain can be generated using the converted 2D path parameters and the present non-uniform offsetting method, and then the corresponding tool paths are obtained by inverse mapping. Simulation and experimental results are given to validate the feasibility and effectiveness of the proposed methods.
Journal: International Journal of Production Research
Pages: 1-15
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1456699
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1456699
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Template-Type: ReDIF-Article 1.0
Author-Name: Rune Larsen
Author-X-Name-First: Rune
Author-X-Name-Last: Larsen
Author-Name: Marco Pranzo
Author-X-Name-First: Marco
Author-X-Name-Last: Pranzo
Title: A framework for dynamic rescheduling problems
Abstract: 
 Academic scheduling problems usually assume deterministic and known in advance data. However, this situation is not often met in practice, since data may be subject to uncertainty and it may change over time. In this paper, we introduce a general rescheduling framework to address such dynamic scheduling problems. The framework consists mainly of a controller that makes use of a solver. The solver can assume deterministic and static data, whereas the controller deals with the uncertain and dynamic aspects of the problem and it is in charge of triggering the solver when needed and when possible. Extensive tests are carried out for the job shop problem, and we demonstrate that the framework can be used to ascertain the benefit of using rescheduling over static methods, decide between rescheduling policies, and finally we show that it can be applied in real-life applications due to a low time overhead. The framework is general enough to be applied to any scheduling environment where a fast enough deterministic solver exists.
Journal: International Journal of Production Research
Pages: 16-33
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1456700
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1456700
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Template-Type: ReDIF-Article 1.0
Author-Name: Andr&#xE9; R.S. Amaral
Author-X-Name-First: Andr&#xE9; R.S.
Author-X-Name-Last: Amaral
Title: A mixed-integer programming formulation for the double row layout of machines in manufacturing systems
Abstract: 
 The Double Row Layout Problem (DRLP) is the problem of allocating a given set of machines on both sides of a straight line corridor so as to minimise the total cost of transporting materials among machines. The DRLP occurs in several manufacturing plants, particularly in semiconductor manufacturing. While it has a large practical importance, the problem is very difficult to solve to optimality. In this paper, we construct a mixed-integer programming (MIP) formulation of the problem, which favourably compares to a previously published MIP formulation. The new model is found to present similar performance to another published MIP formulation, and it has the advantage of being more intuitive for handling qualitative inputs that may be required in a layout refinement phase.
Journal: International Journal of Production Research
Pages: 34-47
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1457811
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1457811
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen-Yang Cheng
Author-X-Name-First: Chen-Yang
Author-X-Name-Last: Cheng
Author-Name: Kuo-Ching Ying
Author-X-Name-First: Kuo-Ching
Author-X-Name-Last: Ying
Author-Name: Hsia-Hsiang Chen
Author-X-Name-First: Hsia-Hsiang
Author-X-Name-Last: Chen
Author-Name: Hsiao-Shan Lu
Author-X-Name-First: Hsiao-Shan
Author-X-Name-Last: Lu
Title: Minimising makespan in distributed mixed no-idle flowshops
Abstract: 
 The rapid growth of distributed manufacturing in industry today has recently attracted significant research attention that has focused on distributed scheduling problems. This work studied the distributed mixed no-idle flowshop scheduling problem using makespan as an optimality criterion. To the best of the authors&#x2019; knowledge, this is the first paper to study the multi-flowshop extension in which each flowshop has mixed no-idle constraints. A novel cloud theory-based iterated greedy (CTBIG) algorithm was proposed for solving the problem. Computational experiments conducted on a set of test instances revealed that the proposed CTBIG algorithm significantly outperformed classic iterated greedy algorithms.
Journal: International Journal of Production Research
Pages: 48-60
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1457812
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1457812
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Template-Type: ReDIF-Article 1.0
Author-Name: Sirikarn Chansombat
Author-X-Name-First: Sirikarn
Author-X-Name-Last: Chansombat
Author-Name: Pupong Pongcharoen
Author-X-Name-First: Pupong
Author-X-Name-Last: Pongcharoen
Author-Name: Christian Hicks
Author-X-Name-First: Christian
Author-X-Name-Last: Hicks
Title: A mixed-integer linear programming model for integrated production and preventive maintenance scheduling in the capital goods industry
Abstract: 
 The scheduling literature is extensive, but much of this work is theoretical and does not capture the complexity of real world systems. Capital goods companies produce products with deep and complex product structures, each of which requires the coordination of jobbing, batch, flow and assembly processes. Many components require numerous operations on multiple machines. Integrated scheduling problems simultaneously consider two or more simultaneous decisions. Previous production scheduling research in the capital goods industry has neglected maintenance scheduling and used metaheuristics with stochastic search that cannot guarantee an optimal solution. This paper presents a novel mixed integer linear programming model for simultaneously solving the integrated production and preventive maintenance scheduling problem in the capital goods industry, which was tested using data from a collaborating company. The objective was to minimise total costs including: tardiness and earliness penalty costs; component and assembly holding costs; preventive maintenance costs; and set-up, production, transfer and production idle time costs. Thus, the objective function and problem formulation were more extensive than previous research. The tool was successfully tested using data obtained from a collaborating company. It was found that the company&#x2019;s total cost could be reduced by up to 63.5%.
Journal: International Journal of Production Research
Pages: 61-82
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1459923
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1459923
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Template-Type: ReDIF-Article 1.0
Author-Name: Roberto Pinto
Author-X-Name-First: Roberto
Author-X-Name-Last: Pinto
Author-Name: Alexandra Lagorio
Author-X-Name-First: Alexandra
Author-X-Name-Last: Lagorio
Author-Name: Ruggero Golini
Author-X-Name-First: Ruggero
Author-X-Name-Last: Golini
Title: The location and sizing of urban freight loading/unloading lay-by areas
Abstract: 
 The volume of freight vehicles operating within city boundaries is steadily increasing, which contributes to road congestion, especially in urban areas with a parking deficit. The proper identification of the location and size of commercial parking lay-by areas, where delivery vehicles can park for a limited time to perform loading/unloading operations, can relieve road congestion. Compared to the existing literature, this paper presents an improved two-stage approach, which includes a mathematical programme and a simulation model for determining the location and sizing of lay-by areas. The robustness and soundness of the results from a methodological and practical point of view are discussed using an example application.
Journal: International Journal of Production Research
Pages: 83-99
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1461269
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1461269
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:1:p:83-99




Template-Type: ReDIF-Article 1.0
Author-Name: Vladmir Polotski
Author-X-Name-First: Vladmir
Author-X-Name-Last: Polotski
Author-Name: Jean-Pierre Kenn&#xE9;
Author-X-Name-First: Jean-Pierre
Author-X-Name-Last: Kenn&#xE9;
Author-Name: Ali Gharbi
Author-X-Name-First: Ali
Author-X-Name-Last: Gharbi
Title: Production control of hybrid manufacturing&#x2013;remanufacturing systems under demand and return variations
Abstract: 
 Hybrid manufacturing systems that use both raw materials and returned products as a supply for their production process are considered. Specifically, the system under study contains two machines: one uses raw materials for manufacturing, while another utilises end-of-life products returned from the market for remanufacturing. Machines are failure-prone, demand and return rates fluctuate in time reflecting market behaviour due to economical, seasonal and environmental changes. The system performance is characterised by a long-term discounted cost that integrates several partial costs (those of manufacturing, remanufacturing, disposal, holding costs in serviceable and return inventories). Optimisation of the hybrid system behaviour requires to determine the combined manufacturing, remanufactruring and disposal policy, withstanding machine failures under dynamic market conditions. Optimality conditions in the form of Hamilton&#x2013;Jacoby&#x2013;Bellman equations are obtained and a novel numerical approach, based on the estimation of value function timederivative, is proposed in order to deal with demand and return variations. Extensive simulations are performed to address the numerous scenarios corresponding to evolving relationship between manufacturing capacities and varying demand and return levels. Simulation results show that the optimal policies have an important property of anticipating the future changes in the demand and return, and making the timely decisions relevant to these changes.
Journal: International Journal of Production Research
Pages: 100-123
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1461272
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1461272
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:1:p:100-123




Template-Type: ReDIF-Article 1.0
Author-Name: Yiyun Tao
Author-X-Name-First: Yiyun
Author-X-Name-Last: Tao
Author-Name: Kai Meng
Author-X-Name-First: Kai
Author-X-Name-Last: Meng
Author-Name: Peihuang Lou
Author-X-Name-First: Peihuang
Author-X-Name-Last: Lou
Author-Name: Xianghui Peng
Author-X-Name-First: Xianghui
Author-X-Name-Last: Peng
Author-Name: Xiaoming Qian
Author-X-Name-First: Xiaoming
Author-X-Name-Last: Qian
Title: Joint decision-making on automated disassembly system scheme selection and recovery route assignment using multi-objective meta-heuristic algorithm
Abstract: 
 Green treatment on Waste Electrical and Electronic Equipmenthas increasingly attracted attention due to its significant environmental benefits and potential recovery earnings. Automated disassembly has been regarded as a powerful solution to enable more efficient recovery operations. Although numerous studies have contributed to the issues of disassembly, there are few researches that focus on decision model for selecting disassembly system scheme and recovery route in automated disassembly. In this paper, we propose a two-phase joint decision-making model to address this problem with the goal of balancing disassembly profit with environmental impact. First, we establish a multi-objective optimisation model to obtain the Pareto optimal recovery routes for each automated disassembly system scheme. Both recovery profit and energy consumption are evaluated for multi-station disassembly system. We design a multi-objective hybrid particle swarm optimisation algorithm based on symbiotic evolutionary mechanism to solve the proposed model. Then, we compare the Pareto optimal solutions of all the system schemes using a fuzzy set method and identify the best scheme. Finally, we conduct real case studies on the automated disassembly of different waste electric metres. The results demonstrate the superiority of automated disassembly and validate the effectiveness of our proposed model and algorithm.
Journal: International Journal of Production Research
Pages: 124-142
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1461274
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1461274
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Template-Type: ReDIF-Article 1.0
Author-Name: Altan Yalcin
Author-X-Name-First: Altan
Author-X-Name-Last: Yalcin
Author-Name: Achim Koberstein
Author-X-Name-First: Achim
Author-X-Name-Last: Koberstein
Author-Name: Kai-Oliver Schocke
Author-X-Name-First: Kai-Oliver
Author-X-Name-Last: Schocke
Title: An optimal and a heuristic algorithm for the single-item retrieval problem in puzzle-based storage systems with multiple escorts
Abstract: 
 Puzzle-based storage systems consist of densely stored unit loads on a square grid. The problem addressed in this paper is to retrieve a stored unit load from a puzzle-based storage using the minimum number of item moves. While previous research contributed optimal algorithms for only up to two empty locations (escorts), our approach solves configurations where multiple empty locations are arbitrarily positioned in the grid. The problem is formulated as a state space problem and solved to optimality using an exact search algorithm. To reduce the search space, we derive bounds on the number of eligible empty locations and develop several search-guiding estimate functions. Furthermore, we present a heuristic variant of the search algorithm to solve larger problem instances. We evaluate both solution algorithms on a large set of problem instances. Our computational results show that the algorithms clearly outperform existing approaches where they are applicate and solve more general configurations, which could not be solved to optimality before. The heuristic variant efficiently yields high-quality solutions for significantly larger instances of practically relevant size.
Journal: International Journal of Production Research
Pages: 143-165
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1461952
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1461952
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Template-Type: ReDIF-Article 1.0
Author-Name: Romain Miclo
Author-X-Name-First: Romain
Author-X-Name-Last: Miclo
Author-Name: Matthieu Lauras
Author-X-Name-First: Matthieu
Author-X-Name-Last: Lauras
Author-Name: Franck Fontanili
Author-X-Name-First: Franck
Author-X-Name-Last: Fontanili
Author-Name: Jacques Lamothe
Author-X-Name-First: Jacques
Author-X-Name-Last: Lamothe
Author-Name: Steven A. Melnyk
Author-X-Name-First: Steven A.
Author-X-Name-Last: Melnyk
Title: Demand Driven MRP: assessment of a new approach to materials management
Abstract: 
 Demand driven material requirements planning or DDMRP is a recent and promising material management method that has been developed and implemented in the practitioner world. Essentially, DDMRP represents a rethinking of the basic MRP logic. By incorporating elements drawn from Lean Systems and the Theory of Constraints and by introducing new features such as dynamic buffers, DDMRP modifies the basic MRP logic so that it is better able to satisfy customer demands in an increasingly demanding, turbulent and dynamic environment. Claims have been made by firms that DDMRP represents a superior planning approach. In this paper, we introduce and explore DDMRP. In addition, we evaluate its effectiveness relative to two other widely accepted approaches &#x2013; MRP II and Kanban/Lean production &#x2013; through a series of structured computer simulation experiments. The results strongly indicate that DDMRP does represent a superior approach &#x2013; one that warrants further academic study.
Journal: International Journal of Production Research
Pages: 166-181
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1464230
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1464230
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Template-Type: ReDIF-Article 1.0
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Michael L. Pinedo
Author-X-Name-First: Michael L.
Author-X-Name-Last: Pinedo
Author-Name: Kangbok Lee
Author-X-Name-First: Kangbok
Author-X-Name-Last: Lee
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Yinfeng Xu
Author-X-Name-First: Yinfeng
Author-X-Name-Last: Xu
Title: Towards robustness of response times: minimising the maximum inter-completion time on parallel machines
Abstract: 
 Motivated by scheduling practices that require a response to unplanned high-priority jobs as soon as possible without preempting any in-processing jobs, this paper considers a deterministic identical parallel machine scheduling problem to achieve robustness with regard to a worst-case response time. To the best of our knowledge, this paper is the first to study the objective of minimising the maximum inter-completion time, i.e. the maximum time difference between any two consecutive completion times of jobs. For this novel scheduling problem, we first show its NP-hardness, and then propose an integer linear programming formulation and three heuristic approaches. Numerical experiments demonstrate the efficiency of our solution methods.
Journal: International Journal of Production Research
Pages: 182-199
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1466063
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1466063
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:1:p:182-199




Template-Type: ReDIF-Article 1.0
Author-Name: Alejandro Bello-Pintado
Author-X-Name-First: Alejandro
Author-X-Name-Last: Bello-Pintado
Author-Name: Teresa Garc&#xED;a Marco
Author-X-Name-First: Teresa
Author-X-Name-Last: Garc&#xED;a Marco
Author-Name: Ferdaous Zouaghi
Author-X-Name-First: Ferdaous
Author-X-Name-Last: Zouaghi
Title: Product/process definition, technology adoption and workforce qualification: impact on performance
Abstract: 
 This paper analyses the impact of manufacturing technologies (MTs) and workers&#x2019; qualifications on labour productivity and flexibility, taking into account the product-process (P-P) strategy adopted by the company. This allows for a discussion about the well-known P-P matrix initially proposed by Hayes and Wheelwright (1994) in order to evaluate options of production systems. The empirical analysis is performed by means of a panel of data of 13&#xA0;years for the Spanish manufacturing industry, which includes a total of 7741 observations. The results indicate a complementary effect between technology and skills to overcome the trade-offs of production systems.
Journal: International Journal of Production Research
Pages: 200-215
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1468096
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1468096
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Template-Type: ReDIF-Article 1.0
Author-Name: Jihene Kaabi
Author-X-Name-First: Jihene
Author-X-Name-Last: Kaabi
Author-Name: Youssef Harrath
Author-X-Name-First: Youssef
Author-X-Name-Last: Harrath
Title: Scheduling on uniform parallel machines with periodic unavailability constraints
Abstract: 
 Scheduling problems under unavailability constraints has become a popular research topic in the last few years. Despite it&#x2019;s important application in the real world, the uniform parallel machine scheduling problem was the least studied due to its complexity. In this paper, we investigated the uniform parallel machine scheduling problem under deterministic availability constraints. Each machine is subject to one unavailability period. Different versions of the problem regarding the type of jobs (identical and non-identical) and the performance measures (the total completion times and the makespan) were studied. For the case of identical jobs and for both performance measures, we developed linear programming models and optimal algorithms to provide a solution to the problem. For the case of non-identical jobs, we proved that the problem is NP-hard and propose a quadratic program. Because, this later cannot solve problems with very large number of jobs and machines, a heuristic was developed to find near optimal solutions to the problem especially with very large number of jobs and machines. The computational results showed that the heuristic&#x2019;s performance is very high regardless the dimensions of problem instances.
Journal: International Journal of Production Research
Pages: 216-227
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1471242
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471242
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Template-Type: ReDIF-Article 1.0
Author-Name: Fangyu Chen
Author-X-Name-First: Fangyu
Author-X-Name-Last: Chen
Author-Name: Gangyan Xu
Author-X-Name-First: Gangyan
Author-X-Name-Last: Xu
Author-Name: Yongchang Wei
Author-X-Name-First: Yongchang
Author-X-Name-Last: Wei
Title: Heuristic routing methods in multiple-block warehouses with ultra-narrow aisles and access restriction
Abstract: 
 This paper focuses on multiple-block warehouses with ultra-narrow aisles and access restriction. These new features observed from one of the largest online retailers in China allow order pickers enter pick aisles from specific entrances but prohibit them from traversing the aisles. This impedes the application of traditional heuristic order picking methods. To address the order picking problem in such warehouses, we propose six heuristic routing methods by extending the basic Return, Largest Gap and Mid-point methods for the single-block warehouse. These six heuristic methods are named RNA, LNA, MNA, RNAP, LNAP and MNAP, respectively. The major improvements are achieved through setting rules with respect to determining the access mode of aisles as well as changing working aisles. Using real order information, a comprehensive simulation for comparison is conducted to evaluate the effectiveness of our improved routing methods under 12 warehouse layouts. The simulation results demonstrate that LNAP achieves the shortest average picking routes in most scenarios. The impacts of warehouse layout on performance measurements are analysed as well. It is ascertained that setting more cross aisles and connect aisles helps mitigate the negative impacts.
Journal: International Journal of Production Research
Pages: 228-249
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1473657
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1473657
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Template-Type: ReDIF-Article 1.0
Author-Name: Timm Weitzel
Author-X-Name-First: Timm
Author-X-Name-Last: Weitzel
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Title: Scheduling a storage-augmented discrete production facility under incentive-based demand response
Abstract: 
 Demand response (DR) is considered as one of the most important measures for balancing energy supply and demand in the smart grid paradigm. Incentive-based programs, one manifestation of DR, contribute to short-term system stability and prevent critical periods when system stability is at risk by enabling the system operator (SO) to directly change total energy demand. The fact that a third party would be empowered to interfere with internal operations is, however, also one of the major drawbacks of DR that prevents especially industrial consumers from participating with full capacity in such programs. This paper considers an alternative Incentive-based program with application to a discrete manufacturing facility where load reduction curves (LRCs) are generated a priori outlining the potential load reduction in the DR period. The SO uses the LRC to determine the desired level of load reduction for critical periods. To illustrate the generation of the LRC, this paper builds on a flexible flow shop (FFS) formulation for a discrete manufacturing facility and presents a model that includes multiple machine modes and product- and machine-specific energy consumption trajectories. Based on the FFS, a procedure is developed to generate the LRC. The paper also investigates the potential of including a battery energy storage system (BESS) into the production facility and illustrates the effects of the BESS on the LRC.
Journal: International Journal of Production Research
Pages: 250-270
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1475764
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1475764
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Template-Type: ReDIF-Article 1.0
Author-Name: Yihai He
Author-X-Name-First: Yihai
Author-X-Name-Last: He
Author-Name: Jiaming Cui
Author-X-Name-First: Jiaming
Author-X-Name-Last: Cui
Author-Name: Fengdi Liu
Author-X-Name-First: Fengdi
Author-X-Name-Last: Liu
Author-Name: Panting Duan
Author-X-Name-First: Panting
Author-X-Name-Last: Duan
Author-Name: Donglin Li
Author-X-Name-First: Donglin
Author-X-Name-Last: Li
Title: Risk-oriented assembly quality analysing approach considering product reliability degradation
Abstract: 
 Assembly process is a critical stage in the formation of product quality and reliability, but related consideration of the produced product reliability and accident risk has not attracted deserved attention in the most assembly quality analysis frameworks. To this end, this paper enhances risk analysis in assembly process quality control, which is advocated by ISO 9001:2015, and presents a risk-oriented assembly quality analysis approach considering the effects of assembly variations on the produced product reliability degradation and accident risk. First, a conceptual QRR chain is presented to illustrate the relationship among assembly process quality (Q), product reliability (R), and failure accident risk (R). Second, a risk-oriented and bidirectional framework for the analysis of assembly process quality is established based on the presented QRR chain aiming to quantitatively identify the risk sources in the assembly process and reduce the risk of failure accidents. Third, an assembly process quality risk model with key function reliability as its core is presented to establish the quantitative relationship between assembly variation and product failure accident risk. Finally, the presented approach is verified through a case study of an assembling quality risk analysing for acid-resistant grinder.
Journal: International Journal of Production Research
Pages: 271-284
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1475765
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1475765
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcel van Assen
Author-X-Name-First: Marcel
Author-X-Name-Last: van Assen
Author-Name: Jeroen de Mast
Author-X-Name-First: Jeroen
Author-X-Name-Last: de Mast
Title: Visual performance management as a fitness factor for Lean
Abstract: 
 Visual performance management (VPM) is a bundle of practices where visual techniques are used to offer timely information to shop-floor employees about the performance of processes. We investigate whether VPM contributes to the beneficial effects of Lean, and if so, what the relationship is between VPM and other Lean practices. Thus, the study builds on and adds to the stream of research that tries to establish how the various practices associated with Lean depend on and reinforce each other. Based on the outcomes of a survey, we establish that VPM is positively related with operations improvement. This effect is not direct, but mediated by Lean practices such as just-in-time and quality management. We conclude, therefore, that VPM should be seen as an infrastructural practice that reinforces an organisation&#x2019;s general fitness, and acting as an enabler for more dedicated Lean practices. In addition, we find that VPM positively moderates the effects of Lean practices, which supports the same conclusion.
Journal: International Journal of Production Research
Pages: 285-297
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1479545
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1479545
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:1:p:285-297




Template-Type: ReDIF-Article 1.0
Author-Name: M. Ganesh Kumar
Author-X-Name-First: M.
Author-X-Name-Last: Ganesh Kumar
Author-Name: R. Uthayakumar
Author-X-Name-First: R.
Author-X-Name-Last: Uthayakumar
Title: Multi-item inventory model with variable backorder and price discount under trade credit policy in stochastic demand
Abstract: 
 In this paper, a two echelon supply chain with one manufacturer and one retailer is developed for multi products. The retailer faced with the uncertain demand for all products which follows a normal distribution. The production process is assumed to be imperfect, and the defectiveness is assumed to follow a beta distribution. The manufacturer produces and delivers the products in a number of equal-sized batches to the manufacturer's warehouse, and thereby it is delivers in a number of equal batches to the retailer's warehouse. Shortages are allowed to occur, at the retailer side, and it is backordered partially. The retailer offers a price discount for backordered items to his customers. Both the lead time crashing cost and the partial backorder ratio are considered as the inverse function of lead time. Under these assumptions, there are three inventory models proposed in this paper, one with non-integrated approach, the other with an integrated approach without trade credit and finally an integrated approach with trade credit. A new iterative algorithmic procedure has been developed to minimise the total cost. Finally, numerical examples are given to illustrate the models and the sensitivity analysis is conducted over various model parameters.
Journal: International Journal of Production Research
Pages: 298-320
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1480839
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1480839
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:1:p:298-320




Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 321-321
Issue: 1
Volume: 57
Year: 2019
Month: 1
X-DOI: 10.1080/00207543.2018.1466976
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1466976
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:1:p:321-321




Template-Type: ReDIF-Article 1.0
Author-Name: Kartik Modi
Author-X-Name-First: Kartik
Author-X-Name-Last: Modi
Author-Name: Harshal Lowalekar
Author-X-Name-First: Harshal
Author-X-Name-Last: Lowalekar
Author-Name: N.M.K. Bhatta
Author-X-Name-First: N.M.K.
Author-X-Name-Last: Bhatta
Title: Revolutionizing supply chain management the theory of constraints way: a case study
Abstract: 
 This research describes in detail an application of theory of constraints (TOC) and its resulting benefits on the supply chain performance of India's largest lock manufacturing company over a period of seven years. Using TOC's thinking process, the core constraints that had limited the company's performance in the areas of production, distribution, supply group and projects were identified and eliminated. TOC's unique approach helped the company achieve a significant reduction in its finished goods, raw material and work-in-process inventories at various levels across the supply chain. The stock-outs and excess in the distribution system nearly disappeared. The existing lead times saw a drastic reduction while the availability of items increased to nearly 100% despite significant decrease in inventory levels in the supply chain. The inventory turns of the distributors and retailers more than tripled and their profitability increased significantly. The overall sales of the company grew nearly three times during the six years post TOC implementation. TOC's holistic approach helped the company to double its profits and improve its cash position during the Great Recession.
Journal: International Journal of Production Research
Pages: 3335-3361
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1523579
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1523579
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3335-3361




Template-Type: ReDIF-Article 1.0
Author-Name: M. Ganesh Kumar
Author-X-Name-First: M.
Author-X-Name-Last: Ganesh Kumar
Author-Name: R. Uthayakumar
Author-X-Name-First: R.
Author-X-Name-Last: Uthayakumar
Title: Modelling on vendor-managed inventory policies with equal and unequal shipments under GHG emission-trading scheme
Abstract: 
 This paper studies five different stock control policies in the supply chain management. The lead time can be shortened by extra investment between two entities. The vendor produces a single product and delivers the order quantity in a number of unequal shipments to the buyer. The unit holding cost is divided into financial and storage components. The vendor takes care of financial component until the products are sold to the end customers to encourage them to buy more products. In order to reduce emissions from production and to protect the environment, some legislative actions have been taken such as implementing taxes and penalties. The cost function also includes these taxes and penalties. The optimal solutions of this constrained mixed integer non-linear programming problem are obtained by using the Genetic Algorithm (GA). Numerical examples are employed and comparison works are carried out with other existing literatures. Results show that the performance of the system is better when it is operated under unequal shipment policies and vendor-managed inventory (VMI) agreement.
Journal: International Journal of Production Research
Pages: 3362-3381
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1530471
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1530471
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3362-3381




Template-Type: ReDIF-Article 1.0
Author-Name: Shou-feng Ji
Author-X-Name-First: Shou-feng
Author-X-Name-Last: Ji
Author-Name: Rong-juan Luo
Author-X-Name-First: Rong-juan
Author-X-Name-Last: Luo
Author-Name: Xiao-shuai Peng
Author-X-Name-First: Xiao-shuai
Author-X-Name-Last: Peng
Title: A probability guided evolutionary algorithm for multi-objective green express cabinet assignment in urban last-mile logistics
Abstract: 
 In the past decade, urban last-mile logistics (ULML) has attracted increasing attention with the growth of e-commerce. Under this background, express cabinet has been gradually advocated to improve the efficiency of ULML. This paper focuses on the multi-objective green express cabinet assignment problem (MGECAP) in ULML, where the objectives to be minimised are the total cost and the energy consumption. MGECAP is concerned with optimising the purchase and assignment decision of express cabinets, which is different from conventional assignment problems. To solve MGECAP, firstly, the integer programming model and the corresponding surrogate model are established. Secondly, problem-dependent heuristics, including the solution representation, genetic operators, and repair strategy of infeasible solutions, are proposed. Thirdly, a probability guided multi-objective evolutionary algorithm based on decomposition (PG-MOEA/D) is proposed, which can balance the limited computation resource among sub-problems during the iterative process. Meanwhile, a feedback strategy is put forward to alternatively generate new solutions when the probability condition is not satisfied. Finally, numerical results and a real-life case study demonstrate the effectiveness and the practical values of the PG-MOEA/D.
Journal: International Journal of Production Research
Pages: 3382-3404
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1533653
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1533653
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3382-3404




Template-Type: ReDIF-Article 1.0
Author-Name: Shuai Huang
Author-X-Name-First: Shuai
Author-X-Name-Last: Huang
Author-Name: Zhi-Ping Fan
Author-X-Name-First: Zhi-Ping
Author-X-Name-Last: Fan
Author-Name: Xiaohuan Wang
Author-X-Name-First: Xiaohuan
Author-X-Name-Last: Wang
Title: Optimal operational strategies of supply chain under financing service by a 3PL firm
Abstract: 
 As an innovative mode of supply chain finance, financing service offered by a third part logistics (3PL) firm has been practiced over the recent years. This paper investigates the optimal operational strategies of the supply chain system consisting of a supplier, a capital-constrained retailer and a 3PL firm. In this study, we compare the optimal operational strategies under both decentralised and centralised decisions, and put forward the supply chain coordination condition when the 3PL firm offers financing service. Several important results are achieved. First, the supplier’s wholesale price strategy has obvious influence on the decisions of the retailer and the 3PL firm. Second, the retailer’s ordering quantity under 3PL financing service is more than that without any financing service; and it can exceed the ordering quantity of a well-funded retailer, if and only if the supplier’s wholesale price and the 3PL’s interest rate meet certain conditions. Finally, we find that under 3PL financing service, the profit of supply chain can achieve Pareto improvement, and the wholesale price contract may realise profit maximisation and channel coordination in the supply chain system under certain condition.
Journal: International Journal of Production Research
Pages: 3405-3420
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1534017
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1534017
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcelo Rosa
Author-X-Name-First: Marcelo
Author-X-Name-Last: Rosa
Author-Name: Marco A. C. Barbosa
Author-X-Name-First: Marco A. C.
Author-X-Name-Last: Barbosa
Author-Name: Marcelo Teixeira
Author-X-Name-First: Marcelo
Author-X-Name-Last: Teixeira
Title: Service-based manufacturing systems: modelling and control
Abstract: 
 In service-based manufacturing systems, functionalities are independently developed as services and a central engine orchestrates their integration. As industrial processes tend to be very large, and performance and productivity are expected to be maximised, there is a constant interest in providing (in-advance) quality guarantees for services interactions, which contrasts with the usual non-automated workflow design. This paper provides an alternative to enhance service orchestration capabilities using supervisory control techniques. Initially, each component (atomic and composite activities) belonging to an orchestration language is modelled as a state-machine. Then, activity models are properly combined and composed, reproducing orchestrated workflows. Finally, supervisory control is used to calculate an optimal version of the orchestrator. Practical implications of handling large state-spaces are discussed and examples are provided.
Journal: International Journal of Production Research
Pages: 3421-3434
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1535723
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1535723
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3421-3434




Template-Type: ReDIF-Article 1.0
Author-Name: Oktay Karabağ
Author-X-Name-First: Oktay
Author-X-Name-Last: Karabağ
Author-Name: Barış Tan
Author-X-Name-First: Barış
Author-X-Name-Last: Tan
Title: An empirical analysis of the main drivers affecting the buyer surplus in E-auctions
Abstract: 
 We empirically examine the impacts of the product category, the auction format, the 2008 global financial crisis, the group purchasing, the contract type, the platform ownership, and the number of participating suppliers on the buyer surplus obtained from e-auctions. To this end, we collect a unique dataset from a purchasing organisation that offers e-auction solutions to its corporate customers. By using a standard Tobit model, we show that the product categories, the auction type, and the number of participating suppliers have significant effects on the decrease in the procurement prices with respect to the minimum of the initial submitted bids. It is observed that the 2008 global financial crisis led to an increase in the buyer surplus. We classify the product categories into three groups based on their impacts on the average of the decrease in the procurement prices. We show that the average decrease in procurement prices is higher for the group purchasing option than for the individual buying option. It is concluded that the types of contract between buyers and auctioneer and the platform ownership have no statistically significant effects on the average decrease in procurement prices.
Journal: International Journal of Production Research
Pages: 3435-3465
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1536835
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1536835
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3435-3465




Template-Type: ReDIF-Article 1.0
Author-Name: Robert R. Inman
Author-X-Name-First: Robert R.
Author-X-Name-Last: Inman
Author-Name: Sita Bhaskaran
Author-X-Name-First: Sita
Author-X-Name-Last: Bhaskaran
Title: Empirical evaluation of the delivery risk of extended supply chains
Abstract: 
 The rise in global sourcing has led to extended supply chains. Extended supply chains generally have more mode changes, border crossings, rail classification yards, port congestion and so forth, that all lead to more delivery disruption risk. To test this assertion, we perform an empirical assessment of the inbound supply chain disruption risk at a major manufacturer that imports components from over three dozen different countries. Although delivery disruption risk can be mitigated with effort, we observe that delivery disruption risk increases with distance. Based on industrial data, we quantify the increase in delivery disruption with international versus domestic suppliers and intercontinental versus continental suppliers.
Journal: International Journal of Production Research
Pages: 3466-3477
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1539264
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1539264
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3466-3477




Template-Type: ReDIF-Article 1.0
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Ying Li
Author-X-Name-First: Ying
Author-X-Name-Last: Li
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Yinfeng Xu
Author-X-Name-First: Yinfeng
Author-X-Name-Last: Xu
Title: Integrated berth allocation and quay crane assignment with maintenance activities
Abstract: 
 With the rapid development of worldwide container trade, quay cranes and other resources in container terminals are suffering from increasing workloads. To reduce their failure probabilities, quay cranes usually require preventive maintenance. However, these important activities are often ignored during quay crane planning in literature. This work studies an integrated berth allocation, quay crane assignment and specific quay crane assignment problem where quay crane maintenance is involved, and establishes an integer linear programming with the objective of minimising the total turnaround time. Due to the NP-hardness of the problem, CPLEX only solves instances with up to 18 vessels. For solving larger instances, we propose Left-and-Right Vessel Move (LRVM) algorithm and improved Genetic Algorithm (GA). Experimental results reveal that GA slightly outperforms LRVM with respect to solution quality as the solution of LRVM serves as one of the initial chromosomes of GA. LRVM can output feasible solutions within seconds, even for instances with 50 vessels. We further present a sensitivity analysis of preferred berth segments, and make numerical comparison on algorithm performance for the relevant model without quay crane maintenance. Both the models and proposed heuristics in this work help in dealing with the operational management of container terminal resources in practice.
Journal: International Journal of Production Research
Pages: 3478-3503
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1539265
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1539265
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3478-3503




Template-Type: ReDIF-Article 1.0
Author-Name: Meimei Zheng
Author-X-Name-First: Meimei
Author-X-Name-Last: Zheng
Author-Name: Jie Lin
Author-X-Name-First: Jie
Author-X-Name-Last: Lin
Author-Name: Xue-Ming Yuan
Author-X-Name-First: Xue-Ming
Author-X-Name-Last: Yuan
Author-Name: Ershun Pan
Author-X-Name-First: Ershun
Author-X-Name-Last: Pan
Title: Impact of an emergency order opportunity on supply chain coordination
Abstract: 
 We consider a manufacturer-retailer supply chain in the pre-selling and selling seasons, whereby the manufacturer can offer the retailer an emergency order opportunity with a limited commitment quantity in addition to the regular order from the retailer before the selling season. Due to the short lead time for the emergency order, the manufacturer needs to prepare for it in the pre-selling season by producing more than the regular order or reserving its capacity for the responsive production. Through mathematically modelling and analyzing the supply chain, we found that, when the emergency order opportunity is provided, the manufacturer might be worse off, although the retailer is always better off. We derive the conditions whereby both the manufacturer and retailer can benefit from the emergency order, and the supply chain profit can be maximised. Further, we show that the supply chain can be coordinated by setting only the unit price and maximum commitment quantity for the emergency order. We also prove that Pareto improvement can be always achieved by setting the unit price for the regular order in addition to the unit price and maximum commitment quantity for the emergency order.
Journal: International Journal of Production Research
Pages: 3504-3521
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1540893
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1540893
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3504-3521




Template-Type: ReDIF-Article 1.0
Author-Name: Xin Guo
Author-X-Name-First: Xin
Author-X-Name-Last: Guo
Author-Name: Jianjun Wu
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wu
Author-Name: Jin Zhou
Author-X-Name-First: Jin
Author-X-Name-Last: Zhou
Author-Name: Xin Yang
Author-X-Name-First: Xin
Author-X-Name-Last: Yang
Author-Name: Desheng Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Wu
Author-Name: Ziyou Gao
Author-X-Name-First: Ziyou
Author-X-Name-Last: Gao
Title: First-train timing synchronisation using multi-objective optimisation in urban transit networks
Abstract: 
 Missed transfers affect urban transportation by increasing the travel times and decreasing the travel possibility, especially in the case of longer headways. A synchronised timetable can improve the transport efficiency of urban mobility and become an important consideration in the operation of urban transit networks (UTN). A mixed integer programming model is proposed to generate an optimal train timetable and minimise the total connection time, which includes smooth synchronisations for rail first-trains and the seamless synchronisation from rail first-trains to the bus service. Meanwhile, to characterise the characteristics of first-trains, binary variables are used to denote key transfer directions. Subsequently, the Sub-network Connection Method in conjunction with Genetic Algorithm is designed to obtain near-optimal solutions in an efficient way. Finally, a real-world case study, 16 rail lines and 41 transfer stations, based on the Beijing metro network and travel demand is conducted to validate the proposed timetabling model. Preliminary numerical results show that our approach improves the synchronisation substantially compared with the currently operated timetable.
Journal: International Journal of Production Research
Pages: 3522-3537
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1542177
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1542177
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3522-3537




Template-Type: ReDIF-Article 1.0
Author-Name: Zhiming Chen
Author-X-Name-First: Zhiming
Author-X-Name-Last: Chen
Author-Name: Kunwen Yuan
Author-X-Name-First: Kunwen
Author-X-Name-Last: Yuan
Author-Name: Shaorui Zhou
Author-X-Name-First: Shaorui
Author-X-Name-Last: Zhou
Title: Supply chain coordination with trade credit under the CVaR criterion
Abstract: 
 Trade credit is a popular payment method in the supply chain. However, it may transfer the market risk facing by the retailer to the manufacturer in the form of default risk. To reduce the default loss, we set up a modified newsvendor model incorporating random default probability. Under the goal of loss minimisation, the manufacturer’s optimal production quantity is derived with the criterion of conditional value at risk, and compared with the retailer’s optimal order quantity. It is found that, compared with traditional newsvendor setting, the setting of default possibility in trade credit can increase the order quantity but decrease the production quantity. If the risk aversion level and gross profit of product are low, the manufacturer may deliver below the quantity ordered. Although the default loss can be reduced by cutting order, the profits of both agents decrease, thereby leading to a deviation from the supply chain coordination. Trade credit coordinating the supply chain requires an extremely long credit period, which is not feasible. Moreover, quantity discount contract is able to improve the retailer’s order quantity, but insufficient to achieve coordination, which also depends on the manufacturer’s risk aversion level.
Journal: International Journal of Production Research
Pages: 3538-3553
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1543966
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543966
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3538-3553




Template-Type: ReDIF-Article 1.0
Author-Name: Anil Kumar
Author-X-Name-First: Anil
Author-X-Name-Last: Kumar
Author-Name: Edmundas Kazimieras Zavadskas
Author-X-Name-First: Edmundas Kazimieras
Author-X-Name-Last: Zavadskas
Author-Name: Sachin Kumar Mangla
Author-X-Name-First: Sachin Kumar
Author-X-Name-Last: Mangla
Author-Name: Varun Agrawal
Author-X-Name-First: Varun
Author-X-Name-Last: Agrawal
Author-Name: Kartik Sharma
Author-X-Name-First: Kartik
Author-X-Name-Last: Sharma
Author-Name: Divyanshu Gupta
Author-X-Name-First: Divyanshu
Author-X-Name-Last: Gupta
Title: When risks need attention: adoption of green supply chain initiatives in the pharmaceutical industry
Abstract: 
 The pharmaceutical industry is very important in delivering life-saving products/services to society. There are many ways for materials/products/services concerned with pharmaceuticals to influence the environment; these include improper disposal of pills/tablets by patients, expired and unused medications, improper release of drugs by pharmacies or household sewage mixed with surplus drugs. In view of this, the present work seeks to integrate green supply chain (GSC) concepts in the pharmaceutical sector in a developing economy Indian context. In so doing, managers need to determine the potential risks in adopting GSC initiatives to achieve sustainability in operational perspectives. In this sense, this work seeks to distinguish the potential risks in adopting GSC initiatives within the pharmaceutical industry. This work uses a literature review and fuzzy Delphi approach in finalising the risks. This research also uses fuzzy Analytical Hierarchy Process (AHP) for prioritisation of the risks under vague and unclear surroundings. According to the findings, cold chain technology and supply risks categories are highly prioritised. This work can assist practising managers and government authorities in effectively developing and managing GSC initiatives in line with sustainable development goals in the context of the pharmaceutical industry. Finally, a sensitivity test is applied to evaluate the stability of ranking of risks.
Journal: International Journal of Production Research
Pages: 3554-3576
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1543969
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543969
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3554-3576




Template-Type: ReDIF-Article 1.0
Author-Name: Cátia Barbosa
Author-X-Name-First: Cátia
Author-X-Name-Last: Barbosa
Author-Name: Américo Azevedo
Author-X-Name-First: Américo
Author-X-Name-Last: Azevedo
Title: Assessing the impact of performance determinants in complex MTO/ETO supply chains through an extended hybrid modelling approach
Abstract: 
 In make-to-order (MTO)/engineer-to-order (ETO) business environments multiple customer-oriented projects compete for and share resources through interdependent engineering and production activities. Deep knowledge of critical dimensions that affect performance is key in this context. For this, we propose a set of determinants – workload, complexity, outsourcing, design reuse, project type, and knowledge/experience with technology, that impact performance. These determinants are input to an extended hybrid simulation model using system dynamics (SD), discrete event simulation (DES) and agent-based simulation (ABS) that tackles the needs imposed by activities of very different nature, as the project development and manufacturing/assembly operations. The hybrid model is applied to the case of an advanced manufacturing company. Through Monte Carlo sampling, the influence of different combinations of determinants in the performance variability is assessed. A correlation analysis shows evidence of association between all performance determinants and the project time and cost, while no evidence of association between the design reuse and project type determinants and the manufacturing and assembly time.
Journal: International Journal of Production Research
Pages: 3577-3597
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1543970
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543970
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3577-3597




Template-Type: ReDIF-Article 1.0
Author-Name: Simone T. Peinkofer
Author-X-Name-First: Simone T.
Author-X-Name-Last: Peinkofer
Author-Name: Terry L. Esper
Author-X-Name-First: Terry L.
Author-X-Name-Last: Esper
Author-Name: Ronn J. Smith
Author-X-Name-First: Ronn J.
Author-X-Name-Last: Smith
Author-Name: Brent D. Williams
Author-X-Name-First: Brent D.
Author-X-Name-Last: Williams
Title: Assessing the impact of drop-shipping fulfilment operations on the upstream supply chain
Abstract: 
 The use of drop-shipping strategies, the practice where end-consumer orders are fulfilled directly from upstream suppliers upon a retailer’s request, has grown in popularity. Due in large part to the growth of online retailing and the increased focus on integrated omni-channel fulfilment, retailers continue to express the strategic urgency of drop-shipping operations. In a broader sense, the concept of drop-shipping represents a new and emerging aspect of the supply chain triad phenomenon, where a buyer contracts with a supplier to deliver services directly to the buyer’s customer. In order to more fully understand the operational nuances and upstream impacts of triadic service supply chain relationships, we adopt a qualitative research methodology to investigate suppliers in the service triad, a perspective that has been, to-date, under-researched. By exploring these issues in the context of the drop-shipping service triad, we more specifically shed light on the processes and operational challenges that suppliers face when assuming the bridge position in drop-shipping service triads. Therefore, this research extends the current drop-shipping literature by shifting the research focus away from retailers to suppliers; and hence, shifting the focus from strategic use of drop-shipping towards a more tactical/operational perspective by exploring those who carry out drop-shipping operations.
Journal: International Journal of Production Research
Pages: 3598-3621
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1543973
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543973
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3598-3621




Template-Type: ReDIF-Article 1.0
Author-Name: Yao Li
Author-X-Name-First: Yao
Author-X-Name-Last: Li
Author-Name: Yang Cheng
Author-X-Name-First: Yang
Author-X-Name-Last: Cheng
Author-Name: Qing Hu
Author-X-Name-First: Qing
Author-X-Name-Last: Hu
Author-Name: Shenghan Zhou
Author-X-Name-First: Shenghan
Author-X-Name-Last: Zhou
Author-Name: Lei Ma
Author-X-Name-First: Lei
Author-X-Name-Last: Ma
Author-Name: Ming K. Lim
Author-X-Name-First: Ming K.
Author-X-Name-Last: Lim
Title: The influence of additive manufacturing on the configuration of make-to-order spare parts supply chain under heterogeneous demand
Abstract: 
 Additive manufacturing (AM), alongside technological developments, has been used in the production of spare parts with positive results for spare parts supply chains. In this study, we investigate spare parts supply chains serving heterogeneous demands from multiple service locations under the mode of make-to-order. We aim to compare different configurations (i.e. centralised and distributed) of spare parts supply chains in terms of their performance (e.g. sojourn time and cost) and to further propose suggestions to better configure AM-based spare parts supply chains by effectively allocating AM machines at service locations (SLs) or regional distribution centres (RDCs). In order to realise these research objectives, the simulation approach is used as the main research method. Different from the existing perception, our results illustrate that the distributed deployment of AM machines does not always guarantee a quick response, and that centralised configuration is desirable when the demand rate is relatively high due to the pooling effect. The distributed configuration, however, can still be suitable, considering the development of AM technology. Our results also indicate the possibility of a mixed configuration of AM-based supply chains with the potential for outperforming the purely centralised/distributed configuration. The criteria to design such a mixed configuration are also offered.
Journal: International Journal of Production Research
Pages: 3622-3641
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1543975
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1543975
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3622-3641




Template-Type: ReDIF-Article 1.0
Author-Name: Moncer Hariga
Author-X-Name-First: Moncer
Author-X-Name-Last: Hariga
Author-Name: Salbi Babekian
Author-X-Name-First: Salbi
Author-X-Name-Last: Babekian
Author-Name: Zied Bahroun
Author-X-Name-First: Zied
Author-X-Name-Last: Bahroun
Title: Operational and environmental decisions for a two-stage supply chain under vendor managed consignment inventory partnership
Abstract: 
 Supply-chain-based organisations are nowadays facing intense pressure to abide to environmental regulatory requirements while they are striving to be responsive to customers’ needs at the least cost possible. As supply chain activities are among the top contributors to carbon emissions, several recent research works have investigated the impact of carbon regulation policies on economic and environmental supply chain performance. This paper presents integrated economic and environmental models for the one-vendor one-buyer supply chain problem under a vendor managed consignment inventory (VMCI) arrangement. Through the developed models, we study the impacts of two carbon reduction policies, namely carbon cap and carbon tax policies, on supply chain wide costs and carbon emissions. We first provide a much simpler and more compact formulation for the basic single-vendor single-buyer supply chain under VMCI agreement. We also present an environmental-based VMCI model where reduction of carbon footprint is considered as the only objective function. We then extend these two basic models to include each of the two carbon emissions reduction policies. We identify structural properties for the optimal solutions of the two hybrid economic and environmental models and propose algorithms to generate optimal solutions. The results of the computational experiments reveal that the implementation of carbon reduction policies, through carbon cap and carbon tax, may call for the adjustment of the vendor’s production and buyer’s delivery quantities to reduce carbon footprint without significantly increasing the operational costs.
Journal: International Journal of Production Research
Pages: 3642-3662
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1548787
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1548787
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3642-3662




Template-Type: ReDIF-Article 1.0
Author-Name: Paolo Priore
Author-X-Name-First: Paolo
Author-X-Name-Last: Priore
Author-Name: Borja Ponte
Author-X-Name-First: Borja
Author-X-Name-Last: Ponte
Author-Name: Rafael Rosillo
Author-X-Name-First: Rafael
Author-X-Name-Last: Rosillo
Author-Name: David de la Fuente
Author-X-Name-First: David
Author-X-Name-Last: de la Fuente
Title: Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments
Abstract: 
 Firms currently operate in highly competitive scenarios, where the environmental conditions evolve over time. Many factors intervene simultaneously and their hard-to-interpret interactions throughout the supply chain greatly complicate decision-making. The complexity clearly manifests itself in the field of inventory management, in which determining the optimal replenishment rule often becomes an intractable problem. This paper applies machine learning to help managers understand these complex scenarios and better manage the inventory flow. Building on a dynamic framework, we employ an inductive learning algorithm for setting the most appropriate replenishment policy over time by reacting to the environmental changes. This approach proves to be effective in a three-echelon supply chain where the scenario is defined by seven variables (cost structure, demand variability, three lead times, and two partners’ inventory policy). Considering four alternatives, the algorithm determines the best replenishment rule around 88% of the time. This leads to a noticeable reduction of operating costs against static alternatives. Interestingly, we observe that the nodes are much more sensitive to inventory decisions in the lower echelons than in the upper echelons of the supply chain.
Journal: International Journal of Production Research
Pages: 3663-3677
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1552369
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1552369
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3663-3677




Template-Type: ReDIF-Article 1.0
Author-Name: Danping Wen
Author-X-Name-First: Danping
Author-X-Name-Last: Wen
Author-Name: Jing Li
Author-X-Name-First: Jing
Author-X-Name-Last: Li
Author-Name: Tiaojun Xiao
Author-X-Name-First: Tiaojun
Author-X-Name-Last: Xiao
Title: Impact of quality regulation policy on performance of a remanufacturing supply chain with non-waste returns
Abstract: 
 Quality issues in a remanufacturing supply chain with non-waste returns have been reported many times. To address these issues, the government proposes different quality regulation policies. This paper develops a multi-agent simulation model to study how the quality regulation policy affects the performance of a remanufacturing supply chain with non-waste returns. Here, the main performance includes profit and hazard ratio of products. Our results indicate that self-regulation of the market cannot realize a desirable outcome (low hazard ratio and high manufacturer’s profit). Adjusting quality regulation probability is more efficient than adjusting the penalty for inferior products. From the view of increasing manufacturer’s average profit, or improving the government’s efficiency, the best policy is the solely adjusting supervision probability policy. From the view of reducing hazard ratio, the best policy is adjusting supervision probability- penalty policy. The appropriate penalty for inferior products can realize the desirable outcome. With an increasing supervision probability, the hazard ratio decreases, and the manufacturer’s average profit increases because the remanufacturing cost and penalty for inferior products decrease.
Journal: International Journal of Production Research
Pages: 3678-3694
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1553316
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1553316
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3678-3694




Template-Type: ReDIF-Article 1.0
Author-Name: Yuhan Guo
Author-X-Name-First: Yuhan
Author-X-Name-Last: Guo
Author-Name: Fangxia Hu
Author-X-Name-First: Fangxia
Author-X-Name-Last: Hu
Author-Name: Hamid Allaoui
Author-X-Name-First: Hamid
Author-X-Name-Last: Allaoui
Author-Name: Youssef Boulaksil
Author-X-Name-First: Youssef
Author-X-Name-Last: Boulaksil
Title: A distributed approximation approach for solving the sustainable supply chain network design problem
Abstract: 
 This paper introduces a comprehensive Mixed Integer Linear Programming (MILP) model for a sustainable supply chain network design problem, and an efficient Distributed Approximation Approach (DAA) to solve it approximately. We study a multi-echelon, multi-product and multi-modal supply chain with different transportation modes. Besides relevant costs in the supply chain such as procurement, production and distribution cost, we also explicitly consider the environmental footprint, represented by carbon emissions and water consumption from production and transportation. The approximation approach is a decomposition-based method. First, the original problem is divided into a partner selection sub-problem and a transportation planning sub-problem. Then multiple filter mechanisms are used to remove potentially infeasible solutions, and an approximate value of the objective function is calculated for each of the remaining solutions to perform a further selection. The one with the lowest approximation is chosen to be applied with a branch-and-bound method. Finally, the algorithm is paralleled and implemented in Apache Spark distributed computing framework to further improve efficiency. Experimental results show that the proposed DAA can provide high quality solutions compared to the optimal solutions of the MILP model with mostly a negligible relative gap and solve large instances in much shorter time than CPLEX. Moreover, in our numerical study, we also compare the results of our model with another version of the model that does not take the environmental footprint into consideration. The results show that explicitly incorporating environmental footprint results in a substantial decrease of CO2 emissions and water consumption at a negligible cost increase. This insight may be of interest to managers and other decision makers and policy makers.
Journal: International Journal of Production Research
Pages: 3695-3718
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1556412
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1556412
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Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3695-3718




Template-Type: ReDIF-Article 1.0
Author-Name: Ignacio Tamayo-Torres
Author-X-Name-First: Ignacio
Author-X-Name-Last: Tamayo-Torres
Author-Name: Leopoldo Gutierrez-Gutierrez
Author-X-Name-First: Leopoldo
Author-X-Name-Last: Gutierrez-Gutierrez
Author-Name: Antonia Ruiz-Moreno
Author-X-Name-First: Antonia
Author-X-Name-Last: Ruiz-Moreno
Title: Boosting sustainability and financial performance: the role of supply chain controversies
Abstract: 
 In recent years, numerous scandals concerning working conditions in Asia have threatened the reputation of large companies like Wal-Mart and Inditex. Since such scandals call attention to activities harmful to sustainable development, it is very important to study the relationships between concerns for sustainable supply chain management (SSCM), sustainability, and organisations’ market value. The added value of our study is, first, to explore SSCM controversies as drivers of or pressures for adopting and applying sustainability practices; and, second, to contribute to the recent but growing literature that analyses the channels through which SSCM and sustainability practices influence the firm’s value. We introduce sustainability environmental, social, and governance (ESG) practices as a mediator between SSCM controversies and market value to examine whether SSCM controversies with firms’ stakeholders lead to improvements in the ESG dimensions of organisational sustainability. We also examine the relationships between the ESG dimensions and market value, measured as Tobin’s Q ratio. The results confirm both the positive relationships of SSCM controversies to the ESG dimensions two years later and a positive relationship of the dimension of governance to Tobin’s Q. We also confirm a negative and significant relationship of the social dimension to Tobin’s Q, and a non-significant relationship of the environmental dimension to Tobin’s Q.
Journal: International Journal of Production Research
Pages: 3719-3734
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2018.1562248
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1562248
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Template-Type: ReDIF-Article 1.0
Author-Name: Robin Hanson
Author-X-Name-First: Robin
Author-X-Name-Last: Hanson
Author-Name: Lars Medbo
Author-X-Name-First: Lars
Author-X-Name-Last: Medbo
Title: Man-hour efficiency of manual kit preparation in the materials supply to mass-customised assembly
Abstract: 
 Addressing the materials feeding principle of kitting, commonly applied in the materials supply to mass-customised assembly, the current paper has the purpose of exploring how the man-hour efficiency of kit preparation is affected by the design and the context of the kit preparation. The study presented in the paper is based on a comprehensive methodology, comprising several steps and considering a large set of qualitative as well as quantitative data from 15 case studies. It also utilises the expertise of practitioners from the industry. The paper provides a valuable addition to the existing literature where empirical evidence is scarce. From a practical perspective, it offers support to the design of man-hour efficient kit preparation systems. The findings show that the design and the context of the kit preparation system can have a decisive, yet complex, impact on the man-hour efficiency and, thereby, on an assessment of the applicability of kitting. The paper identifies several important aspects of both design and context and indicates how these aspects are linked to the man-hour efficiency of kit preparation.
Journal: International Journal of Production Research
Pages: 3735-3747
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2019.1566653
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566653
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Template-Type: ReDIF-Article 1.0
Author-Name: R. Rajesh
Author-X-Name-First: R.
Author-X-Name-Last: Rajesh
Title: Social and environmental risk management in resilient supply chains: A periodical study by the Grey-Verhulst model
Abstract: 
 As sustainability and allied concerns are at present gaining greater than before attention amongst stakeholders, enterprises are enforced to consider social and environmental risk assessments along with conventional economic risk assessments. Hence to advance sustainable competitive advantages, the property of resilience is becoming a success factor for enterprises. Resilience is the property of enterprises or their supply chains to resume operations after disruptions and to regain its sustainable competitive advantages quickly and effectively. This study essentially focuses on identifying drivers of social and environmental risk management (SERM) in resilient supply chains and to acknowledge the importance of these drivers towards the implementation of SERM practices of enterprises. Representative case studies of three electronics manufacturing firms were also considered in this research to gain practical insights. Periodical data analysis has been piloted for the collected datasets from these companies. Since the sequences of the collected data show saturated sigmoidal tendencies, the Verhulst model fits best with the data sequences. A Grey-Verhulst model has been implemented in this research and was practically tested for case firms to exemplify the data sequences of prediction and to effectually improve the SERM performances of firms.
Journal: International Journal of Production Research
Pages: 3748-3765
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2019.1566656
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566656
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Template-Type: ReDIF-Article 1.0
Author-Name: Yeu-Shiang Huang
Author-X-Name-First: Yeu-Shiang
Author-X-Name-Last: Huang
Author-Name: Yung-Chen Hsu
Author-X-Name-First: Yung-Chen
Author-X-Name-Last: Hsu
Author-Name: Chih-Chiang Fang
Author-X-Name-First: Chih-Chiang
Author-X-Name-Last: Fang
Title: A study on contractual agreements in supply chains of agricultural produce
Abstract: 
 Agricultural produce deteriorates in both quality and quantity over time, and how to determine appropriate operating and marketing strategies to reduce the loss from rottenness is essential in supply chains for such items. This study considers a two-echelon supply chain in which agricultural produce is provided by a grower to a wholesaler, and the harvest quantity for the grower may decrease due to unpredictable pest problems or weather factors. In addition, agricultural produce may be damaged during transportation and thus become inferior products with less value. The two different scenarios are considered in this study: with and without a contractual agreement, to develop the corresponding optimal pricing strategies for the grower and wholesaler. The results indicate that a contractual agreement by setting moderate ordering boundaries can achieve a win-win situation for both parties by mitigating the grower’s risk, since it can encourage the grower to plant more produce and thus ensure that the wholesaler can have enough produce to sell. Besides, in case that a low proportion of inferior products and a low discount rate can be managed, the use of contractual agreements would be beneficial for the grower. Moreover, the rise in the retailing prices of both the regular and inferior agricultural produce may collectively increase the total profit of the supply chain, but can actually hurt the wholesaler’s profit.
Journal: International Journal of Production Research
Pages: 3766-3783
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2019.1566658
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566658
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Template-Type: ReDIF-Article 1.0
Author-Name: Xianhai Meng
Author-X-Name-First: Xianhai
Author-X-Name-Last: Meng
Title: Lean management in the context of construction supply chains
Abstract: 
 Construction started its lean journey with learning from manufacturing. Unlike lean manufacturing, few studies to date have investigated lean construction in both breadth and depth, especially from the perspective of construction supply chains. The limited understanding of lean construction results in a research problem. This research aims to explore the implementation of lean principles in the context of project-based construction supply chains. It achieves its aim through an empirical investigation in the UK. A combination of quantitative and qualitative methodologies provides this research with validity and reliability. Lean principles are found applicable to both residential building projects and many other types of construction projects. It is also found that lean construction can be enhanced if it synergizes with supply chain collaboration. Another finding is that lean management has a significant impact on project performance. Nowadays, construction pursues best lean practices through both learning from manufacturing and developing its own paths. Similar to manufacturing, more and more construction projects adopt industrialised and standardised production and lean management with supply chain collaboration to become leaner. On the other hand, construction-specific management approaches and information technology (IT) tools are increasingly used in lean construction practices to maximise value and minimise waste.
Journal: International Journal of Production Research
Pages: 3784-3798
Issue: 11
Volume: 57
Year: 2019
Month: 6
X-DOI: 10.1080/00207543.2019.1566659
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1566659
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Template-Type: ReDIF-Article 1.0
Author-Name: Michael A. Greig
Author-X-Name-First: Michael A.
Author-X-Name-Last: Greig
Author-Name: Judy Village
Author-X-Name-First: Judy
Author-X-Name-Last: Village
Author-Name: Filippo A. Salustri
Author-X-Name-First: Filippo A.
Author-X-Name-Last: Salustri
Author-Name: Saeed Zolfaghari
Author-X-Name-First: Saeed
Author-X-Name-Last: Zolfaghari
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Title: A tool to predict physical workload and task times from workstation layout design data
Abstract: 
 This paper presents the development and proof of concept of a tool to predict worker and system performance using inputs of work element descriptions and hand locations from a seated, light assembly workstation layout. Tool inputs can be obtained in the design stage. Tool outputs include human factors (shoulder load, hand movement, reach zone acceptability) and system (element time and cycle time) information. Shoulder loads are predicted from two-dimensional shoulder models created from a digital human model. The tool is demonstrated on a previous observation-based assessment of a workstation redesign. Results reflected the findings of the observation assessment, but also provided more work cycle information as well as cumulative, work shift information. The tool enables prediction of workload and task performance times from design stage parameters without the need of an ergonomist. It can be used to predict critical components of the layout and plan workflow based on worker, workstation and task information. The tool is available for free downloaded at: www.researchgate.net/project/Workstation-Efficiency-Evaluator-WEE-Tool.
Journal: International Journal of Production Research
Pages: 5306-5323
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1378827
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1378827
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Template-Type: ReDIF-Article 1.0
Author-Name: Golshan Madraki
Author-X-Name-First: Golshan
Author-X-Name-Last: Madraki
Author-Name: Robert P. Judd
Author-X-Name-First: Robert P.
Author-X-Name-Last: Judd
Title: Efficient algorithm to find makespan in manufacturing systems under multiple scheduling perturbations
Abstract: 
 Manufacturing scheduling improvement heuristics iterate over trial schedules to determine a satisfactory schedule. During each iteration, a performance measure (e.g. makespan) is calculated. The paper presents an efficient algorithm, Structural Perturbation Algorithm (SPA), that accelerates the calculation of the makespan. This means all scheduling improvement heuristics using SPA to calculate makespan for each trial schedule will run faster. To achieve this goal, the manufacturing system is modelled by a Directed Acyclic Graph (DAG). Schedule trials can be described as a perturbed DAG where multiple edges are added and deleted. The major contribution of this research is that SPA can handle multiple edge deletions/additions with a single pass which makes it more efficient in terms of time complexity than current approaches. SPA accomplishes this by partitioning the nodes into three regions based on the locations of the added and deleted edges. Then, SPA updates the length of the affected nodes in each region. The application of SPA is not limited to the scheduling problem. The SPA can be applied in other fields as long as the problem can be described as a Perturbed DAG.
Journal: International Journal of Production Research
Pages: 5402-5418
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1407884
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1407884
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiang Yi Zhang
Author-X-Name-First: Xiang Yi
Author-X-Name-Last: Zhang
Author-Name: Lu Chen
Author-X-Name-First: Lu
Author-X-Name-Last: Chen
Title: A re-entrant hybrid flow shop scheduling problem with machine eligibility constraints
Abstract: 
 A production scheduling problem originating from a real rotor workshop is addressed in the paper. Given its specific characteristics, the problem is formulated as a re-entrant hybrid flow shop scheduling problem with machine eligibility constraints. A mixed integer linear programming model of the problem is provided and solved by the Cplex solver. In order to solve larger sized problems, a discrete differential evolution (DDE) algorithm with a modified crossover operator is proposed. More importantly, a new decoder addressing the machine eligibility constraints is developed and embedded to the algorithm. To validate the performance of the proposed DDE algorithm, various test problems are examined. The efficiency of the proposed algorithm is compared with two other algorithms modified from the existing ones in the literatures. A one-way ANOVA analysis and a sensitivity analysis are applied to intensify the superiority of the new decoder. Tightness of due dates and different levels of scarcity of machines subject to machine eligibility restrictions are discussed in the sensitivity analysis. The results indicate the pre-eminence of the new decoder and the proposed DDE algorithm.
Journal: International Journal of Production Research
Pages: 5293-5305
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1408971
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1408971
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Template-Type: ReDIF-Article 1.0
Author-Name: MohammadMohsen Aghelinejad
Author-X-Name-First: MohammadMohsen
Author-X-Name-Last: Aghelinejad
Author-Name: Yassine Ouazene
Author-X-Name-First: Yassine
Author-X-Name-Last: Ouazene
Author-Name: Alice Yalaoui
Author-X-Name-First: Alice
Author-X-Name-Last: Yalaoui
Title: Production scheduling optimisation with machine state and time-dependent energy costs
Abstract: 
 The increase of energy costs specially in manufacturing system encourages researchers to pay more attention to energy management in different ways. This paper investigates a non-preemptive single-machine manufacturing environment to reduce total energy costs of a production system. For this purpose, two new mathematical models are presented. The first contribution consists of an improvement of a mathematical formulation proposed in the literature which deals and deals with a scheduling problem at machine level to process the jobs in a predetermined order. The second model focuses on the generalisation of the previous one to deal simultaneously with the production scheduling at machine level as well as job level. So, the initial predetermined fixed sequence assumption is removed. Since this problem is NP-hard, an heuristic algorithm and a genetic algorithm based on the second model are developed to provide good solutions in reasonable computational time. Finally, the effectiveness of the proposed models and optimisation methods have been tested with different numerical experiments. In average, for small size instances which the mathematical model provides a solution in reasonable computational time, a gap of 2.2% for the heuristic and 1.82% for GA are achieved comparing to the exact method’s solution. These results demonstrate the accuracy and efficiency of both proposed algorithms.
Journal: International Journal of Production Research
Pages: 5558-5575
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1414969
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1414969
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhaojing Wang
Author-X-Name-First: Zhaojing
Author-X-Name-Last: Wang
Author-Name: Hao Hu
Author-X-Name-First: Hao
Author-X-Name-Last: Hu
Title: Dynamic response to demand variability for precast production rescheduling with multiple lines
Abstract: 
 Production scheduling plays a crucial role in the prefabricated construction productivity and on-time delivery of precast components (PCs). However, previous studies mainly focused on the static scheduling of single production line without considering the demand variability in practice. To achieve dynamic production planning, a Two-level Rescheduling Model for Precast Production with multiple production lines is developed to minimise the rescheduling costs based on genetic algorithm, from the two levels of (1) selection of production line and (2) rescheduling of jobs based on PCs’ priority. Further, two scenarios of different and shared mould types are investigated to represent real-world production environments. Finally, a real case study is conducted to test the validity of proposed rescheduling model. 58.1 and 48.5% cost savings are achieved by comparison to no response to changes and heuristic rescheduling methods, respectively. This research contributes to the precast production theory by expanding the insight into dynamic rescheduling with multiple production lines. The methodology will promote the on-time delivery of PCs and enhance the dynamic precast production management.
Journal: International Journal of Production Research
Pages: 5386-5401
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1414970
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1414970
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohamed El Amine Boudella
Author-X-Name-First: Mohamed El Amine
Author-X-Name-Last: Boudella
Author-Name: Evren Sahin
Author-X-Name-First: Evren
Author-X-Name-Last: Sahin
Author-Name: Yves Dallery
Author-X-Name-First: Yves
Author-X-Name-Last: Dallery
Title: Kitting optimisation in Just-in-Time mixed-model assembly lines: assigning parts to pickers in a hybrid robot–operator kitting system
Abstract: 
 With increasing components’ variety in mixed-model assembly lines, industrials show interest in kitting operations using robots. This paper deals with a hybrid kitting system that consists of a robot and an operator working in series to deliver parts to a Just-In-Time mixed-model assembly line. We develop a mathematical model that optimally assigns stock keeping units to either the robot or the operator so that the cycle time of the overall system is optimised. To test the model, a case study from the automotive sector is presented and a sensitivity analysis is carried out on relevant system parameters.
Journal: International Journal of Production Research
Pages: 5475-5494
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1418988
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1418988
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Template-Type: ReDIF-Article 1.0
Author-Name: Burak Gökgür
Author-X-Name-First: Burak
Author-X-Name-Last: Gökgür
Author-Name: Brahim Hnich
Author-X-Name-First: Brahim
Author-X-Name-Last: Hnich
Author-Name: Selin Özpeynirci
Author-X-Name-First: Selin
Author-X-Name-Last: Özpeynirci
Title: Parallel machine scheduling with tool loading: a constraint programming approach
Abstract: 
 This paper presents constraint programming models that aim to solve scheduling and tool assignment problems in parallel machine environments. There are a number of jobs to be processed on parallel machines. Each job requires a set of tools, but limited number of tools are available in the system due to economic restrictions. The problem is to assign the jobs and the required tools to machines and to determine the schedule so that the makespan is minimised. Three constraint programming models are developed and compared with existing methods described in the literature.
Journal: International Journal of Production Research
Pages: 5541-5557
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1421781
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421781
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Template-Type: ReDIF-Article 1.0
Author-Name: Byung Kwon Lee
Author-X-Name-First: Byung Kwon
Author-X-Name-Last: Lee
Author-Name: Loo Hay Lee
Author-X-Name-First: Loo Hay
Author-X-Name-Last: Lee
Author-Name: Ek Peng Chew
Author-X-Name-First: Ek Peng
Author-X-Name-Last: Chew
Title: Analysis on high throughput layout of container yards
Abstract: 
 The operational efficiency of handling resources plays an important role in promoting container flows at a container terminal. As these handling resources operate on specific yard layouts, a well-designed layout will promote the performance of the handling activities. This study aims to discuss a design process to maximise the throughput capacity, as well as minimise the resource configuration when designing the yard layout. Various experiments were conducted and analysed to demonstrate the effects on the layout structure and the resource configuration for the two types of parallel yard layouts: the double-lane yard layout where vehicles can access the block at both side and the single-lane yard layout where two adjacent blocks in a row are grouped together and vehicles can access each block at only one side. According to the findings, the container flows by vehicles exert greater influence on the design of a container yard compared to the time taken for container processing by quay cranes and yard cranes. It is also found that the single-lane yard layout is preferable when high throughput capacity is required, whereas the double-lane yard layout is superior in favour of high efficiency of vehicle flows.
Journal: International Journal of Production Research
Pages: 5345-5364
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2017.1421782
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421782
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Template-Type: ReDIF-Article 1.0
Author-Name: Chin-Chih Chang
Author-X-Name-First: Chin-Chih
Author-X-Name-Last: Chang
Title: Optimal age replacement scheduling for a random work system with random lead time
Abstract: 
 System maintenance and spare parts are two closely related logistics activities since maintenance generates the demand for spare parts. Most studies on integrated models of preventive replacement and inventory of spare parts have focused on age replacement scheduling, while random replacement policy, which is sensible and necessary in practice, is rarely discussed and applied. The purpose of this paper is to present a generalised age replacement policy for a system which works at random time and considers random lead time for replacement delivery. To model an imperfect maintenance action, we consider that the system undergoes minimal repairs at minor failures and corrective replacements at catastrophic failures. Before catastrophic failures, the system is replaced preventively at age T or at the completion of a working time, whichever occurs first. The main objective is to determine an optimal schedule of age replacement that minimises the mean cost rate function of the system in a finite time horizon. The existence and uniqueness of optimal replacement policy are derived analytically and computed numerically. It can be seen that the proposed model is a generalisation of the previous works in maintenance theory.
Journal: International Journal of Production Research
Pages: 5511-5521
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1425017
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1425017
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Template-Type: ReDIF-Article 1.0
Author-Name: Pedro L. Gonzalez-R
Author-X-Name-First: Pedro L.
Author-X-Name-Last: Gonzalez-R
Author-Name: Marcos Calle
Author-X-Name-First: Marcos
Author-X-Name-Last: Calle
Author-Name: Jose L. Andrade-Pineda
Author-X-Name-First: Jose L.
Author-X-Name-Last: Andrade-Pineda
Title: Job shop management of products under internal lifespan and external due date
Abstract: 
 Deteriorating items are found in a wide variety of productive environments and have been extensively reported in the literature. However, the evolution of markets demand the development of new products and new forms of work are made necessary to adapt production systems to those changes. The present work focuses on the production control of perishable products in a job shop environment. Specifically, in those products that have an expiration date within the production interval (internal caducity) that must be delivered before a certain date. As far as we know, there are no previous works that focus on the internal caducity of products at the production-control level. Two systems of different nature have been compared: Workload Control (WLC) and Kanban. WLC is usually a benchmark in job shop and made to order environments. Recent studies show that Kanban, traditionally used in JIT (Just in Time) environments, performs similarly or even better than WLC. The study was performed by discrete events simulation using Python© language, SimPy© and DEAP© modules, and considering several responses of the systems. The results show that both systems have a good performance in a variety of scenarios, with overall performance of Kanban in terms of internal caducity and tardy deliveries.
Journal: International Journal of Production Research
Pages: 5457-5474
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1430908
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1430908
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Template-Type: ReDIF-Article 1.0
Author-Name: Qi Lei
Author-X-Name-First: Qi
Author-X-Name-Last: Lei
Author-Name: Weifei Guo
Author-X-Name-First: Weifei
Author-X-Name-Last: Guo
Author-Name: Yuchuan Song
Author-X-Name-First: Yuchuan
Author-X-Name-Last: Song
Title: Integrated scheduling algorithm based on an operation relationship matrix table for tree-structured products
Abstract: 
 The processing and assembly of tree-structured products can be performed simultaneously, which leads to an integrated scheduling problem. To address this problem, we propose an integrated scheduling algorithm based on an operation relationship matrix table. The algorithm initially establishes an operation relationship matrix table. The improved genetic algorithm based on the table is subsequently adopted to solve this problem. To ensure that the initial population satisfies the sequence constraints, this algorithm uses a novel encoding method based on the dynamic operation relationship matrix table. In addition, corresponding new crossover and mutation methods are designed to ensure the feasibility of the generated offspring individuals. A simple decoding method based on the operation relationship matrix table is also presented. The feasibility and superiority of the proposed algorithm is demonstrated experimentally. Some existing algorithms have defects, such as scale limitation, indispensable repair process and incomplete encoding. However, the proposed algorithm not only overcomes such defects but also significantly reduces the complexity of addressing the problem, which can provide valuable references for solving similar problems.
Journal: International Journal of Production Research
Pages: 5437-5456
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1442942
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1442942
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Template-Type: ReDIF-Article 1.0
Author-Name: Peng Guo
Author-X-Name-First: Peng
Author-X-Name-Last: Guo
Author-Name: Wenming Cheng
Author-X-Name-First: Wenming
Author-X-Name-Last: Cheng
Author-Name: Yi Wang
Author-X-Name-First: Yi
Author-X-Name-Last: Wang
Author-Name: Nils Boysen
Author-X-Name-First: Nils
Author-X-Name-Last: Boysen
Title: Gantry crane scheduling in intermodal rail-road container terminals
Abstract: 
 Modern rail-road container terminals serve as important consolidation nodes in intermodal transportation networks where containers are transferred between freight trains and trucks. Among the most important decision problems in these yards is the crane scheduling problem, which decides on the sequences of container moves executed by each of the parallel gantry cranes. This paper treats a rich crane scheduling problem, which considers plenty relevant constraints and is directly applicable in Chinese intermodal terminals. For solving this problem, we propose a fix-and-optimise procedure, which is easy to implement and shown to successfully solve even large-sized instances with 100 container moves in reasonable time.
Journal: International Journal of Production Research
Pages: 5419-5436
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1444812
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1444812
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Template-Type: ReDIF-Article 1.0
Author-Name: Fan Yue
Author-X-Name-First: Fan
Author-X-Name-Last: Yue
Author-Name: Shiji Song
Author-X-Name-First: Shiji
Author-X-Name-Last: Song
Author-Name: Yuli Zhang
Author-X-Name-First: Yuli
Author-X-Name-Last: Zhang
Author-Name: Jatinder N.D. Gupta
Author-X-Name-First: Jatinder N.D.
Author-X-Name-Last: Gupta
Author-Name: Raymond Chiong
Author-X-Name-First: Raymond
Author-X-Name-Last: Chiong
Title: Robust single machine scheduling with uncertain release times for minimising the maximum waiting time
Abstract: 
 We study a single machine scheduling problem (SMSP) with uncertain job release times (JRTs) under the maximum waiting time (MWT) criterion. To deal with the uncertainty, a robust model is established to find an optimal schedule, which minimises the worst-case MWT (W-MWT) when JRTs vary over given time intervals. Although infinite possible scenarios for JRTs exist, we show that only n scenarios are needed for calculating the W-MWT, where n is the number of jobs. Based on this property, the robust (SMSP) with uncertain JRTs to minimise the W-MWT is formulated as a mixed integer linear programming problem. To solve large-size problem instances, an efficient two-stage heuristic (TSH) is proposed. In the first stage, n near-optimal schedules are obtained by solving n deterministic scenario-based SMSPs, and their W-MWTs are evaluated. To speed up the solution and evaluation process, a modified Gusfield’s heuristic is proposed by exploiting the inner connections of these SMSPs. To further improve the schedule obtained in the first stage, the second stage consists of a variable neighbourhood search method by combining both swap neighbourhood search and insert neighbourhood search. We also develop a method to calculate the lower bound of the proposed model so that we can evaluate the performance of the solutions given by the TSH. Experimental results confirm the robustness of schedules produced and advantages of the proposed TSH over other algorithms in terms of solution quality and run time.
Journal: International Journal of Production Research
Pages: 5576-5592
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1463473
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1463473
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:16:p:5576-5592




Template-Type: ReDIF-Article 1.0
Author-Name: Yan Ye
Author-X-Name-First: Yan
Author-X-Name-Last: Ye
Author-Name: Jingfeng Li
Author-X-Name-First: Jingfeng
Author-X-Name-Last: Li
Author-Name: Kaibin Li
Author-X-Name-First: Kaibin
Author-X-Name-Last: Li
Author-Name: Hui Fu
Author-X-Name-First: Hui
Author-X-Name-Last: Fu
Title: Cross-docking truck scheduling with product unloading/loading constraints based on an improved particle swarm optimisation algorithm
Abstract: 
 Cross-docking is a very useful logistics technique that can substantially reduce distribution costs and improve customer satisfaction. A key problem in its success is truck scheduling, namely, decision on assignment and docking sequence of inbound/outbound trucks to receiving/shipping dock doors. This paper focuses on the problem with the requirement of unloading/loading products in a given order, which is very common in many industries, but is less concerned by existing researches. An integer programming model is established to minimise the makespan. An improved particle swarm optimisation (ωc-PSO) algorithm is proposed for solving it. In the algorithm, a cosine decreasing strategy of inertia weight is designed to dynamically balance global and local search. A repair strategy is put forward for continuous search in the feasible solution space and a crossover strategy is presented to prevent the algorithm from falling into local optimum. After algorithm parameters are tuned using Taguchi method, computational experiments are conducted on different problem scales to evaluate ωc-PSO against genetic algorithm, basic PSO and GLNPSO. The results show that ωc-PSO outperforms other three algorithms, especially when the number of dock doors, trucks and product types is great. Statistical tests show that the performance difference is statistically significant.
Journal: International Journal of Production Research
Pages: 5365-5385
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1464678
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1464678
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Template-Type: ReDIF-Article 1.0
Author-Name: Imad Belassiria
Author-X-Name-First: Imad
Author-X-Name-Last: Belassiria
Author-Name: Mohamed Mazouzi
Author-X-Name-First: Mohamed
Author-X-Name-Last: Mazouzi
Author-Name: Said ELfezazi
Author-X-Name-First: Said
Author-X-Name-Last: ELfezazi
Author-Name: Anass Cherraﬁ
Author-X-Name-First: Anass
Author-X-Name-Last: Cherraﬁ
Author-Name: Zakaria ELMaskaoui
Author-X-Name-First: Zakaria
Author-X-Name-Last: ELMaskaoui
Title: An integrated model for assembly line re-balancing problem
Abstract: 
 In this paper, an integrated approach for assembly line rebalancing problem (IALRP) is proposed to quickly react and find an optimal rebalancing of the line when disruptive event occurs because of product demand changes. This model is motivated by real-life application of an automotive cable manufacturer which provides more realistic constraints. To solve the problem, we propose a genetic algorithm (GA) hybridised with a heuristic priority rule-based procedure. This hybridisation is used to add more rich seeds to the initial population and consequently to improve the convergence capability and performance of the GA. After the disturbance, we aim to find a rebalance with the proposed approach to maximise the line efficiency and distributing the idle time across the workstations as equally as possible. To evaluate the efficiency of the proposed algorithm, set of samples collected from the literature are used. The real case study and the experiment results show the proposed approach is very effective and competitive.
Journal: International Journal of Production Research
Pages: 5324-5344
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1467061
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1467061
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Template-Type: ReDIF-Article 1.0
Author-Name: Tao Meng
Author-X-Name-First: Tao
Author-X-Name-Last: Meng
Author-Name: Quan-Ke Pan
Author-X-Name-First: Quan-Ke
Author-X-Name-Last: Pan
Author-Name: Hong-Yan Sang
Author-X-Name-First: Hong-Yan
Author-X-Name-Last: Sang
Title: A hybrid artificial bee colony algorithm for a flexible job shop scheduling problem with overlapping in operations
Abstract: 
 Overlapping in operations is an effective technology for productivity improvement in modern manufacturing systems. Thus far, however, there are still rare works on flexible job shop scheduling problems (FJSPs) concerning this strategy. In this paper, we present a hybrid artificial bee colony (hyABC) algorithm to minimise the total flowtime for a FJSP with overlapping in operations. In the proposed hyABC, a dynamic scheme is introduced to fine-tune the search scope adaptively. In view of poor exploitation ability of artificial bee colony algorithm, a modified migrating birds optimisation algorithm (MMBO) is developed and integrated into the search process for better balancing global exploration and local exploitation. In MMBO, a forward share strategy with one-job based crossover is designed to make good use of valuable information from behind solutions. Besides, an improved downward share scheme is adopted to increase diversification of the population, and thus alleviate the premature convergence. Extensive experiments based on benchmark instances with different scales are carried out and comparisons with other recent algorithms identify the effectiveness of the proposed hyABC.
Journal: International Journal of Production Research
Pages: 5278-5292
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1467575
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1467575
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Template-Type: ReDIF-Article 1.0
Author-Name: Yiyo Kuo
Author-X-Name-First: Yiyo
Author-X-Name-Last: Kuo
Author-Name: Yen-Po Chen
Author-X-Name-First: Yen-Po
Author-X-Name-Last: Chen
Author-Name: Yu-Cheng Wang
Author-X-Name-First: Yu-Cheng
Author-X-Name-Last: Wang
Title: Operator assignment with cell loading and product sequencing in labour-intensive assembly cells – a case study of a bicycle assembly company
Abstract: 
 This research deals with an operator assignment problem in which cell loading and product sequencing are taken into account in labour-intensive assembly cells. In each cell the number of assembly tasks is more than the number of operators, so multi-assembly tasks are assigned to each operator. Because the assembly procedure and time required for each assembly task are quite different for different products, some tasks will be transferred when the product changes. Reducing the number of task transfers can smooth the process of product change. A four-phase methodology is proposed to minimise the total manpower required and task transfers at the same time. The four phases are manpower configuration design, calculating the number of task transfers, manpower requirement minimization and cell loading and product sequencing optimization. A case study from a bicycle assembly company is introduced. For comparison, two methodologies are applied. The results show that the proposed four phase methodology can provided the solution with fewer task transfers based on the same total manpower requirement. However, when the number of products increases, the computation time of the proposed four-phase methodology increases rapidly.
Journal: International Journal of Production Research
Pages: 5495-5510
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1470345
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1470345
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Template-Type: ReDIF-Article 1.0
Author-Name: Karin Bogner
Author-X-Name-First: Karin
Author-X-Name-Last: Bogner
Author-Name: Ulrich Pferschy
Author-X-Name-First: Ulrich
Author-X-Name-Last: Pferschy
Author-Name: Roland Unterberger
Author-X-Name-First: Roland
Author-X-Name-Last: Unterberger
Author-Name: Herwig Zeiner
Author-X-Name-First: Herwig
Author-X-Name-Last: Zeiner
Title: Optimised scheduling in human–robot collaboration – a use case in the assembly of printed circuit boards
Abstract: 
 Advances in the technologies of sensors and lightweight robots increasingly enable direct physical interaction between humans and robots. This so-called human–robot collaboration is supposed to offer more flexibility in production processes, as opposed to fully automated processes. The aim of this contribution is to describe an integer linear programming model which optimally coordinates the distribution of tasks between humans and robots in a realistic production process of printed circuit boards (PCBs), where the objective is to minimise the completion time of a board. In addition, we discuss an extended case wherein a whole set of different boards is to be assembled, which is highly relevant for low volume production with a high degree of customisation. After stating an extended integer linear programming (ILP) formulation, we propose two practical approaches for solving the computationally more complex second scenario: an order-based heuristic approach and a matheuristic applying a truncated variant of the ILP model with different sequencing strategies. The computational evaluation based on a real-world use case from the PCB industry underlines the efficacy of the matheuristic approach for obtaining a good overall makespan.
Journal: International Journal of Production Research
Pages: 5522-5540
Issue: 16
Volume: 56
Year: 2018
Month: 8
X-DOI: 10.1080/00207543.2018.1470695
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1470695
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Template-Type: ReDIF-Article 1.0
Author-Name: Casper Selmer Frandsen
Author-X-Name-First: Casper Selmer
Author-X-Name-Last: Frandsen
Author-Name: Martin Mathias Nielsen
Author-X-Name-First: Martin Mathias
Author-X-Name-Last: Nielsen
Author-Name: Atanu Chaudhuri
Author-X-Name-First: Atanu
Author-X-Name-Last: Chaudhuri
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Title: In search for classification and selection of spare parts suitable for additive manufacturing: a literature review
Abstract: 
 This paper reviews the literature on additive manufacturing (AM) technologies and equipment, and spare parts classification criteria to propose a systematic process for selecting spare parts which are suitable for AM. This systematic process identifies criteria that can be used to select spare parts that are suitable for AM. The review found that there is limited research that addresses identifying processes for spare parts selection for AM, even though companies have identified this to be a key challenge in adopting AM. Seven areas for future research are identified relating to the methodology of spare parts selection for AM, processes for cross-functional integration in selecting spare parts for AM, broadening the spare parts portfolio that is suitable for AM (by considering usage of AM in conjunction with conventional technologies), and potential impact of AM on product modularity and integrality.
Journal: International Journal of Production Research
Pages: 970-996
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1605226
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1605226
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:970-996




Template-Type: ReDIF-Article 1.0
Author-Name: Shikha Singh
Author-X-Name-First: Shikha
Author-X-Name-Last: Singh
Author-Name: Subhas Chandra Misra
Author-X-Name-First: Subhas Chandra
Author-X-Name-Last: Misra
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Title: Establishment of critical success factors for implementation of product lifecycle management systems
Abstract: 
 The present study has been undertaken with the purpose of investigating the critical success factors for the implementation of product lifecycle management (PLM) systems in manufacturing companies. Two exploratory case-based studies were conducted followed by a generalised study to establish the critical success factors for PLM systems’ implementation in manufacturing firms. Hybrid multi-criteria decision-making methods were employed to identify the causal factors and prioritise them for the implementation of PLM systems in an automotive and aerospace firm. The priority of the factors has also been confirmed by executives from broader PLM domain through a confirmatory t-test. The identified critical success factors can be utilised as directive guidelines by manufacturing organisations for the successful implementation of PLM systems. Most researchers have studied only the technological aspects of PLM, while very few have discussed the success factors to PLM implementation. The present study is highlighting PLM as a management concept, supporting PLM systems implementation in organisations, and discussing the critical success factors for effective PLM systems implementation.
Journal: International Journal of Production Research
Pages: 997-1016
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1605227
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1605227
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:997-1016




Template-Type: ReDIF-Article 1.0
Author-Name: Jianjun Ouyang
Author-X-Name-First: Jianjun
Author-X-Name-Last: Ouyang
Author-Name: Jie Fu
Author-X-Name-First: Jie
Author-X-Name-Last: Fu
Title: Optimal strategies of improving energy efficiency for an energy-intensive manufacturer considering consumer environmental awareness
Abstract: 
 Motivated by the observation that many energy-intensive manufacturers are adopting energy efficiency to deal with rapidly increasing consumer environmental awareness (CEA), this paper is the first attempt that extends CEA into the energy-saving area using several mathematical models and investigates how an energy-intensive manufacturer, facing choices of self-saving, shared savings and guaranteed savings, determines the optimal strategies of improving energy efficiency when CEA is considered. When the actual savings per unit is deterministic (DU scenario), we derive the optimal strategies of improving energy efficiency for both the manufacturer and the energy service company (ESCO) under the two energy-saving modes: self-saving and shared savings. Our results show the following: (1) CEA always has positive impacts on the optimal predicted savings per unit and the optimal profits of both the manufacturer and the ESCO; (2) interestingly, the impact of CEA on the optimal choice between energy saving modes may not exist. Furthermore, when the actual savings per unit is stochastic (UU scenario), and if the energy-intensive manufacturer introduces guaranteed savings, we find that most of the optimal strategies under the UU scenario are similar to those under the DU scenario. Finally, through numerical studies, we demonstrate the important results.
Journal: International Journal of Production Research
Pages: 1017-1033
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1607977
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1607977
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Template-Type: ReDIF-Article 1.0
Author-Name: Guanghui Zhou
Author-X-Name-First: Guanghui
Author-X-Name-Last: Zhou
Author-Name: Chao Zhang
Author-X-Name-First: Chao
Author-X-Name-Last: Zhang
Author-Name: Zhi Li
Author-X-Name-First: Zhi
Author-X-Name-Last: Li
Author-Name: Kai Ding
Author-X-Name-First: Kai
Author-X-Name-Last: Ding
Author-Name: Chuang Wang
Author-X-Name-First: Chuang
Author-X-Name-Last: Wang
Title: Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing
Abstract: 
 Rapid advances in new generation information technologies, such as big data analytics, internet of things (IoT), edge computing and artificial intelligence, have nowadays driven traditional manufacturing all the way to intelligent manufacturing. Intelligent manufacturing is characterised by autonomy and self-optimisation, which proposes new demands such as learning and cognitive capacities for manufacturing cell, known as the minimum implementation unit for intelligent manufacturing. Consequently, this paper proposes a general framework for knowledge-driven digital twin manufacturing cell (KDTMC) towards intelligent manufacturing, which could support autonomous manufacturing by an intelligent perceiving, simulating, understanding, predicting, optimising and controlling strategy. Three key enabling technologies including digital twin model, dynamic knowledge bases and knowledge-based intelligent skills for supporting the above strategy are analysed, which equip KDTMC with the capacities of self-thinking, self-decision-making, self-execution and self-improving. The implementing methods of KDTMC are also introduced by a thus constructed test bed. Three application examples about intelligent process planning, intelligent production scheduling and production process analysis and dynamic regulation demonstrate the feasibility of KDTMC, which provides a practical insight into the intelligent manufacturing paradigm.
Journal: International Journal of Production Research
Pages: 1034-1051
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1607978
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1607978
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:1034-1051




Template-Type: ReDIF-Article 1.0
Author-Name: Jani Koskinen
Author-X-Name-First: Jani
Author-X-Name-Last: Koskinen
Author-Name: Csaba Raduly-Baka
Author-X-Name-First: Csaba
Author-X-Name-Last: Raduly-Baka
Author-Name: Mika Johnsson
Author-X-Name-First: Mika
Author-X-Name-Last: Johnsson
Author-Name: Olli S. Nevalainen
Author-X-Name-First: Olli S.
Author-X-Name-Last: Nevalainen
Title: Rolling horizon production scheduling of multi-model PCBs for several assembly lines
Abstract: 
 The joint task of allocating several PCB assembly jobs to a set of production lines, load balancing of the line machines and job scheduling is considered. The production facility includes a number of assembly lines of different kinds, the PCB jobs are of different types and they should be allocated to suitable (i.e. feasible) lines. Scheduling of the production should respect the predefined release and due dates, and the objective is to minimise the sum of job tardy times. The scheduling is of the rolling-horizon-type where at the beginning of each planning period new jobs are inserted in the current non-preemptive production programme of unfinished jobs from the past planning periods. A mathematical formulation and a two-phase heuristic (including initial job-to-line allocation and schedule improving steps) are given for the problem. Experimental tests with jobs from practice were convincing.
Journal: International Journal of Production Research
Pages: 1052-1073
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1609708
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1609708
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:1052-1073




Template-Type: ReDIF-Article 1.0
Author-Name: Norman Roth
Author-X-Name-First: Norman
Author-X-Name-Last: Roth
Author-Name: Jochen Deuse
Author-X-Name-First: Jochen
Author-X-Name-Last: Deuse
Author-Name: Hubert Biedermann
Author-X-Name-First: Hubert
Author-X-Name-Last: Biedermann
Title: A framework for System Excellence assessment of production systems, based on lean thinking, business excellence, and factory physics
Abstract: 
 This article proposes a production system framework that synthesises lean production, business excellence, and factory physics. The framework, which draws on a deep state-of-the-art understanding, consists of a performance measurement system supporting the achievement of a target condition based on variability and lead time reduction, as well as approaches of continuous improvement. Based on four types of excellence, a System Excellence value is calculated, indicating the distance from a target condition and thus displaying relevant improvement potential. As a key result, the framework proposed provides a contribution to knowledge, as it combines the aforementioned schools of thought, resulting in a holistic framework for action. The measurement system offers a high level of robustness, as it draws on diverse data sources and reflects on the dynamic behaviour over time. It has been successfully implemented in automotive manufacturing plants worldwide, which may suggest considerable practical relevance. Another key result of this research is that through applying the framework, important bottom-line indicators, such as lead time, failure costs, or productivity, could be improved. As the plants are typical automotive industry high-volume plants, it is proposed that the solutions presented offer a suitable standard for this industry and type of plant.
Journal: International Journal of Production Research
Pages: 1074-1091
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1612113
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1612113
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Template-Type: ReDIF-Article 1.0
Author-Name: Patricia van Loon
Author-X-Name-First: Patricia
Author-X-Name-Last: van Loon
Author-Name: Charles Delagarde
Author-X-Name-First: Charles
Author-X-Name-Last: Delagarde
Author-Name: Luk N. Van Wassenhove
Author-X-Name-First: Luk N.
Author-X-Name-Last: Van Wassenhove
Author-Name: Aleš Mihelič
Author-X-Name-First: Aleš
Author-X-Name-Last: Mihelič
Title: Leasing or buying white goods: comparing manufacturer profitability versus cost to consumer
Abstract: 
 Remanufacturing can create opportunities for companies to become more sustainable while remaining profitable. However, not all companies will be able to profit from moving towards a closed-loop business model. This paper investigates the profitability of leasing and remanufacturing washing machines for a large white goods producer based on data provided by them. A simple analytical model is built to simultaneously estimate the costs for consumers and costs and profits for the manufacturer under the leasing system. The results are compared with the costs and profitability of the linear system where premium, economy, and budget washing machines are sold to consumers. A sensitivity analysis is conducted on important factors such as repair, administration and transport costs. Using the replacement chain method, we show that the consumer costs of budget washing machines in the sales system is significantly higher than the costs for premium washing machines. Consequently, those consumers would benefit most from a circular system in which premium washing machines are leased against acceptable fees. However, the additional costs for the manufacturer make it a challenge to generate the same level of profit as in the linear system. The research discusses important cost components companies will have to address when making a move towards a circular business model with leasing and remanufacturing.
Journal: International Journal of Production Research
Pages: 1092-1106
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1612962
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1612962
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:1092-1106




Template-Type: ReDIF-Article 1.0
Author-Name: Jing Wang
Author-X-Name-First: Jing
Author-X-Name-Last: Wang
Author-Name: Yingchen Yan
Author-X-Name-First: Yingchen
Author-X-Name-Last: Yan
Author-Name: Huibin Du
Author-X-Name-First: Huibin
Author-X-Name-Last: Du
Author-Name: Ruiqing Zhao
Author-X-Name-First: Ruiqing
Author-X-Name-Last: Zhao
Title: The optimal sales format for green products considering downstream investment
Abstract: 
 With the increasing public awareness of environmental protection and the popularisation of suppliers' green production, a growing number of e-tailers are also investing in green products or services. The greenization of an e-tailer brings additional sales to the online channel but weakens the bargaining power of the supplier and further complicates the supplier's online channel format choice. This study focuses on the interaction between the e-tailer's green investment strategy and the supplier's choice of online channel format. First, we find that the e-tailer's investment forces the supplier to consider a new factor, the supplier's investment efficiency, which the supplier does not consider when the e-tailer does not invest and completely changes the e-tailer's own preferences. Second, we obtain the counterintuitive result that the supplier does not always benefit from the e-tailer's greenization; in the reseller channel, a supplier with a high investment efficiency is made worse off due to the increased retail price resulting from the e-tailer's investment. Additionally, the e-tailer will go green only when the upstream investment efficiency is high, regardless of the online channel format. The intuition behind this result hinges on each player wanting to free ride but worrying that the other has the same idea.
Journal: International Journal of Production Research
Pages: 1107-1126
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1612963
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1612963
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:1107-1126




Template-Type: ReDIF-Article 1.0
Author-Name: Jing Wen
Author-X-Name-First: Jing
Author-X-Name-Last: Wen
Author-Name: Na Geng
Author-X-Name-First: Na
Author-X-Name-Last: Geng
Author-Name: Xiaolan Xie
Author-X-Name-First: Xiaolan
Author-X-Name-Last: Xie
Title: Real-time scheduling of semi-urgent patients under waiting time targets
Abstract: 
 Semi-urgent patients arrive at an emergency department and visit the physician after triage. Patients right after triage should be served within a maximum allowable waiting time; whereas in-process patients need to be served as soon as possible to avoid adverse events. The physician must determine which one to be served next. To deal with this problem, a Markov decision process (MDP) is proposed for real-time scheduling. The wait of patients right after triage incurs a non-decreasing marginal waiting cost in their lateness, whereas the wait of in-process patients incurs linear cost function. The objective is to minimise the total weighted waiting cost. The properties of the MDP model are analysed. In the special case of long examination time and common treatment rate for all patients, we prove the multimodularity of the value function and the optimality of state-dependent threshold policies. Based on these properties, efficient heuristic policies and an approximate dynamic programming (ADP) policy are proposed. A threshold policy, which is defined by the function of expected tardiness of patients right after triage, is found to excel in all experiments, with average gaps less than 0.7% from the optimal control in small-size instances and 0.18% from ADP in real application.
Journal: International Journal of Production Research
Pages: 1127-1143
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1612965
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1612965
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Template-Type: ReDIF-Article 1.0
Author-Name: Oussama Ben-Ammar
Author-X-Name-First: Oussama
Author-X-Name-Last: Ben-Ammar
Author-Name: Belgacem Bettayeb
Author-X-Name-First: Belgacem
Author-X-Name-Last: Bettayeb
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Integrated production planning and quality control for linear production systems under uncertainties of cycle time and finished product quality
Abstract: 
 This work considers serial production systems with several process steps and a possible quality control at final step. It deals with the problem of optimising planned lead time when the real lead time for each process is stochastic and the finished product quality is uncertain unless it is inspected. Three analytical models are proposed aiming to minimise the expected total cost, which is composed of the inventory and backlogging costs for the finished product and quality costs associated with inspection and non-conformities. These models correspond to three quality control policies: (i) without quality control, (ii) with quality control but without taking into account the inspection duration when optimising the planned lead time and (iii) with quality control and with considering the inspection duration when optimising the planned lead time. Based on the results, it can be highlighted the economic advantage of integrating quality control at the early stage of supply and production planning decisions for some cost parameters conditions. The robustness of the proposed models is also analysed regarding the variance of the probability distributions of the lead times.
Journal: International Journal of Production Research
Pages: 1144-1160
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1613580
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1613580
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaomei He
Author-X-Name-First: Xiaomei
Author-X-Name-Last: He
Author-Name: Shaohua Dong
Author-X-Name-First: Shaohua
Author-X-Name-Last: Dong
Author-Name: Ning Zhao
Author-X-Name-First: Ning
Author-X-Name-Last: Zhao
Title: Research on rush order insertion rescheduling problem under hybrid flow shop based on NSGA-III
Abstract: 
 Rush order insertion is widespread in the enterprises that apply make-to-order production mode which affects the stability of production system. This article studies rush order insertion rescheduling problem (ROIRP) under hybrid flow shop (HFS) with multiple stages and multiple machines. A mathematical model simultaneously considering constraints such as lots, sequence-dependent set-up times and transportation times with objectives to minimise makespan, total transportation time and total machine deviation between the initial scheduling plan and the event-driven rescheduling plan is developed and NSGA-III is applied to solve the problem. Three groups of experiments are carried out which verify the suitability of NSGA-III for HFS scheduling problem with multi-objective and multi-constraint, the effectiveness of NSGA-III for the proposed ROIRP and the feasibility and effectiveness of the proposed model and algorithm in solving the ROIRP of a realistic ship pipe parts manufacturing enterprise.
Journal: International Journal of Production Research
Pages: 1161-1177
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1613581
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1613581
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:1161-1177




Template-Type: ReDIF-Article 1.0
Author-Name: Xiong Li
Author-X-Name-First: Xiong
Author-X-Name-Last: Li
Author-Name: Xiaodong Zhao
Author-X-Name-First: Xiaodong
Author-X-Name-Last: Zhao
Author-Name: Wei Pu
Author-X-Name-First: Wei
Author-X-Name-Last: Pu
Title: Battle damage-oriented spare parts forecasting method based on wartime influencing factors analysis and ε-support vector regression
Abstract: 
 Many peacetime spare parts demand forecasting models have been proposed recently. However, it is difficult to forecast spare parts consumption in wartime. This is due to the complexity and randomness of battle damages. To serve this purpose, we choose a combined army element as study object, and propose a novel method to forecast battle damage-oriented spare parts demand based on wartime influencing factors analysis and ε-Support Vector Regression (ε-SVR). First, we extract the key influencing factors of equipment damages including battlefield environment and fighting capacities of the opposed forces by qualitative analysis, and quantify those factors by combining Delphi technique and fuzzy comprehensive evaluation method. Subsequently, we construct the sample space by using influencing factors of battle damages as the input variables and the corresponding spare parts demand as the output variable, introduce the insensitive loss function (ε) and establish the ε-SVR prediction model of ‘wartime influencing factors – battle damage-oriented spare parts demand’. Finally, we implement a case study of forecasting three representative kinds of spare parts for assault of a combined army element, and thus verify feasibility and effectiveness of the model. We find that the proposed method can provide decision-making references for wartime spare parts supply with higher accuracy and more advantages in contrast with other current methods.
Journal: International Journal of Production Research
Pages: 1178-1198
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1614691
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1614691
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Template-Type: ReDIF-Article 1.0
Author-Name: Illhoe Hwang
Author-X-Name-First: Illhoe
Author-X-Name-Last: Hwang
Author-Name: Young Jae Jang
Author-X-Name-First: Young Jae
Author-X-Name-Last: Jang
Title: Q(λ) learning-based dynamic route guidance algorithm for overhead hoist transport systems in semiconductor fabs
Abstract: 
 A learning-based dynamic routing algorithm is proposed for the overhead hoist transport (OHT) systems of semiconductor fabrication facilities (fabs). An OHT system, which consists of multiple vehicles moving at high speeds on guided rails, is the primary automated material-handling system (AMHS) in a fab. Modern large-scale fabs have hundreds of vehicles moving lots between multiple processing machines. The dynamic routing method is a route guidance method that dynamically selects the best vehicle paths under given traffic conditions and congestion levels. Building on the  $Q(\lambda ) $Q(λ) learning method, we develop a reinforcement learning-based dynamic routing algorithm called QLBWR(λ), which consists of a Boltzmann softmax policy and a reward function. The proposed algorithm uses real-time information to effectively guide each vehicle so that it avoids congestion and finds an efficient path. The algorithm is also designed with a low computational burden, such that the efficient route can be found for hundreds of vehicles in real time. Simulation analyses on an actual fab layout are used to compare the performance of the proposed algorithm with common static and dynamic algorithms. The results show that the proposed algorithm outperforms the benchmarking algorithms.
Journal: International Journal of Production Research
Pages: 1199-1221
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1614692
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1614692
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:1199-1221




Template-Type: ReDIF-Article 1.0
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Michael Hassoun
Author-X-Name-First: Michael
Author-X-Name-Last: Hassoun
Author-Name: Alejandro Sendon
Author-X-Name-First: Alejandro
Author-X-Name-Last: Sendon
Title: A Lagrangian heuristic for minimising risk using multiple heterogeneous metrology tools
Abstract: 
 Motivated by the high investment and operational metrology cost, and subsequently the limited metrology capacity, in modern semiconductor manufacturing facilities, we model and solve the problem of optimally assigning the capacity of several imperfect metrology tools to minimise the risk in terms of expected product loss on heterogeneous production machines. In this paper, metrology tools can differ in terms of reliability and speed. The resulting problem can be reduced to a variant of the Generalized Assignment Problem (GAP), the Multiple Choice, Multiple Knapsack Problem (MCMKP). A Lagrangian heuristic, including multiple feasibility heuristics, is proposed to solve the problem that are tested on randomly generated instances.
Journal: International Journal of Production Research
Pages: 1222-1238
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1614693
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1614693
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:1222-1238




Template-Type: ReDIF-Article 1.0
Author-Name: Guanqun Ni
Author-X-Name-First: Guanqun
Author-X-Name-Last: Ni
Title: Replenishment policy for a purchase-to-order seller: a tradeoff between ordering cost and delay cost
Abstract: 
 We consider replenishment decisions on when and how many goods to purchase for a seller under a purchase-to-order mode where there is no inventory and the seller purchases goods to fulfil orders already placed. For each purchase, there is a constant ordering cost. For each order, delay cost will be incurred if it is not fulfilled timely. Generally, the more frequent the replenishment, the higher the ordering cost but the lower the delay cost. Consequently, there is a tradeoff between the ordering cost and the delay cost for the seller to make replenishment decisions minimising the total cost. In this paper, we study three cases of the problem and investigate both offline versions and online versions according to the seller's knowledge about information of future orders. For offline versions with perfect information, we either develop an optimal policy, or prove it is NP-hard and develop an approximation policy. For online versions without any information about future orders, from the perspective of competitive analysis we prove the lower bound of competitive ratio for any possible online policy and present a 10-competitive online policy for the general case and a 2-competitive online policy for each of two special cases.
Journal: International Journal of Production Research
Pages: 1239-1254
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1616846
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1616846
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Template-Type: ReDIF-Article 1.0
Author-Name: Serena Finco
Author-X-Name-First: Serena
Author-X-Name-Last: Finco
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Xavier Delorme
Author-X-Name-First: Xavier
Author-X-Name-Last: Delorme
Author-Name: Alessandro Persona
Author-X-Name-First: Alessandro
Author-X-Name-Last: Persona
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Title: Workers’ rest allowance and smoothing of the workload in assembly lines
Abstract: 
 Ergonomic aspects have a crucial role in manual assembly systems. They impact on the workers’ health, final product quality and productivity. For these reasons, there is the necessity to integrate them into the assembly line balancing phase as, whereas, only time and cost variables are considered. In this study, human energy expenditures are considered as ergonomic aspects and we integrate them, for the first time, into the assembly line balancing problem type 2 through the rest allowance evaluation. We consider as an objective function the minimization of the smoothness index. Firstly, a new optimal method based on mixed integer linear programming and a new linearization methodology are proposed. Then, a heuristic approach is introduced. To complete the study, a computational experimentation is presented to validate the mathematical model and to compare the methodologies proposed in terms of computational time, complexity and solution. Additionally, we provide a detailed analysis of the impact that rest allowance evaluation can have on productivity comparing the results obtained, taking into account the rest allowance integration before, during and after the assembly balancing process.
Journal: International Journal of Production Research
Pages: 1255-1270
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1616847
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1616847
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:1255-1270




Template-Type: ReDIF-Article 1.0
Author-Name: Fang Huang
Author-X-Name-First: Fang
Author-X-Name-Last: Huang
Author-Name: Juhong Chen
Author-X-Name-First: Juhong
Author-X-Name-Last: Chen
Author-Name: Linhui Sun
Author-X-Name-First: Linhui
Author-X-Name-Last: Sun
Author-Name: Yaqi Zhang
Author-X-Name-First: Yaqi
Author-X-Name-Last: Zhang
Author-Name: Shujun Yao
Author-X-Name-First: Shujun
Author-X-Name-Last: Yao
Title: Value-based contract for smart operation and maintenance service based on equitable entropy
Abstract: 
 Smart operation and maintenance (O&M) service is the major industrial service in Industry 4.0, but it's not easy for manufacturers to achieve high returns. Regularly manufacturers can't set a higher service price due to customer's perception of the service value; a new revenue model is urgently needed. In this study, we develop a value-based contract for smart O&M service based on equitable entropy. Firstly, we summarise the characteristics of smart O&M service's value creation and acquisition. And the service value is measured under the PaaS model by calculating the maximum revenue gap of the customer in the two cases of customer self-O&M and manufacturer's smart O&M service. Then a revenue-sharing model is built based on equitable entropy which the criterion is the valid data provided by each party. The results show that by signing a value-based contract, the smart O&M service can not only significantly improve the customer's revenue by downtime losses reduction and productivity improvement, but also create higher returns for the manufacturer. In addition, the fairest revenue sharing coefficient and relatively fair interval for revenue sharing decision can be accurately calculated by equitable entropy. These conclusions provide a theoretical basis for the manufacturer to better implement smart O&M service.
Journal: International Journal of Production Research
Pages: 1271-1284
Issue: 4
Volume: 58
Year: 2020
Month: 2
X-DOI: 10.1080/00207543.2019.1617450
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1617450
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:4:p:1271-1284




Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Maxim Rozhkov
Author-X-Name-First: Maxim
Author-X-Name-Last: Rozhkov
Title: Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain
Abstract: 
 The ripple effect refers to structural dynamics and describes a downstream propagation of the downscaling in demand fulfilment in the supply chain (SC) as a result of a severe disruption. The bullwhip effect refers to operational dynamics and amplifies in the upstream direction as ordering oscillations. Being interested in uncovering if the ripple effect can be a driver of the bullwhip effect, we performed a simulation-based study to investigate the interrelations of the structural and operational dynamics in the SC. The results advance our knowledge about both ripple and bullwhip effects and reveal, for the first time, that the ripple effect can be a bullwhip-effect driver, while the latter can be launched by a severe disruption even in the downstream direction. The findings show that the ripple effect influences the bullwhip effect through backlog accumulation over the disruption time as a consequence of non-coordinated ordering and production planning policies. To cope with this effect, a contingent production-inventory control policy is proposed that provides results in favour of information coordination in SC disruption management to mitigate both ripple and bullwhip effects. The SC managers need to take into account the risk of bullwhip effect during the capacity disruption and recovery periods.
Journal: International Journal of Production Research
Pages: 1285-1301
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1627438
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1627438
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:5:p:1285-1301




Template-Type: ReDIF-Article 1.0
Author-Name: Nguyen Quoc Viet
Author-X-Name-First: Nguyen Quoc
Author-X-Name-Last: Viet
Author-Name: Behzad Behdani
Author-X-Name-First: Behzad
Author-X-Name-Last: Behdani
Author-Name: Jacqueline Bloemhof
Author-X-Name-First: Jacqueline
Author-X-Name-Last: Bloemhof
Title: Data-driven process redesign: anticipatory shipping in agro-food supply chains
Abstract: 
 Anticipatory shipping uses historical order and customer data to predict future orders and accordingly ship products to the nearest distribution centres before customers actually place the orders. It is a method to meet the increasing customer requirements on delivery service and simultaneously to reduce operational costs. This paper presents a case of anticipatory shipping in the context of agro-food supply chains. The challenge in these chains is the product perishability that leads to product obsolescence in the case of un-balanced supply and demand. This study introduces a data-driven approach that integrates product quality characteristics in data analytics to identify suitable products for anticipatory shipping at the strategic level. It also proposes process redesigns concerning production and transportation at the operational level to realise anticipatory shipping. Finally, using historical data from a Dutch floriculture supplier as input for a multi-agent simulation, the proposed approach and process redesigns are verified. The simulation output shows that anticipatory shipping could increase delivery service level up to 35.3% and reduce associated costs up to 9.3%.
Journal: International Journal of Production Research
Pages: 1302-1318
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1629673
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629673
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Template-Type: ReDIF-Article 1.0
Author-Name: Sachin Kamble
Author-X-Name-First: Sachin
Author-X-Name-Last: Kamble
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Neelkanth C. Dhone
Author-X-Name-First: Neelkanth C.
Author-X-Name-Last: Dhone
Title: Industry 4.0 and lean manufacturing practices for sustainable organisational performance in Indian manufacturing companies
Abstract: 
 The current literature claims the direct effects of industry 4.0 technologies (I4 T) on lean manufacturing practices (LMP) and sustainable organisational performance (SOP). LMP are also found to have a positive influence on SOP. However, the integrated effect of I4 T and LMP on SOP has not been empirically investigated. To address this gap, this research study investigates the indirect effects of I4 T on SOP with LMP as the mediating variable; furthermore, it aims to confirm or not the direct effects of I4 T on LMP and SOP. The study is based on data collected from 205 managers, working in 115 manufacturing firms. The findings suggest significant direct and indirect effects of I4 T on SOP and confirm the presence of LMP as a strong mediating variable. The results of the study extend the literature on I4 T by identifying I4 T as an enabler of LMP, leading to enhancement of the SOP. Implications and future research directions for academicians, practitioners, and consultants are provided.
Journal: International Journal of Production Research
Pages: 1319-1337
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1630772
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630772
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:5:p:1319-1337




Template-Type: ReDIF-Article 1.0
Author-Name: Vahid Nooraie
Author-X-Name-First: Vahid
Author-X-Name-Last: Nooraie
Author-Name: Mahdi Fathi
Author-X-Name-First: Mahdi
Author-X-Name-Last: Fathi
Author-Name: Masoud Narenji
Author-X-Name-First: Masoud
Author-X-Name-Last: Narenji
Author-Name: Mahour M. Parast
Author-X-Name-First: Mahour M.
Author-X-Name-Last: Parast
Author-Name: Panagote M. Pardalos
Author-X-Name-First: Panagote M.
Author-X-Name-Last: Pardalos
Author-Name: P. M. Stanfield
Author-X-Name-First: P. M.
Author-X-Name-Last: Stanfield
Title: A multi-objective model for risk mitigating in supply chain design
Abstract: 
 The goal of this study is to recognise various factors for responsive SCs that affect supply risk and model their impact on SC design and operation. We propose a conceptual model for SC responsiveness that encompasses practices such as flexibility, agility, internal integration, and visibility. This conceptual model is utilised to build up a multi-objective, multi-period SC design and operation model. A heuristic algorithm is developed to find the supplier, product, period, and production rate for the numerical problem. The improved genetic algorithm (GA) produces solutions with more accuracy in considerably less time than a traditional GA. Finally, an approach to prioritise the objective functions is developed that allows managers to focus on specific objective functions more than optimum values. This approach provides risk-averse, responsiveness-oriented, cost-effective managers the capability to set priorities based on their policies.
Journal: International Journal of Production Research
Pages: 1338-1361
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1633024
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1633024
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:5:p:1338-1361




Template-Type: ReDIF-Article 1.0
Author-Name: Jiho Yoon
Author-X-Name-First: Jiho
Author-X-Name-Last: Yoon
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Author-Name: Claudia Rosales
Author-X-Name-First: Claudia
Author-X-Name-Last: Rosales
Title: Procurement decisions and information sharing under multi-tier disruption risk in a supply chain
Abstract: 
 We consider a manufacturer's procurement decision in a three-tier supply chain (SC) under disruption risk. The manufacturer sources components from a single first-tier supplier (FT). The FT, in turn, sources raw materials from a single second-tier supplier (ST). Suppliers in both tiers are unreliable, i.e. prone to disruption risk. Increasing SC visibility through information sharing is a potential disruption management strategy for the manufacturer. While the manufacturer can obtain disruption risk information for the FT, disruption risk information for the ST is not easily accessible to the manufacturer except through the FT, who may not be willing to share ST information. We study different mechanisms under which the manufacturer can obtain ST information, and its impact on manufacturer's and FT's decisions and potential profits. We show that information sharing makes the manufacturer's procurement decisions more conservative, i.e. carrying more inventories, but the FT's procurement decision is contingent on the ST's reliability; more proactive (conservative) when ST is unreliable (reliable), i.e. carrying less (more) inventories. We demonstrate that there are two ways to induce the FT to share its information, and numerically show that their effectiveness is contingent on multiple factors, including FT and ST reliabilities and information sharing costs.
Journal: International Journal of Production Research
Pages: 1362-1383
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1634296
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634296
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:5:p:1362-1383




Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Moeuf
Author-X-Name-First: Alexandre
Author-X-Name-Last: Moeuf
Author-Name: Samir Lamouri
Author-X-Name-First: Samir
Author-X-Name-Last: Lamouri
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Author-Name: Simon Tamayo-Giraldo
Author-X-Name-First: Simon
Author-X-Name-Last: Tamayo-Giraldo
Author-Name: Estefania Tobon-Valencia
Author-X-Name-First: Estefania
Author-X-Name-Last: Tobon-Valencia
Author-Name: Romain Eburdy
Author-X-Name-First: Romain
Author-X-Name-Last: Eburdy
Title: Identification of critical success factors, risks and opportunities of Industry 4.0 in SMEs
Abstract: 
 SMEs, as prominent actors in industry, must meet more and more complex customer expectations. Recently, the concept of Industry 4.0 has emerged. This new approach enables the control of production processes by providing real-time synchronisation of flows and by enabling the production of unitary and customised products. Our research goal is to identify Industry 4.0 risks, opportunities and critical success factors with regards to the industrial performance of SMEs. The recent emergence of Industry 4.0 and the inherent difficulty of identifying detailed examples has not yet enabled a satisfactory statistical study to be conducted on Industry 4.0 cases in SMEs. To reach our research goal, we selected 12 experts to conduct a Delphi study supplemented by Régnier’s abacuses. Our study demonstrates that the major risks facing the adoption of Industry 4.0 in SMEs include a lack of expertise and a short-term strategy mindset. Our research also indicates that training is the most important factor for success, that managers have a prominent role in the success and/or failure of an Industry 4.0 project, and that SMEs should be supported by external experts. Lastly, Industry 4.0 offers a unique opportunity to redesign SME production processes and to adopt new business models.
Journal: International Journal of Production Research
Pages: 1384-1400
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1636323
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1636323
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:5:p:1384-1400




Template-Type: ReDIF-Article 1.0
Author-Name: Barış Tan
Author-X-Name-First: Barış
Author-X-Name-Last: Tan
Title: Design of balanced energy savings performance contracts
Abstract: 
 Energy savings performance contracts between the energy users and the energy service companies (ESCO) are used to finance energy efficiency investments by using the future energy savings that will result from these investments. We present an analytical model to characterise the energy savings performance contracts and discuss how the risks of estimating the energy savings affect the energy user and the service provider. This characterisation allows determination of the contract parameters for a balanced contract with the information about the energy savings that are expected from the planned energy-efficiency investments. Since it is difficult to get the statistical information about the energy savings before investing in an energy-efficiency project, we develop a distribution-free contract that sets the guaranteed energy savings level based on the mean and the standard deviation of the energy savings and the profit-sharing ratio between the ESCO and the energy user. We show that a simple distribution-free balanced contract performs satisfactorily when the distribution of the energy savings is not known and its mean and the standard deviation are estimated with error. Our analytical results show that the energy savings contracts with the right parameters can mitigate the risks related to realisation of the anticipated energy savings.
Journal: International Journal of Production Research
Pages: 1401-1424
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1641240
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641240
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:5:p:1401-1424




Template-Type: ReDIF-Article 1.0
Author-Name: Gerd J. Hahn
Author-X-Name-First: Gerd J.
Author-X-Name-Last: Hahn
Title: Industry 4.0: a supply chain innovation perspective
Abstract: 
 The Fourth Industrial Revolution – also known as Industry 4.0 (i4.0) – comprises the digitalisation of the industrial sector. This paper uses the theoretical lens of supply chain innovation (SCI) to investigate the implications of i4.0 on supply chain management. For these purposes, the method of structured content analysis is applied to more than 200 use cases of i4.0-enabled SCI introduced by both established and startup companies. i4.0-enabled SCI manifests along three dimensions: process, technology, and business architecture. The key findings of this study can be summarised as follows: first, i4.0-enabled SCI extends the initial focus on productivity improvements in SC processes towards scalability and flexibility. Second, extant i4.0 solutions rely mostly on analytics and smart things while omitting smart people technology and the human-centric approach associated with the i4.0 paradigm. Third, established companies adopt i4.0 merely to sustain their existing business architectures while startup companies radically change their operating models, relying heavily on data analytics and the platform economy. Consequently, established companies pursue a problem-driven, engineering-based approach to SCI while startup companies follow an ‘asset-light’, business-driven approach. Lastly, there are two distinct approaches to digitalising operational SC processes: platform-based crowdsourcing of standard processes and on-demand provision of customised services.
Journal: International Journal of Production Research
Pages: 1425-1441
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1641642
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641642
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Manikas
Author-X-Name-First: Andrew
Author-X-Name-Last: Manikas
Author-Name: Lynn Boyd
Author-X-Name-First: Lynn
Author-X-Name-Last: Boyd
Author-Name: Jian (Jeff) Guan
Author-X-Name-First: Jian (Jeff)
Author-X-Name-Last: Guan
Author-Name: Kyle Hoskins
Author-X-Name-First: Kyle
Author-X-Name-Last: Hoskins
Title: A review of operations management literature: a data-driven approach
Abstract: 
 Production and operations management has been a significant field of research for many years. However, other than an educated guess by researchers in the field or a perusal of textbook chapter titles, the major topics and their trends over time are not well established. This study provides a comprehensive review of production and operations management literature using a data-driven approach. We use Latent Semantic Analysis on 21,053 abstracts representing all publications in six leading operations management journals since their inception. 18 unique topic clusters were identified algorithmically. Just being aware of the history of research topics should be of great interest to all academics in the field, but to help future researchers we conducted three post hoc analyses: 1) analysis of methods used in all these studies, 2) citation rates by topic area over time, and 3) the growing prevalence of research covering multiple topics.
Journal: International Journal of Production Research
Pages: 1442-1461
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1651459
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1651459
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Template-Type: ReDIF-Article 1.0
Author-Name: Carla Gonçalves Machado
Author-X-Name-First: Carla Gonçalves
Author-X-Name-Last: Machado
Author-Name: Mats Peter Winroth
Author-X-Name-First: Mats Peter
Author-X-Name-Last: Winroth
Author-Name: Elias Hans Dener Ribeiro da Silva
Author-X-Name-First: Elias Hans Dener
Author-X-Name-Last: Ribeiro da Silva
Title: Sustainable manufacturing in Industry 4.0: an emerging research agenda
Abstract: 
 This systematic review intends to identify how sustainable manufacturing research is contributing to the development of the Industry 4.0 agenda and for a broader understanding about the links between the Industry 4.0 and Sustainable Manufacturing by mapping and summarising existing research efforts, identifying research agendas, as well as gaps and opportunities for research development. A conceptual framework formed by the principles and technological pillars of Industry 4.0, sustainable manufacturing scope, opportunities previously identified, and sustainability dimensions, guided analysis of 35 papers from 2008–2018, selected by a systematic approach. Bibliometrics data and social network analysis complement results identifying how research is being organised and its respective research agendas, relevant publications, and status of the research lifecycle. Results point to that the current research is aligned with the goals defined by different national industrial programs. There are, however, research gaps and opportunities for field development, becoming more mature and having a significant contribution to fully developing the agenda of Industry 4.0.
Journal: International Journal of Production Research
Pages: 1462-1484
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1652777
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1652777
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaolong Guo
Author-X-Name-First: Xiaolong
Author-X-Name-Last: Guo
Author-Name: Lihong Cheng
Author-X-Name-First: Lihong
Author-X-Name-Last: Cheng
Author-Name: Jie Liu
Author-X-Name-First: Jie
Author-X-Name-Last: Liu
Title: Green supply chain contracts with eco-labels issued by the sales platform: profitability and environmental implications
Abstract: 
 Considering environmentally conscious consumers, a manufacturer, and a sales platform which provides eco-labels for qualified manufacturers, this paper develops a supply chain model to study how eco-labels affect green supply chain operations, from the profitability and environmental perspectives. The results show that the sales platform prefers the agency contract, but the manufacturer prefers the wholesale price contract. Considering the performance of the supply chain, the agency contract brings a higher profit while the wholesale price contract results in a bigger environmental improvement. An unexpected but interesting result is that when the agency contract is used and consumer green awareness increases, the sale price declines rather than increasing as it does under the wholesale price contract. This decline happens because the required marketing effort of the sales platform will be lower, which incentivises the platform to reduce the commission rate. Consequently, the manufacturer faces a lower commission rate and a higher margin when consumers display greater green awareness. Moreover, as the core and more powerful player of the supply chain, the sales platform can propose a platform-led revenue sharing contract to fully coordinate the supply chain, which improves the performance of the supply chain both in profitability and environmental perspectives.
Journal: International Journal of Production Research
Pages: 1485-1504
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1658911
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1658911
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Template-Type: ReDIF-Article 1.0
Author-Name: Sunil Luthra
Author-X-Name-First: Sunil
Author-X-Name-Last: Luthra
Author-Name: Anil Kumar
Author-X-Name-First: Anil
Author-X-Name-Last: Kumar
Author-Name: Edmundas Kazimieras Zavadskas
Author-X-Name-First: Edmundas Kazimieras
Author-X-Name-Last: Zavadskas
Author-Name: Sachin Kumar Mangla
Author-X-Name-First: Sachin Kumar
Author-X-Name-Last: Mangla
Author-Name: Jose Arturo Garza-Reyes
Author-X-Name-First: Jose Arturo
Author-X-Name-Last: Garza-Reyes
Title: Industry 4.0 as an enabler of sustainability diffusion in supply chain: an analysis of influential strength of drivers in an emerging economy
Abstract: 
 Industry 4.0 (I4.0) and sustainability are recent buzzwords in manufacturing environments. However, the connection between these two concepts is less explored in the literature. In the current business context, the future generation of manufacturing systems is greatly influenced by the rapid advancement of information technology. Therefore, this study aims to examine the drivers of I4.0 to diffuse sustainability in Supply Chains (SCs). This research identifies the most relevant drivers through the literature and discusses them with area experts. Afterwards, an empirical analysis is conducted to validate the key drivers. Finally, the Grey based DEMATEL method is employed to examine the influential strength of the identified drivers and to build an interrelationship diagram. ‘Government supportive policies’ and ‘Collaboration and transparency among supply chain members’ were reported as highly significant drivers of I4.0. This study is an initial effort that investigates the key drivers of I4.0 to achieve high triple bottom line (ecological-economic-social) gains in SCs by taking an example from an emerging economy, i.e. India. This study may help managers, practitioners and policy makers interested in I4.0 applications to diffuse sustainability in SCs.
Journal: International Journal of Production Research
Pages: 1505-1521
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1660828
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660828
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Template-Type: ReDIF-Article 1.0
Author-Name: Ifeyinwa Juliet Orji
Author-X-Name-First: Ifeyinwa Juliet
Author-X-Name-Last: Orji
Author-Name: Simonov Kusi-Sarpong
Author-X-Name-First: Simonov
Author-X-Name-Last: Kusi-Sarpong
Author-Name: Himanshu Gupta
Author-X-Name-First: Himanshu
Author-X-Name-Last: Gupta
Title: The critical success factors of using social media for supply chain social sustainability in the freight logistics industry
Abstract: 
 This paper pioneers the investigation of the significant factors that influence corporate decisions on the use of social media for supply chain social sustainability, and it highlights a crucial research area that is currently understudied in supply chain management literature. A theoretical framework was developed in this study based upon the Technology–Organization–Environment (TOE) and Human–Organization–Technology (HOT) theories to obtain the significant critical success factors (CSFs) which influence the use of social media for supply chain social sustainability in freight logistics firms in Nigeria. The Best-Worst Method was applied to analyse and rank the CSFs using their determined relative importance level. The research findings indicate that customer satisfaction, sufficient security and privacy, affordability and competitive pressure are the highest ranked CSFs to achieve supply chain social sustainability using of social media. This research has important implications for policy makers and practitioners to gain perspectives on how to foster the use of social media in the freight logistics sector for supply chain social sustainability.
Journal: International Journal of Production Research
Pages: 1522-1539
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1660829
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660829
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Template-Type: ReDIF-Article 1.0
Author-Name: Maximilian Kunovjanek
Author-X-Name-First: Maximilian
Author-X-Name-Last: Kunovjanek
Author-Name: Gerald Reiner
Author-X-Name-First: Gerald
Author-X-Name-Last: Reiner
Title: How will the diffusion of additive manufacturing impact the raw material supply chain process?
Abstract: 
 This study investigates the potential of additive manufacturing (i.e. 3D printing) to alter established manufacturing and supply chain processes, complementing previous research work that deals with additive manufacturing and rapid prototyping. Additive manufacturing is a manufacturing technique, which allows the direct fabrication of three-dimensional design models using an additive approach by adding layer after layer. As additive manufacturing is inherently less wasteful and only applies raw material where needed, it constitutes a chance to reduce materials usage and related inventories. Even though the technology has faced considerable hype, its adoption still does not match the high expectations. The aim of this study is to overcome limitations of state-of-the-art impact assessments by integrating the potential reduction of materials inventories through the adoption of additive manufacturing in manufacturing and to point out possible implications for supply chain processes. For this purpose, a dynamic evaluation model was developed analysing the adoption of additive manufacturing by integrating the Bass Diffusion Model to provide interesting and novel results for both practitioners and researchers. The study shows that additive manufacturing can indeed reduce raw materials inventory by approximately 4% and that the diffusion rate is likely to be affected by the utility of the technology.
Journal: International Journal of Production Research
Pages: 1540-1554
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1661537
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1661537
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Template-Type: ReDIF-Article 1.0
Author-Name: Sameer Mittal
Author-X-Name-First: Sameer
Author-X-Name-Last: Mittal
Author-Name: Muztoba Ahmad Khan
Author-X-Name-First: Muztoba Ahmad
Author-X-Name-Last: Khan
Author-Name: Jayant Kishor Purohit
Author-X-Name-First: Jayant Kishor
Author-X-Name-Last: Purohit
Author-Name: Karan Menon
Author-X-Name-First: Karan
Author-X-Name-Last: Menon
Author-Name: David Romero
Author-X-Name-First: David
Author-X-Name-Last: Romero
Author-Name: Thorsten Wuest
Author-X-Name-First: Thorsten
Author-X-Name-Last: Wuest
Title: A smart manufacturing adoption framework for SMEs
Abstract: 
 Smart Manufacturing (SM) a revolutionary paradigm that aims to improve production systems’ performance in terms of quality, time, cost, and flexibility, as well as human and machine decision-making capabilities. Most large enterprises have already taken first steps towards adopting SM. Small and Medium-sized Enterprises (SMEs) on the other hand, are struggling with developing a SM adoption roadmap. Our research builds on the real and perceived needs and challenges faced by manufacturing SMEs and advances the field by developing and evaluating an SME-specific ‘SM adoption framework’. We have employed a multiple case study approach to acknowledge the lessons learned by selected early-adopter SMEs that have recently implemented and deployed SM tools and practices. We propose an SM adoption framework with five vital steps that SMEs interested in SM should follow: (i) identify manufacturing data available within the SME, (ii) readiness assessment of the SME data-hierarchy steps, (iii) developing SM awareness of SME leadership and staff, (iv) develop a SM tailored vision for the SMEs, and (v) identify appropriate SM tools and practices necessary to realise the tailored SM vision. Moreover, the results of the case study analysis enabled us to formulate many generalisations.
Journal: International Journal of Production Research
Pages: 1555-1573
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1661540
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1661540
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Template-Type: ReDIF-Article 1.0
Author-Name: Shradha A. Gawankar
Author-X-Name-First: Shradha A.
Author-X-Name-Last: Gawankar
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Sachin Kamble
Author-X-Name-First: Sachin
Author-X-Name-Last: Kamble
Title: A study on investments in the big data-driven supply chain, performance measures and organisational performance in Indian retail 4.0 context
Abstract: 
 The use of digital technologies such as ‘internet of things’ and ‘big data analytics’ have transformed the traditional retail supply chains into data-driven retail supply chains referred to as ‘Retail 4.0.’ These big data-driven retail supply chains have the advantage of providing superior products and services and enhance the customers shopping experience. The retailing industry in India is highly competitive and eager to transform into the environment of retail 4.0. The literature on big data in the supply chain has mainly focused on the applications in manufacturing industries and therefore needs to be further investigated on how the big data-driven retail supply chains influence the supply chain performance. Therefore, this study investigates how the retailing 4.0 context in India is influencing the existing supply chain performance measures and what effect it has on the organisational performance. The findings of the study provide valuable insights for retail supply chain practitioners on planning BDA investments. Based on a survey of 380 respondents selected from retail organisations in India, this study uses governance structure as the moderating variable. Implications for managers and future research possibilities are presented.
Journal: International Journal of Production Research
Pages: 1574-1593
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1668070
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1668070
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Kusiak
Author-X-Name-First: Andrew
Author-X-Name-Last: Kusiak
Title: Convolutional and generative adversarial neural networks in manufacturing
Abstract: 
 Manufacturing is undergoing transformation driven by the developments in process technology, information technology, and data science. A future manufacturing enterprise will be highly digital. This will create opportunities for machine learning algorithms to generate predictive models across the enterprise in the spirit of the digital twin concept. Convolutional and generative adversarial neural networks have received some attention of the manufacturing research community. Representative research and applications of the two machine learning concepts in manufacturing are presented. Advantages and limitations of each neural network are discussed. The paper might be helpful in identifying research gaps, inspire machine learning research in new manufacturing domains, contribute to the development of successful neural network architectures, and getting deeper insights into the manufacturing data.
Journal: International Journal of Production Research
Pages: 1594-1604
Issue: 5
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1662133
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1662133
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Template-Type: ReDIF-Article 1.0
Author-Name: Liane Mahlmann Kipper
Author-X-Name-First: Liane Mahlmann
Author-X-Name-Last: Kipper
Author-Name: Leonardo Bertolin Furstenau
Author-X-Name-First: Leonardo Bertolin
Author-X-Name-Last: Furstenau
Author-Name: Daniel Hoppe
Author-X-Name-First: Daniel
Author-X-Name-Last: Hoppe
Author-Name: Rejane Frozza
Author-X-Name-First: Rejane
Author-X-Name-Last: Frozza
Author-Name: Sandra Iepsen
Author-X-Name-First: Sandra
Author-X-Name-Last: Iepsen
Title: Scopus scientific mapping production in industry 4.0 (2011–2018): a bibliometric analysis
Abstract: 
 Research in industry 4.0 is growing, driven by the innovations in production systems on a continuous basis. In this study, we identified the evolution of themes inherent in the industry 4.0 using a bibliometric software, namely SciMAT (Science Mapping Analysis Software Tool). The analyses included 1882 documents, 4231 keywords, and the relevant information was extracted based on frequency of co-occurrence of keywords. The clusters were plotted in two-dimensional strategic diagrams and analysed using the bibliometric indicators such as the number of publications, number of associated documents, and h-index. The results revealed that 2017 had the largest number of publications. Expert authors in the field and the periodicals that published the most were identified. The science mapping presented 31 clusters in which the most representative motor themes were CPS (Cyber-Physical System), IoT (Internet of Things), and Big Data. In addition, it was possible to identify fields with high investment of efforts by the scientific community such as the union between lean production and industry 4.0, production-centered CPS (CPPS), IoT (Industrial Internet of Things - IIoT), among others. The overlapping map showed an increase in the number of keywords from 338 to 1231 over the period of data. The map of scientific developments supported by an exhaustive research, it was possible to show the state of the art, the main challenges and perspectives for future research in the field of industry 4.0 such as Technology, Collaboration/Integration, Management and Implementation.
Journal: International Journal of Production Research
Pages: 1605-1627
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1671625
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1671625
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Template-Type: ReDIF-Article 1.0
Author-Name: Jae-Gon Kim
Author-X-Name-First: Jae-Gon
Author-X-Name-Last: Kim
Author-Name: Seokwoo Song
Author-X-Name-First: Seokwoo
Author-X-Name-Last: Song
Author-Name: BongJoo Jeong
Author-X-Name-First: BongJoo
Author-X-Name-Last: Jeong
Title: Minimising total tardiness for the identical parallel machine scheduling problem with splitting jobs and sequence-dependent setup times
Abstract: 
 This paper focuses on an identical parallel machine scheduling problem with minimising total tardiness of jobs. There are two major issues involved in this scheduling problem; (1) jobs which can be split into multiple sub-jobs for being processed on parallel machines independently and (2) sequence-dependent setup times between the jobs with different part types. We present a novel mathematical model with meta-heuristic approaches to solve the problem. We propose two encoding schemes for meta-heuristic solutions and three decoding methods for obtaining a schedule from the meta-heuristic solutions. Six different simulated annealing algorithms and genetic algorithms, respectively, are developed with six combinations of two encoding schemes and three decoding methods. Computational experiments are performed to find the best combination from those encoding schemes and decoding methods. Our findings show that the suggested algorithm provides not only better solution quality, but also less computation time required than the commercial optimisation solvers.
Journal: International Journal of Production Research
Pages: 1628-1643
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1672900
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1672900
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Template-Type: ReDIF-Article 1.0
Author-Name: Frédéric Rosin
Author-X-Name-First: Frédéric
Author-X-Name-Last: Rosin
Author-Name: Pascal Forget
Author-X-Name-First: Pascal
Author-X-Name-Last: Forget
Author-Name: Samir Lamouri
Author-X-Name-First: Samir
Author-X-Name-Last: Lamouri
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Title: Impacts of Industry 4.0 technologies on Lean principles
Abstract: 
 Industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies. On the other hand, many companies have already partially or fully implemented principles and tools from the Lean management approach, which is also aimed at improving productivity. While the two approaches use very different strategies, they share some common principles. The objective of this article is to highlight the links between the principles and tools proposed by Industry 4.0 and those proposed by the Lean management approach, with a particular focus on how some of Industry 4.0's technologies are improving the implementation of Lean principles, depending on the technologies’ capability levels. As such, this study aims to provide a characterisation of the impacts of Industry 4.0 technologies on Lean principles according to targeted capability levels. The results obtained show strong support for Industry 4.0 technologies for Just-in-time and Jidoka, but little or no support for waste reduction and People and Team work. There is, therefore, a clear need to pursue the deployment of Lean management while improving certain Lean principles using Industry 4.0 technologies.
Journal: International Journal of Production Research
Pages: 1644-1661
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1672902
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1672902
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:6:p:1644-1661




Template-Type: ReDIF-Article 1.0
Author-Name: Paolo Rosa
Author-X-Name-First: Paolo
Author-X-Name-Last: Rosa
Author-Name: Claudio Sassanelli
Author-X-Name-First: Claudio
Author-X-Name-Last: Sassanelli
Author-Name: Andrea Urbinati
Author-X-Name-First: Andrea
Author-X-Name-Last: Urbinati
Author-Name: Davide Chiaroni
Author-X-Name-First: Davide
Author-X-Name-Last: Chiaroni
Author-Name: Sergio Terzi
Author-X-Name-First: Sergio
Author-X-Name-Last: Terzi
Title: Assessing relations between Circular Economy and Industry 4.0: a systematic literature review
Abstract: 
 Industry 4.0 (I4.0) and Circular Economy (CE) are undoubtedly two of the most debated topics of the last decades. Progressively, they gained the interest of policymakers, practitioners and scholars all over the world. Even if they have been usually described as two independent research fields, there are some examples presenting overlaps between these topics, represented by hybrid categories like Circular I4.0 and Digital CE. Starting from these two perspectives, an innovative framework both highlighting the links between I4.0 and CE and unveiling future research fields has been developed. Basing on one of the two perspectives, results show as it is possible to enhance a set of different relations. Depending on a dedicated area of either CE or I4.0 it is possible to see the prevalence of some I4.0 technology than others. However, the influence of I4.0 technologies on CE is always verified.
Journal: International Journal of Production Research
Pages: 1662-1687
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1680896
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1680896
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Template-Type: ReDIF-Article 1.0
Author-Name: Juan Tang
Author-X-Name-First: Juan
Author-X-Name-Last: Tang
Author-Name: Bang-Yi Li
Author-X-Name-First: Bang-Yi
Author-X-Name-Last: Li
Author-Name: Kevin W. Li
Author-X-Name-First: Kevin W.
Author-X-Name-Last: Li
Author-Name: Zhi Liu
Author-X-Name-First: Zhi
Author-X-Name-Last: Liu
Author-Name: Jun Huang
Author-X-Name-First: Jun
Author-X-Name-Last: Huang
Title: Pricing and warranty decisions in a two-period closed-loop supply chain
Abstract: 
 For a two-period closed-loop supply chain (CLSC) consisting of a manufacturer and a retailer, Stackelberg game analyses are conducted to examine pricing and warranty decisions under two warranty models depending on who offers warranty for new and remanufactured products and the corresponding benchmark models with a warranty for new products only. Next, we identify the conditions under which warranty for remanufactured products is offered and investigate how this warranty affects the CLSC operations. Subsequently, comparative studies are carried out to examine equilibrium decisions, profitability and consumer surplus of the CLSC between the two warranty models. Analytical results show that offering warranty for remanufactured products does not affect new product pricing in period 2, but influences the pricing of new products in period 1 and remanufactured products in period 2, thereby enhancing remanufacturing, individual and channel profitability, and consumer surplus. Compared to the retailer warranty for remanufactured products, the manufacturer warranty can attain a more equitable profit distribution. If the warranty cost advantage of the manufacturer (retailer) is significant relative to that of the retailer (the manufacturer), the manufacturer (retailer) arises as a natural choice to offer warranty for remanufactured products as this decision enhances both profitability and consumer surplus.
Journal: International Journal of Production Research
Pages: 1688-1704
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1683246
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683246
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Template-Type: ReDIF-Article 1.0
Author-Name: Hongtao Ren
Author-X-Name-First: Hongtao
Author-X-Name-Last: Ren
Author-Name: Wenji Zhou
Author-X-Name-First: Wenji
Author-X-Name-Last: Zhou
Author-Name: Ying Guo
Author-X-Name-First: Ying
Author-X-Name-Last: Guo
Author-Name: Lizhen Huang
Author-X-Name-First: Lizhen
Author-X-Name-Last: Huang
Author-Name: Yongping Liu
Author-X-Name-First: Yongping
Author-X-Name-Last: Liu
Author-Name: Yadong Yu
Author-X-Name-First: Yadong
Author-X-Name-Last: Yu
Author-Name: Liyun Hong
Author-X-Name-First: Liyun
Author-X-Name-Last: Hong
Author-Name: Tieju Ma
Author-X-Name-First: Tieju
Author-X-Name-Last: Ma
Title: A GIS-based green supply chain model for assessing the effects of carbon price uncertainty on plastic recycling
Abstract: 
 Recycling plastic can abate the environmental pollution as well as CO2 emissions by saving the carbon-intensive feedstock input. The uncertain carbon price places significant effects on the establishment and operation of the whole supply chain. This study develops a green supply chain model combined with geographic information system (GIS) to account for carbon price uncertainty and evaluate its effects on the closed-loop supply chain (CLSC) of plastic recycling. A two-stage stochastic programming model is constructed, in which the stochastic variable, CO2 price is modelled as a geometric Brownian motion process. Six scenarios are designed with respect to price expectation and volatility. A case study is performed with the GIS information of the plastic supply chain in Zhejiang province, China. The results illustrate that triggering the establishment of reverse logistics requires a carbon price threshold significantly beyond the current level. Lower price volatility would facilitate the decision-making of investment into the reverse logistics. Mechanisms to alleviate the market variation shall be introduced. A sound market condition is desired to obtain the optimal balance that encourages the CLSC without creating extra pressure on the firms. The proposed modelling framework can be easily applied to other sectors with similar characteristics.
Journal: International Journal of Production Research
Pages: 1705-1723
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1693656
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693656
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Template-Type: ReDIF-Article 1.0
Author-Name: Sen Yan
Author-X-Name-First: Sen
Author-X-Name-Last: Yan
Author-Name: Xiaoyu Ji
Author-X-Name-First: Xiaoyu
Author-X-Name-Last: Ji
Title: Supply chain network design under the risk of uncertain disruptions
Abstract: 
 Facility disruptions in the supply chain often lead to catastrophic consequences, although they occur rarely. The low frequency and non-repeatability of disruptive events also make it impossible to estimate the disruption probability accurately. Therefore, we construct an uncertain programming model to design the three-echelon supply chain network with the disruption risk, in which disruptions are considered as uncertain events. Under the constraint of satisfying customer demands, the model optimises the selection of retailers with uncertain disruptions and the assignment of customers and retailers, in order to minimise the expected total cost of network design. In addition, we simplify the proposed model by analysing its properties and further linearise the simplified model. A Lagrangian relaxation algorithm for the linearised model and a genetic algorithm for the simplified model are developed to solve medium-scale problems and large-scale problems, respectively. Finally, we illustrate the effectiveness of proposed models and algorithms through several numerical examples.
Journal: International Journal of Production Research
Pages: 1724-1740
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1696999
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1696999
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Template-Type: ReDIF-Article 1.0
Author-Name: Farivar Ranjbaran
Author-X-Name-First: Farivar
Author-X-Name-Last: Ranjbaran
Author-Name: Ali Husseinzadeh Kashan
Author-X-Name-First: Ali
Author-X-Name-Last: Husseinzadeh Kashan
Author-Name: Abolfazl Kazemi
Author-X-Name-First: Abolfazl
Author-X-Name-Last: Kazemi
Title: Mathematical formulation and heuristic algorithms for optimisation of auto-part milk-run logistics network considering forward and reverse flow of pallets
Abstract: 
 The operational planning of distribution network for automotive industry is complex with many conditions to consider, including heterogeneous fleet, enforcing the feasibility of 3D-packing of pallets into vehicles to address the vehicle's capacity in terms of weight and volume, compatibility of orders in a vehicle, returning empty pallets from assembly-plants backwards to suppliers, and delivery time windows. A mathematical model (MILP) is proposed that takes account of these conditions to minimise total transportation costs. The network structure can be a combination of direct shipment and milk-run for both forward and reverse flow of pallets. The model is solved optimally for small-size problems. For solving larger problems, a heuristic algorithm (in two versions) is proposed that uses a similarity measure to generate a reasonable list of orders. Best/first-fit strategies are employed to generate a feasible solution with the aid of a relaxed version of the proposed MILP. Improvement heuristics are also designed. Unlike most of existing constructive heuristics, our aim for developing the heuristic approach is to force routing decision, with all of its considerations, being made optimal. We also use the proposed best-fit strategy in the body of grouping evolution strategy (GES) algorithm to attain an effective meta-heuristic approach. The effectiveness of heuristics is tested on generated instances which demonstrates they are optimal for small-size problems. They are also tested on the data of daily auto-parts shipments gathered from the largest Iranian automobile company. Results demonstrate there exists a significant potential for cost saving through milk-run strategy compared with the direct shipping strategy.
Journal: International Journal of Production Research
Pages: 1741-1775
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1617449
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1617449
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Template-Type: ReDIF-Article 1.0
Author-Name: Gregory D. DeYong
Author-X-Name-First: Gregory D.
Author-X-Name-Last: DeYong
Title: The price-setting newsvendor: review and extensions
Abstract: 
 The newsvendor problem is a staple of operations management research, pedagogy and practice. From its humble roots as a single-period problem for a price-taking newspaper seller, this problem (and its solutions) has inspired generations of researchers and students while contributing to inventory management at countless firms. One major extension of the newsvendor problem was the extension of the decision variables to include price as well as quantity. This extension has been known for decades, but recently gained new life, as researchers have expended considerable energy in analysing and exploring this scenario. We trace major developments in the single-period, price- and quantity-setting newsvendor problem in the recent past and propose extensions of these developments. We also extend a relatively unexplored model describing a price-setting newsvendor faced with a fixed stock level to show that there is a unique optimising price and that, as in the price- and quantity-setting newsvendor problem, the optimal price depends heavily on the form of the demand uncertainty.
Journal: International Journal of Production Research
Pages: 1776-1804
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1671624
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1671624
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:6:p:1776-1804




Template-Type: ReDIF-Article 1.0
Author-Name: Mohammadali Vosooghidizaji
Author-X-Name-First: Mohammadali
Author-X-Name-Last: Vosooghidizaji
Author-Name: Atour Taghipour
Author-X-Name-First: Atour
Author-X-Name-Last: Taghipour
Author-Name: Béatrice Canel-Depitre
Author-X-Name-First: Béatrice
Author-X-Name-Last: Canel-Depitre
Title: Supply chain coordination under information asymmetry: a review
Abstract: 
 Aligning supply chain decisions of separate entities with independent objectives can be considered to be one of the difficulties of supply chain management. This difficulty becomes worse if the supply chains are characterised by an asymmetrical distribution of information. Although considerable research has recently been devoted to supply chain coordination, less attention has been paid to different information asymmetry settings to the mechanisms underlying it. This research attempts to help fill this gap by reviewing and classifying the literature based on supply chain features, applied methodology, coordination mechanisms, and types of information asymmetry. The proposed classification is used to highlight the ongoing issues in the area and identify the direction for future research.
Journal: International Journal of Production Research
Pages: 1805-1834
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1685702
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685702
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Template-Type: ReDIF-Article 1.0
Author-Name: Tobias Bier
Author-X-Name-First: Tobias
Author-X-Name-Last: Bier
Author-Name: Anne Lange
Author-X-Name-First: Anne
Author-X-Name-Last: Lange
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Title: Methods for mitigating disruptions in complex supply chain structures: a systematic literature review
Abstract: 
 Supply chain risk management is extremely important for the success of a company. Due to the increasing complexity of supply chains, avoiding and mitigating the effects of disruptions is very challenging. This article presents the results of a systematic literature review and content analysis in order to provide a comprehensive overview of the methods that are currently used for mitigating supply chain disruptions. The results of the review indicate that research in this field is interdisciplinary and that no common modelling language has emerged thus far. Prior research mostly redraws to graph theory and/or social network analysis, although a few methods have been developed recently specifically for supply chain risk management. We observe that prior contributions addressed risk and structure mostly separately and that only a few works focused on their intersection. The results of this review are consolidated in a research agenda that calls for research on the risk-structure-interface and the development of proxy methods.
Journal: International Journal of Production Research
Pages: 1835-1856
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1687954
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1687954
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Template-Type: ReDIF-Article 1.0
Author-Name: Christopher M. Durugbo
Author-X-Name-First: Christopher M.
Author-X-Name-Last: Durugbo
Title: After-sales services and aftermarket support: a systematic review, theory and future research directions
Abstract: 
 After-sales and aftermarkets are significant revenue streams for industrial companies. After-sales services are activities during warranty periods that include field technical assistance, spare parts distribution, customer care, and accessories sale. Aftermarket support involves secondary market transactions for additional products (e.g. accessories and add-ons) and product recovery processes. An awareness of the potentials of both concepts is evident by the extensive body of production and operations management (POM) publications that investigate the perspectives of both academia and practitioners. Yet, there is an absence of a systematic review to analyse research studies on after-sales and aftermarkets in a POM context. This article reviews the POM literature on after-sales services and aftermarket support. The review identifies and critically appraises 249 peer-reviewed articles published between 1970 and 2018. It examines the research clusters, investigated industry sectors, research methodologies, theories and contributions of studies. Using insights from the review process, the article also proposes theoretical foundations, sets a research agenda, and identifies optimisation problems for future after-sales and aftermarket studies.
Journal: International Journal of Production Research
Pages: 1857-1892
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1693655
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693655
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Template-Type: ReDIF-Article 1.0
Author-Name: Shupeng Huang
Author-X-Name-First: Shupeng
Author-X-Name-Last: Huang
Author-Name: Andrew Potter
Author-X-Name-First: Andrew
Author-X-Name-Last: Potter
Author-Name: Daniel Eyers
Author-X-Name-First: Daniel
Author-X-Name-Last: Eyers
Title: Social media in operations and supply chain management: State-of-the-Art and research directions
Abstract: 
 Recently, industrial and academic communities in the operations and supply chain management (OSCM) field are paying increasing attention to social media. However, the value of social media in OSCM is quite unclear, and more investigations are still needed. To pave the way for directed future research, this paper systematically reviewed and synthesised 152 peer-review journal papers to identify research focus and gaps in this area, supported by an appropriate conceptual framework. The result reveals that the research interests in this area have increased dramatically within the last decade across various industries and regions. Different companies’ OSCM activities, such as sourcing and delivery, can benefit from employment of social media. This paper also indicates that future research can explore the value of social media in sourcing, delivery, product return and reverse logistics, forecasting and inventory management, and product development and production.
Journal: International Journal of Production Research
Pages: 1893-1925
Issue: 6
Volume: 58
Year: 2020
Month: 3
X-DOI: 10.1080/00207543.2019.1702228
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1702228
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Template-Type: ReDIF-Article 1.0
Author-Name: Dimitris Mourtzis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Mourtzis
Title: Simulation in the design and operation of manufacturing systems: state of the art and new trends
Abstract: 
 As the industrial requirements change at a rapid pace due to the drastic evolution of technology, the necessity of quickly investigating potential system alternatives towards a more efficient manufacturing system design arises more intensely than ever. Manufacturing systems simulation has proven to be a powerful tool for designing and evaluating a manufacturing system due to its low cost, quick analysis, low risk and meaningful insight that it may provide, improving thus the understanding of the influence of each component. Simulation comprises an indispensable set of IT tools and methods for the successful implementation of digital manufacturing. It allows experimentation and validation of product, process, and system design and configuration. This paper investigates the major historical milestones in the evolution of manufacturing systems simulation technologies and examines recent industrial and research approaches in key fields of manufacturing. It describes how the urge towards digitalisation of manufacturing in the context of the 4th Industrial revolution has shaped simulation in the design and operation of manufacturing systems and reviews the new approaches that have arisen in the literature. Particular focus is given to technologies in the digitalised factories of the future that are gaining ground in industrial applications simulation, offering multiple advantages.
Journal: International Journal of Production Research
Pages: 1927-1949
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1636321
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1636321
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Template-Type: ReDIF-Article 1.0
Author-Name: Jin Tao
Author-X-Name-First: Jin
Author-X-Name-Last: Tao
Author-Name: Lusheng Shao
Author-X-Name-First: Lusheng
Author-X-Name-Last: Shao
Author-Name: Zhimin Guan
Author-X-Name-First: Zhimin
Author-X-Name-Last: Guan
Author-Name: William Ho
Author-X-Name-First: William
Author-X-Name-Last: Ho
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Title: Incorporating risk aversion and fairness considerations into procurement and distribution decisions in a supply chain
Abstract: 
 This paper considers a three-tier supply chain in which a manufacturer uses raw materials sourced from multiple suppliers to produce an item and sells it through multiple distributors. We develop an integrated optimisation model to study supply chain procurement and distribution decisions incorporating the manufacturer’s aversion to risk and the distributors’ concern for fairness in a climate of uncertain supply and demand. Resilient strategies, such as alternative sourcing and transshipment, are also considered when optimising the supply chain cost and service level. To solve the problem, a Monte Carlo simulation-based multi-objective stochastic programming model is built. It uses the CVaR (Conditional Value-at-Risk) and unfairness aversion utility function to reflect the decision maker’s risk aversion and the customer’s concern for fairness, respectively. A Normalised Normal Constraint based algorithm is adopted to obtain the Pareto Frontier. In addition, the numerical analysis provides some valuable insights for supply chain managers.
Journal: International Journal of Production Research
Pages: 1950-1967
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1637955
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1637955
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:7:p:1950-1967




Template-Type: ReDIF-Article 1.0
Author-Name: Mehdi Firoozi
Author-X-Name-First: Mehdi
Author-X-Name-Last: Firoozi
Author-Name: M. Zied Babai
Author-X-Name-First: M. Zied
Author-X-Name-Last: Babai
Author-Name: Walid Klibi
Author-X-Name-First: Walid
Author-X-Name-Last: Klibi
Author-Name: Yves Ducq
Author-X-Name-First: Yves
Author-X-Name-Last: Ducq
Title: Distribution planning for multi-echelon networks considering multiple sourcing and lateral transshipments
Abstract: 
 Nowadays, due to the increasing complexity of business environment, especially demand uncertainty, supply chain managers need to establish more-effective sourcing and distribution strategies to ensure high customer service and low stock costs. To overcome this challenge multi-echelon network structures and alternative distribution strategies such as lateral transshipments and multiple sourcing should be considered in inventory optimisation models. In this article, we propose a scenario-based modelling approach to solve a two-stage multi-echelon inventory optimisation problem with a non-stationary demand. The model is based on a distribution requirements planning (DRP) approach and minimises the expected total cost that is composed of the fixed allocation, inventory holding, procurement, transportation, and back-ordering costs. Alternative inventory optimisation models, including the lateral transshipment strategy and multiple sourcing, are thus built, and the corresponding stochastic programmes are solved using the sample average approximation method. Through a numerical investigation conducted with several generated instances and an empirical investigation based on the case of a major French retailer’s distribution network, we show the substantial benefit of lateral transshipments and multiple sourcing in reducing the expected total costs of the distribution network.
Journal: International Journal of Production Research
Pages: 1968-1986
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1639841
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1639841
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Template-Type: ReDIF-Article 1.0
Author-Name: Ehsan Aghamohammadzadeh
Author-X-Name-First: Ehsan
Author-X-Name-Last: Aghamohammadzadeh
Author-Name: Mahsa Malek
Author-X-Name-First: Mahsa
Author-X-Name-Last: Malek
Author-Name: Omid Fatahi Valilai
Author-X-Name-First: Omid Fatahi
Author-X-Name-Last: Valilai
Title: A novel model for optimisation of logistics and manufacturing operation service composition in Cloud manufacturing system focusing on cloud-entropy
Abstract: 
 In recent years, economic globalisation and manufacturing resource globalisation as two key factors have driven enterprises to transform their business processes to survive in competitive environments. This transformation is challenging as manufacturing enterprises should maintain their support for their customers with high-quality products, lower cost, product customisation capabilities, and quick delivery. Moreover, globalisation has resulted in geographically distributed suppliers across the globe. This challenge will turn into a major research topic when paradigms like Cloud manufacturing are introduced. Cloud manufacturing is a new paradigm which provides ubiquitous, convenient, on-demand network access to a shared pool of configurable manufacturing resources. In this paper, to achieve the ideal goal of Cloud manufacturing, the concept of supplier network logistics planning and manufacturing service composition is focused. Every production task and logistics operation would be defined as a service considering operation process chart flows. The paper has proposed a mathematical model which selects an optimal set of manufacturing and logistics service composition in order to lower operation and logistics costs in operational perspective while fulfilling a novel idea for configured cloud entropy of logistics and operation suppliers. Finally, the paper has presented a numerical example and concluded the remarks, and outlined future research.
Journal: International Journal of Production Research
Pages: 1987-2015
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1640406
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1640406
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Template-Type: ReDIF-Article 1.0
Author-Name: Yue Xie
Author-X-Name-First: Yue
Author-X-Name-Last: Xie
Author-Name: Wanhua He
Author-X-Name-First: Wanhua
Author-X-Name-Last: He
Author-Name: Wai-Ki Ching
Author-X-Name-First: Wai-Ki
Author-X-Name-Last: Ching
Author-Name: Allen H. Tai
Author-X-Name-First: Allen H.
Author-X-Name-Last: Tai
Author-Name: Wai-Hung Ip
Author-X-Name-First: Wai-Hung
Author-X-Name-Last: Ip
Author-Name: Kai-Leung Yung
Author-X-Name-First: Kai-Leung
Author-X-Name-Last: Yung
Author-Name: Na Song
Author-X-Name-First: Na
Author-X-Name-Last: Song
Title: Optimal advertising outsourcing strategy with different effort levels and uncertain demand
Abstract: 
 This paper studies the issue of advertising outsourcing and production planning for a manufacturer facing asymmetric advertising cost and uncertain market demand. To improve product sales, a manufacturer would hire an advertising agency to provide professional service on product advertising before the production takes place. A contract taking into account both advertising effort level and payment is introduced to incentivize the advertising agency to report the exact cost to the manufacturer. Furthermore, a model with the goal of maximising the manufacturer's net profit is proposed, in which both product demand and payment to the advertising agency are affected by the advertising effort level. Analytical solutions of the optimal strategies including the optimal advertising effort level and the optimal payment to the advertising agency are derived. Optimal retail price and the optimal production quantity are also obtained for the manufacturer in making managerial decisions.
Journal: International Journal of Production Research
Pages: 2016-2035
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1641235
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641235
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Template-Type: ReDIF-Article 1.0
Author-Name: María Isabel Roldán Bravo
Author-X-Name-First: María Isabel
Author-X-Name-Last: Roldán Bravo
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Author-Name: Antonia Ruiz Moreno
Author-X-Name-First: Antonia Ruiz
Author-X-Name-Last: Moreno
Author-Name: Francisco Javier Lloréns Montes
Author-X-Name-First: Francisco Javier
Author-X-Name-Last: Lloréns Montes
Title: Absorptive and desorptive capacity configurations in supply chains: An inverted U-shaped relationship
Abstract: 
 The extant literature has highlighted the importance of knowledge transfer between a buyer and its supply network for strengthening supply chain competence. This is a bi-directional exchange where the buyer and supply network each act as the sender and receiver of knowledge. Prior research has however largely focused on the knowledge recipient only. We consider both sender and recipient using two key dynamic capabilities related to knowledge transfer: (i) desorptive capacity, which enables the safe transfer of knowledge from the sender; and, (ii) absorptive capacity, which enables the acquisition and assimilation of external knowledge by the recipient. Using the concept of ‘fit’, we investigate whether organisations strengthen supply chain competence when their desorptive capacity exceeds that of their supply network's (positive misfit) and consider the moderating role of the organisation’s and supply network’s absorptive capacity. Multiple regression analysis of survey data from 250 firms identifies an inverted U-shaped relationship between positive desorptive capacity misfit and supply chain competence. Further, this relationship is shown to be moderated by the supply network’s absorptive capacity level. The paper furthers our understanding of supply chain knowledge management enabling buyers and their supply networks to achieve more successful knowledge transfer outcomes.
Journal: International Journal of Production Research
Pages: 2036-2053
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1642530
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1642530
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:7:p:2036-2053




Template-Type: ReDIF-Article 1.0
Author-Name: Lenny Koh
Author-X-Name-First: Lenny
Author-X-Name-Last: Koh
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: Blockchain in transport and logistics – paradigms and transitions
Journal: International Journal of Production Research
Pages: 2054-2062
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2020.1736428
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1736428
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:7:p:2054-2062




Template-Type: ReDIF-Article 1.0
Author-Name: Mehrdokht Pournader
Author-X-Name-First: Mehrdokht
Author-X-Name-Last: Pournader
Author-Name: Yangyan Shi
Author-X-Name-First: Yangyan
Author-X-Name-Last: Shi
Author-Name: Stefan Seuring
Author-X-Name-First: Stefan
Author-X-Name-Last: Seuring
Author-Name: S.C. Lenny Koh
Author-X-Name-First: S.C. Lenny
Author-X-Name-Last: Koh
Title: Blockchain applications in supply chains, transport and logistics: a systematic review of the literature
Abstract: 
 This paper presents current academic and industrial frontiers on blockchain application in supply chain, logistics and transport management. We conduct a systematic review of the literature and find four main clusters in the co-citation analysis, namely Technology, Trust, Trade, and Traceability/Transparency. For each cluster, and based on the pool of articles included in it, we apply an inductive method of reasoning and discuss the emerging themes and applications of blockchains for supply chains, logistics and transport. We conclude by discussing the main themes for future research on blockchain technology and its application in industry and services.
Journal: International Journal of Production Research
Pages: 2063-2081
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1650976
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1650976
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:7:p:2063-2081




Template-Type: ReDIF-Article 1.0
Author-Name: Yanling Chang
Author-X-Name-First: Yanling
Author-X-Name-Last: Chang
Author-Name: Eleftherios Iakovou
Author-X-Name-First: Eleftherios
Author-X-Name-Last: Iakovou
Author-Name: Weidong Shi
Author-X-Name-First: Weidong
Author-X-Name-Last: Shi
Title: Blockchain in global supply chains and cross border trade: a critical synthesis of the state-of-the-art, challenges and opportunities
Abstract: 
 Blockchain possesses the potential of transforming global supply chain management. Gartner predicts that blockchain could be able to track $2 T of goods and services in their movement across the globe by 2023, and blockchain will be a more than $3 trillion business by 2030. Nowadays, a growing number of blockchain initiatives are disrupting traditional business models in each sector. In this paper, we provide a timely and holistic overview of the state-of-the-art, challenges, gaps and opportunities in global supply chain and trade operations for both the private sector and governmental agencies, by synthesising a wide range of resources from business leaders, global international organisations, leading supply chain consulting firms, research articles, trade magazines and conferences. We then identify collaborative schema and future research directions for industry, government, and academia to jointly work together in ensuring that the full potential of blockchain is unleashed amidst the socioeconomic, geopolitical and technological disruptions that global supply chains and trade are facing.
Journal: International Journal of Production Research
Pages: 2082-2099
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1651946
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1651946
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Template-Type: ReDIF-Article 1.0
Author-Name: Lai-Wan Wong
Author-X-Name-First: Lai-Wan
Author-X-Name-Last: Wong
Author-Name: Garry Wei-Han Tan
Author-X-Name-First: Garry Wei-Han
Author-X-Name-Last: Tan
Author-Name: Voon-Hsien Lee
Author-X-Name-First: Voon-Hsien
Author-X-Name-Last: Lee
Author-Name: Keng-Boon Ooi
Author-X-Name-First: Keng-Boon
Author-X-Name-Last: Ooi
Author-Name: Amrik Sohal
Author-X-Name-First: Amrik
Author-X-Name-Last: Sohal
Title: Unearthing the determinants of Blockchain adoption in supply chain management
Abstract: 
 The behavioural intention to adopt Blockchain for supply chain management (BCSCM) is studied in this paper. The research framework adopted considers how Performance Expectancy (PE), Effort Expectancy (EE), Facilitating Condition (FC), Technology Readiness (TR), Technology Affinity (TA) and Trust (TT) can lead to the adoption of the technology. Data gathered from 157 firms is analysed using SPSS version 2 while the quality of the measurement is tested using WarpPLS. Findings revealed that FC, TR and TA have a positive influence on intention to use BCSCM and regulatory support moderates the effect of FC. This study offers valuable insights into the applicability of Blockchain technology for supply chain management.
Journal: International Journal of Production Research
Pages: 2100-2123
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2020.1730463
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1730463
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Template-Type: ReDIF-Article 1.0
Author-Name: Dominik Roeck
Author-X-Name-First: Dominik
Author-X-Name-Last: Roeck
Author-Name: Henrik Sternberg
Author-X-Name-First: Henrik
Author-X-Name-Last: Sternberg
Author-Name: Erik Hofmann
Author-X-Name-First: Erik
Author-X-Name-Last: Hofmann
Title: Distributed ledger technology in supply chains: a transaction cost perspective
Abstract: 
 With the emergence of distributed ledger technology (DLT), numerous practitioners and researchers have proclaimed its beneficial impact on supply chain transactions in the future. However, the vast majority of DLT initiatives are discontinued after a short period. With the full potential of DLT laying far down the road, especially managers in supply chain management (SCM) seek for short-term cost-saving effects of DLT in order to achieve long-term benefits of DLT in the future. However, the extant research has bypassed grounding long-term as well as short-term effects of DLT on supply chain transaction with empirical data. We address this shortcoming, following an abductive research approach and combining empirical data from a multiple case study design with the corresponding literature. Our study reveals that the effects of DLT on supply chain transactions are two-sided. We found six effects of DLT solutions that have a cost-reducing or cost avoidance impact on supply chain transactions. In addition, we found two effects that change the power distribution between buyers and suppliers in transactions and a single effect that reduces the dependency of supply chain transactions on third parties. While cost-reducing and avoidance as well as dependency-reducing effects are positive effects, the change in power distribution might come with disadvantages. With these findings, the paper provides the first empirical evidence of the impact of DLT on supply chain transactions, which will enable managers to improve their assessment of DLT usage in supply chains.
Journal: International Journal of Production Research
Pages: 2124-2141
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1657247
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1657247
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Template-Type: ReDIF-Article 1.0
Author-Name: Chunguang Bai
Author-X-Name-First: Chunguang
Author-X-Name-Last: Bai
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: A supply chain transparency and sustainability technology appraisal model for blockchain technology
Abstract: 
 Blockchain technology is a technology that can effectively support supply chain transparency. An important initial managerial activity is for organisations in supply chains to evaluate and select the most suitable blockchain technology. However, uncertainty and emphasis on sustainable transparency has made this appraisal more complex. This paper: (1) introduces blockchain technology performance measures incorporating various sustainable supply chain transparency and technical attributes; and (2) introduces a new hybrid group decision method, integrated hesitant fuzzy set and regret theory, for blockchain technology evaluation and selection. This method emphasises decision maker psychological characteristics and variation in decision maker opinions. An illustrative application and sensitivity analysis is introduced to aid supply chain managers and researchers understand the blockchain technology selection decision. Methodological and managerial implications associated with the decision tool and application are introduced. This research sets the foundation for significant future research in blockchain technologies evaluation in a supply chain environment.
Journal: International Journal of Production Research
Pages: 2142-2162
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1708989
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1708989
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiho Yoon
Author-X-Name-First: Jiho
Author-X-Name-Last: Yoon
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Author-Name: Hakan Yildiz
Author-X-Name-First: Hakan
Author-X-Name-Last: Yildiz
Author-Name: Chwen Sheu
Author-X-Name-First: Chwen
Author-X-Name-Last: Sheu
Title: The value of Blockchain technology implementation in international trades under demand volatility risk
Abstract: 
 The extant literature has conceptually argued that Blockchain technology can provide both financial and operational benefits to firms in international trades. However, no studies have systematically and analytically investigated the effectiveness of Blockchain. This study introduces analytical models that consider the implementation of Blockchain technology in international trades, to test whether the technology improves an exporting firm's performance under demand volatility risk. The simulation and numerical analysis results show that the reduced lead time and decreased ocean transport cost under Blockchain enable the exporting firm to increase shipment via the ocean, which reduces the quantity shipped via air. In addition, the reduced total unit cost for ocean and air transports leads the firm to effectively reserve spaces for air transport, which implies that Blockchain makes the firm more proactive while preparing a backup plan to more effectively and efficiently react to demand realisation. We conclude that Blockchain can be beneficial for firms facing considerable demand volatility in international trades, and that such effectiveness could be more effective for firms that prioritise minimising lost sales (by efficiently utilising ocean and effectively exploiting air) over minimising excess quantity shipped by ocean.
Journal: International Journal of Production Research
Pages: 2163-2183
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1693651
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693651
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Semyon Potryasaev
Author-X-Name-First: Semyon
Author-X-Name-Last: Potryasaev
Author-Name: Boris Sokolov
Author-X-Name-First: Boris
Author-X-Name-Last: Sokolov
Author-Name: Marina Ivanova
Author-X-Name-First: Marina
Author-X-Name-Last: Ivanova
Author-Name: Frank Werner
Author-X-Name-First: Frank
Author-X-Name-Last: Werner
Title: Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain
Abstract: 
 Recently, the applications of Blockchain technology have begun to revolutionise different aspects of supply chain (SC) management. Among others, Blockchain is a platform to execute the smart contracts in the SC as transactions. We develop and test a new model for smart contract design in the SC with multiple logistics service providers and show that this problem can be presented as a multi-processor flexible flow shop scheduling. A distinctive feature of our approach is that the execution of physical operations is modelled inside the start and completion of cyber information services. We name this modelling concept ‘virtual operation’. The constructed model and the developed experimental environment constitute an event-driven dynamic approach to task and service composition when designing the smart contract. Our approach is also of value when considering the contract execution stage. The use of state control variables in our model allows for operations status updates in the Blockchain that in turn, feeds automated information feedbacks, disruption detection and control of contract execution. The latter launches the re-scheduling procedure, comprehensively combining planning and adaptation decisions within a unified methodological framework of dynamic control theory. The modelling complex developed can be used to design and control smart contracts in the SC.
Journal: International Journal of Production Research
Pages: 2184-2199
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1627439
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1627439
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Template-Type: ReDIF-Article 1.0
Author-Name: Ali Vatankhah Barenji
Author-X-Name-First: Ali
Author-X-Name-Last: Vatankhah Barenji
Author-Name: Zhi Li
Author-X-Name-First: Zhi
Author-X-Name-Last: Li
Author-Name: W. M. Wang
Author-X-Name-First: W. M.
Author-X-Name-Last: Wang
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Author-Name: David A. Guerra-Zubiaga
Author-X-Name-First: David A.
Author-X-Name-Last: Guerra-Zubiaga
Title: Blockchain-based ubiquitous manufacturing: a secure and reliable cyber-physical system
Abstract: 
 With product customisation and emerging business opportunities, small and medium manufacturing enterprises (SMEs) must find ways to collaborate and share competency in a trustable manner to survive a turbulent market. Therefore, service industry turns to the manufacturing industry and SMEs migrate to cloud manufacturing (CM) and ubiquitous manufacturing. However, existing platforms use centralised networking, which suffers from security, scalability and big-data problems. In this paper, we propose a blockchain-based platform as a trustable network to eradicate third-party problems, which can improve the scalability, security and big-data problems for SMEs. Our proposed platform is developed based on a consortium blockchain which provides a peer-to-peer communication network between the end user and the service provider. We improve existing consensus mechanism and communication protocol based on a cyber-physical system (CPS), via an autonomous agent. Firstly, we provide a review of cloud manufacturing, ubiquitous manufacturing and blockchain-based manufacturing approaches by highlighting the main problems. Then, the proposed platform, blockchain ubiquitous manufacturing (BCUM), is explained, based on its architecture, consensus algorithm and CPS, with the help of autonomous agent communication. The proposed platform has been developed for 3D printing companies which are geographically distributed and tested based on network performance and three practical scenarios.
Journal: International Journal of Production Research
Pages: 2200-2221
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1680899
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1680899
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Template-Type: ReDIF-Article 1.0
Author-Name: V. K. Manupati
Author-X-Name-First: V. K.
Author-X-Name-Last: Manupati
Author-Name: Tobias Schoenherr
Author-X-Name-First: Tobias
Author-X-Name-Last: Schoenherr
Author-Name: M. Ramkumar
Author-X-Name-First: M.
Author-X-Name-Last: Ramkumar
Author-Name: Stephan M. Wagner
Author-X-Name-First: Stephan M.
Author-X-Name-Last: Wagner
Author-Name: Sai Krishna Pabba
Author-X-Name-First: Sai Krishna
Author-X-Name-Last: Pabba
Author-Name: R. Inder Raj Singh
Author-X-Name-First: R.
Author-X-Name-Last: Inder Raj Singh
Title: A blockchain-based approach for a multi-echelon sustainable supply chain
Abstract: 
 Blockchain technology is destined to revolutionise supply chain processes. At the same time, governmental and regulatory policies are forcing firms to adjust their supply chains in response to environmental concerns. The objective of this study is therefore to develop a distributed ledger-based blockchain approach for monitoring supply chain performance and optimising both emission levels and operational costs in a synchronised fashion, producing a better outcome for the supply chain. We propose the blockchain approach for different production allocation problems within a multi-echelon supply chain (MESC) under a carbon taxation policy. As such, we couple recent advances in digitalisation of operations with increasingly stringent regulatory environmental policies. Specifically, with lead time considerations under emission rate constraints (imposed by a carbon taxation policy), we simultaneously consider the production, distribution and inventory control decisions in a production allocation-based MESC problem. The problem is then formulated as a Mixed Integer Non-Linear Programming (MINLP) model. We show that the distributed ledger-based blockchain approach minimises both total cost and carbon emissions. We then validate the feasibility of the proposed approach by comparing the results with a non-dominated sorting genetic algorithm (NSGA-II). The findings provide support for policymakers and supply chain executives alike.
Journal: International Journal of Production Research
Pages: 2222-2241
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1683248
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683248
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Template-Type: ReDIF-Article 1.0
Author-Name: Sajjad Rahmanzadeh
Author-X-Name-First: Sajjad
Author-X-Name-Last: Rahmanzadeh
Author-Name: Mir Saman Pishvaee
Author-X-Name-First: Mir Saman
Author-X-Name-Last: Pishvaee
Author-Name: Mohammad Reza Rasouli
Author-X-Name-First: Mohammad Reza
Author-X-Name-Last: Rasouli
Title: Integrated innovative product design and supply chain tactical planning within a blockchain platform
Abstract: 
 In globalised manufacturing and production environments, companies increasingly tend to exploit public contribution advantages within designing, manufacturing and marketing processes. To be benefited from outbound capabilities, this paper presents a tactical supply chain planning model to integrate the designing process in the form of open innovation within the supply chain main processes. In this regard, a fuzzy mathematical model is proposed to optimise the tactical decisions according to supply chain objectives and open innovation considerations. On the other hand, intellectual property issues and protecting the rights of innovators are significant concerns that sometimes avoid companies to be engaged in open innovation initiatives. Therefore, this paper proposes a registering mechanism in which the ideas and creative works are collected, refined and finally approved within a blockchain platform. Furthermore, in order to deal with epistemic environmental uncertainty, the fuzzy set theory is utilised. To investigate the applicability of the developed model, a case study in home appliances domain is employed. The results show that the company can achieve favourable designs by spending approximately 1% of the supply chain total cost. Additionally, benefiting the registering mechanism can decrease the cost of using non-original designs more than 41%.
Journal: International Journal of Production Research
Pages: 2242-2262
Issue: 7
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1651947
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1651947
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianming Zhang
Author-X-Name-First: Jianming
Author-X-Name-Last: Zhang
Author-Name: Xifan Yao
Author-X-Name-First: Xifan
Author-X-Name-Last: Yao
Author-Name: Yun Li
Author-X-Name-First: Yun
Author-X-Name-Last: Li
Title: Improved evolutionary algorithm for parallel batch processing machine scheduling in additive manufacturing
Abstract: 
 With the increasing prosperity of additive manufacturing, the 3D-printing shop scheduling problem has presented growing importance. The scheduling of such a shop is imperative for saving time and cost, but the problem is hard to solve, especially for simultaneous multi-part assignment and placement. This paper develops an improved evolutionary algorithm for application to additive manufacturing, by combining a genetic algorithm with a heuristic placement strategy to take into account the allocation and placement of parts integrally. The algorithm is designed also to enhance the optimisation efficiency by introducing an initialisation method based on the characteristics of the 3D printing process through the development of corresponding time calculation model. Experiments show that the developed algorithm can find better solutions compared with state-of-the-art algorithms such as simple genetic algorithm, particle swarm optimisation and heuristic algorithms.
Journal: International Journal of Production Research
Pages: 2263-2282
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1617447
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1617447
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:8:p:2263-2282




Template-Type: ReDIF-Article 1.0
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Author-Name: Xiaodong Wang
Author-X-Name-First: Xiaodong
Author-X-Name-Last: Wang
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Jianbo Yu
Author-X-Name-First: Jianbo
Author-X-Name-Last: Yu
Title: An energy-efficient two-stage hybrid flow shop scheduling problem in a glass production
Abstract: 
 Energy-efficient scheduling is highly necessary for energy-intensive industries, such as glass, mould or chemical production. Inspired by a real-world glass-ceramics production process, this paper investigates a bi-criteria energy-efficient two-stage hybrid flow shop scheduling problem, in which parallel machines with eligibility are at stage 1 and a batch machine is at stage 2. The performance measures considered are makespan and total energy consumption. Time-of-use (TOU) electricity prices and different states of machines (working, idle and turnoff) are integrated. To tackle this problem, a mixed integer programming (MIP) is formulated, based on which an augmented ε-constraint (AUGMECON) method is adopted to obtain the exact Pareto front. A problem-tailored constructive heuristic method with local search strategy, a bi-objective tabu search algorithm and a bi-objective ant colony optimisation algorithm are developed to deal with medium- and large-scale problems. Extensive computational experiments are conducted, and a real-world case is solved. The results show effectiveness of the proposed methods, in particular the bi-objective tabu search.
Journal: International Journal of Production Research
Pages: 2283-2314
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1624857
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1624857
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Template-Type: ReDIF-Article 1.0
Author-Name: Ke Rong
Author-X-Name-First: Ke
Author-X-Name-Last: Rong
Author-Name: Yong Lin
Author-X-Name-First: Yong
Author-X-Name-Last: Lin
Author-Name: Jiang Yu
Author-X-Name-First: Jiang
Author-X-Name-Last: Yu
Author-Name: Yue Zhang
Author-X-Name-First: Yue
Author-X-Name-Last: Zhang
Title: Manufacturing strategies for the ecosystem-based manufacturing system in the context of 3D printing
Abstract: 
 This paper aims to investigate the manufacturing strategies for the manufacturing systems in the context of 3D printing, referring to ecosystem-based manufacturing systems, rather than firm-based and network-based ones. A case study approach was adopted for this research, as the data was mainly collected via semi-structured interviews with staff members of companies in China. Besides the elements of strategic choices and manufacturing capabilities identified in the extant literature, this research verified three additional strategic choice elements (functional role, platform and solution) and identified two factors (platform openness and solution diversity) to classify an ecosystem-based manufacturing system. Meanwhile, four manufacturing capabilities of the ecosystem-based manufacturing system have been identified: collaborative manufacturing flexibility, rapid thriftiness ability, self-customisation and co-evolved design capability. The research results contribute to the area of manufacturing strategy via expanding its view from the firm and network levels to the ecosystem level. Meanwhile, the research results present operations managers with an understanding of the strategic choices and manufacturing capabilities of an ecosystem-based manufacturing system in the context of 3D printing.
Journal: International Journal of Production Research
Pages: 2315-2334
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1627436
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1627436
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Template-Type: ReDIF-Article 1.0
Author-Name: Rufeng Xu
Author-X-Name-First: Rufeng
Author-X-Name-Last: Xu
Author-Name: Xun Li
Author-X-Name-First: Xun
Author-X-Name-Last: Li
Author-Name: Guangming Zheng
Author-X-Name-First: Guangming
Author-X-Name-Last: Zheng
Author-Name: Xiang Cheng
Author-X-Name-First: Xiang
Author-X-Name-Last: Cheng
Author-Name: Yebing Tian
Author-X-Name-First: Yebing
Author-X-Name-Last: Tian
Title: A radius compensation method of barrel tool based on macro variables in five-axis flank machining of sculptured surfaces
Abstract: 
 Barrel tool radius compensation is very important to improve the five-axis CNC machining precision and efficiency of sculptured surfaces. By combining macro variables and math function of CNC controller, a radius compensation method of barrel tool based on macro variables in five-axis flank machining of sculptured surfaces was presented. The basic principle of barrel tool radius compensation in five-axis flank machining was firstly investigated. For a specific five-axis CNC machine tool with dual rotary tables, a relationship equation between compensated cutter location (CL) data and machine control (MC) data could be derived. A post-processor with the function of five-axis barrel tool radius compensation was then developed by using the C++ language, which could generate the NC programme with macro variables of barrel tool radius compensation. Finally, the NC programme was obtained automatically by the developed post-processor for the aero-engine blade surface machining. The machining process was simulated on the software VERICUT, and machining experiments were also conducted on the five-axis machine tool. Both the simulation and experimental results showed that the proposed method could perform the function of barrel tool radius compensation in the NC programme for five-axis flank machining.
Journal: International Journal of Production Research
Pages: 2335-2351
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1627437
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1627437
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:8:p:2335-2351




Template-Type: ReDIF-Article 1.0
Author-Name: X. Wang
Author-X-Name-First: X.
Author-X-Name-Last: Wang
Author-Name: A.W.W. Yew
Author-X-Name-First: A.W.W.
Author-X-Name-Last: Yew
Author-Name: S.K. Ong
Author-X-Name-First: S.K.
Author-X-Name-Last: Ong
Author-Name: A.Y.C. Nee
Author-X-Name-First: A.Y.C.
Author-X-Name-Last: Nee
Title: Enhancing smart shop floor management with ubiquitous augmented reality
Abstract: 
 This paper describes a framework for implementing Smart manufacturing Shop floor systems based on the Ubiquitous Augmented Reality technology (SSUAR). The proposed system makes use of data sharing between shop floor resources and a sensor network in order to optimise the production schedules for carrying out projects. The optimisation is performed in real-time and the production scheduling responds to new projects as well as the changing status of resources, such as machines and workers. Ubiquitous augmented reality interface has been developed and utilised as a user interface for the shop floor workers to receive information, instructions and guidance from the experts and manufacturing systems, and to update the systems on task parameters, such as estimated completion times, progress and machine status. A review of related work, methodology and implementation of the proposed system, and a case study are presented in this paper. Using this architecture, real-time scheduling of tasks in the smart shop floor can be achieved. The case study demonstrated the ability of SSUAR to integrate task scheduling with two-way communication between the system and the users.
Journal: International Journal of Production Research
Pages: 2352-2367
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1629667
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629667
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:8:p:2352-2367




Template-Type: ReDIF-Article 1.0
Author-Name: Shanyong Wang
Author-X-Name-First: Shanyong
Author-X-Name-Last: Wang
Author-Name: Jing Wang
Author-X-Name-First: Jing
Author-X-Name-Last: Wang
Author-Name: Feng Yang
Author-X-Name-First: Feng
Author-X-Name-Last: Yang
Author-Name: Jun Li
Author-X-Name-First: Jun
Author-X-Name-Last: Li
Author-Name: Jian Song
Author-X-Name-First: Jian
Author-X-Name-Last: Song
Title: Determinants of consumers’ remanufactured products purchase intentions: Evidence from China
Abstract: 
 Previous studies have examined the main factors that influence consumer acceptance of remanufactured products based on the theory of planned behaviour (TPB). However, researchers have not yet conducted detailed studies to classify the variables of TPB. In the present research, this gap is addressed by using a TPB model which (1) differentiates attitude into experiential attitude and instrumental attitude, (2) differentiates subjective norm into normative social influence and informational social influence, and (3) differentiates perceived behavioural control into product knowledge, perceived risk, and perceived inconvenience. In this study, past experience and the interaction effect of attitude and subjective norm are also considered. The research results suggest that experiential and instrumental attitude, normative and informational social influence, product knowledge, and past experience are positive determinants of consumers’ purchase intentions toward remanufactured products, while perceived inconvenience and perceived risk are negative determinants. Furthermore, the findings also suggest that the interaction effects of experiential attitude and subjective norms positively affect purchase intentions, whereas the interaction effects of instrumental attitude and subjective norms have a negative effect. Based on the research conclusions, this study concludes with a discussion of proposals for improving consumers’ remanufactured product purchase intentions, implications for product design and manufacturing, limitations of the current study, and recommendations for further research.
Journal: International Journal of Production Research
Pages: 2368-2383
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1630767
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630767
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Template-Type: ReDIF-Article 1.0
Author-Name: Morteza Ghobakhloo
Author-X-Name-First: Morteza
Author-X-Name-Last: Ghobakhloo
Title: Determinants of information and digital technology implementation for smart manufacturing
Abstract: 
 This study aims to identify and analyse factors that determine the implementation of Information and Digital Technologies (IDT) of smart manufacturing. By performing a state-of-the-art and content-driven review of literature, consulting a group of experts from academia and industry, and implementing interpretive structural modelling methodology, the study identified eleven enabling factors and mapped the contextual interrelationships among them. The study further explained the complex precedence relationships that exist among determinants of smart manufacturing IDT adoption. Results showed that perceived benefits and management support are the two driver determinants that act as stepping-stones in the implementation of smart manufacturing IDT. Operations technology maturity and cybersecurity maturity were found to be the dependent determinants of smart manufacturing IDT implementation and highly driven by the linkage and driver determinates. The findings are expected to assist academicians, industrialists, and the policymakers with achieving a detailed understanding of smart manufacturing transformation processes, and conditions that facilitate the manufacturing digitalisation in the Industry 4.0 era.
Journal: International Journal of Production Research
Pages: 2384-2405
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1630775
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630775
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhaohui Deng
Author-X-Name-First: Zhaohui
Author-X-Name-Last: Deng
Author-Name: Lishu Lv
Author-X-Name-First: Lishu
Author-X-Name-Last: Lv
Author-Name: Wenliang Huang
Author-X-Name-First: Wenliang
Author-X-Name-Last: Huang
Author-Name: Linlin Wan
Author-X-Name-First: Linlin
Author-X-Name-Last: Wan
Author-Name: Shichun Li
Author-X-Name-First: Shichun
Author-X-Name-Last: Li
Title: Modelling of carbon utilisation efficiency and its application in milling parameters optimisation
Abstract: 
 At present, the evaluation index for low carbon manufacturing was mainly focused on the relationship between carbon emission and economic benefits or removal volume. But there was rarely comprehensive evaluation index to evaluate the carbon utilisation level of processing. Based on this, this paper presented the carbon utilisation efficiency as the comprehensive evaluation index in low carbon manufacturing. The carbon utilisation efficiency was defined as the ratio of the carbon emission of materials removal to the whole carbon emission in manufacturing process. A carbon utilisation efficiency model was established in milling process, based on flow characteristics and removal mechanism of carbon emission during milling. Then a multi-objective optimisation model was established based on Particle Swarm Optimisation, and the minimum processing time and high carbon utilisation efficiency were set as the optimisation objectives. And the experiment was performed to confirm the undetermined constant in the optimisation model and verify the effectiveness of the optimisation model. The optimised milling parameters were verified to reduce the processing time and improve the carbon utilisation efficiency.
Journal: International Journal of Production Research
Pages: 2406-2420
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1633026
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1633026
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Template-Type: ReDIF-Article 1.0
Author-Name: Maya Golan
Author-X-Name-First: Maya
Author-X-Name-Last: Golan
Author-Name: Yuval Cohen
Author-X-Name-First: Yuval
Author-X-Name-Last: Cohen
Author-Name: Gonen Singer
Author-X-Name-First: Gonen
Author-X-Name-Last: Singer
Title: A framework for operator –  workstation interaction in Industry 4.0
Abstract: 
 We draw on cognitive and behavioural theories and on the artificial intelligence literature in order to propose a framework of future operator – workstation interaction in the ‘Industry 4.0’ era. We name the proposed framework ‘Operator – Workstation Interaction 4.0’. The latter’s capabilities permit an adaptive, ongoing interaction that aims to improve operator safety, performance, well-being, and satisfaction as well as the factory’s production measures. The framework is composed of three subsystems: (1) the observation subsystem which observes the operator and the processes occurring in the workstation, (2) the analysis subsystem which generates understanding and implications of the observations output, (3) the reaction subsystem which determines if and how to respond. The paper describes these elements and illustrate them using an example of a fatigued worker. The contributions, implications, and limitations of the proposed framework are discussed, and future research directions are presented.
Journal: International Journal of Production Research
Pages: 2421-2432
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1639842
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1639842
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Template-Type: ReDIF-Article 1.0
Author-Name: Katsuhiko Takahashi
Author-X-Name-First: Katsuhiko
Author-X-Name-Last: Takahashi
Author-Name: Kazuyoshi Ishii
Author-X-Name-First: Kazuyoshi
Author-X-Name-Last: Ishii
Author-Name: Chin-Yin Huang
Author-X-Name-First: Chin-Yin
Author-X-Name-Last: Huang
Author-Name: Ilkyeong Moon
Author-X-Name-First: Ilkyeong
Author-X-Name-Last: Moon
Author-Name: Bhaskar Bhandarkar
Author-X-Name-First: Bhaskar
Author-X-Name-Last: Bhandarkar
Author-Name: The Jin Ai
Author-X-Name-First: The Jin
Author-X-Name-Last: Ai
Author-Name: Tak Nam Wong
Author-X-Name-First: Tak Nam
Author-X-Name-Last: Wong
Title: Special issue on present and future of production in Asia Pacific countries
Journal: International Journal of Production Research
Pages: 2433-2435
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2020.1729948
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1729948
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Ivan Tomašević
Author-X-Name-First: Ivan
Author-X-Name-Last: Tomašević
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Author-Name: Constantin Blome
Author-X-Name-First: Constantin
Author-X-Name-Last: Blome
Author-Name: Steven Melnyk
Author-X-Name-First: Steven
Author-X-Name-Last: Melnyk
Author-Name: Hing Kai Chan
Author-X-Name-First: Hing Kai
Author-X-Name-Last: Chan
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: A systematic review of China’s belt and road initiative: implications for global supply chain management
Abstract: 
 China’s Belt and Road Initiative (BRI) is one of the world’s largest infrastructure projects, with its potential political and economic impact being widely discussed since its inception in 2013. Yet the phenomenon has received only limited attention in the Supply Chain Management (SCM) literature. In response, we first conduct a broad systematic review of the literature to assess how China’s BRI is portrayed. Using this as a backdrop, we then distil the likely impact of the BRI on location decisions and supply chain flows. Finally, in a broader discussion of the SCM literature, we explore the implications of the BRI for future research in four key areas: supply chain configuration, supply chain resilience, sustainable SCM, and cross border SCM. While these areas are not new, the BRI presents a unique context that can be used to enhance theory and understanding in each area. The BRI reduces time distance independent of geographical distance by diverting supply chain flows from established routes to new routes via far less accessible regions. This introduces new risks and sustainability issues that call for multi-criteria decision support systems. Another important issue is the adoption and diffusion of the BRI since this will ultimately determine project success.
Journal: International Journal of Production Research
Pages: 2436-2453
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1605225
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1605225
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Template-Type: ReDIF-Article 1.0
Author-Name: Rajdeep Singh
Author-X-Name-First: Rajdeep
Author-X-Name-Last: Singh
Author-Name: Neeraj Bhanot
Author-X-Name-First: Neeraj
Author-X-Name-Last: Bhanot
Title: An integrated DEMATEL-MMDE-ISM based approach for analysing the barriers of IoT implementation in the manufacturing industry
Abstract: 
 Incorporation of smart devices within the older framework has brought along significant challenges. This paper presents a detailed analysis of the barriers faced during the implementation of Internet of Things (IoT) within the manufacturing sector. In addition, the authors aim to obtain a hierarchical structure, which will help the policymakers to identify the most crucial barriers enabling them to make an informed decision. With the help of databases like Scopus, Web of Science, etc. a comprehensive list of 22 barriers was initially obtained. This list was further narrowed down to 10 critical barriers. The first step of the analysis involved the application of Decision Making Trial and Evaluation Laboratory (DEMATEL) technique, which quantifies the influence of the barriers amongst one another. Maximum Mean De-Entropy (MMDE) technique is then used to obtain a scientific threshold value, which is later used in the Interpretive Structural Modelling (ISM) technique from which a hierarchical structure of the barriers is obtained. The results of this study are expected to highlight the most crucial barriers wherein the researchers and practitioners can focus their strategic efforts. This will facilitate the addressal of implicit issues while implementing IoT Techniques in the manufacturing industry.
Journal: International Journal of Production Research
Pages: 2454-2476
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1675915
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1675915
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Template-Type: ReDIF-Article 1.0
Author-Name: Sei Okayama
Author-X-Name-First: Sei
Author-X-Name-Last: Okayama
Author-Name: Haruka Yamashita
Author-X-Name-First: Haruka
Author-X-Name-Last: Yamashita
Author-Name: Kenta Mikawa
Author-X-Name-First: Kenta
Author-X-Name-Last: Mikawa
Author-Name: Masayuki Goto
Author-X-Name-First: Masayuki
Author-X-Name-Last: Goto
Author-Name: Tomohiro Yoshikai
Author-X-Name-First: Tomohiro
Author-X-Name-Last: Yoshikai
Title: Relational analysis model of weather conditions and sales patterns based on nonnegative tensor factorization
Abstract: 
 It is necessary to analyze the relationships between the retail sales of various items and weather conditions. However, the relationship between the sales of each item and the weather condition may vary among stores. Additionally, it is necessary to model the statistical relationships between a wide variety of goods and weather conditions by using past sales data. In such a case, it becomes unrealistic to construct a forecast model for every individual item owing to the breadth of items and the number of retail shops. This study proposes a model to analyze the relationships between the sales of various items and weather conditions. This method can be used to decompose the data into three matrices based on the nonnegative tensor factorization (NTF) method. The results of the analysis clarified that the proposed model can identify important items whose demand is strongly influenced by weather conditions, thereby increasing the effectiveness of inventory management. Additionally, the store clusters estimated by the proposed model can facilitate the construction of regression models that demonstrate the relationship between the sales of each item and weather conditions.
Journal: International Journal of Production Research
Pages: 2477-2489
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1692157
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1692157
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Template-Type: ReDIF-Article 1.0
Author-Name: Giuseppe Timperio
Author-X-Name-First: Giuseppe
Author-X-Name-Last: Timperio
Author-Name: Sunil Tiwari
Author-X-Name-First: Sunil
Author-X-Name-Last: Tiwari
Author-Name: José Manuel Gaspar Sánchez
Author-X-Name-First: José Manuel
Author-X-Name-Last: Gaspar Sánchez
Author-Name: Rafael Adrián García Martín
Author-X-Name-First: Rafael Adrián
Author-X-Name-Last: García Martín
Author-Name: Robert de Souza
Author-X-Name-First: Robert
Author-X-Name-Last: de Souza
Title: Integrated decision support framework for distribution network design
Abstract: 
 In the current business environment of competition shifting from company-to-company to supply chain against supply chain, there is an increasing need for logistics providers (LSP) to gain cost effectiveness with no compromise on service levels. One key initiative that LSP can undertake is to allocate and utilise their storage and transportation assets optimally. The current work is an attempt in that direction and provides a hands-on decision support framework that integrates MCDM, network optimisation, and discrete event simulation to address distribution network design and transport optimisation. The use case of PT Pos Indonesia in the metropolitan area of Greater Surabaya highlights the benefits of combining ICT tools with well-established best practices in supply chain management. Findings of this work highlight that the number of distribution facilities for the case at hand should be reduced from nine to four. Compared to the existing, the identified network configuration unlocks potential cost saving in transportation and warehousing of 18%–22%, reduces CO2 emissions by nearly 30%, with no deterioration in service level. Managerial implications about transportation policies are highlighted in the conclusive part of this paper.
Journal: International Journal of Production Research
Pages: 2490-2509
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1680894
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1680894
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Template-Type: ReDIF-Article 1.0
Author-Name: Yasuhiko Takemoto
Author-X-Name-First: Yasuhiko
Author-X-Name-Last: Takemoto
Author-Name: Ikuo Arizono
Author-X-Name-First: Ikuo
Author-X-Name-Last: Arizono
Title: Moral hazard problem and collaborative coordination in supply chain with capacity reservation contract
Abstract: 
 This paper has considered collaborative coordination in supply chains with capacity reservation contracts using the game theory. In some traditional papers, the capacity reservation contracts have contained a capacity quantity, a reservation quantity and a reservation fee as a decision variable. Each decision variable is determined separately based on individual profit functions of a supplier and a manufacturer under the noncooperative game theory. Those papers have assumed that the supplier is always forced to build sufficient capacity to cover the reservation amount of the manufacturer. However, the supplier might not always comply with the reservation amount of the manufacturer since the capacity quantity is a private decision in the supplier and not released to external companies in practice. For instance, the supplier may choose to under-build knowingly to ensure high utilisation of his capacity. This is a kind of moral hazard problems. This paper has investigated such a strategy that the supplier and manufacturer voluntarily comply with the contract for the purpose of solving the moral hazard problem in the capacity reservation contract. Consequently, we have proposed a method of determining the decision variables collaboratively in the contract such that a consensus of the supplier and manufacturer is built.
Journal: International Journal of Production Research
Pages: 2510-2526
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1633027
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1633027
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Xin Liu
Author-X-Name-First: Xin
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Profit-oriented distributionally robust chance constrained flowshop scheduling considering credit risk
Abstract: 
 Customer credit risk or payment probability, influenced by factors such as financial conditions and bank policies, has hindered fast Asia-Pacific economic growth. Besides, the working time is usually limited due to regulations and limited resources. Driven by profit, some jobs may be rejected on tactical level and the accepted jobs are scheduled on operational level, respecting the allowed working time. This paper studies a stochastic flowshop scheduling problem, assuming that only the mean and covariance matrix of uncertain payment probabilities and processing times are known. The objective is to maximise the profit level, i.e. the probability of the profit no less than the planned one, while controlling the risk of surpassing the limited working time. A new distributionally robust chance constrained model is proposed. The sample average approximation (SAA) method, the robust SAA method and a hierarchical approach, based on an approximated mixed integer second-order conic program, are developed. Numerical experiments show that the hierarchical approach is more efficient. Moreover, some managerial insights are drawn.
Journal: International Journal of Production Research
Pages: 2527-2549
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2020.1711982
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1711982
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Template-Type: ReDIF-Article 1.0
Author-Name: Ikuo Arizono
Author-X-Name-First: Ikuo
Author-X-Name-Last: Arizono
Author-Name: Kazunori Yoshimoto
Author-X-Name-First: Kazunori
Author-X-Name-Last: Yoshimoto
Author-Name: Ryosuke Tomohiro
Author-X-Name-First: Ryosuke
Author-X-Name-Last: Tomohiro
Title: Variable stage-independent double sampling plan with screening for acceptance quality loss limit inspection scheme
Abstract: 
 The quality loss suggested by Taguchi has been recognised as a new quality evaluation based on variable property instead of the quality evaluation based on traditional attribute property such as the proportion of nonconforming items. Some variable sampling inspection plans in order to assure the quality have been considered. As one of those sampling inspection plans, the single sampling plan with screening (SSPS) has been constructed for acceptance quality loss limit inspection scheme. Further, the repetitive group sampling plan with screening (RGSPS) has been developed for reducing the average total inspection (ATI). Although ATI by RGSPS has successfully been reduced in comparison with ATI by SSPS, RGSPS may sometimes increase the average sampling frequency (ASF) in return for reducing ATI. In this study, the stage-independent double sampling plan with screening (SIDSPS) based on the concept of the acceptance quality loss limit inspection scheme is proposed under the consideration of the trade-off between ATI and ASF. Through some numerical comparisons about ATI and ASF in SSPS, RGSPS, and SIDSPS, the usefulness of SIDSPS proposed in this study is confirmed.
Journal: International Journal of Production Research
Pages: 2550-2559
Issue: 8
Volume: 58
Year: 2020
Month: 4
X-DOI: 10.1080/00207543.2019.1598594
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1598594
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Template-Type: ReDIF-Article 1.0
Author-Name: Yong Zhou
Author-X-Name-First: Yong
Author-X-Name-Last: Zhou
Author-Name: Jian-jun Yang
Author-X-Name-First: Jian-jun
Author-X-Name-Last: Yang
Author-Name: Zhuang Huang
Author-X-Name-First: Zhuang
Author-X-Name-Last: Huang
Title: Automatic design of scheduling policies for dynamic flexible job shop scheduling via surrogate-assisted cooperative co-evolution genetic programming
Abstract: 
 At present, a lot of references use discrete event simulation to evaluate the fitness of evolved rules, but which simulation configuration can achieve better evolutionary rules in a limited time has not been fully studied. This study proposes three types of hyper-heuristic methods for coevolution of the machine assignment rules (MAR) and job sequencing rules (JSR) to solve the DFJSP, including the cooperative coevolution genetic programming with two sub-populations (CCGP), the genetic programming with two sub-trees (TTGP) and the genetic expression programming with two sub-chromosomes (GEP). After careful parameter tuning, a surrogate simulation model is used to evaluate the fitness of evolved scheduling policies (SP). Computational simulations and comparisons demonstrate that the proposed surrogate-assisted CCGP method (CCGP-SM) shows competitive performance with other evolutionary approaches using the same computation time. Furthermore, the learning process of the proposed methods demonstrates that the surrogate-assisted GP methods help accelerating the evolutionary process and improving the quality of the evolved SPs without a signiﬁcant increase in the length of SP. In addition, the evolved SPs generated by the CCGP-SM show superior performance as compared with existing rules in the literature. These results demonstrate the effectiveness and robustness of the proposed method.
Journal: International Journal of Production Research
Pages: 2561-2580
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1620362
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1620362
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Template-Type: ReDIF-Article 1.0
Author-Name: Douglas Alem
Author-X-Name-First: Douglas
Author-X-Name-Last: Alem
Author-Name: Fabricio Oliveira
Author-X-Name-First: Fabricio
Author-X-Name-Last: Oliveira
Author-Name: Miguel Carrión Ruiz Peinado
Author-X-Name-First: Miguel Carrión Ruiz
Author-X-Name-Last: Peinado
Title: A practical assessment of risk-averse approaches in production lot-sizing problems
Abstract: 
 This paper presents an empirical assessment of four state-of-the-art risk-averse approaches to deal with the capacitated lot-sizing problem under stochastic demand. We analyse two mean-risk models based on the semideviation and on the conditional value-at-risk risk measures, and alternate first and second-order stochastic dominance approaches. The extensive computational experiments based on different instances characteristics and on a case-study suggest that CVaR exhibits a good trade-off between risk and performance, followed by the semideviation and first-order stochastic dominance approach. For all approaches, enforcing risk-aversion helps to reduce the cost-standard deviation substantially, which is usually accomplished via increasing production rates. Overall, we can say that very risk-averse decision-makers would be willing to pay an increased price to have a much less risky solution given by CVaR. In less risk-averse settings, though, semideviation and first-order stochastic dominance can be appealing alternatives to provide significantly more stable production planning costs with a marginal increase of the expected costs.
Journal: International Journal of Production Research
Pages: 2581-2603
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1620364
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1620364
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Template-Type: ReDIF-Article 1.0
Author-Name: Fei Shi
Author-X-Name-First: Fei
Author-X-Name-Last: Shi
Author-Name: Shikui Zhao
Author-X-Name-First: Shikui
Author-X-Name-Last: Zhao
Author-Name: Yue Meng
Author-X-Name-First: Yue
Author-X-Name-Last: Meng
Title: Hybrid algorithm based on improved extended shifting bottleneck procedure and GA for assembly job shop scheduling problem
Abstract: 
 With the makespan as the optimisation goal, we propose a hybrid solving method that combines improved extended shifting bottleneck procedure (i-ESB) and genetic algorithm (GA) for the assembly job shop scheduling problem (AJSSP). Hybrid genetic algorithm (HGA) uses a GA based on operation constraint chain coding to achieve global search and a local search based on an i-ESB. In the design of i-ESB, an extended disjunctive graph model (EDG) corresponding to AJSSP is presented. The calculation method of the operation head and tail length based on EDG is studied, as well as the searching method of key operations. The Schrage algorithm with disturbance is used to solve the single-machine scheduling subproblem. The selection criterion for bottleneck machines is increased. A greedy bottleneck machine re-optimisation process is designed. The effectiveness and superiority of the proposed algorithm are verified by testing and analysing the relevant examples in the literature. 
Journal: International Journal of Production Research
Pages: 2604-2625
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1622052
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1622052
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Template-Type: ReDIF-Article 1.0
Author-Name: Shuang Zheng
Author-X-Name-First: Shuang
Author-X-Name-Last: Zheng
Author-Name: Zhen Yang
Author-X-Name-First: Zhen
Author-X-Name-Last: Yang
Author-Name: Zhengwen He
Author-X-Name-First: Zhengwen
Author-X-Name-Last: He
Author-Name: Nengmin Wang
Author-X-Name-First: Nengmin
Author-X-Name-Last: Wang
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Author-Name: Haiyang Yu
Author-X-Name-First: Haiyang
Author-X-Name-Last: Yu
Title: Hybrid simulated annealing and reduced variable neighbourhood search for an aircraft scheduling and parking problem
Abstract: 
 Aircraft stands and runways at airports are critical airport resources for aircraft scheduling and parking. Making use of limited apron and runway resources to improve airport efficiency is becoming increasingly important. In this paper, we study a realistic Aircraft Scheduling and Parking Problem (ASPP) with the goal of simultaneously determining the takeoff and landing time of each aircraft with consideration for wake vortex effect constraints and parking positions in the limited parking apron at a target airport. The objective of the ASPP is to minimise the total service time for aircraft. We developed a mixed-integer linear programme formulation for the ASPP. A novel improved bottom-left/right strategy is applied to construct solutions and a Hybrid Simulated Annealing and Reduced Variable Neighborhood Search (HSARVNS) is proposed to identify near-optimal solutions. Numerical experiments on randomly generated ASPP instances and on a large set of benchmarks for a reduced version of the ASPP (i.e. the classical Two-Dimensional Strip-Packing Problem (2D-SPP)) demonstrate the effectiveness and efficiency of the proposed approach. For the ASPP, HSARVNS can find optimal solutions for small instances in a fraction of a second and can find high-quality solutions for instances with up to 250 aircraft within a reasonable timeframe. For the 2D-SPP, the HSARVNS can find optimal solutions for 32 of 38 tested benchmarks within 90 s on average.
Journal: International Journal of Production Research
Pages: 2626-2646
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1629663
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629663
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Template-Type: ReDIF-Article 1.0
Author-Name: Guodong Zhao
Author-X-Name-First: Guodong
Author-X-Name-Last: Zhao
Author-Name: Jiyin Liu
Author-X-Name-First: Jiyin
Author-X-Name-Last: Liu
Author-Name: Yun Dong
Author-X-Name-First: Yun
Author-X-Name-Last: Dong
Title: Scheduling the operations of a double-load crane in slab yards
Abstract: 
 This paper studies a double-load crane scheduling problem (DLCSP) in steel slab yards. A slab yard stores slabs in stacks. To prepare for use in production, some slabs need to be moved from one place to another. These movement tasks are performed by a double-load crane which can hold up to two slabs simultaneously. Given a set of tasks and possibly precedence relationships among them, the scheduling problem is to allocate the tasks to double-load operations and determine the schedule for the crane to perform the tasks so as to minimise the makespan. The problem is first formulated as a mixed integer linear programming (MILP) model with variables representing the order of tasks. Based on properties of the problem, it is then reformulated from a crane operation perspective. Computational experiments are carried out on practical data collected from a steel company. The results show that both models can solve practical sized problems optimally, with the second model being more efficient.
Journal: International Journal of Production Research
Pages: 2647-2657
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1629666
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629666
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Genrikh Levin
Author-X-Name-First: Genrikh
Author-X-Name-Last: Levin
Author-Name: Boris Rozin
Author-X-Name-First: Boris
Author-X-Name-Last: Rozin
Title: Optimisation of the aggregation and execution rates for intersecting operation sets: an example of machining process design
Abstract: 
 A sequence of multiple parts is processed on a multi-position transfer line of conveyor type. This sequence consists of identical subsequences (batches). The sets of operations executed for each part at each position are given and these sets for different parts can intersect. Some operations executed at one position can be aggregated into blocks of operations. Each block is executed at a uniform rate (in particular, feed per minute) by a common drive unit. The set of potentially feasible blocks is specified. We consider the situation when the sets of operations for different blocks do not intersect and each potential block can be executed either completely aggregated (i.e. as one block) or completely disaggregated (individually). Aggregation reduces the investment costs, but can increase the consumption of tools due to excluding the individual selection of rates for aggregated operations. The accepted option of the aggregation and the rates of operations remain invariable during the line functioning. The problem is to select the optimal option of aggregation and rates of all operations that minimise the total batch processing cost while ensuring the required line productivity. A mathematical model of the problem and a two-level decomposition method for its solution are proposed. The statement of the problem and the results of its solution are illustrated on a real industrial example. The developed model and method can be applied to solve similar problems arising in other domains.
Journal: International Journal of Production Research
Pages: 2658-2676
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1629668
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629668
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Template-Type: ReDIF-Article 1.0
Author-Name: Pavel Borisovsky
Author-X-Name-First: Pavel
Author-X-Name-Last: Borisovsky
Author-Name: Anton Eremeev
Author-X-Name-First: Anton
Author-X-Name-Last: Eremeev
Author-Name: Josef Kallrath
Author-X-Name-First: Josef
Author-X-Name-Last: Kallrath
Title: Multi-product continuous plant scheduling: combination of decomposition, genetic algorithm, and constructive heuristic
Abstract: 
 We propose a polylithic method for medium-term scheduling of a large-scale industrial plant operating in a continuous mode. The method combines a decomposition approach, a genetic algorithm (GA) and a constructive MILP-based heuristic. In the decomposition, decisions are made at two levels, using the rolling horizon approach. At the upper level, a reduced set of products and the time period is chosen to be considered in the lower level. At the lower level, a short-term scheduling MILP-model with event-based representation is used. A heuristic solution to the lower level problem is found using a constructive Moving Window heuristic guided by a genetic algorithm. The GA is applied for finding efficient utilisation of critical units in the lower level problem. For solving the one unit scheduling problem, a parallel dynamic programming algorithm is proposed. Implementation of the dynamic programming algorithm for a graphics processing unit (GPU) is incorporated in the GA for improving its performance. The experimental study of the proposed method on a real case of a large-scale plant shows a significant improvement of the solution quality and the solving time comparing to the pure decomposition algorithm proposed in the earlier study, and confirmed suitability of the proposed approach for the real-life production scheduling. In particular, the reduction of the number of changeovers and their duration in the obtained solution as well as the CPU time of solving the problem was about 60% using the new approach.
Journal: International Journal of Production Research
Pages: 2677-2695
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1630764
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630764
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Template-Type: ReDIF-Article 1.0
Author-Name: Dhananjay Thiruvady
Author-X-Name-First: Dhananjay
Author-X-Name-Last: Thiruvady
Author-Name: Kerri Morgan
Author-X-Name-First: Kerri
Author-X-Name-Last: Morgan
Author-Name: Amiza Amir
Author-X-Name-First: Amiza
Author-X-Name-Last: Amir
Author-Name: Andreas T. Ernst
Author-X-Name-First: Andreas T.
Author-X-Name-Last: Ernst
Title: Large neighbourhood search based on mixed integer programming and ant colony optimisation for car sequencing
Abstract: 
 We investigate the problem of scheduling a sequence of cars to be placed on an assembly line. Stations, along the assembly line install options (e.g. air conditioning), but have limited capacities, and hence cars requiring the same options need to be distributed far enough apart. The desired separation is not always feasible, leading to an optimisation problem that minimises the violation of the ideal separation requirements. In order to solve the problem, we use a large neighbourhood search (LNS) based on mixed integer programming (MIP). The search is implemented as a sliding window, by selecting overlapping subsequences of manageable sizes, which can be solved efficiently. Our experiments show that, with LNS, substantial improvements in solution quality can be found.
Journal: International Journal of Production Research
Pages: 2696-2711
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1630765
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630765
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Template-Type: ReDIF-Article 1.0
Author-Name: Mateus Martin
Author-X-Name-First: Mateus
Author-X-Name-Last: Martin
Author-Name: Pedro H.D.B. Hokama
Author-X-Name-First: Pedro H.D.B.
Author-X-Name-Last: Hokama
Author-Name: Reinaldo Morabito
Author-X-Name-First: Reinaldo
Author-X-Name-Last: Morabito
Author-Name: Pedro Munari
Author-X-Name-First: Pedro
Author-X-Name-Last: Munari
Title: The constrained two-dimensional guillotine cutting problem with defects: an ILP formulation, a Benders decomposition and a CP-based algorithm
Abstract: 
 This paper addresses a variant of two-dimensional cutting problems in which rectangular small pieces are obtained by cutting a rectangular object through guillotine cuts. The characteristics of this variant are (i) the object contains some defects, and the items cut must be defective-free; (ii) there is an upper bound on the number of times an item type may appear in the cutting pattern; (iii) the number of guillotine stages is not restricted. This problem commonly arises in industrial settings that deal with defective materials, e.g. either by intrinsic characteristics of the object as in the cutting of wooden boards with knotholes in the wood industry, or by the manufacturing process as in the production of flat glass in the glass industry. We propose a compact integer linear programming (ILP) model for this problem based on the discretisation of the defective object. As solution methods for the problem, we develop a Benders decomposition algorithm and a constraint-programming (CP) based algorithm. We evaluate these approaches through computational experiments, using benchmark instances from the literature. The results show that the methods are effective on different types of instances and can find optimal solutions even for instances with dimensions close to real-size.
Journal: International Journal of Production Research
Pages: 2712-2729
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1630773
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630773
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen-Fu Chien
Author-X-Name-First: Chen-Fu
Author-X-Name-Last: Chien
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Woonghee Tim Huh
Author-X-Name-First: Woonghee Tim
Author-X-Name-Last: Huh
Author-Name: Young Jae Jang
Author-X-Name-First: Young Jae
Author-X-Name-Last: Jang
Author-Name: James R. Morrison
Author-X-Name-First: James R.
Author-X-Name-Last: Morrison
Title: Artificial intelligence in manufacturing and logistics systems: algorithms, applications, and case studies
Journal: International Journal of Production Research
Pages: 2730-2731
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2020.1752488
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1752488
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Template-Type: ReDIF-Article 1.0
Author-Name: Congying Deng
Author-X-Name-First: Congying
Author-X-Name-Last: Deng
Author-Name: Jianguo Miao
Author-X-Name-First: Jianguo
Author-X-Name-Last: Miao
Author-Name: Ying Ma
Author-X-Name-First: Ying
Author-X-Name-Last: Ma
Author-Name: Bo Wei
Author-X-Name-First: Bo
Author-X-Name-Last: Wei
Author-Name: Yi Feng
Author-X-Name-First: Yi
Author-X-Name-Last: Feng
Title: Reliability analysis of chatter stability for milling process system with uncertainties based on neural network and fourth moment method
Abstract: 
 A reliability analysis of the milling system with uncertainties is developed in this paper to predict reliable chatter-free machining parameters. The chatter reliability refers to the probability of no chatter for the dynamic milling system. Then a reliability model is established to predict the chatter vibration, in which the dominant modal parameters of the dynamic milling system are defined as random variables. To solve the reliable model with the second-order fourth-moment (SOFM) method, the limiting axial cutting depth is substituted by an explicit expression obtained using a neural network. Therefore, after distributions of the random parameters are experimentally determined, the reliability of the given machining parameters can be computed with the SOFM method. Furthermore, a reliable stability lobe diagram (RSLD) can be plotted to obtain more reliable and accurate stable region instead of the conventional SLD. A case study is performed to validate the feasibility of the proposed method. The reliability of the milling system was calculated with the SOFM method, the first-order second-moment (FOSM) method and the Monte Carlo simulation (MCS) method. The results from the SOFM method and MCS method were found to be more consistent. Moreover, a RSLD with the reliability level 0.99 was compared with a conventional SLD plotted using the mean values of the random parameters. Chatter tests shown that the RSLD with the higher reliability level was more accurate for predicting the chatter-free machining parameters.
Journal: International Journal of Production Research
Pages: 2732-2750
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1636327
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1636327
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Template-Type: ReDIF-Article 1.0
Author-Name: Weiguang Fang
Author-X-Name-First: Weiguang
Author-X-Name-Last: Fang
Author-Name: Yu Guo
Author-X-Name-First: Yu
Author-X-Name-Last: Guo
Author-Name: Wenhe Liao
Author-X-Name-First: Wenhe
Author-X-Name-Last: Liao
Author-Name: Karthik Ramani
Author-X-Name-First: Karthik
Author-X-Name-Last: Ramani
Author-Name: Shaohua Huang
Author-X-Name-First: Shaohua
Author-X-Name-Last: Huang
Title: Big data driven jobs remaining time prediction in discrete manufacturing system: a deep learning-based approach
Abstract: 
 Implementing advanced big data (BD) analytic is significant for successful incorporation of artificial intelligence in manufacturing. With the widespread deployment of smart sensors and internet of things (IOT) in the job shop, there is an increasing need for handling manufacturing BD for predictive manufacturing. In this study, we conceive the jobs remaining time (JRT) prediction during manufacturing execution based on deep learning (DL) with production BD. We developed a procedure for JRT prediction that includes three parts: raw data collection, candidate dataset design and predictive modelling. First, the historical production data are collected by the widely deployed IOT in the job shop. Then, the candidate dataset is formalised to capture various contributory factors for JRT prediction. Further, a DL model named stacked sparse autoencoder (S-SAE) is constructed to learn representative features from high dimensional manufacturing BD to make robust and accurate JRT prediction. Our work represents the first DL model for the JRT prediction at run time during production. The proposed methods are applied in a large-scale job shop that is equipped with 44 machine tools and produces 13 types of parts. Lastly, the experimental results show the S-SAE model has higher accuracy than previous linear regression, back-propagation network, multi-layer network and deep belief network in JRT prediction.
Journal: International Journal of Production Research
Pages: 2751-2766
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1602744
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1602744
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:9:p:2751-2766




Template-Type: ReDIF-Article 1.0
Author-Name: Yunqing Rao
Author-X-Name-First: Yunqing
Author-X-Name-Last: Rao
Author-Name: Ronghua Meng
Author-X-Name-First: Ronghua
Author-X-Name-Last: Meng
Author-Name: Jing Zha
Author-X-Name-First: Jing
Author-X-Name-Last: Zha
Author-Name: Xiaofei Xu
Author-X-Name-First: Xiaofei
Author-X-Name-Last: Xu
Title: Bi-objective mathematical model and improved algorithm for optimisation of welding shop scheduling problem
Abstract: 
 This paper addresses a bi-objective welding shop scheduling problem (BWSSP) aiming to minimise the total tardiness and the machine interaction effect. The BWSSP is a special flow-shop scheduling problem (FSP) which is characterised by the fact that more than one machine can process on one job at a certain stage. This study analyses the operation of a structural metal manufacturing plant, and includes various aspects such as job sequence, machine-number-dependent processing time, lifting up time, lifting down time and different delivery time. A novel mixed-integer programming model (MIPM) is established, which can be used to minimise the delayed delivery time and the total machine interaction effect. One machine interaction effect formula is given in this paper. In order to solve this BWSSP, an appropriate non-dominated sorting Genetic Algorithm III (NSGAIII), embedded with a restarted strategy (RNSGAIII), is proposed. The restarted strategy, which can increase the diversity of the solutions, will be triggered with a restart probability. Following the iterative process, an effective strategy is applied to reduce the interaction effect penalty, on the premise that the makespan will remain unchanged. Total five algorithms, namely NSGAII, NSGAIII, harmony search algorithm (HSA), strength Pareto evolutionary algorithm (SPEA2), and RNSGAIII are utilised to solve this engineering problem. Numerical simulations show that the improved RNSGAIII outperforms the other methods, and the Pareto solution distribution and diversity, in particular, are significantly improved.
Journal: International Journal of Production Research
Pages: 2767-2783
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1656837
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656837
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen-Fu Chien
Author-X-Name-First: Chen-Fu
Author-X-Name-Last: Chien
Author-Name: Yun-Siang Lin
Author-X-Name-First: Yun-Siang
Author-X-Name-Last: Lin
Author-Name: Sheng-Kai Lin
Author-X-Name-First: Sheng-Kai
Author-X-Name-Last: Lin
Title: Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor
Abstract: 
 A semiconductor distributor that plays a third-party role in the supply chain will buy diverse components from different suppliers, warehouse and resell them to a number of electronics manufacturers with vendor-managed inventories, while suffering both risks of oversupply and shortage due to demand uncertainty. However, demand fluctuation and supply chain complexity are increasing due to shortening product life cycle in the consumer electronics era and long lead time for capacity expansion for high-tech manufacturing. Focusing realistic needs of a leading distributor for semiconductor components and modules, this study aims to construct a UNISON framework based on deep reinforcement learning (RL) for dynamically selecting the optimal demand forecast model for each of the products with the corresponding demand patterns to empower smart production for Industry 3.5. Deep RL that integrates deep learning architecture and RL algorithm can learn successful policies from the dynamic and complex real world. The reward function mechanism of deep RL can reduce negative impact of demand uncertainty. An empirical study was conducted for validation showing practical viability of the proposed approach. Indeed, the developed solution has been in real settings.
Journal: International Journal of Production Research
Pages: 2784-2804
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2020.1733125
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1733125
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Template-Type: ReDIF-Article 1.0
Author-Name: Byunghoon Kim
Author-X-Name-First: Byunghoon
Author-X-Name-Last: Kim
Author-Name: Young-Seon Jeong
Author-X-Name-First: Young-Seon
Author-X-Name-Last: Jeong
Author-Name: Seung Hoon Tong
Author-X-Name-First: Seung Hoon
Author-X-Name-Last: Tong
Author-Name: Myong K. Jeong
Author-X-Name-First: Myong K.
Author-X-Name-Last: Jeong
Title: A generalised uncertain decision tree for defect classification of multiple wafer maps
Abstract: 
 Classification of defect chip patterns is one of the most important tasks in semiconductor manufacturing process. During the final stage of the process just before release, engineers must manually classify and summarise information of defect chips from a number of wafers that can aid in diagnosing the root causes of failures. Traditionally, several learning algorithms have been developed to classify defect patterns on wafer maps. However, most of them focused on a single wafer bin map based on certain features. The objective of this study is to propose a novel approach to classify defect patterns on multiple wafer maps based on uncertain features. To classify distinct defect patterns described by uncertain features on multiple wafer maps, we propose a generalised uncertain decision tree model considering correlations between uncertain features. In addition, we propose an approach to extract uncertain features of multiple wafer maps from the critical fail bit test (FBT) map, defect shape, and location based on a spatial autocorrelation method. Experiments were conducted using real-life DRAM wafers provided by the semiconductor industry. Results show that the proposed approach is much better than any existing methods reported in the literature.
Journal: International Journal of Production Research
Pages: 2805-2821
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1637035
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1637035
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Template-Type: ReDIF-Article 1.0
Author-Name: Cheng-Hung Wu
Author-X-Name-First: Cheng-Hung
Author-X-Name-Last: Wu
Author-Name: Fang-Yi Zhou
Author-X-Name-First: Fang-Yi
Author-X-Name-Last: Zhou
Author-Name: Chi-Kang Tsai
Author-X-Name-First: Chi-Kang
Author-X-Name-Last: Tsai
Author-Name: Cheng-Juei Yu
Author-X-Name-First: Cheng-Juei
Author-X-Name-Last: Yu
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Title: A deep learning approach for the dynamic dispatching of unreliable machines in re-entrant production systems
Abstract: 
 This research combines deep neural network (DNN) and Markov decision processes (MDP) for the dynamic dispatching of re-entrant production systems. In re-entrant production systems, jobs enter the same workstation multiple times and dynamic dispatching oftentimes aims to dynamically assign different priorities to various job groups to minimise weighted cycle time or maximise throughput. MDP is an effective tool for dynamic production control, but it suffers from two major challenges in dynamic control problems. First, the curse of dimensionality limits the computational performance of solving large MDP problems. Second, a different model should be built and solved after system configuration is changed. DNN is used to overcome both challenges by learning directly from optimal dispatching policies generated by MDP. Results suggest that a properly trained DNN model can instantly generate near-optimal dynamic control policies for large problems. The quality of the DNN solution is compared with the optimal dynamic control policies through the standard K-fold cross-validation test and discrete event simulation. On average, the performance of the DNN policy is within 2% of optimal in both tests. The proposed artificial intelligence algorithm illustrates the potential of machine learning methods in manufacturing applications.
Journal: International Journal of Production Research
Pages: 2822-2840
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2020.1727041
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1727041
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Template-Type: ReDIF-Article 1.0
Author-Name: Hietam Elhoone
Author-X-Name-First: Hietam
Author-X-Name-Last: Elhoone
Author-Name: Tianyang Zhang
Author-X-Name-First: Tianyang
Author-X-Name-Last: Zhang
Author-Name: Mohd Anwar
Author-X-Name-First: Mohd
Author-X-Name-Last: Anwar
Author-Name: Salil Desai
Author-X-Name-First: Salil
Author-X-Name-Last: Desai
Title: Cyber-based design for additive manufacturing using artificial neural networks for Industry 4.0
Abstract: 
 Additive Manufacturing (AM) requires integrated networking, embedded controls and cloud computing technologies to increase their efficiency and resource utilisation. However, currently there is no readily applicable system that can be used for cloud-based AM. The objective of this research is to develop a framework for designing a cyber additive manufacturing system that integrates an expert system with Internet of Things (IoT). An Artificial Neural Network (ANN) based expert system was implemented to classify input part designs based on CAD data and user inputs. Three ANN algorithms were trained on a knowledge base to identify optimal AM processes for different part designs. A two-stage model was used to enhance the prediction accuracy above 90% by increasing the number of input factors and datasets. A cyber interface was developed to query AM machine availability and resource capability using a Node-RED IoT device simulator. The dynamic AM machine identification system developed using an application programme interface (API) that integrates inputs from the smart algorithm and IoT interface for real-time predictions. This research establishes a foundation for the development of a cyber additive design for manufacturing system which can dynamically allocate digital designs to different AM techniques over the cyber network.
Journal: International Journal of Production Research
Pages: 2841-2861
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1671627
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1671627
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Template-Type: ReDIF-Article 1.0
Author-Name: Darko Stanisavljevic
Author-X-Name-First: Darko
Author-X-Name-Last: Stanisavljevic
Author-Name: David Cemernek
Author-X-Name-First: David
Author-X-Name-Last: Cemernek
Author-Name: Heimo Gursch
Author-X-Name-First: Heimo
Author-X-Name-Last: Gursch
Author-Name: Günter Urak
Author-X-Name-First: Günter
Author-X-Name-Last: Urak
Author-Name: Gernot Lechner
Author-X-Name-First: Gernot
Author-X-Name-Last: Lechner
Title: Detection of interferences in an additive manufacturing process: an experimental study integrating methods of feature selection and machine learning
Abstract: 
 Additive manufacturing becomes a more and more important technology for production, mainly driven by the ability to realise extremely complex structures using multiple materials but without assembly or excessive waste. Nevertheless, like any high-precision technology additive manufacturing responds to interferences during the manufacturing process. These interferences – like vibrations – might lead to deviations in product quality, becoming manifest for instance in a reduced lifetime of a product or application issues. This study targets the issue of detecting such interferences during a manufacturing process in an exemplary experimental setup. Collection of data using current sensor technology directly on a 3D-printer enables a quantitative detection of interferences. The evaluation provides insights into the effectiveness of the realised application-oriented setup, the effort required for equipping a manufacturing system with sensors, and the effort for acquisition and processing the data. These insights are of practical utility for organisations dealing with additive manufacturing: the chosen approach for detecting interferences shows promising results, reaching interference detection rates of up to 100% depending on the applied data processing configuration.
Journal: International Journal of Production Research
Pages: 2862-2884
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1694719
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1694719
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:9:p:2862-2884




Template-Type: ReDIF-Article 1.0
Author-Name: Ke Wang
Author-X-Name-First: Ke
Author-X-Name-Last: Wang
Author-Name: Yan Yang
Author-X-Name-First: Yan
Author-X-Name-Last: Yang
Author-Name: Jian Zhou
Author-X-Name-First: Jian
Author-X-Name-Last: Zhou
Author-Name: Mark Goh
Author-X-Name-First: Mark
Author-X-Name-Last: Goh
Title: Fuzzy belief propagation in constrained Bayesian networks with application to maintenance decisions
Abstract: 
 Bayesian networks have been widely applied to domains such as medical diagnosis, fault analysis, and preventative maintenance. In some applications, because of insufficient data and the complexity of the system, fuzzy parameters and additional constraints derived from expert knowledge can be used to enhance the Bayesian reasoning process. However, very few methods are capable of handling the belief propagation in constrained fuzzy Bayesian networks (CFBNs). This paper therefore develops an improved approach which addresses the inference problem through a max-min programming model. The proposed approach yields more reasonable inference results and with less computational effort. By integrating the probabilistic inference drawn from diverse sources of information with decision analysis considering a decision-maker's risk preference, a CFBN-based decision framework is presented for seeking optimal maintenance decisions in a risk-based environment. The effectiveness of the proposed framework is validated based on an application to a gas compressor maintenance decision problem.
Journal: International Journal of Production Research
Pages: 2885-2903
Issue: 9
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2020.1715503
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1715503
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak
Abstract: 
 An intertwined supply network (ISN) is an entirety of interconnected supply chains (SC) which, in their integrity secure the provision of society and markets with goods and services. The ISNs are open systems with structural dynamics since the firms may exhibit multiple behaviours by changing the buyer-supplier roles in interconnected or even competing SCs. From the positions of resilience, the ISNs as a whole provide services to society (e.g. food service, mobility service or communication service) which are required to ensure a long-term survival. The analysis of survivability at the level of ISN requires a consideration at a large scale as resilience of individual SCs. The recent example of coronavirus COVID-19 outbreak clearly shows the necessity of this new perspective. Our study introduces a new angle in SC resilience research when a resistance to extraordinary disruptions needs to be considered at the scale of viability. We elaborate on the integrity of the ISN and viability. The contribution of our position study lies in a conceptualisation of a novel decision-making environment of ISN viability. We illustrate the viability formation through a dynamic game-theoretic modelling of a biological system that resembles the ISN. We discuss some future research areas.
Journal: International Journal of Production Research
Pages: 2904-2915
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2020.1750727
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1750727
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Template-Type: ReDIF-Article 1.0
Author-Name: György Kovács
Author-X-Name-First: György
Author-X-Name-Last: Kovács
Title: Combination of Lean value-oriented conception and facility layout design for even more significant efficiency improvement and cost reduction
Abstract: 
 Global market competition and fluctuating customers’ demands require manufacturing enterprises to focus on cost reduction and efficiency improvement to increase competitiveness and sustainability. The purpose of the research was the elaboration of the methodology and procedure of a new combined efficiency improvement method which basically applies Lean methods and also uses the facility layout design (FLD) method simultaneously, integrating the different advantages of these methods, which is even more efficient that applying each of the methods individually. The main significant added-value of the study is the elaboration of a new combined method, which results in even more significant improvement of efficiency and several KPIs, furthermore, cost reduction, which is confirmed by a real case study for the improvement of a manufacturing plant. In the case study, the application of 13 Lean methods and the FLD method (which aims at the minimisation of material workflow, travel distance of materials, material handling cost and space used for assembly) led to the improvement of 10 quantitative and 5 qualitative indicators: productivity; cycle-time; number of workstations and operators; WIP (work-in-process) inventories; space used for assembly; material workflow; travel distance of materials; material handling cost; labour cost; component supply; products’ quality; transparency; standardisation; workplace ergonomics.
Journal: International Journal of Production Research
Pages: 2916-2936
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2020.1712490
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1712490
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Template-Type: ReDIF-Article 1.0
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Nikolai Guschinsky
Author-X-Name-First: Nikolai
Author-X-Name-Last: Guschinsky
Title: Optimal cost design of flow lines with reconfigurable machines for batch production
Abstract: 
 Modular reconfigurable machines offer the possibility to efficiently produce a family of different parts. This paper formalises a cost optimisation problem for flow lines equipped with reconfigurable machines which carry turrets, machining modules and single spindles. The proposed models take into account constraints related to: (i) design of machining modules, turrets, and machines, (ii) part locations, and (iii) precedence relations among operations. The goal is to minimise equipment cost while reaching a given output and satisfying all the constraints. A mixed integer programming model is developed for the considered optimisation problem. The approach is validated through an industrial case study and extensive numerical experiments.
Journal: International Journal of Production Research
Pages: 2937-2952
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2020.1716092
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1716092
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Template-Type: ReDIF-Article 1.0
Author-Name: Jan Stentoft
Author-X-Name-First: Jan
Author-X-Name-Last: Stentoft
Author-Name: Christopher Rajkumar
Author-X-Name-First: Christopher
Author-X-Name-Last: Rajkumar
Title: The relevance of Industry 4.0 and its relationship with moving manufacturing out, back and staying at home
Abstract: 
 In view of the fact that Industry 4.0 is becoming increasingly essential, the implementation of Industry 4.0 technologies is believed to be an essential strategic component in further increasing the efficiency of manufacturing processes and in determining decisions concerning globalisation strategies. Thus, this paper provides an empirical analysis of the essential constructs of Industry 4.0, and drivers and barriers for Industry 4.0. The paper is based on 270 valid answers to a questionnaire-survey distributed among Danish manufacturers. Regression analyses were used to test the proposed hypotheses. The results of the analyses reveal that the identified drivers and barriers for Industry 4.0 have a positive impact on the perceived relevance of Industry 4.0 among companies. Furthermore, the analyses show that the perceived relevance of Industry 4.0 among companies has a positive impact on companies that have moved manufacturing back and on companies that have moved manufacturing out and back. Conversely, the perceived relevance of Industry 4.0 among companies has a negative impact on companies that have remained domestic. The perceived relevance of Industry 4.0 has no impact on companies that have moved manufacturing out. This research, in general, offers to both researchers and practitioners an increased consciousness concerning the relevant drivers and barriers for Industry 4.0 in decision processes about where to locate manufacturing.
Journal: International Journal of Production Research
Pages: 2953-2973
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1660823
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660823
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Template-Type: ReDIF-Article 1.0
Author-Name: Shokraneh K. Moghaddam
Author-X-Name-First: Shokraneh K.
Author-X-Name-Last: Moghaddam
Author-Name: Mahmoud Houshmand
Author-X-Name-First: Mahmoud
Author-X-Name-Last: Houshmand
Author-Name: Kazuhiro Saitou
Author-X-Name-First: Kazuhiro
Author-X-Name-Last: Saitou
Author-Name: Omid Fatahi Valilai
Author-X-Name-First: Omid
Author-X-Name-Last: Fatahi Valilai
Title: Configuration design of scalable reconfigurable manufacturing systems for part family
Abstract: 
 Intense global competition, dynamic product variations, and rapid technological developments force manufacturing systems to adapt and respond quickly to various changes in the market. Such responsiveness could be achieved through new paradigms such as Reconfigurable manufacturing systems (RMS). In this paper, the problem of configuration design for a scalable reconfigurable RMS that produces different products of a part family is addressed. In order to handle demand fluctuations of products throughout their lifecycles with minimum cost, RMS configurations must change as well. Two different approaches are developed for addressing the system configuration design in different periods. Both approaches make use of modular reconfigurable machine tools (RMTs), and adjust the production capacity of the system, with minimum cost, by adding/removing modules to/from specific RMTs. In the first approach, each production period is designed separately, while in the second approach, future information of products’ demands in all production periods is available in the beginning of system configuration design. Two new mixed integer linear programming (MILP) and integer linear programming (ILP) formulations are presented in the first and the second approaches respectively. The results of these approaches are compared with respect to many different aspects, such as total system design costs, unused capacity, and total number of reconfigurations. Analyses of the results show the superiority of both approaches in terms of exploitation and reconfiguration cost.
Journal: International Journal of Production Research
Pages: 2974-2996
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1620365
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1620365
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Template-Type: ReDIF-Article 1.0
Author-Name: Hengameh Hadian
Author-X-Name-First: Hengameh
Author-X-Name-Last: Hadian
Author-Name: S. Chahardoli
Author-X-Name-First: S.
Author-X-Name-Last: Chahardoli
Author-Name: Amir-Mohammad Golmohammadi
Author-X-Name-First: Amir-Mohammad
Author-X-Name-Last: Golmohammadi
Author-Name: Ali Mostafaeipour
Author-X-Name-First: Ali
Author-X-Name-Last: Mostafaeipour
Title: A practical framework for supplier selection decisions with an application to the automotive sector
Abstract: 
 One of the most strategic materials used in automotive industries is galvanised steel sheets, of which 50% to 85% of the weight of each car is made. However, these materials with the desired specification cannot be produced in Iran and must be outsourced to foreign providers. Therefore, outsourcing has become an indispensable part of Iranian automotive industries and a cooperative buyer-provider relationship is essential to survive and to acquire a reasonable profit. A recent approach in MCDM models is the BOCR analysis of Benefits, Opportunities, Costs, and Risks which evaluate both positive and negative aspects of each provider. However, due to the incommensurability among the composite priorities on the four merit factors, different synthesis approaches introduced in BOCR may offer different orderings of alternatives; which can be confusing for decision-makers to reach a final decision. On the other hand, the VIKOR method determines a compromise solution which is the closest to the ideal in the presence of conflicting and incommensurable criteria. This paper suggests integrated VIKOR-AHP-BOCR to select the best providers of galvanised steel sheets for IKCO that is the largest Iranian automaker. The proposed model and defined criteria can be used as a comprehensive guide by other companies for this purpose.
Journal: International Journal of Production Research
Pages: 2997-3014
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1624854
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1624854
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Template-Type: ReDIF-Article 1.0
Author-Name: Mingyao Sun
Author-X-Name-First: Mingyao
Author-X-Name-Last: Sun
Author-Name: Feng Wu
Author-X-Name-First: Feng
Author-X-Name-Last: Wu
Author-Name: Sisi Zhao
Author-X-Name-First: Sisi
Author-X-Name-Last: Zhao
Title: Machine diagnostic service centre design under imperfect diagnosis with uncertain error cost consideration
Abstract: 
 As modern machines are always highly customised, it is important to diagnose the specific maintenance requirement of each machine before performing regular maintenance tasks. However, the diagnosis cannot always be accurate. In this study, we focus on a diagnostic service design problem considering imperfect diagnosis with uncertain error cost, which increases in the inaccuracy of the diagnosis. The service system is modelled as a multiple server queue, with servers performing a sequential diagnosis and customers deciding whether or not to use the service. We consider the case where the expert skill level is exogenous, uncertain and endogenous, respectively. The results suggests that (1) when the expert skill level is exogenous, the congestion of the system increases in expert skill level. In addition, the error costs for the two major stakeholders-the service centre and the customer-may affect the optimal service time and number of experts in different ways; (2) when expert skill level becomes more uncertain, the service centre should improve the optimal service time further and will see a further erosion of the profit; and (3) different from the exogenous expert skill level, high skill level experts always accompany with long service time when expert skill level is endogenous.
Journal: International Journal of Production Research
Pages: 3015-3035
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1624855
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1624855
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Template-Type: ReDIF-Article 1.0
Author-Name: Dong-Yuh Yang
Author-X-Name-First: Dong-Yuh
Author-X-Name-Last: Yang
Author-Name: Yi-Hsuan Chen
Author-X-Name-First: Yi-Hsuan
Author-X-Name-Last: Chen
Author-Name: Chia-Huang Wu
Author-X-Name-First: Chia-Huang
Author-X-Name-Last: Wu
Title: Modelling and optimisation of a two-server queue with multiple vacations and working breakdowns
Abstract: 
 This paper presents a steady-state analysis of an M/M/2 queue with heterogeneous servers (Server 1 and Server 2). Server 1 is reliable and may leave for a vacation when the system becomes empty. Sever 2 is unreliable and may break down while serving customers. When a breakdown occurs, Server 2 reduces the service rate rather than halting service. We formulate this queueing model as a quasi birth-and-death (QBD) process, using the matrix geometric method to compute the stationary distribution of system size. We also develop several measures to evaluate the performance of the system. A cost model based on system performance measures is formulated as a heuristic cost optimisation problem subject to stability conditions. A canonical particle swarm optimisation algorithm is used to obtain numerical solutions for the approximate optimal service rates of Server 1 and Server 2. Moreover, we present numerical results showing the effects of various parameters on the approximate optimal service rates as well as a practical example illustrating the application of the proposed model.
Journal: International Journal of Production Research
Pages: 3036-3048
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1624856
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1624856
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Template-Type: ReDIF-Article 1.0
Author-Name: Daniel Y. Mo
Author-X-Name-First: Daniel Y.
Author-X-Name-Last: Mo
Author-Name: Yue Wang
Author-X-Name-First: Yue
Author-X-Name-Last: Wang
Author-Name: Lawrence C. Leung
Author-X-Name-First: Lawrence C.
Author-X-Name-Last: Leung
Author-Name: Mitchell M. Tseng
Author-X-Name-First: Mitchell M.
Author-X-Name-Last: Tseng
Title: Optimal service parts contract with multiple response times and on-site spare parts
Abstract: 
 This study examines user outsourcing of spare parts management to vendors through a service contract. The user’s selection of a fixed-price service parts contract is formulated as a stochastic integer programming model that decides multiple response times and on-site spare parts, while considering component breakdown with uncertain failure rates. We analytically derive the optimality conditions for the continuous case and subsequently design an efficient algorithm. Numerical illustrations and analyses are conducted to evaluate decisions under various scenarios. Our analysis shows that when both failure rate and expedited contract cost are high, coupled with low part cost, users would prefer the purchase of spare parts for all components to expedited contracts. A fixed-price expedited contract has a lower marginal cost with respect to failure rate than a fixed-price next day contract and a usage-based contract. We also examine inventory behaviour for a single part, multiple types of parts, and multiple groups of parts. It is shown that there is a cost-saving pooling effect in spare parts for identical items, which significantly raises the likelihood of having on-site stored parts. The problem becomes more complex for multiple items, reflecting bundling effects between items for a given contract.
Journal: International Journal of Production Research
Pages: 3049-3065
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1625487
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1625487
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohit Goswami
Author-X-Name-First: Mohit
Author-X-Name-Last: Goswami
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Title: A supplier performance evaluation framework using single and bi-objective DEA efficiency modelling approach: individual and cross-efficiency perspective
Abstract: 
 In view of complexities associated with supplier performance evaluation based on traditional business criterions (such as costs, quality levels, and delivery timelines) and emerging criterions (such as those related to environmental sustainability), we in this research evolve two different supplier efficiency measurement models that unify such criterions possessing characteristics of both desirable and undesirable outputs. The first model is a single-objective DEA efficiency assessment model wherein both types of outputs are integrated into a single composite efficiency measure. Using data from suppliers of Hyundai Steel Company, we determine composite efficiencies of each of these suppliers thus ranking them in terms of an overall efficiency score that would be useful as far as the first-cut supplier discrimination is concerned. However, due to the relative inability of evolved single-objective efficiency model to perform trade-offs amongst desirable and undesirable outputs and, owing to unidimensionality aspects, we evolve a goal programming based bi-objective efficiency model wherein trade-offs can be performed between both conventional and emerging dimensions criterions leading to different supplier evaluations for varied scenarios. We also integrate our evolved models with the cross-efficiency view of efficiency determination in order to enable the decision-makers to achieve peer-to-peer evaluation and maximum discrimination amongst suppliers.
Journal: International Journal of Production Research
Pages: 3066-3089
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1629665
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629665
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Template-Type: ReDIF-Article 1.0
Author-Name: Weimiao Liu
Author-X-Name-First: Weimiao
Author-X-Name-Last: Liu
Author-Name: Kanglin Liu
Author-X-Name-First: Kanglin
Author-X-Name-Last: Liu
Author-Name: Tianhu Deng
Author-X-Name-First: Tianhu
Author-X-Name-Last: Deng
Title: Modelling, analysis and improvement of an integrated chance-constrained model for level of repair analysis and spare parts supply control
Abstract: 
 In traditional practices, maintenance system and spare parts inventory control are usually considered in isolation, resulting in suboptimality. In a military system, the level of repair analysis (LORA) is often employed to help operate its repair networks. In this paper, we consider an integrated LORA and inventory control problem and formulate this problem as a mixed-integer nonlinear programming problem with chance constraints. Two second-order cone constraints are proposed to approximate the chance constraints. Furthermore, we propose an outer approximation (OA) algorithm based on the OA cuts. Extensive numerical results show that the OA algorithm significantly improves the computational efficiency under various types of components and network complexity. Next, we investigate the influence of service level and resource capacity, and propose the findings. Our results indicate that a higher service level leads to steeper costs, more resources, larger storage and heavier repair burdens at operating sites. Moreover, enhancements in resource capacity from the status quo lead to improvements in repairs and shrinkage in discards, bringing direct economic benefits. The insights extend to uncertain settings. It may be initially counterintuitive for many practitioners that demand uncertainty poses relatively subtle impacts.
Journal: International Journal of Production Research
Pages: 3090-3109
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1629669
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629669
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:10:p:3090-3109




Template-Type: ReDIF-Article 1.0
Author-Name: Kuen-Suan Chen
Author-X-Name-First: Kuen-Suan
Author-X-Name-Last: Chen
Author-Name: Tsang-Chuan Chang
Author-X-Name-First: Tsang-Chuan
Author-X-Name-Last: Chang
Title: Construction and fuzzy hypothesis testing of Taguchi Six Sigma quality index
Abstract: 
 By taking process targeting as well as process variability into consideration, the Taguchi capability index  ${C_{pm}} $Cpm gives a reasonable indication of process loss. This makes it an ideal tool for practical applications that depend on the evaluation of process quality. The ability of Six Sigma quality management to reduce process defect rates has led a number of researchers to investigate the relationship between  ${C_{pm}} $Cpm and Six Sigma quality levels. Unfortunately, previous efforts indicate the quality level using only a range, rather than a specific value. Our objective in this study was to develop a Taguchi Six Sigma quality index  ${Q_{pm}} $Qpm that retains the advantages of  ${C_{pm}} $Cpm in the assessment of process performance, while providing a specific value for the quality level associated with the process in question. To ensure rigorous quality assessments, we employed the upper confidence limit of  ${Q_{pm}} $Qpm in the design of a testing model for use by manufacturers. Fuzziness and stochastic uncertainty are unavoidable aspects of data collection. We, therefore, adopted a right half triangular-shaped fuzzy number for  ${\hat{Q}_{pm}} $Qˆpm to deal with imprecise data. We also developed a method of the fuzzy hypothesis testing for  ${Q_{pm}} $Qpm to make reliable decisions for process quality assessment.
Journal: International Journal of Production Research
Pages: 3110-3125
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1629671
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1629671
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Template-Type: ReDIF-Article 1.0
Author-Name: Supun Perera
Author-X-Name-First: Supun
Author-X-Name-Last: Perera
Author-Name: Dharshana Kasthurirathna
Author-X-Name-First: Dharshana
Author-X-Name-Last: Kasthurirathna
Author-Name: Michael Bell
Author-X-Name-First: Michael
Author-X-Name-Last: Bell
Author-Name: Michiel Bliemer
Author-X-Name-First: Michiel
Author-X-Name-Last: Bliemer
Title: Topological rationality of supply chain networks
Abstract: 
 In this study, we apply a topologically distributed bounded rationality model to quantify the level of rationality in supply chain networks. We use the averaged Jensen-Shannon divergence values between Nash and Quantal Response equilibria for all inter-firm strategic interactions, which are represented as Prisoner’s Dilemma games, to characterise the average level of rationality in a given supply chain network. This is based on the game theoretic assumption that as the rationality of a particular interaction increases, it converges towards Nash equilibrium, in a certain strategic decision making scenario. Using this model, we demonstrate that hub-and-spoke topologies are collectively more rational compared to scale-free and random network topologies. Finally, we compare our theoretical results against the empirical findings reported for networked systems in various domains. In particular, it is shown that network topologies comprising higher average rationality levels emerge under increasingly competitive environments.
Journal: International Journal of Production Research
Pages: 3126-3149
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1630763
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630763
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhi Chen
Author-X-Name-First: Zhi
Author-X-Name-Last: Chen
Author-Name: Erik Demeulemeester
Author-X-Name-First: Erik
Author-X-Name-Last: Demeulemeester
Author-Name: Sijun Bai
Author-X-Name-First: Sijun
Author-X-Name-Last: Bai
Author-Name: Yuntao Guo
Author-X-Name-First: Yuntao
Author-X-Name-Last: Guo
Title: A Bayesian approach to set the tolerance limits for a statistical project control method
Abstract: 
 In this paper, we address the project schedule control problem under an uncertain environment. We propose a new method to set the tolerance limits based on the Earned Value Management/Earned Schedule (EVM/ES) schedule performance metrics. These tolerance limits can help a project manager to identify whether the schedule deviations from the baseline schedule are within the possible deviations derived from the expected variability of the project or if corrective actions must be taken to get the project back on track. We view the project control problem as a statistical hypothesis test with the null hypothesis being that the project progress is out of control. First, a simulation is performed to generate two types of empirical conditional distributions of the monitored schedule indicator. Afterwards, an algorithm that uses the derived conditional distributions as inputs is proposed to optimise the tolerance limits. An extensive computational experiment is carried out to assess the performance of the proposed approach. Additionally, sensitivity experiments are conducted to analyse four underlying factors that may influence the power of the proposed method. Experimental results show that our approach can keep the first type error under the required level ( $\alpha = 0.05 $α=0.05) in any situation, meanwhile reducing the second type error significantly compared with three other methods in the literature.
Journal: International Journal of Production Research
Pages: 3150-3163
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1630766
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630766
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Template-Type: ReDIF-Article 1.0
Author-Name: Mainara Cristina Lorencena
Author-X-Name-First: Mainara Cristina
Author-X-Name-Last: Lorencena
Author-Name: Luiz Fernando Puttow Southier
Author-X-Name-First: Luiz Fernando Puttow
Author-X-Name-Last: Southier
Author-Name: Dalcimar Casanova
Author-X-Name-First: Dalcimar
Author-X-Name-Last: Casanova
Author-Name: Richardson Ribeiro
Author-X-Name-First: Richardson
Author-X-Name-Last: Ribeiro
Author-Name: Marcelo Teixeira
Author-X-Name-First: Marcelo
Author-X-Name-Last: Teixeira
Title: A framework for modelling, control and supervision of poultry farming
Abstract: 
 Thermal comfort is a decisive factor in broiler chicken production, as it defines the relationship between food consumption and meat production. Temperature and humidity are major parameters for thermal balance. In spite of available automation technology, poultry farming is still dependent on an expert to observe the process and set up control parameters accordingly. Besides being inefficient, this is also uncomfortable and error-prone. This article proposes a framework for control, supervision, and decision-making in poultry farming. We initially set up a plant architecture that enables us to take advantage of emerging modern technologies, such as sensor networks, control theory, and remote monitoring, to handle temperature and humidity inside a poultry house. Then, we present the steps of modelling, synthesis, and implementation of a controller that observes events in the plant and commands the actuators in a minimally restrictive, controllable and non-blocking way, while complying with a set of operational requirements. Our final result provides a dual-channel web-based supervision system that shows the process status remotely for users and allows them to interfere with control, whenever convenient.
Journal: International Journal of Production Research
Pages: 3164-3179
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1630768
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630768
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Template-Type: ReDIF-Article 1.0
Author-Name: Nuno O. Fernandes
Author-X-Name-First: Nuno O.
Author-X-Name-Last: Fernandes
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Tatiana M. Pinho
Author-X-Name-First: Tatiana M.
Author-X-Name-Last: Pinho
Author-Name: Pedro Torres
Author-X-Name-First: Pedro
Author-X-Name-Last: Torres
Author-Name: Sílvio Carmo-Silva
Author-X-Name-First: Sílvio
Author-X-Name-Last: Carmo-Silva
Title: Workload control and optimised order release: an assessment by simulation
Abstract: 
 An important scheduling function of manufacturing systems is controlled order release. While there exists a broad literature on order release, reported release procedures typically use simple sequencing rules and greedy heuristics to determine which jobs to select for release. While this is appealing due to its simplicity, its adequateness has recently been questioned. In response, this study uses an integer linear programming model to select orders for release to the shop floor. Using simulation, we show that optimisation has the potential to improve performance compared to ‘classical’ release based on pool sequencing rules. However, in order to also outperform more powerful pool sequencing rules, load balancing and timing must be considered at release. Existing optimisation-based release methods emphasise load balancing in periods when jobs are on time. In line with recent advances in Workload Control theory, we show that a better percentage tardy performance can be achieved by only emphasising load balancing when many jobs are urgent. However, counterintuitively, emphasising urgency in underload periods leads to higher mean tardiness. Compared to previous literature we further highlight that continuous optimisation-based release outperforms periodic optimisation-based release. This has important implications on how optimised-based release should be designed.
Journal: International Journal of Production Research
Pages: 3180-3193
Issue: 10
Volume: 58
Year: 2020
Month: 5
X-DOI: 10.1080/00207543.2019.1630769
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630769
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Title: The use of finite loading to guide short-term capacity adjustments in make-to-order job shops: an assessment by simulation
Abstract: 
 Although there is a broad literature on capacity management, there has been only limited attention on how to support short-term capacity control decisions, especially in high-variety make-to-order shops. While finite loading has been identified as a potential means of guiding capacity adjustments, the actual performance impact of this solution has not been adequately assessed. Using a simulation model of a make-to-order job shop, we compare the performance impact of four different forward and backward finite loading methods and a load trigger method recently presented in the literature. Results confirm the potential of finite loading to improve performance when compared to a general capacity increase. Yet all four methods are outperformed by the load trigger method. The capacity adjustments made under finite loading methods are determined by individual jobs and their properties. This may lead to no adjustments despite an overload period (e.g. if a job has a long due date but only one overload station in its routing) or to unnecessary adjustments when there is no overload (e.g. if a large job has a tight due date). This finding draws into question the use of finite loading altogether and reinforces the importance of the load trigger method.
Journal: International Journal of Production Research
Pages: 3554-3569
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1630771
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630771
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:12:p:3554-3569




Template-Type: ReDIF-Article 1.0
Author-Name: M. Assid
Author-X-Name-First: M.
Author-X-Name-Last: Assid
Author-Name: A. Gharbi
Author-X-Name-First: A.
Author-X-Name-Last: Gharbi
Author-Name: A. Hajji
Author-X-Name-First: A.
Author-X-Name-Last: Hajji
Title: Production and subcontracting control for an unreliable manufacturing system with setups
Abstract: 
 This paper deals with the problem of joint production, setup and subcontracting control of unreliable manufacturing systems producing two product types. The production requires setups each time it switches from one product type to another. Subcontracting is an integral part of the decision-making process due to limited production capacity in existing facility. The objective is to propose an effective control policy for the considered system which simultaneously manages production, setup and subcontracting activities. The complexity of the problem lies in the interaction between internal manufacturing decisions and subcontracting that outsource a part of the production, in a dynamic and stochastic environment. An experimental optimisation approach is adopted to determine the optimal control parameters which minimise the average total cost. Extensive sensitivity analyses are performed to illustrate the robustness and the usefulness of the adopted approach. An in-depth study comparing five control policies across a wide range of system parameters is also conducted. Extended cases closer to reality are also investigated considering elements such as the preventive maintenance and the production of non-conforming products. The best control policy in terms of economic performance is then obtained. Valuable insights providing a better understanding of interactions involving production, setup, and subcontracting are discussed.
Journal: International Journal of Production Research
Pages: 3570-3588
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1630776
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630776
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Template-Type: ReDIF-Article 1.0
Author-Name: Yahui Zhang
Author-X-Name-First: Yahui
Author-X-Name-Last: Zhang
Author-Name: Xiaofeng Hu
Author-X-Name-First: Xiaofeng
Author-X-Name-Last: Hu
Author-Name: Chuanxun Wu
Author-X-Name-First: Chuanxun
Author-X-Name-Last: Wu
Title: Improved imperialist competitive algorithms for rebalancing multi-objective two-sided assembly lines with space and resource constraints
Abstract: 
 In this paper, a mathematical model and an improved imperial competition algorithm (IICA) are proposed to solve the multi-objective two-sided assembly line rebalancing problem with space and resource restrictions (MTALRBP-SR). The aim is to find lines’ rebalance with the trade-off between efficiency, rebalancing cost and smoothing after reconfiguration. IICA utilises a new initialisation heuristic procedure based on classic heuristic rules to generate feasible initial solutions. A novel heuristic assimilation method is developed to vigorously conduct local search. In addition, a group-based decoding heuristic procedure is developed to fulfil the final task reassignment with the additional restrictions. To investigate the performance of the proposed algorithm, it is first tested on MTALRBP of benchmark problems and compared with some existing algorithms such as genetic algorithm, variable neighbourhood search algorithm, discrete artificial bee colony algorithm, and two iterated greedy algorithms. Next, the efficiency of the proposed IICA for solving MTALRBP-SR is revealed by comparison with a non-dominated sorting genetic algorithm (NSGA-II) and two versions of original ICA. Computational results and comparisons show the efficiency and effectiveness of IICA. Furthermore, a real-world case study is conducted to validate the proposed algorithm.
Journal: International Journal of Production Research
Pages: 3589-3617
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1633023
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1633023
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Template-Type: ReDIF-Article 1.0
Author-Name: Tulika Chakraborty
Author-X-Name-First: Tulika
Author-X-Name-Last: Chakraborty
Author-Name: Satyaveer S. Chauhan
Author-X-Name-First: Satyaveer S.
Author-X-Name-Last: Chauhan
Author-Name: Mustapha Ouhimmou
Author-X-Name-First: Mustapha
Author-X-Name-Last: Ouhimmou
Title: Mitigating supply disruption with a backup supplier under uncertain demand: competition vs. cooperation
Abstract: 
 In case of supply disruption following major disasters, many supply chains tend to break down due to stock-outs and take a long time to recover. However, by keeping emergency sources of supply, some supply chains continue to function smoothly even after a major disaster. In this work, using a game-theoretic-framework, we consider a two-suppliers-one-retailer supply chain with price-dependent stochastic demand in which suppliers are prone to disruption. To investigate the impact of supply disruption we consider two models: SC model, in which the retailer does not maintain any emergency sources of supply against any supply disruption, and SCB model, in which the retailer maintains a backup supplier to mitigate the impact of supply disruption. We mainly focus on the pricing strategies of the suppliers and the mitigating strategies of the retailer under supply and demand uncertainty. We address two coordinating mechanisms to enhance supply chain performance. Our results indicate that in the presence of supply disruption, even with lower probabilities, the retailer would always prefer to take the advantage of a backup supplier and the optimal reserve quantity increases with disruption probabilities. We further investigate the scenario in which the suppliers would always prefer to cooperate with each other.
Journal: International Journal of Production Research
Pages: 3618-3649
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1633025
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1633025
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Template-Type: ReDIF-Article 1.0
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme Luz
Author-X-Name-Last: Tortorella
Author-Name: Diego Fettermann
Author-X-Name-First: Diego
Author-X-Name-Last: Fettermann
Author-Name: Paulo A. Cauchick Miguel
Author-X-Name-First: Paulo A.
Author-X-Name-Last: Cauchick Miguel
Author-Name: Rapinder Sawhney
Author-X-Name-First: Rapinder
Author-X-Name-Last: Sawhney
Title: Learning organisation and lean production: an empirical research on their relationship
Abstract: 
 This study aims at identifying the pairwise relationship between specific sets of Lean Production (LP) practices and Learning Organisation (LO) dimensions. More specifically, the association between 10 LP operational constructs and seven LO dimensions, based upon previous literature, is empirically examined. A survey-based study was carried out with 135 companies undergoing a LP implementation. The study sample was categorised according to two control variables: type of organisation and company’s LP implementation experience. Collected data was analysed through multivariate techniques. Results indicate that LP implementation and LO development are highly correlated. Additionally, findings also show that the extent of relationships varies according to the context, allowing the identification of synergistic associations and conflicting ones. The identification of these relationships provides means to better comprehend how the implementation of specific LP practices corroborates to enhancing LO capabilities within the organisation and vice-versa.
Journal: International Journal of Production Research
Pages: 3650-3666
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1633028
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1633028
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Template-Type: ReDIF-Article 1.0
Author-Name: Jaouad Abisourour
Author-X-Name-First: Jaouad
Author-X-Name-Last: Abisourour
Author-Name: Mohsine Hachkar
Author-X-Name-First: Mohsine
Author-X-Name-Last: Hachkar
Author-Name: Badia Mounir
Author-X-Name-First: Badia
Author-X-Name-Last: Mounir
Author-Name: Abdelmajid Farchi
Author-X-Name-First: Abdelmajid
Author-X-Name-Last: Farchi
Title: Methodology for integrated management system improvement: combining costs deployment and value stream mapping
Abstract: 
 Integrated Management System – Quality, Environment, Safety (IMS-QES) combines all related components of a business into one system for easier management and operations Quality (QMS/ISO 9001), Environmental (EMS/ISO 14001), and Health & Safety (OHSAS 18001). IMS-QES has been generally used to increase operational performance in manufacturing systems. However, the economic impact of standard approach of IMS-QES remains difficult due to the lack of alignment between IMS-QES objectives and strategic management of the company (policy of IMS-QES) and also the inadequacy between the improvement processes and the cost of losses.Therefore, the main objective of this work is to overcome this limitation. The Framework proposed approach called IM-VCF integrates concepts from IMS-QES, Value Stream Mapping and Cost Deployment tool. It is structured in ten steps. It allows a company to assure proper alignment between IMS-QES policy and business operations and identify the categories of losses. IM-VCF allows analysing critical issues and estimating the potential savings, in terms of cost. A case study taken from the application of the IM-VSF within certified QSE chemical fertiliser port is presented.
Journal: International Journal of Production Research
Pages: 3667-3685
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1633482
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1633482
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Template-Type: ReDIF-Article 1.0
Author-Name: Junfei Chu
Author-X-Name-First: Junfei
Author-X-Name-Last: Chu
Author-Name: Jie Wu
Author-X-Name-First: Jie
Author-X-Name-Last: Wu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Title: A new DEA common-weight multi-criteria decision-making approach for technology selection
Abstract: 
 This paper addresses an advanced manufacturing technology selection problem by proposing a new common-weight multi-criteria decision-making (MCDM) approach in the evaluation framework of data envelopment analysis (DEA). We improve existing technology selection models by giving a new mathematical formulation to simplify the calculation process and to ensure its use in more general situations with multiple inputs and multiple outputs. Further, an algorithm is provided to solve the proposed model based on mixed-integer linear programming and dichotomy. Compared with previous approaches for technology selection, our approach brings new contributions. First, it guarantees that only one decision-making unit (DMU) (referring to a technology) can be evaluated as efficient and selected as the best performer while maximising the minimum efficiency among all the DMUs. Second, the number of mixed-integer linear programs to solve is independent of the number of candidates. In addition, it guarantees the uniqueness of the final optimal set of common weights. Two benchmark instances are used to compare the proposed approach with existing ones. A computational experiment with randomly generated instances is further proceeded to show that the proposed approach is more suitable for situations with large datasets.
Journal: International Journal of Production Research
Pages: 3686-3700
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1634294
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634294
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Template-Type: ReDIF-Article 1.0
Author-Name: Haizhu Zhang
Author-X-Name-First: Haizhu
Author-X-Name-Last: Zhang
Author-Name: Shengfeng Qin
Author-X-Name-First: Shengfeng
Author-X-Name-Last: Qin
Author-Name: Rong Li
Author-X-Name-First: Rong
Author-X-Name-Last: Li
Author-Name: Yisheng Zou
Author-X-Name-First: Yisheng
Author-X-Name-Last: Zou
Author-Name: Guofu Ding
Author-X-Name-First: Guofu
Author-X-Name-Last: Ding
Title: Progressive modelling of feature-centred product family development
Abstract: 
 Modelling a product family is critical for understanding the evolution of key design and manufacturing features associated with products in the product through-life development. This research aims to establish a model for the holistic description of the evolution process of a product family to support rapid development of new products with hybrid innovations. In this study, a new broader definition of the product family is proposed for products on cross-platforms but in the same class or category, called feature-centred product family. A progressive modelling of feature-centred product family is developed for progressively addressing the evolution of products and achieving the dynamic expression of a product family. A prototype system has been developed and tested with an industrial case study, which indicates that the proposed new feature-centred product family concept and progressive modelling method are not only supportive to realise the common and adaptive analysis of key design features but also helpful to improve the design and production efficiency of innovative products with knowledge and feature reuse.
Journal: International Journal of Production Research
Pages: 3701-3723
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1634295
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634295
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Template-Type: ReDIF-Article 1.0
Author-Name: Stefan Haeussler
Author-X-Name-First: Stefan
Author-X-Name-Last: Haeussler
Author-Name: Pia Netzer
Author-X-Name-First: Pia
Author-X-Name-Last: Netzer
Title: Comparison between rule- and optimization-based workload control concepts: a simulation optimization approach
Abstract: 
 An important goal of Production Planning and Control systems is to achieve short and predictable flow times, especially where high flexibility in meeting customer demand is required, while maintaining high output and due-date performance. One approach to this problem is the workload control (WLC) concept. Within WLC research two directions have been developed, largely separately, over time: Rule based and optimisation-based models. If a company intends to introduce an order release concept based on WLC it first has to decide which of these two approaches should be applied. Therefore, this paper compares two of the most widely used and considered best performing periodic order release models out of both streams: the LUMS (rule based) and the clearing function model (optimisation based). The parameters of both approaches are set using simulation optimisation. The performance is compared using a simulation study of a hypothetical job shop in a rolling horizon setting. The results show that the optimisation model outperforms the rule-based mechanism in all instances with stochastic demand (exponential inter-arrival times), but is outperformed in aggregate cost of backorders and inventory holding and balancing measures by the LUMS approach for scenarios with high utilisation and seasonal demand.
Journal: International Journal of Production Research
Pages: 3724-3743
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1634297
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634297
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Template-Type: ReDIF-Article 1.0
Author-Name: Wuhua Chen
Author-X-Name-First: Wuhua
Author-X-Name-Last: Chen
Author-Name: Zhe George Zhang
Author-X-Name-First: Zhe George
Author-X-Name-Last: Zhang
Author-Name: Xiaohong Chen
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Chen
Title: On two-tier healthcare system under capacity constraint
Abstract: 
 In the healthcare industry, to reduce the waiting time for patients, policy makers may allow private hospitals (or called the toll system) to enter the market. However, when the total healthcare capacity in the market is limited (e.g. the number of medical staff or equipment is limited), the entrance of the toll system may offer higher salaries to attract medical staff from public hospitals (or called the free system) and reduce its capacity. Then whether or not introducing toll system in the system can reduce the waiting time becomes an issue. In this paper, we investigate the impact of capacity constraint on a two-tier healthcare system. The results show that when the total capacity is tight enough, the two-tier healthcare system often yields less social welfare than the one-tier free system; and when the total capacity is sufficient (the demand does not exceed the total capacity), the two-tier healthcare system improves the social welfare. Specially, we find under certain conditions the capacity constraint can improve social welfare. In addition, if the capacity constraint has a negative effect on the two-tier system’s performance, the government can set an appropriate upper limit for the toll system’s capacity to remove the negative effect.
Journal: International Journal of Production Research
Pages: 3744-3764
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1634846
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634846
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Reza Rasouli
Author-X-Name-First: Mohammad Reza
Author-X-Name-Last: Rasouli
Title: An architecture for IoT-enabled intelligent process-aware cloud production platform: a case study in a networked cloud clinical laboratory
Abstract: 
 Cloud production is an emerging paradigm that supports co-designing and co-producing integrated solutions with customers. The realisation of this paradigm requires integrated platforms that enable parties collaborating within a production ecosystem to inter-operate networked business processes. Previous research has proposed different architectures for cloud production platforms from different perspectives like virtualiseng and servitiseng manufacturing resources, distributed and networked sensing supported by IoT technologies, and service-oriented and process-centred computing to compose and enact networked production services. However, an integrated architecture that brings together insights from service-oriented cloud manufacturing, IoT-enabled intelligence, and networked process-centred service composition and enactment has not been sufficiently addressed in previous research. In order to incorporate insights from the mentioned different perspectives, in this paper architectural analysis, synthesis, and evaluation steps are conducted to propose a conceptual architecture for IoT-enabled intelligent process-aware cloud production platforms. This architecture describes design-time and run-time components of a cloud production platform that can sense and intelligently respond to events within a value network. To evaluate the applicability of the proposed architecture within real-life scenarios, a case study is conducted in a cloud clinical laboratory in Tehran, Iran. Within this case study, a concrete cloud clinical laboratory platform has been instantiated.
Journal: International Journal of Production Research
Pages: 3765-3780
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1634847
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634847
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Template-Type: ReDIF-Article 1.0
Author-Name: Guiliang Gong
Author-X-Name-First: Guiliang
Author-X-Name-Last: Gong
Author-Name: Qianwang Deng
Author-X-Name-First: Qianwang
Author-X-Name-Last: Deng
Author-Name: Raymond Chiong
Author-X-Name-First: Raymond
Author-X-Name-Last: Chiong
Author-Name: Xuran Gong
Author-X-Name-First: Xuran
Author-X-Name-Last: Gong
Author-Name: Hezhiyuan Huang
Author-X-Name-First: Hezhiyuan
Author-X-Name-Last: Huang
Author-Name: Wenwu Han
Author-X-Name-First: Wenwu
Author-X-Name-Last: Han
Title: Remanufacturing-oriented process planning and scheduling: mathematical modelling and evolutionary optimisation
Abstract: 
 Remanufacturing has been widely studied for its potential to achieve sustainable production in recent years. In the literature of remanufacturing research, process planning and scheduling are typically treated as two independent parts. However, these two parts are in fact interrelated and often interact with each other. Doing process planning without considering scheduling related factors can easily introduce contradictions or even infeasible solutions. In this work, we propose a mathematical model of integrated process planning and scheduling for remanufacturing (IPPSR), which simultaneously considers the process planning and scheduling problems. An effective hybrid multi-objective evolutionary algorithm (HMEA) is presented to solve the proposed IPPSR. For the HMEA, a multidimensional encoding operator is designed to get a high-quality initial population. A multidimensional crossover operator and a multidimensional mutation operator are also proposed to improve the convergence speed of the algorithm and fully exploit the solution space. Finally, a specific legalising method is used to ‘legalise’ possible infeasible solutions generated by the initialisation method and mutation operator. Extensive computational experiments carried out to compare the HMEA with some well-known algorithms confirm that the proposed HMEA is able to obtain more and better Pareto solutions for IPPSR.
Journal: International Journal of Production Research
Pages: 3781-3799
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1634848
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634848
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:12:p:3781-3799




Template-Type: ReDIF-Article 1.0
Author-Name: Francisco Campuzano-Bolarín
Author-X-Name-First: Francisco
Author-X-Name-Last: Campuzano-Bolarín
Author-Name: Josefa Mula
Author-X-Name-First: Josefa
Author-X-Name-Last: Mula
Author-Name: Manuel Díaz-Madroñero
Author-X-Name-First: Manuel
Author-X-Name-Last: Díaz-Madroñero
Author-Name: Álvar-Ginés Legaz-Aparicio
Author-X-Name-First: Álvar-Ginés
Author-X-Name-Last: Legaz-Aparicio
Title: A rolling horizon simulation approach for managing demand with lead time variability
Abstract: 
 This paper proposes a rolling horizon (RH) approach to deal with management problems under dynamic demand in planning horizons with variable lead times using system dynamics (SD) simulation. Thus, the nature of dynamic RH solutions entails no inconveniences to contemplate planning horizons with unpredictable demands. This is mainly because information is periodically updated and replanning is done in time. Therefore, inventory and logistic costs may be lower. For the first time, an RH is applied for demand management with variable lead times along with SD simulation models, which allowed the use of lot-sizing techniques to be evaluated (Wagner-Whitin and Silver-Meal). The basic scenario is based on a real-world example from an automotive single-level SC composed of a first-tier supplier and a car assembler that contemplates uncertain demands while planning the RH and 216 subscenarios by modifying constant and variable lead times, holding costs and order costs, combined with lot-sizing techniques. Twenty-eight more replications comprising 504 new subscenarios with variable lead times are generated to represent a relative variation coefficient of the initial demand. We conclude that our RH simulation approach, along with lot-sizing techniques, can generate more sustainable planning results in total costs, fill rates and bullwhip effect terms.
Journal: International Journal of Production Research
Pages: 3800-3820
Issue: 12
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1634849
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634849
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Template-Type: ReDIF-Article 1.0
Author-Name: Ömer Faruk Yılmaz
Author-X-Name-First: Ömer Faruk
Author-X-Name-Last: Yılmaz
Title: Operational strategies for seru production system: a bi-objective optimisation model and solution methods
Abstract: 
 In recent years, the interest in seru production system (SPS) has increased to enhance the flexibility of production systems. Because the worker resource in an SPS is critical for adapting to changes in demand, this study focuses on workforce-related operational strategies rarely considered for SPS. To this end, for the first time in the literature, a bi-objective workforce scheduling problem is addressed by considering the interseru worker transfer in SPS. A novel optimisation model is proposed to achieve two objectives, that of minimising makespan and reducing workload imbalance among workers. Because it is proved that the problem falls within a non-deterministic polynomial-time hardness (NP-hard) class, non-dominated sorting genetic algorithm-II (NSGA-II) is employed to solve large-sized problems. For small-sized problems, the second version of the augmented ε-constrained (AUGMECON2) method is implemented and Pareto-optimal solutions are obtained. A set of evaluation metrics is considered to compare two different operational strategies in terms of the desired objectives. The computational results indicate that allowing worker transfer leads to better results for all metrics. The main contribution of the present study is to provide a novel optimisation model for the addressed problem to compare two operational strategies by considering the heterogeneity inherent of workers.
Journal: International Journal of Production Research
Pages: 3195-3219
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1669841
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1669841
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3195-3219




Template-Type: ReDIF-Article 1.0
Author-Name: Zixiang Li
Author-X-Name-First: Zixiang
Author-X-Name-Last: Li
Author-Name: Zeynel Abidin Çil
Author-X-Name-First: Zeynel Abidin
Author-X-Name-Last: Çil
Author-Name: Süleyman Mete
Author-X-Name-First: Süleyman
Author-X-Name-Last: Mete
Author-Name: Ibrahim Kucukkoc
Author-X-Name-First: Ibrahim
Author-X-Name-Last: Kucukkoc
Title: A fast branch, bound and remember algorithm for disassembly line balancing problem
Abstract: 
 In recent years, the interests of disassembly line have increased owing to economic reasons and the increase of environmental awareness. Effective line can provide many advantages in terms of economic aspect and it facilitates competition the companies with others. This study contributes to the relevant literature by a branch, bound and remember algorithm for disassembly line balancing problem with AND/OR precedence. The proposed exact solution method employs the memory-based dominance rule to eliminate the reduplicated sub-problems by storing all the searched sub-problems and to utilise cyclic best-first search strategy to obtain high-quality complete solutions fast. In this paper, minimising the number of stations is taken as the performance measure. The proposed methodology is tested on a set of 260 instances and compared with the mathematical model using CPLEX solver and five well-known metaheuristics. Computational results show that the proposed method is capable of obtaining the optimal solutions for all the tested instances with less than 0.1 seconds on average. Additionally, comparative study demonstrates that the proposed method is the state-of-the-art algorithm and outperforms the CPLEX solver and metaheuristics in terms of both solution quality and search speed aspects.
Journal: International Journal of Production Research
Pages: 3220-3234
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1630774
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630774
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Template-Type: ReDIF-Article 1.0
Author-Name: Honghan Ye
Author-X-Name-First: Honghan
Author-X-Name-Last: Ye
Author-Name: Wei Li
Author-X-Name-First: Wei
Author-X-Name-Last: Li
Author-Name: Barrie R. Nault
Author-X-Name-First: Barrie R.
Author-X-Name-Last: Nault
Title: Trade-off balancing between maximum and total completion times for no-wait flow shop production
Abstract: 
 We propose a trade-off balancing (TOB) heuristic in a no-wait flow shop to minimise the weighted sum of maximum completion time ( $C_{\max } $Cmax) and total completion time (TCT) based on machine idle times. We introduce a factorisation scheme to construct the initial sequence based on current and future idle times at the operational level. In addition, we propose a novel estimation method to establish the mathematical relationship between the objectives min( $C_{\max } $Cmax) and min(TCT) at the production line level. To evaluate the performance of the TOB heuristic, computational experiments are conducted on the classic Taillard's benchmark and one-year historical data from University of Kentucky HealthCare (UKHC). The computational results show that minimisations of  $C_{\max } $Cmax and TCT yield inconsistent scheduling sequences, and these two sequences are relatively uncorrelated. We also show that our TOB heuristic performs better than the best existing heuristics with the same computational complexity and generates stable performances in balancing trade-offs.
Journal: International Journal of Production Research
Pages: 3235-3251
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1630777
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1630777
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3235-3251




Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: ‘A blessing in disguise’ or ‘as if it wasn’t hard enough already’: reciprocal and aggravate vulnerabilities in the supply chain
Abstract: 
 We investigate the interrelations of structural and operational vulnerabilities in the supply chain (SC) using discrete-event simulation for a real life case study. We theorise a notion of SC overlays and explore conditions surrounding their appearance. Such overlays occur if the negative consequences of changes in a SC structure as a result of a disruption are either amplified or mitigated by changes in the operational environment. We hypothesise that these overlays can be both reciprocal (i.e. complementary or mitigating) and aggravate (i.e. concurrent or enhancing). Our approach can be used for an efficient management of SC resilience capabilities by varying their levels over time. We show different ripple and bullwhip effect profiles, which lead to either reciprocal or aggravate overlays, and then we develop recommendations on the overlay-driven dynamic variation of resilience capability levels in order to enhance both SC resilience and efficiency through dynamic redundancy allocation. The results can be of value in selecting and deploying operational policies at the right time and scale during and after the recovery periods. Restricting analysis to the disruption period only and ignoring operational dynamics after capacity recovery can result in misleading or inefficient SC resilience and recovery policies.
Journal: International Journal of Production Research
Pages: 3252-3262
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1634850
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634850
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Template-Type: ReDIF-Article 1.0
Author-Name: Maroua Nouiri
Author-X-Name-First: Maroua
Author-X-Name-Last: Nouiri
Author-Name: Abdelghani Bekrar
Author-X-Name-First: Abdelghani
Author-X-Name-Last: Bekrar
Author-Name: Damien Trentesaux
Author-X-Name-First: Damien
Author-X-Name-Last: Trentesaux
Title: An energy-efficient scheduling and rescheduling method for production and logistics systems†
Abstract: 
 Scheduling can be defined as the allocation of available resources over time while optimising a set of criteria like early completion time of task, holding inventory, etc. The complexity of the scheduling problem, already known to be high, increases if dynamic events and disruptions are considered. In addition, in production and logistics, designers of scheduling systems must consider sustainability-related expectations. This paper presents an energy-efficient scheduling and rescheduling method (named Green Rescheduling Method, GRM). GRM aims at the solving of the dynamic scheduling problem under the condition of a certain level of routing flexibility enabling the reassignment of tasks to new resources. The key performance indicators integrated into the proposed GRM are effectiveness and efficiency-oriented. Applications concern the domains of production and logistics. In order to assess the proposed approach, experimentations have been made and results illustrate the applicability of GRM to build efficient and effective scheduling and rescheduling both for flexible manufacturing systems and inventory distribution systems in a physical internet network. A mathematical formulation for flexible job shop problem with energy consumption is also proposed using mixed Integer programming to evaluate the performance of the predictive part of GRM.
Journal: International Journal of Production Research
Pages: 3263-3283
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1660826
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660826
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3263-3283




Template-Type: ReDIF-Article 1.0
Author-Name: Seyedmohsen Hosseini
Author-X-Name-First: Seyedmohsen
Author-X-Name-Last: Hosseini
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Ripple effect modelling of supplier disruption: integrated Markov chain and dynamic Bayesian network approach
Abstract: 
 The ripple effect can occur when a supplier base disruption cannot be localised and consequently propagates downstream the supply chain (SC), adversely affecting performance. While stress-testing of SC designs and assessment of their vulnerability to disruptions in a single-echelon-single-event setting is desirable and indeed critical for some firms, modelling the ripple effect impact in multi-echelon-correlated-events systems is becoming increasingly important. Notably, ripple effect assessment in multi-stage SCs is particularly challenged by the need to consider both vulnerability and recoverability capabilities at individual firms in the network. We construct a new model based on integration of Discrete-Time Markov Chain (DTMC) and a Dynamic Bayesian Network (DBN) to quantify the ripple effect. We use the DTMC to model the recovery and vulnerability of suppliers. The proposed DTMC model is then equalised with a DBN model in order to simulate the propagation behaviour of supplier disruption in the SC. Finally, we propose a metric that quantifies the ripple effect of supplier disruption on manufacturers in terms of total expected utility and service level. This ripple effect metric is applied to two case studies and analysed. The findings suggest that our model can be of value in uncovering latent high-risk paths in the SC, analysing the performance impact of both a disruption and its propagation, and prioritising contingency and recovery policies.
Journal: International Journal of Production Research
Pages: 3284-3303
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1661538
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1661538
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3284-3303




Template-Type: ReDIF-Article 1.0
Author-Name: Bo Yan
Author-X-Name-First: Bo
Author-X-Name-Last: Yan
Author-Name: Zhuo Chen
Author-X-Name-First: Zhuo
Author-X-Name-Last: Chen
Author-Name: Xinni Wang
Author-X-Name-First: Xinni
Author-X-Name-Last: Wang
Author-Name: Zijie Jin
Author-X-Name-First: Zijie
Author-X-Name-Last: Jin
Title: Influence of logistic service level on multichannel decision of a two-echelon supply chain
Abstract: 
 This paper investigates the channel structure and pricing problem of a two-echelon supply chain consisting of a manufacturer and a retailer. There are four common channel structures: (1) traditional retail channel, (2) the retailer’s traditional and online channel, (3) traditional retail channel and the manufacturer’s online channel, (4) traditional retail channel and online channel of a manufacturer and a retailer. Four Models (Model R, Model RD, Model MR, and Model MRD) are established and analysed based on four channel structures. Considering the influence of logistic services on consumers’ channel choice, this paper uses Stackelberg game and consumer utility function to analyse the profit of the manufacturer, the retailer and the whole supply chain, and obtains the optimal channel strategy of the manufacturer and the retailer in the four models. In addition, our study also finds that First, the manufacturer’s online channel opening can indirectly stimulate consumers to buy products in the traditional retail channel, which increases the demand for traditional retail channel. Second, the manufacturer’s online channel is more conducive to improving the profit of the whole supply chain than the retailer’s online channel under the dual channel structure. Third, multiple channels consisting of traditional retail channel and online channel of the manufacturer and the retailer can provide consumers with the lowest retail price, which is most beneficial to the retailer.
Journal: International Journal of Production Research
Pages: 3304-3329
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1671622
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1671622
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandra Brintrup
Author-X-Name-First: Alexandra
Author-X-Name-Last: Brintrup
Author-Name: Johnson Pak
Author-X-Name-First: Johnson
Author-X-Name-Last: Pak
Author-Name: David Ratiney
Author-X-Name-First: David
Author-X-Name-Last: Ratiney
Author-Name: Tim Pearce
Author-X-Name-First: Tim
Author-X-Name-Last: Pearce
Author-Name: Pascal Wichmann
Author-X-Name-First: Pascal
Author-X-Name-Last: Wichmann
Author-Name: Philip Woodall
Author-X-Name-First: Philip
Author-X-Name-Last: Woodall
Author-Name: Duncan McFarlane
Author-X-Name-First: Duncan
Author-X-Name-Last: McFarlane
Title: Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing
Abstract: 
 Although predictive machine learning for supply chain data analytics has recently been reported as a significant area of investigation due to the rising popularity of the AI paradigm in industry, there is a distinct lack of case studies that showcase its application from a practical point of view. In this paper, we discuss the application of data analytics in predicting first tier supply chain disruptions using historical data available to an Original Equipment Manufacturer (OEM). Our methodology includes three phases: First, an exploratory phase is conducted to select and engineer potential features that can act as useful predictors of disruptions. This is followed by the development of a performance metric in alignment with the specific goals of the case study to rate successful methods. Third, an experimental design is created to systematically analyse the success rate of different algorithms, algorithmic parameters, on the selected feature space. Our results indicate that adding engineered features in the data, namely agility, outperforms other experiments leading to the final algorithm that can predict late orders with 80% accuracy. An additional contribution is the novel application of machine learning in predicting supply disruptions. Through the discussion and the development of the case study we hope to shed light on the development and application of data analytics techniques in the analysis of supply chain data. We conclude by highlighting the importance of domain knowledge for successfully engineering features.
Journal: International Journal of Production Research
Pages: 3330-3341
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1685705
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685705
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Template-Type: ReDIF-Article 1.0
Author-Name: Xianpei Hong
Author-X-Name-First: Xianpei
Author-X-Name-Last: Hong
Author-Name: Lan Wang
Author-X-Name-First: Lan
Author-X-Name-Last: Wang
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Wanying (Amanda) Chen
Author-X-Name-First: Wanying (Amanda)
Author-X-Name-Last: Chen
Title: What is the role of value-added service in a remanufacturing closed-loop supply chain?
Abstract: 
 While the previous literature overlooks value-added service in a closed-loop supply chain (CLSC), we consider new research problems with embedding value-added service into remanufacturing models. In this paper, we mainly study the role of value-added service in a CLSC and investigate how the value-added service influences profits and other decision variables. Then, we evaluate the performance of the CLSC in different service structures, where a manufacturer or a retailer provide the value-added service. Systematic comparisons and numerical studies show that the supply chain is more effective when service is provided by a manufacturer rather than by a retailer. Also, value-added service improves the whole supply chain performance and plays a regulatory role in a CLSC and influences the decisions of supply chain members. We also show that while a service cost-sharing mechanism can only optimise rather than achieve the supply chain coordination, and the degree of optimisation depends on cost-sharing percentage, the two-part tariff contract can be an effective mechanism to coordinate decentralised service scenarios by generating the same supply chain performance in a centralised service architecture model.
Journal: International Journal of Production Research
Pages: 3342-3361
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1702230
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1702230
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3342-3361




Template-Type: ReDIF-Article 1.0
Author-Name: Daming Shi
Author-X-Name-First: Daming
Author-X-Name-Last: Shi
Author-Name: Wenhui Fan
Author-X-Name-First: Wenhui
Author-X-Name-Last: Fan
Author-Name: Yingying Xiao
Author-X-Name-First: Yingying
Author-X-Name-Last: Xiao
Author-Name: Tingyu Lin
Author-X-Name-First: Tingyu
Author-X-Name-Last: Lin
Author-Name: Chi Xing
Author-X-Name-First: Chi
Author-X-Name-Last: Xing
Title: Intelligent scheduling of discrete automated production line via deep reinforcement learning
Abstract: 
 The reinforcement learning (RL) is being used for scheduling to improve the adaptability and flexibility of an automated production line. However, the existing methods only consider processing time certain and known and ignore production line layouts and transfer unit, such as robots. This paper introduces deep RL to schedule an automated production line, avoiding manually extracted features and overcoming the lack of structured data sets. Firstly, we present a state modelling method in discrete automated production lines, which is suitable for linear, parallel and re-entrant production lines of multiple processing units. Secondly, we propose an intelligent scheduling algorithm based on deep RL for scheduling automated production lines. The algorithm establishes a discrete-event simulation environment for deep RL, solving the confliction of advancing transferring time and the most recent event time. Finally, we apply the intelligent scheduling algorithm into scheduling linear, parallel and re-entrant automated production lines. The experiment shows that our scheduling strategy can achieve competitive performance to the heuristic scheduling methods and maintains stable convergence and robustness under processing time randomness.
Journal: International Journal of Production Research
Pages: 3362-3380
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2020.1717008
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1717008
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3362-3380




Template-Type: ReDIF-Article 1.0
Author-Name: Rameshwar Dubey
Author-X-Name-First: Rameshwar
Author-X-Name-Last: Dubey
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: David J. Bryde
Author-X-Name-First: David J.
Author-X-Name-Last: Bryde
Author-Name: Yogesh K. Dwivedi
Author-X-Name-First: Yogesh K.
Author-X-Name-Last: Dwivedi
Author-Name: Thanos Papadopoulos
Author-X-Name-First: Thanos
Author-X-Name-Last: Papadopoulos
Title: Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting
Abstract: 
 There has been tremendous interest in blockchain technology (BT) (also known as distributed ledger technology) around the globe and across sectors. Following significant success in the financial sector, other sectors, such as humanitarian sector, have started deploying BT at various levels. Although the use of BT in the humanitarian sector is in its infancy, donors and government agencies are increasingly calling for building BT-enabled swift-trust (ST) and more collaborative relationships among various humanitarian actors in order to improve the transparency and traceability of disaster relief materials, information exchanges and flow of funds in disaster relief supply chains. Our study, which is informed by organisational information processing theory and relational view, proposes a theoretical model to understand how BT can influence operational supply chain transparency (OSTC) and ST among actors engaged in disaster relief operations. Our model also shows how BT-enabled ST can further improve collaboration (CO) among actors engaged in disaster relief operations and enhance supply chain resilience (SCR). We formulated and tested six research hypotheses, using data gathered from international non-governmental organisations with the help of the Coordinator for Humanitarian Affairs (OCHA) database. We received 256 usable responses using a pre-tested survey-based instrument designed for key informants. Our results confirm that our six hypotheses were supported. Our study offers significant and valid contributions to the literature on ST, CO and SCR and BT/distributed ledger technology. We have also noted the limitations of our study and have offered future research directions.
Journal: International Journal of Production Research
Pages: 3381-3398
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2020.1722860
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1722860
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3381-3398




Template-Type: ReDIF-Article 1.0
Author-Name: Knut Blind
Author-X-Name-First: Knut
Author-X-Name-Last: Blind
Author-Name: Jo-Ann Müller
Author-X-Name-First: Jo-Ann
Author-X-Name-Last: Müller
Title: Why corporate groups care about company standards
Abstract: 
 The role of company standards as a strategic tool for the optimisation of internal processes and governance of inter-firm relationships has only recently received researchers’ attention. This paper adds to the very limited body of literature by providing empirical evidence of the motives to implement company standards in general and their importance in corporate groups in particular. Using data on German companies active in standardisation, the empirical analysis confirms that companies that are part of a corporate group utilise a higher number of company standards than single firms. By codifying and transferring company-specific information, internal standardisation enhances legal security, productivity, and quality. In particular for corporate groups, internal standards additionally play a crucial role in the realisation of technical interoperability, which facilitates the development and management of internal platforms. The data, therefore, provides empirical evidence that standardisation can be used as a tool to improve efficiency and communication, and thereby facilitate global governance of multinational firms.
Journal: International Journal of Production Research
Pages: 3399-3414
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2020.1735658
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735658
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3399-3414




Template-Type: ReDIF-Article 1.0
Author-Name: Patricia van Loon
Author-X-Name-First: Patricia
Author-X-Name-Last: van Loon
Author-Name: Luk N. Van Wassenhove
Author-X-Name-First: Luk N.
Author-X-Name-Last: Van Wassenhove
Title: Transition to the circular economy: the story of four case companies
Abstract: 
 Shifting from a linear sales model to a circular service-based business model is far from straightforward. Many challenges accrue in the transition process, including finding the right market for the recirculated product/service, setting up the reverse supply chain, selecting the right partners, and making sure the new business model is sustainable in the short, medium and long term. This paper discusses the challenges of four companies trying to close the loop while preserving current profit levels. It describes their initial ideas on how the circular business model should be designed, the process they went through, challenges faced, and the eventual outcome. Based on the learnings of the four case companies, we summarise recommendations about preparatory steps required before making the transition towards a circular business model.
Journal: International Journal of Production Research
Pages: 3415-3422
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2020.1748907
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1748907
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3415-3422




Template-Type: ReDIF-Article 1.0
Author-Name: Abdul Jabbar
Author-X-Name-First: Abdul
Author-X-Name-Last: Jabbar
Author-Name: Samir Dani
Author-X-Name-First: Samir
Author-X-Name-Last: Dani
Title: Investigating the link between transaction and computational costs in a blockchain environment
Abstract: 
 The research and thinking pertaining to blockchain have thus far focused on cryptocurrency and Bitcoin. However, there is increased interest in using the technology to solve operational challenges in manufacturing and service supply chains. In this study, we introduce a new implication of using blockchain technology and propose two unique contributions. First, we introduce the notion of computational costs (measured in units of gas) as an essential mechanism for completing operational transactions in the blockchain environment. Second, we discuss the use of smart contracts and their influence on operational transactions. To investigate the link between blockchain transaction and computational costs, this study uses an experimental methodology. We develop and implement a fully functional virtual public blockchain to store, validate, and maintain transactions. The methodology provides a process to measure the computational costs, frequency, and intensity of transactions. This research contributes to conceptual research on the blockchain implementation paradigm. Its novelty stems from the identification of computational costs for operational transactions and use of an experimental methodology. This research provides managers an insight into the design of smart contract transactions in a supply chain from a cost perspective.
Journal: International Journal of Production Research
Pages: 3423-3436
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2020.1754487
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1754487
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Template-Type: ReDIF-Article 1.0
Author-Name: Fabian G. Beck
Author-X-Name-First: Fabian G.
Author-X-Name-Last: Beck
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Title: The economic lot scheduling problem: a content analysis
Abstract: 
 The paper at hand addresses the Economic Lot Scheduling Problem (ELSP), which is concerned with finding a feasible and cost-minimal production schedule for multiple items produced in lots on a single machine. The ELSP started to attract the attention of researchers in the 1950s, where the focus was primarily on the development of simple heuristics for solving the problem. Over the subsequent decades, this topic has frequently been addressed in the literature, with the subject of research being the development of new scheduling policies or solution procedures or extensions of the scope of the original model. To date, a large number of journal articles has been published on the ELSP and its model variants. To identify key research themes, publication patterns and opportunities for future research, the paper at hand applies a content analysis to a sample of 242 papers published on the Economic Lot Scheduling Problem. The results of the content analysis indicate that prior research on this topic had a strong focus on the development of solution methodologies, and that several aspects that are directly connected to lot sizing and scheduling have not attracted much attention in research on the ELSP yet, such as, for example, energy cost and sustainability.
Journal: International Journal of Production Research
Pages: 3437-3454
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1668071
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1668071
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Template-Type: ReDIF-Article 1.0
Author-Name: Amirmohsen Golmohammadi
Author-X-Name-First: Amirmohsen
Author-X-Name-Last: Golmohammadi
Author-Name: Elkafi Hassini
Author-X-Name-First: Elkafi
Author-X-Name-Last: Hassini
Title: Review of supplier diversification and pricing strategies under random supply and demand
Abstract: 
 Uncertainties of supply and demand are two major sources of risk in any supply chain. As a result, the companies are implementing different strategies to mitigate the effects of these risks. Supplier diversification and responsive pricing are two of the main strategies that are used to mitigate the supply and demand risks. In supplier diversification, a firm uses multiple channels of sourcing while in responsive pricing, a firm manipulates demand through pricing to mitigate supply and demand risks. In this paper, we review lot-sizing problems when supply and demand are random. We focus on studies that have considered supplier diversification or responsive pricing as a mitigation strategy. We classify the studies based on their main assumptions and summarise their major findings. Finally, we present some directions for future research. Part of what we have found is that most studies that use multiple decision makers have focused on cases where information is complete and non-cooperative. There is a need to consider more realistic situations when there is information asymmetry between the decision makers. In addition, we have found that there is a lack of studies that look at the impact of joint ordering and pricing in the existence of multiple suppliers.
Journal: International Journal of Production Research
Pages: 3455-3487
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2019.1705419
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1705419
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3455-3487




Template-Type: ReDIF-Article 1.0
Author-Name: Linh Nguyen Khanh Duong
Author-X-Name-First: Linh Nguyen Khanh
Author-X-Name-Last: Duong
Author-Name: Josephine Chong
Author-X-Name-First: Josephine
Author-X-Name-Last: Chong
Title: Supply chain collaboration in the presence of disruptions: a literature review
Abstract: 
 The supply chain collaboration has gained significant attention, especially in the presence of disruptions. This paper presents findings from a systematic literature review to answer the question: how collaborations help supply chains respond and recover from a disruption. A total of 157 papers from the year 2000 were studied. The thematic and descriptive analysis identified usefulness, used research methodologies, collaboration mechanisms, and influential factors in collaboration. This comprehensive review provides in-depth insights into the current state of literature, proposes a research framework, and identifies several future research directions. It also highlights the role of each collaboration mechanism based on each severity level of disruptions.
Journal: International Journal of Production Research
Pages: 3488-3507
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2020.1712491
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1712491
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3488-3507




Template-Type: ReDIF-Article 1.0
Author-Name: Song Xu
Author-X-Name-First: Song
Author-X-Name-Last: Xu
Author-Name: Xiaotong Zhang
Author-X-Name-First: Xiaotong
Author-X-Name-Last: Zhang
Author-Name: Lipan Feng
Author-X-Name-First: Lipan
Author-X-Name-Last: Feng
Author-Name: Wenting Yang
Author-X-Name-First: Wenting
Author-X-Name-Last: Yang
Title: Disruption risks in supply chain management: a literature review based on bibliometric analysis
Abstract: 
 Disruption risks in supply chain management have a great negative influence on the performance of supply chain members. Therefore, the field of supply chain disruption (SCD) has received increasing attention on mitigating the risks and improving the supply chain performance. This paper presents a comprehensive bibliometric overview and visualisation of the field of SCD based on 1,310 publications derived from the core collection of the Web of Science. The influential authors, organisations, and SCD keywords are discussed in detail based on some visualisation tools. Then, the leading publications and main clusters of SCD are identified to find out the key research topics based on citation analysis and reference co-citation analysis. The paper will be a helpful resource for researchers and practitioners who are interested in the field of SCD to capture the current research hotspots and potential research directions.
Journal: International Journal of Production Research
Pages: 3508-3526
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2020.1717011
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1717011
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Template-Type: ReDIF-Article 1.0
Author-Name: Ramesh Kumar
Author-X-Name-First: Ramesh
Author-X-Name-Last: Kumar
Author-Name: L. Ganapathy
Author-X-Name-First: L.
Author-X-Name-Last: Ganapathy
Author-Name: Ravindra Gokhale
Author-X-Name-First: Ravindra
Author-X-Name-Last: Gokhale
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Quantitative approaches for the integration of production and distribution planning in the supply chain: a systematic literature review
Abstract: 
 Production and distribution are the two primary internal elements of the supply chain. This paper presents a systematic literature review (SLR) of quantitative approaches for the integration of production and distribution planning (IPDP) in the supply chain. We provide a classification framework with eight dimensions and give a brief overview of the quantitative approaches such as modelling approaches and solution approaches for the IPDP problem in the supply chain. The SLR has been carried out using two basic search databases Scopus and Web of Science. In all, we identify relevant articles in the period from 2000 to 2019. We also highlight certain research opportunities, suggestions, and research gaps for possible future research by assessing the current knowledge on the quantitative approaches for IPDP problems in the supply chain.
Journal: International Journal of Production Research
Pages: 3527-3553
Issue: 11
Volume: 58
Year: 2020
Month: 6
X-DOI: 10.1080/00207543.2020.1762019
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1762019
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:11:p:3527-3553




Template-Type: ReDIF-Article 1.0
Author-Name: Mingbao Cheng
Author-X-Name-First: Mingbao
Author-X-Name-Last: Cheng
Author-Name: Shuxian Xiao
Author-X-Name-First: Shuxian
Author-X-Name-Last: Xiao
Author-Name: Renfei Luo
Author-X-Name-First: Renfei
Author-X-Name-Last: Luo
Author-Name: Zhaotong Lian
Author-X-Name-First: Zhaotong
Author-X-Name-Last: Lian
Title: Single-machine scheduling problems with a batch-dependent aging effect and variable maintenance activities
Abstract: 
 We consider single-machine scheduling problems with a batch-dependent ageing effect and variable maintenance activities between batches. The machine can process several jobs as a batch. It requires maintenance activities where the maintenance time depends on the flow time of the pre-batch, i.e. the batch processed before a batch. A job’s actual processing time is an increasing exponential function of its operation time within a batch. The objectives are to minimise the makespan and the total completion time. We develop polynomial time algorithms for the makespan minimisation problem and the total completion time minimisation problem under the condition that the ageing factor is greater than one. We also provide a mathematical programming approach and two heuristic algorithms to analyse the total completion time minimisation problem when the ageing factor is less than one for even one batch. The computational analysis indicates that the proposed heuristic algorithms are more efficient for the smaller ageing factor, whereas the Modified Shortest Processing Time algorithm is more efficient than the proposed heuristic algorithms for the larger ageing factor.
Journal: International Journal of Production Research
Pages: 7051-7063
Issue: 23
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1398424
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398424
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Template-Type: ReDIF-Article 1.0
Author-Name: Hakan F. Karagul
Author-X-Name-First: Hakan F.
Author-X-Name-Last: Karagul
Author-Name: Donald P. Warsing
Author-X-Name-First: Donald P.
Author-X-Name-Last: Warsing
Author-Name: Thom J. Hodgson
Author-X-Name-First: Thom J.
Author-X-Name-Last: Hodgson
Author-Name: Maaz S. Kapadia
Author-X-Name-First: Maaz S.
Author-X-Name-Last: Kapadia
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Title: A comparison of mixed integer programming formulations of the capacitated lot-sizing problem
Abstract: 
 We propose a novel mixed integer programming formulation for the capacitated lot-sizing problem with set-up times and set-up carryover. We compare our formulation to two earlier formulations, the Classical and Modified formulations, and a more recent formulation due to Suerie and Stadtler. Extensive computational experiments show that our formulation consistently outperforms the Classical and Modified formulations in terms of CPU time and solution quality. It is competitive with the Suerie–Stadtler (S&S) formulation, but outperforms all other formulations on the most challenging instances, those with low-capacity slack and a dense jobs matrix. We show that some of the differences in the performance of these various formulations arise from their different use of binary variables to represent production or set-up states. We also show that the LP relaxation of our Novel formulation provides a tighter lower bound than that of the Modified formulation. Our experiments demonstrate that, while the S&S formulation provides a much tighter LP bound, the Novel formulation is better able to exploit the intelligence of the CPLEX solution engine.
Journal: International Journal of Production Research
Pages: 7064-7084
Issue: 23
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1401232
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1401232
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:23:p:7064-7084




Template-Type: ReDIF-Article 1.0
Author-Name: Luiz Henrique Cherri
Author-X-Name-First: Luiz Henrique
Author-X-Name-Last: Cherri
Author-Name: Adriana Cristina Cherri
Author-X-Name-First: Adriana Cristina
Author-X-Name-Last: Cherri
Author-Name: Maria Antónia Carravilla
Author-X-Name-First: Maria Antónia
Author-X-Name-Last: Carravilla
Author-Name: José Fernando Oliveira
Author-X-Name-First: José Fernando
Author-X-Name-Last: Oliveira
Author-Name: Franklina Maria Bragion Toledo
Author-X-Name-First: Franklina Maria Bragion
Author-X-Name-Last: Toledo
Author-Name: Andréa Carla Gonçalves Vianna
Author-X-Name-First: Andréa Carla Gonçalves
Author-X-Name-Last: Vianna
Title: An innovative data structure to handle the geometry of nesting problems
Abstract: 
 As in many other combinatorial optimisation problems, research on nesting problems (aka irregular packing problems) has evolved around the dichotomy between continuous (time consuming) and discrete (memory consuming) representations of the solution space. Recent research has been devoting increasing attention to discrete representations for the geometric layer of nesting problems, namely in mathematical programming-based approaches. These approaches employ conventional regular meshes, and an increase in their precision has a high computational cost. In this paper, we propose a data structure to represent non-regular meshes, based on the geometry of each piece. It supports non-regular discrete geometric representations of the shapes, and by means of the proposed data structure, the discretisation can be easily adapted to the instances, thus overcoming the precision loss associated with discrete representations and consequently allowing for a more efficient implementation of search methods for the nesting problem. Experiments are conducted with the dotted-board model – a recently published mesh-based binary programming model for nesting problems. In the light of both the scale of the instances, which are now solvable, and the quality of the solutions obtained, the results are very promising.
Journal: International Journal of Production Research
Pages: 7085-7102
Issue: 23
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1413256
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1413256
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:23:p:7085-7102




Template-Type: ReDIF-Article 1.0
Author-Name: Safwan A. Altarazi
Author-X-Name-First: Safwan A.
Author-X-Name-Last: Altarazi
Author-Name: Maysa M. Ammouri
Author-X-Name-First: Maysa M.
Author-X-Name-Last: Ammouri
Title: Concurrent manual-order-picking warehouse design: a simulation-based design of experiments approach
Abstract: 
 The design of manual-order-picking warehouses is a combination of interdependent decisions with enormous possible varieties in design components. The strong interrelationship between these components, in addition to the dynamic and interconnected stochastic nature of the problem; necessitate the utilisation of a simultaneous simulation-based approach. This study proposes a concurrent simulation-based design of experiments approach for the design of manual-order-picking warehouses. The proposed approach can investigate all possible warehousing design combinations with their stochastic nature and interactions; hence, widening the search for performance improvement. The examined design components include warehouse throughput, size, layout, operational policies and manpower/carts. Furthermore, the presented approach captures the probabilistic nature of all the key warehouse functions of receiving, unloading, put away, storage, preparation and picking and shipping; and evaluates the performance of the studied designs using the cycle time for a stock keeping unit in the warehouse. Statistical analysis of the simulation results showed several interesting findings; horizontal layout was preferable over all other types of layouts and small size warehouses perform better than other large sizes. The study has also recommended using high throughput for traditional layout-small size warehouses.
Journal: International Journal of Production Research
Pages: 7103-7121
Issue: 23
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1421780
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1421780
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:23:p:7103-7121




Template-Type: ReDIF-Article 1.0
Author-Name: Ahlam Azzamouri
Author-X-Name-First: Ahlam
Author-X-Name-Last: Azzamouri
Author-Name: Pierre Fénies
Author-X-Name-First: Pierre
Author-X-Name-Last: Fénies
Author-Name: Frédéric Fontane
Author-X-Name-First: Frédéric
Author-X-Name-Last: Fontane
Author-Name: Vincent Giard
Author-X-Name-First: Vincent
Author-X-Name-Last: Giard
Title: Scheduling of open-pit phosphate mine extraction
Abstract: 
 Open-pit deposits are often characterised by a stack of layers of different geological nature. Some layers are worthless while the ore of the others is of a varying economic value depending on grade. To reach a layer, it is necessary to have first removed the upper layers above the extraction zone. This action results in uncovering the layer in this particular place and in facilitating access to the layers below. This extraction process involves a series of 2–7 basic operations; each one is performed by a machine, some of which are able to perform up to three different operations. Ensuring the consistency of mining extraction scheduling over a few months, in order to meet known or forecast demand, is a challenging task. A mining extraction model based on mathematical programming is proposed but it is hardly usable, due to its size. Therefore, a model based on a Discrete Event Simulation, is created to test how ore supplies are affected by the tactical and operational decisions relating to the choice of parcels to be processed and to the allocation of machines to the different basic operations.
Journal: International Journal of Production Research
Pages: 7122-7141
Issue: 23
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1433341
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1433341
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:23:p:7122-7141




Template-Type: ReDIF-Article 1.0
Author-Name: Xiaofei Kou
Author-X-Name-First: Xiaofei
Author-X-Name-Last: Kou
Author-Name: Gangyan Xu
Author-X-Name-First: Gangyan
Author-X-Name-Last: Xu
Author-Name: Chuanyun Yi
Author-X-Name-First: Chuanyun
Author-X-Name-Last: Yi
Title: Belt-conveyor based efficient parallel storage system design and travel time model analysis
Abstract: 
 This paper presents a belt-conveyor based parallel storage system (PSS). Compared with the conventional AS/RS, it has advantages including more efficient utilisation of storage space, and faster storage and retrieval of products. The PSS consists of three components: the automated retrieval system (ARS), the automated storage system (ASS) and the compact storage rack (CSR). In the ARS, a vertical screw conveyor is used to facilitate the vertical movement of the unit loads, while a powered belt-conveyor is used for the horizontal dimension. Additionally, a powered conveyor system enables motion along the depth dimension, meaning each lane in the CSR is connected to several storage cells. Horizontal belt-conveyor and powered conveyor in the lane constitute cross-belt which causes the parallel process. On the other side of the rack, a unit load lift, a RGV lift, several rail-guided vehicles and a buffer rack constitute the ASS. Based on the system, we formulate separate travel-time models for ARS and ASS, under the assumption of randomised, uniformly distributed storage rack positions. Computer simulation with Matlab is used to validate the models, and optimise the automated storage system.
Journal: International Journal of Production Research
Pages: 7142-7159
Issue: 23
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1436784
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1436784
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Template-Type: ReDIF-Article 1.0
Author-Name: Chaoqun Duan
Author-X-Name-First: Chaoqun
Author-X-Name-Last: Duan
Author-Name: Chao Deng
Author-X-Name-First: Chao
Author-X-Name-Last: Deng
Author-Name: Abolfazl Gharaei
Author-X-Name-First: Abolfazl
Author-X-Name-Last: Gharaei
Author-Name: Jun Wu
Author-X-Name-First: Jun
Author-X-Name-Last: Wu
Author-Name: Bingran Wang
Author-X-Name-First: Bingran
Author-X-Name-Last: Wang
Title: Selective maintenance scheduling under stochastic maintenance quality with multiple maintenance actions
Abstract: 
 Many systems are required to perform a series of missions with finite breaks between any two consecutive missions. To improve the probability of system successfully completing the next mission, maintenance action is carried out on components during the breaks. In this work, a selective maintenance model with stochastic maintenance quality for multi-component systems is investigated. At each scheduled break, a set of maintenance actions with different degrees of impact are available for each component. The impact of a maintenance action is assumed to be random and follow an identified probability distribution. The corresponding maintenance cost and time are modelled based on the expected impact of the maintenance action. The objective of selective maintenance scheduling is to find the cost-optimal maintenance action for each component at every scheduled break subject to reliability and duration constraints. A simulated annealing algorithm is used to solve the complicated optimisation problem where both multiple maintenance actions and stochastic quality model are taken into account. Two illustrative numerical examples and a real case study have been solved to demonstrate the performance of the proposed approach. A comparison with deterministic maintenance shows the importance of considering the proposed stochastic quality in selective maintenance scheduling.
Journal: International Journal of Production Research
Pages: 7160-7178
Issue: 23
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1436789
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1436789
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:23:p:7160-7178




Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 7179-7179
Issue: 23
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1452358
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1452358
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:23:p:7179-7179




Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Corrigendum
Journal: International Journal of Production Research
Pages: 7180-7180
Issue: 23
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1457819
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1457819
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:23:p:7180-7180




Template-Type: ReDIF-Article 1.0
Author-Name: Mohit Goswami
Author-X-Name-First: Mohit
Author-X-Name-Last: Goswami
Title: An integrative product line redesign approach for modular engineering products within a competitive market space: a multi-objective perspective
Abstract: 
 The purpose of this research is to aid enterprises to redesign their existing product line from the standpoint of two critical competitive dimensions i.e. time to market (TTM) and market share. An integrative methodology for product line redesign is evolved that sews together aspects related to product functionality, modularity and competitive market segments. Firstly, the existing level functionality of a multi-modular product is established employing the functional analysis systems technique for the given manufacturer under consideration and other market players. Thereafter, product premium and TTM functions for respective modules in terms of the linear relationships are established. Further, a detailed mathematical model is evolved where the two objective functions related to minimisation of TTM and maximisation of the product premium are formulated. The constraints in the devised optimisation model pertain to market segment, product profile, engineering design and non-negativity and integrality considerations. Finally, employing the non-dominated sorting genetic algorithm (NSGA-II), the devised model is solved that yields a number of Pareto-optimal redesigned products for the three market segments under consideration. Analysis of the results yields several managerial insights that are discussed. The devised framework is illustrated employing a real-life case of Black and Decker’s power tool product line.
Journal: International Journal of Production Research
Pages: 7258-7279
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1364443
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1364443
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:24:p:7258-7279




Template-Type: ReDIF-Article 1.0
Author-Name: Samira Keivanpour
Author-X-Name-First: Samira
Author-X-Name-Last: Keivanpour
Author-Name: Daoud Ait Kadi
Author-X-Name-First: Daoud
Author-X-Name-Last: Ait Kadi
Title: Strategic eco-design map of the complex products: toward visualisation of the design for environment
Abstract: 
 With growing sustainability and environmental concerns regarding the products, decision-makers and business managers need to integrate sustainability into business strategies and support it via systematic business processes and decision support tools. With the integration of the eco-efficiency attributes to the product development, more data should be analysed in engineering design. This integration also increases the complexity of the design process due to the large volume of data processing and diversity of the different attributes and features of the products. In this paper, we used the stock market metaphor to develop a visual data mining approach to the strategic eco-design assessment of the complex products. We presented a fresh framework using clustering and visualisation techniques to analyse the eco-efficiency profile of the different modules, components and parts of a complex product, and provide an efficient data exploration tool for decision-makers to facilitate processing of eco-design attributes, and strategic objectives at the same time. An illustrative example is provided to show the procedure of the application and the effectiveness of the proposed approach.
Journal: International Journal of Production Research
Pages: 7296-7312
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1388931
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1388931
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:24:p:7296-7312




Template-Type: ReDIF-Article 1.0
Author-Name: Jaime A. Mesa
Author-X-Name-First: Jaime A.
Author-X-Name-Last: Mesa
Author-Name: Iván Esparragoza
Author-X-Name-First: Iván
Author-X-Name-Last: Esparragoza
Author-Name: Heriberto Maury
Author-X-Name-First: Heriberto
Author-X-Name-Last: Maury
Title: Development of a metric to assess the complexity of assembly/disassembly tasks in open architecture products
Abstract: 
 This paper describes two metrics to measure the complexity involved in assembly and disassembly tasks for open architecture products during its use phase. The approach proposed is based on the summary of all tasks required to assemble and disassemble a predefined set of modules to generate several product variants, which comprise different working levels or functionalities. The aim of the method is to provide a useful tool to designers in the analysis of product complexity regarding use and further phases in which the assembly and disassembly of modules are required. The benefits and usefulness of the metrics are oriented to enhance the sustainability performance of products through the measurement of complexity in modular systems for the decision-making during the design stage. The reduction of complexity involves significant benefits in all lifecycle phases of product, especially when the user or customer is responsible for many related tasks (maintenance, upgrading, reconfiguration and final disposal of modules). The metrics and their calculation process are illustrated using two case study products.
Journal: International Journal of Production Research
Pages: 7201-7219
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1398431
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1398431
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:24:p:7201-7219




Template-Type: ReDIF-Article 1.0
Author-Name: Rupinder Singh
Author-X-Name-First: Rupinder
Author-X-Name-Last: Singh
Author-Name: Ravinder Sharma
Author-X-Name-First: Ravinder
Author-X-Name-Last: Sharma
Author-Name: J. Paulo Davim
Author-X-Name-First: J. Paulo
Author-X-Name-Last: Davim
Title: Mechanical properties of bio compatible functional prototypes for joining applications in clinical dentistry
Abstract: 
 In the presented research, work investigations have been made for mechanical properties of the functional prototypes prepared from biocompatible filament of fused deposition modelling (FDM), comprising of hydroxyapatite (HAp), polypropylene (PP) and polyvinyl chloride (PVC). The functional prototypes will be used in clinical dentistry (mainly for joining application for job-type production activities). The filament has been prepared in house using twin screw extrusion process. For evaluation purpose, standard tensile specimens as per ASTM D-638 have been prepared on FDM. This study highlights the effect of three parameters of FDM (namely: infill percentage, layer thickness and speed of extrusion head) on the mechanical properties (namely: load at peak and load at break). The results of the study suggest that infill density has majorly contributed, 92% on load at peak and 89% for load at break, and deposition speed has very less contribution i.e., 1% towards the mechanical strength of the specimen. Further, the results are supported with thermal analysis using differential scanning calorimeter (DSC), which ensures that the specimen prepared are thermally stable and can be put in for joining applications for job-type production activities in clinical dentistry.
Journal: International Journal of Production Research
Pages: 7330-7340
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1405167
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1405167
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:24:p:7330-7340




Template-Type: ReDIF-Article 1.0
Author-Name: Zhiyuan Jiao
Author-X-Name-First: Zhiyuan
Author-X-Name-Last: Jiao
Author-Name: Yanfeng Xing
Author-X-Name-First: Yanfeng
Author-X-Name-Last: Xing
Title: Clamping-sequence optimisation based on heuristic algorithm for sheet-metal components
Abstract: 
 The traditional clamping-sequence optimisation of sheet-metal parts requires many complicated finite element analyses, and clamping-sequence planning does not account for the springback from clamp-release. Therefore, this paper proposes a new optimisation method based on a heuristic algorithm. We first propose a new contact model of parts, clamps and supporting locators to analyse assembly deformation. Then, we use the distance between the actual and nominal positions to evaluate the clamp layout. Finally, we apply the heuristic algorithm to optimise the clamping sequence. We illustrate the proposed method with a case study of a taillight bracket, whose results show that the method of clamping-sequence optimisation can effectively decrease the deformation of sheet metal from clamping.
Journal: International Journal of Production Research
Pages: 7190-7200
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1410245
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1410245
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:24:p:7190-7200




Template-Type: ReDIF-Article 1.0
Author-Name: Jaime A. Mesa
Author-X-Name-First: Jaime A.
Author-X-Name-Last: Mesa
Author-Name: Danny Illera
Author-X-Name-First: Danny
Author-X-Name-Last: Illera
Author-Name: Iván Esparragoza
Author-X-Name-First: Iván
Author-X-Name-Last: Esparragoza
Author-Name: Heriberto Maury
Author-X-Name-First: Heriberto
Author-X-Name-Last: Maury
Author-Name: Humberto Gómez
Author-X-Name-First: Humberto
Author-X-Name-Last: Gómez
Title: Functional characterisation of mechanical joints to facilitate its selection during the design of open architecture products
Abstract: 
 New trends in product design require the use of modularity as key feature aimed to improve functional performance and the generation of open architecture products. For mechanical systems, one of the challenges during early design stages of these products involves the proper selection of joining methods among their constructive components. A robust joint selection process must consider product requirements, life cycle analysis and eventual procedures for assembly and disassembly. However, the general approach towards a Design-for-Assembly (DFA)/Design-for-Disassembly (DFD) only considers design, manufacturing and in some cases final disposal stage. Additionally, most of the works found in the literature are merely focused on assembly operations, disregarding economic and environmental benefits from optimising disassembly complexity. Herein, a functional characterisation of mechanical joint methods for the assembly and disassembly activities that take place throughout the product life cycle is proposed, focusing on open architecture products. Additionally, a classification of joining methods, a joint complexity metric valuation and a selection process are proposed for the conceptual design stage. The approach integrates both DFA and DFD principles in a formal methodology. The proposed selection roadmap can be implemented to increase product sustainability positively regarding resources optimisation, operational time and costs in reuse, remanufacturing and recycling tasks.
Journal: International Journal of Production Research
Pages: 7390-7404
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1412530
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1412530
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohand Lounes Bentaha
Author-X-Name-First: Mohand Lounes
Author-X-Name-Last: Bentaha
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Author-Name: Robert J. Riggs
Author-X-Name-First: Robert J.
Author-X-Name-Last: Riggs
Author-Name: Jack Hu
Author-X-Name-First: Jack
Author-X-Name-Last: Hu
Title: Profit-oriented partial disassembly line design: dealing with hazardous parts and task processing times uncertainty
Abstract: 
 This paper addresses the problem of profit-oriented disassembly line design and balancing considering partial disassembly, presence of hazardous parts and uncertainty of task processing times. Few papers have studied the stochastic disassembly line balancing problem and existing approaches have focused on heuristic and metaheuristic methods. Most existing work has concentrated on complete disassembly where task times are assumed to be normal random variables and where AND/OR graphs are not considered. The objective of this paper is the design of a serial line that obtains the maximum revenue and then balances the workload under uncertainty. The processing time of a disassembly task is assumed to be a random variable with any known probability distribution. An AND/OR graph is used to model the precedence relationships among tasks. Stochastic programming models and exact-based solution approaches combining the L-shaped algorithm and Monte Carlo sampling techniques are proposed. The relevance and applicability of the proposed models and solution methods are shown by solving efficiently a set of disassembly problem instances from the literature.
Journal: International Journal of Production Research
Pages: 7220-7242
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2017.1418987
File-URL: http://hdl.handle.net/10.1080/00207543.2017.1418987
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:24:p:7220-7242




Template-Type: ReDIF-Article 1.0
Author-Name: Süleyman Mete
Author-X-Name-First: Süleyman
Author-X-Name-Last: Mete
Author-Name: Zeynel Abidin Çil
Author-X-Name-First: Zeynel Abidin
Author-X-Name-Last: Çil
Author-Name: Eren Özceylan
Author-X-Name-First: Eren
Author-X-Name-Last: Özceylan
Author-Name: Kürşad Ağpak
Author-X-Name-First: Kürşad
Author-X-Name-Last: Ağpak
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Title: An optimisation support for the design of hybrid production lines including assembly and disassembly tasks
Abstract: 
 The optimisation problems related to the assignment of tasks to workstations in assembly and disassembly lines have been largely discussed in the literature. They are known, respectively, as Assembly Line Balancing and Disassembly Line Balancing Problems. In this study, both types of task performed on the identical product are integrated in a common hybrid production system. Therefore, the logistic process is simplified and disassembly tasks can supply easier the assembly tasks with the required components. The considered production system has the layout of two parallel lines with common workstations. The product flow is conventional in the assembly line and reverse in the disassembly line. The paper provides a new mathematical model for designing such a hybrid system and an approximate approach based on ant colony optimisation for solving large-scale instances. The solution method is tested in a case study. The obtained results are compared with the solution provided by the design of two independent lines. The analysis of the results highlights the potential benefits of the hybrid production system.
Journal: International Journal of Production Research
Pages: 7375-7389
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1428774
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1428774
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Template-Type: ReDIF-Article 1.0
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Junkai He
Author-X-Name-First: Junkai
Author-X-Name-Last: He
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Title: A new distribution-free model for disassembly line balancing problem with stochastic task processing times
Abstract: 
 Effective conduct with End of Life (EOL) products is a hot research topic in green and smart manufacturing. For EOL product recycling and remanufacturing, a fundamental problem is to design an efficient disassembly line under consideration of stochastic task processing times. This problem focuses on selecting alternative task processes, determining the number of opened workstations, and assigning operational tasks to the workstations. The goal is to minimise the total cost consisting of workstation operational cost and hazardous component processing cost. Most existing works assume that the probability distribution of task processing times can be estimated, however, it is often not likely to access the complete probability distribution due to various difficulties. Therefore, this study investigates disassembly line design with the assumption that only the mean, standard deviation and an upper bound of task processing times are known. Our main contributions include: (i) a new decomposition color graph is proposed to intuitively describe all possible processes, (ii) a new distribution-free model is proposed, and (iii) some problem properties are established to solve the model. Experimental results show that the distribution-free model can effectively deal with stochastic task processing times without given probability distributions.
Journal: International Journal of Production Research
Pages: 7341-7353
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1430909
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1430909
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Template-Type: ReDIF-Article 1.0
Author-Name: Hyung-Won Kim
Author-X-Name-First: Hyung-Won
Author-X-Name-Last: Kim
Author-Name: Chuljin Park
Author-X-Name-First: Chuljin
Author-X-Name-Last: Park
Author-Name: Dong-Ho Lee
Author-X-Name-First: Dong-Ho
Author-X-Name-Last: Lee
Title: Selective disassembly sequencing with random operation times in parallel disassembly environment
Abstract: 
 Selective disassembly sequencing is the problem of determining the sequence of disassembly operations to extract one or more target components of a product. This study considers the problem with random operation times in the parallel disassembly environment in which one or more components can be removed at the same time by a single disassembly operation. After representing all possible disassembly sequences using the extended process graph, a stochastic integer programming model is developed for the objective of minimising the sum of disassembly and penalty costs, where the disassembly costs consist of sequence-dependent set-up and operation costs and the penalty cost is the expectation of the costs incurred when the total disassembly time exceeds a threshold value. A sample average approximation-based solution algorithm is proposed that incorporates an optimal algorithm to solve the sample average approximating problem under a given set of scenarios for disassembly operation times. The algorithm is illustrated with a hand-light case and a large-sized random instance, and the results are reported.
Journal: International Journal of Production Research
Pages: 7243-7257
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1432911
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1432911
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Template-Type: ReDIF-Article 1.0
Author-Name: Martin Løkkegaard
Author-X-Name-First: Martin
Author-X-Name-Last: Løkkegaard
Author-Name: Niels Henrik Mortensen
Author-X-Name-First: Niels Henrik
Author-X-Name-Last: Mortensen
Author-Name: Lars Hvam
Author-X-Name-First: Lars
Author-X-Name-Last: Hvam
Title: Using business critical design rules to frame new architecture introduction in multi-architecture portfolios
Abstract: 
 When introducing new architectures to an industrial portfolio, counting multiple existing product and manufacturing solutions, time-to-market and investments in manufacturing equipment can be significantly reduced if new concepts are aligned with the existing portfolio. This can be done through component sharing, or sharing critical design principles. This alignment is not trivial, as extensive design knowledge is needed to overview a portfolio with many, often highly different products and manufacturing lines. In this paper, we suggest establishing a frame of reference for new-product introduction based on several ‘game rules’, or Business Critical Design Rules (BCDRs), which denote the most critical features of the product and manufacturing architectures, and should be considered an obligatory reference for design when introducing new architectures. BCDRs are derived from the portfolio, architecture and module levels, including modelling of the most critical links between the product and manufacturing domains. The suggested modelling principle has been tested as a frame for new-architecture introduction, capturing critical modularisation principles in a large and global OEM. Application of the suggested method revealed a potential for reducing time-to-market and potentially cutting 35% off investments in new manufacturing equipment when introducing new products in the portfolio.
Journal: International Journal of Production Research
Pages: 7313-7329
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1450531
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1450531
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Template-Type: ReDIF-Article 1.0
Author-Name: Vladimir Modrak
Author-X-Name-First: Vladimir
Author-X-Name-Last: Modrak
Author-Name: Zuzana Soltysova
Author-X-Name-First: Zuzana
Author-X-Name-Last: Soltysova
Title: Development of operational complexity measure for selection of optimal layout design alternative
Abstract: 
 Characterising existing approaches to operational complexity, it can be stated that for those metrics are characterful different factors used as variables such as product structure, machine composition, number of technological functions performed by machine, and others. Moreover, the complexity metrics using the information content as a basis can be divided into two groups: those which define complexity as an absolute entropy quantity, and metrics defining complexity as the relative entropy magnitude. Our view on the operational complexity is based on an assumption that process complexity value obtained as a sum of the partial complexities is not so important than a balanced operational complexity value expressing relative quantity to equilibrium levels. Accordingly, this paper introduces the novel operational complexity measure that initially identifies operational complexities of individual machines based on the number of parts, machines and operations. In the subsequent steps, these sub-measures are used to define summary complexity measure involving two balanced operational complexity characteristics. The novel measure can be effectively used to find the most suitable layout design alternative. For the purpose to prove its effectiveness, on two practical cases where tested its practicability by comparing it to the complexity indicator expressing the sum of the partial complexities.
Journal: International Journal of Production Research
Pages: 7280-7295
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1456696
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1456696
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Handle: RePEc:taf:tprsxx:v:56:y:2018:i:24:p:7280-7295




Template-Type: ReDIF-Article 1.0
Author-Name: Jyh-Wen Ho
Author-X-Name-First: Jyh-Wen
Author-X-Name-Last: Ho
Title: Cost strategy for product planning under competition
Abstract: 
 This study proposes a manufacturing system for the production of a new product, which is achieved by optimum collaboration between members of the supply chain. From the perspective of an incumbent firm, the behaviours of randomly occurring competitors could significantly affect order quantities, and the resultant profitability could diminish competitiveness in the product market. An effective method is therefore required to quantitatively evaluate the influence of competitive companies on the incumbent’s profitability. The objective of this study is to minimise the incumbent’s cost for a new product under competition through an economical cost distribution. Considering the whole life of a product in the market, the Bayesian approach is used to analyse the behaviours of competitors, the work efficiency of employees, in addition to the related costs of the incumbent firm. The adequate cost strategy for manufacturing a new product under competition can be then available.
Journal: International Journal of Production Research
Pages: 7444-7457
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1461273
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1461273
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanling Feng
Author-X-Name-First: Yanling
Author-X-Name-Last: Feng
Author-Name: Guo Li
Author-X-Name-First: Guo
Author-X-Name-Last: Li
Author-Name: Suresh P. Sethi
Author-X-Name-First: Suresh P.
Author-X-Name-Last: Sethi
Title: Pull and push contracts in a decentralised assembly system with random component yields
Abstract: 
 This study investigates how random component yields can influence pricing and production decisions under pull and push contracts. We consider a decentralised assembly system where a manufacturer procures complementary components from two suppliers with random yields. We first characterise the centralised equilibrium decision as a benchmark and then analyse the equilibrium solutions in a decentralised assembly system under each contract. We find that neither contract is always superior to the other in terms of system profit. Under a push contract, suppliers always achieve the first mover advantage with higher payoff. However, the first mover advantage does not hold for the manufacturer under a pull contract. We further conduct sensitivity analysis to study the impact of random component yields and retail price on equilibrium solutions under each contract. Interestingly, the wholesale prices charged by suppliers always increase with supply yield uncertainty under a pull contract, but decrease under a push contract. In contrast with the centralised solution, the equilibrium quantities in the decentralised solution decrease with supply yield uncertainty under both pull and push contracts. We then extend our model to a general case with multiple suppliers. The system payoff decreases with the number of suppliers, and the main results derived in two suppliers setting still hold in the system with multiple suppliers.
Journal: International Journal of Production Research
Pages: 7405-7425
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1471237
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471237
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Template-Type: ReDIF-Article 1.0
Author-Name: Lixia Zhu
Author-X-Name-First: Lixia
Author-X-Name-Last: Zhu
Author-Name: Zeqiang Zhang
Author-X-Name-First: Zeqiang
Author-X-Name-Last: Zhang
Author-Name: Yi Wang
Author-X-Name-First: Yi
Author-X-Name-Last: Wang
Title: A Pareto firefly algorithm for multi-objective disassembly line balancing problems with hazard evaluation
Abstract: 
 The safety hazards existing in the process of disassembling waste products pose potential harms to the physical and mental health of the workers. In this article, these hazards involved in the disassembly operations are evaluated and taken into consideration in a disassembly line balancing problem. A multi-objective mathematical model is constructed to minimise the number of workstations, maximise the smoothing rate and minimise the average maximum hazard involved in the disassembly line. Subsequently, a Pareto firefly algorithm is proposed to solve the problem. The random key encoding method based on the smallest position rule is used to adapt the firefly algorithm to tackle the discrete optimisation problem of the disassembly line balancing. To avoid the search being trapped in a local optimum, a random perturbation strategy based on a swap operation is performed on the non-inferior solutions. The validity of the proposed algorithm is tested by comparing with two other algorithms in the existing literature using a 25-task phone disassembly case. Finally, the proposed algorithm is applied to solve a refrigerator disassembly line problem based on the field investigation and a comparison of the proposed Pareto firefly algorithm with another multi-objective firefly algorithm in the existing literature is performed to further identify the superior performance of the proposed Pareto firefly algorithm, and eight Pareto optimal solutions are obtained for decision makers to make a decision.
Journal: International Journal of Production Research
Pages: 7354-7374
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1471238
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1471238
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Template-Type: ReDIF-Article 1.0
Author-Name: A. Salmi
Author-X-Name-First: A.
Author-X-Name-Last: Salmi
Author-Name: P. David
Author-X-Name-First: P.
Author-X-Name-Last: David
Author-Name: E. Blanco
Author-X-Name-First: E.
Author-X-Name-Last: Blanco
Author-Name: O. Briant
Author-X-Name-First: O.
Author-X-Name-Last: Briant
Author-Name: J. Summers
Author-X-Name-First: J.
Author-X-Name-Last: Summers
Title: A cost estimation model to support automation decision in assembly systems design
Abstract: 
 Cost analysis is crucial in the design of assembly systems and the decision on their level of automation (LoA). This paper presents a cost estimation model of assembly system that is used to decide their LoA during the early phase of projects. Based on an extensive literature review, a complete cost model integrating multiple cost drivers is proposed. This model is then exploited to create the objective function of an integer linear programme model utilised to solve the LoA decision problem. The work provides a way to perform cost estimation of assembly systems alternatives and to decide the most appropriate LoA in assembly. The cost estimation model is built with a parametric approach allowing the definition of various optimisation objectives. The proposed integer programme, complement this approach by proposing the suitable constraints set, that describes the LoA decision problem.
Journal: International Journal of Production Research
Pages: 7426-7443
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1486050
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1486050
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Sunderesh S. Heragu
Author-X-Name-First: Sunderesh S.
Author-X-Name-Last: Heragu
Author-Name: Semyon M. Meerkov
Author-X-Name-First: Semyon M.
Author-X-Name-Last: Meerkov
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Design for manufacturing and assembly/disassembly: joint design of products and production systems
Abstract: 
 Design for Manufacturing, Assembly, and Disassembly is important in today’s production systems because if this aspect is not considered, it could lead to inefficient operations and excessive material usage, both of which have a significant impact on manufacturing cost and time. Attention to this topic is important in achieving the target standards of Industry 4.0 which is inclusive of material utilisation, manufacturing operations, machine utilisation, features selection of the products, and development of suitable interfaces with information communication technologies (ICT) and other evolving technologies. Design for manufacturing (DFM) and Design for Assembly (DFA) have been around since the 1980’s for rectifying and overcoming the difficulties and waste related to the manufacturing as well as assembly at the design stage. Furthermore, this domain includes a decision support system and knowledge base with manufacturing and design guidelines following the adoption of ICT. With this in mind, ‘Design for manufacturing and assembly/disassembly: Joint design of products and production systems’, a special issue has been conceived and its contents are elaborated in detail. In this paper, a background of the topics pertaining to DFM, DFA and related topics seen in today’s manufacturing systems are discussed. The accepted papers of this issue are categorised in multiple sections and their significant features are outlined.
Journal: International Journal of Production Research
Pages: 7181-7189
Issue: 24
Volume: 56
Year: 2018
Month: 12
X-DOI: 10.1080/00207543.2018.1549795
File-URL: http://hdl.handle.net/10.1080/00207543.2018.1549795
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Template-Type: ReDIF-Article 1.0
Author-Name: Antonella Meneghetti
Author-X-Name-First: Antonella
Author-X-Name-Last: Meneghetti
Author-Name: Sara Ceschia
Author-X-Name-First: Sara
Author-X-Name-Last: Ceschia
Title: Energy-efficient frozen food transports: the Refrigerated Routing Problem
Abstract: 
 Given the growing importance of cold chains and the need to promote sustainable processes, energy efficiency in refrigerated transports is investigated at operational level. The Refrigerated Routing Problem is defined, involving multi-drop deliveries of palletised unit loads of frozen food from a central depot to clients. The objective is to select the route with minimum fuel consumption for both traction and refrigeration. The problem formulation considers speed variation due to traffic congestion phenomena, as well as decreasing load on board along the route as successive clients are visited. Transmission load for exposure of the vehicle to outdoor temperatures and infiltration load at door opening are modelled, taking into account outdoor conditions varying along the day and the year. The resulting multi-period problem is modelled and solved by means of Constraint Programming. Test scenarios come from a real local network for frozen bread dough distributed to supermarkets. Results show how fuel minimisation leads to the selection of different routes in comparison to the traditional total travel distance or time objectives. Energy savings are affected by demand distribution among the clients, departure time, number of visits per tour, seasonality and location of the delivery network.
Journal: International Journal of Production Research
Pages: 4164-4181
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1640407
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1640407
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Template-Type: ReDIF-Article 1.0
Author-Name: Nadia Ndhaief
Author-X-Name-First: Nadia
Author-X-Name-Last: Ndhaief
Author-Name: Rezg Nidhal
Author-X-Name-First: Rezg
Author-X-Name-Last: Nidhal
Author-Name: Adnène Hajji
Author-X-Name-First: Adnène
Author-X-Name-Last: Hajji
Author-Name: Olivier Bistorin
Author-X-Name-First: Olivier
Author-X-Name-Last: Bistorin
Title: Environmental issue in an integrated production and maintenance control of unreliable manufacturing/remanufacturing systems
Abstract: 
 This paper addresses a joint production and maintenance problem under environmental constraints and reliability issues in a manufacturing/remanufacturing context. The manufacturing system is composed of one machine producing one type of product. The remanufacturing system, also composed of one machine, retrieves returned products from the market in order to refurbish them. The manufacturing and remanufacturing systems aim to satisfy random demands under a given service level. Moreover, the entire system generates harmful emissions. Exceeding carbon emission limits defined by authorities may risk sanctions. We aim to propose a compromise between ecologic and economic production and maintenance plan by calling on green subcontracting in order to satisfy the demand and avoid emission excess. Three models are proposed in this paper. These models tackle mainly the basic production problems and propose alternative equivalent solution schemas for future extensions. The robustness and usefulness of the proposals are illustrated with various examples and sensitivity analyses.
Journal: International Journal of Production Research
Pages: 4182-4200
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1650212
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1650212
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Template-Type: ReDIF-Article 1.0
Author-Name: Imen Harbaoui Dridi
Author-X-Name-First: Imen
Author-X-Name-Last: Harbaoui Dridi
Author-Name: Essia Ben Alaïa
Author-X-Name-First: Essia
Author-X-Name-Last: Ben Alaïa
Author-Name: Pierre Borne
Author-X-Name-First: Pierre
Author-X-Name-Last: Borne
Author-Name: Hanen Bouchriha
Author-X-Name-First: Hanen
Author-X-Name-Last: Bouchriha
Title: Optimisation of the multi-depots pick-up and delivery problems with time windows and multi-vehicles using PSO algorithm
Abstract: 
 Many sectors in the transport industry are concerned about the vehicle routing problem (VRP), hence the growing interest of researchers for this type of problem and its variants. This is due essentially to its many real applications in logistics for the transport of goods. The originality and contribution of our work is that we have dealt a problem that combines several variants: multiple vehicles (m), multiple depots (MD), pickup and delivery problem (PDP) with time windows (TW). Hence the notation of our problem: m-MDPDPTW. In this paper, we present the m-MDPDPTW, which is an optimisation problem belonging to the category of NP Hard problems. This problem must meet requests for transport between customers and suppliers satisfying precedence, capacity and time constraints. The goal is to find the best solution, which is the best route minimising the total travelled distance. To solve and optimise our m-MDPDPTW, we have developed a new algorithm based on the particle swarm optimisation (PSO) method. The performance of this new approach is tested on data set instances of Li and Lim's benchmark problems in which we have added multiple depot locations. Comparing with prior works, our proposed approach gave better results by decreasing the distance for several studied instances.
Journal: International Journal of Production Research
Pages: 4201-4214
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1650975
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1650975
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Template-Type: ReDIF-Article 1.0
Author-Name: Zijie Tang
Author-X-Name-First: Zijie
Author-X-Name-Last: Tang
Author-Name: Desheng Dash Wu
Author-X-Name-First: Desheng Dash
Author-X-Name-Last: Wu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Option contracts for online celebrities as retailers in supply chains
Abstract: 
 The online celebrity economy, also called the internet celebrity economy, is growing rapidly in China. Celebrity retailers are usually demand sensitive and capital constrained. The capital constraints along with information asymmetry often render supply chains inefficient when manufacturers are producing at non-optimal levels. Few studies have shed light on the online celebrity supply chain, especially with respect to options. In this study, we examine how option contracts can coordinate supply chains. We find that a capital-constrained retailer can achieve more profitable orders when given an option. The manufacturer – without the full information of market demand – also benefits from offering an option to the retailer. Our numerical case shows that the options contract generates different payoffs depending on the capital of the retailer.
Journal: International Journal of Production Research
Pages: 4215-4232
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1650977
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1650977
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Template-Type: ReDIF-Article 1.0
Author-Name: Angela Patricia Velasco Acosta
Author-X-Name-First: Angela Patricia
Author-X-Name-Last: Velasco Acosta
Author-Name: Christian Mascle
Author-X-Name-First: Christian
Author-X-Name-Last: Mascle
Author-Name: Pierre Baptiste
Author-X-Name-First: Pierre
Author-X-Name-Last: Baptiste
Title: Applicability of Demand-Driven MRP in a complex manufacturing environment
Abstract: 
 Push and pull methods have been adopted for specific volume production and uncertainty scenarios in order to plan and control production. The further development of hybrid or integrated methods allows benefit to be drawn from opposing approaches. The literature concerning Demand-Driven Material Requirements Planning (DDMRP) proves its superiority under conditions of internal and external uncertainty for high-volume production compared to the most implemented push method (manufacturing requirements planning MRPII). Companies that have adopted this method, manufacture on average 10–15 parts per product, with 2 or 3 levels of bills of materials. In this paper, we evaluate the applicability of DDMRP in a complex manufacturing environment (e.g. products of four levels of bill of materials) in terms of customer satisfaction and stock levels. Buffered and non-buffered items clustered in seven types of decoupling structures contributed to this complexity. We developed a DDMRP model for planning and execution purposes, which was simulated in ARENA's discrete events software. We analysed the model's on-hand stock and delayed orders. DDMRP works effectively under the manufacturing conditions considered. It is found to prevent inventory stockouts and overstocks, reduce lead time by 41% and reduce stock levels by 18%. The success of this method; however, depends on the strategic positioning of the buffers.
Journal: International Journal of Production Research
Pages: 4233-4245
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1650978
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1650978
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Template-Type: ReDIF-Article 1.0
Author-Name: Yigit Kazancoglu
Author-X-Name-First: Yigit
Author-X-Name-Last: Kazancoglu
Author-Name: Yesim Deniz Ozkan-Ozen
Author-X-Name-First: Yesim Deniz
Author-X-Name-Last: Ozkan-Ozen
Title: Sustainable disassembly line balancing model based on triple bottom line
Abstract: 
 End of life (EOL) phase of a product is receiving more attention due to increase in environmental concerns, and many studies have been conducted for value creation in EOL, focusing on concepts as remanufacturing, reuse and recycling in sustainable production manner. This study especially focuses on one of global problem, e-waste. To minimise the amount of wastes and maximise recovered materials from EOL, disassembly is one of the most important concept, associated with reuse, and balancing disassembly line in an optimal way is essential for organisations. In disassembly line balancing (DLB), not only precedence of tasks, but also risk criteria related to environment and human safety should be considered for sustainability. The aim of this study is to propose a model based on triple bottom line (TBL) dimensions, i.e. human safety, environmental safety and business criteria. To achieve sustainability in DLB, and for risk assessment in sustainable DLB, it had been decided to use a multi-criteria method, i.e. TODIM, acronym in Portuguese of ‘Tomada de Decisão Iterativa Multicritério’. The proposed model included 22 disassembly criteria categorised under TBL dimensions, which are derived from the literature. Implementation of the study was conducted for computer disassembly processes, and as a result of the study approximately 12% an improvement in cycle time was succeeded. In the long run, the integration of sustainability in disassembly operations may contribute to the competitive advantage of the company in terms of differentiation and corporate image by achieving business, environment and human targets simultaneously.
Journal: International Journal of Production Research
Pages: 4246-4266
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1651456
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1651456
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Template-Type: ReDIF-Article 1.0
Author-Name: William Ferrell
Author-X-Name-First: William
Author-X-Name-Last: Ferrell
Author-Name: Kimberly Ellis
Author-X-Name-First: Kimberly
Author-X-Name-Last: Ellis
Author-Name: Phil Kaminsky
Author-X-Name-First: Phil
Author-X-Name-Last: Kaminsky
Author-Name: Chase Rainwater
Author-X-Name-First: Chase
Author-X-Name-Last: Rainwater
Title: Horizontal collaboration: opportunities for improved logistics planning
Abstract: 
 The logistics industry is a critical economic component in most countries and has a significant impact on their citizens' quality of life. In the U.S., 48 million tons of freight valued at more than $46 billion are moved every day and serve 300,000 manufacturing sites, 350,000 warehouses, and 7.5 million businesses. However, the industry is plagued with inefficiencies that can negatively impact corporate profits, the environment, urban congestion, and worker well-being. No single solution will address all of these issues; however, horizontal collaboration appears to offer an opportunity to take a significant step in the right direction. There is an abundance of opportunities for logistics service providers to collaborate, but there is little effective collaboration in practice, and the issues related to this gap remain largely unexplored by academic researchers. This paper offers a review of the existing research in horizontal collaboration, specifically highlighting efforts focussed in the areas of on-demand logistics, freight consolidation, facility sharing, incentives, case studies, and quantitative analyses. A path for pursuing an improved logistics system is offered, and specific research needs in the collaborative logistics field are detailed. We conclude with a discussion of emerging issues that will have immediate impacts on horizontal collaboration efforts.
Journal: International Journal of Production Research
Pages: 4267-4284
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1651457
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1651457
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Template-Type: ReDIF-Article 1.0
Author-Name: Cristina Sancha
Author-X-Name-First: Cristina
Author-X-Name-Last: Sancha
Author-Name: Frank Wiengarten
Author-X-Name-First: Frank
Author-X-Name-Last: Wiengarten
Author-Name: Annachiara Longoni
Author-X-Name-First: Annachiara
Author-X-Name-Last: Longoni
Author-Name: Mark Pagell
Author-X-Name-First: Mark
Author-X-Name-Last: Pagell
Title: The moderating role of temporary work on the performance of lean manufacturing systems
Abstract: 
 Companies are extensively employing lean manufacturing practices and temporary work, which at face value are in stark contrast to each other. While lean manufacturing emphasises the value of workers, temporary work refers to precarious work arrangements that, based on social exchange theory, may harm workers’ commitment. The objective of this paper is to unveil the role of temporary work on the lean manufacturing – operational performance (i.e. cost, quality, delivery, flexibility) relationship. To answer our research question and test our hypotheses we utilise cross-country data collected through the sixth iteration of the International Manufacturing Strategy Survey and conduct multilevel regression analysis. Our results indicate that while lean manufacturing improves operational performance, the use of temporary work positively influences the relationship between lean manufacturing and mix and volume flexibility performance.
Journal: International Journal of Production Research
Pages: 4285-4305
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1651458
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1651458
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcos Pueo
Author-X-Name-First: Marcos
Author-X-Name-Last: Pueo
Author-Name: Jorge Santolaria
Author-X-Name-First: Jorge
Author-X-Name-Last: Santolaria
Author-Name: Raquel Acero
Author-X-Name-First: Raquel
Author-X-Name-Last: Acero
Author-Name: Jorge Sierra-Pérez
Author-X-Name-First: Jorge
Author-X-Name-Last: Sierra-Pérez
Title: Design methodology for production systems retrofit in SMEs
Abstract: 
 Investment in the productive systems of small and medium-sized enterprises (SMEs) in the manufacturing sector is usually quite limited. For this reason, normal practice is to apply minor developments internally or upgrade equipment as it becomes obsolete to increase their productive capacity and competitiveness at a lower cost. However, the work team, mostly made up of engineers, does not usually have experience in the use of design methodologies but also they are often familiar with the functioning of various design and quality-management tools. This paper presents a clear and simple design methodology that facilitates the development of adaptations to items of equipment that might be considered one-off products. It includes a selection of design tools that are, according to the literature on the subject, the most common and best-known among engineers, and which are also best-suited to the environment of an SME. The design methodology was validated experimentally with the upgrading of a gear-rolling tester installed on the premises of an SME in the sector. The recommended techniques and tools were satisfactory applied opening the possibilities for further application of the methodology in similar machine’s upgrades in the future.
Journal: International Journal of Production Research
Pages: 4306-4324
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1651460
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1651460
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Template-Type: ReDIF-Article 1.0
Author-Name: Morteza Yazdani
Author-X-Name-First: Morteza
Author-X-Name-Last: Yazdani
Author-Name: Dragan Pamucar
Author-X-Name-First: Dragan
Author-X-Name-Last: Pamucar
Author-Name: Prasenjit Chatterjee
Author-X-Name-First: Prasenjit
Author-X-Name-Last: Chatterjee
Author-Name: Shankar Chakraborty
Author-X-Name-First: Shankar
Author-X-Name-Last: Chakraborty
Title: Development of a decision support framework for sustainable freight transport system evaluation using rough numbers
Abstract: 
 Among various operational decision-making tasks in a transportation system, sustainable performance evaluation has a very promising and direct influence on the community as well as environment. To prevent and reduce the negative impacts of a freight transportation system, a constant monitoring and performance measurement system has of paramount significance in the process of supply chain management. However, studies of complex transport evaluation systems are very scarce in the existing literature. This paper aims to resolve the problem of freight transport system’s performance measurement while developing a comprehensive framework with incorporation of sustainable elements and establishing a rough set-based decision-making approach. The applicability of the proposed framework is investigated to evaluate the performance of seven freight transportation companies in Spain. A decision support tool is designed by integrating rough number-based decision-making trial and evaluation laboratory (DEMATEL) and multi-attributive border approximation area comparison (MABAC) methods for their performance appraisal. Sensitivity analysis and comparison with other popular methods are also performed to validate the efficacy of the proposed approach. It is established that rough number-based methodologies have advantages over fuzzy or interval-based models.
Journal: International Journal of Production Research
Pages: 4325-4351
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1651945
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1651945
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Template-Type: ReDIF-Article 1.0
Author-Name: Li Li
Author-X-Name-First: Li
Author-X-Name-Last: Li
Author-Name: Junqi Liu
Author-X-Name-First: Junqi
Author-X-Name-Last: Liu
Author-Name: Lei Zhu
Author-X-Name-First: Lei
Author-X-Name-Last: Zhu
Author-Name: Xiao-Bing Zhang
Author-X-Name-First: Xiao-Bing
Author-X-Name-Last: Zhang
Title: How to design a dynamic feed-in tariffs mechanism for renewables – a real options approach
Abstract: 
 Feed-in tariffs (FITs) are among the most favoured policies with which to drive the deployment of renewable energy. This paper offers insights into quantifying dynamic FITs to realise the expected installed capacity target with minimum policy cost under uncertainties of renewable intermittence and technology learning. We incorporate real options and use stochastic dynamic programming to model the strategic behaviour between policy-maker and investor and extend the one-time investment decision described by Farrell et al. [2017. ‘Specifying an Efficient Renewable Energy Feed-in Tariff.’ The Energy Journal 38: 53–75] to multiple-period decisions. An approach that combines binary tree scenario generation and a least squares Monte Carlo method is used to numerically identify the optimal FITs plan in practice. China’s offshore wind power investment is used as a case study to investigate the relationships among the optimal dynamic FITs level, the total policy cost, the expected capacity target, and the learning effect. The simulation results demonstrate that our proposed dynamic FITs can track the changes in technology learning well and that they can avoid the inefficiency of fixed FITs in stimulating technology adoption in the initial periods, along with overpayment by the policy-maker.
Journal: International Journal of Production Research
Pages: 4352-4366
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1652776
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1652776
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Template-Type: ReDIF-Article 1.0
Author-Name: Kun Wang
Author-X-Name-First: Kun
Author-X-Name-Last: Wang
Author-Name: Yiming Yang
Author-X-Name-First: Yiming
Author-X-Name-Last: Yang
Author-Name: Ruixue Li
Author-X-Name-First: Ruixue
Author-X-Name-Last: Li
Title: Travel time models for the rack-moving mobile robot system
Abstract: 
 The rack-moving mobile robot (RMMR) system is a special parts-to-picker automated warehousing system that uses hundreds of rack-moving machines to accomplish the repetitive tasks of storing and retrieving parts by lifting and transporting unit racks autonomously. This paper investigates the operation cycle of the rack-moving machine for storage and retrieval from the perspective of the lane depth, especially exploring the particularity of the RMMR system in multi-deep lanes, and proposes expected travel time models of the rack-moving machine for single- and multi-deep layouts of the RMMR system. To validate the effectiveness of the proposed models, an experimental simulation was conducted with a 1–4-deep layout under six scenarios of different numbers of aisles and layers, and results were compared with results obtained using proposed models. The paper presents useful guidelines for the configuration of the RMMR system layout including the determination of the optimal lane depth.
Journal: International Journal of Production Research
Pages: 4367-4385
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1652778
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1652778
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Template-Type: ReDIF-Article 1.0
Author-Name: Frederik Ferid Ostermeier
Author-X-Name-First: Frederik Ferid
Author-X-Name-Last: Ostermeier
Title: The impact of human consideration, schedule types and product mix on scheduling objectives for unpaced mixed-model assembly lines
Abstract: 
 There is an increasing awareness in scheduling research that human behaviour needs to be considered explicitly in scheduling models. Although most scheduling literature ignores human behaviour, especially sequence-dependent processing times form a good basis for explicit consideration. Hence, a processing time function is derived that considers the effects of learning, forgetting, fatigue and recovery. The necessity for explicit human consideration can be regarded as most urgent for unpaced highly-manual mixed-model assembly lines. Based on real data a simulation study is conducted to determine the effect of explicit human consideration while also taking into account the effects of different idealised schedule types and the product mix. The results strongly indicate that the product mix has a consistently high impact on scheduling objectives, the schedule type affects lower-level objectives like starving and blocking times to a greater extent than higher-level objectives like makespan and flow time, and that for certain objectives the height of the objective values and the relative favourability of schedule types depends on human consideration.
Journal: International Journal of Production Research
Pages: 4386-4405
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1652780
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1652780
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Template-Type: ReDIF-Article 1.0
Author-Name: Guiliang Gong
Author-X-Name-First: Guiliang
Author-X-Name-Last: Gong
Author-Name: Raymond Chiong
Author-X-Name-First: Raymond
Author-X-Name-Last: Chiong
Author-Name: Qianwang Deng
Author-X-Name-First: Qianwang
Author-X-Name-Last: Deng
Author-Name: Xuran Gong
Author-X-Name-First: Xuran
Author-X-Name-Last: Gong
Title: A hybrid artificial bee colony algorithm for flexible job shop scheduling with worker flexibility
Abstract: 
 The traditional flexible job shop scheduling problem (FJSP) considers machine flexibility but not worker flexibility. Given the influence and potential of human factors in improving production efficiency and decreasing the cost in practical production systems, we propose a mathematical model of an extended FJSP with worker flexibility (FJSPW). A hybrid artificial bee colony algorithm (HABCA) is presented to solve the proposed FJSPW. For the HABCA, effective encoding, decoding, crossover and mutation operators are designed, and a new effective local search method is developed to improve the speed and exploitation ability of the algorithm. The Taguchi method of Design of Experiments is used to obtain the best combination of key parameters of the HABCA. Extensive computational experiments carried out to compare the HABCA with some well-performing algorithms from the literature confirm that the proposed HABCA is more effective than these algorithms, especially on large-scale FJSPW instances.
Journal: International Journal of Production Research
Pages: 4406-4420
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1653504
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1653504
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Template-Type: ReDIF-Article 1.0
Author-Name: Harshal Lowalekar
Author-X-Name-First: Harshal
Author-X-Name-Last: Lowalekar
Author-Name: Sumanta Basu
Author-X-Name-First: Sumanta
Author-X-Name-Last: Basu
Title: Theory of constraints based mafia offer for supply chains of deteriorating products
Abstract: 
 Mafia offer is an unbelievably good offer that a company makes to its customers; the attractiveness of the offer makes it impossible for the customers to decline the offer and difficult for the competitors to match it [Cox, James, III, and John Schleier. 2010. Theory of Constraints Handbook. McGraw-Hill]. This study analyses the performance of one such offer that a producer of deteriorating items can make to its customers in the supply chain, such as retailers and distributors. The results from the analytical model show that the mafia offer increases the profits of both the producer and the retailer in a deteriorating items' supply chain. The efficacy of the proposed offer is tested for multiple combinations of ordering cost, wholesale price, and the retailer's cash constraints. The experimental results suggest that the producer would be able to increase its profits by more than 60%, for a given level of retailer's profits, owing to the mafia offer. The availability of the existing items offered by the retailer will increase significantly, despite a reduction in the retailer's inventory levels. The offer will result in an average increase of over 56% in the variety of items held by the retailer. The producer will also be able to command significantly higher margins (more than 44%) from the retailer for the existing items without adversely affecting the retailer's profitability.
Journal: International Journal of Production Research
Pages: 4421-4449
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1654629
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1654629
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Template-Type: ReDIF-Article 1.0
Author-Name: Zied Hajej
Author-X-Name-First: Zied
Author-X-Name-Last: Hajej
Author-Name: Nidhal Rezg
Author-X-Name-First: Nidhal
Author-X-Name-Last: Rezg
Title: An optimal integrated lot sizing and maintenance strategy for multi-machines system with energy consumption
Abstract: 
 This paper proposes an integrated model for multi-machines dynamic lot sizing aiming to produce a single item, considering the energy consumption during the production horizon. The objective is to find, firstly, the optimal lot size as well as the number of machines that satisfy a random demand under given service level and secondly, maintenance plan depended to production planning to minimise the total production, energy and maintenance costs. In fact, the problem of energy consumption is one of the most evoked topics especially with the decision of many governments to reduce theirs (For example France is willing to reduce the total consumption by 20% by 2020). The keys of this study are to consider, firstly, the correlation between the forecasting of demand, the variation of the working machines as well as their production rates under energy constraint and secondly the correlation between the production cadences and the maintenance strategy of all machines.
Journal: International Journal of Production Research
Pages: 4450-4470
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1654630
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1654630
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Template-Type: ReDIF-Article 1.0
Author-Name: Sihan Huang
Author-X-Name-First: Sihan
Author-X-Name-Last: Huang
Author-Name: Yan Yan
Author-X-Name-First: Yan
Author-X-Name-Last: Yan
Title: Design of delayed reconfigurable manufacturing system based on part family grouping and machine selection
Abstract: 
 To improve the convertibility of reconfigurable manufacturing system (RMS), the concept of delayed reconfigurable manufacturing system (D-RMS) was proposed. RMS and D-RMS are both constructed around part family. However, D-RMS may suffer from ultra-long system problem with unacceptable idle machines using generic RMS part families. Besides, considering the complex basic system structure of D-RMS, machine selection of D-RMS should be addressed, including dedicated machine, flexible machine, and reconfigurable machine. Therefore, a system design method for D-RMS based on part family grouping and machine selection is proposed. Firstly, a part family grouping method is proposed for D-RMS that groups the parts with more former common operations into the same part family. The concept of longest relative position common operation subsequence (LPCS) is proposed. The similarity coefficient among the parts is calculated based on LPCS. The reciprocal value of the operation position of LPCS is adopted as the characteristic value. The average linkage clustering (ALC) algorithm is used to cluster the parts. Secondly, a machine selection method is proposed to complete the system design of D-RMS, including machine selection rules and the dividing point decision model. Finally, a case study is given to implement and verify the proposed system design method for D-RMS. The results show that the proposed system design method is effective, which can group parts with more former common operations into the same part family and select appropriate machine types.
Journal: International Journal of Production Research
Pages: 4471-4488
Issue: 14
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1654631
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1654631
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Template-Type: ReDIF-Article 1.0
Author-Name: Mitali Sarkar
Author-X-Name-First: Mitali
Author-X-Name-Last: Sarkar
Author-Name: Byung Do Chung
Author-X-Name-First: Byung Do
Author-X-Name-Last: Chung
Title: Flexible work-in-process production system in supply chain management under quality improvement
Abstract: 
 For a complex product production, any flexible manufacturing system with a work-in-process inventory is recommended for a supply chain management (SCM) system. Building a flexible manufacturing system increases the total cost of the supply chain; for this reason, a discrete investment is important. For flexible production systems, production rate within a finite specific interval of production rate as work-in-process inventory is calculated. The aim of the supply chain is to reduce the total cost when demand during the lead time is a random variable with a normal distribution. A crashing cost is utilised to reduce the duration of lead time within the supply chain system. A model is proposed to obtain the optimal flexible production rate with the reduced total cost of the supply chain. A classical optimisation technique is employed to obtain the closed-form and quasi-closed-form solutions of the decision variables. An improved algorithm is designed to obtain the global minimum cost of SCM under the framework of a flexible production system. An illustrative numerical example and sensitivity analysis are given to test the model. A numerical study proves that this model obtains the minimum cost with the optimal decision variables.
Journal: International Journal of Production Research
Pages: 3821-3838
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1634851
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634851
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Template-Type: ReDIF-Article 1.0
Author-Name: Yangyang Liang
Author-X-Name-First: Yangyang
Author-X-Name-Last: Liang
Author-Name: Nanfang Cui
Author-X-Name-First: Nanfang
Author-X-Name-Last: Cui
Author-Name: Xuejun Hu
Author-X-Name-First: Xuejun
Author-X-Name-Last: Hu
Author-Name: Erik Demeulemeester
Author-X-Name-First: Erik
Author-X-Name-Last: Demeulemeester
Title: The integration of resource allocation and time buffering for bi-objective robust project scheduling
Abstract: 
 In the recent decades, the recognition that uncertainty lies at the heart of modern project management has induced considerable research efforts on robust project scheduling for dealing with uncertainty in a scheduling environment. The literature generally provides two main strategies for the development of a robust predictive project schedule, namely robust resource allocation and time buffering. Yet, the previous studies seem to have neglected the potential benefits of an integration between the two. Besides, few efforts have been made to protect simultaneously the project due date and the activity start times against disruptions during execution, which is desperately demanded in practice. In this paper, we aim at constructing a proactive schedule that is not only short in time but also less vulnerable to disruptions. Firstly, a bi-objective optimisation model with a proper normalisation of the two components is proposed in the presence of activity duration variability. Then a two-stage heuristic algorithm is developed which deals with a robust resource allocation problem in the first stage and optimally determines the position and the size of time buffers using a simulated annealing algorithm in the second stage. Finally, an extensive computational experiment on the PSPLIB network instances demonstrates the superiority of the combination between resource allocation and time buffering as well as the effectiveness of the proposed two-stage algorithm for generating proactive project schedules with composite robustness.
Journal: International Journal of Production Research
Pages: 3839-3854
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1636319
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1636319
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Template-Type: ReDIF-Article 1.0
Author-Name: Marco Caserta
Author-X-Name-First: Marco
Author-X-Name-Last: Caserta
Author-Name: Stefan Voß
Author-X-Name-First: Stefan
Author-X-Name-Last: Voß
Title: A general corridor method-based approach for capacitated facility location
Abstract: 
 The Capacitated Facility Location Problem (CFLP) is a well-known optimisation problem with applications in a number of fields, such as distribution system planning, telecommunication network design, and supply chain design. The goal of this paper is to present a matheuristic algorithm based on the corridor method, to develop a general algorithm for a number of variants of the CFLP. The algorithm exploits solutions obtained via Lagrangean relaxation and builds corridors around such solutions via the introduction of constraints around the incumbent solution, used to limit the size of the solution space explored at each iteration. A thorough exploration of the neighbourhoods induced by the corridors is carried out using a mixed integer programming (MIP) solver. More precisely, we solve to (near) optimality over 500 benchmark instances, using the single-source as well as the multi-source formulations, both in the nominal variant, i.e. the deterministic version of the problem, and the robust variant, i.e. the version obtained when using robust optimisation to model the uncertainty of the problem parameters. The performance of the algorithm is highly competitive when compared with the best approaches proposed in the literature for each variant of the CFLP, especially considering that the algorithm has not been designed with a specific CFLP formulation in mind.
Journal: International Journal of Production Research
Pages: 3855-3880
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1636320
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1636320
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandros Diamantidis
Author-X-Name-First: Alexandros
Author-X-Name-Last: Diamantidis
Author-Name: Jun-Ho Lee
Author-X-Name-First: Jun-Ho
Author-X-Name-Last: Lee
Author-Name: Chrissoleon T. Papadopoulos
Author-X-Name-First: Chrissoleon T.
Author-X-Name-Last: Papadopoulos
Author-Name: Jingshan Li
Author-X-Name-First: Jingshan
Author-X-Name-Last: Li
Author-Name: Cathal Heavey
Author-X-Name-First: Cathal
Author-X-Name-Last: Heavey
Title: Performance evaluation of flow lines with non-identical and unreliable parallel machines and finite buffers
Abstract: 
 This paper examines serial production lines with unreliable non-identical parallel machines at each workstation and intermediate buffers with finite capacities. All machines are assumed to have exponential service times, times to failure and repair times. An efficient decomposition technique is introduced for the performance evaluation of such lines. Rather than replacing each parallel-machine workstation with an equivalent single-server workstation, the main contribution of this paper is the presentation of a direct approach to derive and apply decomposition equations directly for every parallel machine at each workstation. Experimental results indicate that such a method can provide a computationally efficient algorithm to analyse large serial unreliable multi-server production lines with a good accuracy compared against simulation and other available methods.
Journal: International Journal of Production Research
Pages: 3881-3904
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1636322
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1636322
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Template-Type: ReDIF-Article 1.0
Author-Name: Leilei Meng
Author-X-Name-First: Leilei
Author-X-Name-Last: Meng
Author-Name: Chaoyong Zhang
Author-X-Name-First: Chaoyong
Author-X-Name-Last: Zhang
Author-Name: Xinyu Shao
Author-X-Name-First: Xinyu
Author-X-Name-Last: Shao
Author-Name: Biao Zhang
Author-X-Name-First: Biao
Author-X-Name-Last: Zhang
Author-Name: Yaping Ren
Author-X-Name-First: Yaping
Author-X-Name-Last: Ren
Author-Name: Wenwen Lin
Author-X-Name-First: Wenwen
Author-X-Name-Last: Lin
Title: More MILP models for hybrid flow shop scheduling problem and its extended problems
Abstract: 
 With the rapid development of computer technology and related softwares for mathematical models, mathematical modelling of scheduling problems is receiving growing attention from researchers. In this work, the hybrid flow shop scheduling problem with unrelated parallel machines (HFSP-UPM) with the objective aimed to minimise the makespan is studied. According to the characteristics of the HFSP-UPM, eight mixed integer linear programming (MILP) models are formulated in order to obtain optimal solutions based on different modelling ideas. Then, these models are extended to solve HFSP-UPM with sequence-dependent setup times (HFSP-UPM-SDST), no-wait HFSP-UPM (HFSP-UPM-NW) and HFSP-UPM with blocking (HFSP-UPM-B). All the proposed models and the existing model are detailedly compared and evaluated under three aspects namely modelling process, size complexity and computational complexity. Numerical experiments show that MILP models dependent on diverse modelling ideas perform very differently. The model developed based on stage precedence is the best one and should be given preference in future applications. In addition, the proposed models of HFSP-UPM-NW and HFSP-UPM-B improve several best known solutions for the test instances in the existing literature.
Journal: International Journal of Production Research
Pages: 3905-3930
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1636324
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1636324
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Template-Type: ReDIF-Article 1.0
Author-Name: Zheng Wang
Author-X-Name-First: Zheng
Author-X-Name-Last: Wang
Author-Name: Hongzhan Ma
Author-X-Name-First: Hongzhan
Author-X-Name-Last: Ma
Author-Name: Hansi Chen
Author-X-Name-First: Hansi
Author-X-Name-Last: Chen
Author-Name: Bo Yan
Author-X-Name-First: Bo
Author-X-Name-Last: Yan
Author-Name: Xuening Chu
Author-X-Name-First: Xuening
Author-X-Name-Last: Chu
Title: Performance degradation assessment of rolling bearing based on convolutional neural network and deep long-short term memory network
Abstract: 
 Many traditional approaches for performance degradation assessment of rolling bearings, using sensor data, make assumptions about how they degrade or fault evolve. However, the sequential sensor data cannot be directly taken as input in the traditional models since the data always contain noise and change in length. To solve these problems, a convolutional neural network and deep long-short term memory (CNN-DLSTM) based architecture is proposed to obtain an unsupervised H-statistic for performance degradation assessment of rolling bearing using sensor time-series data. Firstly, a CNN is applied to extract local abstract features from raw sensor data. Secondly, a deep LSTM is explored to extract temporal features. CNN-DLSTM is trained to reconstruct the time-series sensor signal reflecting the health condition of rolling bearing. The D- and Q-statistic are used to compute H-statistic which is then used for performance degradation assessment. The proposed approach is evaluated on an experiment with rolling bearings and the results are presented on a public dataset of rolling bearing, verifying that the proposed approach outperforms several state-of-the-art methods.
Journal: International Journal of Production Research
Pages: 3931-3943
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1636325
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1636325
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Template-Type: ReDIF-Article 1.0
Author-Name: José Antonio Larco Martinelli
Author-X-Name-First: José Antonio
Author-X-Name-Last: Larco Martinelli
Author-Name: Jan Fransoo
Author-X-Name-First: Jan
Author-X-Name-Last: Fransoo
Author-Name: Amir Gharehgozli
Author-X-Name-First: Amir
Author-X-Name-Last: Gharehgozli
Author-Name: Vincent Wiers
Author-X-Name-First: Vincent
Author-X-Name-Last: Wiers
Title: The scheduler’s balancing act of sensing and reacting: a behavioural perspective on scheduling
Abstract: 
 The scheduler has been extensively studied from the point of view of their schedules, using operations research. However, the scheduler not only fulfils a decision-maker role but also an informational role, responding to requests and disruptions, both from the supply and the demand side. Responding in a timely manner to such requests and disruptions is paramount for the scheduling job. Using a field study with job shadowing of schedulers in a Fortune 500 chemical company, we characterise the scheduler’s workflow in a simulation model; this allows us to discriminate between contextual factors of the scheduler’s job and behavioural factors inherent to them. Furthermore, it explicitly assesses the effect of increasing the frequency sensing of the outer world on responsiveness. Our findings show that the studied schedulers prioritise sensing activities related to checking emails rather than monitoring for disruptions in a decision support system. Thus, we find a higher potential for relative improvement in terms of responding to possible disruptions shown in decision support systems rather than responding to email requests. Moreover, we show that by adjusting email frequency checking and preemption behaviours, it is possible to revert an out of control situation to finite response times.
Journal: International Journal of Production Research
Pages: 3944-3955
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1636326
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1636326
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Template-Type: ReDIF-Article 1.0
Author-Name: Yael Perlman
Author-X-Name-First: Yael
Author-X-Name-Last: Perlman
Author-Name: Uri Yechiali
Author-X-Name-First: Uri
Author-X-Name-Last: Yechiali
Title: On tandem stochastic networks with time-deteriorating product quality
Abstract: 
 We consider an n-site tandem stochastic production network where each product moves sequentially through the sites, and the product's quality deteriorates with its sojourn time in the system. At each site the product goes through two stages: the first stage is a processing operation with a generally-distributed random duration. This operation either does or does not conclude successfully; in the latter case, the operation is repeated immediately. Once the processing operation concludes successfully, the product goes through an inspection stage lasting a generally-distributed random duration. At the end of the inspection the product's state is determined as follows: either (i) it requires additional processing and moves forward to the next site; or (ii) it is found ‘good’ and exits the network with quality value depending on its total sojourn time in the system; or (iii) it is declared ‘failed’, discarded, and exits the network with zero quality value. Two scenarios are analysed: (i) a new product enters the system only after the preceding product has exited and (ii) the network is a tandem Jackson-type system. For each scenario, we construct both time-dependent and quality-dependent performance measures. In the case where the sites can be arranged in an arbitrary order, we derive easy to implement optimal index-type policies of ordering the sites so as to maximise the quality rate of the production network.
Journal: International Journal of Production Research
Pages: 3956-3964
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1637034
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1637034
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Template-Type: ReDIF-Article 1.0
Author-Name: Erwin Pesch
Author-X-Name-First: Erwin
Author-X-Name-Last: Pesch
Author-Name: Katarzyna Anna Kuzmicz
Author-X-Name-First: Katarzyna Anna
Author-X-Name-Last: Kuzmicz
Title: Non-approximability of the single crane container transhipment problem
Abstract: 
 The makespan of operations at container terminals is crucial for the lead time of cargo and consequently the reduction of transportation costs. Therefore, an efficient transhipment and short storage of containers are demanded. Our paper refers to the consolidation process of trains in a container transhipment terminal as well as to the intermediate storage of containers in seaports in order to accelerate the loading and unloading of the vessels. It can also be encountered in automated storage/retrieval systems. Each of these (container) storage and retrieval moves corresponds to a crane operation, carrying a load from its pickup to its drop-off position. The problem is to find a permutation of the loaded crane moves that minimises the total empty crane travel time, which is the sum of times the crane needs to get from the last drop-off point of a load to the next pickup point of a load. We address the problem as an extension of an asymmetric travelling salesman problem (ATSP), assuming that n ordered pairs of points in the two-dimensional Euclidean space need to be traversed. Each point corresponds to a crane operation carrying a load from its pickup to its drop-off position. Despite that the problem seems to be easier than the ATSP, because a simple constant factor approximation exists, which was for a long time an open question for the ATSP, we are the first to prove that there is no polynomial-time approximation algorithm with an approximation guarantee less than  $1+{0.23}/{n} $1+0.23/n unless  $\textsc{P}=\textsc{NP} $P=NP.
Journal: International Journal of Production Research
Pages: 3965-3975
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1637036
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1637036
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhaofu Hong
Author-X-Name-First: Zhaofu
Author-X-Name-Last: Hong
Author-Name: Yunrong Zhang
Author-X-Name-First: Yunrong
Author-X-Name-Last: Zhang
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Dynamic pricing for remanufacturing within socially environmental incentives
Abstract: 
 We study a dual-product dynamic pricing problem for a remanufacturing system in which a manufacturer makes new and remanufactured products competing for a certain market share. The socially environmental incentives, consisting of consumers' environmentally conscious demand and governments' subsidy on remanufactured products, are considered in this study, which encourage the manufacturer to exert production effort toward environmentally friendly remanufacturing. Three models, namely, two-period, multi-period, and infinite-period scenarios, are formulated to investigate the dynamic pricing problem. Analytical results show that the government's subsidy policies, which provide subsidies to consumers or firms, have equivalent effects for the manufacturer in terms of production and profit. Consumers' environmental consciousness and government subsidy are effective incentives to induce the manufacturer to make more remanufactured products. Some threshold policies are proposed to provide decision supports for manufacturers to formulate pricing and production strategies. By comparing the pricing and production strategies of the three models, we find it interesting that the pricing and production strategies of the multi-period model can be ideally characterised by those of the two-period and infinite-period models. This managerial concept is valuable for manufacturers in formulating pricing and production strategies when the precise production planning horizon is unknown.
Journal: International Journal of Production Research
Pages: 3976-3997
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1637037
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1637037
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcello Braglia
Author-X-Name-First: Marcello
Author-X-Name-Last: Braglia
Author-Name: Roberto Gabbrielli
Author-X-Name-First: Roberto
Author-X-Name-Last: Gabbrielli
Author-Name: Leonardo Marrazzini
Author-X-Name-First: Leonardo
Author-X-Name-Last: Marrazzini
Title: Rolling Kanban: a new visual tool to schedule family batch manufacturing processes with kanban
Abstract: 
 Rolling Kanban is the name of a kanban management methodology for batch processes manufacturing environment. Proposed in the early 2000s by FESTO Consulting, for two decades we have lost knowledge both from operative and scientific point of view. Basically, Rolling Kanban means a visual planning methodology based on the production of product-families and variants where: (i) set-up times are reduced between the products of the same family, and (ii) relevant times (dozens of minutes if not even hours) must be considered for changeover between products of different families. In addition, the cyclic production sequence between different product families cannot be maintained. Considering that very few technical information and documents are available about this approach, the main objective of this paper is to retrieve and present, for the first time to the scientific community, the Rolling Kanban methodology. Besides, a real industrial implementation concerning a manufacturer of domestic fittings is discussed as a case study. More specifically, two novel versions of the original Rolling Kanban technique are fully presented to effectively overcome certain limits and criticalities found during its operative use, such as the difficulty to realise a pull production, considering increased set-up time for changeover between products of different families.
Journal: International Journal of Production Research
Pages: 3998-4014
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1639224
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1639224
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Template-Type: ReDIF-Article 1.0
Author-Name: Lei Xiao
Author-X-Name-First: Lei
Author-X-Name-Last: Xiao
Author-Name: Tangbin Xia
Author-X-Name-First: Tangbin
Author-X-Name-Last: Xia
Author-Name: Ershun Pan
Author-X-Name-First: Ershun
Author-X-Name-Last: Pan
Author-Name: Xinghui Zhang
Author-X-Name-First: Xinghui
Author-X-Name-Last: Zhang
Title: Long-term predictive opportunistic replacement optimisation for a small multi-component system using partial condition monitoring data to date
Abstract: 
 The advanced condition monitoring tools and sensors have changed the decision making on maintenance in modern manufacturing. To face the change, an integrated ‘prognostics-replacement’ framework is proposed to optimise the replacement decision from component-level layer into production system-level layer by using condition monitoring data in this paper. Some special situations such as no failure or suspension histories of many of same or similar components for prognosis, etc., are considered. A novel degradation prediction model is introduced and the failure risk of a component is estimated based on its degradation level and service time. A total current-term cost rate function is defined to determine the replacement clusters and time for performing replacement from an integrated and economic view. A conservative window is used to adjust the replacement time and overcome the prognostic results varying at different inspection time in a long task. To optimise the replacement clusters effectively, a random-keys genetic algorithm (GA) based on convex set theory is developed. The proposed framework is validated by different small systems. Two commonly adopted replacement policies are compared. Sensitive analysis is conducted and the results show the outperformance of our proposed framework.
Journal: International Journal of Production Research
Pages: 4015-4032
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1641236
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641236
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Template-Type: ReDIF-Article 1.0
Author-Name: Chun Su
Author-X-Name-First: Chun
Author-X-Name-Last: Su
Author-Name: Yang Liu
Author-X-Name-First: Yang
Author-X-Name-Last: Liu
Title: Multi-objective imperfect preventive maintenance optimisation with NSGA-II
Abstract: 
 Maintenance optimisation is a multi-objective problem in nature, and it usually needs to achieve a trade-off among the conflicting objectives. In this study, a multi-objective maintenance optimisation (MOMO) model is proposed for electromechanical products, where both the soft failure and hard failure are considered, and minimal repair is performed accordingly. Imperfect preventive maintenance (IPM) is carried out during the preplanned periods, and modelled with a hybrid failure rate model and quasi-renewal coefficient. The initial IPM period and the total number of IPM periods are set as the decision variables, and a MOMO model is developed to optimise the availability and cost rate concurrently. The fast elitist non-dominated sorting genetic algorithm (NSGA-II) is applied to solve the model. A case study of wind turbine’s gearbox is provided. The results show that there are 30 optimal solutions in the MOMO’s Pareto frontier that can maximise the availability and minimise the cost rate simultaneously. Compared with the single-objective maintenance optimisation, it can provide more choices for maintenance decision, and better satisfy the resource constraints and the customer’s preference. The results of the sensitivity analysis show that the effect of age reduction factor on optimisation results is greater than that of failure rate increase factor.
Journal: International Journal of Production Research
Pages: 4033-4049
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1641237
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641237
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Template-Type: ReDIF-Article 1.0
Author-Name: Peixin Ge
Author-X-Name-First: Peixin
Author-X-Name-Last: Ge
Author-Name: Ying Meng
Author-X-Name-First: Ying
Author-X-Name-Last: Meng
Author-Name: Jiyin Liu
Author-X-Name-First: Jiyin
Author-X-Name-Last: Liu
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Author-Name: Ren Zhao
Author-X-Name-First: Ren
Author-X-Name-Last: Zhao
Title: Logistics optimisation of slab pre-marshalling problem in steel industry
Abstract: 
 We study the slab pre-marshalling problem to re-position slabs in a way that the slabs are stored in the least number of stacks and each stack contains only the slabs of the same group, which can be utilised interchangeably. In this way, when a slab of any group is required, the topmost slab can always be picked up without shuffling. During pre-marshalling, however, at most two slabs can be moved by one operation. In this paper, we present a network model with three valid inequalities to solve this problem. With a small amount of labelled data from the model approach, a self-training technique is applied to train a function for predicting the best next move. Then, a new hybrid algorithm is developed to solve the practical problems by combining the self-training technique, heuristics, and the branch-and-bound algorithm with five dominance rules. The experimental results demonstrate the effectiveness of this network model and valid inequalities, and the performances of different components of this algorithm. The new algorithm produces high-quality solutions within seconds.
Journal: International Journal of Production Research
Pages: 4050-4070
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1641238
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641238
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:13:p:4050-4070




Template-Type: ReDIF-Article 1.0
Author-Name: Weihong Guo
Author-X-Name-First: Weihong
Author-X-Name-Last: Guo
Author-Name: Xi Gu
Author-X-Name-First: Xi
Author-X-Name-Last: Gu
Title: Joint decision-making of production and maintenance in mixed model assembly systems with delayed differentiation configurations
Abstract: 
 Mixed model assembly systems (MMASs) can simultaneously manufacture multiple product variants and are developed to satisfy customers’ increasing desire for products with a high variety. This paper investigates the joint decision-making of production and maintenance policies in MMASs with delayed differentiation configurations, where common operations are performed before differentiated processes. The problem is formulated as a Markov Decision Process (MDP) problem that minimises the average cost per unit time. Monte Carlo simulation is used to evaluate the system performance measures (e.g. volume mix ratio, product quality) under the optimal policy. Numerical examples are presented to illustrate the structure of the optimal policy and the impact of different factors on the system performance in an MMAS that produces two types of product variants. Techniques that can potentially solve the problem in large-sized MMASs are also discussed.
Journal: International Journal of Production Research
Pages: 4071-4085
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1641641
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641641
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:13:p:4071-4085




Template-Type: ReDIF-Article 1.0
Author-Name: Jingying Huang
Author-X-Name-First: Jingying
Author-X-Name-Last: Huang
Author-Name: Liya Wang
Author-X-Name-First: Liya
Author-X-Name-Last: Wang
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: A method combining rules with genetic algorithm for minimizing makespan on a batch processing machine with preventive maintenance
Abstract: 
 This paper considers the problem of minimising makespan on a single batch processing machine with flexible periodic preventive maintenance. This problem combines two sub-problems, scheduling on a batch processing machine with jobs’ release dates considered and arranging the preventive maintenance activities on a batch processing machine. The preventive maintenance activities are flexible but the maximum continuous working time of the machine, which is allowed, is determined. A mathematical model for integrating flexible periodic preventive maintenance into batch processing machine problem is proposed, in which the grouping of jobs with incompatible job families, the starting time of batches and the preventive maintenance activities are optimised simultaneously. A method combining rules with the genetic algorithm is proposed to solve this model, in which a batching rule is proposed to group jobs with incompatible job families into batches and a modified genetic algorithm is proposed to schedule batches and arrange preventive maintenance activities. The computational results indicate the method is effective under practical problem sizes. In addition, the influences of jobs’ parameters on the performance of the method are analyzed, such as the number of jobs, the number of job families, jobs’ processing time and jobs’ release time.
Journal: International Journal of Production Research
Pages: 4086-4102
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1641643
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1641643
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:13:p:4086-4102




Template-Type: ReDIF-Article 1.0
Author-Name: Xu Zheng
Author-X-Name-First: Xu
Author-X-Name-Last: Zheng
Author-Name: Shengchao Zhou
Author-X-Name-First: Shengchao
Author-X-Name-Last: Zhou
Author-Name: Rui Xu
Author-X-Name-First: Rui
Author-X-Name-Last: Xu
Author-Name: Huaping Chen
Author-X-Name-First: Huaping
Author-X-Name-Last: Chen
Title: Energy-efficient scheduling for multi-objective two-stage flow shop using a hybrid ant colony optimisation algorithm
Abstract: 
 Reducing energy costs has become an important concern for sustainable manufacturing systems, owing to concern for the environment. We present a multi-objective hybrid ant colony optimisation (MHACO) algorithm for a real-world two-stage blocking permutation flow shop scheduling problem to address the trade-off between total energy costs (TEC) and makespan ( ${C_{\max }} $Cmax) as measures of the service level with the time-of-use (TOU) electricity price. We explore the energy-saving potential of the manufacturing industry in consideration of the differential energy costs generated by variable-speed machines. A mixed integer programming model is developed to formulate this problem. In the MHACO algorithms, the max–min pheromone restriction rules and the local search rules avoid the localisation trap and enhance neighbourhood search capabilities, respectively. The Taguchi method and small-scale pilot experiments are employed to determine the appropriate experimental parameters. Based on three well-known multi-objective optimisation algorithms, viz., NSGAII, SPEA2, and MODEA, six algorithms with different batch-sorting methods are adopted as a comparison in small-, moderate-, and large-scale instances. A four-dimensional performance evaluation system is established to evaluate the obtained Pareto frontier approximations. The computational results show that the proposed MHACO–Johnson algorithm outperforms other algorithms in terms of solution quality, quantity, and distribution, although it is time consuming when dealing with moderate- to large-scale instances.
Journal: International Journal of Production Research
Pages: 4103-4120
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1642529
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1642529
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Template-Type: ReDIF-Article 1.0
Author-Name: Sukran N. Atadeniz
Author-X-Name-First: Sukran N.
Author-X-Name-Last: Atadeniz
Author-Name: Sri V. Sridharan
Author-X-Name-First: Sri V.
Author-X-Name-Last: Sridharan
Title: Effectiveness of nervousness reduction policies when capacity is constrained
Abstract: 
 A number of studies have examined a variety of solutions for overcoming master production schedule nervousness which is a major cause of cost increase and material flow disruption throughout the supply chain. The study reported in this paper provides a comprehensive review of the literature and provides insights on the effect of capacity constraints on the effectiveness of policies for dampening schedule nervousness. The insights on the impact of capacity constraints are then confirmed via a simulation study investigating the effectiveness of three nervousness reduction policies. The relative effectiveness of the policies (freezing a portion of the schedule, using safety stock at the end item level, and a combination policy of freezing and safety stock) are examined under a variety of conditions characterised by variations in the level of demand uncertainty faced by the system and product structure complexity.
Journal: International Journal of Production Research
Pages: 4121-4137
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1643513
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1643513
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Boris Sokolov
Author-X-Name-First: Boris
Author-X-Name-Last: Sokolov
Title: Reconfigurable supply chain: the X-network
Abstract: 
 Research on supply chain (SC) digitalization, resilience, sustainability and leagility has remarkably progressed, most of it focused on the individual contributions of these four major frameworks. However, a lack of integration spanning these individual frameworks can be observed. In this conceptual paper, we hypothesize that reconfigurability can be considered such an integral perspective that consolidates the research in SC adaptation to ever changing environments. We theorize a new notion – a Reconfigurable SC or the X-network – that exhibits some crucial design and control characteristics for complex value-adding systems in highly vulnerable environments. We support our argumentation and conceptual viewpoints by a literature analysis along with tertiary studies to review and structure contextual factors of designing the X-networks. We propose respective frameworks and discuss the implementation principles and technologies at the macro and micro levels. Two novel concepts – dynamic SC meta-structures and dynamic autonomous services – are introduced. Distinctively, we go beyond the existing knowledge to predict proactively the future directions in the reconfigurable SCs. Our results can be of value for decision-makers to decipher chances and barriers in contemporary SC transformations.
Journal: International Journal of Production Research
Pages: 4138-4163
Issue: 13
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1774679
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1774679
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Template-Type: ReDIF-Article 1.0
Author-Name: Yasmeen Jaghbeer
Author-X-Name-First: Yasmeen
Author-X-Name-Last: Jaghbeer
Author-Name: Robin Hanson
Author-X-Name-First: Robin
Author-X-Name-Last: Hanson
Author-Name: Mats Ingemar Johansson
Author-X-Name-First: Mats Ingemar
Author-X-Name-Last: Johansson
Title: Automated order picking systems and the links between design and performance: a systematic literature review
Abstract: 
 With new market developments and e-commerce, there is an increased use of and interest in automation for order picking. This paper presents a systematic review and content analysis of the literature. It has the purpose of understanding the relevant performance aspects for automated, or partly automated, OPSs and identifying the studied links between design and performance, i.e. identifying which combinations of design aspects and performance aspects have been studied in previous research. For this purpose, 74 papers were selected and reviewed. From the review, it is clear that there has been an increased number of papers dealing with the performance of automated, or partly automated, OPSs in recent years. Moreover, there are differences between the different OPS types, but, overall, the performance categories of throughput, lead time, and operational efficiency have received the most attention in the literature. The paper identifies links between design and performance that have been studied, as well as links that appear to be under-researched. For academics, this paper synthesises the current knowledge on the performance of automation in OPSs and identifies opportunities for future research. For practitioners, the paper provides knowledge that can support the decision-making process of automation in OPSs.
Journal: International Journal of Production Research
Pages: 4489-4505
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1788734
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1788734
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Template-Type: ReDIF-Article 1.0
Author-Name: Natalia Iakymenko
Author-X-Name-First: Natalia
Author-X-Name-Last: Iakymenko
Author-Name: Anita Romsdal
Author-X-Name-First: Anita
Author-X-Name-Last: Romsdal
Author-Name: Erlend Alfnes
Author-X-Name-First: Erlend
Author-X-Name-Last: Alfnes
Author-Name: Marco Semini
Author-X-Name-First: Marco
Author-X-Name-Last: Semini
Author-Name: Jan Ola Strandhagen
Author-X-Name-First: Jan Ola
Author-X-Name-Last: Strandhagen
Title: Status of engineering change management in the engineer-to-order production environment: insights from a multiple case study
Abstract: 
 Engineering Changes (ECs) are a fact of life for companies in the Engineer-To-Order (ETO) production environment. Various Engineering Change Management (ECM) strategies, practices and tools exist, but no explicit distinction has been made regarding ECM in different production environments. Using a multiple case study method, this article investigates how ETO companies manage ECs and how ETO characteristics influence ECM. A generic ECM framework was developed and used to map ECM in the cases. The study showed that ETO companies use similar practices for handling ECs, while ECM tools are either not used by the companies or used to a very limited extent. It was found that the use of some ECM practices and tools is complicated by specific ETO company characteristics. However, no reasons were found for the lack of computer-based tools, change propagation and impact assessment tools, change reduction and front-loading tools, and design tools. This suggests, firstly, that there is vast room for improvement in ETO companies when it comes to ECM; and secondly, that the applicability of such tools should be further tested in the ETO environment. Based on the findings, some suggestions as to how ECM can be improved in ETO companies are given to practitioners.
Journal: International Journal of Production Research
Pages: 4506-4528
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1759836
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1759836
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Template-Type: ReDIF-Article 1.0
Author-Name: Jafar Rezaei
Author-X-Name-First: Jafar
Author-X-Name-Last: Rezaei
Author-Name: Nadia Pourmohammadzia
Author-X-Name-First: Nadia
Author-X-Name-Last: Pourmohammadzia
Author-Name: Charalampos Dimitropoulos
Author-X-Name-First: Charalampos
Author-X-Name-Last: Dimitropoulos
Author-Name: Lori Tavasszy
Author-X-Name-First: Lori
Author-X-Name-Last: Tavasszy
Author-Name: Mark Duinkerken
Author-X-Name-First: Mark
Author-X-Name-Last: Duinkerken
Title: Co-procurement: making the most of collaborative procurement
Abstract: 
 While the procurement decision is generally made by individual buyers, this study investigates how a group of buyers can make a shared decision. We call this collaborative approach, co-procurement. A mathematical model is formulated for the decision of procurement from multiple suppliers. The model is solved for individual buyers. The outcome shows the optimal number of items a buyer should buy from different suppliers such that the total cost is minimised for that buyer. Next, it is investigated how a group of buyers could make this decision together. The proposed model takes into account transaction costs of collaboration, to determine the optimal size of the collaboration and the involved parties. The idea is new in the old direction of procurement and it introduces the concept of transaction costs in this area and analyses its impact on the optimal collaboration size and mix. A case study from Dutch Food Valley is provided to investigate the benefits of co-procurement and validate the developed structure. The results indicate that co-procurement can bring considerable cost-savings through consolidation of orders and more efficient transportation schedules. A sensitivity analysis is conducted to determine the impact of changes in the transaction cost in favour of the co-procurement.
Journal: International Journal of Production Research
Pages: 4529-4540
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1770355
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1770355
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Template-Type: ReDIF-Article 1.0
Author-Name: Yu Han
Author-X-Name-First: Yu
Author-X-Name-Last: Han
Author-Name: Woon Kian Chong
Author-X-Name-First: Woon Kian
Author-X-Name-Last: Chong
Author-Name: Dong Li
Author-X-Name-First: Dong
Author-X-Name-Last: Li
Title: A systematic literature review of the capabilities and performance metrics of supply chain resilience
Abstract: 
 Research on supply chain resilience (SCRE) capabilities and its performance measurement has been growing in recent years. However, the investigation of these concepts has primarily been conducted independently despite the interdependence of these concepts. A systematic literature review of 153 papers was conducted based on the principles of rigour, transparency and replicability required by the methodology. For the first time, we structurally reviewed the 11 SCRE performance metrics categories and its capabilities in SCRE Capabilities-Performance Metrics Framework (SCPM) developed based on the three resilience dimensions (readiness, response and recovery). The framework enables researchers to seek fundamental knowledge and to pursue further research regarding SCRE assessment. This study also provides practical value offering a guidance for decision-makers considering the trade-off among different capabilities and performance metrics.
Journal: International Journal of Production Research
Pages: 4541-4566
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1785034
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1785034
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Template-Type: ReDIF-Article 1.0
Author-Name: Qingyun Zhu
Author-X-Name-First: Qingyun
Author-X-Name-Last: Zhu
Author-Name: Purvi Shah
Author-X-Name-First: Purvi
Author-X-Name-Last: Shah
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: A paler shade of green: implications of green product deletion on supply chains
Abstract: 
 Product management activities by operations, marketing, and finance functions have typically focused on the innovation, acquisition, growth, and management of product lines and products. The same is true when considering product management for green products. The latter stages of critical strategic decisions related to product deletion or discontinuation have received less emphasis. In this conceptual paper, the focus is on green product deletion implications for supply chain management and operations. Organisations may view green product deletion as evolving from a deep green to a paler shade of green in their product offerings. A proposed strategic framework pays particular attention to the implications of the green product deletion decision for supply chain processes and operational competencies. In this situation, lessened organisational greenness needs to be weighed against other organisational and operational competencies. The strategic and inter-organisational relationships associated with this decision help set the stage for future research on this critical, yet neglected, organisational and operational supply chain issue.
Journal: International Journal of Production Research
Pages: 4567-4588
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1781279
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1781279
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Template-Type: ReDIF-Article 1.0
Author-Name: Chee Yew Wong
Author-X-Name-First: Chee Yew
Author-X-Name-Last: Wong
Author-Name: Christina W.Y. Wong
Author-X-Name-First: Christina W.Y.
Author-X-Name-Last: Wong
Author-Name: Sakun Boon-itt
Author-X-Name-First: Sakun
Author-X-Name-Last: Boon-itt
Title: Effects of green supply chain integration and green innovation on environmental and cost performance
Abstract: 
 This paper argues that mechanisms such as information sharing and collaboration used in green supply chain integration (GSCI) to improve information processing capacity can reduce uncertain outcomes of green product and process innovation. Based on data from a survey of Chinese (Hong Kong) firms, the paper tests whether the three dimensions of GSCI (green internal, customer and supplier integration) improve environmental performance and cost reduction by facilitating green product and process innovation. The results show that green customer integration improves cost and environmental performance through green process innovation (not green product innovation). Both green product and process innovations are facilitated by green customer integration (not green supplier integration), while both green customer and supplier integration significantly depend on green internal integration. These suggest that the distinctive information processing capacity created by green internal and customer integration can facilitate the green process innovation required to improve environmental and cost efficiency, while green product innovation and green supplier integration cannot create such efficiencies.
Journal: International Journal of Production Research
Pages: 4589-4609
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1756510
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1756510
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Template-Type: ReDIF-Article 1.0
Author-Name: Oscar Rodríguez-Espíndola
Author-X-Name-First: Oscar
Author-X-Name-Last: Rodríguez-Espíndola
Author-Name: Soumyadeb Chowdhury
Author-X-Name-First: Soumyadeb
Author-X-Name-Last: Chowdhury
Author-Name: Ahmad Beltagui
Author-X-Name-First: Ahmad
Author-X-Name-Last: Beltagui
Author-Name: Pavel Albores
Author-X-Name-First: Pavel
Author-X-Name-Last: Albores
Title: The potential of emergent disruptive technologies for humanitarian supply chains: the integration of blockchain, Artificial Intelligence and 3D printing
Abstract: 
 The growing importance of humanitarian operations has created an imperative to overcome the complications currently recorded in the field. Challenges such as delays, congestion, poor communication and lack of accountability may represent opportunities to test the reported advantages of emergent disruptive technologies. Meanwhile, the literature on humanitarian supply chains looks at isolated applications of technology and lacks a framework for understanding challenges and solutions, a gap that this article aims to fill. Using a case study based on the flood of Tabasco of 2007 in Mexico, this research identifies solutions based on the use of emergent disruptive technologies. Furthermore, this article argues that the integration of different technologies is essential to deliver real benefits to the humanitarian supply chain. As a result, it proposes a framework to improve the flow of information, products and financial resources in humanitarian supply chains integrating three emergent disruptive technologies; Artificial Intelligence, Blockchain and 3D Printing. The analysis presented shows the potential of the framework to reduce congestion in the supply chain, enhance simultaneous collaboration of different stakeholders, decrease lead times, increase transparency, traceability and accountability of material and financial resources, and allow victims to get involved in the fulfilment of their own needs.
Journal: International Journal of Production Research
Pages: 4610-4630
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1761565
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1761565
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Template-Type: ReDIF-Article 1.0
Author-Name: Daqiang Guo
Author-X-Name-First: Daqiang
Author-X-Name-Last: Guo
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Author-Name: Shiquan Ling
Author-X-Name-First: Shiquan
Author-X-Name-Last: Ling
Author-Name: Yiming Rong
Author-X-Name-First: Yiming
Author-X-Name-Last: Rong
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: A roadmap for Assembly 4.0: self-configuration of fixed-position assembly islands under Graduation Intelligent Manufacturing System
Abstract: 
 The layout of fixed-position assembly islands (FPAI) is widely used for producing fragile or bulky products. With the increasing customised demand and unique operation patterns, manufacturing practitioners are facing challenges on flexible and efficient production arrangement to meet customer demand, which lead to inappropriate assembly islands configuration, frequent setups and long waiting times in FPAI. Industry 4.0 comes with the promise of improved flexibility and efficiency in manufacturing. In the context of Industry 4.0, this paper proposes a 5-layer APICS (assembly layer, perception layer, interaction layer, cognition layer, and service layer) roadmap for transformation and implementation of Assembly 4.0. Following the 5-layer APICS roadmap, a Graduation Intelligent Manufacturing System (GiMS) is presented as the pioneering implementation in FPAI. A graduation-inspired assembly system is designed for FPAI at assembly layer. Internet of Things (IoT) and industrial wearable technologies are deployed for perception, connection, and collaboration among various manufacturing resources at perception and interaction layer. A self-configuration model is proposed at cognition layer for autonomously configuring optimal assembly islands and corresponding production activities to meet customer demand. Cloud-based services are developed for managers and onsite operators to facilitate their decision-making and daily operations at service layer. Finally, a demonstrative case is conducted to verify the feasibility of the proposed methods.
Journal: International Journal of Production Research
Pages: 4631-4646
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1762944
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1762944
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Kusiak
Author-X-Name-First: Andrew
Author-X-Name-Last: Kusiak
Title: Open manufacturing: a design-for-resilience approach
Abstract: 
 Open systems have been of interest to the research and industrial community for decades, e.g. software development, telecommunication, and innovation. The presence of open manufacturing enterprises in a cloud calls for broadly interpretable models. Though there is no global standard for representation of digital models of processes and systems in a cloud, the existing process modelling methodologies and languages are of interest to the manufacturing cloud. The models residing in the cloud need to be configured and reconfigured to meet different objectives, including complexity reduction and interpretability which coincide with the resilience requirements. Digitisation, greater openness, and growing service orientation of manufacturing offer opportunities to address resilience at the design rather than the operations stage. An algorithm is presented for complexity reduction of digital models. The complexity reduction algorithm decomposes complex structures and enhances interpretability and visibility of their components. The same algorithm and its variants could serve other known concepts supporting resilience such as modularity of products and processes as well as delayed product differentiation. The ideas introduced in the paper and the complexity reduction algorithm of digital models are illustrated with examples. Properties of the graph and matrix representations produced by the algorithm are discussed.
Journal: International Journal of Production Research
Pages: 4647-4658
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1770894
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1770894
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Template-Type: ReDIF-Article 1.0
Author-Name: Kay Peeters
Author-X-Name-First: Kay
Author-X-Name-Last: Peeters
Author-Name: Henny van Ooijen
Author-X-Name-First: Henny
Author-X-Name-Last: van Ooijen
Title: Hybrid make-to-stock and make-to-order systems: a taxonomic review
Abstract: 
 Production planning and control (PPC) systems that employ aspects from both make-to-order (MTO) and make-to-stock (MTS) production control are known as hybrid MTS/MTO systems. While both MTO and MTS separately have been studied extensively, their combined use has received less attention. However, the literature on this topic is growing and this paper shows that the review performed in this paper is an important addition to the field. We categorise relevant literature according to a novel taxonomy and show that hybrid MTS/MTO production control can be used in different contexts. In addition, an overview of the modelling techniques and methods used in these papers is provided. Based on the reviewed literature, relevant research questions and directions for future research are identified. Finally, it is shown that hybrid MTS/MTO production control is prevalent in practice by discussing research with industrial applications. The paper contains an overview of research on hybrid MTS/MTO production control to be used as reference for researchers active in the field, and provides managerial insights and directions for future research on this topic.
Journal: International Journal of Production Research
Pages: 4659-4688
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1778204
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1778204
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Template-Type: ReDIF-Article 1.0
Author-Name: Nazli Turken
Author-X-Name-First: Nazli
Author-X-Name-Last: Turken
Author-Name: Vincent Cannataro
Author-X-Name-First: Vincent
Author-X-Name-Last: Cannataro
Author-Name: Avinash Geda
Author-X-Name-First: Avinash
Author-X-Name-Last: Geda
Author-Name: Ashutosh Dixit
Author-X-Name-First: Ashutosh
Author-X-Name-Last: Dixit
Title: Nature inspired supply chain solutions: definitions, analogies, and future research directions
Abstract: 
 Supply chains are becoming increasingly complex, and many companies and researchers are looking to nature for finding solutions. In this paper, we provide a narrative synthesis and systematic review to explore state-of-the-art, and identify key areas for exploration of nature inspired solutions in the supply chain area. We consider strategic, tactical, and operational decisions within supply chains and identify analogies between biological systems and supply chains to create a new research agenda. Our findings show that the majority of the research in nature inspired supply chains from the systemic perspective focuses on closed loop supply chains. In contrast, similar systemic solutions such as industrial symbiosis, circular economy, and industrial ecology have not been explored as frequently. Reducing production waste (industrial symbiosis) in addition to end-of-life product waste (closed loop supply chains), optimising raw material use and extending the life of used resources (circular economy), investigating the interactions between biosphere and technosphere (industrial ecology), and seeking solutions to industrial problems from nature (biomimicry) are all possible paths for reaching a zero-waste economy. These systemic solutions have a considerable impact on the supply chains at the strategic, tactical, and operational levels, which need to be explored to identify efficient and effective solutions.
Journal: International Journal of Production Research
Pages: 4689-4715
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1778206
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1778206
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Template-Type: ReDIF-Article 1.0
Author-Name: Valentina Di Pasquale
Author-X-Name-First: Valentina
Author-X-Name-Last: Di Pasquale
Author-Name: Salvatore Miranda
Author-X-Name-First: Salvatore
Author-X-Name-Last: Miranda
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Title: Ageing and human-system errors in manufacturing: a scoping review
Abstract: 
 Population ageing is acknowledged as a global trend affecting the manufacturing workforce. The progressive age-related decline of human capabilities may lead to an increase in human-system errors (HSEs) in production environments; hence, the study conducted a scoping literature review to determine the relationship between ageing and HSEs in manufacturing contexts. The review identified only 26 relevant studies, which showed that age is associated with HSEs in complex ways. With increasing age, the number, frequency, and probability of HSEs tend to increase, but this trend may be countered by experience effects. The review results suggested that it is necessary to consider the impact of ageing on operators’ performance. A theoretical framework for addressing the relationship between ageing and HSEs in manufacturing contexts was proposed. The framework highlighted the absence of studies reporting on perceptual, cognitive, and/or physical task demands, and the limited application of existing error typologies in the current literature. The results highlighted that important safety, productivity, and quality benefits accrue from paying attention to HSEs in system design and management, which should motivate further research in this area of growing importance.
Journal: International Journal of Production Research
Pages: 4716-4740
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1773561
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1773561
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Template-Type: ReDIF-Article 1.0
Author-Name: Valentina Di Pasquale
Author-X-Name-First: Valentina
Author-X-Name-Last: Di Pasquale
Author-Name: Maria Elena Nenni
Author-X-Name-First: Maria Elena
Author-X-Name-Last: Nenni
Author-Name: Stefano Riemma
Author-X-Name-First: Stefano
Author-X-Name-Last: Riemma
Title: Order allocation in purchasing management: a review of state-of-the-art studies from a supply chain perspective
Abstract: 
 Supplier selection (SS) and order allocation (OA) are strategic decisions that have a substantial effect on a company’s performance. However, order allocation is often neglected, since it results from supplier selection and is considered supplementary: little attention has been paid to its specific nature and complexity. Consequently, the authors conducted a systematic literature review specifically regarding order allocation methods. The research aimed to evaluate how often and when the issue has been dignified with an individual focus, independently of the supplier selection problem. This study conducted a comprehensive examination of the order allocation models and solutions, criteria for order quantity allocation, features of suppliers, items, planning periods, and demand most commonly considered in the literature. Finally, it aimed to discover whether supply chain configurations and trends have been considered in efforts to find a solution to the problem. The scientific contribution of this study is threefold: (i) to expand the review of scientific literature regarding order allocation models, (ii) to identify research gaps and highlight research opportunities, and (iii) to suggest a research agenda for the development of order allocation models according to the requirements of current trends in supply chain management.
Journal: International Journal of Production Research
Pages: 4741-4766
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1751338
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1751338
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Template-Type: ReDIF-Article 1.0
Author-Name: Gianfranco Genta
Author-X-Name-First: Gianfranco
Author-X-Name-Last: Genta
Author-Name: Maurizio Galetto
Author-X-Name-First: Maurizio
Author-X-Name-Last: Galetto
Author-Name: Fiorenzo Franceschini
Author-X-Name-First: Fiorenzo
Author-X-Name-Last: Franceschini
Title: Inspection procedures in manufacturing processes: recent studies and research perspectives
Abstract: 
 Quality inspections are performed in almost every production system to prevent nonconforming products from reaching final customers or end users. Quality inspections are typically performed referring to specific inspection procedures, depending on the production process. Two general inspection paradigms may be identified: online inspection and offline inspection. These are differentiated by the way in which inspections are made. The paper presents a recent survey on new studies on inspection procedures for both paradigms. The main novelty of the study is the identification of new research perspectives in such a highly explored field. New schemes of analysis allow highlighting the research areas which are not adequately covered by the literature. A brief examination of some bibliometric aspects is also proposed.
Journal: International Journal of Production Research
Pages: 4767-4788
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1766713
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766713
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Template-Type: ReDIF-Article 1.0
Author-Name: Angelo Corallo
Author-X-Name-First: Angelo
Author-X-Name-Last: Corallo
Author-Name: Maria Elena Latino
Author-X-Name-First: Maria Elena
Author-X-Name-Last: Latino
Author-Name: Marta Menegoli
Author-X-Name-First: Marta
Author-X-Name-Last: Menegoli
Author-Name: Pierpaolo Pontrandolfo
Author-X-Name-First: Pierpaolo
Author-X-Name-Last: Pontrandolfo
Title: A systematic literature review to explore traceability and lifecycle relationship
Abstract: 
 Traceability is the ability to follow a product along its lifecycle. It ensures product safety and quality along the supply chain, managing information generated by several players. Even though regulations establish the information that has to be traced, each player generates much more product (and process) information, which could be used to add value to products, with respect to, not only traceability, but also the lifecycle approach. However, the concepts do not appear to be immediately related in scientific panorama. This paper aims to explore the relationship between traceability and lifecycle through a systematic literature review. Six industries (Software, Manufacturing, Automotive, Automation, Aircraft, and Aerospace) and seven subject areas (Software engineering; System engineering; Industry 4.0; New product development; Process management; Data Management; and Environmental sustainability) were identified through bibliometric analysis. To better explore this relationship in the context of the food industry, a content analysis on lead papers’ sample was performed to identify traceability and lifecycle definitions, methodologies and technologies and their relation. The results of the work, synthetised in a proposed research map, will be of interest to those who are approaching the subject for the first time, and for companies involved in product lifecycle management and food traceability.
Journal: International Journal of Production Research
Pages: 4789-4807
Issue: 15
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1771455
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1771455
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Template-Type: ReDIF-Article 1.0
Author-Name: Yingying Wu
Author-X-Name-First: Yingying
Author-X-Name-Last: Wu
Author-Name: Chen Zhou
Author-X-Name-First: Chen
Author-X-Name-Last: Zhou
Author-Name: Wenkai Ma
Author-X-Name-First: Wenkai
Author-X-Name-Last: Ma
Author-Name: Xiang T. R. Kong
Author-X-Name-First: Xiang T. R.
Author-X-Name-Last: Kong
Title: Modelling and design for a shuttle-based storage and retrieval system
Abstract: 
 The shuttle-based storage and retrieval system (SBS/RS) is a relatively new part-to-picker order picking system. We have developed a performance estimation and design algorithm for the SBS/RS. The performance estimation is based on a queuing model. The design algorithm aims to find the minimum cost configurations in terms of number of tiers, aisles, lifts and workstations with given throughput, tote capacity and order cycle time requirements. We used simulation driven by parameters abstracted from an actual SBS/RS to verify the performance estimation, and applied the design algorithm in the case study. The results indicate that: (1) compared to simulation results, the throughput of the performance estimation is nearly identical when the arrival rate is below the maximum capacity; (2) the design algorithm yields a configuration with 28.1% cost reduction in the current system. In addition, we also compared the shuttle system with the competing robotic order fulfilment system (robotic system in short) in terms of facility cost, building cost and order cycle time. We found that the shuttle system is a better choice if large storage capacity and high throughput are required whereas the robotic order fulfilment system performs better if small storage capacity and low throughput are required.
Journal: International Journal of Production Research
Pages: 4808-4828
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1665202
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1665202
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanjun Wang
Author-X-Name-First: Yanjun
Author-X-Name-Last: Wang
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Title: Flexible strategies under supply disruption: the interplay between contingent sourcing and responsive pricing
Abstract: 
 Due to possible supply disruptions because of a low-cost unreliable supplier, a firm may use a high-cost reliable supplier as an additional regular supplier (dual sourcing) or an emergency backup supplier with an extra emergency cost (contingent sourcing). We consider the firm's sourcing problem when the pricing decision is made before any supply uncertainty is resolved (committed pricing) or after the supply state is realised (responsive pricing). By comparing the relative value of responsive pricing in contingent sourcing to that in dual sourcing, we study the relationship between contingent sourcing and responsive pricing in mitigating supply disruption risks. We show that the emergency cost and potential lost sales caused by disruption probability jointly impact the interplay of these two strategies. More specifically, when the emergency cost is low and the potential lost sales are lower under contingent sourcing than that under dual sourcing, contingent sourcing and responsive pricing are substitutes; otherwise, they are complements. Furthermore, we examine how disrupted capacity, i.e. the quantity that the unreliable supplier can deliver when disrupted, impacts the interplay, and find that the probability of the substitution relationship becomes higher when the disrupted capacity increases. We also find that under committed pricing, contingent sourcing is not optimal for any value of disruption probability when the emergency cost is high, a phenomenon that does not exist under responsive pricing.
Journal: International Journal of Production Research
Pages: 4829-4850
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1722326
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1722326
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Template-Type: ReDIF-Article 1.0
Author-Name: Guoqing Zhao
Author-X-Name-First: Guoqing
Author-X-Name-Last: Zhao
Author-Name: Shaofeng Liu
Author-X-Name-First: Shaofeng
Author-X-Name-Last: Liu
Author-Name: Carmen Lopez
Author-X-Name-First: Carmen
Author-X-Name-Last: Lopez
Author-Name: Huilan Chen
Author-X-Name-First: Huilan
Author-X-Name-Last: Chen
Author-Name: Haiyan Lu
Author-X-Name-First: Haiyan
Author-X-Name-Last: Lu
Author-Name: Sachin Kumar Mangla
Author-X-Name-First: Sachin Kumar
Author-X-Name-Last: Mangla
Author-Name: Sebastian Elgueta
Author-X-Name-First: Sebastian
Author-X-Name-Last: Elgueta
Title: Risk analysis of the agri-food supply chain: A multi-method approach
Abstract: 
 Agri-food supply chains (AFSCs) are becoming more complex in structure, and thus more susceptible to different vulnerabilities and risks. Therefore, to enhance performance, we need to manage the risks in AFSCs effectively and efficiently. This study analyses various AFSC risks using a multi-method approach, including thematic analysis, total interpretive structural modelling (TISM) and fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis. Based on the empirical data collected from experienced AFSC practitioners and following thematic analysis, eight categories of risk and 16 risk factors were identified as important. Furthermore, the interrelationships among the identified risks were built using TISM. Finally, the identified risks were classified into various categories according to their dependence and driving power using fuzzy MICMAC analysis. The research results indicate that the weather-related and political risks have the highest driving power and are located at the lowest level in the TISM hierarchy. These risks have a high tendency to disturb the whole flow of AFSC and so  should be managed effectively. This study advances existing literature on identifying risk factors, defining interrelations between different AFSC risks, and determining the key risks. The risk analysis results can help AFSC practitioners in AFSC to identify, categorise and analyse the risks.
Journal: International Journal of Production Research
Pages: 4851-4876
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1725684
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1725684
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Template-Type: ReDIF-Article 1.0
Author-Name: Cheng-Feng Wu
Author-X-Name-First: Cheng-Feng
Author-X-Name-Last: Wu
Author-Name: Mahdi Fathi
Author-X-Name-First: Mahdi
Author-X-Name-Last: Fathi
Author-Name: David M. Chiang
Author-X-Name-First: David M.
Author-X-Name-Last: Chiang
Author-Name: Panagote M. Pardalos
Author-X-Name-First: Panagote M.
Author-X-Name-Last: Pardalos
Title: Credit guarantee mechanism with information asymmetry: a single sourcing model
Abstract: 
 This study concerns small and medium-sized enterprise (SME) suppliers suffering from cash constraints in operations, money shortages with possible disruptions and cost uncertainty because of the distributor’s supply risk and the information asymmetry. Thus, this study adopts the distributor’s (buyer’s) perspective and applies a credit guarantee mechanism with an incentive contract as a risk management tool. The distributor can adopt incentive contracts to reveal the type of its supplier; the higher the inefficient supplier’s contribution to the distributor, the smaller the gap between procurement contract quantities with the efficient supplier and procurement contract quantities with the inefficient supplier. An insight into practice is that incentive contracts are tools for acquiring ideal suppliers in the supply base and help companies such as Li & Fung enhance their competitive capabilities.
Journal: International Journal of Production Research
Pages: 4877-4893
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1727039
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1727039
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Template-Type: ReDIF-Article 1.0
Author-Name: Vijaya Sunder M
Author-X-Name-First: Vijaya
Author-X-Name-Last: Sunder M
Author-Name: Anupama Prashar
Author-X-Name-First: Anupama
Author-X-Name-Last: Prashar
Title: Empirical examination of critical failure factors of continuous improvement deployments: stage-wise results and a contingency theory perspective
Abstract: 
 Organisations implement various Continuous Improvement (CI) practices such as Total Quality Management, Lean, Six Sigma and Lean Six Sigma (LSS) for improving their processes. Drawing from the success and failure stories of these structured CI practices, scholars enumerated Critical Success Factors and Critical Failure Factors (CFFs). This study empirically examines the occurrence of various CFFs across different stages of CI deployment. Further, from a contingency theoretic perspective, this study investigates their associations with contextual variables by collecting survey data from 213 business units from the USA, the UK, China, and India. Principal Component Analysis is used to group CFFs across five CI deployment stages leading to an empirically refined framework for CI. Crosstab analysis using the chi-square likelihood ratio presented associations of CFFs with contextual variables. Findings reveal significant differences in the occurrence of CFFs across countries. There is evidence that LSS is less prone to failures when compared with TQM, Lean and Six Sigma. The occurrence of CFFs has been relatively lower in smaller and medium-sized enterprises operating in the service sector. Findings also reveal that lessons learned from each CI deployment cycle, contribute to organisational learning, and thence, leading to success at the strategic CI level of maturity.
Journal: International Journal of Production Research
Pages: 4894-4915
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1727044
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1727044
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:16:p:4894-4915




Template-Type: ReDIF-Article 1.0
Author-Name: M. M. L. Chang
Author-X-Name-First: M. M. L.
Author-X-Name-Last: Chang
Author-Name: A. Y. C. Nee
Author-X-Name-First: A. Y. C.
Author-X-Name-Last: Nee
Author-Name: S. K. Ong
Author-X-Name-First: S. K.
Author-X-Name-Last: Ong
Title: Interactive AR-assisted product disassembly sequence planning (ARDIS)
Abstract: 
 This paper presents a proof-of-concept novel near real-time interactive AR-assisted product disassembly sequence planning system (ARDIS) based on product information, such as interference matrix and 3D models. The system is developed using Unity and consists of three modules, including an intelligent disassembly sequence planning module, an automatic content authoring module and an intuitive augmented reality (AR) user interface (UI) with various features, such as a virtual panel for customisation and an option panel for sequence regeneration. Given the retrieval targets specified by a user, optimised disassembly sequences are computed using an evolutionary computing algorithm. For the sequences computed, the respective AR disassembly instruction sequences, such as 2D text instructions and animated 3D models, are generated dynamically based on a taxonomy that links each disassembly step in a sequence with the corresponding Unity templates that have been created beforehand. Hence, the need for manual authoring to provide AR disassembly guidance is reduced. If necessary, the user can request for alternative disassembly sequences which can be re-computed in near real-time. Several case studies have been carried out to demonstrate and evaluate the performance of the system within the laboratory environment.
Journal: International Journal of Production Research
Pages: 4916-4931
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1730462
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1730462
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Template-Type: ReDIF-Article 1.0
Author-Name: Yina Li
Author-X-Name-First: Yina
Author-X-Name-Last: Li
Author-Name: Yang Tong
Author-X-Name-First: Yang
Author-X-Name-Last: Tong
Author-Name: Fei Ye
Author-X-Name-First: Fei
Author-X-Name-Last: Ye
Author-Name: Jiajia Song
Author-X-Name-First: Jiajia
Author-X-Name-Last: Song
Title: The choice of the government green subsidy scheme: innovation subsidy vs. product subsidy
Abstract: 
 A critical problem that beleaguers governments in the promotion of green development is determining which approach to employ in establishing an efficient green subsidy scheme. In this study, we scrutinise the effects of three government subsidy schemes: a green non-subsidy (GNS), a green product subsidy (GPS), and a green innovation subsidy (GIS). Taking social welfare into consideration, the optimal green subsidy scheme of governments in different settings is investigated. Interestingly, we find that a green subsidy is not always a good choice for the government. When the cost of green innovation is particularly low, or when both the cost of green innovation and the variable production cost of green product are high, if the environmental improvement effectiveness yielded by green innovation is insignificant, the GNS is the best. Otherwise, both the GPS and the GIS achieve greater levels of social welfare. In addition, counter to intuition, the GPS outperforms the GIS when the cost of green innovation is sufficiently high and green innovation reduces the variable production cost of green product significantly, even if the GIS can directly help to lighten the green innovation cost load. However, from the perspective of maximising subsidy efficiency, the GIS is always better than the GPS.
Journal: International Journal of Production Research
Pages: 4932-4946
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1730466
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1730466
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Template-Type: ReDIF-Article 1.0
Author-Name: Ashfaq Farooqui
Author-X-Name-First: Ashfaq
Author-X-Name-Last: Farooqui
Author-Name: Kristofer Bengtsson
Author-X-Name-First: Kristofer
Author-X-Name-Last: Bengtsson
Author-Name: Petter Falkman
Author-X-Name-First: Petter
Author-X-Name-Last: Falkman
Author-Name: Martin Fabian
Author-X-Name-First: Martin
Author-X-Name-Last: Fabian
Title: Towards data-driven approaches in manufacturing: an architecture to collect sequences of operations
Abstract: 
 The technological advancements of recent years have increased the complexity of manufacturing systems, and the ongoing transformation to Industry 4.0 will further aggravate the situation. This is leading to a point where existing systems on the factory floor get outdated, increasing the gap between existing technologies and state-of-the-art systems, making them incompatible. This paper presents an event-based data pipeline architecture, that can be applied to legacy systems as well as new state-of-the-art systems, to collect data from the factory floor. In the presented architecture, actions executed by the resources are converted to event streams, which are then transformed into an abstraction called operations. These operations correspond to the tasks performed in the manufacturing station. A sequence of these operations recount the task performed by the station. We demonstrate the usability of the collected data by using conformance analysis to detect when the manufacturing system has deviated from its defined model. The described architecture is developed in Sequence Planner – a tool for modelling and analysing production systems – and is currently implemented at an automotive company as a pilot project.
Journal: International Journal of Production Research
Pages: 4947-4963
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1735660
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735660
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
Author-Name: Sushil Punia
Author-X-Name-First: Sushil
Author-X-Name-Last: Punia
Author-Name: Konstantinos Nikolopoulos
Author-X-Name-First: Konstantinos
Author-X-Name-Last: Nikolopoulos
Author-Name: Surya Prakash Singh
Author-X-Name-First: Surya Prakash
Author-X-Name-Last: Singh
Author-Name: Jitendra K. Madaan
Author-X-Name-First: Jitendra K.
Author-X-Name-Last: Madaan
Author-Name: Konstantia Litsiou
Author-X-Name-First: Konstantia
Author-X-Name-Last: Litsiou
Title: Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail
Abstract: 
 This paper proposes a novel forecasting method that combines the deep learning method – long short-term memory (LSTM) networks and random forest (RF). The proposed method can model complex relationships of both temporal and regression type which gives it an edge in accuracy over other forecasting methods. We evaluated the new method on a real-world multivariate dataset from a multi-channel retailer. We benchmark the forecasting performance of the new proposition against neural networks, multiple regression, ARIMAX, LSTM networks, and RF. We employed forecasting performance metrics to measure bias, accuracy, and variance, and the empirical evidence suggests that the new proposition is (statistically) significantly better. Furthermore, our method ranks the explanatory variables in terms of their relative importance. The empirical evaluations are replicated for longer forecasting horizons, and online and offline channels and the same conclusions hold; thus, advocating for the robustness of our forecasting proposition as well as the suitability in multi-channel retail demand forecasting.
Journal: International Journal of Production Research
Pages: 4964-4979
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1735666
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735666
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Template-Type: ReDIF-Article 1.0
Author-Name: Niels De Smet
Author-X-Name-First: Niels
Author-X-Name-Last: De Smet
Author-Name: Stefan Minner
Author-X-Name-First: Stefan
Author-X-Name-Last: Minner
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Author-Name: Bram Desmet
Author-X-Name-First: Bram
Author-X-Name-Last: Desmet
Title: A linearisation approach to the stochastic dynamic capacitated lotsizing problem with sequence-dependent changeovers
Abstract: 
 We present a mixed-integer linear programming formulation that simultaneously optimises lot sizes and production sequences on a capacity constrained machine with sequence-dependent changeovers subject to stochastic dynamic demand while at the same time satisfying a fill rate constraint. To tackle the non-linearity of the exact formulation, we introduce a piecewise linearisation technique both for the expected inventory on hand and for the backorder functions that uses the target service level and the parameters of the demand distribution to assign breakpoints to the most promising intervals of the linearisation domain. We show that our strategy leads to lower cost and to more conservative production plans, in comparison to techniques recommended by earlier research. In addition, we discuss why any breakpoint selection strategy that does not exclude the concave region for  $t \geq 2 $t≥2, is prone to be outperformed by the approach we present. Finally, we propose a Relax-and-Fix with Fix-and-Optimize heuristic, and show based on the broad set of instances from Haase, Knut, and Alf Kimms [2000. “Lot sizing and scheduling with sequence-dependent setup costs and times and efficient rescheduling opportunities.” International Journal of Production Economics 66 (2): 159–169], that it is more effective than a state-of-the-art solver in terms of run time and solution quality.
Journal: International Journal of Production Research
Pages: 4980-5005
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1736722
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1736722
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Template-Type: ReDIF-Article 1.0
Author-Name: Peter Ralston
Author-X-Name-First: Peter
Author-X-Name-Last: Ralston
Author-Name: Jennifer Blackhurst
Author-X-Name-First: Jennifer
Author-X-Name-Last: Blackhurst
Title: Industry 4.0 and resilience in the supply chain: a driver of capability enhancement or capability loss?
Abstract: 
 The purpose of this research is to develop a better understanding of smart systems and autonomous processes of the Industry 4.0 era. Does the implementation of Industry 4.0 processes and systems expose firms to higher levels of risk in the supply chain through capability loss or does Industry 4.0 spur capability enhancement and thereby increase supply chain resilience? Industry 4.0 is centred on the idea that certain tasks and decisions can be automated through smart systems and autonomous processes. However, is there a risk of losing critical capabilities and the ability to be flexible, agile and resilient to unexpected disruptions in the supply chain? In order to address these questions, this research presents results from semi-structured interviews across multiple industries to provide findings on firms’ uses of smart systems and capability development associated with these systems. Results from this exploratory study may be classified into two primary insights. First, although Industry 4.0 systems are new and, in many cases untested, firms are eager regarding the potential of smart systems to positively impact firm performance and to leverage Industry 4.0 processes for a competitive supply chain advantage. Second, companies did not claim any human capability loss associated with Industry 4.0. In fact, these smart systems may lead to increased supply chain resilience because of capability enhancement and new skill development.
Journal: International Journal of Production Research
Pages: 5006-5019
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1736724
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1736724
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Template-Type: ReDIF-Article 1.0
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme Luz
Author-X-Name-Last: Tortorella
Author-Name: Ninad Pradhan
Author-X-Name-First: Ninad
Author-X-Name-Last: Pradhan
Author-Name: Enrique Macias de Anda
Author-X-Name-First: Enrique
Author-X-Name-Last: Macias de Anda
Author-Name: Samuel Trevino Martinez
Author-X-Name-First: Samuel
Author-X-Name-Last: Trevino Martinez
Author-Name: Rupy Sawhney
Author-X-Name-First: Rupy
Author-X-Name-Last: Sawhney
Author-Name: Maneesh Kumar
Author-X-Name-First: Maneesh
Author-X-Name-Last: Kumar
Title: Designing lean value streams in the fourth industrial revolution era: proposition of technology-integrated guidelines
Abstract: 
 Despite the envisioned interrelations, the way Industry 4.0 (I4.0) technologies can influence the design and implementation of lean value streams is still unknown and little empirical evidence is found in the literature. This article aims at proposing guidelines integrated with I4.0 technologies for designing lean value streams. We gathered experts’ opinions regarding the relationship between guidelines for designing a lean value stream and I4.0 technologies. The identification of the most important relationships provided arguments for the proposition of enhanced guidelines for designing lean value streams within the Fourth Industrial Revolution context. The integration of I4.0 technologies into the guidelines for designing a lean value stream raises a distinct approach that benefits from the simplicity and efficiency of Lean Production with ease and agility of the technologies typical of the Fourth Industrial Revolution. Such technology-integrated guidelines may allow overcoming existing barriers while lead companies to superior performance results.
Journal: International Journal of Production Research
Pages: 5020-5033
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1743893
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1743893
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Template-Type: ReDIF-Article 1.0
Author-Name: Miguel Núñez-Merino
Author-X-Name-First: Miguel
Author-X-Name-Last: Núñez-Merino
Author-Name: Juan Manuel Maqueira-Marín
Author-X-Name-First: Juan Manuel
Author-X-Name-Last: Maqueira-Marín
Author-Name: José Moyano-Fuentes
Author-X-Name-First: José
Author-X-Name-Last: Moyano-Fuentes
Author-Name: Pedro José Martínez-Jurado
Author-X-Name-First: Pedro José
Author-X-Name-Last: Martínez-Jurado
Title: Information and digital technologies of Industry 4.0 and Lean supply chain management: a systematic literature review
Abstract: 
 The purpose of this paper is to provide an overview of the current state of research and the key aspects and implications of the relationships between Information and Digital Technologies (IDT) of Industry 4.0 and Lean Supply Chain Management (LSCM), with the identification of the lines of research developed and an analysis of the main findings. A Systematic Literature Review methodology has been used for the identification, selection, and evaluation of the published research. A set of 78 papers deduced from the most relevant scientific databases, including Web of Science, Scopus, and ABI/Inform, from 1996 to December 2019, has been analyzed and synthesized. The analysis and evaluation of these papers has enabled a new classification of the literature to be offered that identifies four lines of research based on the Life Cycle of Technology: obsolete IDT in LSCM; mature IDT in LSCM; emerging IDT in LSCM; and an Information Systems and IDT general approach in LSCM. The paper goes on to discuss the gaps found in the literature and proposes new opportunities and challenges for future research. A series of implications are presented intended to be useful from not only an academic point-of-view but also from a management focus, including recommendations for industrial managers and policymakers.
Journal: International Journal of Production Research
Pages: 5034-5061
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1743896
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1743896
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Template-Type: ReDIF-Article 1.0
Author-Name: Byeongseop Kim
Author-X-Name-First: Byeongseop
Author-X-Name-Last: Kim
Author-Name: Yongkuk Jeong
Author-X-Name-First: Yongkuk
Author-X-Name-Last: Jeong
Author-Name: Jong Gye Shin
Author-X-Name-First: Jong Gye
Author-X-Name-Last: Shin
Title: Spatial arrangement using deep reinforcement learning to minimise rearrangement in ship block stockyards
Abstract: 
 As the shipbuilding industry is an engineering-to-order industry, different types of products are manufactured according to customer requests, and each product goes through different processes and workshops. During the shipbuilding process, if the product is not able to go directly to the subsequent process due to physical constraints of workshop, it temporarily waits in a stockyard. Since the waiting process involves unpredictable circumstances, plans regarding time and space cannot be established in advance. Therefore, unnecessary movement often occurs when ship blocks enter or depart from the stockyard. In this study, a reinforcement learning approach was proposed to minimise rearrangement in such circumstances. For this purpose, an environment in which blocks are arranged and rearranged was defined. Rewards based on the simplified rules were logically defined, and simulation was performed for quantitative evaluation using the proposed reinforcement learning algorithm. This algorithm was verified using an example model derived from actual data from a shipyard. The method proposed in this study can be used not only to the arrangement problem of ship block stockyards but also to the various arrangement and allocation problems or logistics problems in the manufacturing industry.
Journal: International Journal of Production Research
Pages: 5062-5076
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1748247
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1748247
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Template-Type: ReDIF-Article 1.0
Author-Name: Li Jiang
Author-X-Name-First: Li
Author-X-Name-Last: Jiang
Author-Name: Mohamed Dhiaf
Author-X-Name-First: Mohamed
Author-X-Name-Last: Dhiaf
Author-Name: Junfeng Dong
Author-X-Name-First: Junfeng
Author-X-Name-Last: Dong
Author-Name: Changyong Liang
Author-X-Name-First: Changyong
Author-X-Name-Last: Liang
Author-Name: Shuping Zhao
Author-X-Name-First: Shuping
Author-X-Name-Last: Zhao
Title: A traveling salesman problem with time windows for the last mile delivery in online shopping
Abstract: 
 With the fast growth of the parcel volume of online shopping, home delivery (delivering parcels to customers’ homes or workplaces) has accentuated the pressure on last mile delivery actors. Customer pickup, which allows customers to pick up their parcels from shared delivery facilities near them, has become widely popular. This study introduces a novel travelling salesman problem with time windows for the last mile delivery in online shopping. The purpose is to find a minimum cost tour over given customers and/or shared delivery facilities (SDFs) in which unvisited customers are assigned to the SDFs. A general variable neighbourhood search heuristic is developed to solve the problem. Computational results corroborate that the proposed heuristic is competitive relative to well-known algorithms.
Journal: International Journal of Production Research
Pages: 5077-5088
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2019.1656842
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656842
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianxin (Roger) Jiao
Author-X-Name-First: Jianxin (Roger)
Author-X-Name-Last: Jiao
Author-Name: Feng Zhou
Author-X-Name-First: Feng
Author-X-Name-Last: Zhou
Author-Name: Nagi Z. Gebraeel
Author-X-Name-First: Nagi Z.
Author-X-Name-Last: Gebraeel
Author-Name: Vincent Duffy
Author-X-Name-First: Vincent
Author-X-Name-Last: Duffy
Title: Towards augmenting cyber-physical-human collaborative cognition for human-automation interaction in complex manufacturing and operational environments
Abstract: 
 The importance of augmenting human-technology collaborative cognition has been envisioned as one of the fundamental ways to bolster human cognition through human-automation interaction in complex manufacturing and operational environments. The focus on collaborative cognition entails a human-automation mutual adaption strategy for augmenting team cognition and collective intelligence. This paper provides an overview of augmenting collaborative cognition from an analytic and model-based decision-making perspective. Aiming to advance basic research for understanding human cognition augmentation, the fundamental and applied aspects of creating mathematical and computational models are discussed in regard to cognitive state sensing and assessment, human-automation interaction adaption and control, as well as group decision making in human-automation systems. A research roadmap towards cyber-physical-human analysis is deliberated to reveal a variety of opportunities of developing novel methods for enhancing affective cognition and perception learning, trust dynamics modelling, human cognitive performance prediction, as well as human-automation interaction optimisation.
Journal: International Journal of Production Research
Pages: 5089-5111
Issue: 16
Volume: 58
Year: 2020
Month: 7
X-DOI: 10.1080/00207543.2020.1722324
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1722324
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Template-Type: ReDIF-Article 1.0
Author-Name: Chang Liu
Author-X-Name-First: Chang
Author-X-Name-Last: Liu
Author-Name: Yongfu Feng
Author-X-Name-First: Yongfu
Author-X-Name-Last: Feng
Author-Name: Dongtao Lin
Author-X-Name-First: Dongtao
Author-X-Name-Last: Lin
Author-Name: Liang Wu
Author-X-Name-First: Liang
Author-X-Name-Last: Wu
Author-Name: Min Guo
Author-X-Name-First: Min
Author-X-Name-Last: Guo
Title: Iot based laundry services: an application of big data analytics, intelligent logistics management, and machine learning techniques
Abstract: 
 The authors propose an innovative Internet of Things (IoT) based E-commerce business model Cloud Laundry for mass scale laundry services. The model utilises big data analytics, intelligent logistics management, and machine learning techniques. Using GPS and real-time update of big data, it calculates the best transportation path and update and re-route the logistic terminals quickly and simultaneously. Cloud laundry intelligently and dynamically provides the best laundry solutions based on the current state spaces of the laundry terminals through the user's specifications and thus offers local hotel customers with convenient, efficient, and transparent laundry services. Taking advantage of the rapid development of the big data industry, user interest modelling, and information security and privacy considerations, cloud laundry uses smartphone terminal control and big data models to maintain customers’ security needs. Different from the traditional laundry industry, cloud laundry companies have higher capital turnover, more liquidity, and stronger profitability. Therefore, this new generation of smart laundry business model could be of interest to not only academic researchers, but E-commerce entrepreneurs as well.
Journal: International Journal of Production Research
Pages: 5113-5131
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1677961
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1677961
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Template-Type: ReDIF-Article 1.0
Author-Name: Min Kong
Author-X-Name-First: Min
Author-X-Name-Last: Kong
Author-Name: Jun Pei
Author-X-Name-First: Jun
Author-X-Name-Last: Pei
Author-Name: Jin Xu
Author-X-Name-First: Jin
Author-X-Name-Last: Xu
Author-Name: Xinbao Liu
Author-X-Name-First: Xinbao
Author-X-Name-Last: Liu
Author-Name: Xiaoyu Yu
Author-X-Name-First: Xiaoyu
Author-X-Name-Last: Yu
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Title: A robust optimization approach for integrated steel production and batch delivery scheduling with uncertain rolling times and deterioration effect
Abstract: 
 Efficient collaboration between various sub-processes of steel production is of considerable significance, which directly affects a product’s production cycle and energy consumption. However, current collaborative optimisation models and methods in steel production are still limited: (1) Most of the current collaborative manufacturing problems in steel production focus on obtaining joint schedule between steel-making and continuous casting (SCC), and the works considering continuous casting and hot rolling (CCHR) are very few. (2) The processing time is assumed as a constant in most of the existing SCC scheduling models. However, the rolling time of a product in hot rolling operation is actually uncertain and deteriorating. (3) Exact algorithms cannot be applied to solve the complicated collaborative optimisation problems because of their high complexities. To address these problems, we propose an integrated CCHR and batch delivery scheduling model where interval rolling time and linear deterioration effect are considered. With the concept of min–max regret value, we formulate the collaborative optimisation problem as a robust optimisation problem. Instead of using the exact algorithm, we develop an Improved Variable Neighborhood Search (IVNS) algorithm incorporated a novel population update mechanism and neighbourhood structures to solve the robust optimisation problem. Moreover, we develop an exact algorithm that combines CPLEX solver and two dynamic programming algorithms to obtain the maximum regret value of a given rolling sequence. The results of computational experiments show the excellent performance of the proposed algorithms.Abbreviations: IVNS: improved variable neighbourhood search; TOPSIS: technique for order of preference by similarity to ideal solution; PUM-TOPSIS: population update mechanism based on TOPSIS; DP: dynamic programming; NSs-PUC: neighbourhood structures based on the parameterised uniform crossover; SNRT: shortest normal rolling time; SNRT-DP: DP algorithm based on SNRT rule; BRKGA: biased random-key genetic algorithm; SCC: steelmaking and continuous casting; MINP: mixed integer nonlinear programme; CCHR: continuous casting and hot rolling; PSO: particle swarm optimisation; GA: genetic algorithm; VNS-HS: variable neighbourhood search and harmony search; HPSO + GA: hybrid PSO and GA; SA: simulated annealing; B&B: branch-and-bound; TPSO: two-phase soft optimisation; TSAUN: tabued simulated annealing with united-scenario neighbourhood; VNS: variable neighbourhood search; ABC: artificial bee colony; PRVNS: population-based reduced variable neighbourhood search; NS1: neighbourhood structure 1; NS2: neighbourhood structure 2; DE: differential evolution; WSR: Wilcoxon signed-rank test; ENS: exchange neighbourhood structure; IVNS-ENS: IVNS with ENS; RPI: relative percentage increase; ARPI: average RPI; SD: standard deviation.
Journal: International Journal of Production Research
Pages: 5132-5154
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1693659
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Template-Type: ReDIF-Article 1.0
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: Z.X. Wang
Author-X-Name-First: Z.X.
Author-X-Name-Last: Wang
Author-Name: A. Goswami
Author-X-Name-First: A.
Author-X-Name-Last: Goswami
Author-Name: A. Singhania
Author-X-Name-First: A.
Author-X-Name-Last: Singhania
Author-Name: M.K. Tiwari
Author-X-Name-First: M.K.
Author-X-Name-Last: Tiwari
Title: Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations
Abstract: 
 Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO2 emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.
Journal: International Journal of Production Research
Pages: 5155-5174
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1701209
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Template-Type: ReDIF-Article 1.0
Author-Name: Wen Jun Tan
Author-X-Name-First: Wen Jun
Author-X-Name-Last: Tan
Author-Name: Wentong Cai
Author-X-Name-First: Wentong
Author-X-Name-Last: Cai
Author-Name: Allan N. Zhang
Author-X-Name-First: Allan N.
Author-X-Name-Last: Zhang
Title: Structural-aware simulation analysis of supply chain resilience
Abstract: 
 Supply chain resilience (SCRES) refers to the ability of a supply chain (SC) to both resist disruptions and recover its operational capability after disruptions. This paper presents a simulation model that includes network structural properties in the analysis of SCRES. This simulation model extends an existing graph model to consider operational behaviours in order to capture disruption-recovery dynamics. Through structural analysis of a supply chain network (SCN), mitigation strategies are designed to build redundancy, while contingency strategies are developed to prioritise recovery of the affected SCN. SCRES indexes are proposed by sampling SC performance measures of disruption for each plant and aggregating the measures based on the criticality of the plants in the SCN. The applicability of this simulation model is demonstrated in a real-world case study of different disruption scenarios. The application of mitigation and contingency strategies is shown to both improve recovery and reduce the total costs associated with disruptions. Through such simulation-based analysis, firms can gain insight into the SCRES of their existing SCNs and identify suitable strategies to improve SCRES by considering recovery time and costs.
Journal: International Journal of Production Research
Pages: 5175-5195
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1705421
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1705421
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Template-Type: ReDIF-Article 1.0
Author-Name: Pankaj C. Patel
Author-X-Name-First: Pankaj C.
Author-X-Name-Last: Patel
Author-Name: Gurjeet Kaur Sahi
Author-X-Name-First: Gurjeet Kaur
Author-X-Name-Last: Sahi
Author-Name: Mahesh Gupta
Author-X-Name-First: Mahesh
Author-X-Name-Last: Gupta
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Title: Service profit chain and throughput orientation: a manager-employee-customer triad perspective in services
Abstract: 
 Building on the Theory of Constraints (TOC) in the service context and drawing on internal and external service profit chain literature, we explore the role of throughput orientation at the manager-employee-customer triad level. Controlling for archival performance data at the branch level of banks, in a sample of 136 triads of managers-frontline employees-customers at 37 branches from a bank in a northern state in India, we find that throughput orientation is positively associated with external service profit chain; and this association is further strengthened under stronger internal service profit chain. By integrating a service-operations based perspective of service employees at a triadic level, we demonstrate the importance of throughput orientation in service profit chains.
Journal: International Journal of Production Research
Pages: 5196-5217
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1708991
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1708991
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Template-Type: ReDIF-Article 1.0
Author-Name: Elisabeth Brevik
Author-X-Name-First: Elisabeth
Author-X-Name-Last: Brevik
Author-Name: Anna Ø. Lauen
Author-X-Name-First: Anna Ø.
Author-X-Name-Last: Lauen
Author-Name: Maria C. B. Rolke
Author-X-Name-First: Maria C. B.
Author-X-Name-Last: Rolke
Author-Name: Kjetil Fagerholt
Author-X-Name-First: Kjetil
Author-X-Name-Last: Fagerholt
Author-Name: Jone R. Hansen
Author-X-Name-First: Jone R.
Author-X-Name-Last: Hansen
Title: Optimisation of the broiler production supply chain
Abstract: 
 In this paper, we propose a mixed integer programming (MIP) model for the Chicken Flock Sizing, Allocation and Scheduling Problem (CFSASP), which is an important planning problem in the broiler production supply chain. To solve the CFSASP efficiently, two variants of rolling horizon heuristics (RHHs) have been developed and applied on the case of a Norwegian broiler production company. Computational results show that the RHHs successfully obtain high-quality solutions within a reasonable time. The value of optimisation is verified through comparison with the case company's plans, where the solutions from optimisation outperforms the current solutions. Sensitivity analyses are also conducted to provide managerial insights regarding certain strategic decisions, such as how many and which days to use for hatching of chickens. Due to the promising results, the case company is now implementing an optimisation-based decision support system based on the MIP model and solution methods shown in this paper.
Journal: International Journal of Production Research
Pages: 5218-5237
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2020.1713415
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1713415
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Template-Type: ReDIF-Article 1.0
Author-Name: Wilma Polini
Author-X-Name-First: Wilma
Author-X-Name-Last: Polini
Author-Name: Andrea Corrado
Author-X-Name-First: Andrea
Author-X-Name-Last: Corrado
Title: Digital twin of composite assembly manufacturing process
Abstract: 
 Industry is facing the management of geometrical deviations along the entire lifecycle of the product. It is helped by digital twin tools that may minimise the geometrical deviations from nominal of products. The new digital twin tools allow to manage geometrical variations through a set of steps fully related by modern information and communication technologies that establish a continuous and unambiguous flow of information among the different steps of this digital process along the whole product lifecycle. They are based on data coming from manufacturing, assembly and inspection. The available large data sets from manufacturing and inspection allow to develop new and more accurate simulation models that realistically consider form deviations and process signature, i.e. the pattern left by the manufacturing process on the produced part surfaces. The present work introduces a digital twin tool to support the lightweight design of assemblies in composite material. It establishes a continuous and unambiguous flow of variation information from the part design to assembly, passing through manufacturing by considering the manufacturing signature. It was applied to a case study and the obtained results agree with the experimental ones.
Journal: International Journal of Production Research
Pages: 5238-5252
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2020.1714091
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1714091
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Template-Type: ReDIF-Article 1.0
Author-Name: Ehsan Badakhshan
Author-X-Name-First: Ehsan
Author-X-Name-Last: Badakhshan
Author-Name: Paul Humphreys
Author-X-Name-First: Paul
Author-X-Name-Last: Humphreys
Author-Name: Liam Maguire
Author-X-Name-First: Liam
Author-X-Name-Last: Maguire
Author-Name: Ronan McIvor
Author-X-Name-First: Ronan
Author-X-Name-Last: McIvor
Title: Using simulation-based system dynamics and genetic algorithms to reduce the cash flow bullwhip in the supply chain
Abstract: 
 The bullwhip effect (BWE) is a phenomenon, which is caused by ineffective inventory decisions made by supply chain members. In addition to known inefficiencies caused by the bullwhip effect within a supply chain product flow, such as excessive inventory, it can also lead to inefficiencies in cash flow such as the cash flow bullwhip (CFB). The CFB reduces the efficiency of the supply chain (SC) through heterogeneous distribution of cash among supply chain members. This paper aims to decrease both the BWE and the CFB across a SC through applying a simulation-based optimisation approach, which integrates system dynamics (SD) simulation and genetic algorithms. For this purpose, cash flow modelling is incorporated into the SD structure of the beer distribution game (BG) to develop the CFB function. A multi objective optimisation model is then integrated with the SD-BG simulation model. Finally, a genetic algorithm (GA) is applied to determine the optimal values for the inventory, supply line, and financial decision parameters. Results show that the proposed integrated framework leads to efficient liquidity management in the SC in addition to cost management.
Journal: International Journal of Production Research
Pages: 5253-5279
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2020.1715505
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1715505
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Template-Type: ReDIF-Article 1.0
Author-Name: Ehsan Aghamohammadzadeh
Author-X-Name-First: Ehsan
Author-X-Name-Last: Aghamohammadzadeh
Author-Name: Omid Fatahi Valilai
Author-X-Name-First: Omid
Author-X-Name-Last: Fatahi Valilai
Title: A novel cloud manufacturing service composition platform enabled by Blockchain technology
Abstract: 
 In the near future, manufacturing industries will be mostly recognised with characteristics like IoT, and massive data transactions. To fulfil these characteristics, paradigms like Cloud manufacturing, Industry 4.0 and smart factory have passed their preliminary steps to become the primary inspirations. Considering the nature of Cloud manufacturing which consists of a vast number of service providers and Service demanders being introduced to the manufacturing cloud, service composition problem is introduced. However, there is a big challenge for fulfilling the dynamic behaviour of parameters which change rapidly over time in the service composition problem. This paper challenges the centralised mechanism of service composition problem and introduces a novel platform entitled Blockchain-based service composition model (Block-SC) based on the Blockchain technology. Block-SC as a novel manufacturing architecture conquers the centralised mechanism by dividing the original service composition problem into multiple sub-problems each of which contains a small fraction of the service/task pool. The capabilities of the proposed platform are remarkable from two perspectives; first, it provides an effective mechanism for collaboration of service composition service providers with a service-oriented approach and from the second perspective, the optimality of service composition problem is profoundly affected considering the dynamic behaviour of Cloud manufacturing.
Journal: International Journal of Production Research
Pages: 5280-5298
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2020.1715507
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1715507
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Template-Type: ReDIF-Article 1.0
Author-Name: Francisco J. Tapia-Ubeda
Author-X-Name-First: Francisco J.
Author-X-Name-Last: Tapia-Ubeda
Author-Name: Pablo A. Miranda
Author-X-Name-First: Pablo A.
Author-X-Name-Last: Miranda
Author-Name: Irene Roda
Author-X-Name-First: Irene
Author-X-Name-Last: Roda
Author-Name: Marco Macchi
Author-X-Name-First: Marco
Author-X-Name-Last: Macchi
Author-Name: Orlando Durán
Author-X-Name-First: Orlando
Author-X-Name-Last: Durán
Title: Modelling and solving spare parts supply chain network design problems
Abstract: 
 Spare parts are key operational assets in order to minimise unexpected equipment downtimes that may significantly impact a company’s results. The spare parts supply chain network supports the entire spare parts operations management and it is essential to achieve the planned goals. However, most of the traditional literature on spare parts management has not focused on the underlying supply chain network. Thus, this paper studies the integration of supply chain network design and control with traditional spare parts management. In particular, a generic network optimisation modelling structure is proposed, with simultaneous optimisation of warehouse locations and inventory control decisions, allowing minimising the total costs associated with the spare parts supply chain network. The generic model is specified based on three inventory control policies widely employed in the industry, which are suitable for managing a great variety of spare parts, i.e. (s, Q), (R, s, S) and (S-1, S). Furthermore, a solution approach is proposed based on Generalised Benders Decomposition. Finally, numerical results from a real-world application case in the process industry are shown and discussed.
Journal: International Journal of Production Research
Pages: 5299-5319
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2020.1720924
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1720924
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Template-Type: ReDIF-Article 1.0
Author-Name: Pascal Wichmann
Author-X-Name-First: Pascal
Author-X-Name-Last: Wichmann
Author-Name: Alexandra Brintrup
Author-X-Name-First: Alexandra
Author-X-Name-Last: Brintrup
Author-Name: Simon Baker
Author-X-Name-First: Simon
Author-X-Name-Last: Baker
Author-Name: Philip Woodall
Author-X-Name-First: Philip
Author-X-Name-Last: Woodall
Author-Name: Duncan McFarlane
Author-X-Name-First: Duncan
Author-X-Name-Last: McFarlane
Title: Extracting supply chain maps from news articles using deep neural networks
Abstract: 
 Supply chains are increasingly global, complex and multi-tiered. Consequently, companies often struggle to maintain complete visibility of their supply network. This poses a problem as visibility of the network structure is required for tasks like effectively managing supply chain risk. In this paper, we discuss automated supply chain mapping as a means of maintaining structural visibility of a company's supply chain, and we use Deep Learning to automatically extract buyer–supplier relations from natural language text. Early results show that supply chain mapping solutions using Natural Language Processing and Deep Learning could enable companies to (a) automatically generate rudimentary supply chain maps, (b) verify existing supply chain maps, or (c) augment existing maps with additional supplier information.
Journal: International Journal of Production Research
Pages: 5320-5336
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2020.1720925
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1720925
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Template-Type: ReDIF-Article 1.0
Author-Name: Makusee Masae
Author-X-Name-First: Makusee
Author-X-Name-Last: Masae
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: Panupong Vichitkunakorn
Author-X-Name-First: Panupong
Author-X-Name-Last: Vichitkunakorn
Title: Optimal order picker routing in a conventional warehouse with two blocks and arbitrary starting and ending points of a tour
Abstract: 
 This paper investigates manual order picking, where workers travel through the warehouse to retrieve requested items from shelves. To minimise the completion time of orders, researchers have developed various routing procedures that guide order pickers through the warehouse. The paper at hand contributes to this stream of research and proposes an optimal order picker routing policy for a conventional warehouse with two blocks and arbitrary starting and ending points of a tour. The procedure proposed in this paper extends an earlier work of Löffler et al. (2018. Picker routing in AGV-assisted order picking systems, Working Paper, DPO-01/2018, Deutsche Post Chair-Optimization of Distribution Networks, RWTH Aachen University, 2018) by applying the concepts of Ratliff and Rosenthal (1983. “Order-picking in a Rectangular Warehouse: a Solvable Case of the Traveling Salesman Problem.” Operations Research 31 (3): 507–521) and Roodbergen and de Koster (2001a. “Routing Order Pickers in a Warehouse with a Middle Aisle.” European Journal of Operational Research 133 (1): 32–43) that used graph theory and dynamic programming for finding an optimal picker route. We also propose a routing heuristic, denoted S*-shape, for conventional two-block warehouses with arbitrary starting and ending points of a tour. In computational experiments, we compare the average order picking tour length in a conventional warehouse with a single block to the case of a conventional warehouse with two blocks to assess the impact of the middle cross aisle on the performance of the warehouse. Furthermore, we evaluate the performance of the S*-shape heuristic by comparing it to the exact algorithm proposed in this study.
Journal: International Journal of Production Research
Pages: 5337-5358
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2020.1724342
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1724342
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhaoguang Xu
Author-X-Name-First: Zhaoguang
Author-X-Name-Last: Xu
Author-Name: Yanzhong Dang
Author-X-Name-First: Yanzhong
Author-X-Name-Last: Dang
Title: Automated digital cause-and-effect diagrams to assist causal analysis in problem-solving: a data-driven approach
Abstract: 
 Causal analysis is an integral part of product quality problem-solving (QPS). Quality management within the manufacturing industry has generated a considerable amount of QPS data; while this implies a historical and extensive body of QPS experience, these valuable empirical data are not being fully utilised. Therefore, the current study proposes a method by which to mine know-why from historical empirical data, and it develops an approach for constructing digital cause-and-effect diagrams (CEDs). The K-means algorithm is first adopted to cluster the problems and causes. The random forest classifier is then selected to classify cause text into the main cause categories, which manifest as ‘rib branches’ in the CED. Based on the clustering and classification results, we obtain an abstract cause-and-effect diagram (ACED) and a detailed cause-and-effect diagram (DCED). We use the quality data of an automotive company to validate the method, and we additionally undertake a pilot run of the Fishbone Next system to demonstrate how users can obtain these two CEDs to support causal analysis in QPS. The results show that the proposed approach efficiently constructs a digital CED and thus provides quality management problem-solvers with decision support to derive the potential causes of problems, thereby improving the efficiency and effectiveness of their causal analysis initiatives.
Journal: International Journal of Production Research
Pages: 5359-5379
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2020.1727043
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1727043
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Template-Type: ReDIF-Article 1.0
Author-Name: Jighyasu Gaur
Author-X-Name-First: Jighyasu
Author-X-Name-Last: Gaur
Author-Name: Mehdi Amini
Author-X-Name-First: Mehdi
Author-X-Name-Last: Amini
Author-Name: Arza Keshava Rao
Author-X-Name-First: Arza Keshava
Author-X-Name-Last: Rao
Title: The impact of supply chain disruption on the closed-loop supply chain configuration profit: a study of sourcing policies
Abstract: 
 A closed-loop supply chain configuration (CLSCC) encompasses the decisions related to the optimal selection of options at each stage of a closed-loop supply chain (CLSC) for the introduction and reconstruction of new products. The extant literature ignores the impact of supply chain disruptions on CLSCC. An attempt is made to fill this gap in this study. Thus, an integrated multi-sourcing CLSCC optimisation model for new and reconstructed products is developed. The optimisation model presented is a mixed-integer nonlinear programming (MINLP) model. Based on a real-world case study of an auto-parts manufacturer in India presented, a comprehensive set of computational experiments, scenario analyses are conducted. The key finding/observation that resulted from our computational experiments is that multi-sourcing generates higher net present value of total profit compared to single sourcing under the risk of supply chain disruption. Several other observations and managerial insights are drawn from computational experiments, and scenario analyses. Firms interested in configuring their CLSC under the risk of supply chain disruption may use the study's outcomes to understand the profit impact of various CLSCC parameters, individually and in combination.
Journal: International Journal of Production Research
Pages: 5380-5400
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1657244
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1657244
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Template-Type: ReDIF-Article 1.0
Author-Name: Manuel Parente
Author-X-Name-First: Manuel
Author-X-Name-Last: Parente
Author-Name: Gonçalo Figueira
Author-X-Name-First: Gonçalo
Author-X-Name-Last: Figueira
Author-Name: Pedro Amorim
Author-X-Name-First: Pedro
Author-X-Name-Last: Amorim
Author-Name: Alexandra Marques
Author-X-Name-First: Alexandra
Author-X-Name-Last: Marques
Title: Production scheduling in the context of Industry 4.0: review and trends
Abstract: 
 Notwithstanding its disruptive potential, which has been the object of considerable debate, Industry4.0 (I4.0) operationalisation still needs significant study. Specifically, scheduling is a key process that should be explored from this perspective. The purpose of this study is to shed light on the issues regarding scheduling that need to be considered in the new I4.0 framework. To achieve this, a two-stage cascade literature review is performed. The review begins with an analysis regarding the opportunities and challenges brought by I4.0 to the scheduling field, outputting a set of critical scheduling areas (CSA) in which development is essential. The second-stage literature review is performed to understand which steps have been taken so far by previous research in the scheduling field to address those challenges. Thus, a first contribution of this work is to provide insight on the influence and expected changes brought by I4.0 to scheduling, while showcasing relevant research. Another contribution is to identify the most promising future lines of research in this field, in which relevant challenges such as holistic scheduling, or increased flexibility requirements are highlighted. Concurrently, CSA such as decentralised decision-making, and human–robot collaboration display large gaps between current practice and the required technological level of development.
Journal: International Journal of Production Research
Pages: 5401-5431
Issue: 17
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2020.1718794
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1718794
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Template-Type: ReDIF-Article 1.0
Author-Name: Xianhao Xu
Author-X-Name-First: Xianhao
Author-X-Name-Last: Xu
Author-Name: Xiaozhen Zhao
Author-X-Name-First: Xiaozhen
Author-X-Name-Last: Zhao
Author-Name: Bipan Zou
Author-X-Name-First: Bipan
Author-X-Name-Last: Zou
Author-Name: Yeming (Yale) Gong
Author-X-Name-First: Yeming (Yale)
Author-X-Name-Last: Gong
Author-Name: Hongwei Wang
Author-X-Name-First: Hongwei
Author-X-Name-Last: Wang
Title: Travel time models for a three-dimensional compact AS/RS considering different I/O point policies
Abstract: 
 This paper studies a three-dimensional automated storage and retrieval system that uses conveyors for depth transportation and a crane for both horizontal and vertical transportation. While previous studies put input and output points together at the system bottom, we consider separating and elevating them by proposing four I/O point policies: input and output points at two sides, input and output points elevated at one side, input and output points elevated at two sides, input and output points elevated at a midpoint. We build travel time models to analyse these policies and use simulation for validation. We theoretically find the optimal system structure and compare these I/O point policies, in terms of expected S/R machine travel time. The results show that the square-in-time structure is optimal in most cases and the mid-point elevation I/O point policy performs the best in terms of expected travel time. Moreover, we compare our I/O point policies with the lower mid-point policy. The results show that the mid-point elevation I/O point policy outperforms the I/O point at the lower mid-point by about  $6.07\% $6.07% in terms of expected travel time, while other I/O point policies are dominated by the I/O point at the lower mid-point.
Journal: International Journal of Production Research
Pages: 5432-5455
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1659519
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1659519
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Template-Type: ReDIF-Article 1.0
Author-Name: Claudio Vitari
Author-X-Name-First: Claudio
Author-X-Name-Last: Vitari
Author-Name: Elisabetta Raguseo
Author-X-Name-First: Elisabetta
Author-X-Name-Last: Raguseo
Title: Big data analytics business value and firm performance: linking with environmental context
Abstract: 
 Previous studies, grounded on the resource based view, have already explored the relationship between the business value that Big Data Analytics (BDA) can bring to firm performance. However, the role played by the environmental characteristics in which companies operate has not been investigated in the literature. We inform the theory, in that direction, via the integration of the contingency theory to the resource based view theory of the firm. This original and integrative model examines the moderating influence of environmental features on the relationship between BDA business value and firm performance. The combination of survey data and secondary financial data on a representative sample of medium and large companies makes possible the statistical validation of our research model. The results offer evidence that BDA business value leads to higher firm performance, namely financial performance, market performance and customer satisfaction. More original is the demonstration that this relationship is stronger in munificent environments, while the dynamism of the environment does not have any moderating effect on the performance of BDA solutions. It means that managers working for firms in markets with a growing demand are in the best position to profit from BDA.
Journal: International Journal of Production Research
Pages: 5456-5476
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1660822
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660822
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Template-Type: ReDIF-Article 1.0
Author-Name: Tarik Chargui
Author-X-Name-First: Tarik
Author-X-Name-Last: Chargui
Author-Name: Abdelghani Bekrar
Author-X-Name-First: Abdelghani
Author-X-Name-Last: Bekrar
Author-Name: Mohamed Reghioui
Author-X-Name-First: Mohamed
Author-X-Name-Last: Reghioui
Author-Name: Damien Trentesaux
Author-X-Name-First: Damien
Author-X-Name-Last: Trentesaux
Title: Proposal of a multi-agent model for the sustainable truck scheduling and containers grouping problem in a Road-Rail physical internet hub
Abstract: 
 Physical Internet (PI) was introduced as a global standardised and interconnected logistics system based on PI-nodes, PI-movers and PI-containers as a mean toward global logistics sustainability. One important issue regarding PI-nodes concerns the planning and scheduling of operations and the management of PI-containers, both in a deterministic and a perturbed environment. This research considers the Road-Rail PI-hub sustainable truck scheduling and PI-containers grouping problem. In our research we consider the weighted sum of the number of used wagons, the internal distance travelled by PI-containers from PI-docks to wagons as well as the trucks’ tardiness, which translate the search for sustainable logistics. In this paper, an effective and reactive multi-agent system based model (MAS) is developed for the resolution of the trucks scheduling and PI-containers grouping. To ensure the efficiency of the MAS and improve the quality of each of its solutions, three concurrent hybrid meta-heuristics are embedded within three parallel scheduling agents. Then, a mixed integer linear programming model (MILP) is proposed to evaluate the performance of the MAS. Finally, the MAS is also evaluated under internal perturbations. The obtained results show the ability of the MAS to provide alternative sustainable solutions by rescheduling trucks in case of disruptions.
Journal: International Journal of Production Research
Pages: 5477-5501
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1660825
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660825
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Template-Type: ReDIF-Article 1.0
Author-Name: Ahlam Azzamouri
Author-X-Name-First: Ahlam
Author-X-Name-Last: Azzamouri
Author-Name: Najat Bara
Author-X-Name-First: Najat
Author-X-Name-Last: Bara
Author-Name: Selwa Elfirdoussi
Author-X-Name-First: Selwa
Author-X-Name-Last: Elfirdoussi
Author-Name: Imane Essaadi
Author-X-Name-First: Imane
Author-X-Name-Last: Essaadi
Author-Name: Frédéric Fontane
Author-X-Name-First: Frédéric
Author-X-Name-Last: Fontane
Author-Name: Vincent Giard
Author-X-Name-First: Vincent
Author-X-Name-Last: Giard
Title: DSS approach for heterogeneous parallel machines scheduling considering proximate supply chain constraints
Abstract: 
 This paper describes the basis of a Decision Support System (DSS) designed to schedule fertiliser production orders to be delivered within time windows, in plants made up of multiple heterogeneous parallel processors (production lines), considering that fertiliser production rates and nomenclatures depend on lines, that setup times depend on sequence and lines, and taking into account downtime constraints (preventive maintenance …). A mixed linear programming model is encapsulated in the DSS which considers the schedule’s impacts, immediately upstream and downstream of plants in the supply chain. These side-effects may make the proposed solution unfeasible and the DSS helps redefining the problem to avoid them.
Journal: International Journal of Production Research
Pages: 5502-5520
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1661539
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1661539
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Template-Type: ReDIF-Article 1.0
Author-Name: D. G. Mogale
Author-X-Name-First: D. G.
Author-X-Name-Last: Mogale
Author-Name: Naoufel Cheikhrouhou
Author-X-Name-First: Naoufel
Author-X-Name-Last: Cheikhrouhou
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Modelling of sustainable food grain supply chain distribution system: a bi-objective approach
Abstract: 
 Growing food demand, environmental degradation, post-harvest losses and the dearth of resources encourage the decision makers from developing nations to integrate the economic and environmental aspects in food supply chain network design. This paper aims to develop a bi-objective decision support model for sustainable food grain supply chain considering an entire network of procurement centres, central, state and district level warehouses, and fair price shops. The model seeks to minimise the cost and carbon dioxide emission simultaneously. The model covers several problem peculiarities such as multi-echelon, multi-period, multi-modal transportation, multiple sourcing and distribution, emission caused due to various motives, heterogeneous capacitated vehicles and limited availability, and capacitated warehouses. Multiple realistic problem instances are solved using the two Pareto based multi-objective algorithms. Sensitivity analysis results imply that the decision makers should establish a sufficient number of warehouses in each producing and consuming states by maintaining the suitable balance between the two objectives. Various policymakers like Food Corporation of India, logistics providers and state government agencies will be benefited from this research study.
Journal: International Journal of Production Research
Pages: 5521-5544
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1669840
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1669840
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Template-Type: ReDIF-Article 1.0
Author-Name: Mejdal A. Alqahtani
Author-X-Name-First: Mejdal A.
Author-X-Name-Last: Alqahtani
Author-Name: Myong K. Jeong
Author-X-Name-First: Myong K.
Author-X-Name-Last: Jeong
Author-Name: Elsayed A. Elsayed
Author-X-Name-First: Elsayed A.
Author-X-Name-Last: Elsayed
Title: Multilevel spatial randomness approach for monitoring changes in 3D topographic surfaces
Abstract: 
 The 3D surface topography of finished products is a key characteristic for monitoring the quality of products and manufacturing processes. The topography has unique properties in which the topographic values are spatially autocorrelated with their neighbours and the locations of topographic values randomly change from one surface to another under the in-control process behaviour, making the online detection of local topographic changes challenging. Due to the complex structure of topographic data, the existing monitoring approaches lack the detection of local changes. Therefore, we develop a novel online monitoring approach for detecting local changes in 3D topographic surfaces. We introduce a multilevel surface thresholding algorithm for enhancing the representation of topographic values by slicing the 3D surface topography into cumulative levels in reference to the characteristics of the in-control surfaces. The spatial and random properties of topographic values are quantified at each surface level through the proposed spatial randomness profile. After obtaining the spatial randomness profile, an effective monitoring statistic based on the functional principal component analysis is developed for detecting anomaly surfaces. The proposed approach shows superior performance in identifying a wide range of fault patterns and outperforms the existing approaches in both simulated and real-life topographic data.
Journal: International Journal of Production Research
Pages: 5545-5558
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1675918
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1675918
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Template-Type: ReDIF-Article 1.0
Author-Name: Aseem Kinra
Author-X-Name-First: Aseem
Author-X-Name-Last: Kinra
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Ajay Das
Author-X-Name-First: Ajay
Author-X-Name-Last: Das
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Ripple effect quantification by supplier risk exposure assessment
Abstract: 
 Supply chain (SC) disruptions are considered events that temporarily change the structural design and operational policies of SCs with significant resilience implications. The SC dynamics and complexity drive such disruptions beyond local event node boundaries to affect large parts of the SC. The propagation of a disruption through a SC and its associated impact is called the ripple effect. Previous approaches to ripple effect modelling have mainly focused on estimating the likelihood of a disruption; our study looks at the disruption consequences. We develop a new model to assess the ripple effect of a supplier disruption, based on possible maximum loss. Our risk exposure model quantifies the ripple effect, comprehensively combining features such as financial, customer, and operational performance impacts, consideration of multi-echelon inventory, disruption duration, and supplier importance. The ripple effect quantification is validated with simulations using actual company data. The findings suggest that the model can be of value in revealing latent high-risk supplier relations, and in prioritising risk mitigation efforts when probability estimations are difficult. The performance indicators proposed can be used by managers to analyse disruption propagation impact and to identify the set of most critical suppliers to be included in the disruption risk analysis.
Journal: International Journal of Production Research
Pages: 5559-5578
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1675919
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1675919
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Template-Type: ReDIF-Article 1.0
Author-Name: Joseph Geunes
Author-X-Name-First: Joseph
Author-X-Name-Last: Geunes
Author-Name: Yiqiang Su
Author-X-Name-First: Yiqiang
Author-X-Name-Last: Su
Title: Single-period assortment and stock-level decisions for dual sales channels with capacity limits and uncertain demand
Abstract: 
 This paper addresses a dual channel, clicks-and-mortar retailer's problem of determining which among a set of products with seasonal demand will occupy limited retail shelf space, which products will be offered via an online channel, and which items will be available through both channels. Using a consumer choice model in which the set of products offered influences each product's demand in each channel, we consider stocking and price decisions under uncertain demand in a single-period setting with a constraint on the probability of stocking out. The resulting model is a large-scale, chance-constrained, two-stage stochastic programme. We propose a sample average approximation (SAA) method that permits quickly arriving at near-optimal solutions for this complex problem class. We also exercise the proposed model to gain insights on the problem's key tradeoffs and properties of optimal solutions.
Journal: International Journal of Production Research
Pages: 5579-5600
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1693648
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693648
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Template-Type: ReDIF-Article 1.0
Author-Name: Masih Fadaki
Author-X-Name-First: Masih
Author-X-Name-Last: Fadaki
Author-Name: Shams Rahman
Author-X-Name-First: Shams
Author-X-Name-Last: Rahman
Author-Name: Caroline Chan
Author-X-Name-First: Caroline
Author-X-Name-Last: Chan
Title: Leagile supply chain: design drivers and business performance implications
Abstract: 
 In the context of a dynamic and hypercompetitive business environment, effective supply chain design helps organisations to align resources for improved flow of products and services and satisfy customers’ diverse needs. Scholars have proposed several mutually exclusive supply chain designs such as efficient versus responsive, and lean versus agile. Quantitative testing has revealed that supply chain designs of many firms do not match with what was conceptually expected. To address this mismatch, in this study, a new approach to supply chain leagility is introduced and the impact of uncertainty as the key design driver of supply chains on leagility is investigated. The partial least squares (PLS) was employed to analyse data collected from 299 Australian firms by administering a structured questionnaire. Results indicate that higher performance is achievable on minimising the deviation from a balanced supply chain in which aspects of both leanness and agility are equally embedded. Further, the level of uncertainty directly and positively affects the Deviation from Leagility (DFL) index.
Journal: International Journal of Production Research
Pages: 5601-5623
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1693660
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693660
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Template-Type: ReDIF-Article 1.0
Author-Name: Wen Song
Author-X-Name-First: Wen
Author-X-Name-Last: Song
Author-Name: Jianjun Zhu
Author-X-Name-First: Jianjun
Author-X-Name-Last: Zhu
Author-Name: Hehua Wang
Author-X-Name-First: Hehua
Author-X-Name-Last: Wang
Author-Name: Anlin Chang
Author-X-Name-First: Anlin
Author-X-Name-Last: Chang
Title: Multistage risk assessment of direct delivery business from local oil refineries in Sinopec Group based on normal cloud model
Abstract: 
 This paper studies the risk assessment problem of the direct delivery business from local oil refineries in Sinopec Group. A total of 23 risk factors associated with four segments of the direct delivery business are first identified. Through explaining the respective characteristics, the connotation of each risk factor is analysed in depth. Next, on the basis of the severity and possibility of each risk factor, a multistage risk assessment method for normal cloud model rooted in the extended TOPSIS approach is developed, and then applied to a real-world case. From the investigation, the weaknesses of the present risk assessment process are addressed from various aspects, including the risk factors, segments, and alternatives. Moreover, considering the possible correlation among risk factors, the proposed method is further extended by using the approach of Choquet integral. Additional discussions and recommendations are provided for improving the risk management process of the direct delivery business from local oil refineries.
Journal: International Journal of Production Research
Pages: 5624-5650
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1656835
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656835
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Template-Type: ReDIF-Article 1.0
Author-Name: Lohithaksha M. Maiyar
Author-X-Name-First: Lohithaksha M.
Author-X-Name-Last: Maiyar
Author-Name: Jitesh J. Thakkar
Author-X-Name-First: Jitesh J.
Author-X-Name-Last: Thakkar
Title: Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions
Abstract: 
 The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.
Journal: International Journal of Production Research
Pages: 5651-5675
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1656836
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656836
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei Qi
Author-X-Name-First: Wei
Author-X-Name-Last: Qi
Author-Name: Xinggang Luo
Author-X-Name-First: Xinggang
Author-X-Name-Last: Luo
Author-Name: Yang Yu
Author-X-Name-First: Yang
Author-X-Name-Last: Yu
Author-Name: Jiafu Tang
Author-X-Name-First: Jiafu
Author-X-Name-Last: Tang
Title: Product line optimisation based on semiparametric choice model
Abstract: 
 Consumer choice behaviour is important in the product line optimisation problem. The extant literature on product line optimisation is mostly based on traditional consumer choice models, such as the multinomial logit and multinomial probit models. These models either assume that the utility errors are independent from irrelevant alternatives (IIA) or are limited by complex calculation processes or pre-given, specific distributions of measuring errors. The marginal moment model (MMM), which is classified as a semiparametric choice model, does not require specific distributions of errors; thus, it can overcome the IIA shortcoming. This study focuses on the concavity of the profit functions of a product line optimisation model based on MMM. We prove that the profit function based on MMM is concave in market share under a monopoly or oligopoly. Numerical experiments show that the choice probabilities obtained from the MMM, multinomial logit, and multinomial probit models are similar although they are obtained under different assumptions. Experimental results under monopolistic, Cournot, and Bertrand competition based on MMM are compared. Some interesting managerial insights are summarised based on the sensitivity analysis of the various model parameters.
Journal: International Journal of Production Research
Pages: 5676-5692
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1656838
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656838
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Template-Type: ReDIF-Article 1.0
Author-Name: Jimut Bahan Chakrabarty
Author-X-Name-First: Jimut Bahan
Author-X-Name-Last: Chakrabarty
Author-Name: Shovan Chowdhury
Author-X-Name-First: Shovan
Author-X-Name-Last: Chowdhury
Author-Name: Soumya Roy
Author-X-Name-First: Soumya
Author-X-Name-Last: Roy
Title: Optimum life test plan for Type-I hybrid censored Weibull distributed products sold under general rebate warranty
Abstract: 
 The selection of an appropriate life test plan is extremely important for any product as it not just improves the quality of the product but also reduces testing costs. In this approach, however, the choice of suitable costs play an important role. In this paper, a decision model is developed to determine the optimal life testing plan (LTP) by minimising the relevant costs involved for non-repairable products sold under the general rebate warranty. LTP are developed in the presence of Type-I hybrid censoring for products having Weibull distributed lifetimes. A constrained optimisation approach is followed considering both producer's and consumer's risk and suitable analysis techniques are employed in obtaining the optimal solution. Monte Carlo simulation is conducted for numerical illustration. In order to study the sensitivity of the optimal solution due to mis-specification of parameter values and cost components, a well-designed sensitivity analysis is incorporated using a real-life Type-I hybrid censored data set.
Journal: International Journal of Production Research
Pages: 5693-5706
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1656839
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656839
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Template-Type: ReDIF-Article 1.0
Author-Name: Maria Pires
Author-X-Name-First: Maria
Author-X-Name-Last: Pires
Author-Name: Ana Camanho
Author-X-Name-First: Ana
Author-X-Name-Last: Camanho
Author-Name: Pedro Amorim
Author-X-Name-First: Pedro
Author-X-Name-Last: Amorim
Title: Solving the grocery backroom sizing problem
Abstract: 
 Backrooms are an important echelon of the retail supply chain. However, research focus has been mostly targeted to optimise both distribution centres and stores' sales area. In this paper, we propose two mathematical programming formulations to solve the grocery backroom sizing problem. This problem consists of determining the dimension of each storage department in the backroom area to optimise its overall efficiency. The first formulation is a bottom-up approach that aims to reduce the backroom life-cycle costs by determining the optimum floor space and storage height for each department. The second is a top-down approach based on Data Envelopment Analysis (DEA), which determines the efficient level of storage floor space for each backroom department, based on a comparison with the benchmarks observed among existing stores. Each approach has distinct characteristics that turn the models suitable for different retail contexts. We also describe the application of the proposed approaches to a case study of a European retailer. The application of this methodology in the design process demonstrated substantial potential for space savings (6% for the bottom-up model and 16% for the top-down model). This space reduction should either allow higher revenues in the sales area and/or lower backroom-related costs.
Journal: International Journal of Production Research
Pages: 5707-5720
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1656840
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656840
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Template-Type: ReDIF-Article 1.0
Author-Name: Junkai He
Author-X-Name-First: Junkai
Author-X-Name-Last: He
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: A multi-objective distribution-free model and method for stochastic disassembly line balancing problem
Abstract: 
 End-of-life product recycling is a hot research topic in recent years, which can reduce the waste and protect the environment. To disassemble products, the disassembly line balancing is a principal problem that selects tasks and assigns them to a number of workstations under stochastic task processing times. In existing works, stochastic task processing times are usually estimated by probability distributions or fuzzy numbers. However, in real-life applications, only their partial information is accessible. This paper studies a bi-objective stochastic disassembly line balancing problem to minimise the line design cost and the cycle time, with only the knowledge of the mean, standard deviation and upper bound of stochastic task processing times. For the problem, a bi-objective chance-constrained model is developed, which is further approximated into a bi-objective distribution-free one. Based on the problem analysis, two versions of the ϵ-constraint method are proposed to solve the transformed model. Finally, a fuzzy-logic technique is adapted to propose a preferable solution for decision makers according to their preferences. A case study is presented to illustrate the validity of the proposed models and algorithms. Experimental results on 277 benchmark-based and randomly generated instances show the efficiency of the proposed methods.
Journal: International Journal of Production Research
Pages: 5721-5737
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1656841
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1656841
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Template-Type: ReDIF-Article 1.0
Author-Name: Federico Trigos
Author-X-Name-First: Federico
Author-X-Name-Last: Trigos
Author-Name: Eduardo Manuel López
Author-X-Name-First: Eduardo Manuel
Author-X-Name-Last: López
Title: About tooling capacity for the vulcanising planning decision problem to improve strategic business profit
Abstract: 
 Original equipment manufacturers (among others) from several industries experience the vulcanising planning decision problem (VPDP) on a periodical basis. VPDP assumes tooling capacity (number of tools per part-number) as input data, but when these companies face the possibility of manufacturing a new family of part-numbers satisfying VPDP conditions tooling capacity has to be determined. Tooling costs per part number are significant: design, capacity, maintenance and salvage value. Strategic business profit is impacted since these contracts tend to have a life time that includes several years. The contribution of this work is fourfold: the definition of the tooling capacity problem (TCP) for VPDP, the development of part-number wise lower bounds on tooling capacity, a heuristic (along with an upper bound on optimality gap) to find tooling capacity values and preliminary results on sensitivity analysis over contract demand changes. Numerical experimentation demonstrates the efficiency of the heuristic.
Journal: International Journal of Production Research
Pages: 5738-5749
Issue: 18
Volume: 58
Year: 2020
Month: 9
X-DOI: 10.1080/00207543.2019.1660820
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660820
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Template-Type: ReDIF-Article 1.0
Author-Name: Xu Wang
Author-X-Name-First: Xu
Author-X-Name-Last: Wang
Author-Name: Hong Fang
Author-X-Name-First: Hong
Author-X-Name-Last: Fang
Author-Name: Wenyan Song
Author-X-Name-First: Wenyan
Author-X-Name-Last: Song
Title: Technical attribute prioritisation in QFD based on cloud model and grey relational analysis
Abstract: 
 Promptly development of new products can be achieved through quality function deployment (QFD) process, which is critical to companies’ survival. Since the multi-criteria decision-making problem involved in QFD, a novel method integrating cloud model and grey relational analysis is put forward in this paper. Taking into account the subjectivity and ambiguity in linguistic evaluations, some scholars utilise fuzzy theory, rough theory, interval-valued fuzzy-rough sets and MCDM methods to improve traditional QFD. However, much priori information requirements, inability to handle subjectivity and randomness, and lack of mechanism to overcome small sample size problem are some inevitable drawbacks in these methods. To solve these deficiencies, a hybrid methodology is proposed in this paper, integrating the fortes of cloud model in processing ambiguity and randomness, and the merits of grey relational analysis in overcoming small sample size error as well as revealing the inner correlations. The comparative analysis of different approaches as well as the sensitivity analysis of criteria weights is implemented to prove the stability of the novel method. The results obtained in this paper shows that the proposed method can be a practical tool for improving the efficiency and accuracy of traditional QFD in reality management.
Journal: International Journal of Production Research
Pages: 5751-5768
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1657246
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1657246
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Template-Type: ReDIF-Article 1.0
Author-Name: Ole Hansen
Author-X-Name-First: Ole
Author-X-Name-Last: Hansen
Author-Name: Hanno Friedrich
Author-X-Name-First: Hanno
Author-X-Name-Last: Friedrich
Author-Name: Sandra Transchel
Author-X-Name-First: Sandra
Author-X-Name-Last: Transchel
Title: An inventory management approximation for estimating aggregated regional food stock levels
Abstract: 
 Food is an important resource in disaster management, and food stock levels hold significance for disaster mitigation research and practice. The presence or absence of food stocks is a vulnerability indicator of a region. A large part of overall food stock, before a disaster strikes, is held by private companies (retailers, wholesalers and food producers). However, there is little-to-no information on the food stock levels of commercial companies, and no approach exists to derive such information. We develop an approximation model based on essential inventory management principles and available data sources to estimate aggregated food stock levels in supply networks. The model is applied in a case example that features dairy product stock levels in the German state of Saxonia. The resulting overall stock levels are normalised, and their usability is showcased in a simple vulnerability analysis. Disaster managers are provided with a model that can be used estimate otherwise unavailable data and facilitates investigations into the regional resilience of an area. The limitations of our study are based on the aggregated nature of the supply network structure and data usage (i.e. in the model, we do not consider any seasonality or trend effects).
Journal: International Journal of Production Research
Pages: 5769-5785
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1657248
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1657248
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Template-Type: ReDIF-Article 1.0
Author-Name: Gernot Lechner
Author-X-Name-First: Gernot
Author-X-Name-Last: Lechner
Author-Name: Marc Reimann
Author-X-Name-First: Marc
Author-X-Name-Last: Reimann
Title: Integrated decision-making in reverse logistics: an optimisation of interacting acquisition, grading and disposition processes
Abstract: 
 In view of global environmental and social challenges the transition towards a Circular Economy is considered as a crucial factor for sustainable development. Therefore, the replacement of traditional linear business models involving product discard at the end of product life with concepts focusing on re-use of resources is essential. Reverse Logistics and Closed-loop Supply Chains are seen to be key elements of such a transition. Motivated by findings from a case study of an independent reprocessing company, we address integrated decision-making in Reverse Logistics in this paper. We present a non-linear optimisation model with interrelated processes in terms of acquisition of used products, grading for determination of product quality and reprocessing disposition. The decisions to be made concern the effort spent for active acquisition of used products and the number of reprocessed goods; both decisions are influenced by heterogeneous condition of used products. The consideration of deterministic and stochastic demand facilitates the representation of a variety of business cases. For both demand types we provide analytical insights in the form of complete strategies consisting of different scenarios which allow optimal decision-making under variable conditions. Numerical examples complement insights into the model by conducting a sensitivity analysis of relevant model parameters.
Journal: International Journal of Production Research
Pages: 5786-5805
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1659518
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1659518
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Xin Liu
Author-X-Name-First: Xin
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Robust disassembly line balancing with ambiguous task processing times
Abstract: 
 Disassembly line balancing problem (DLBP), which is to select disassembly process, open workstations and assign selected tasks to opened workstations, plays an important role in the recycling of End Of Life products. In real-world disassembly operations, task processing times are usually stochastic due to various factors. Most related works address the uncertain processing times by assuming that the probability distribution is known and the task processing times are independent of each other. In practice, however, it is difficult to get the complete distributional information and there is always underlying correlation between the uncertain processing times. This paper investigates the DLBP with partial uncertain knowledge, i.e. the mean and covariance matrix of task processing times. A new distributionally robust formulation with a joint chance constraint is proposed. To solve the problem, an approximated mixed integer second-order cone programming (MI-SOCP) model is proposed, and a two-stage parameter-adjusting heuristic is further developed. Numerical experiments are conducted, to evaluate the performance of the proposed method. We also draw some managerial insights and consider an extension problem.
Journal: International Journal of Production Research
Pages: 5806-5835
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1659520
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1659520
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Template-Type: ReDIF-Article 1.0
Author-Name: Caroline Cloutier
Author-X-Name-First: Caroline
Author-X-Name-Last: Cloutier
Author-Name: Parnian Oktaei
Author-X-Name-First: Parnian
Author-X-Name-Last: Oktaei
Author-Name: Nadia Lehoux
Author-X-Name-First: Nadia
Author-X-Name-Last: Lehoux
Title: Collaborative mechanisms for sustainability-oriented supply chain initiatives: state of the art, role assessment and research opportunities
Abstract: 
 Whether from government policies, customer expectations or personal beliefs, there is increasing pressure on firms and their supply chains to adopt sustainable practices. Manufacturing companies are particularly targeted, for example, to reduce CO2 emissions, offer sustainable products, etc. Research in this field has significantly increased in recent years. Most research states the importance of collaboration with upstream and downstream entities as a critical success factor when aiming for a sustainable supply chain and proposes various collaborative mechanisms (CMs) to enable firms in the implementation of a sustainability-oriented initiative. The goal of this paper is to investigate the role of collaboration in these initiatives and explore the proposed CMs via a systematic literature review method. A total of 404 articles were reviewed and the multitude of CMs proposed in the literature were classified into seven categories: relationship management, contractual and economic practices, joint practices, technological and information sharing practices, governance practices, assessment practices, and supply chain design. This systematic mapping of the field provides an in-depth view of the current state of research as well as research gaps. It also intends to help practitioners by highlighting the role played by these mechanisms in four phases of sustainable supply chain deployment.
Journal: International Journal of Production Research
Pages: 5836-5850
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1660821
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660821
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Template-Type: ReDIF-Article 1.0
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Ilenia Zennaro
Author-X-Name-First: Ilenia
Author-X-Name-Last: Zennaro
Author-Name: Eleonora Florian
Author-X-Name-First: Eleonora
Author-X-Name-Last: Florian
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Title: Age replacement policy in the case of no data: the effect of Weibull parameter estimation
Abstract: 
 Age replacement is a common maintenance policy when wear-out failures occur, and it is characterised by periodic replacement of components. Data on time to failure (TTF), often modelled with the Weibull function, are necessary for estimating optimal replacement intervals to minimise the total maintenance costs. In many cases, such as new components, new machines or new installations, no TTF data are available, so the Weibull parameters and optimal replacement interval cannot be estimated. To overcome this problem, these parameters can be assessed from the experience of the maintenance engineers and technicians. The aim of this study is investigating the relationship between the error in parameter estimation and additional maintenance costs related to this error. Analysis of variance (ANOVA) and multifactorial analysis are carried out for investigating the influence of these estimations on the final costs. Economic decision maps are introduced for supporting maintenance engineering in defining the maintenance policy with minimal additional cost in the case of no data being available. The analysis shows that, when no data are available, the application of the age replacement policy can result in a global saving of more than 50% compared with corrective maintenance.
Journal: International Journal of Production Research
Pages: 5851-5869
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1660824
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660824
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhifeng Qian
Author-X-Name-First: Zhifeng
Author-X-Name-Last: Qian
Author-Name: Junwu Chai
Author-X-Name-First: Junwu
Author-X-Name-Last: Chai
Author-Name: Hengyu Li
Author-X-Name-First: Hengyu
Author-X-Name-Last: Li
Author-Name: Wei Yan
Author-X-Name-First: Wei
Author-X-Name-Last: Yan
Author-Name: Hong Chen
Author-X-Name-First: Hong
Author-X-Name-Last: Chen
Title: Implications of product upgrading confronting supplier remanufacturing
Abstract: 
 It is generally believed that new products upgrading is an effective strategy to deal with the cannibalisation problem from remanufacturing, however, it is not clear how the new product upgrading strategy affect the decision-making of the downstream manufacturer and the upstream supplier. By examining the relationship between supplier remanufacturing profits and product cannibalisation, we develop two models to investigate the implications of the manufacturer's product upgrading confronting supplier remanufacturing. The results show that an product upgrading strategy can effectively enhance the manufacturer's profits if the investment cost is relatively low. Although the product upgrading strategy may hinder the remanufacturing operations, it will always be beneficial for the wholesaling of the supplier's new products. Therefore, the upgrading strategy can mitigate cannibalisation problems and create an optimal pareto improvement for both parties. Finally, we conduct a data analysis to provide additional managerial insights regarding the supply chain.
Journal: International Journal of Production Research
Pages: 5870-5892
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1660827
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1660827
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Template-Type: ReDIF-Article 1.0
Author-Name: Chunguang Bai
Author-X-Name-First: Chunguang
Author-X-Name-Last: Bai
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Author-Name: Fengfu Yin
Author-X-Name-First: Fengfu
Author-X-Name-Last: Yin
Author-Name: Yijie Dou
Author-X-Name-First: Yijie
Author-X-Name-Last: Dou
Title: Sustainable supply chain flexibility and its relationship to circular economy-target performance
Abstract: 
 The circular economy (CE) is an evolving economic and sustainable development model. In this new environment, companies face a more dynamic, uncertain, and complex market environment. These challenges arise from material closed-loop flows necessary for a functioning CE. It is important to build flexibility capabilities into sustainable supply chains to address CE operational challenges. Building this operational capability needs to occur without incurring performance degradation, increasing costs, or compromising product quality. Supply chain designers have recognised the importance of sustainable supply chain flexibility (SSCF) efforts for meeting CE-targeted performance. CE-targeted performance includes reuse of materials and energy, closed flow of materials, and pollution reduction. Exploration of relationships between SSCF efforts and CE-targeted performance is limited. An objective-DEMATEL method is used to evaluate the relationship between a new SSCF measures framework and CE-targeted performance. A field study helps to identify and refine significant SSCF measures (efforts) to effectively improve CE-targeted performance. Managerial implications and future research directions for sustainable supply chain flexibility within the CE environment are presented.
Journal: International Journal of Production Research
Pages: 5893-5910
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1661532
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1661532
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Template-Type: ReDIF-Article 1.0
Author-Name: Manish Shukla
Author-X-Name-First: Manish
Author-X-Name-Last: Shukla
Author-Name: Kristian Pal
Author-X-Name-First: Kristian
Author-X-Name-Last: Pal
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: A framework for understanding institutional factors affecting the success and failure of offshoring models in India
Abstract: 
 The objective of this paper is to identify and analyse the factors that influence offshore location decisions from an institutional theory perspective. In the years, emerging economies have shown great growth potential and have attracted significant foreign direct investment, especially from companies willing to set up operations. Despite such a seemingly favourable trade environment, not all companies that entered an emerging economy have been successful. Thus, there is a need to understand the factors that influence the success of any offshore location decision. It is also important to understand the relative importance of these factors, in order to develop novel insights useful to practitioners. There is a lack of literature addressing this issue, which this study aims to fill. We conducted a multi-case analysis with examples of European companies entering India. The findings indicate that successful companies employed locally focused business strategies that enabled them to acquire important relationships and knowledge, and also to adapt to formal institutions, including governmental and regulatory procedures. It was found that, irrespective of size, disregarding collaborative strategies was the main reason for exiting India. These findings are highly relevant for managers and policy makers.
Journal: International Journal of Production Research
Pages: 5911-5928
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1661533
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1661533
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Template-Type: ReDIF-Article 1.0
Author-Name: Antonella Moretto
Author-X-Name-First: Antonella
Author-X-Name-Last: Moretto
Author-Name: Andrea Stefano Patrucco
Author-X-Name-First: Andrea Stefano
Author-X-Name-Last: Patrucco
Author-Name: Christine Mary Harland
Author-X-Name-First: Christine Mary
Author-X-Name-Last: Harland
Title: The dynamics of reshoring decisions and the role of purchasing
Abstract: 
 Reshoring is a reversal of offshoring decisions and is increasing in business practice. There is limited understanding of how different drivers relate to different reshoring decisions. There has been little examination of purchasing's role in reshoring decision-making. Through 25 case studies of reshoring decisions taken by 18 companies, this research examines the relationship between different drivers and the type of reshoring decision taken, and how purchasing was involved at different stages of the reshoring decision-making process. The findings reveal four types of reshoring; most companies made mono-dimensional reshoring decisions, and three types of mono-dimensional decisions were found. One type of bi-dimensional reshoring initiatives involved changed location and ownership. The most common drivers for reshoring were operational reasons and brand reputation, as reasons for the original offshoring decision had changed over time. Four types of involvement of purchasing in different stages of reshoring decisions were found: no involvement, operational involvement in implementation, early involvement in feasibility studies, and strategic involvement throughout the whole process. Different types of purchasing involvement were found to relate to different types of reshoring with particularly strong involvement in bi-dimensional reshoring decisions.
Journal: International Journal of Production Research
Pages: 5929-5944
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1661534
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1661534
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhen Chen
Author-X-Name-First: Zhen
Author-X-Name-Last: Chen
Author-Name: Xu Zheng
Author-X-Name-First: Xu
Author-X-Name-Last: Zheng
Author-Name: Shengchao Zhou
Author-X-Name-First: Shengchao
Author-X-Name-Last: Zhou
Author-Name: Chuang Liu
Author-X-Name-First: Chuang
Author-X-Name-Last: Liu
Author-Name: Huaping Chen
Author-X-Name-First: Huaping
Author-X-Name-Last: Chen
Title: Quantum-inspired ant colony optimisation algorithm for a two-stage permutation flow shop with batch processing machines
Abstract: 
 This paper studied two-stage permutation flow shop problems with batch processing machines, considering different job sizes and arbitrary arrival times, with the optimisation objective of minimising the makespan. The quantum-inspired ant colony optimisation (QIACO) algorithm was proposed to solve the problem. In the QIACO algorithm, the ants are divided into two groups: one group selects the largest job in terms of job size as the initial job for each batch and the other group selects the smallest job as the initial job for each batch. Each group of ants has its own pheromone matrix. In the computational experiment, our novel algorithm was compared with the hybrid discrete differential evolution (HDDE) algorithm and the batch-based hybrid ant colony optimisation (BHACO) algorithm. Although the HDDE algorithm has a shorter run time, the quality of the solution for large-scale jobs is not good, while the BHACO algorithm always obtains a better solution but requires a longer run time. The computational results show that the QIACO algorithm embedded in the quantum information has advantages in terms of both solution quality and running time.
Journal: International Journal of Production Research
Pages: 5945-5963
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1661535
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1661535
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Template-Type: ReDIF-Article 1.0
Author-Name: Mengli Li
Author-X-Name-First: Mengli
Author-X-Name-Last: Li
Author-Name: Xumei Zhang
Author-X-Name-First: Xumei
Author-X-Name-Last: Zhang
Author-Name: Bin Dan
Author-X-Name-First: Bin
Author-X-Name-Last: Dan
Title: Competition and cooperation in a supply chain with an offline showroom under asymmetric information
Abstract: 
 Offline showrooms develop rapidly to resolve consumers’ uncertainty about whether products fit their needs when they purchase online. This paper considers a supply chain where an offline showroom provides experience service for an existing online retailer and intends to introduce a new competing online retailer to satisfy consumers’ heterogeneous demand. The offline showroom has better knowledge of demand information due to closer to offline consumers. We examine the impact of competition and the offline showroom's optimal channel cooperation strategy under asymmetric information and analyse the equilibrium results under the optimal strategy to shed light on channel cooperation and information strategy for supply chain members. We find that under asymmetric information competition prompts the offline showroom to conceal information which generates signal cost (negative information effect) and to increase experience service level which creates value (positive service effect). The optimal channel cooperation strategy depends on the trade-off between these effects. We also find that competition increases the existing online retailer's profit in some conditions. Besides, in some conditions information asymmetry harms all supply chain members, which suggests the offline showroom to share information with the online retailers; in some conditions, information asymmetry harms the offline showroom but benefits the online retailers.
Journal: International Journal of Production Research
Pages: 5964-5979
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1661536
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1661536
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Template-Type: ReDIF-Article 1.0
Author-Name: Haolan Liao
Author-X-Name-First: Haolan
Author-X-Name-Last: Liao
Author-Name: Neng Shen
Author-X-Name-First: Neng
Author-X-Name-Last: Shen
Author-Name: Yanzhen Wang
Author-X-Name-First: Yanzhen
Author-X-Name-Last: Wang
Title: Design and realisation of an efficient environmental assessment method for 3R systems: a case study on engine remanufacturing
Abstract: 
 Recently, the manufacturing industry has been striving for sustainability because of the environmental degradation and resource depletion caused by it. Remanufacturing considerably saves material and is energy efficient, and thus, it can represent an important solution to environmental issues. However, the uncertainty of remanufacturing makes the practical management of closed-loop supply chains (CLSCs) difficult. To unlock the value potential of end-of-life (EOL) products, we studied a reuse, remanufacture, and recycle (3R) processing system under quality uncertainty for returned EOL engines. In the system, the returned cores were distributed into different processing routes, depending on the results of quality grading. The proposed matrix operations could efficiently assess the environmental benefits; moreover, we designed an algorithm to calculate the quality coefficient that reflects the overall quality condition of returned EOL cores. The impacts of quality uncertainty on the environment could be efficiently quantified via our proposed method. Furthermore, using Monte Carlo simulation and the law of large numbers, we devised a model to establish direct and definite quantitative relationships between the quality coefficient and production indexes. This model provides a basis for the formulation of optimal acquisition strategies under different returning scenarios.
Journal: International Journal of Production Research
Pages: 5980-6003
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1662132
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1662132
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenjie Chen
Author-X-Name-First: Wenjie
Author-X-Name-Last: Chen
Author-Name: Hainan Guo
Author-X-Name-First: Hainan
Author-X-Name-Last: Guo
Author-Name: Kwok-Leung Tsui
Author-X-Name-First: Kwok-Leung
Author-X-Name-Last: Tsui
Title: A new medical staff allocation via simulation optimisation for an emergency department in Hong Kong
Abstract: 
 Whether triage targets can be achieved has been an imperative assessment of service qualities for an emergency department in healthcare management. In this research, we focus on triage targets and try to fully meet the target of fast emergency response for critical patients subject to triage requirements for other category patients by optimising the medical staff allocation in the emergency department. Main challenges stem from multiple stochastic constraints and the time-consuming simulation. To solve the stochastically constrained discrete optimisation via simulation problem, we develop a discrete-event simulation model and propose a simulated-annealing-based algorithm called ConSA that adopts a special searching mechanism and an efficient simulation budget allocation rule to find a high-quality configuration of medical staff. A case study based on the data from a public hospital in Hong Kong is carried out. Numerical experiments demonstrate that our algorithm leads to a 38.28% improvement in the main performance compared to the current staff allocation and dominates other algorithms in terms of computational efficiency and output accuracy. It indicates that our method is a good decision tool for hospital managers.
Journal: International Journal of Production Research
Pages: 6004-6023
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1665201
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1665201
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanxia Wu
Author-X-Name-First: Yanxia
Author-X-Name-Last: Wu
Author-Name: Guozhu Jia
Author-X-Name-First: Guozhu
Author-X-Name-Last: Jia
Author-Name: Yang Cheng
Author-X-Name-First: Yang
Author-X-Name-Last: Cheng
Title: Cloud manufacturing service composition and optimal selection with sustainability considerations: a multi-objective integer bi-level multi-follower programming approach
Abstract: 
 The process of service composition and optimal selection (SCOS) is an important issue in cloud manufacturing (CMfg). However, the current studies on CMfg and SCOS have generally focused on optimising the allocation of resources against quality of service (QoS), in terms of e.g. cost, quality, and time. They have seldom taken the perspective of sustainability into discussion, although sustainability is indispensable in the CMfg environment. Addressing this gap, we aim to (1) propose a comprehensive method to assess the sustainability of cloud manufacturing (SoM) in terms of the economic, environmental, and social aspects; (2) establish a multi-objective integer bi-level multi-follower programming (MOIBMFP) model to simultaneously maximise SoM and QoS from the perspectives of both platform operator and multiple service demanders; and (3) design a hybrid particle swarm optimisation algorithm to solve the proposed MOIBMFP model. The experimental results show that the proposed algorithm is more feasible and effective than the typical multi-objective particle swarm optimisation algorithm when solving the proposed model. In other words, the proposed model and algorithm suggest better alternatives to meet the needs of the platform operator and service demanders in the CMfg environment.
Journal: International Journal of Production Research
Pages: 6024-6042
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1665203
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1665203
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Template-Type: ReDIF-Article 1.0
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Title: A two-period model for selection of resilient multi-tier supply portfolio
Abstract: 
 A two-period decision-making model is developed for selection of resilient supply portfolio in a multi-tier supply chain under disruption risks. The planning horizon is divided into two aggregate periods: before and after the disruption. The resilience of the supply chain is achieved by selection ahead of time primary supply portfolio and by pre-positioning of risk mitigation inventory of parts at different tiers that will hedge against all disruption scenarios. Simultaneously, recovery and transshipment portfolios are determined for each disruption scenario and decisions on usage the pre-positioned inventory are made to minimise expected cost or maximise expected service level. Some properties of optimal solutions, derived from the proposed model provide additional managerial insights. The findings also indicate that the developed portfolio approach with an embedded network flow structure leads to computationally efficient stochastic mixed integer program with a strong LP relaxation.
Journal: International Journal of Production Research
Pages: 6043-6060
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1665204
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1665204
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanyan Zhang
Author-X-Name-First: Yanyan
Author-X-Name-Last: Zhang
Author-Name: Gary G. Yen
Author-X-Name-First: Gary G.
Author-X-Name-Last: Yen
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Title: Soft constraint handling for a real-world multiobjective energy distribution problem
Abstract: 
 Real-world optimisation problems usually involve some conflicting objectives and a number of constraints. In such cases, finding a feasible, Pareto-optimal solution poses a demanding challenge. In reality, constraints bear different importance levels to these conflicting objectives. If some constraints are relaxed within an acceptable degree, quality infeasible solutions could be found on the boundary from the infeasible side of the searching region. This paper formulates an energy distribution problem arising from a real-world iron and steel production as a multiobjective optimisation problem. During the course of the optimisation search, this paper attempts to handle certain constraints in a soft manner to find solutions with good balance among objective and constraints violation. Based on the analysis of constraints from the real-world perspective, different tolerance values are defined. The proposed constraint violation degree-based soft handling approach is incorporated into the advanced version of non-dominated sorting genetic algorithm framework, as a case study, to examine the efficiency of the proposed soft constraint handling approach for a real-world energy distribution problem. The proposed approach is also implemented in different ways of constraint handling and tested on some benchmark functions to further demonstrate the performance of soft constraint handling for multiobjective optimisation problems.
Journal: International Journal of Production Research
Pages: 6061-6077
Issue: 19
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1667039
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1667039
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Template-Type: ReDIF-Article 1.0
Author-Name: Zied Hajej
Author-X-Name-First: Zied
Author-X-Name-Last: Hajej
Author-Name: Rezg Nidhal
Author-X-Name-First: Rezg
Author-X-Name-Last: Nidhal
Author-Name: Chelbi Anis
Author-X-Name-First: Chelbi
Author-X-Name-Last: Anis
Author-Name: Maryem Bouzoubaa
Author-X-Name-First: Maryem
Author-X-Name-Last: Bouzoubaa
Title: An optimal integrated production and maintenance strategy for a multi-wind turbines system
Abstract: 
 This paper presents an optimal integrated production and maintenance strategy for a wind farm. A cost model is developed in order to determine sequentially the optimal plan of energy production characterised by the number of working wind turbines and their production rates, and the optimal preventive maintenance policy to be adopted. We model the relationship between the variation of energy production rates and the failure rate of the wind turbines. A numerical example and a sensitivity analysis are presented and the obtained results are discussed.
Journal: International Journal of Production Research
Pages: 6417-6440
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1680897
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1680897
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei Sun
Author-X-Name-First: Wei
Author-X-Name-Last: Sun
Author-Name: Yang Yu
Author-X-Name-First: Yang
Author-X-Name-Last: Yu
Author-Name: Qi Lou
Author-X-Name-First: Qi
Author-X-Name-Last: Lou
Author-Name: Junwei Wang
Author-X-Name-First: Junwei
Author-X-Name-Last: Wang
Author-Name: Yuechao Guan
Author-X-Name-First: Yuechao
Author-X-Name-Last: Guan
Title: Reducing the total tardiness by Seru production: model, exact and cooperative coevolution solutions
Abstract: 
 Seru Production is widely used in the Japanese electronics industry owing to its benefits. The total tardiness can be significantly reduced by Seru Production. We focus on investigating the fundamental principle of the total tardiness reduction brought by Seru Production. We formulate the seru system operation with minimising the total tardiness and analyse the solution space. We clarify that the model is non-linear. To exactly obtain the optimal solution of the non-linear model, we decompose the non-linear model into seru formation and seru scheduling which is formulated as a linear model. Thus, the small-scale seru system operation with minimising the total tardiness is solved exactly. For the large-scale problems, we propose a cooperative coevolution algorithm, where two evolution algorithms deal with the seru formation and seru scheduling. In the coevolution process, the two algorithms perform cooperation to seek the better solutions of seru system operation with minimising the total tardiness. Extensive experiments are tested to investigate how Seru Production reduces the total tardiness.
Journal: International Journal of Production Research
Pages: 6441-6452
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1680898
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1680898
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Template-Type: ReDIF-Article 1.0
Author-Name: Samareh Azimpoor
Author-X-Name-First: Samareh
Author-X-Name-Last: Azimpoor
Author-Name: Sharareh Taghipour
Author-X-Name-First: Sharareh
Author-X-Name-Last: Taghipour
Title: Optimal job scheduling and inspection of a machine with delayed failure
Abstract: 
 In this paper, we consider a single machine, which must process n jobs in sequence. The machine's failure process follows the two-stage Delay Time Model, i.e. it starts with an initial defect, and will lead to eventual failure if the defect is left unattended. An inspection may be performed before starting a job to detect a defect. We improve the machine's maintenance decision making process by considering the possibility of performing minimal repair or replacement at any event time with regard to the age of the machine. This assumption affects the complexity of the problems in terms of executing loops in MATLAB excessively. The objective is to find the optimal inspection policy and the jobs sequence, which minimise the total expected makespan. We will develop two models and derive their corresponding recursive formulas. For the optimisation of the first model, we will combine the Genetic Algorithm with the recursive equations to jointly optimise the job sequence and inspection policy. In the second model, due to cumbersome recursive equations, we will adopt a simulation algorithm to obtain the required expected values in the objective function. We will provide numerical examples to present the application of the models, and study the inﬂuence of various input parameters on the best-obtained policies. We conduct extensive computational experiments on randomly generated problems with different configurations to evaluate the efficiency of models.
Journal: International Journal of Production Research
Pages: 6453-6473
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1680900
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1680900
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Template-Type: ReDIF-Article 1.0
Author-Name: Gonzalo Mejía
Author-X-Name-First: Gonzalo
Author-X-Name-Last: Mejía
Author-Name: Dimitri Lefebvre
Author-X-Name-First: Dimitri
Author-X-Name-Last: Lefebvre
Title: Robust scheduling of flexible manufacturing systems with unreliable operations and resources
Abstract: 
 This paper addresses the topic of robust scheduling for flexible manufacturing systems (FMS) with operation interruptions and unreliable resources. The proposed approach uses timed Petri nets as a model of the FMS in uncertain environments. This model includes controllable and uncontrollable transitions. The unexpected firings of the uncontrollable transitions represent operation and resource failures and the risk to deviate from the scheduled trajectories. This paper proposes an anytime graph search algorithm with a new objective function that combines performance and risk. In addition, the graph search incorporates a new filtering mechanism that learns from previous runs and two node expansion strategies. The performance of the proposed algorithm is compared with that of another already existing algorithm. A running example and a case study from a real company illustrate the efficiency of the proposed scheduling approach.
Journal: International Journal of Production Research
Pages: 6474-6492
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1682706
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1682706
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Template-Type: ReDIF-Article 1.0
Author-Name: D. G. Mogale
Author-X-Name-First: D. G.
Author-X-Name-Last: Mogale
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Sri Krishna Kumar
Author-X-Name-First: Sri Krishna
Author-X-Name-Last: Kumar
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Modelling supply chain network for procurement of food grains in India
Abstract: 
 The procurement of food grains from farmers and their transportation to regional level has become decisive due to increasing food demand and post-harvest losses in developing countries. To overcome these challenges, this paper attempts to develop a robust data-driven supply chain model for the efficient procurement of food grains in India. Following the data collected from three leading wheat producing Indian regions, a mixed-integer linear programming model is formulated for minimising total supply chain network costs and determining number and location of procurement centres. The NK Hybrid Genetic Algorithm (NKHGA) is employed to cluster the villages, along with a novel density-based approach to optimise the supply chain network. Sensitivity analysis indicates that policymakers should focus on creating an adequate number of procurement centres in each surplus state, well before the start of the harvesting season. The study is expected to benefit food grain supply chain stakeholders such as farmers, procurement agencies, logistics providers and government bodies in making an informed decision.
Journal: International Journal of Production Research
Pages: 6493-6512
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1682707
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1682707
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Template-Type: ReDIF-Article 1.0
Author-Name: Siavash Valizadeh
Author-X-Name-First: Siavash
Author-X-Name-Last: Valizadeh
Author-Name: Omid Fatahi Valilai
Author-X-Name-First: Omid
Author-X-Name-Last: Fatahi Valilai
Author-Name: Mahmoud Houshmand
Author-X-Name-First: Mahmoud
Author-X-Name-Last: Houshmand
Title: Flexible flow line scheduling considering machine eligibility in a digital dental laboratory
Abstract: 
 Introduction of digital solutions has made dentistry more efficient and effective in response to patients’ demands. Moreover, digital solution helps participants to manage daily workflow simpler than traditional practices. Scanners, CAD/CAM software, CNC machines and 3D printers are components of digital solutions in current dentistry. Responding to patients as quickly as possible is essential in medical fields and dentistry has similar situations. On the other hand, demands in dentistry are highly customized that it makes managing orders more difficult because each order needs special design and production. Thus, this paper assesses orders in digital dentistry and develops a mathematical model to optimize production planning and scheduling of orders by considering different objectives and requirements that are common in dentistry. In addition, a metaheuristics algorithm was developed based on PSO to respond to NP-hard challenges of the model. The developed algorithm includes two steps that PSO metaheuristics consider in the second step to search new solutions. Finally, through case studies, performance of the developed model and proposed algorithm was investigated. Developed algorithm generates solutions with proper quality considering makespan and total completion time objectives and required time to obtain a solution with high quality depends on problem data and can increase.
Journal: International Journal of Production Research
Pages: 6513-6531
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1683247
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683247
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Template-Type: ReDIF-Article 1.0
Author-Name: Melek Rodoplu
Author-X-Name-First: Melek
Author-X-Name-Last: Rodoplu
Author-Name: Taha Arbaoui
Author-X-Name-First: Taha
Author-X-Name-Last: Arbaoui
Author-Name: Alice Yalaoui
Author-X-Name-First: Alice
Author-X-Name-Last: Yalaoui
Title: A fix-and-relax heuristic for the single-item lot-sizing problem with a flow-shop system and energy constraints
Abstract: 
 This study addresses a new single-item lot-sizing problem for flow-shop configurations by integrating the capacity contract selection problem with multiple energy sources. To the best of our knowledge, this problem has never been tackled before. We introduce a mathematical model which defines optimum production plan and energy contract option regarding the objectives and constraints of the production system and energy supplier contract conditions. Since the problem is NP-Hard, a Fix-and-Relax heuristic is introduced to solve the problem. Two different relaxation procedures are applied and the performance of the solution approach is tested on randomly generated instances. It is seen that the obtained results are quite promising. The applied heuristic approach produces solutions with the optimality gap  $0.2\% $0.2% in average for the small problem sizes such as (N5_T5,N5_T7). For the larger instances, it allows to reach better results than the results obtained by commercial solvers within a shorter time.
Journal: International Journal of Production Research
Pages: 6532-6552
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1683249
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683249
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Template-Type: ReDIF-Article 1.0
Author-Name: Miguel R. Lopes
Author-X-Name-First: Miguel R.
Author-X-Name-Last: Lopes
Author-Name: Andrea Costigliola
Author-X-Name-First: Andrea
Author-X-Name-Last: Costigliola
Author-Name: Rui Pinto
Author-X-Name-First: Rui
Author-X-Name-Last: Pinto
Author-Name: Susana Vieira
Author-X-Name-First: Susana
Author-X-Name-Last: Vieira
Author-Name: Joao M.C. Sousa
Author-X-Name-First: Joao M.C.
Author-X-Name-Last: Sousa
Title: Pharmaceutical quality control laboratory digital twin – A novel governance model for resource planning and scheduling
Abstract: 
 A digital twin of pharmaceutical quality control laboratory was developed and employed as a benchmarking platform to estimate the performance of a new facility under alternative governance models. Key performance metrics, such as sample processing times and utilisation rates of analytical staff and equipment were computed and compared under alternative governance scenarios, to determine solutions to be implemented in practice. Two frameworks were evaluated, leading to the conclusion that higher efficiency can be achieved under a novel, free-for-all governance, without the need to procure additional resources.
Journal: International Journal of Production Research
Pages: 6553-6567
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1683250
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683250
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Template-Type: ReDIF-Article 1.0
Author-Name: J. S. Neufeld
Author-X-Name-First: J. S.
Author-X-Name-Last: Neufeld
Author-Name: F. F. Teucher
Author-X-Name-First: F. F.
Author-X-Name-Last: Teucher
Author-Name: U. Buscher
Author-X-Name-First: U.
Author-X-Name-Last: Buscher
Title: Scheduling flowline manufacturing cells with inter-cellular moves: non-permutation schedules and material flows in the cell scheduling problem
Abstract: 
 A major goal of the concept of cellular manufacturing is to form independent cells. However, the formation of entirely independent cells is rarely found in practice, where inter-cellular transports of jobs are often accepted to a certain level. The resulting scheduling task in flowline manufacturing cells is referred to as cell scheduling problem. Usually it is modelled and solved analogously to the group scheduling problem, which arises within a single cell with multiple part families. In this study, we point out several characteristics that specify the distinctiveness of cell scheduling. Furthermore, a new cell-based objective, namely total cell makespan, is introduced. As no appropriate benchmark instances are available so far, new test problems are developed, that integrate the derived characteristics. In an extensive computational study known constructive heuristics as well as simulated annealing algorithms to generate permutation and non-permutation schedules are tested. It is revealed that especially the type of material flows between cells has an immense impact on the algorithms' performance. The findings support a better problem understanding and point out the necessity of developing new heuristics especially for certain types of the cell scheduling problem.
Journal: International Journal of Production Research
Pages: 6568-6584
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1683251
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683251
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Template-Type: ReDIF-Article 1.0
Author-Name: Fan Zhang
Author-X-Name-First: Fan
Author-X-Name-Last: Zhang
Author-Name: Jie Song
Author-X-Name-First: Jie
Author-X-Name-Last: Song
Author-Name: Yingzhuo Dai
Author-X-Name-First: Yingzhuo
Author-X-Name-Last: Dai
Author-Name: Jie Xu
Author-X-Name-First: Jie
Author-X-Name-Last: Xu
Title: Semiconductor wafer fabrication production planning using multi-fidelity simulation optimisation
Abstract: 
 Semiconductor wafer fabrication is a complicated and time-consuming production process in the semiconductor manufacturing industry. It is very important for the manufacturer to come up with production plans that can most efficiently utilise the manufacturing equipment and fulfil customer orders placed in a planning horizon. Because of the complexity of the manufacturing processes, it is necessary to use high-fidelity discrete-event simulations to provide accurate estimates of delivery lead time for any given production plan. However, high-fidelity simulations are time-consuming, and thus decision-makers may only evaluate a small number of production plans once customer orders are received. In this paper, we propose the use of a multi-fidelity simulation optimisation approach to efficiently evaluate and select the best production plan from a large set of alternative plans under consideration. We develop an open queue approximation model for a wafer fabrication system and then use the low-fidelity estimates of lead times obtained from the approximation model in a recently developed multi-fidelity simulation optimisation method. Simulation experiment results show that the multi-fidelity approach significantly improves the computational efficiency of simulation-based production planning.
Journal: International Journal of Production Research
Pages: 6585-6600
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1683252
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683252
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Template-Type: ReDIF-Article 1.0
Author-Name: Yosep Oh
Author-X-Name-First: Yosep
Author-X-Name-Last: Oh
Author-Name: Chi Zhou
Author-X-Name-First: Chi
Author-X-Name-Last: Zhou
Author-Name: Sara Behdad
Author-X-Name-First: Sara
Author-X-Name-Last: Behdad
Title: The impact of build orientation policies on the completion time in two-dimensional irregular packing for additive manufacturing
Abstract: 
 The study investigates the impact of build orientation policies on the production time in additive manufacturing (AM) for mass customisation business models. Two main orientation policies are considered: (1) Laying Policy (LP) that focuses on reducing the height of parts; and (2) Standing Policy (SP) that aims to minimise the projection base plane of parts to reduce the number of jobs. While LP minimises the build time per job since parts have low height, it could increase the total completion time as the number of parts increases. On the other hand, SP takes longer build time per job due to the high height of parts, where it could lead to a fewer number of jobs. Several numerical experiments have been conducted based on Stereolithography (SLA). The results show that, when the number of parts is experimentally about 40, SP could be more preferred than LP for minimising the completion time where the shape tendency of parts is likely to affect the extent of preference for the policies. When 40 parts with long and flat shape are considered, SP reduces the completion time by 15.7% over the default policy, the initial orientation of a part, while LP reduces by only 6.6%.
Journal: International Journal of Production Research
Pages: 6601-6615
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1683253
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683253
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Template-Type: ReDIF-Article 1.0
Author-Name: Zied Hajej
Author-X-Name-First: Zied
Author-X-Name-Last: Hajej
Author-Name: Nidhal Rezg
Author-X-Name-First: Nidhal
Author-X-Name-Last: Rezg
Author-Name: Ali Gharbi
Author-X-Name-First: Ali
Author-X-Name-Last: Gharbi
Title: Maintenance on leasing sales strategies for manufacturing/remanufacturing system with increasing failure rate and carbon emission
Abstract: 
 Several literature works have treated the quality question of the new and remanufactured products and its production cost and if the all returned-used products are remanufacturable. In this context, this study treated the case of returned-used products in the lease contract with/without maintenance monitoring option and its influence on the production and maintenance strategies for a manufacturing/remanufacturing system. A new integrated maintenance to production strategy studies the influence of the new and returned-used products according to its quality on the production cost and the degradation level of the manufacturing and remanufacturing units. Firstly, the objective of this study is to determine the economical production plan of manufacturing and remanufacturing units to satisfy the random demands under a given service level and during a finite horizon. Secondly, by considering the influence of the degradation on the failure and emission rates, we determine the optimal preventive maintenance strategy for each production unit, which minimise the total cost of production, maintenance and carbon emission. Numerical results are provided to show the efficiency of the proposed strategies by studying the impact of different parameters of the proposed model.
Journal: International Journal of Production Research
Pages: 6616-6637
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1683254
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683254
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Template-Type: ReDIF-Article 1.0
Author-Name: Wucheng Yang
Author-X-Name-First: Wucheng
Author-X-Name-Last: Yang
Author-Name: Wenming Cheng
Author-X-Name-First: Wenming
Author-X-Name-Last: Cheng
Title: Modelling and solving mixed-model two-sided assembly line balancing problem with sequence-dependent setup time
Abstract: 
 Two-sided assembly lines balancing problem has been extensively studied in recent years. However, only limited attention has been paid to balancing mixed-model two-sided assembly lines problem (MTALBP). Moreover, the majority of balancing research assumes the setup as negligible, although it is ubiquitous in the assembly process. As the non-increment activities, setups occur in two ways: forward and backward setups. According to our best knowledge, no published work in literature on MTALBP has simultaneously considered forward and backward setups. In this paper, the problem of balancing mixed-model two-sided assembly lines with setups (MTALBPS) is considered. The purpose of this paper is twofold. The primary objective is to develop a mixed-integer programming (MIP) mathematical model to formulate the type-I problem of MTALBPS. The secondary objective is to propose an effective variable neighbourhood search (VNS) algorithm to solve it, especially for the large-sized problems. In addition, to test the effectiveness of the proposed approaches, a number of test problems from the literature with up to 148 tasks are solved and compared with the lower bound. The results demonstrate that the proposed algorithm is effective and produces very close results to the lower bound in a reasonable time.
Journal: International Journal of Production Research
Pages: 6638-6659
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1683255
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1683255
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Template-Type: ReDIF-Article 1.0
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Ata Allah Taleizadeh
Author-X-Name-First: Ata Allah
Author-X-Name-Last: Taleizadeh
Author-Name: Xiaohang Yue
Author-X-Name-First: Xiaohang
Author-X-Name-Last: Yue
Title: Game theory applications in production research in the sharing and circular economy era
Abstract: 
 In recent years, topics such as sharing economy and circular supply chains have emerged in production research and operations management. To explore them and tackle the associated challenges, we need to acquire a full understanding of decision makers’ strategic behaviours as well as the deployment of sophisticated analytical methods such as game theory. In this article, we concisely examine the meanings of sharing economy and circular supply chains in production research. We then introduce the featured papers of the special issue and highlight the major insights developed. Future research directions are discussed.
Journal: International Journal of Production Research
Pages: 6660-6669
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1684593
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1684593
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiao-qiu Shi
Author-X-Name-First: Xiao-qiu
Author-X-Name-Last: Shi
Author-Name: Wei Long
Author-X-Name-First: Wei
Author-X-Name-Last: Long
Author-Name: Yan-yan Li
Author-X-Name-First: Yan-yan
Author-X-Name-Last: Li
Author-Name: Ding-shan Deng
Author-X-Name-First: Ding-shan
Author-X-Name-Last: Deng
Author-Name: Yong-lai Wei
Author-X-Name-First: Yong-lai
Author-X-Name-Last: Wei
Author-Name: Hua-guo Liu
Author-X-Name-First: Hua-guo
Author-X-Name-Last: Liu
Title: Research on supply network resilience considering random and targeted disruptions simultaneously
Abstract: 
 Supply networks (SN) must maintain operations and connectedness under disruptions to remain competitive; this is referred to as SN resilience. Building a resilient SN is an underlying challenge in supply chain management. In this paper, SN resilience is examined from the complex network topology perspective to understand how supply chain managers construct resilient networks. The proposed growth model considers enterprises leaving the network, which previous studies have ignored. Considering the heterogeneous roles of enterprises, new metrics based on a new proposed sub-network concept are presented to evaluate resilience. Using a computer simulation, the resilience of the SN generated by the model proposed in this paper is compared with that of other models, and the results indicate that (i) the proposed model can be tuned to generate a desired resilient network; (ii) the proposed metrics capture the resilience requirements of the SN very well; (iii) the more uniform the distribution of the enterprises, the more resilient the corresponding SN; and (iv) the higher the values of α and β, the lower the SN resilience, and β affects the resilience more than α does.
Journal: International Journal of Production Research
Pages: 6670-6688
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685697
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685697
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Template-Type: ReDIF-Article 1.0
Author-Name: Benjamin Vincent
Author-X-Name-First: Benjamin
Author-X-Name-Last: Vincent
Author-Name: Christophe Duhamel
Author-X-Name-First: Christophe
Author-X-Name-Last: Duhamel
Author-Name: Libo Ren
Author-X-Name-First: Libo
Author-X-Name-Last: Ren
Author-Name: Nikolay Tchernev
Author-X-Name-First: Nikolay
Author-X-Name-Last: Tchernev
Title: A population-based metaheuristic for the capacitated lot-sizing problem with unrelated parallel machines
Abstract: 
 This paper deals with the capacitated lot-sizing problem with multiple items, setup time and unrelated parallel machines. The aim of the article is to propose an efficient population-based metaheuristic to tackle this problem. In the proposed approach, a dynamic constructive heuristic is proposed for generating a set of initial solutions. A path-relinking strategy between solutions in the current population is integrated in the diversification procedure, allowing us to explore the solution space further. The population is then intensified using a local search procedure which uses an operator based on machine capacity relaxation coupled with a repair procedure. The proposed approach is evaluated from the instances introduced in Toledo, F. M. B., and V. A. Armentano (2006.“A Lagrangian-Based Heuristic for the Capacitated Lot-Sizing Problem in Parallel Machines.” European Journal of Operational Research 175 (2): 1070–1083). The results of the experiment show that the proposed approach yields competitive results in terms of solution quality for most of the instances.
Journal: International Journal of Production Research
Pages: 6689-6706
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685699
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685699
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Template-Type: ReDIF-Article 1.0
Author-Name: Beixin Xia
Author-X-Name-First: Beixin
Author-X-Name-Last: Xia
Author-Name: Chen Wang
Author-X-Name-First: Chen
Author-X-Name-Last: Wang
Author-Name: Ya Gao
Author-X-Name-First: Ya
Author-X-Name-Last: Gao
Author-Name: Yunfang Peng
Author-X-Name-First: Yunfang
Author-X-Name-Last: Peng
Author-Name: Lei Liu
Author-X-Name-First: Lei
Author-X-Name-Last: Liu
Title: A new approach to the analysis of homogeneous transfer lines with unreliable buffers subject to time-dependent failure
Abstract: 
 This paper presents a new analytical approach to the analysis of transfer lines with unreliable machines and unreliable buffers running in a steady state. The buffers are assumed to be subject to time-dependent failure, i.e. they can fail in any condition, even when not loaded. As the most common representative of this type of buffer, accumulating conveyors are widely adopted in actual transfer lines. In this paper, a continuous model is established for such transfer lines in which the part flow is approximated by a continuous flow. Then, an efficient decomposition method based on a generalised exponential distribution is proposed to analyse the model. A new set of decomposition equations that take into account the mechanism of time-dependent failure are derived and then solved by an advanced algorithm. Extensive numerical experiments are performed. The results show that the proposed method is valid and efficient.
Journal: International Journal of Production Research
Pages: 6707-6723
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685700
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685700
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Template-Type: ReDIF-Article 1.0
Author-Name: Nuno O. Fernandes
Author-X-Name-First: Nuno O.
Author-X-Name-Last: Fernandes
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Author-Name: Sílvio Carmo-Silva
Author-X-Name-First: Sílvio
Author-X-Name-Last: Carmo-Silva
Title: Lot synchronization in make-to-order shops with order release control: an assessment by simulation
Abstract: 
 Lot splitting is an important strategy for avoiding the starvation of workstations, for accelerating the progress of jobs, and ultimately for improving overall due date performance. While lot splitting has received much attention in the extant literature, the use of alternative lot transfer policies that determine how the flow of lots through the production system is synchronised has been largely neglected. This study uses simulation to assess the performance of different lot synchronisation policies at release and different lot transfer policies on the shop floor in a ConWIP (Constant Work-In-Process) controlled job shop. The results suggest that different approaches should be applied at the release and shop floor levels. While lots should be synchronised in some form at order release, their progress on the shop floor should not be synchronised. Instead, lot coordination should be executed by dispatching in accordance with repetitive lots logic. The results further highlight that if lot progress is synchronised in systems that limit the workload, then lot release should also be synchronised. Otherwise, blocking may occur if lot progress on the shop floor depends on the release of lots, which in turn depends on lot progress. These findings have important implications for research and practice.
Journal: International Journal of Production Research
Pages: 6724-6738
Issue: 21
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685701
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685701
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Template-Type: ReDIF-Article 1.0
Author-Name: Hoai An Le Thi
Author-X-Name-First: Hoai An
Author-X-Name-Last: Le Thi
Title: DC programming and DCA for supply chain and production management: state-of-the-art models and methods
Abstract: 
 It is undoubtedly that mathematical modelling and optimisation play a key role in the supply chain and the production management (SCPM). In this paper, we provide a survey on DC (Difference of Convex function) programming and DCA (DC Algorithm), a state-of-the-art optimisation approach for challenging problems in SCPM. DC programming and DCA constitute the backbone of non-convex programming and global optimisation. Whilst DC programming and DCA were widely and successfully investigated in many areas, it seems that they were not so much popular in the community of SCPM. There is therefore a need to further develop this efficient and scalable approach for SCPM applications, especially for large-scale problems in the context of Big data. For such purpose, this paper aims to present benchmark models and state-of-the-art DCA-based methods for solving challenging problems in SCPM systems. We prove that all the benchmark classes of optimisation models appeared in SCPM systems can be formulated/reformulated as a DC program and show how to solve these classes of problems by DCA-based algorithms. We offer the community of researchers in SCPM efficient algorithms in a unified DC programming framework to tackle various applications such as supply chain design, scheduling, multi-stage production/inventory system, vehicle routing, …
Journal: International Journal of Production Research
Pages: 6078-6114
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1657245
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1657245
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Template-Type: ReDIF-Article 1.0
Author-Name: Mashal Farid
Author-X-Name-First: Mashal
Author-X-Name-Last: Farid
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Title: Modelling the effects of employee injury risks on injury, productivity and production quality using system dynamics
Abstract: 
 The aim of the current study is to explore the use of system dynamics (SD) modelling as a tool to examine the impacts of human factors in production on worker low back injury, productivity and quality performance parameters. The SD model was created using relationships in the scientific literature. This data supplemented with input from both a quality and a safety manager in an automotive plant, who also reviewed the resulting causal loop diagrams. Results showed that, over the 5-year simulation period of the base model, percentage of operators reporting low back pain increased from ∼0% to 1.3%, human error rates increased by 40%, and production rate dropped by 0.2%. This example model addressed three risk factors for a single injury type – and is therefore an underestimate of total system impacts of poor HF. While the extension of the model is needed, the current example highlights a cautionary point for managers and designers who may not see an immediate impact of a poor design but may face increased injury, quality and productivity problems over time. This novel application of SD modelling can help isolate and quantify these effects.
Journal: International Journal of Production Research
Pages: 6115-6129
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1667040
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1667040
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Template-Type: ReDIF-Article 1.0
Author-Name: Seyed Ashkan Zarghami
Author-X-Name-First: Seyed Ashkan
Author-X-Name-Last: Zarghami
Author-Name: Indra Gunawan
Author-X-Name-First: Indra
Author-X-Name-Last: Gunawan
Author-Name: Graciela Corral de Zubielqui
Author-X-Name-First: Graciela
Author-X-Name-Last: Corral de Zubielqui
Author-Name: Bassam Baroudi
Author-X-Name-First: Bassam
Author-X-Name-Last: Baroudi
Title: Incorporation of resource reliability into critical chain project management buffer sizing
Abstract: 
 The methods presently used for buffer sizing of Critical Chain Project Management (CCPM) have lagged far behind capturing the stochastic nature of resource acquisition in real-world projects. The work described herein represents a new step towards the sizing of buffers for CCPM by developing a probabilistic measure obtained through a reliability analysis of project resources. The proposed method treats the resource availability as a random variable in project scheduling, meaning that each resource has a distribution of possible values of availability. In this method, buffer size is determined by assigning a scaling factor to the standard deviation of a chain. This scaling factor is the function of the reliability of available resources assigned to the chain activities, taking into account the likelihood of timely completion of the chain given the reliability of each individual resource. Sensitivity analysis, as well as the comparison of the proposed method with the conventional buffer sizing methods, reveal the effectiveness of the new method.
Journal: International Journal of Production Research
Pages: 6130-6144
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1667041
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1667041
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Template-Type: ReDIF-Article 1.0
Author-Name: Feiyan Han
Author-X-Name-First: Feiyan
Author-X-Name-Last: Han
Author-Name: Chuanwei Zhang
Author-X-Name-First: Chuanwei
Author-X-Name-Last: Zhang
Author-Name: Wu Zhang
Author-X-Name-First: Wu
Author-X-Name-Last: Zhang
Author-Name: Wei Guo
Author-X-Name-First: Wei
Author-X-Name-Last: Guo
Author-Name: Bin Feng
Author-X-Name-First: Bin
Author-X-Name-Last: Feng
Title: A dynamic synchronous optimisation method of tool sequence selection and multi-state process models depth distribution for high efficiency machining
Abstract: 
 In order to overcome the problem that the existing tool selection method only considers how to select the tool on a given single or multiple process surfaces, and the tool sequence of the whole machining process obtained by this existing method is not necessarily optimal. In this paper, a synchronous optimisation method about the tool sequence selection and the depth distribution of multi-state intermediate surfaces is proposed. Firstly, a mathematical model is established to optimise the depth distribution of the process surfaces with the minimum processing time as the objective function, and then it is transformed into an optimisation model which is related to the tool sequence through the parametric analysis, and the constraint equation is established based on the relationship between the parameter variables which associates with the tool, here the parameter variables contain the machinable area of a tool, the number of tool reuse times and the maximum cutting depth. Secondly, a two-step method of calculation the largest available tool set and the optimal tool sequence is given for solving this optimisation model. Finally, the impeller machining is taken as an example, the optimised depth distribution of process surfaces for impeller channel machining is calculated. A comparison machining of the optimised process surfaces and un-optimised process surfaces is carried out. The result shows that the optimised method presented in this paper reduces the total processing time by 126 s and improves the machining efficiency by 6.5% for a single impeller channel.
Journal: International Journal of Production Research
Pages: 6145-6158
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1668069
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1668069
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Template-Type: ReDIF-Article 1.0
Author-Name: Mikhail V. Batsyn
Author-X-Name-First: Mikhail V.
Author-X-Name-Last: Batsyn
Author-Name: Ekaterina K. Batsyna
Author-X-Name-First: Ekaterina K.
Author-X-Name-Last: Batsyna
Author-Name: Ilya S. Bychkov
Author-X-Name-First: Ilya S.
Author-X-Name-Last: Bychkov
Title: NP-completeness of cell formation problem with grouping efficacy objective
Abstract: 
 In the current paper we provide a proof of NP-completeness for the Cell Formation Problem (CFP) with the fractional grouping efficacy objective function. First the CFP with a linear objective function is considered. Following the ideas of Pinheiro et al. (2016) we show that it is equivalent to the Bicluster Graph Editing Problem (BGEP), which is known to be NP-complete due to the reduction from the 3-Exact 3-Cover Problem – 3E3CP (Amit, 2004). Then we suggest a polynomial reduction of the CFP with the linear objective to the CFP with the grouping efficacy objective. It proves the NP-completeness of this fractional CFP formulation. Along with the NP-status our paper presents important connections of the CFP with the BGEP and 3E3CP. Such connections could be used for ”transferring” of known theoretical properties, efficient algorithms, polynomial cases, and other features of well-studied graph editing and exact covering problems to the CFP.
Journal: International Journal of Production Research
Pages: 6159-6169
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1668072
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1668072
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Template-Type: ReDIF-Article 1.0
Author-Name: Kevin Grant
Author-X-Name-First: Kevin
Author-X-Name-Last: Grant
Author-Name: Roman Matousek
Author-X-Name-First: Roman
Author-X-Name-Last: Matousek
Author-Name: Martin Meyer
Author-X-Name-First: Martin
Author-X-Name-Last: Meyer
Author-Name: Nickolaos G. Tzeremes
Author-X-Name-First: Nickolaos G.
Author-X-Name-Last: Tzeremes
Title: Research and development spending and technical efficiency: evidence from biotechnology and pharmaceutical sector
Abstract: 
 Set within the expenditure context of the global financial crisis (GFC), this paper explores how the research and development (R&D) expenditures of biotechnology and pharmaceutical companies affect their technical efficiency levels. A balanced panel of 149 US firms operating in the biotechnology and pharmaceutical sector (covering the period 2000–2017) was employed. Output-oriented partial frontier measures were used to measure the effect of R&D expenditure on firms’ technical efficiency levels. Findings suggest that company efficiency is an important contributor on the effects of R&D on productivity and efficiency. Result suggests that a relationship between technical efficiency and R&D expenditure exhibits a ‘U’-shape relationship. The estimated efficiency of biotechnology firms is higher compared to pharmaceutical firms driven by their higher R&D expenditure levels. We demonstrate that R&D expenditures are essential for firm efficiency. We posit that a threshold level for achieving optimal efficiency levels exist, which can be used to inform managerial and policy-making decisions at the firm level.
Journal: International Journal of Production Research
Pages: 6170-6184
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1671623
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1671623
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Template-Type: ReDIF-Article 1.0
Author-Name: Thomas Ditlev Brunoe
Author-X-Name-First: Thomas Ditlev
Author-X-Name-Last: Brunoe
Author-Name: Ann-Louise Andersen
Author-X-Name-First: Ann-Louise
Author-X-Name-Last: Andersen
Author-Name: Daniel G.H. Sorensen
Author-X-Name-First: Daniel G.H.
Author-X-Name-Last: Sorensen
Author-Name: Kjeld Nielsen
Author-X-Name-First: Kjeld
Author-X-Name-Last: Nielsen
Author-Name: Mads Bejlegaard
Author-X-Name-First: Mads
Author-X-Name-Last: Bejlegaard
Title: Integrated product-process modelling for platform-based co-development
Abstract: 
 Changeable manufacturing and platform-based co-development of products and manufacturing systems are becoming increasingly relevant for industrial manufacturing in order to respond to volatile markets, increased product variety and shorter product life cycles. However, in order to conduct platform-based co-development, it is necessary to manage the relations between the product domain and the manufacturing domain. This paper proposes an approach and meta-model for developing company-specific ontologies, which can be used for modelling the portfolio of components, processes and equipment and their interrelations as a basis for co-evolution. Developing such a model has implications for developing and utilising changeable manufacturing, which is also analysed in this paper.
Journal: International Journal of Production Research
Pages: 6185-6201
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1671628
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1671628
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Template-Type: ReDIF-Article 1.0
Author-Name: Woo-Kyun Jung
Author-X-Name-First: Woo-Kyun
Author-X-Name-Last: Jung
Author-Name: Hyungjung Kim
Author-X-Name-First: Hyungjung
Author-X-Name-Last: Kim
Author-Name: Young-Chul Park
Author-X-Name-First: Young-Chul
Author-X-Name-Last: Park
Author-Name: Jae-Won Lee
Author-X-Name-First: Jae-Won
Author-X-Name-Last: Lee
Author-Name: Sung-Hoon Ahn
Author-X-Name-First: Sung-Hoon
Author-X-Name-Last: Ahn
Title: Smart sewing work measurement system using IoT-based power monitoring device and approximation algorithm
Abstract: 
 To enable Small and Medium-sized Enterprises (SMEs) level garment manufacturers to measure and monitor the work of individual workers without incurring a large financial burden, a smart sewing work measurement system was developed using an IoT-based power monitoring device and an approximation algorithm. The amount of electric current used in the sewing work was measured, and the measured data was transmitted to a server using Wi-Fi communication. The analysis of the data was conducted through the Symbolic Aggregate approximation (SAX) and Dynamic Time Warping (DTW) methods. The daily workload of each worker derived from the system developed through this study showed an error rate of 8% compared to the actual workload, and the time measured by the sensor was different from the time measured by a manager using a stopwatch. These differences are considered to be due to measurement errors in the stopwatch, human noise from the measurer and the operator, and the relatively few samples relative to the total workload. The IoT-based power monitoring and work measurement system for sewing work developed through this study can be applied to smart garment manufacturing factories at an acceptable cost level, while SMEs can realise high recognition rates and semi-real-time monitoring.
Journal: International Journal of Production Research
Pages: 6202-6216
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1671629
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1671629
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Template-Type: ReDIF-Article 1.0
Author-Name: Renu Agarwal
Author-X-Name-First: Renu
Author-X-Name-Last: Agarwal
Author-Name: Paul J. Brown
Author-X-Name-First: Paul J.
Author-X-Name-Last: Brown
Author-Name: Christopher Bajada
Author-X-Name-First: Christopher
Author-X-Name-Last: Bajada
Author-Name: Philip Stevens
Author-X-Name-First: Philip
Author-X-Name-Last: Stevens
Author-Name: Roy Green
Author-X-Name-First: Roy
Author-X-Name-Last: Green
Title: The effects of competition on management practices in New Zealand – a study of manufacturing firms
Abstract: 
 Competition is a key factor in driving performance improvements across a range of firm activities including reductions in costs, increasing the levels of productivity, promoting entrepreneurial efforts, fostering innovation, driving better management practices, and exercising strategic managerial decisions. The questions of how and why competitive market forces influence management practices are the focus of this paper. Using data on management practices from 152 New Zealand manufacturing firms, and competition data obtained for various industries of the NZ economy, we examine the association between different dimensions of competition and management practices. Notably, we find little or no association between better management practices and competition when utilising simpler measures of competition, namely the number of competitors, industry concentration measured by HHI and the price-cost margin are used. However, using a more refined measure of competition, competition intensity characterised by profit elasticity, has a positive and significant association with the quality of management practices adopted by firms.
Journal: International Journal of Production Research
Pages: 6217-6234
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1672901
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1672901
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Template-Type: ReDIF-Article 1.0
Author-Name: Jun Yang
Author-X-Name-First: Jun
Author-X-Name-Last: Yang
Author-Name: Fanbing Meng
Author-X-Name-First: Fanbing
Author-X-Name-Last: Meng
Author-Name: Shuo Huang
Author-X-Name-First: Shuo
Author-X-Name-Last: Huang
Author-Name: Yanhe Cui
Author-X-Name-First: Yanhe
Author-X-Name-Last: Cui
Title: Process capability analysis for manufacturing processes based on the truncated data from supplier products
Abstract: 
 Quality data fraud not only destroys the trust between suppliers and customers but also misleads the decision-making when choosing suppliers. Thus, it is preferred to use the quality data measured by customers to evaluate the manufacturing process capability indexes (PCIs). In practice, the suppliers always conduct a preliminary internal inspection to eliminate the nonconforming items before selling products, and quality data measured by the customers are truncated by the specification limits, which makes it difficult to measure the PCIs. This paper proposes a novel method to estimate the PCIs based on the truncated data. First, we propose a new data filling method called the QA-EM by integrating the EM and quantile-filling algorithms. Consequently, the truncated data can be converted into pseudo-complete data. A comparison study with other methods is further carried out to demonstrate the superiority of our proposed method. Then, various interval methods for estimating PCIs are applied to calculate the lower confidence limits of  ${C_{pk}} $Cpk based on the pseudo-complete data. We investigate the performance of different methods in terms of coverage rate. The results indicate that the generalised confidence interval method performs better than the competitors. Finally, an industrial example is presented to illustrate the application of our method.
Journal: International Journal of Production Research
Pages: 6235-6251
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1675916
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1675916
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Template-Type: ReDIF-Article 1.0
Author-Name: Jabir Mumtaz
Author-X-Name-First: Jabir
Author-X-Name-Last: Mumtaz
Author-Name: Zailin Guan
Author-X-Name-First: Zailin
Author-X-Name-Last: Guan
Author-Name: Lei Yue
Author-X-Name-First: Lei
Author-X-Name-Last: Yue
Author-Name: Li Zhang
Author-X-Name-First: Li
Author-X-Name-Last: Zhang
Author-Name: Cong He
Author-X-Name-First: Cong
Author-X-Name-Last: He
Title: Hybrid spider monkey optimisation algorithm for multi-level planning and scheduling problems of assembly lines
Abstract: 
 The production planning and scheduling problems of printed circuit board (PCB) assembly line robustly influence the production efficiency of PCB industries. The current study focuses on the optimisation of the multi-level planning and scheduling problem by minimising the cycle time of the PCB assembly lines. Two levels of planning problems i.e. component allocation problem (CAP) and component placement sequence problem (CPSP) are solved simultaneously using mixed integer linear programming model. In CAP, a model is formulated with the objective of balancing the workload among the surface mounted machines (SMM), while in CPSP, a model is formulated to find optimum sequencing for allocated components at each SMM. A novel hybrid spider monkey optimisation (HSMO) algorithm is proposed with the addition of new sorting food sources and genetic operators in the standard spider monkey optimisation (SMO) algorithm. The performance of the proposed HSMO algorithm is validated by comparing the solutions with well-known algorithms, i.e. genetic algorithm (GA), particle swarm optimisation (PSO), simulated annealing (SA) and artificial bee colony (ABC) algorithms. The proposed HSMO algorithm is tested on different problem set instances scaled based on the realistic production of PCB industries. The detailed analysis of results indicates that the proposed HSMO algorithm outperforms the compared algorithms in efficiency and effectiveness.
Journal: International Journal of Production Research
Pages: 6252-6267
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1675917
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1675917
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Template-Type: ReDIF-Article 1.0
Author-Name: Jesús F. Lampón
Author-X-Name-First: Jesús F.
Author-X-Name-Last: Lampón
Author-Name: Javier González-Benito
Author-X-Name-First: Javier
Author-X-Name-Last: González-Benito
Title: Backshoring and improved key manufacturing resources in firms’ home location
Abstract: 
 This research explores the influence on manufacturing backshoring of improved key manufacturing resources in the home location of firms. Analysis of recent cases of backshoring in the European manufacturing industry shows that the production processes of firms that have backshored to their home location offer greater optimisation in terms of workforce, are more production assets intensive and have a higher technological level than when they offshored. The results highlight the relevance of internal factors in manufacturing backshoring analysis. This is of special interest from a production systems perspective because it is these internal factors that managers can control and therefore gain decision-making power regarding the location of manufacturing activities. This study also contributes to the debate on how innovations and improvements in manufacturing processes could increase industrial production and employment in advanced economies.
Journal: International Journal of Production Research
Pages: 6268-6282
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1676479
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1676479
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:20:p:6268-6282




Template-Type: ReDIF-Article 1.0
Author-Name: Sofia Panagiotidou
Author-X-Name-First: Sofia
Author-X-Name-Last: Panagiotidou
Title: Joint optimization of spare parts ordering and age-based preventive replacement
Abstract: 
 In this paper, an integrated model for the joint optimisation of preventive replacement time and spare parts ordering policy is proposed for systems with more than one identical items that operate in parallel. The operating items are preventively replaced under an item-specific age-based preventive replacement policy, while the inventory of spare parts is continuously monitored and replenished under an (s, S) continuous review policy, combined with emergency orders in case of shortages during lead time. The optimal cost of the proposed model is compared against the one of sequential optimisation, where the preventive replacement time is first selected using a traditional age-based preventive replacement model and the inventory control parameters are then optimised for the resulting value of the preventive replacement time. The numerical analysis shows that, unless a preventive replacement is not economically advisable, the proposed model significantly outperforms sequential optimisation. In addition, the proposed model is also compared against the case where the system inter-replacement times are assumed to follow the exponential distribution. The numerical analysis shows that such an approximation, although it is satisfactory when the number of items is large, can be very costly when the number of items in the system and/or the order lead time is quite small.
Journal: International Journal of Production Research
Pages: 6283-6299
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1677959
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1677959
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Template-Type: ReDIF-Article 1.0
Author-Name: Yi Wang
Author-X-Name-First: Yi
Author-X-Name-Last: Wang
Author-Name: Sheng Hao Zhang
Author-X-Name-First: Sheng Hao
Author-X-Name-Last: Zhang
Author-Name: Sean X. Zhou
Author-X-Name-First: Sean X.
Author-X-Name-Last: Zhou
Author-Name: Yong Zhang
Author-X-Name-First: Yong
Author-X-Name-Last: Zhang
Title: Anticipated rationing policy for inventory systems with two demand classes and backlogging costs
Abstract: 
 This paper studies a periodic-review, infinite-horizon, backlogging inventory model with two demand classes and a constant lead time, where inventory replenishment follows a base-stock policy. We consider an anticipated rationing policy which reserves inventory for future high-priority demands with higher backlogging costs by taking the coming delivery of the next period into consideration. Due to the lack of nice properties such as convexity, both the optimal base-stock level and the optimal critical level when minimising inventory costs have to be found by an exhaustive search. Instead, we study a single-period problem truncated from the original infinite-horizon problem and derive its optimal reservation level with a closed-form expression. Surprisingly, the solution form of the single-period problem coincides exactly with the anticipated rationing policy and hence this solution serves as a good approximation for the optimal critical level of the infinite-horizon problem. An empirical study further demonstrates that our closed-form approximation is quite attractive in both solution accuracy and computation efficiency based on spare parts inventory data from a petrochemical plant in China.
Journal: International Journal of Production Research
Pages: 6300-6314
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1677960
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1677960
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiuxian Wang
Author-X-Name-First: Xiuxian
Author-X-Name-Last: Wang
Author-Name: Xuran Gong
Author-X-Name-First: Xuran
Author-X-Name-Last: Gong
Author-Name: Na Geng
Author-X-Name-First: Na
Author-X-Name-Last: Geng
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Author-Name: Liping Zhou
Author-X-Name-First: Liping
Author-X-Name-Last: Zhou
Title: Metamodel-based simulation optimisation for bed allocation
Abstract: 
 Hospital beds are one of the most critical resources in healthcare institutions. In practice, beds are usually allocated to different departments in advance to accommodate different kinds of patients. Inappropriate decisions in the allocation may lead to the idleness of beds or the high rejection ratio of patients. Hospital managers are under pressure to allocate beds to different departments. High variability in patient arrivals and service times make the allocation problem complex and challenging to solve. To address this problem, a mixed-integer non-linear programming model is formulated, with the objective of minimising the weighted cost of rejecting patients and holding them waiting. To solve this model, a data-driven metamodel simulation optimisation method is proposed, in which metamodels, based on an analytical queuing model and a general function, are proposed and embedded into a general-purpose algorithm Adaptive Hyperbox Algorithm. The metamodels designated for local and global approximation are separately fitted using different sets of simulation observations, which can combine structural information and simulation information, and can provide insightful guidance in solution improvements. A case study is conducted based on the real data collected from a public hospital in Shanghai. Numerical results demonstrate the efficiency of the proposed method.
Journal: International Journal of Production Research
Pages: 6315-6335
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1677962
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1677962
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Haiwen Zhang
Author-X-Name-First: Haiwen
Author-X-Name-Last: Zhang
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Author-Name: Federica Costa
Author-X-Name-First: Federica
Author-X-Name-Last: Costa
Author-Name: Lin Ma
Author-X-Name-First: Lin
Author-X-Name-Last: Ma
Title: Worker assignment in dual resource constrained assembly job shops with worker heterogeneity: an assessment by simulation
Abstract: 
 Most shops in practice are constrained by more than one resource. Consequently, a large body of literature on dual resource constrained shops has emerged. This research typically focuses on worker assignment rules, with attention being on when and where to move workers. In contrast, the decision concerning who to reallocate to a station has received limited attention. The limited prior work assumes workers are assigned to a new station as soon as they become available or seeks to minimise the risk of worker idleness. Using simulation, we question this assumption and show that it can be beneficial to introduce additional worker idleness to ensure workers only work at their most efficient station(s). In general, it is less likely that there are several workers available for one station than it is for there to be multiple stations available for one worker. Consequently, the Who Rule is used less frequently than the Where rule and has less of an impact on performance. Finally, considering the criticality of work orders as part of the Where Rule is important in assembly shops; but if labour is heterogeneous then the focus should be on efficiency. The findings have important implications for research and practice.
Journal: International Journal of Production Research
Pages: 6336-6349
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1677963
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1677963
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:20:p:6336-6349




Template-Type: ReDIF-Article 1.0
Author-Name: Diego Jacinto Fiorotto
Author-X-Name-First: Diego Jacinto
Author-X-Name-Last: Fiorotto
Author-Name: Jackeline del Carmen Huaccha Neyra
Author-X-Name-First: Jackeline del Carmen
Author-X-Name-Last: Huaccha Neyra
Author-Name: Silvio Alexandre de Araujo
Author-X-Name-First: Silvio Alexandre
Author-X-Name-Last: de Araujo
Title: Impact analysis of setup carryover and crossover on lot sizing problems
Abstract: 
 This paper presents a literature classification and a detailed computational study analysing the impact of considering the possibility of setup carryover and crossover when solving the lot sizing problem. This problem is an extension of the standard Capacitated Lot Sizing Problem. A setup carryover is defined as the possibility to begin a period with production (instead of setup) of the item that was being produced at the end of the previous period. A setup crossover allows the opportunity to start a setup operation in one period and continue it to the following one, i.e. the setup operation can span over two periods. We adapt and compare two formulations proposed in the literature that have not been compared each other. Furthermore, some formulations proposed in the literature for modelling the setup crossover with a reduced number of binary variables, are extended to the addressed problem. Finally, a relax-and-fix and fix-and-optimise (RF-FO) heuristic is also applied to solve some difficult instances. Computational results are presented based on random generated data.
Journal: International Journal of Production Research
Pages: 6350-6369
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1680892
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1680892
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Template-Type: ReDIF-Article 1.0
Author-Name: Maurizio Bevilacqua
Author-X-Name-First: Maurizio
Author-X-Name-Last: Bevilacqua
Author-Name: Filippo Emanuele Ciarapica
Author-X-Name-First: Filippo Emanuele
Author-X-Name-Last: Ciarapica
Author-Name: Giulio Marcucci
Author-X-Name-First: Giulio
Author-X-Name-Last: Marcucci
Author-Name: Giovanni Mazzuto
Author-X-Name-First: Giovanni
Author-X-Name-Last: Mazzuto
Title: Fuzzy cognitive maps approach for analysing the domino effect of factors affecting supply chain resilience: a fashion industry case study
Abstract: 
 The domino effect that occurs among the concepts that affect Supply Chain Resilience has only been marginally analysed, and no conceptual models have been proposed in the literature. In this work, a conceptual model for analysing this domino effect is developed. The method aims to identify which supply chain concepts can support the containment of disruptions and how these concepts affect one another. The proposed methodology is based on Fuzzy Cognitive Maps. The Cognitive Maps tool enables us to connect multidimensional and multidisciplinary concepts (e.g. sources of risk, disruption factors, supply chain management practices and other aspects). Moreover, this tool allows company managers to develop a detailed understanding of a system's behaviour and to explicitly consider the mind models of different players in the supply chain. A case study of the fashion industry supply chain is used to illustrate the application of the proposed method in an operating context. The proposed method enables a company to evaluate the hidden chain reaction of causes behind the most important factors that, from a single trigger event, are able to harm the entire Supply Chain. Through analysis of the causal relationships that this methodology highlights, decision makers can examine the domino effect among the concepts that influence Supply Chain Resilience in a step-by-step manner.
Journal: International Journal of Production Research
Pages: 6370-6398
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1680893
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1680893
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Template-Type: ReDIF-Article 1.0
Author-Name: Heng Zhang
Author-X-Name-First: Heng
Author-X-Name-Last: Zhang
Author-Name: Utpal Roy
Author-X-Name-First: Utpal
Author-X-Name-Last: Roy
Author-Name: Yung-Tsun Tina Lee
Author-X-Name-First: Yung-Tsun Tina
Author-X-Name-Last: Lee
Title: Enriching analytics models with domain knowledge for smart manufacturing data analysis
Abstract: 
 Today, data analytics plays an important role in Smart Manufacturing decision making. Domain knowledge is very important to support the development of analytics models. However, in today's data analytics projects, domain knowledge is only documented, but not properly captured and integrated with analytics models. This raises problems in interoperability and traceability of the relevant domain knowledge that is used to develop analytics models. To address these problems, this paper proposes a methodology to enrich analytics models with domain knowledge. To illustrate the proposed methodology, a case study is introduced to demonstrate the utilisation of the enriched analytics model to support the development of a Bayesian Network model. The case study shows that the utilisation of an enriched analytics model improves the efficiency in developing the Bayesian Network model.
Journal: International Journal of Production Research
Pages: 6399-6415
Issue: 20
Volume: 58
Year: 2020
Month: 10
X-DOI: 10.1080/00207543.2019.1680895
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1680895
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Template-Type: ReDIF-Article 1.0
Author-Name: Chaoyang Zhang
Author-X-Name-First: Chaoyang
Author-X-Name-Last: Zhang
Author-Name: Zhengxu Wang
Author-X-Name-First: Zhengxu
Author-X-Name-Last: Wang
Author-Name: Kai Ding
Author-X-Name-First: Kai
Author-X-Name-Last: Ding
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: Weixi Ji
Author-X-Name-First: Weixi
Author-X-Name-Last: Ji
Title: An energy-aware cyber physical system for energy Big data analysis and recessive production anomalies detection in discrete manufacturing workshops
Abstract: 
 With the development of sensing and communications technology, some new features have emerged in manufacturing processes, such as highly correlated, deeply integrated, dynamically integrated, and a huge volume of data. There is a strong need to deeply excavate information from manufacturing Big Data, especially the energy consumption data, for energy-efficient manufacturing operations management and analysis. However, relevant data reduction and association analysis to support energy-efficient manufacturing are still ineffective and error-prone, especially for discrete manufacturing workshops. In this paper, an energy-aware Cyber Physical System (E-CPS) is proposed for energy Big Data analysis and recessive production anomalies detection. Firstly, E-CPS is introduced to acquire manufacturing Big Data. Then, a Big Data analysis method, including data reduction and data association analysis, is proposed to analyse the manufacturing data in the E-CPS. Considering the complexity and dynamics of manufacturing processes, an energy Big Data-driven recessive production anomalies analysis method is proposed based on deep belief networks. The proposed method in this paper realises the integrated utilisation of production Big Data and energy Big Data in the E-CPS. Further, the efficiency evaluation and recessive anomalies detection methods can be used in existing production information systems.
Journal: International Journal of Production Research
Pages: 7059-7077
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1748904
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1748904
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Template-Type: ReDIF-Article 1.0
Author-Name: Lishu Lv
Author-X-Name-First: Lishu
Author-X-Name-Last: Lv
Author-Name: Zhaohui Deng
Author-X-Name-First: Zhaohui
Author-X-Name-Last: Deng
Author-Name: Can Yan
Author-X-Name-First: Can
Author-X-Name-Last: Yan
Author-Name: Tao Liu
Author-X-Name-First: Tao
Author-X-Name-Last: Liu
Author-Name: Linlin Wan
Author-X-Name-First: Linlin
Author-X-Name-Last: Wan
Author-Name: Qianwei Gu
Author-X-Name-First: Qianwei
Author-X-Name-Last: Gu
Title: Modelling and analysis for processing energy consumption of mechanism and data integrated machine tool
Abstract: 
 Reducing the energy consumption of machine tool processing has been a consistent concern and research issue in the international manufacturing industry. To achieve energy conservation and emissions reduction in machine tools, an energy consumption model of the machining process must first be established. However, considering the differences in machining equipment, complex energy flow conditions and time-varying load forces, accurate energy consumption of machining process can be difficult to obtain. Against this backdrop, our research proposes a modelling method for processing energy consumption with an integration mechanism and data, that considers the advantages of mechanism analysis modelling and data modelling. Among them, the mechanism analytical model for characterising energy consumption is determined by the dynamic mechanism of the multi-energy source of the machine tool. The data model is built using a support vector machine (SVM) algorithm based on the deviation between the actual results and the theoretical model. Then, a case study is performed to verify the feasibility and practicability of the proposed method. The results demonstrate accurate prediction and quantitative analysis of energy consumption.
Journal: International Journal of Production Research
Pages: 7078-7093
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1756508
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1756508
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhengxu Wang
Author-X-Name-First: Zhengxu
Author-X-Name-Last: Wang
Author-Name: Waqar Ahmed Khan
Author-X-Name-First: Waqar Ahmed
Author-X-Name-Last: Khan
Author-Name: Hoi-Lam Ma
Author-X-Name-First: Hoi-Lam
Author-X-Name-Last: Ma
Author-Name: Xin Wen
Author-X-Name-First: Xin
Author-X-Name-Last: Wen
Title: Cascade neural network algorithm with analytical connection weights determination for modelling operations and energy applications
Abstract: 
 The performance and learning speed of the Cascade Correlation neural network (CasCor) may not be optimal because of redundant hidden units’ in the cascade architecture and the tuning of connection weights. This study explores the limitations of CasCor and its variants and proposes a novel constructive neural network (CNN). The basic idea is to compute the input connection weights by generating linearly independent hidden units from the orthogonal linear transformation, and the output connection weights by connecting hidden units in a linear relationship to the output units. The work is unique in that few attempts have been made to analytically determine the connection weights on both sides of the network. Experimental work on real energy application problems such as predicting powerplant electrical energy, predicting seismic hazards to prevent fatal accidents and reducing energy consumption by predicting building occupancy detection shows that analytically calculating the connection weights and generating non-redundant hidden units improves the convergence of the network. The proposed CNN is compared with that of the state-of-the-art machine learning algorithms. The work demonstrates that proposed CNN predicts a wide range of applications better than other methods.
Journal: International Journal of Production Research
Pages: 7094-7111
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1764656
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1764656
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiage Huo
Author-X-Name-First: Jiage
Author-X-Name-Last: Huo
Author-Name: Jianghua Zhang
Author-X-Name-First: Jianghua
Author-X-Name-Last: Zhang
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Title: A fuzzy control system for assembly line balancing with a three-state degradation process in the era of Industry 4.0
Abstract: 
 The assembly line balancing problem is always explored using the assumption that the processing ability of each workstation is constant. However, the initial workload balance can be easily broken by the changing processing condition of the machines, due to degradation. In the context of Industry 4.0, real-time information related to the machine health state is available. The aim is to improve the performance of the assembly process by making full use of the obtained real-time information. This research is the first exploration of real-time assembly line balancing with the changing health states of machines and the trigger point of adjustments to the assembly line. In this study, a fuzzy control system is developed to determine when to re-balance the assembly line and how to adjust the production rates to smooth the workloads of the workstations. The numerical results show that the assembly line with the proposed fuzzy control system satisfies the demand for most cases, and achieves higher utilisation of machines and lower buffer levels. Therefore, the real-time information brought by Industry 4.0 can be used to improve the performance of an assembly line.
Journal: International Journal of Production Research
Pages: 7112-7129
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1786186
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1786186
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Template-Type: ReDIF-Article 1.0
Author-Name: Corentin Le Hesran
Author-X-Name-First: Corentin
Author-X-Name-Last: Le Hesran
Author-Name: Aayush Agarwal
Author-X-Name-First: Aayush
Author-X-Name-Last: Agarwal
Author-Name: Anne-Laure Ladier
Author-X-Name-First: Anne-Laure
Author-X-Name-Last: Ladier
Author-Name: Valérie Botta-Genoulaz
Author-X-Name-First: Valérie
Author-X-Name-Last: Botta-Genoulaz
Author-Name: Valérie Laforest
Author-X-Name-First: Valérie
Author-X-Name-Last: Laforest
Title: Reducing waste in manufacturing operations: bi-objective scheduling on a single-machine with coupled-tasks
Abstract: 
 This study addresses a scheduling problem involving a single-machine with coupled-tasks and bi-objective optimisation considering simultaneously inventory and environmental waste. A Mixed Integer Linear Program representing the problem is first developed. Subsequently, a Genetic Algorithm (GA) is presented, followed by numerical experiments on multiple instances. Pareto fronts are determined using the ϵ-constraint and weighted sum methods, and a trade-off point is selected according to a distance criterion. Numerical experiments on both small and large instances show near-optimal results for small instances, and considerably reduced computing times for large ones when using the GA. The results show that a compromise can be found, with a decrease in setup-related waste up to 36% for an increase of inventory of 12%. This will help decision-makers to better consider the environmental aspect when designing schedules, as well as reduce their production environmental impact and waste-management costs.
Journal: International Journal of Production Research
Pages: 7130-7148
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2019.1693653
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693653
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Template-Type: ReDIF-Article 1.0
Author-Name: Oliver Polo-Mejía
Author-X-Name-First: Oliver
Author-X-Name-Last: Polo-Mejía
Author-Name: Christian Artigues
Author-X-Name-First: Christian
Author-X-Name-Last: Artigues
Author-Name: Pierre Lopez
Author-X-Name-First: Pierre
Author-X-Name-Last: Lopez
Author-Name: Virginie Basini
Author-X-Name-First: Virginie
Author-X-Name-Last: Basini
Title: Mixed-integer/linear and constraint programming approaches for activity scheduling in a nuclear research facility
Abstract: 
 This paper presents the results of a research project aiming to optimise the scheduling of activities within a research laboratory of the ‘Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA)’. To tackle this problem, we decompose every activity into a set of elementary tasks to apply standard scheduling methods. We model the problem as an extended version of the Multi-Skill Project Scheduling Problem (MSPSP). As a first approach, we propose a Multi-Skill Project Scheduling Problem with penalty for preemption, along with its mixed-integer/linear programming (MILP) formulation, where the preemption is allowed applying a penalty every time an activity is interrupted. However, the previous approach does not take into account all safety constraints at the facility, and a more accurate variant of the problem is needed. We propose then to integrate the concept of partial preemption to the MSPSP. This concept, that has not been yet studied in the scientific literature, implies that only a subset of resources is released during preemption periods. The resulting MSPSP with partial preemption (MSPSP-PP) is modelled using two methodologies: MILP and constraint programming. Regarding the industrial need of having good solutions in a short time, we also present a greedy algorithm for the MSPSP-PP.
Journal: International Journal of Production Research
Pages: 7149-7166
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2019.1693654
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693654
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Template-Type: ReDIF-Article 1.0
Author-Name: Hui Yang
Author-X-Name-First: Hui
Author-X-Name-Last: Yang
Author-Name: Ding Zhang
Author-X-Name-First: Ding
Author-X-Name-Last: Zhang
Author-Name: Bintong Chen
Author-X-Name-First: Bintong
Author-X-Name-Last: Chen
Author-Name: Baosheng Gu
Author-X-Name-First: Baosheng
Author-X-Name-Last: Gu
Title: Competitive consignment matching: applications in supply chain
Abstract: 
 This paper studies consignment matching between consignee(s) and consignors, where a consignee can be a retailer in a supply chain or a ridesharing platform while consignors are manufacturers or drivers, respectively. Each consignee determines her consignment policy, which consists of a slotting fee and a withholding percentage of the revenue generated by consignors. Consignors then choose which consignee to work with to maximise their respective profits. We consider cases where the consignee is a monopoly or faces competition. In case of a monopoly, we consider a system with one consignee and multiple consigners. We formulate the problem as a 0–1 mixed integer programming and propose an efficient corner point method to find the optimal consignment policy. In case of competition, we consider the consignment matching between two competing consignees and two consignors. When one consignee dominates the other, we model the problem as a leader-follower game and propose a barrier line strategy to obtain its Stackelberg equilibrium. The impact of competition on consignees’ consignment policy, the resulting matching with consignors, and the associated profits, are thoroughly investigated. When the two consignees do not dominate, their competition is modelled as a Cournot-Nash game. We show, however, no pure strategy Nash equilibrium exists. We provide numerical examples to illustrate our algorithms and demonstrate the impacts of competition on consignment policies.
Journal: International Journal of Production Research
Pages: 7167-7180
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2019.1693657
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693657
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Template-Type: ReDIF-Article 1.0
Author-Name: Surendra M. Gupta
Author-X-Name-First: Surendra M.
Author-X-Name-Last: Gupta
Author-Name: Aşkıner Güngör
Author-X-Name-First: Aşkıner
Author-X-Name-Last: Güngör
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Eren Özceylan
Author-X-Name-First: Eren
Author-X-Name-Last: Özceylan
Author-Name: Can Berk Kalaycı
Author-X-Name-First: Can Berk
Author-X-Name-Last: Kalaycı
Author-Name: Rajesh Piplani
Author-X-Name-First: Rajesh
Author-X-Name-Last: Piplani
Title: Responsible & sustainable manufacturing
Journal: International Journal of Production Research
Pages: 7181-7182
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1841968
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1841968
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Template-Type: ReDIF-Article 1.0
Author-Name: Özden Tozanlı
Author-X-Name-First: Özden
Author-X-Name-Last: Tozanlı
Author-Name: Elif Kongar
Author-X-Name-First: Elif
Author-X-Name-Last: Kongar
Author-Name: Surendra M. Gupta
Author-X-Name-First: Surendra M.
Author-X-Name-Last: Gupta
Title: Trade-in-to-upgrade as a marketing strategy in disassembly-to-order systems at the edge of blockchain technology
Abstract: 
 Growing environmental awareness and widening extended producer responsibility have heightened the need for economically, environmentally, and socially sustainable business strategies levered by digital technologies. As an extension, various take-back policies focusing on product waste and recovery are put in place by the high-tech manufacturing industry. With an attempt to increase sales while ensuring the environmental sustainability of products, trade-in programmes that incentivize consumers to exchange used goods for new and most recent technology products became a value-adding strategy for businesses. Due to the high unpredictability in the quality of returned devices however, determining trade-in margins is a challenging task for original equipment manufacturers (OEMs). This inevitably reveals the need for incorporating intelligent technologies into the formation of manufacturing and logistics architectures to simultaneously preserve OEMs profitability and ensure the sustainable development of the closed-loop supply chain activities. With this motivation, this study presents the use of IoT-embedded products in a blockchain-enabled disassembly-to-order system to determine the optimal trade-in-to-upgrade policy. A discrete-event simulation model is developed to obtain the expected cost of the disassembly-to-order system. Optimal incentives for varying product qualities are then computed by utilising this cost in the trade-in policy model.
Journal: International Journal of Production Research
Pages: 7183-7200
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1712489
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1712489
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Template-Type: ReDIF-Article 1.0
Author-Name: Sirish Kumar Gouda
Author-X-Name-First: Sirish Kumar
Author-X-Name-Last: Gouda
Author-Name: Haritha Saranga
Author-X-Name-First: Haritha
Author-X-Name-Last: Saranga
Title: Pressure or premium: what works best where? Antecedents and outcomes of sustainable manufacturing practices
Abstract: 
 In this study, we empirically test the antecedents and consequences of sustainable manufacturing practices across emerging as well as developed countries such as India, China and OECD. We use data from the sixth edition of International Manufacturing Strategy Survey (IMSS) and partial least squares structural equation modelling (PLS-SEM) to test our conjectures. Our findings suggest that while customer willingness to pay has a significant impact on sustainable manufacturing practices everywhere, stakeholder pressure is able to influence their adoption in OECD and India, but not in China. We also find that firms that are high on sustainable manufacturing practices not only reap sustainability benefits, but also derive cost reduction and quality improvement in many contexts. However, this relationship between sustainability efforts and operational performance is mediated through sustainability performance.
Journal: International Journal of Production Research
Pages: 7201-7217
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1717010
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1717010
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Template-Type: ReDIF-Article 1.0
Author-Name: Liangchuan Zhou
Author-X-Name-First: Liangchuan
Author-X-Name-Last: Zhou
Author-Name: Surendra M. Gupta
Author-X-Name-First: Surendra M.
Author-X-Name-Last: Gupta
Title: Value depreciation factors for new and remanufactured high-technology products: a case study on iPhones and iPads
Abstract: 
 Governmental regulations for expansion of e-waste and customers’ awareness of green goods drive remanufacturing practices in high-technology electronic products. Selling remanufactured high-technology products is a challenge because of the shorter residual life of usage and potential cannibalisation of new items. Smartphones and tablets, as hi-tech products, are replaced by new generation models quickly due to rapid development. Products belonging to earlier generations become less demanding. Customer’s acceptance for outmoded remanufactured items is even less. Learning how value depreciated is vital for the sellers to make a wise price decision for these new and remanufactured products belonging to various generations. This study leverages transaction data of iPhones and iPads from eBay, uses partial least square method to explore the factors that affect value depreciation rate and price differentiation between new and remanufactured products. Variables which are categorised as marketing elements, technology features, appearance design, and customer attention are hypothesised to be critical to value depreciation. The result differs in iPhones and iPads but shows some consistency that time since release, product thickness, camera resolution, and fans/hits ratio are highly correlated to the value depreciation rate. ApplePay slows down the rate for iPhones while cellular data function accelerates the rate for iPads.
Journal: International Journal of Production Research
Pages: 7218-7249
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1722327
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1722327
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Template-Type: ReDIF-Article 1.0
Author-Name: Zülal Diri Kenger
Author-X-Name-First: Zülal
Author-X-Name-Last: Diri Kenger
Author-Name: Çağrı Koç
Author-X-Name-First: Çağrı
Author-X-Name-Last: Koç
Author-Name: Eren Özceylan
Author-X-Name-First: Eren
Author-X-Name-Last: Özceylan
Title: Integrated disassembly line balancing and routing problem
Abstract: 
 This paper introduces the integrated disassembly line balancing and routing problem (I-DLB-RP). The I-DLB-RP simultaneously optimises two well-known problems. The former one balances the disassembly lines in the disassembly centres, whereas the latter one constructs a routing plan to distribute the usable components, generated by the disassembly process, from disassembly centre to the remanufacturing centres, i.e. customers. With the increasing importance of the disassembly process for tackling with the burden of waste and the number of disassembled products, the distribution planning of usable components released after the disassembly process becomes essential. This paper considers several scenarios: single-component distribution, multi-component distribution, inventory cost, and multi-period conditions. We propose five linear and non-linear mathematical models. Extensive computational experiments conducted on generated realistic benchmark instances. The analyses quantify the benefits of integrating the two problems.
Journal: International Journal of Production Research
Pages: 7250-7268
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1740346
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1740346
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Template-Type: ReDIF-Article 1.0
Author-Name: Ying Luo
Author-X-Name-First: Ying
Author-X-Name-Last: Luo
Author-Name: Xiaowen Jie
Author-X-Name-First: Xiaowen
Author-X-Name-Last: Jie
Author-Name: Xiaoping Li
Author-X-Name-First: Xiaoping
Author-X-Name-Last: Li
Title: The organic joint point of new kinetic energy and green development in Chinese manufacturing SMEs
Abstract: 
 Even though manufacturing industrialisation has significantly contributed to Chinese economic growth, it has also resulted in resource abuse and environmental pollution. Therefore, manufacturing enterprises need to pursue green development to obtain legitimacy. The successful implementation of green manufacturing requires the joint efforts by enterprises, society and government, as well as the support of technology. Only by putting limited resources into the elements that can drive manufacturing SMEs to implement green practices and obtain sustainable performance, can achieve the effectiveness of Pareto. To this end, this paper constructed a ‘new kinetic energy – green practices – sustainable performance’ evaluation model, which is verified by partial least squares structural equation modelling (PLS-SEM) and multi-group analysis (PLS-MGA). It was found that top manager commitment and consumer demand did not have a positive impact on enterprise green practices in all industry types. However, while technology was found to play a crucial role in technology-intensive industries, and employee engagement was only found to promote green behaviour in labour-intensive industries. Although new kinetic energies were observed to play different roles in the different industrial types, the results showed that green practices could result in economic, environmental, resource and social benefits in all industrial types.
Journal: International Journal of Production Research
Pages: 7269-7291
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1777341
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1777341
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Template-Type: ReDIF-Article 1.0
Author-Name: Maria Holgado
Author-X-Name-First: Maria
Author-X-Name-Last: Holgado
Author-Name: Marco Macchi
Author-X-Name-First: Marco
Author-X-Name-Last: Macchi
Author-Name: Stephen Evans
Author-X-Name-First: Stephen
Author-X-Name-Last: Evans
Title: Exploring the impacts and contributions of maintenance function for sustainable manufacturing
Abstract: 
 This investigation studies advanced practitioners of maintenance management and seeks to uncover the related impacts and contributions of best practice maintenance toward sustainable manufacturing operations. This exploratory research conducted a novel empirical analysis focused on maintenance functions in nine manufacturing companies from diverse sectors. The analysis uncovered insights related to the economic, environmental, and social benefits of deeper involvement of maintenance function in plant operations and decision-making. We observed links of maintenance function with product competitiveness and with energy management activities that were unexpected. We confirmed benefits from keeping machinery in good working conditions and restoring promptly good working conditions when an issue happens. The depth of maintenance contribution on each area identified in this study will depend on the operational and business context of the manufacturing company; thus, companies need to reflect on these based on their specific processes, business needs and goals. Ultimately, this work can inspire managers in manufacturing companies to organise maintenance functions strategically toward fostering long-term competitive, responsible and sustainable performance.
Journal: International Journal of Production Research
Pages: 7292-7310
Issue: 23
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1808257
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1808257
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Template-Type: ReDIF-Article 1.0
Author-Name: Mahsa Noori-daryan
Author-X-Name-First: Mahsa
Author-X-Name-Last: Noori-daryan
Author-Name: Ata Allah Taleizadeh
Author-X-Name-First: Ata Allah
Author-X-Name-Last: Taleizadeh
Author-Name: Masoud Rabbani
Author-X-Name-First: Masoud
Author-X-Name-Last: Rabbani
Title: Advance booking pricing in O2O commerce with demand leakage using game theory for tourism supply chains
Abstract: 
 In this research, the pricing and selling decisions of two supply chains are examined to maximise the profit of the chains considering an advance booking policy where the chains offer complementary items and customers able to buy products from both online and real stores (offline). The proposed model is developed without/with online-to-offline (O2O) retail marketing under the first and second scenarios, respectively. In addition, there is a possibility of demand leakage between the online and offline channels, thus customers can take advantage of the channel that would be most desirable for them. The behaviors of the partners are surveyed by different game-theoretic approaches under two scenarios to determine the optimal decisions and the optimal values of variables and the profits of the chains. Then, the closed form solutions are derived which are examined by a numerical example and sensitivity analyses are performed to analyse the efficiency of key parameters. It is found that employing O2O marketing mechanism causes more profit for chains due to enhancing the market demand. Also, advance booking policy leads to manage the market and attract the customers who follow the items at lower prices so that longer advance booking periods, more orders and higher profits.
Journal: International Journal of Production Research
Pages: 6739-6774
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685703
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685703
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Template-Type: ReDIF-Article 1.0
Author-Name: Man Yu
Author-X-Name-First: Man
Author-X-Name-Last: Yu
Author-Name: Erbao Cao
Author-X-Name-First: Erbao
Author-X-Name-Last: Cao
Title: Information sharing format and carbon emission abatement in a supply chain with competition
Abstract: 
 This paper aims to investigate the interaction between information management and operational management and a retailer’s ability of truthful information sharing, considering government environmental policies and public eco-friendly awareness. Under cap-and-trade regulation, we analyse different information sharing formats (no information sharing, partial information sharing, and public information sharing) among a supply chain comprised of one manufacturer, one incumbent retailer with private demand information, and an uninformed entrant retailer. The result shows that the incumbent retailer’s decision on information sharing format and the ability of truthful information are significantly affected by the manufacturer’s capability in abating carbon emissions and the demand uncertainty. In partial information sharing scenario, a babbling equilibrium dominates an informative equilibrium. In public information sharing scenario, the incumbent retailer is able to share truthful information under a sequential-move. Moreover, we examine the impacts of public information sharing on every member’s profit. The results show that public information sharing benefits the incumbent retailer when the demand uncertainty is relatively small. The manufacturer always benefit from public information sharing. Consequently, to obtain the benefits of information sharing, the manufacturer should make effort to improve carbon emission abatement capacity.
Journal: International Journal of Production Research
Pages: 6775-6790
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685704
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685704
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Template-Type: ReDIF-Article 1.0
Author-Name: Jinhe Wang
Author-X-Name-First: Jinhe
Author-X-Name-Last: Wang
Author-Name: Xiaohong Zhang
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Zhang
Author-Name: Jianchao Zeng
Author-X-Name-First: Jianchao
Author-X-Name-Last: Zeng
Author-Name: Yunzheng Zhang
Author-X-Name-First: Yunzheng
Author-X-Name-Last: Zhang
Title: Optimal dynamic imperfect preventive maintenance of wind turbines based on general renewal processes
Abstract: 
 With the rapid growth in wind turbine technology worldwide, the high operational and maintenance costs of wind turbines have posed a major challenge to wind power operating companies. Considering the high replacement cost, imperfect maintenance measures are employed widely once downtime failures occur. However, as the metric to describe the effect of imperfect maintenance is a non-intuitive variable, the evaluation results obtained from existing research do not conform with actual wind turbine situations. To address this issue, the virtual age factor and failure intensity update factor are expressed by intuitive variables to illustrate the imperfect maintenance effect. Additionally, we propose a failure rate function update model considering the above factors. To minimise maintenance costs while ensuring the availability of the wind turbine, we investigate a periodic dynamic imperfect preventive maintenance decision model based on the proposed failure rate function update model. We also provide a brief illustration of the accuracy and feasibility of the proposed model through optimal solution and sensitivity analyses. The results obtained from the case analysis and strategies comparison, based on actual wind turbine maintenance data, demonstrate the economic advantages of our approach.
Journal: International Journal of Production Research
Pages: 6791-6810
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685706
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685706
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Template-Type: ReDIF-Article 1.0
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Yang Sui
Author-X-Name-First: Yang
Author-X-Name-Last: Sui
Author-Name: E Zhang
Author-X-Name-First: E
Author-X-Name-Last: Zhang
Author-Name: Yinfeng Xu
Author-X-Name-First: Yinfeng
Author-X-Name-Last: Xu
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Title: Two parallel identical machines scheduling to minimise the maximum inter-completion time
Abstract: 
 In many manufacturing and service systems, it is of great importance to generate processing schedules with strong response abilities to unexpected or urgent jobs. In this paper, we investigate the problem of scheduling jobs on two parallel identical machines. The objective is to minimise the maximum difference between any two consecutive completion times of jobs, i.e. to minimise the maximum inter-completion time. The processing of any job cannot be interrupted, and a smaller objective value of the processing schedule implies a faster response to an unexpected job that may arrive at any time point. The problem was introduced by Zheng, Pinedo, Lee, Liu, and Xu [2019. “Towards Robustness of Response Times: Minimising the Maximum Inter-completion Time on Parallel Machines.” International Journal of Production Research 57 (1): 182–199]. In this work, we first give a sufficient condition of feasible solutions with respect to the makespan constraint, and reveal several basic properties of any optimal solution. We then prove a theoretical lower bound of the objective value, and propose a  $O(n^2) $O(n2) time algorithm to compute the lower bound. An efficient heuristic algorithm is further constructed to solve the considered problem. Experimental results show that the proposed algorithm outperforms all the three heuristics introduced in Zheng, Pinedo, Lee, Liu, and Xu 2019.
Journal: International Journal of Production Research
Pages: 6811-6825
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685707
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685707
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Template-Type: ReDIF-Article 1.0
Author-Name: Like Zhang
Author-X-Name-First: Like
Author-X-Name-Last: Zhang
Author-Name: Qianwang Deng
Author-X-Name-First: Qianwang
Author-X-Name-Last: Deng
Author-Name: Guiliang Gong
Author-X-Name-First: Guiliang
Author-X-Name-Last: Gong
Author-Name: Wenwu Han
Author-X-Name-First: Wenwu
Author-X-Name-Last: Han
Title: A new unrelated parallel machine scheduling problem with tool changes to minimise the total energy consumption
Abstract: 
 The previous studies on scheduling problem with tool changes take processing time as the only reason for the tool wear, which is not accurate in the real manufacturing system. This paper takes processing speed and processing time into consideration simultaneously and proposes a new unrelated parallel machine scheduling problem (UPMSP) with tool changes caused by the tool wear, in which the energy consumption rate of the parallel machines is influenced by two factors: tool changes and corresponding processing speed. A new effective heuristic evolutionary algorithm (NHEA) is presented to solve the proposed UPMSP with objectives of optimising total energy consumption and makespan. For the NHEA, some effective operators such as target-searching operators are designed to accelerate the search efficiency and further exploit the solution space. A first fit decreasing algorithm is presented and incorporated into the NHEA to reduce the number of tool changes. The Taguchi method of Design of Experiments is used to obtain the best combination of key parameters of the NHEA. Extensive computational experiments are carried out to compare the NHEA with some well-known algorithms. The results validate that the proposed NHEA is able to obtain better Pareto solutions for UPMSP with tool changes.
Journal: International Journal of Production Research
Pages: 6826-6845
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685708
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685708
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Template-Type: ReDIF-Article 1.0
Author-Name: Shaohui Xi
Author-X-Name-First: Shaohui
Author-X-Name-Last: Xi
Author-Name: Qingxin Chen
Author-X-Name-First: Qingxin
Author-X-Name-Last: Chen
Author-Name: James MacGregor Smith
Author-X-Name-First: James
Author-X-Name-Last: MacGregor Smith
Author-Name: Ning Mao
Author-X-Name-First: Ning
Author-X-Name-Last: Mao
Author-Name: Ailin Yu
Author-X-Name-First: Ailin
Author-X-Name-Last: Yu
Author-Name: Huiyu Zhang
Author-X-Name-First: Huiyu
Author-X-Name-Last: Zhang
Title: A new method for solving buffer allocation problem in large unbalanced production lines
Abstract: 
 Solving the buffer allocation problem (BAP) in long production lines is difficult because it is an NP-hard problem. In this paper, we propose a new approach to solve the BAP for long series-parallel unbalanced production lines with the objective of minimising the average work-in-process subject to a throughput rate constraint. Instead of directly optimising a long line, this method decomposes the original long line into several small decoupled subsystems and adds relation condition variables between the subsystems. After several iterations between subsystem optimisation and condition updating, this method can obtain the optimal or near-optimal solution of the original system with a significantly improved computational efficiency. Extensive numerical experiments demonstrate the accuracy and efficiency of this approach. Finally, several examples and a multi-factorial experimental analysis are provided to show the influence of the decomposition strategy, initial values, and parameters of the target systems on the performance of the proposed method.
Journal: International Journal of Production Research
Pages: 6846-6867
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685709
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685709
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:22:p:6846-6867




Template-Type: ReDIF-Article 1.0
Author-Name: Lei Guan
Author-X-Name-First: Lei
Author-X-Name-Last: Guan
Author-Name: Yongxue Mu
Author-X-Name-First: Yongxue
Author-X-Name-Last: Mu
Author-Name: Xiaolin Xu
Author-X-Name-First: Xiaolin
Author-X-Name-Last: Xu
Author-Name: Lianmin Zhang
Author-X-Name-First: Lianmin
Author-X-Name-Last: Zhang
Author-Name: Jun Zhuang
Author-X-Name-First: Jun
Author-X-Name-Last: Zhuang
Title: Keep it or give back? Optimal pricing strategy of reward-based crowdfunding with a hybrid mechanism in the sharing economy
Abstract: 
 Reward-based crowdfunding is a new fund-raising method in sharing economy, and it can also be a powerful tool for companies to handle the time mismatch between money invested and revenue generated in Circular Economy (CE). While all-or-nothing (AON) mechanism and keep-it-all (KIA) mechanism are both used in crowdfunding projects, some websites start using a new hybrid mechanism where the creator can keep a proportion of the funds raised even if the crowdfunding project fails. In this paper, we investigate this hybrid mechanism in reward-based crowdfunding projects. For a basic two-stage model, we find that AON can provide the creator with the largest expected revenue under different pricing policies when the valuation of investors is discrete. However, with continuous investors’ valuation, a hybrid mechanism is better for the creator, and the price in the first stage should be lower than the one in the second stage. For a three-stage model, we find that the results with continuous valuation still hold, and a hybrid mechanism will be the optimal mechanism under menu pricing with discrete valuation.
Journal: International Journal of Production Research
Pages: 6868-6889
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685711
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685711
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Template-Type: ReDIF-Article 1.0
Author-Name: Joo Y. Lee
Author-X-Name-First: Joo Y.
Author-X-Name-Last: Lee
Author-Name: Kwanwoo Lee
Author-X-Name-First: Kwanwoo
Author-X-Name-Last: Lee
Author-Name: Sangchul Park
Author-X-Name-First: Sangchul
Author-X-Name-Last: Park
Title: Virtual commissioning for an Overhead Hoist Transporter in a semiconductor FAB
Abstract: 
 Presented in the paper is a virtual commissioning methodology for the design and verification of an OHT (Overhead Hoist Transporter), which is a vehicle that travels on the overhead track in a FAB (Factory for making semiconductor chips), and directly accesses the load port of the stocker or process equipment by the belt driven hoisting mechanism. Since the material flows of a FAB is extremely complicated, it is important to design the OHT control software by considering various situations. The proposed virtual commissioning methodology supports the full verification of the OHT control software by performing the simulation involving a ‘virtual OHT model’ and a ‘real OHT controller’. We separate the virtual OHT model into two parts, a physical model (mechanical part) and a logical model (electrical part) to achieve the concurrency of mechanical and electrical designs of an OHT. Virtual commissioning identifies and addresses design flaws and operational faults so that significant savings can be achieved. The prototype of the proposed virtual commissioning methodology has been implemented and tested with several examples.
Journal: International Journal of Production Research
Pages: 6890-6898
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1685712
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1685712
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Template-Type: ReDIF-Article 1.0
Author-Name: Hao Guo
Author-X-Name-First: Hao
Author-X-Name-Last: Guo
Author-Name: Ying Zhang
Author-X-Name-First: Ying
Author-X-Name-Last: Zhang
Author-Name: Chunnan Zhang
Author-X-Name-First: Chunnan
Author-X-Name-Last: Zhang
Author-Name: Yidong Zhang
Author-X-Name-First: Yidong
Author-X-Name-Last: Zhang
Author-Name: Zixin Han
Author-X-Name-First: Zixin
Author-X-Name-Last: Han
Title: A multi-commodity location-inventory problem in a closed-loop supply chain with commercial product returns
Abstract: 
 Commercial product returns represent a growing financial and operational concern for many firms, and they consist of true and false failure returns in the real-world business. This paper studies a joint location-inventory problem in a closed-loop system by considering multi-commodity flows and commercial product returns. First, this problem is formulated as a mixed-integer nonlinear programming model. Next, a novel heuristic method based on differential evolution is designed to solve this model efficiently. Finally, numerical experiments and results are presented to validate the solution approach and provide meaningful managerial insights for business managers to improve their supply chain practice in a closed-loop system with false failure returns.
Journal: International Journal of Production Research
Pages: 6899-6916
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1686186
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1686186
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Template-Type: ReDIF-Article 1.0
Author-Name: Luiz J.P. Araújo
Author-X-Name-First: Luiz J.P.
Author-X-Name-Last: Araújo
Author-Name: Ajit Panesar
Author-X-Name-First: Ajit
Author-X-Name-Last: Panesar
Author-Name: Ender Özcan
Author-X-Name-First: Ender
Author-X-Name-Last: Özcan
Author-Name: Jason Atkin
Author-X-Name-First: Jason
Author-X-Name-Last: Atkin
Author-Name: Martin Baumers
Author-X-Name-First: Martin
Author-X-Name-Last: Baumers
Author-Name: Ian Ashcroft
Author-X-Name-First: Ian
Author-X-Name-Last: Ashcroft
Title: An experimental analysis of deepest bottom-left-fill packing methods for additive manufacturing
Abstract: 
 The adoption of Additive Manufacturing (AM) technology requires the efficient utilisation of the avail- able build volumes to minimise production times and costs. Three-dimensional algorithms, particularly the Deepest Bottom-Left-Fill (DBLF) heuristic, have been extensively used to tackle the problem of packing arbitrary 3D geometries within the AM sector. A particularly common method applied to more realistic packing problems is the combination of DBLF and metaheuristics such as Genetic Algorithms (GAs). Through a series of experiments, this paper experimentally investigates the practical aspects, and comparative performance of different DBLF based methods including a brute force algorithm and GA combined with DBLF for AM build volume packing. The insights into the relationship between algorithm efficiency (in terms of volume utilisation), simulation runtime, and practical requirements, in particular geometry rotation constraints are investigated. In addition to providing an increased comprehension of the practical aspects of applying DBLF algorithms in the AM context, this study confirms the limita- tions of traditional DBLF and the requirements for more flexible and intelligent placement strategies while experimentally demonstrating that higher degrees of freedom for part rotation contribute to small improvements in volume density. The resulting additional computational effort discourages this strategy, however.
Journal: International Journal of Production Research
Pages: 6917-6933
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1686187
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1686187
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuyan He
Author-X-Name-First: Yuyan
Author-X-Name-Last: He
Author-Name: Aihu Wang
Author-X-Name-First: Aihu
Author-X-Name-Last: Wang
Author-Name: Hailiang Su
Author-X-Name-First: Hailiang
Author-X-Name-Last: Su
Title: The impact of incomplete vessel arrival information on container stacking
Abstract: 
 Container stacking determines the incoming containers’ exact locations in a terminal storage yard which matters to the competitiveness of a port. The uncertain stacking or arrival sequence of containers caused by uncertain vessel arrival information brings some new challenges to container stacking. Based on the perspective of uncertainty, this article uses heuristic algorithms to evaluate the use of vessel arrival information to reduce the number of reshuffles, which differs from previous research mainly in the following three aspects: firstly, three different stacking principles i.e. the least reshuffle principle, lowest stack principle and nearest stack principle, are combined to create five new heuristics. Secondly, the incomplete information is divided into little, moderate and high levels and a variety of scenarios with different levels of vessel arrival information are generated to explore the effect of incomplete information on container stacking. Lastly, numerical experiments demonstrate that the results for complete information are presented to provide a lower bound reference. Moreover, the results obtained by different heuristics under different levels of vessel arrival information are closely related to factors like the bay scale, the bay utilisation rate and the number of containers.
Journal: International Journal of Production Research
Pages: 6934-6948
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1686188
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1686188
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Template-Type: ReDIF-Article 1.0
Author-Name: David Revillot-Narváez
Author-X-Name-First: David
Author-X-Name-Last: Revillot-Narváez
Author-Name: Francisco Pérez-Galarce
Author-X-Name-First: Francisco
Author-X-Name-Last: Pérez-Galarce
Author-Name: Eduardo Álvarez-Miranda
Author-X-Name-First: Eduardo
Author-X-Name-Last: Álvarez-Miranda
Title: Optimising the storage assignment and order-picking for the compact drive-in storage system
Abstract: 
 One of the most common systems in non-automated warehouses, is drive-in pallet racking with a shared storage policy (which is usually based on the duration-of-stay). Such scheme targets towards an efficient use of storage space, since its operation costs are directly related to the size and layout of the warehouse. In this paper, two mathematical programming models and two greedy-randomised based heuristics for finding (nearly) optimal storage and retrieval operation sequences for this type of storage system are proposed. The computational effectiveness of the proposed approaches is measured by considering two sets of synthetic instances. The obtained results show that the proposed heuristics are not only able to compute high-quality solutions (as observed when being compared with the optimal solutions attained by the mathematical programming models), but it is also capable of providing solutions in very short running times even for large instances for which the mathematical programming model failed to find feasible solutions. At the light of these results, the best heuristic is also tested using a rolling-horizon planning strategy in a real-world case study, obtained from a Chilean company. It turns out that the attained results are more effective than the company's current storage policy.
Journal: International Journal of Production Research
Pages: 6949-6969
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1687951
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1687951
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Template-Type: ReDIF-Article 1.0
Author-Name: Ji Li
Author-X-Name-First: Ji
Author-X-Name-Last: Li
Author-Name: Anjun Xu
Author-X-Name-First: Anjun
Author-X-Name-Last: Xu
Author-Name: Xuesong Zang
Author-X-Name-First: Xuesong
Author-X-Name-Last: Zang
Title: Simulation-based solution for a dynamic multi-crane-scheduling problem in a steelmaking shop
Abstract: 
 Here, we present a simulation-based solution for a multi-crane-scheduling problem derived from a steelmaking shop. This problem features non-conflict constraint between cranes, station-capacity constraint, and jobs with inaccurate release times and different temporal scheduling objectives. The predictive–reactive rescheduling strategy was applied to solve the problem. The problem was modelled considering different temporal objectives for the jobs and workload objective for the cranes and the model was solved by a heuristic. In the simulation, the jobs were not directly given but generated by a job-prediction method. The cranes’ moving behaviours were controlled by a designed crane trajectory solution. Experimental tests were conducted using data from the site and the results show that the proposed crane-scheduling solution provided better scheduling results than both the exhaustive method and the method that is used in the production field. The best predictive spans for the jobs in this specific crane-scheduling problem were found to be 7–14 min. The real-time performance of the crane-scheduling solution is demonstrated to highly guarantee its practicability.
Journal: International Journal of Production Research
Pages: 6970-6984
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1687952
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1687952
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiao-shuai Peng
Author-X-Name-First: Xiao-shuai
Author-X-Name-Last: Peng
Author-Name: Shou-feng Ji
Author-X-Name-First: Shou-feng
Author-X-Name-Last: Ji
Author-Name: Ting-ting Ji
Author-X-Name-First: Ting-ting
Author-X-Name-Last: Ji
Title: Promoting sustainability of the integrated production-inventory-distribution system through the Physical Internet
Abstract: 
 Owing to its interconnections and open characteristics, Physical Internet (PI) has the potential to help companies meet the sustainability challenges. In this paper, to investigate the sustainability performance of the PI in an integrated production-inventory-distribution system, we propose a multi-objective mixed integer linear programming model (MOMILP) that encompasses all three dimensions of sustainability. The economic and environmental objectives are measured through the total cost and greenhouse gas (GHG) emissions, respectively. The social objective is captured by the impact of accident risk. Then, we solve the model by using the augmented ϵ-constraint method and compare the sustainability performance of the PI-enabled model with that of models enabled by the traditional (TR) and horizontal collaboration (HC) networks. The results show that the PI can not only improve the economic and environmental performance by increasing vehicle utilisation, but also alleviate the impacts of accident risks by avoiding risky routes. More interestingly, good compromise solutions featuring the PI can further improve the sustainability performance while guaranteeing the performance of the TR at the ideal point—something unachievable for the HC and TR. Moreover, sensitivity analyses demonstrate that the PI can still guarantee significant sustainability performance advantages under different common retailer quantities and network structures.
Journal: International Journal of Production Research
Pages: 6985-7004
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1687953
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1687953
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiguang Chen
Author-X-Name-First: Jiguang
Author-X-Name-Last: Chen
Author-Name: He Xu
Author-X-Name-First: He
Author-X-Name-Last: Xu
Author-Name: Pin Zhou
Author-X-Name-First: Pin
Author-X-Name-Last: Zhou
Title: Delegation vs. direct sourcing revisited: contract types under correlated supply risks and asymmetric cost information
Abstract: 
 As a popular practice in purchasing, an ever-increasing number of upper-tier suppliers are being added in the supply base of the original equipment manufacturer (OEM) and leveraged to reduce supply risk. This new trend increases the OEM's opportunities to directly source from tier-2 suppliers (direct sourcing for better control) in addition to delegating tier-1 suppliers to source on behalf of the OEM itself (delegation). This paper is devoted to comparing these two mechanisms (delegation vs. direct souring) under both asymmetric information on the production costs of tier-2 suppliers and correlated supply disruptions with tier-2 suppliers. When the OEM offers a revenue-sharing term contract or a base-commitment term contract (in which the OEM is required to procure a fixed base quantity in addition to an option of procuring additional units at a pre-specified price) to a tier-1 supplier under delegation, delegation achieves the same profit for the OEM as direct sourcing does. However, under a fixed-quantity term contract, delegation achieves a lower profit for the OEM than direct sourcing does, no matter the CM is subject to the procurement budget constraint or deep pocket. Moreover, we find delegation may lead to a higher profit for the OEM than direct sourcing does if an improved fixed-quantity term contract is used under delegation with a deep-pocket CM.
Journal: International Journal of Production Research
Pages: 7005-7022
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1689307
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1689307
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Template-Type: ReDIF-Article 1.0
Author-Name: Michel Stella Ravelomanantsoa
Author-X-Name-First: Michel Stella
Author-X-Name-Last: Ravelomanantsoa
Author-Name: Yves Ducq
Author-X-Name-First: Yves
Author-X-Name-Last: Ducq
Author-Name: Bruno Vallespir
Author-X-Name-First: Bruno
Author-X-Name-Last: Vallespir
Title: General enterprise performance measurement architecture
Abstract: 
 Enterprise performance has been investigated since the 1900s, leading to many approaches, methods, and frameworks around the world, developed either by researchers or by practitioners and consultants. The purpose of these approaches is the design and the implementation of performance indicators and performance measurement systems (PMSs). More than 65 approaches have been identified and several studies conducted to compare them. They concluded that each approach, even the most famous ones, can be improved based on the qualities of others. The objective of this paper is to propose a generic architecture for combining the ingredients of individual approaches and methods in a coherent way. This architecture must be generic enough to be widely applicable to all types of approaches and, more generally, to all types of application domains. The first objective of this reference architecture is to propose a synergy and consolidation of the best features of each approach into the best possible system. The second objective is to organise the development and use of the PMS methodologies and tools needed by potential users to integrate a PMS into their own enterprise.
Journal: International Journal of Production Research
Pages: 7023-7043
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1692158
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1692158
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:22:p:7023-7043




Template-Type: ReDIF-Article 1.0
Author-Name: Qingfeng Meng
Author-X-Name-First: Qingfeng
Author-X-Name-Last: Meng
Author-Name: Leilei Chu
Author-X-Name-First: Leilei
Author-X-Name-Last: Chu
Author-Name: Zhen Li
Author-X-Name-First: Zhen
Author-X-Name-Last: Li
Author-Name: Jingxian Chen
Author-X-Name-First: Jingxian
Author-X-Name-Last: Chen
Author-Name: Jianguo Du
Author-X-Name-First: Jianguo
Author-X-Name-Last: Du
Author-Name: Changzhi Wu
Author-X-Name-First: Changzhi
Author-X-Name-Last: Wu
Title: Cooperation performance of multi-organisations operating in a sharing economy: game theory with agent-based modelling
Abstract: 
 Sustainable development within a sharing economy requires close cooperation between participating organisations, while a more complicated management problem involves how to improve the cooperation performance between such organisations. This paper researches multi-organisational cooperation under a shared economy model to analyse the impact of the organisation’s revenue distribution plan, the organisational members’ characteristic abilities and other factors on the cooperation performance among organisations and core enterprises’ profit performance. It aims to provide a theoretical basis for core enterprises to rationally formulate revenue distribution strategy and the promotion of sustainable development of the shared economy. The research results reveal that under the shared economy model, the core enterprise’s revenue-distribution method based on fixed revenue and revenue-sharing can improve cooperation performance among organisational members to some extent. Moreover, the barriers and obstacles in organisations’ cooperation process are small, which will positively increase system profits, core enterprise profit and the proportion of core enterprise profits, but does not necessarily improve system profit margins. The core enterprise should control the cooperation costs between organisations through different incentive strategies to achieve better system profits and system profit margins.
Journal: International Journal of Production Research
Pages: 7044-7057
Issue: 22
Volume: 58
Year: 2020
Month: 11
X-DOI: 10.1080/00207543.2019.1693650
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693650
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Handle: RePEc:taf:tprsxx:v:58:y:2020:i:22:p:7044-7057




Template-Type: ReDIF-Article 1.0
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Title: Special issue on sustainability with innovation for manufacturing and supply chain management
Journal: International Journal of Production Research
Pages: 7311-7313
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1813466
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1813466
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Template-Type: ReDIF-Article 1.0
Author-Name: Violetta Giada Cannas
Author-X-Name-First: Violetta Giada
Author-X-Name-Last: Cannas
Author-Name: Federica Ciccullo
Author-X-Name-First: Federica
Author-X-Name-Last: Ciccullo
Author-Name: Margherita Pero
Author-X-Name-First: Margherita
Author-X-Name-Last: Pero
Author-Name: Roberto Cigolini
Author-X-Name-First: Roberto
Author-X-Name-Last: Cigolini
Title: Sustainable innovation in the dairy supply chain: enabling factors for intermodal transportation
Abstract: 
 There is a need for the dairy supply chain to improve its environmental performance. Intermodal rail-road transportation can be a way to reduce CO2 emissions. However, despite technological innovations in the realm of cooling technology, which could enable a shift to intermodal transportation, the use of intermodal rail-road in the dairy supply chain is still low. A blueprint is needed to foster the application of intermodal transportation in the sector. Literature provides little guidance in this sense. Therefore, this paper investigates how to ease the shift to intermodal rail-road transportation in the dairy supply chain through multiple case studies, performed at different stages of the supply chain. A set of enablers of the shift is discussed, along with a blueprint for innovative technology, and logistics and business models. The plan takes into account all the actors of the dairy industry, as well as other players, i.e. technology providers, academia and institutions. This paper enriches literature, thanks to its multi-stage research, providing managers with a practical tool to support the shift to intermodal transportation in the dairy industry. The main limitations lay in the choice of the sample, i.e. only Italian companies and no small retailers and farmers have been involved.
Journal: International Journal of Production Research
Pages: 7314-7333
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1809731
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1809731
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Template-Type: ReDIF-Article 1.0
Author-Name: Ananna Paul
Author-X-Name-First: Ananna
Author-X-Name-Last: Paul
Author-Name: Md. Abdul Moktadir
Author-X-Name-First: Md. Abdul
Author-X-Name-Last: Moktadir
Author-Name: Sanjoy Kumar Paul
Author-X-Name-First: Sanjoy Kumar
Author-X-Name-Last: Paul
Title: An innovative decision-making framework for evaluating transportation service providers based on sustainable criteria
Abstract: 
 Evaluating transportation service providers is an applied and multi-criteria decision-making problem. To ensure supply chain sustainability, it is important to consider all sustainable criteria for assessing and evaluating transport service providers. This paper aims to develop a new decision-making framework to evaluate transport service providers considering sustainable criteria from economic, environmental, social and operational aspects. The decision-making framework integrates both qualitative expert opinion and quantitative best-worst method (BWM) and VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method. The developed framework contributes to the academic literature by expanding the knowledge in supply chain sustainability by considering all possible sustainable criteria and integrating both qualitative and quantitative methods for evaluating transport service providers. This study also contributes to practice by developing a decision support tool, by which decision-makers can make an accurate, systematic and prompt decision to identify and assess sustainable criteria and to evaluate the priority of different transport service providers.
Journal: International Journal of Production Research
Pages: 7334-7352
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2019.1652779
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1652779
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Template-Type: ReDIF-Article 1.0
Author-Name: Fatemeh Sabouhi
Author-X-Name-First: Fatemeh
Author-X-Name-Last: Sabouhi
Author-Name: Mohammad Saeed Jabalameli
Author-X-Name-First: Mohammad Saeed
Author-X-Name-Last: Jabalameli
Author-Name: Armin Jabbarzadeh
Author-X-Name-First: Armin
Author-X-Name-Last: Jabbarzadeh
Author-Name: Behnam Fahimnia
Author-X-Name-First: Behnam
Author-X-Name-Last: Fahimnia
Title: A multi-cut L-shaped method for resilient and responsive supply chain network design
Abstract: 
 We present a stochastic optimisation model that can be used to design a resilient supply chain operating under random disruptions. The model aims to determine sourcing and network design decisions that minimise the expected total cost while ensuring that the minimum customer service level is achieved. The proposed model incorporates several resilience strategies including multiple sourcing, multiple transport routes, considering backup suppliers, adding extra production capacities, as well as lateral transshipment and direct shipment. A multi-cut L-shaped solution approach is developed to solve the proposed model. Data from a real case problem in the paint industry is utilised to test the model and solution approach. Important managerial insights are obtained from the case study. Our analyses focus on (1) exploring the relationship between supply chain cost and customer service level, (2) examining the impacts of different types of disruptions on the total cost, (3) evaluating the utility of resilience strategies, (4) investigating the benefits of the proposed solution approach to solve problems of different sizes and (5) benchmarking the performance of the proposed stochastic programming approach.
Journal: International Journal of Production Research
Pages: 7353-7381
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1779369
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1779369
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Template-Type: ReDIF-Article 1.0
Author-Name: Mariam Lafkihi
Author-X-Name-First: Mariam
Author-X-Name-Last: Lafkihi
Author-Name: Shenle Pan
Author-X-Name-First: Shenle
Author-X-Name-Last: Pan
Author-Name: Eric Ballot
Author-X-Name-First: Eric
Author-X-Name-Last: Ballot
Title: Rule-based incentive mechanism design for a decentralised collaborative transport network
Abstract: 
 This paper considers an incentive mechanism coupled with a set of collaborative rules in a decentralised collaborative transport network (CTN), taking the Physical Internet as an example. The goal of the proposed mechanism is to increase the efficiency, effectiveness, and sustainability of the network without decreasing the individual profit of the independent carriers. A multi-agent simulation model was developed to evaluate the performance of the proposed mechanism and rules and to analyse the impacts on the overall performance of the decentralised CTN. Moreover, two significant factors were identified and studied: network and market characteristics (e.g. demand to supply ratio), and competition between carriers. A baseline scenario with no collaboration was also simulated for comparison. The results indicate that collaborative rules are advantageous for all market types regardless of the competition in the network. This paper is among the first to investigate collaborative mechanisms and rules for decentralised CTN, especially with regard to sustainability issues. It also provides an effective methodology for designing mechanisms and rules in decentralised CTN, as well as for assessing performance.
Journal: International Journal of Production Research
Pages: 7382-7398
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2019.1693658
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693658
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhi Li
Author-X-Name-First: Zhi
Author-X-Name-Last: Li
Author-Name: Hanyang Guo
Author-X-Name-First: Hanyang
Author-X-Name-Last: Guo
Author-Name: Ali Vatankhah Barenji
Author-X-Name-First: Ali Vatankhah
Author-X-Name-Last: Barenji
Author-Name: W. M. Wang
Author-X-Name-First: W. M.
Author-X-Name-Last: Wang
Author-Name: Yijiang Guan
Author-X-Name-First: Yijiang
Author-X-Name-Last: Guan
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: A sustainable production capability evaluation mechanism based on blockchain, LSTM, analytic hierarchy process for supply chain network
Abstract: 
 Due to the rapid development of information technology, supply chain network is evolving, which involves a higher level of interdependence between organisations. Conventional production capability evaluation relies on centralised approaches with limited sharing of performance and evaluation data. Besides, traditional evaluation methods are mainly based on subjective manual operation using limited data. In this paper, we propose a production capability evaluation system by incorporating Internet of Things (IoT), machine learning and blockchain technology for supply chain network. It contributes to achieving real-time data collection and automated enterprise production capability evaluation mechanism. Besides, blockchain technology is adopted to enable open and decentralised data storage and sharing, provide fair and automatic trading of data. The proposed system is evaluated through a simulation experiment. It demonstrated how to utilise the proposed system to choose suitable upstream enterprises. The successful development of the system could help to enhance production efficiency, reduce risk and provide a reasonable and more sustainable production management in supply chain network.
Journal: International Journal of Production Research
Pages: 7399-7419
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1740342
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1740342
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianming Yao
Author-X-Name-First: Jianming
Author-X-Name-Last: Yao
Author-Name: Heyun Shi
Author-X-Name-First: Heyun
Author-X-Name-Last: Shi
Author-Name: Chang Liu
Author-X-Name-First: Chang
Author-X-Name-Last: Liu
Title: Optimising the configuration of green supply chains under mass personalisation
Abstract: 
 To achieve sustainable development, manufacturing firms should consider both environmental protection and customers’ growing personalised demands in supply chain management. Although research on sustainable manufacturing with focus on green supply chain management is increasing, only a few studies have emphasised the significance of mass personalisation. This study proposes a novel supply chain configuration approach that effectively combines the two aspects. A fuzzy analytic hierarchy process evaluation method is developed to rank suppliers into different green levels. Based on this, a supply chain scheduling optimisation model is established to match supply with demand. Simulation results show that the optimal solution for a scheduling scheme can not only satisfy customers’ personalised requirements on products, services functions, and completion time, but also improve the green management performance of the entire supply chain by selecting suppliers with high green levels and enabling them to achieve economies of scale, thereby verifying the reliability and validity of the model. The corresponding algorithm also shows good calculation efficiency. This study contributes to the research on sustainable manufacturing by integrating firms’ demands on green supply chain management and customers’ demands on personalisation into one research framework and provides an effective decision-making tool for managers.
Journal: International Journal of Production Research
Pages: 7420-7438
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1723814
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1723814
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Template-Type: ReDIF-Article 1.0
Author-Name: Mostafa Parsa
Author-X-Name-First: Mostafa
Author-X-Name-Last: Parsa
Author-Name: Ali Shahandeh Nookabadi
Author-X-Name-First: Ali Shahandeh
Author-X-Name-Last: Nookabadi
Author-Name: Zümbül Atan
Author-X-Name-First: Zümbül
Author-X-Name-Last: Atan
Title: A joint economic lot-size model for sustainable industries of recycled content products
Abstract: 
 Coupling forward and reverse operations in closed-loop supply chains (CLSCs) can lead to a higher degree of sustainability. Previous studies on CLSCs have focused on the products that are either purely remanufactured or purely new. The emphasis on recycling necessitates research that considers recycled content products, which are made from a mix of virgin and recycled material. We study a CLSC consisting of a manufacturer, a retailer, a supplier, a material recovery facility (MRF) and a recycling facility. The supplier and the recycling facility provide the virgin and recycled raw materials, respectively, to the manufacturer who mixes them based on a predefined proportion known as the recycled content level to produce the ﬁnished products for the retailer. The recycling facility recovers the manufacturer’s production waste as well as the used products collected by the MRF. We aim at maximising the chain-wide profit by optimising the shipments among the supply chain parties. We propose a Branch-and-Bound algorithm to obtain the optimal solution, and a heuristic procedure, which provides the optimal solution in 96% of all tested instances. In addition, we prove the optimality of a bang-bang policy for the recycled content level in most cases.
Journal: International Journal of Production Research
Pages: 7439-7470
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1802078
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1802078
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuyan Wang
Author-X-Name-First: Yuyan
Author-X-Name-Last: Wang
Author-Name: Runjie Fan
Author-X-Name-First: Runjie
Author-X-Name-Last: Fan
Author-Name: Liang Shen
Author-X-Name-First: Liang
Author-X-Name-Last: Shen
Author-Name: Mingzhou Jin
Author-X-Name-First: Mingzhou
Author-X-Name-Last: Jin
Title: Decisions and coordination of green e-commerce supply chain considering green manufacturer's fairness concerns
Abstract: 
 With the rapid development of the cyber economy and green consumption demand, more and more consumers choose to purchase green products through e-commerce platforms. Considering the product green degree and the e-commerce platform's service, the paper studies the decisions and coordination of green e-commerce supply chain under green manufactures’ fairness concerns. The centralised model and the decentralised models with and without fairness concern are constructed and analysed with consideration of product green degree and service level. Then, the ‘cost-sharing joint commission’ contract is proposed to realise system coordination. Finally, propositions and conclusions are verified by numerical simulation. The results indicate that unlike traditional offline and dual-channel supply chains, the manufacturer's behaviour in response to fairness concerns can result in the decline both in product green degree and system efficiency but has no impact on service level. Under the centralised model, the product green degree is not the highest but is more affected by consumers’ green preferences. In addition, the product price and the service level will reach the highest under the centralised model. The increase in green technology investments can downsize the feasible interval of the contract, and the consumers’ green preferences can extend the feasible interval.
Journal: International Journal of Production Research
Pages: 7471-7489
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1765040
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1765040
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhiheng Zhao
Author-X-Name-First: Zhiheng
Author-X-Name-Last: Zhao
Author-Name: Mengdi Zhang
Author-X-Name-First: Mengdi
Author-X-Name-Last: Zhang
Author-Name: Gangyan Xu
Author-X-Name-First: Gangyan
Author-X-Name-Last: Xu
Author-Name: Dengyin Zhang
Author-X-Name-First: Dengyin
Author-X-Name-Last: Zhang
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Logistics sustainability practices: an IoT-enabled smart indoor parking system for industrial hazardous chemical vehicles
Abstract: 
 Logistics sustainability practices in industrial cases gain more attention recently especially when transportation efficiency becomes a bottleneck. The research of smart parking develops rapidly especially the thriving of Internet of Things (IoT). In this research, the industrial hazardous chemical vehicle (IHCV) consists of tractor and trailer. The vehicle coupling and decoupling occur frequently in order to fulfil logistics missions. The real-time dynamic indoor location information of both tractors and trailers are of great significance among users. Excessive time and human effort consumed in locating the vehicles lead to the transportation delay and disorderly parking exacerbate congestion inside the indoor parking garage. In this paper, we propose an IoT-enabled smart indoor parking system for logistics vehicles. A self-learning genetic tracking algorithm is developed to ensure the tracking performance. The feasibility and effectiveness of this solution architecture and algorithm are verified in a real-life chemical logistics company. The results show that the proposed algorithm not only performs constant improving location accuracy up to 96.7% after learning but also ensure the long-term use compared to the triangulation method. Moreover, disorderly parking can be identified by location cell partition as to eliminate potential risks. Improved logistics efficiency and lowered congestion situation contribute to the sustainable logistics.
Journal: International Journal of Production Research
Pages: 7490-7506
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1720928
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1720928
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Template-Type: ReDIF-Article 1.0
Author-Name: Binshuo Bao
Author-X-Name-First: Binshuo
Author-X-Name-Last: Bao
Author-Name: Junhai Ma
Author-X-Name-First: Junhai
Author-X-Name-Last: Ma
Author-Name: Mark Goh
Author-X-Name-First: Mark
Author-X-Name-Last: Goh
Title: Short- and long-term repeated game behaviours of two parallel supply chains based on government subsidy in the vehicle market
Abstract: 
 In response to environmental protection policies issued by the United Nations Environment Program, battery electric vehicles (BEVs) have been developed. This paper studies the short- and long-term repeated game behaviours of two parallel supply chains involving duopoly vehicle manufacturers producing BEVs and fuel vehicles (FVs). Taking consumers’ low-carbon preference and government subsidy scheme into account, optimal decisions and comparative analyses under the three game strategies of non-cooperative game and cooperative game and cost-sharing contract under supply chain coordination have been conducted. In the short-term game supply chain, three game models (non-cooperative, cooperative and cost-sharing contract) are formulated and three optimal decisions are compared. In the long-term repeated game supply chain, the dynamic behaviours of two parallel supply chains under non-cooperative game are analysed. We uncovered that the prices of BEVs are more dependent on the reduction of carbon emissions and government subsidy than FVs. In addition to supply chain coordination, consumers’ low-carbon preference also improves the total profits of the three game models. Furthermore, the adjustment speed of the eco-friendly level of BEVs has the most significant impact on the vehicle market.
Journal: International Journal of Production Research
Pages: 7507-7530
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1711988
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1711988
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Template-Type: ReDIF-Article 1.0
Author-Name: Tzu-Yen Hong
Author-X-Name-First: Tzu-Yen
Author-X-Name-Last: Hong
Author-Name: Chen-Fu Chien
Author-X-Name-First: Chen-Fu
Author-X-Name-Last: Chien
Title: A simulation-based dynamic scheduling and dispatching system with multi-criteria performance evaluation for Industry 3.5 and an empirical study for sustainable TFT-LCD array manufacturing
Abstract: 
 As the existing manufacturing systems may not be ready to support flexible decisions for smart production with increasing product mix and shortening product life cycle, it is crucial to rapidly respond to dynamic needs to improve bottleneck productivity and ensure the throughput of the whole manufacturing system. Limitations of the existing approaches can be traced in part to the lack of a framework within which different decisions in real settings can be integrated and aligned in light of the changes of manufacturing contexts. To fill the gaps, this study aims to develop a dynamic scheduling and dispatching system with the constructed discrete event simulation model to optimise the scheduling for bottleneck and associated dispatching rules for remaining processes, while considering the manufacturing system as a whole to empower smart manufacturing and reduce waste for sustainable production. A hybrid genetic algorithm is developed to minimise photolithography capacity loss, while considering the waiting time constraints and determining the optimal dispatching rules for non-bottleneck workstations by the design of experiments and multi-criteria decision analysis to integrate related decisions for the manufacturing system as a whole. An empirical study was conducted for validation. The results have shown its practical viability.
Journal: International Journal of Production Research
Pages: 7531-7547
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1777342
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1777342
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Template-Type: ReDIF-Article 1.0
Author-Name: Hongfei Guo
Author-X-Name-First: Hongfei
Author-X-Name-Last: Guo
Author-Name: Ru Zhang
Author-X-Name-First: Ru
Author-X-Name-Last: Zhang
Author-Name: Yingxin Zhu
Author-X-Name-First: Yingxin
Author-X-Name-Last: Zhu
Author-Name: Ting Qu
Author-X-Name-First: Ting
Author-X-Name-Last: Qu
Author-Name: Min Zou
Author-X-Name-First: Min
Author-X-Name-Last: Zou
Author-Name: Xiangyue Chen
Author-X-Name-First: Xiangyue
Author-X-Name-Last: Chen
Author-Name: Yaping Ren
Author-X-Name-First: Yaping
Author-X-Name-Last: Ren
Author-Name: Zhihui He
Author-X-Name-First: Zhihui
Author-X-Name-Last: He
Title: Sustainable quality control mechanism of heavy truck production process for Plant-wide production process
Abstract: 
 To overcome disability and default in process quality control and failure of traditional quality management in job shop manufacturing and customised orders, which are important issues in lean production, we investigate a sustainable quality control of plant-wide production process. In this paper, we construct the mechanisms consisting of pre-production quality prevention, quality control of production process and post-production feedback, using modified turtle diagram and VDA-based evaluation model. After the application of the mechanism in a large heavy truck enterprise in Chine for three years, the average benefit of the enterprise reached 36.58 million yuan, the gross loss of the single after-sales service decreased by 37.4%, and the net loss decreased by 21.1%, which indicates improvement of capacity of sustainable development. Case above in our paper shows that the mechanism we put forward is effective and practical for continuous improvement of quality management and sustainable development of enterprises. Besides, it provides a further supplement to existing lean production theory.
Journal: International Journal of Production Research
Pages: 7548-7564
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1844918
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1844918
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohit Goswami
Author-X-Name-First: Mohit
Author-X-Name-Last: Goswami
Author-Name: Arijit De
Author-X-Name-First: Arijit
Author-X-Name-Last: De
Author-Name: Muhammad Khoirul Khakim Habibi
Author-X-Name-First: Muhammad Khoirul Khakim
Author-X-Name-Last: Habibi
Author-Name: Yash Daultani
Author-X-Name-First: Yash
Author-X-Name-Last: Daultani
Title: Examining freight performance of third-party logistics providers within the automotive industry in India: an environmental sustainability perspective
Abstract: 
 The purpose of this study is to examine relationships between measures of sustainable freight transport performance (in the context of mid-sized third-party auto components’ logistics players) with the associated externalities and firms’ intrinsic characteristics when information exchange occurs between logistics firms and the auto manufacturer. Employing a survey-based research methodology, appropriate data were collected for a number of third-party logistics players, thus yielding a total of 708 responses from the operational managers of these firms. The research construct was validated through a rigorous procedure involving measurement and structural equation model. From a theoretical perspective, the results of this study provide evidences supporting systemic relationships between internal enablers of the logistics firms and externalities in the backdrop of environmental sustainability. Major findings indicate that transportation planning and distribution network and, commodity considerations backed by top management support can further environmental performance. Further, we also find evidence that effective transport planning and distribution network design used in conjunction with commodity considerations can be a source of sustainable supply chain performance. By bridging the literature pertaining to environmental sustainability, information exchange, and pertinent external/internal nuances of logistics firms, this study reveals novel findings that can help logistics players streamline operations focused at achieving environmental sustainability performance.
Journal: International Journal of Production Research
Pages: 7565-7592
Issue: 24
Volume: 58
Year: 2020
Month: 12
X-DOI: 10.1080/00207543.2020.1756504
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1756504
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Template-Type: ReDIF-Article 1.0
Author-Name: Yu Wang
Author-X-Name-First: Yu
Author-X-Name-Last: Wang
Author-Name: Jiacong Wu
Author-X-Name-First: Jiacong
Author-X-Name-Last: Wu
Author-Name: Li Lin
Author-X-Name-First: Li
Author-X-Name-Last: Lin
Author-Name: Sara Shafiee
Author-X-Name-First: Sara
Author-X-Name-Last: Shafiee
Title: An online community-based dynamic customisation model: the trade-off between customer satisfaction and enterprise profit
Abstract: 
 In recent years, the challenges of mass customisation (MC) have been increasing sales conversion rate and effectively matching supply with demand. Additionally, online customer communities (OCCs) have become increasingly popular and have proven to provide substantial value to both customers and enterprises. Therefore, the focus of this paper is to (1) propose a mathematical online community-based dynamic customisation model, (2) explain its practical mechanism and (3) solve its dynamic trade-off challenge. Accordingly, first, the trade-off challenge was formulated according to a multi-objective optimisation model to optimise the trade-off between customer satisfaction and enterprise profit. Second, based on the mechanism of the model, three different matching modes of production between customised products and manufacturers were delineated and analysed. Finally, genetic algorithm (GA) was developed to solve the proposed mathematical model. To validate the proposed model, a case study of an enterprise that provides customised menswear was selected. The degree of customisation and the weights given to the functions of enterprise profit and customer satisfaction were further analysed. The proposed model assists researchers and practitioners to decide the cooperation mode with manufacturers, pricing strategy and the degree of customisation for an optimal trade-off in the context of online community-based dynamic customisation.
Journal: International Journal of Production Research
Pages: 1-29
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1693649
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693649
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Template-Type: ReDIF-Article 1.0
Author-Name: Fábio Francisco da Costa Fontes
Author-X-Name-First: Fábio Francisco da Costa
Author-X-Name-Last: Fontes
Author-Name: Gilles Goncalves
Author-X-Name-First: Gilles
Author-X-Name-Last: Goncalves
Title: A variable neighbourhood decomposition search approach applied to a global liner shipping network using a hub-and-spoke with sub-hub structure
Abstract: 
 This paper presents a new concept for a hub-and-spoke network structure, called “sub-hub”, applied to global operations of liner shipping. Hub-and-spoke networks are widely used in transportation due to the economy of scale offered to the demands between hubs. However, efficient network structures require more than an economy of scale with regard to transport costs. This study therefore, aims to demonstrate that lower transport costs are achievable by a hub-and-spoke with sub-hub structure because the economy of scale this model provides is combined with shorter alternative paths. A short sea operation in liner shipping is a circular route at cluster level (the hub and its allocated spokes). A deep sea operation functions as a direct connection between hubs. A sub-hub is an intersection point between two regional (cluster) routes, thereby allowing the transshipment of goods, for certain demands, without using hub nodes. Hubs and sub-hubs are selected between the existing ports (nodes), and installation costs are not included for these models. A cutting plane approach was implemented. Although the computation results of the models, which are classified as hub location-routing problems, were compared on small instances, a Variable Neighbourhood Decomposition Search (VNDS) was implemented to test large instances.
Journal: International Journal of Production Research
Pages: 30-46
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1693652
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1693652
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Template-Type: ReDIF-Article 1.0
Author-Name: Jin Xu
Author-X-Name-First: Jin
Author-X-Name-Last: Xu
Author-Name: Xiaohan Zhou
Author-X-Name-First: Xiaohan
Author-X-Name-Last: Zhou
Author-Name: Jianghua Zhang
Author-X-Name-First: Jianghua
Author-X-Name-Last: Zhang
Author-Name: Daniel Zhuoyu Long
Author-X-Name-First: Daniel Zhuoyu
Author-X-Name-Last: Long
Title: The optimal channel structure with retail costs in a dual-channel supply chain
Abstract: 
 This paper considers a dual-channel supply chain consisting of a monopoly manufacturer, an independent retailer and a continuum of heterogeneous consumers who are classified into two segments according to their channel preferences. Due to various activities undertaken in different channels leading to retail costs, we highlight the effect of retail costs (i.e. fixed, linear and quadratic costs) on the optimal channel structures for the manufacturer, consumers and society. Our results show that the retail cost greatly influences the optimal channel structures for different parties. First, the manufacturer's channel selection varies considerably across retail costs. Specifically, when there are variable costs (linear and quadratic costs): on the one hand, the manufacturer might give up the grocery encroachment strategy; on the other hand, some profitable strategies which are missed in the case with fixed cost are likely to be implemented. Second, both consumer surplus and social welfare are maximised in the manufacturer-owned online channel unless the linear costs are sufficiently high or the cost gap between different channels is large. Collectively, the optimal channel structure for the manufacturer is not always optimal for consumer surplus or social welfare.
Journal: International Journal of Production Research
Pages: 47-75
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1694185
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1694185
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Template-Type: ReDIF-Article 1.0
Author-Name: Fabio De Felice
Author-X-Name-First: Fabio
Author-X-Name-Last: De Felice
Author-Name: Antonella Petrillo
Author-X-Name-First: Antonella
Author-X-Name-Last: Petrillo
Author-Name: Laura Petrillo
Author-X-Name-First: Laura
Author-X-Name-Last: Petrillo
Title: Captive offshoring drivers in the manufacturing industry: criteria and sub-criteria that influence the location choice
Abstract: 
 Captive offshoring is one of the most strategic approach in complex, dynamic and competitive global supply chains. In the present research, a rigorous decision-making model to identify captive offshoring drivers, that play a role in the company strategy and limiting the subjectivity of human decisions, has been proposed. Firstly, the Delphi method has been used to investigate and to identify criteria and sub-criteria that influence the captive offshoring strategy. Then, the Fuzzy Analytic Hierarchy Process (FAHP) method has been employed to calculate the weight of importance of each criteria and sub-criteria. The purpose of this paper is to address the relevance of strategic capabilities for the operation of international manufacturing to the captive offshoring decision. A real case study on captive offshoring concerning an Italian manufacturing company has been analysed. This study adds to the limited number of studies on the identification of captive offshoring drivers and contributes to the quantitative research on this topic. From a practical perspective, the research highlights that multi-criteria decision methods are well indicated to select criteria and sub-criteria that influence the location choice. The result will help managers to make specific decisions concerning their current captive offshoring policy.
Journal: International Journal of Production Research
Pages: 76-94
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1694718
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1694718
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Template-Type: ReDIF-Article 1.0
Author-Name: Sergey Kovalev
Author-X-Name-First: Sergey
Author-X-Name-Last: Kovalev
Author-Name: Isabelle Chalamon
Author-X-Name-First: Isabelle
Author-X-Name-Last: Chalamon
Author-Name: Stephane E. Collignon
Author-X-Name-First: Stephane E.
Author-X-Name-Last: Collignon
Title: Minimizing maximum job dependent ergonomic risk
Abstract: 
 We study a problem, in which workers must be assigned to jobs over a number of time periods and each assignment incurs a job dependent ergonomic risk for the worker. The risks of the same worker are summarised over the time periods. The objective is to minimise the maximum risk of all workers. The problem has an interesting combinatorial structure such that it is not immediately clear if it is polynomially solvable or NP-hard. Its computational complexity remained open for 35 years. We prove its NP-hardness and discuss polynomially solvable special cases, in which either the number of workers is fixed or optimal solutions are attained at a lower bound. The results can be used in production planning approaches considering elimination of excessive ergonomic risks as one of the objectives.
Journal: International Journal of Production Research
Pages: 95-101
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1694720
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1694720
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: Ripple effect and supply chain disruption management: new trends and research directions
Abstract: 
 Ripple effect is a specific area of SC disruptions and a strong stressor to SC resilience. Research on the ripple effect analyses how one or more disruptive events propagate through the SC and impact its resilience and performance. The phenomenon of the ripple effect, immensely existing in practice, has received great research interest in recent years. Ripple effect management, modelling and assessment became visible research avenues with a growing number and scope of contributions. This Special Issue presents recent developments on the ripple effect in SCs. The Special Issue focuses on studies that address the ripple effect and provide a comprehensive picture of the state of the art and future perspectives. The methodologies comprise of mathematical optimisation, simulation, game theory, control theoretic, data-driven analytics, network complexity, reliability theory research, and empirical research. Even though a variety of valuable insights have been developed in this area in recent years, new research avenues and ripple effect taxonomies are identified for further exploring the ripple effect in the settings of the COVID-19 pandemic, SC viability, viable SC model, and reconfigurable SCs.
Journal: International Journal of Production Research
Pages: 102-109
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2021.1840148
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1840148
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Template-Type: ReDIF-Article 1.0
Author-Name: Rameshwar Dubey
Author-X-Name-First: Rameshwar
Author-X-Name-Last: Dubey
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Stephen J. Childe
Author-X-Name-First: Stephen J.
Author-X-Name-Last: Childe
Author-Name: Samuel Fosso Wamba
Author-X-Name-First: Samuel
Author-X-Name-Last: Fosso Wamba
Author-Name: David Roubaud
Author-X-Name-First: David
Author-X-Name-Last: Roubaud
Author-Name: Cyril Foropon
Author-X-Name-First: Cyril
Author-X-Name-Last: Foropon
Title: Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience
Abstract: 
 Supply chain resilience and data analytics capability have generated increased interest in academia and among practitioners. However, existing studies often treat these two streams of literature independently. Our study model reconciles two different streams of literature: data analytics capability as a means to improve information-processing capacity and supply chain resilience as a means to reduce a ripple effect in supply chain or quickly recover after disruptions in the supply chain. We have grounded our theoretical model in the organisational information processing theory (OIPT). Four research hypotheses are tested using responses from 213 Indian manufacturing organisations collected via a pre-tested survey-based instrument. We further test our model using variance-based structural equation modelling, popularly known as PLS-SEM. All of the hypotheses were supported. The findings of our study offer a unique contribution to information systems (IS) and operations management (OM) literature. The findings further provide numerous directions to the supply chain managers. Finally, we note our study limitations and provide further research directions.
Journal: International Journal of Production Research
Pages: 110-128
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1582820
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1582820
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Template-Type: ReDIF-Article 1.0
Author-Name: Deepa Mishra
Author-X-Name-First: Deepa
Author-X-Name-Last: Mishra
Author-Name: Yogesh K. Dwivedi
Author-X-Name-First: Yogesh K.
Author-X-Name-Last: Dwivedi
Author-Name: Nripendra P. Rana
Author-X-Name-First: Nripendra P.
Author-X-Name-Last: Rana
Author-Name: Elkafi Hassini
Author-X-Name-First: Elkafi
Author-X-Name-Last: Hassini
Title: Evolution of supply chain ripple effect: a bibliometric and meta-analytic view of the constructs
Abstract: 
 In the broad sphere of Operations Management, Supply Chain Risk Management (SCRM) is a significant area of interest for both academics and practitioners. As SCRM has transitioned from an emerging topic to a growing research area, there is a need to review existing literature in order to ascertain development in this area. There are many literature reviews on this topic, however, there is a lack of an extensive review using network analysis and meta-analysis within SCRM context including ripple effect. To address this gap, we performed a review of 2564 articles published in peer-reviewed academic journals from 1976 to December 2018. First, we apply a network analysis tool on 2564 articles and identify emerging research clusters. Second, to conduct meta-analysis, we collated empirical results from the studies identified. Of those 2564 articles, 42 studies were empirical in nature including 29 studies that used a range of different constructs with appropriate correlation values required for performing meta-analysis. Through this study, we contribute to the literature on SCRM by discussing the challenges of current research, but more importantly, by identifying and proposing five research clusters and future research directions. Finally, the paper acknowledges the theoretical contribution, the limitations of this study, and suggests further research directions.
Journal: International Journal of Production Research
Pages: 129-147
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1668073
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1668073
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhimei Lei
Author-X-Name-First: Zhimei
Author-X-Name-Last: Lei
Author-Name: Ming K. Lim
Author-X-Name-First: Ming K.
Author-X-Name-Last: Lim
Author-Name: Li Cui
Author-X-Name-First: Li
Author-X-Name-Last: Cui
Author-Name: Yanzhang Wang
Author-X-Name-First: Yanzhang
Author-X-Name-Last: Wang
Title: Modelling of risk transmission and control strategy in the transnational supply chain
Abstract: 
 With the process of economic globalisation, especially the Belt and Road Initiative implemented by China, the transnational supply chain is dramatically increasing, and the risk ripple effect is becoming increasingly important. Understanding and predicting the dynamic trend of risk transmission within the transnational supply chain is important to prevent the spread of risks. However, the current research lacks the dynamic interpretation of risk transmission and control in the transnational supply chain and ignores the impact of differences among suppliers and the network structure. Therefore, this paper proposed an improved susceptible-infectious-susceptible (SIS) model combined with a complex network model and an optimised approach to the selection of risk control strategies to explore three issues: first, the dynamic change and trend of risk transmission; second, the relationships and impacts of different suppliers and structure of the supply chain on risk transmission; and third, the selection of a risk control strategy within the transnational supply chain. A numerical analysis and an example of a risk control strategy selection are conducted to reveal four properties of risk transmission within the transnational supply chain. In addition, the model is verified with a simulation of a real-world scenario based on the 2011 Japanese earthquake and tsunami.
Journal: International Journal of Production Research
Pages: 148-167
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1698782
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1698782
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Template-Type: ReDIF-Article 1.0
Author-Name: Brandon W. Lee
Author-X-Name-First: Brandon W.
Author-X-Name-Last: Lee
Author-Name: Jiho Yoon
Author-X-Name-First: Jiho
Author-X-Name-Last: Yoon
Author-Name: Seung Jun Lee
Author-X-Name-First: Seung Jun
Author-X-Name-Last: Lee
Title: A ripple effect in prehospital stroke patient care
Abstract: 
 We examine a ripple effect in prehospital stroke care processes. Stroke patient care in prehospital stages is provided by emergency medical services (EMS). We divide EMS processes into three segments: dispatcher, field provider service without a patient (i.e., en route to the patient scene), and field provider service with a patient (i.e., transporting the patient to a hospital). We use both empirical and analytical models in this study. The results of the empirical analysis suggest that the dispatcher's stroke identification can influence the time performance of the dispatch center itself and of the subsequent downstream processes of the prehospital stroke care, indicating a potential ripple effect in the care system. Our analytical models demonstrate the impact of misidentification (i.e., a disruptive event at the dispatcher stage) and the unavailability of an Advanced Life Support (ALS) ambulance (i.e., a disruptive event at the field provider stage) on the severity of the stroke patient's prehospital condition. The models indicate that there is an optimal diagnostic time on the part of the dispatcher that minimizes the adverse consequences throughout the prehospital stages of care under disruptive events, and that a centralized system can mitigate a ripple effect in prehospital stroke care.
Journal: International Journal of Production Research
Pages: 168-187
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2020.1825862
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1825862
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Template-Type: ReDIF-Article 1.0
Author-Name: Shigui Ma
Author-X-Name-First: Shigui
Author-X-Name-Last: Ma
Author-Name: Yong He
Author-X-Name-First: Yong
Author-X-Name-Last: He
Author-Name: Ran Gu
Author-X-Name-First: Ran
Author-X-Name-Last: Gu
Title: Dynamic generic and brand advertising decisions under supply disruption
Abstract: 
 Enterprise captures market share from competitors through brand advertising and increases consumer demand for this category of products through general advertising. In this paper, considering a supply chain with a manufacturer who is responsible for generic advertising and a retailer who undertakes brand advertising, a Stackelberg differential game-theoretic model is established to examine the impact of supply disruption faced by the manufacturer on the optimal decision-making and profits of supply chain members. When the supply of raw materials is disrupted, the optimal advertising strategies and advertising subsidy scheme designed for the initially estimated product sales need to be revised. The key to solving this problem is to explicitly consider possible deviation profit margins of supply chain members and total market demand for products caused by changes in the original product supply. Considering that the deviations of the profit margins and the total market demand are arbitrary, we analytically derive several propositions and obtain the optimal advertising strategies and the advertising subsidy scheme before and after the supply disruption. Then, we explore the impact of supply disruption through numerical analysis and provide management insights that are helpful for managers to re-design the advertising strategies and advertising subsidy schemes under supply disruption.
Journal: International Journal of Production Research
Pages: 188-212
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2020.1812751
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1812751
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Template-Type: ReDIF-Article 1.0
Author-Name: Amir Azaron
Author-X-Name-First: Amir
Author-X-Name-Last: Azaron
Author-Name: Uday Venkatadri
Author-X-Name-First: Uday
Author-X-Name-Last: Venkatadri
Author-Name: Alireza Farhang Doost
Author-X-Name-First: Alireza
Author-X-Name-Last: Farhang Doost
Title: Designing profitable and responsive supply chains under uncertainty
Abstract: 
 In this paper, we develop a multi-objective two-stage stochastic programming model, which takes into account the selection of warehouse and retailer sites and the decision about production levels, inventory levels, and shipping quantities among the entities of the supply chain network. The first objective function is to maximise the chain’s total profit over multiple periods, and the second objective function is to minimise the total travel times for unsatisfied customers, whose demands must be met by retailers which have been established in other markets, to maximise the chain’s responsiveness. Demands, selling prices and productions times at manufacturing sites are all considered as uncertain parameters. The two objective functions are in conflict with each other, and we use ϵ-constraint method to generate a set of Pareto optimal solutions for the proposed multi-objective problem. We then generalise the case and assume the uncertain parameters are continuously distributed random variables and use a simulation approach called sample average approximation (SAA) scheme to compute near optimal solutions to the stochastic model with potentially infinite number of scenarios. A computational study involving hypothetical networks of different sizes and a real supply chain network are presented to highlight the efficiency of the proposed solution methodology.
Journal: International Journal of Production Research
Pages: 213-225
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2020.1785036
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1785036
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Template-Type: ReDIF-Article 1.0
Author-Name: Hamed Jahani
Author-X-Name-First: Hamed
Author-X-Name-Last: Jahani
Author-Name: Babak Abbasi
Author-X-Name-First: Babak
Author-X-Name-Last: Abbasi
Author-Name: Zahra Hosseinifard
Author-X-Name-First: Zahra
Author-X-Name-Last: Hosseinifard
Author-Name: Masih Fadaki
Author-X-Name-First: Masih
Author-X-Name-Last: Fadaki
Author-Name: James P. Minas
Author-X-Name-First: James P.
Author-X-Name-Last: Minas
Title: Disruption risk management in service-level agreements
Abstract: 
 This paper studies the impact of capacity/inventory disruption on a supplier's cost, where the supplier has heterogeneous service level agreements (SLAs) in place with multiple customers (retailers). We compare three capacity allocation policies in the presence of supply disruption, with both full and partial disruption cases investigated. The results show that the two-stage policy outperforms other capacity allocation policies when a disruption is anticipated and that partial disruption is more manageable than full disruption in terms of meeting the SLAs. Furthermore, the supplier is better off to negotiate a longer performance review period assuming the penalty per time unit is fixed. This result is contrary to findings in the literature for SLAs when there is no consideration of disruption. The insights from this study can assist suppliers in determining their capacity level, making capacity-related decisions such as locations of warehouses or production sites, in allocating capacity to customers and in negotiating SLA terms such as the performance review period length and penalty rates.
Journal: International Journal of Production Research
Pages: 226-244
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2020.1748248
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1748248
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Template-Type: ReDIF-Article 1.0
Author-Name: Gökhan Özçelik
Author-X-Name-First: Gökhan
Author-X-Name-Last: Özçelik
Author-Name: Ömer Faruk Yılmaz
Author-X-Name-First: Ömer
Author-X-Name-Last: Faruk Yılmaz
Author-Name: Fatma Betül Yeni
Author-X-Name-First: Fatma
Author-X-Name-Last: Betül Yeni
Title: Robust optimisation for ripple effect on reverse supply chain: an industrial case study
Abstract: 
 This study examines the ripple effect on the system performance of the reverse supply chain (RSC) network and introduces a robust optimisation model for designing strong RSC networks to cope with the uncertainties caused by the ripple effect. In this manner, to the best knowledge of authors, a robust optimisation model for RSC design against the ripple effect in the context of green principles is formulated for the first time. That being the case, the study aims to provide remarkable managerial insights thanks to the developed robust optimisation model by adopting a proactive strategy before a long-term disruption occurs in the network. To this end, the robust optimisation model is applied to an industrial case study from an enterprise disassembling the household appliance. The scope of the case study is limited to the enterprise's recycling activities in the northern region of Turkey which is a potential landslide site due to the heavy rainfall. Computational experiments are performed through a set of scenarios regarding the different weight uncertainty values to reveal the changes in objective function value and decision variables. Based on the results, whilst the computationally tractable robust solutions are obtained; the price of robustness is higher than expected to protect the constraints against violation when the probability of constraint violation equals 0.01.
Journal: International Journal of Production Research
Pages: 245-264
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2020.1740348
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1740348
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Zhongzheng Liu
Author-X-Name-First: Zhongzheng
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: A new robust dynamic Bayesian network approach for disruption risk assessment under the supply chain ripple effect
Abstract: 
 Dynamic Bayesian network (DBN) theory provides a valid tool to estimate the risk of disruptions, propagating along the supply chain (SC), i.e. the ripple effect. However, in cases of data scarcity, obtaining perfect information on probability distributions required by the DBN is impractical. To overcome this difficulty, a new robust DBN approach is, for the first time, proposed in this study to analyse the worst-case oriented disruption propagation in the SC. This work considers an SC with multiple suppliers and one manufacturer over several time periods, in which only probability intervals of the suppliers' states and those of the related disruption propagations are known. The objective is to acquire the robust performance of risk estimation, measured by the worst-case probability in the disrupted state for the manufacturer. We first establish a nonlinear programming formulation to mathematically materialise the proposed robust DBN, which can be used to solve small-size problems. To overcome the computational difficulty in solving large-size problems, an efficient simulated annealing algorithm is further designed. Numerical experiments are conducted to validate its efficiency.
Journal: International Journal of Production Research
Pages: 265-285
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2020.1841318
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1841318
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Template-Type: ReDIF-Article 1.0
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Title: Facing market disruptions: values of elastic logistics in service supply chains
Abstract: 
 Market disruptions are commonly seen nowadays which directly affect demand. However, in logistics service supply chains, service capacity suppliers and service providers usually have to prepare logistics-service-capacity before demand is known. In this paper, we explore a logistics service supply chain with which the logistics-service provider (LP) has to decide the quantity of capacity to reserve to satisfy future demand in the upcoming season, which depends on whether market disruption occurs or not. The optimal capacity planning policy is determined and the impacts brought by the chance of market disruption are uncovered. Then, we consider the scenario with ‘elastic logistics’ in which capacity can be adjusted after the market state is known. We analytically establish the corresponding optimal dynamic policy and prove that it helps to stop the ripple effect from appearing. We explore the value of elastic logistics and propose conditions and measures to achieve Pareto improvement in the supply chain upon the adoption of elastic logistics. We extend the analysis to the case with the risk-averse LP and uncover that our qualitative findings remain robust, irrespective of the LP’s risk attitude.
Journal: International Journal of Production Research
Pages: 286-300
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2020.1722861
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1722861
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Template-Type: ReDIF-Article 1.0
Author-Name: Seyed Mohammad Gholami-Zanjani
Author-X-Name-First: Seyed Mohammad
Author-X-Name-Last: Gholami-Zanjani
Author-Name: Mohammad Saeed Jabalameli
Author-X-Name-First: Mohammad Saeed
Author-X-Name-Last: Jabalameli
Author-Name: Walid Klibi
Author-X-Name-First: Walid
Author-X-Name-Last: Klibi
Author-Name: Mir Saman Pishvaee
Author-X-Name-First: Mir Saman
Author-X-Name-Last: Pishvaee
Title: A robust location-inventory model for food supply chains operating under disruptions with ripple effects
Abstract: 
 Given the inevitable globalisation in the food sector and the specific security challenges this industry faces, designing food supply chains has become a substantial topic for academics and practitioners. The integration of food product-specific characteristics and potential disruptions has continuously gained importance because it better reflects real-world problems and responds to a crucial need for resilience, robustness, and competitiveness. In this article, a generic two-stage mixed-integer mathematical model is developed to integrate key features of location-allocation and inventory-replenishment decisions. Then, food-specific disruptions with ripple effects are incorporated through plausible scenarios. For such a setting, three resiliency strategies – namely, readiness, flexibility, and responsiveness – are used to deal with uncertainties. Based on extensive numerical experiments, the solutions obtained highlight behaviour of different design models to hedge against ripple effects as well as the importance of incorporating food-specific assumptions and risk aversion attitudes.
Journal: International Journal of Production Research
Pages: 301-324
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2020.1834159
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1834159
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:1:p:301-324




Template-Type: ReDIF-Article 1.0
Author-Name: Vinod Kumar Chauhan
Author-X-Name-First: Vinod Kumar
Author-X-Name-Last: Chauhan
Author-Name: Supun Perera
Author-X-Name-First: Supun
Author-X-Name-Last: Perera
Author-Name: Alexandra Brintrup
Author-X-Name-First: Alexandra
Author-X-Name-Last: Brintrup
Title: The relationship between nested patterns and the ripple effect in complex supply networks
Abstract: 
 Supply networks (SNs) play a vital role in fuelling trade and economic growth. Due to their interconnectedness, firm-level disruptions can cause perturbations to ripple through SNs, magnifying initial impact. Contemporary research on ripple effects focussed on understanding various structural features of SNs to predict and control disruption propagation. Our work adds to this body of knowledge by analysing an intriguing topological property that emerges in SNs: ‘nestedness’, which is defined as a pattern of organisation where products that are supplied by specialist suppliers are a subset of products that are supplied by generalist suppliers. In other words, generalists are also specialists. While previous research examined the emergence of nestedness and its possible reasons, its relationship to SN resilience remained unknown. Here, we develop a cascade model by bringing together the product-supplier-buyer structure; which provides us with fine-grained information on SN dependencies. We simulate disruptions in nested and non-nested organisations of the global automotive SN, and find that nested organisations are significantly more robust to random disruptions but vulnerable to hub disruptions under cascade conditions. However, nested structures are not as resilient; as they do not benefit from a response strategy where buyers seek alternative suppliers; because alternative suppliers do not exist. On the other hand, randomly connected SNs are vulnerable to cascades but can allow network reconfiguration.
Journal: International Journal of Production Research
Pages: 325-341
Issue: 1
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2020.1831096
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1831096
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:1:p:325-341




Template-Type: ReDIF-Article 1.0
Author-Name: Wouter Lefever
Author-X-Name-First: Wouter
Author-X-Name-Last: Lefever
Author-Name: Faycal A. Touzout
Author-X-Name-First: Faycal A.
Author-X-Name-Last: Touzout
Author-Name: Khaled Hadj-Hamou
Author-X-Name-First: Khaled
Author-X-Name-Last: Hadj-Hamou
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Title: Benders' decomposition for robust travel time-constrained inventory routing problem
Abstract: 
 The time-constrained inventory routing problem (TCIRP) is a variant of the standard inventory routing problem (IRP), in which each vehicle's trip duration must not exceed a predefined maximum duration limit. In this paper, we consider the TCIRP on a network in which arc travel times are uncertain. In particular, we investigate the case where the only available information on the arc travel times is that they take values in symmetric and bounded intervals around their mean values. To solve this problem, a robust optimisation approach that generates solutions with a controlled level of conservatism is implemented. To cope with the complexity of the resulting robust counterpart, we develop a Benders' decomposition-based heuristic. Furthermore, we describe how the valid inequalities developed for the IRP can be strengthened so that the Benders' decomposition master problem can be solved effectively. We compare the proposed approach with two standard approaches for finding robust solutions. The analysis of the results show that the proposed method is able to find robust solutions that are not too conservative in reasonable time.
Journal: International Journal of Production Research
Pages: 342-366
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1695167
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1695167
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:342-366




Template-Type: ReDIF-Article 1.0
Author-Name: Jianjiang Wang
Author-X-Name-First: Jianjiang
Author-X-Name-Last: Wang
Author-Name: Xuejun Hu
Author-X-Name-First: Xuejun
Author-X-Name-Last: Hu
Author-Name: Erik Demeulemeester
Author-X-Name-First: Erik
Author-X-Name-Last: Demeulemeester
Author-Name: Yan Zhao
Author-X-Name-First: Yan
Author-X-Name-Last: Zhao
Title: A bi-objective robust resource allocation model for the RCPSP considering resource transfer costs
Abstract: 
 Resource allocation is one of the core issues in project scheduling to ensure the effective use of scare renewable resources, and has been regularly encountered in production systems in the manufacturing and service industries. The transfers of renewable resources between activities generally incur certain scheduling costs and affect the robustness of a certain schedule in an uncertain environment. To address this issue, a bi-objective optimisation model is proposed to make the resource transfer decisions, which aims to minimise the transfer cost and maximise solution robustness in the presence of activity duration variability. The proposed model employs a novel resource-oriented flow formulation that is different from those of the previous literature. A NSGA-II and a Pareto simulated annealing (PSA) algorithm have been applied as the solution methodologies. Besides, the effectiveness of the metaheuristics are evaluated in comparison with a  $\varepsilon $ε-constraint method. In detail, the algorithms are carried out on a set of benchmarks and are compared to test their efficiencies based on four performance metrics: number of non-dominated solutions, general distance, hypervolume and spacing. Finally, a case study of a real project further indicates that the suggested model and algorithms are applicable and beneficial to the problem in practice.
Journal: International Journal of Production Research
Pages: 367-387
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1695168
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1695168
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Template-Type: ReDIF-Article 1.0
Author-Name: Amar Oukil
Author-X-Name-First: Amar
Author-X-Name-Last: Oukil
Author-Name: Ahmed El-Bouri
Author-X-Name-First: Ahmed
Author-X-Name-Last: El-Bouri
Title: Ranking dispatching rules in multi-objective dynamic flow shop scheduling: a multi-faceted perspective
Abstract: 
 In this paper, we present a multi-faceted approach for ranking dispatching rules (DRs) in multi-objective dynamic flow shop scheduling systems using data envelopment analysis (DEA). The merits of the proposed DEA-based approach stem in its ability to (1) integrate explicitly, under the same DEA framework, desirable and undesirable performance criteria of DRs without a priori normalisation or aggregation; (2) guarantee that the best DR preserves its benchmarking status regardless of the production scenario; (3) circumvent potential occurrence of multiple efficient DRs through embedding ordered weighted averaging (OWA) under DEA cross evaluation to produce aggregate ranking scores for the DRs. The evaluation of the new ranking approach is conducted using 18 data instances of 20 DRs each. The results reveal that, whatever the OWA optimism level, the preferred DR shifts away from the Shortest Processing Time (SPT) rule to the Cost Over Time (COVERT) rule as due-date tightness becomes relaxed, which appears consistent with known performance expectations of these DRs under such settings. To demonstrate a possible implementation of these results to support decision making in operations scheduling, we present a basic adaptive rule that switches automatically between the preferred rules based on real-time due-date tightness and machine utilisation levels.
Journal: International Journal of Production Research
Pages: 388-411
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1696487
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1696487
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Template-Type: ReDIF-Article 1.0
Author-Name: Majid Eskandarpour
Author-X-Name-First: Majid
Author-X-Name-Last: Eskandarpour
Author-Name: Pierre Dejax
Author-X-Name-First: Pierre
Author-X-Name-Last: Dejax
Author-Name: Olivier Péton
Author-X-Name-First: Olivier
Author-X-Name-Last: Péton
Title: Multi-directional local search for sustainable supply chain network design
Abstract: 
 In this paper, we propose a bi-objective MILP formulation to minimise logistics costs as well as  ${{\rm CO}_2} $CO2 emissions in a supply chain network design problem with multiple layers of facilities, technology levels and transportation mode decisions. The proposed model aims at investigating the trade-off between cost and  ${{\rm CO}_2} $CO2 emissions through supply chain activities (i.e. raw material supply, manufacturing, warehousing, and transportation). To this end, a multi-directional local search (MDLS) metaheuristic is developed. The proposed method provides a limited set of non-dominated solutions ranging from a purely cost effective solution to a purely environmentally effective one. Each iteration of the MDLS consists in performing local searches from all non-dominated solutions. To do so, a Large Neighborhood Search (LNS) algorithm is used. Extensive experiments based on randomly generated instances of various sizes and features are described. Three classic performance measures are used to compare the set of non-dominated solutions obtained by the MDLS algorithm and by directly solving the MILP model with the epsilon-constraint approach. This paper is concluded by managerial insights about the impact of using greener technology on the supply chain topology.
Journal: International Journal of Production Research
Pages: 412-428
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1696488
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1696488
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:412-428




Template-Type: ReDIF-Article 1.0
Author-Name: Lei Xu
Author-X-Name-First: Lei
Author-X-Name-Last: Xu
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Title: Real-time order allocation model by considering available-to-promise reserving, occupying and releasing mechanisms
Abstract: 
 Based on the available-to-promise (ATP for short) theory, a three-stage model is proposed to help manufacturers manage Assemble-to-Order supply chain with the high and low class of customers. A mixed integer programming model is formulated to find the optimal ATP reserving policy from history data in the first stage. And two other policies commonly seen in the literature are also constructed. One is based on the probability of high class customers and the other is constructed from the percentage of high class customers in history data. Then in the second stage, each reserving policy is applied with the occupying mechanism to deal with the real orders. Numerical results show that though these policies bring a higher acceptance rate of high class customers, the profit of the manufacturer could be hurt. Among the three reserving polices, our policy offers a balanced way for keeping a high acceptance rate with limited loss. Then in the third stage, the releasing mechanism is considered together with the reserving policy. In this case, no reserving policy becomes the worst and the policy we proposed achieves an overall well performance on average. Numerical experiments also show that our policy tends to reserve more than expected amount for high class customers when the probability of high class customers is low, which helps to improve the service level for high class customers, and less than the expected amount when the probability of high class customers is high, which takes the profit from low class customers into account.
Journal: International Journal of Production Research
Pages: 429-443
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1696489
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1696489
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Template-Type: ReDIF-Article 1.0
Author-Name: Xuemei Liu
Author-X-Name-First: Xuemei
Author-X-Name-Last: Liu
Author-Name: Jiawei Chen
Author-X-Name-First: Jiawei
Author-X-Name-Last: Chen
Author-Name: Aiping Li
Author-X-Name-First: Aiping
Author-X-Name-Last: Li
Title: Optimisation of line configuration and balancing for reconfigurable transfer lines considering demand uncertainty
Abstract: 
 Reconfigurable transfer lines (RTLs), which are highly responsive to demand fluctuations, have gained increasing attention. This research deals with the line configuration design and balancing problem of RTLs under uncertain demand where line configuration can be changed to satisfy a given demand with minimum cost. It is assumed that the demand of a single product is in interval form. Such RTL is composed of a sequence of workstations and each workstation consists of several identical CNC machining centres. The RTL production capability could be adjusted by adding/removing machines or overtime work. The line configuration and balancing decision is to determine the number of workstations, specify the set-up and the number of machines in each workstation, then assign operations to workstations with various constrains satisfied. Interval optimisation theory is introduced to cope with demand uncertainty. A two-stage optimisation model is developed to handle the primary RTL design and the necessary system reconfiguration. A heuristic algorithm based on greedy randomised adaptive search procedure combined with variable neighbourhood search is given for operation assignment. An industrial case study is carried out and multiple near-optimal solutions are obtained. The feasibility and effectiveness of the proposed method is verified by the comparison of computational experiments.
Journal: International Journal of Production Research
Pages: 444-466
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1696490
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1696490
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:444-466




Template-Type: ReDIF-Article 1.0
Author-Name: Hsien-Jen Lin
Author-X-Name-First: Hsien-Jen
Author-X-Name-Last: Lin
Title: An economic production quantity model with backlogging and imperfect rework process for uncertain demand
Abstract: 
 This paper deals with a lot-sizing problem in the economic production quantity model with imperfect production processes and failure in repair where a Brownian motion process governs the inventory level variation. We assume that the unsatisfied demand is fully backlogged. In addition, we assume that all imperfect items produced are stocked separately and then reworked. Reworking and shortage costs are included in the proposed mathematical modelling and analysis. The aim of this research is to determine the optimal production lot size and backorder level such that the long-run total expected cost of the system is minimised. For the proposed model, we prove closed-form expressions for the inventory process and for the backlog costs. Moreover, a computer code using software package for the numerical work is furnished to derive the optimal solution. Some numerical examples and sensitivity analysis are provided to illustrate the validity of the proposed model.
Journal: International Journal of Production Research
Pages: 467-482
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1696491
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1696491
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:467-482




Template-Type: ReDIF-Article 1.0
Author-Name: Hadi Abdollahzadeh Sangroudi
Author-X-Name-First: Hadi
Author-X-Name-Last: Abdollahzadeh Sangroudi
Author-Name: Mehdi Ranjbar-Bourani
Author-X-Name-First: Mehdi
Author-X-Name-Last: Ranjbar-Bourani
Title: Solving a flexible job shop lot sizing problem with shared operations using a self-adaptive COA
Abstract: 
 This paper deals with lot sizing decisions in a flexible job shop manufacturing system considering dependencies between lot sizing decisions. A novel mathematical model is developed to optimise lot sizing and scheduling simultaneously using a product-oriented approach as opposed to the job-oriented approach which has been prevalently considered in the literature. Moreover, the proposed model considers further underlying assumptions such as assembly operations, sequence-dependent setup times, initial inventory and safety stock levels, as well as lots with unequal and variable sizes. The objective is to minimise the total production, setup, and tardiness penalty costs of the system. To solve the formulated problem, a self-adaptive Cuckoo Optimisation Algorithm (COA) embedded with three new immigration mechanisms is developed. Numerical experiments are conducted to demonstrate the validity of the model and investigate the efficiency and effectiveness of the employed optimisation algorithm.
Journal: International Journal of Production Research
Pages: 483-515
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1696492
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1696492
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:483-515




Template-Type: ReDIF-Article 1.0
Author-Name: Sijing Deng
Author-X-Name-First: Sijing
Author-X-Name-Last: Deng
Author-Name: Xu Guan
Author-X-Name-First: Xu
Author-X-Name-Last: Guan
Author-Name: Jiayan Xu
Author-X-Name-First: Jiayan
Author-X-Name-Last: Xu
Title: The coopetition effect of learning-by-doing in outsourcing
Abstract: 
 Learning-by-doing is a prevailing phenomenon in which a firm's production cost decreases in its production quantity. We build a two-period model to investigate the coopetition effect of learning-by-doing in a supply chain with two competing original equipment manufacturers (OEMs) outsourcing to a common contract manufacturer (CM) whose production exhibits the learning-by-doing effect. Excluding the learning cooperation between OEMs, the learning-by-doing intensifies the price competition to such an extent that OEMs' two-period overall profits could be lower than the case of no learning. Outsourcing to a common CM brings OEMs higher learning benefits which dominate the negative effect of intensified competition. OEMs' two-period overall profits are always higher in this case. Interestingly, increasing the product substitution rate has two opposite effects on the OEMs' overall profits. Under certain condition, OEMs' profits might be increasing in the substitution rate since the positive cooperation effect dominates the negative competition effect. With coopetition effect of learning-by-doing, we show that OEMs' other simpler pricing strategies, such as myopic pricing and uniform pricing, may outperform the strategic differential pricing strategy. Moreover, when the two OEMs are significantly differentiated in market base, the larger OEM may prefer not outsourcing to a common CM due to the coopetition concern. Finally, we find that asymmetric production learning and CM's pricing power have important impacts on OEMs' decisions and profits.
Journal: International Journal of Production Research
Pages: 516-541
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1696493
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1696493
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:516-541




Template-Type: ReDIF-Article 1.0
Author-Name: Minghai Yuan
Author-X-Name-First: Minghai
Author-X-Name-Last: Yuan
Author-Name: Xianxian Cai
Author-X-Name-First: Xianxian
Author-X-Name-Last: Cai
Author-Name: Zhuo Zhou
Author-X-Name-First: Zhuo
Author-X-Name-Last: Zhou
Author-Name: Chao Sun
Author-X-Name-First: Chao
Author-X-Name-Last: Sun
Author-Name: Wenbin Gu
Author-X-Name-First: Wenbin
Author-X-Name-Last: Gu
Author-Name: Jinting Huang
Author-X-Name-First: Jinting
Author-X-Name-Last: Huang
Title: Dynamic service resources scheduling method in cloud manufacturing environment
Abstract: 
 Aiming at the characteristics and existing problems of dynamic service resource scheduling in cloud manufacturing (CMfg) environment, this paper studies the scheduling method of CMfg dynamic service resources. Firstly, the problem of optimal scheduling of dynamic service resources is studied. The mechanism of CMfg scheduling is summarised. The operation mechanism and scheduling system of CMfg scheduling are described. Secondly, from the perspective of resource allocation, the CMfg scheduling problem is assumed. The optimal scheduling model of dynamic service resources in CMfg environment is established with the goal of time, cost, quality and capability. Then, the ant optimisation algorithm (AO) is improved, and some functions in the genetic algorithm (GA) are used to optimise the objective function. A genetic-ant optimisation fusion algorithm(GA-AO) is proposed to solve the model. Finally, taking the production of a car component as an example, the algorithm is applied as an example, and compared with the general GA and AO, the model and algorithm proposed in this paper are proved to be more feasible and effective.
Journal: International Journal of Production Research
Pages: 542-559
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1697000
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1697000
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:542-559




Template-Type: ReDIF-Article 1.0
Author-Name: Tatiana Romanova
Author-X-Name-First: Tatiana
Author-X-Name-Last: Romanova
Author-Name: Yuri Stoyan
Author-X-Name-First: Yuri
Author-X-Name-Last: Stoyan
Author-Name: Alexandr Pankratov
Author-X-Name-First: Alexandr
Author-X-Name-Last: Pankratov
Author-Name: Igor Litvinchev
Author-X-Name-First: Igor
Author-X-Name-Last: Litvinchev
Author-Name: Konstantin Avramov
Author-X-Name-First: Konstantin
Author-X-Name-Last: Avramov
Author-Name: Marina Chernobryvko
Author-X-Name-First: Marina
Author-X-Name-Last: Chernobryvko
Author-Name: Igor Yanchevskyi
Author-X-Name-First: Igor
Author-X-Name-Last: Yanchevskyi
Author-Name: Irina Mozgova
Author-X-Name-First: Irina
Author-X-Name-Last: Mozgova
Author-Name: Julia Bennell
Author-X-Name-First: Julia
Author-X-Name-Last: Bennell
Title: Optimal layout of ellipses and its application for additive manufacturing
Abstract: 
 The paper studies a layout problem of variable number of ellipses with variable sizes placed into an arbitrary disconnected polygonal domain with maximum packing factor. The ellipses can be continuously translated and rotated. Restrictions on the dimensions of the ellipses are taken into account. Tools for the mathematical modelling of placement constraints (distance constraints between ellipses and containment of ellipses into a polygonal domain) using the phi-function technique are introduced. The tools make it possible to formulate the layout problem in the form of MIP model that is equivalent to a sequence of nonlinear programming subproblems. We develop a new solution algorithm that involves the feasible starting point algorithm and optimisation procedure to search for efficient locally optimal solutions of the layout problem. This algorithm can be used in the design of parts for «support-free» additive manufacturing, taking into account the conditions for its static/ dynamic strength. Results of the algorithm implementation for a topologically optimised flat part with the analysis of a stress state are provided.
Journal: International Journal of Production Research
Pages: 560-575
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1697836
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1697836
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:560-575




Template-Type: ReDIF-Article 1.0
Author-Name: Lei Shi
Author-X-Name-First: Lei
Author-X-Name-Last: Shi
Author-Name: Gang Guo
Author-X-Name-First: Gang
Author-X-Name-Last: Guo
Author-Name: Xiaohui Song
Author-X-Name-First: Xiaohui
Author-X-Name-Last: Song
Title: Multi-agent based dynamic scheduling optimisation of the sustainable hybrid flow shop in a ubiquitous environment
Abstract: 
 With the increased awareness of the market competition and protection of the environment, many studies have examined sustainable manufacturing, which combines lean production and sustainable performance, but there still exist barriers between the theories and the practices. This paper proposes a dynamic scheduling unit (DSU) with the multi-agent system (MAS) to build and formulate a kind of sustainable hybrid flow shop in a ubiquitous environment. The processing time, energy consumption and carbon emission are considered the sustainability indicators; and the machine failure, job inserting and job reworking are considered the disruption events. Then, a GA-based dynamic scheduling optimisation with variable priorities is proposed, including a weighted sum of indicators-genetic algorithm (WSI-GA) and an event-driven priority weights local search (EPW-LS) to dynamically generate the prescheduling and rescheduling solutions of the sustainable hybrid flow shop. Lastly, the proposed theories are applied to a computational case of part machining via the discrete event simulation method to demonstrate their validity and feasibility. The results show that the WSI-GA for prescheduling is superior to the referenced traditional priority-based genetic algorithms in the four different production modes and that EPW-LS for rescheduling can effectively improve the solutions of the preschedulings once disruption events occur.
Journal: International Journal of Production Research
Pages: 576-597
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1699671
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1699671
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:576-597




Template-Type: ReDIF-Article 1.0
Author-Name: Amir Nourmohammadi
Author-X-Name-First: Amir
Author-X-Name-Last: Nourmohammadi
Author-Name: Hamidreza Eskandari
Author-X-Name-First: Hamidreza
Author-X-Name-Last: Eskandari
Author-Name: Masood Fathi
Author-X-Name-First: Masood
Author-X-Name-Last: Fathi
Author-Name: Amos H.C. Ng
Author-X-Name-First: Amos H.C.
Author-X-Name-Last: Ng
Title: Integrated locating in-house logistics areas and transport vehicles selection problem in assembly lines
Abstract: 
 Decentralised in-house logistics areas, known as supermarkets, are widely used in the manufacturing industry for parts feeding to assembly lines. In contrary to the literature and inspired by observation in a real case, this study relaxes the assumption of using identical transport vehicles when deciding on the supermarkets’ location by considering the availability of different vehicles. In this regard, this study deals with the integrated supermarket location and transport vehicles selection problems (SLTVSP). A mixed-integer programming (MIP) model of the problem is developed. Due to the complexity of the problem, a hybrid genetic algorithm (GA) with variable neighborhood search (GA-VNS) is also proposed to address large-sized problems. The performance of GA-VNS is compared against the MIP, the basic GA, and simulated annealing (SA) algorithm. The computational results from the real case and a set of generated test problems show that GA-VNS provides a very good approximation of the MIP solutions at a much shorter computational time while outperforming the other compared algorithms. The analysis of the results reveals that it is beneficial to apply different transport vehicles rather than identical vehicles for SLTVSP.
Journal: International Journal of Production Research
Pages: 598-616
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1701207
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1701207
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:2:p:598-616




Template-Type: ReDIF-Article 1.0
Author-Name: Öncü Hazır
Author-X-Name-First: Öncü
Author-X-Name-Last: Hazır
Author-Name: Maher A. N. Agi
Author-X-Name-First: Maher A. N.
Author-X-Name-Last: Agi
Author-Name: Jérémy Guérin
Author-X-Name-First: Jérémy
Author-X-Name-Last: Guérin
Title: An efficient branch and bound algorithm for smoothing the workloads on simple assembly lines
Abstract: 
 In this study, we develop a branch and bound solution algorithm to solve the workload smoothing problem. Our algorithm incorporates new formulas for dynamically computing a lower bound on the optimal value of the objective function and for determining the earliest workstations for tasks. It also uses a fast heuristic for computing a good initial upper bound. A comprehensive experimental analysis is conducted in this study. The analysis demonstrates the outstanding performance of the algorithm and its efficiency in solving medium-sized workload smoothing problems.
Journal: International Journal of Production Research
Pages: 617-634
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1701208
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1701208
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Template-Type: ReDIF-Article 1.0
Author-Name: Zuoxu Wang
Author-X-Name-First: Zuoxu
Author-X-Name-Last: Wang
Author-Name: Chun-Hsien Chen
Author-X-Name-First: Chun-Hsien
Author-X-Name-Last: Chen
Author-Name: Pai Zheng
Author-X-Name-First: Pai
Author-X-Name-Last: Zheng
Author-Name: Xinyu Li
Author-X-Name-First: Xinyu
Author-X-Name-Last: Li
Author-Name: Li Pheng Khoo
Author-X-Name-First: Li Pheng
Author-X-Name-Last: Khoo
Title: A graph-based context-aware requirement elicitation approach in smart product-service systems
Abstract: 
 The paradigm of Smart product-service systems (Smart PSS) has emerged recently owing to the edge-cutting Information and Communication Technology (ICT) and artificial intelligence (AI) techniques. The unique features of Smart PSS including smartness and connectedness, value co-creation and data-driven design manner, enable the collection and analysis of large volume and heterogeneous contextual data to extract useful knowledge. Therefore, requirement elicitation, as a critical process for new solution (i.e. product-service) design, can be conducted in a rather context-aware manner, assured by those massive user-generated data and product-sensed data during the usage stage. Nevertheless, despite a few works on semantic modelling, scarcely any reports on such mechanism in today's smart, connected environment. Aiming to fill this gap, for the first time, a graph-based context-aware requirement elicitation approach considering contextual information within the Smart PSS is proposed. It leverages the pre-defined product, service, and condition ontologies together with Deepwalk technique, to formulate those concepts as nodes and their relationships as the edge of the proposed requirement graph. Implicit stakeholder requirements within a specific context can be further derived based on such interrelationships in a data-driven manner. To demonstrate its feasibility and effectiveness, an example of smart bike share system is addressed to illustrate the requirement elicitation process. It is hoped that this explorative study can offer valuable insights for the service providers who would like to extract requirements not only from the voice of customers but also from the user-generated data and product-sensed data.
Journal: International Journal of Production Research
Pages: 635-651
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1702227
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1702227
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiang Li
Author-X-Name-First: Xiang
Author-X-Name-Last: Li
Author-Name: Xueqing Cui
Author-X-Name-First: Xueqing
Author-X-Name-Last: Cui
Author-Name: Yongjian Li
Author-X-Name-First: Yongjian
Author-X-Name-Last: Li
Author-Name: Daqi Xu
Author-X-Name-First: Daqi
Author-X-Name-Last: Xu
Author-Name: Fangchao Xu
Author-X-Name-First: Fangchao
Author-X-Name-Last: Xu
Title: Optimisation of reverse supply chain with used-product collection effort under collector’s fairness concerns
Abstract: 
 Fairness has been regarded as a vital role in developing and sustaining benign channel cooperation relationships. One can exhibit either distributional fairness when comparing with upstream/downstream parties or peer-induced fairness when comparing with competitors located at the same stage of the supply chain. This paper examines distributional fairness in a simple reverse supply chain (RSC) consisting of one collector and one remanufacturer, and then extends to the case of one remanufacturer and two collectors to investigate the case of peer-induced fairness. Adopting the game-theory analysis framework, we explore the optimal decisions of transfer price and collection effort in the fair-minded RSC and discuss the impacts of fairness concern. It is shown that under some condition channel coordination can be achieved by a simple contract of constant transfer price with distributional fairness concern from the collector, but this is not true when the collectors are peer-induced fair-minded.
Journal: International Journal of Production Research
Pages: 652-663
Issue: 2
Volume: 59
Year: 2021
Month: 1
X-DOI: 10.1080/00207543.2019.1702229
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1702229
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Xin Liu
Author-X-Name-First: Xin
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: An exact method for disassembly line balancing problem with limited distributional information
Abstract: 
 As an important part in product recycling, disassembly line balancing problem (DLBP) has attracted a large amount of attention. Stochastic DLBP is now a hot and challenging research topic, due to its wide applications. This work investigates a DLBP with uncertain task times, where the distributional information is limited, i.e. only the mean values and standard deviations are given, due to the lack of data. From a two-stage perspective, a disassembly process is determined and the disassembly tasks are assigned to workstations in the first stage, and the penalty cost (i.e. the recourse cost) for exceeding the cycle time is minimised in the second stage. The objective is to minimise the expected system cost. For the problem, a two-stage distributionally robust formulation is devised, to minimise the worst-case expected system cost out of all possible probability distributions. Different from literature that focuses on approximation methods to tackle the limited distributional information, an exact method, i.e. the cutting-plane algorithm, is developed. Numerical results show that compared with the state-of-the-art solution methods, our developed cutting-plane algorithm can provide more reliable solutions in term of the robustness, especially in some extreme cases.
Journal: International Journal of Production Research
Pages: 665-682
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2019.1704092
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1704092
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:665-682




Template-Type: ReDIF-Article 1.0
Author-Name: Joshua Aboah
Author-X-Name-First: Joshua
Author-X-Name-Last: Aboah
Author-Name: Mark M.J. Wilson
Author-X-Name-First: Mark M.J.
Author-X-Name-Last: Wilson
Author-Name: Kathryn Bicknell
Author-X-Name-First: Kathryn
Author-X-Name-Last: Bicknell
Author-Name: Karl M. Rich
Author-X-Name-First: Karl M.
Author-X-Name-Last: Rich
Title: Identifying the precursors of vulnerability in agricultural value chains: A system dynamics approach
Abstract: 
 Conventional approaches for assessing supply chain vulnerability do not capture endogenous disruptions emanating from chain actors’ decisions that might increase value chain vulnerability. These approaches adopt a reactive analytical explanation of vulnerability, rather than one that considers issues of feedback effects. To address this issue, this paper adopts a system dynamics modelling approach to identify the precursors of vulnerabilities in Ghana’s cocoa value chain. The paper assesses the vulnerability levels of the cocoa value chain by adjusting the baseline values of several key parameters that can be influenced by chain actors. Results of the sensitivity analyses indicate that the precursors of vulnerability situated upstream of the cocoa value chain have varying impacts on chain vulnerability, but the same magnitude of effect on the vulnerability levels of chain actors. However, precursors of vulnerability that are situated midstream of the cocoa value chain have an unequal magnitude of effect on the vulnerability levels of chain actors. Results suggest that policies governing cocoa trading can become countervailing factors that obstruct the government’s call for upgrading along the cocoa value chain. The system dynamics model presented here enables a proactive assessment of vulnerability which can facilitate collaborative planning among stakeholders in the value chain.
Journal: International Journal of Production Research
Pages: 683-701
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2019.1704592
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1704592
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:683-701




Template-Type: ReDIF-Article 1.0
Author-Name: Wen-Jie Xu
Author-X-Name-First: Wen-Jie
Author-X-Name-Last: Xu
Author-Name: Li-Jun He
Author-X-Name-First: Li-Jun
Author-X-Name-Last: He
Author-Name: Guang-Yu Zhu
Author-X-Name-First: Guang-Yu
Author-X-Name-Last: Zhu
Title: Many-objective flow shop scheduling optimisation with genetic algorithm based on fuzzy sets
Abstract: 
 To solve many-objective flow-shop scheduling problems (FSP), a genetic algorithm based on the relative entropy of fuzzy sets (REFS_GA) is proposed. A mathematical model of the many-objective FSP is built, which involves four scheduling criterions of FSP. In REFS_GA, the Pareto front is mapped to fuzzy set, and the relational entropy coefficient of fuzzy sets is used to measure the similarity between the fuzzy sets of Pareto solutions and ideal solution. The coefficient is used as the fitness of genetic algorithm (GA) and to guide algorithm evolution. The performance of REFS_GA is evaluated through compared with GA based on g-dominance (gGA), random weight GA (rwGA) and the third version of non-dominated sorting genetic algorithm (NSGA-III). Experiments are carried out with eight DTLZ benchmark functions, six MaF benchmark functions with 4, 7 or 10 objectives, respectively, nine scheduling problems with four objectives and a real-world many-objective FSP. Experimental results show that REFS_GA can solve may-objective benchmark functions and many-objective FSP. The optimisation solution and performance indicators of REFS_GA are better than gGA, rwGA and NSGA-III. It can be concluded that REFS_GA is an effective method to solve many-objective optimisation problems. The main contributions of the work are that a four-objective model of FSP is built and a priori approach based on fuzzy set is proposed to solve many-objective FSP.
Journal: International Journal of Production Research
Pages: 702-726
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2019.1705418
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1705418
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:702-726




Template-Type: ReDIF-Article 1.0
Author-Name: Joost Berkhout
Author-X-Name-First: Joost
Author-X-Name-Last: Berkhout
Author-Name: Eric Pauwels
Author-X-Name-First: Eric
Author-X-Name-Last: Pauwels
Author-Name: Rob van der Mei
Author-X-Name-First: Rob
Author-X-Name-Last: van der Mei
Author-Name: Jan Stolze
Author-X-Name-First: Jan
Author-X-Name-Last: Stolze
Author-Name: Siem Broersen
Author-X-Name-First: Siem
Author-X-Name-Last: Broersen
Title: Short-term production scheduling with non-triangular sequence-dependent setup times and shifting production bottlenecks
Abstract: 
 A novel mathematical model is introduced that allows solving real-life scheduling problems in complex multi-stage machine environment with (i) non-triangular sequence-dependent setup times and (ii) shifting production bottlenecks, both of which are important aspects appearing in varying manufacturing industries. The primary goal is to minimise the tardiness of customer orders, which may consist of multiple production orders each in turn composed of several batches. A secondary objective is to maximise the production capacity utilization as measured by the makespan. The model is elaborated for general animal-feed plants which have to deal with the particular production scheduling problem on a daily basis. Dispatching rules are introduced to enhance the optimization progress. Numerical experiments show that optimising the model leads to schedules that meet the due dates. Moreover, by reducing the mean idle time of production lines with 35.6%, the optimization leads to a makespan reduction of 6.5% on average compared to real-life applied schedules.
Journal: International Journal of Production Research
Pages: 727-751
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2019.1705420
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1705420
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:727-751




Template-Type: ReDIF-Article 1.0
Author-Name: Abhijit Majumdar
Author-X-Name-First: Abhijit
Author-X-Name-Last: Majumdar
Author-Name: Sanjib Kumar Sinha
Author-X-Name-First: Sanjib Kumar
Author-X-Name-Last: Sinha
Author-Name: Mahesh Shaw
Author-X-Name-First: Mahesh
Author-X-Name-Last: Shaw
Author-Name: K. Mathiyazhagan
Author-X-Name-First: K.
Author-X-Name-Last: Mathiyazhagan
Title: Analysing the vulnerability of green clothing supply chains in South and Southeast Asia using fuzzy analytic hierarchy process
Abstract: 
 Various risks related to green clothing supply chains of South and Southeast Asian countries have been quantified based on their impact and probability of occurrence. Risks were classified into five categories, namely supply risks, demand risks, process or operation risks, business environment risks and financial risks. These risks were further divided into 18 specific risks. The fuzzy analytic hierarchy process (FAHP) was used to incorporate the vagueness of perception of experts regarding the impact of various supply chain risks. The probability of various risks was quantified by capturing the experts’ opinion using fuzzy numbers. Financial and business environment-related risks were found to have high impact whereas supply, demand and process-related risks have a high probability of occurrence in green clothing supply chain. Finally, a vulnerability matrix was developed where each specific risk was mapped based on their respective impact and probability. The outcome of this research would be very helpful for developing strategies for resilient green clothing supply chains in South and Southeast Asia. This would further drive the implementation of green clothing supply chain management practices in this geographic region.
Journal: International Journal of Production Research
Pages: 752-771
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2019.1708988
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1708988
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:752-771




Template-Type: ReDIF-Article 1.0
Author-Name: Maria Pires
Author-X-Name-First: Maria
Author-X-Name-Last: Pires
Author-Name: Elsa Silva
Author-X-Name-First: Elsa
Author-X-Name-Last: Silva
Author-Name: Pedro Amorim
Author-X-Name-First: Pedro
Author-X-Name-Last: Amorim
Title: Solving the grocery backroom layout problem
Abstract: 
 The backroom of retail stores has structural differences when compared with other warehouses and distribution centres, which are more traditionally studied in the literature. This paper presents a mathematical optimisation approach for an unequal area facility layout problem, applied in designing the backroom layout in grocery retail. A set of rectangular facilities (backroom departments) with given area requirements has to be placed, without overlapping, on a limited floor space (backroom area), which can have a regular or an irregular shape. The objective is to find the location and format of the storage departments, such that the walking distances in the store by store employees are minimised. The proposed approach is tested in a European grocery retailer. In the computational experiments, several real store layouts are compared with the ones suggested by the proposed model. The decrease in the walking distances is, on average, 30 percent. In order to understand what the current designers' strategy is, a set of scenarios was created and compared with the real layouts. Each scenario ignores a characteristic of the problem. The goal is to understand what aspect designers are currently discarding. The findings indicate that, currently, designers neglect the different replenishment frequencies of storage departments.
Journal: International Journal of Production Research
Pages: 772-797
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2019.1708990
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1708990
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:772-797




Template-Type: ReDIF-Article 1.0
Author-Name: Olawale J. Adeleke
Author-X-Name-First: Olawale J.
Author-X-Name-Last: Adeleke
Author-Name: M. Montaz Ali
Author-X-Name-First: M. Montaz
Author-X-Name-Last: Ali
Title: An efficient model for locating solid waste collection sites in urban residential areas
Abstract: 
 A new model for the efficient collection of solid waste in urban residential areas is proposed as a set covering facility location problem. The model finds the optimal location of waste collection sites such that all the customers are covered. An important feature of the model is that, rather than aggregate the quantity of waste from a group of demand points, it is assumed that the volume of waste of different types is known for each customer. This assumption encourages point-of-collection sorting which helps provide an improved solution to the problem of waste collection. A Lagrangian relaxation (LR) of the problem was developed, and the resulting dual problem was solved using an LR procedure in which the vectors of Lagrangian multipliers were updated through the subgradient optimisation. A simple linear relaxation heuristic was developed to obtain a feasible solution to the primal problem. Five newly constructed datasets mimicking the scenario of a local municipality were used to test the efficiency of the model and the solution technique. Preliminary results and comparison with existing results showed that the proposed model is efficient as considerable reductions were obtained for the total number of activated collection sites and allocated containers.
Journal: International Journal of Production Research
Pages: 798-812
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2019.1709670
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1709670
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:798-812




Template-Type: ReDIF-Article 1.0
Author-Name: Andy Ham
Author-X-Name-First: Andy
Author-X-Name-Last: Ham
Title: Transfer-robot task scheduling in job shop
Abstract: 
 This paper studies a simultaneous scheduling of production and material transfer in a job shop environment. The simultaneous scheduling approach has been recently adopted by warehouse operations, wherein transbots pick up jobs and deliver to pick-machines for processing that requires a simultaneous scheduling of jobs, transbots, and machines. However, both a large proportion of literature and real-world scheduling systems consider only one side of the problem. In our study, machines and transbot are both considered as constraining resources. The contributions of this paper are twofold. First, we propose a novel application of constraint programming for the job shop scheduling problem (JSP) with transbots, significantly outperforming all other benchmark approaches in the literature and proving optimality of the well-known benchmark instances, for the first time. Second, we propose a medium-scale benchmark instance.
Journal: International Journal of Production Research
Pages: 813-823
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2019.1709671
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1709671
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:813-823




Template-Type: ReDIF-Article 1.0
Author-Name: Enrique Gerstl
Author-X-Name-First: Enrique
Author-X-Name-Last: Gerstl
Author-Name: Gur Mosheiov
Author-X-Name-First: Gur
Author-X-Name-Last: Mosheiov
Title: The single machine CON problem with unavailability period
Abstract: 
 The classical CON problem focuses on scheduling jobs on a single machine sharing a common due-date. We study the CON problem with a given unavailability period. The basic problem (assuming linear job-independent costs and no idle times prior to or after the unavailability period) is easily shown to be NP-hard, and an efficient pseudo-polynomial dynamic programming algorithm is introduced. Extensions of the algorithm to general monotonic job-independent costs, and to linear job-dependent costs are studied as well. All algorithms are tested numerically, and are shown to produce optimal schedules in reasonable time. Then we allow idle times, verify that this case is NP-hard in the ordinary sense as well, and introduce a greedy-type heuristic. Numerical tests are performed, and the results indicate that the heuristic performs extremely well.
Journal: International Journal of Production Research
Pages: 824-838
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2019.1709672
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1709672
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:824-838




Template-Type: ReDIF-Article 1.0
Author-Name: İhsan Yanıkoğlu
Author-X-Name-First: İhsan
Author-X-Name-Last: Yanıkoğlu
Author-Name: Meltem Denizel
Author-X-Name-First: Meltem
Author-X-Name-Last: Denizel
Title: The value of quality grading in remanufacturing under quality level uncertainty
Abstract: 
 In remanufacturing, variability in quality levels of available cores (end-of-life products) has an impact on both the process cost and the process time. While previous research suggests that quality grading adds value, there are also concerns raised regarding how reliably the grades can be identified. We argue that uncertainty is inherent to the grading process and investigate the value of grading by taking into account the underlying uncertainty. We develop a robust optimisation model for remanufacturing planning, where both the per-unit cost and resource requirement to remanufacture a core are uncertain parameters that are assumed to reside in two different uncertainty sets; box and ellipsoidal. We analyse both uncapacitated and capacitated cases, and based on extensive numerical analysis, conclude that while on average, there is still value in grading, it becomes significantly smaller when the inherent uncertainty is accounted for. For the capacitated case, we also consider a cost for grading and find that it may cause a significant deterioration in the value of grading, if not rendering the grading totally useless. We show the validity of our approach through extensive numerical analyses.
Journal: International Journal of Production Research
Pages: 839-859
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1711983
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1711983
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:839-859




Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Lima
Author-X-Name-First: Alexandre
Author-X-Name-Last: Lima
Author-Name: Valeria Borodin
Author-X-Name-First: Valeria
Author-X-Name-Last: Borodin
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Philippe Vialletelle
Author-X-Name-First: Philippe
Author-X-Name-Last: Vialletelle
Title: A sampling-based approach for managing lot release in time constraint tunnels in semiconductor manufacturing
Abstract: 
 For the sake of product yield and quality considerations, time constraints (TCs) are imposed between process operations in various multi-product manufacturing systems. Often spanning a number of operations, time constraints tend to follow each other in close succession and overlap, forming thus time constraint tunnels (TCTs). The regulation problem of releasing lots in these time constraint tunnels is particularly challenging in semiconductor manufacturing systems, because of re-entrant flows, machine heterogeneity and high mix low volume (HM-LV) production configurations, which are typical in many wafer fabrication facilities. In such an evolving and time-varying context, this paper proposes a sequential sampling-based approach to estimate the probability that, prior to its release, a lot leaves a given time constraint tunnel on time. The proposed approach proves to be competitive in various respects by (i) taking into account industry specific features, (ii) being industrially tractable, and (iii) being sensitive and responsive to the current manufacturing system. Based on real-life instances, numerical experiments highlight the computational effectiveness and the industrial soundness of the proposed problem modelling together with the solution approach.
Journal: International Journal of Production Research
Pages: 860-884
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1711984
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1711984
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:860-884




Template-Type: ReDIF-Article 1.0
Author-Name: Antonio Casimiro Caputo
Author-X-Name-First: Antonio Casimiro
Author-X-Name-Last: Caputo
Author-Name: Pacifico Marcello Pelagagge
Author-X-Name-First: Pacifico Marcello
Author-X-Name-Last: Pelagagge
Author-Name: Paolo Salini
Author-X-Name-First: Paolo
Author-X-Name-Last: Salini
Title: A model for planning and economic comparison of manual and automated kitting systems
Abstract: 
 Parts kitting is a frequently adopted method to feed parts from a warehouse to an assembly line. While kitting allows minimisation of space occupation and Work In Process holding cost at the workstations, also simplifying materials flow and supporting manual assembly, it is penalised by high workforce cost for manual kits preparation. For this reason, automated kitting systems have been also proposed although their practical application is somewhat limited owing to the relevant capital investment and scarce performances of robotised kitting systems. Moreover, economic models allowing a quantitative comparison of manual and automated kitting systems are not yet available in the literature. As a contribution to fill this gap, in this paper a cost model useful to compare manual and automation-assisted parts retrieval and kitting systems is presented. The model can be used as a decision-making tool when planning and justifying kitting systems. The model includes capital investment, workforce, space occupation and quality costs. A case study as an application example is also included to demonstrate the model capabilities. Results show that automation-assisted kitting systems can be competitive in comparison to manual kitting and that break-even conditions can be also identified by the proposed method.
Journal: International Journal of Production Research
Pages: 885-908
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1711985
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1711985
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:885-908




Template-Type: ReDIF-Article 1.0
Author-Name: Yanfang Zheng
Author-X-Name-First: Yanfang
Author-X-Name-Last: Zheng
Author-Name: Wenhui Zhou
Author-X-Name-First: Wenhui
Author-X-Name-Last: Zhou
Author-Name: Xi Chen
Author-X-Name-First: Xi
Author-X-Name-Last: Chen
Author-Name: Weixiang Huang
Author-X-Name-First: Weixiang
Author-X-Name-Last: Huang
Title: The effect of emission permit allocation in an early-stage cap-and-trade for a duopoly market
Abstract: 
 Cap-and-trade systems, or emission trading systems (ETS), are increasingly adopted by countries and regions to provide economic incentives for reducing greenhouse gas emissions. The majority of existing ETS are early-stage systems implemented in and after 2013. These early-stage ETS are typically characterised by a focus on few industry sectors, and the employment of free emission allocation schemes including grandfathering and benchmarking. In this paper, we investigate the impact of emission allocation schemes in an early-stage cap-and-trade system in a duopoly market. We show that benchmarking scheme may lead the energy-efficient firm to reserve part of its emission permits, while firms always use up their after-trading permits under grandfathering. We also find that a more stringent emission cap may increase firms' profits rather than decreasing them under both allocation schemes, suggesting a possible cause for windfall profits observed in early-stage ETS. Benchmarking is found to lead to lower emissions compared to those under grandfathering, while it may result in higher or lower firm profits, consumer surplus, and the overall social welfare. Furthermore, under either allocation scheme, allowing emission trading does not affect the total emissions, while it can increase firm profits and consumer surplus and therefore the overall social welfare.
Journal: International Journal of Production Research
Pages: 909-925
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1711986
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1711986
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Template-Type: ReDIF-Article 1.0
Author-Name: Youqiong Ai
Author-X-Name-First: Youqiong
Author-X-Name-Last: Ai
Author-Name: Yifan Xu
Author-X-Name-First: Yifan
Author-X-Name-Last: Xu
Title: Strategic sourcing in forward and spot markets with reliable and unreliable suppliers
Abstract: 
 We study sourcing and purchasing strategies of a monopolistic retailer in a market with a reliable but expensive supplier and an unreliable but cheap supplier with random yield. The retailer can solely source from either supplier or adopt dual sourcing in the forward market while engaging in spot trade. Our study shows that the retailer's relative reliance on forward sourcing is lessened in the presence of a reliable supplier with higher cost, an unreliable supplier with more variable yield, and a more sensitive spot market. Moreover, highly variable forward supply enhances the value of a spot market when compared with high forward cost. Regarding the forward sourcing decision, we find that dual sourcing always benefits the retailer as well as the whole society, whereas upstream competition is not definitely harmful to suppliers. Dual sourcing might benefit the reliable supplier when its cost is sufficiently low or the unreliable supplier when its yield variability is sufficiently small. Besides, dual sourcing could degrade into unreliable sole sourcing when the reliable supplier is relatively expensive. Moreover, in spite of the competition between suppliers in the forward market, dual sourcing does not definitely increase the retailer's reliance on forward sourcing relative to spot trade.
Journal: International Journal of Production Research
Pages: 926-941
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1711987
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1711987
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Template-Type: ReDIF-Article 1.0
Author-Name: Shu-Jung Sunny Yang
Author-X-Name-First: Shu-Jung Sunny
Author-X-Name-Last: Yang
Author-Name: Kai-Yu Hsieh
Author-X-Name-First: Kai-Yu
Author-X-Name-Last: Hsieh
Title: Supply chain investment and de-escalation of capacity competition
Abstract: 
 Research on capacity competition has examined the conditions under which early mover’s capacity investment might preempt, or instead escalate, latecomers’ capacity investment. In contrast, this paper investigates the role of early mover’s supply chain investment in de-escalating subsequent capacity competition, in a setting where competing firms enter a new location to establish new production sites. Supply chain investment refers to investment in developing and integrating with supply chain partners in the location where a production site resides. We build a two-stage model where an early mover and a latecomer first make their investment decisions sequentially, and next choose either their output level (Cournot competition) or pricing (Bertrand competition) simultaneously. Predictions derived from the analytical model is then tested using data on a set of leading IT manufacturers. Both analytical and empirical results suggest that latecomer’s capacity investment increases correspondingly with early mover’s capacity investment, but decreases with early mover’s supply chain investment.
Journal: International Journal of Production Research
Pages: 942-958
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1711989
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1711989
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Template-Type: ReDIF-Article 1.0
Author-Name: Qinyu Song
Author-X-Name-First: Qinyu
Author-X-Name-Last: Song
Author-Name: Yaodong Ni
Author-X-Name-First: Yaodong
Author-X-Name-Last: Ni
Author-Name: Dan A. Ralescu
Author-X-Name-First: Dan A.
Author-X-Name-Last: Ralescu
Title: The impact of lead-time uncertainty in product configuration
Abstract: 
 Product configuration is widely practiced and is very effective when offering mass customisation production. This strategy assists manufacturers in understanding customers' preferences and demands, presenting product relevant rules, choosing alternative components and modules, and constructing theoretical models. However, the uncertainties (such as lead-time uncertainty) are not fully considered in the product configuration. To fill this gap, we develop an uncertain product configuration model based on uncertain lead-time and time-sensitive demand using uncertain programming. Another contribution is that we explored the interdependence between uncertain lead-time and outsourcing strategy. This uncertain mixed-integer programming is solved by using CPLEX 12.8. During a series of numerical experiments, we found that the profit and the sourcing strategies are sensitive to the uncertain lead-time and the outsourcing strategy helps companies reduce losses due to uncertainty.
Journal: International Journal of Production Research
Pages: 959-981
Issue: 3
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1715506
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1715506
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Template-Type: ReDIF-Article 1.0
Author-Name: Hui-Yu Zhang
Author-X-Name-First: Hui-Yu
Author-X-Name-Last: Zhang
Author-Name: Shao-Hui Xi
Author-X-Name-First: Shao-Hui
Author-X-Name-Last: Xi
Author-Name: Qing-Xin Chen
Author-X-Name-First: Qing-Xin
Author-X-Name-Last: Chen
Author-Name: James MacGregor Smith
Author-X-Name-First: James MacGregor
Author-X-Name-Last: Smith
Author-Name: Ning Mao
Author-X-Name-First: Ning
Author-X-Name-Last: Mao
Author-Name: Xiang Li
Author-X-Name-First: Xiang
Author-X-Name-Last: Li
Title: Performance analysis of a flexible flow shop with random and state-dependent batch transport
Abstract: 
 In many manufacturing contexts, performance modelling of an integrated production and material handling system is a complex problem. Existing research lacks an in-depth consideration of the integration of these two areas. A flexible flow shop with random and state-dependent batch transport, where the batch size depends on the number of jobs in the buffers and the capacity of automated guided vehicles, is considered and modelled as an open queueing network with blocking. A decomposition method of state space is proposed for computing system performance measures. The accuracy and efficiency of the proposed method are demonstrated by comparing the results with simulations from numerical experiments. Meanwhile, the properties of the system, especially for material handling processes, are investigated and analyzed according to the experiments. The results of this paper can be used as a basis for system design, analysis, and resource planning.
Journal: International Journal of Production Research
Pages: 982-1002
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1712488
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1712488
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Template-Type: ReDIF-Article 1.0
Author-Name: Yixiao Zhao
Author-X-Name-First: Yixiao
Author-X-Name-Last: Zhao
Author-Name: Yihai He
Author-X-Name-First: Yihai
Author-X-Name-Last: He
Author-Name: Di Zhou
Author-X-Name-First: Di
Author-X-Name-Last: Zhou
Author-Name: Anqi Zhang
Author-X-Name-First: Anqi
Author-X-Name-Last: Zhang
Author-Name: Xiao Han
Author-X-Name-First: Xiao
Author-X-Name-Last: Han
Author-Name: Yao Li
Author-X-Name-First: Yao
Author-X-Name-Last: Li
Author-Name: Wenzhuo Wang
Author-X-Name-First: Wenzhuo
Author-X-Name-Last: Wang
Title: Functional risk-oriented integrated preventive maintenance considering product quality loss for multistate manufacturing systems
Abstract: 
 During the abnormal operations before breakdown of a multistate manufacturing system, product quality loss could systematically characterise the affected economic cost in advance. However, few studies have considering the valuable quality loss data, thus, a novel risk-oriented optimisation approach of integrated maintenance is proposed considering the quality loss of work-in-process (WIP) obtained from the manufacturing system. First, the functional risks in manufacturing systems are expounded and classified by detectable deviations and potential manufacturing defects of the finished product based on machine performance state, and product quality loss is therefore applied for preventive maintenance activities. Second, the degradation path of machine performance and its effect on WIP are clarified. Explicit risk is presented by dimensional deviations of key quality characteristics, whereas implicit risk is quantified by the influence of component- and system-level manufacturing defects on the early product usage phase. Third, different levels of maintenance actions are proposed, and the integrated preventive maintenance plan for the entire production horizon is obtained by minimising product quality loss and PM investments. The optimal decision combination is solved by genetic algorithm. Finally, the optimal maintenance strategy is presented to verify the superiority of this method through the analysis of a cylinder head manufacturing system.
Journal: International Journal of Production Research
Pages: 1003-1020
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1713416
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1713416
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Template-Type: ReDIF-Article 1.0
Author-Name: Delphine Guillon
Author-X-Name-First: Delphine
Author-X-Name-Last: Guillon
Author-Name: Rania Ayachi
Author-X-Name-First: Rania
Author-X-Name-Last: Ayachi
Author-Name: Élise Vareilles
Author-X-Name-First: Élise
Author-X-Name-Last: Vareilles
Author-Name: Michel Aldanondo
Author-X-Name-First: Michel
Author-X-Name-Last: Aldanondo
Author-Name: Éric Villeneuve
Author-X-Name-First: Éric
Author-X-Name-Last: Villeneuve
Author-Name: Christophe Merlo
Author-X-Name-First: Christophe
Author-X-Name-Last: Merlo
Title: Product⋎service system configuration: a generic knowledge-based model for commercial offers
Abstract: 
 At a time when modes of consumption are rapidly evolving, consumer attitudes and expectations are changing. Today, customers want more and more products and services that can be customised to their needs. Furthermore, they are more willing to pay for usage of a product rather than ownership. On the other hand, companies are adding more and more services to the products they are bringing to market in order to create added value and differentiate themselves from their competitors. To adapt to these new market trends, companies now have to offer their customers a more sophisticated catalog of solutions, in both product and services, including all conceivable combinations of the two. The aim of this article is to propose a generic knowledge-based model, dedicated to commercial offer configuration which is able to cope with the whole variety of solutions a company can deliver. To our knowledge, although some works on product configuration, service and product-service system configuration exist, none of them is generic enough to support product, service and product-service configuration at the same time when defining commercial offers. In this article, after giving a state-of-the-art assessment of product and service configurations, the need for a generic model able to cover the whole range and diversity of commercial offers is established, a knowledge-based model is defined and its relevance is demonstrated on seven use-cases coming from secondary and tertiary sector companies.
Journal: International Journal of Production Research
Pages: 1021-1040
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1714090
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1714090
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Template-Type: ReDIF-Article 1.0
Author-Name: Minh Hung Ho
Author-X-Name-First: Minh Hung
Author-X-Name-Last: Ho
Author-Name: Faicel Hnaien
Author-X-Name-First: Faicel
Author-X-Name-Last: Hnaien
Author-Name: Frederic Dugardin
Author-X-Name-First: Frederic
Author-X-Name-Last: Dugardin
Title: Electricity cost minimisation for optimal makespan solution in flow shop scheduling under time-of-use tariffs
Abstract: 
 The industrial sector consumes half of the world delivered energy and is responsible for a third of carbon dioxide emissions which cause severe environmental pollution. The industry has to change its behaviour concerning the energy consumption. Since two-machine flow shop scheduling (
 $F2|perm|C_{{\rm max}} $F2|perm|Cmax) is one of the typical problems of the manufacturing industry, this paper aims to build an energy-cost-aware scheduling plan. This work tackles the joint optimisation of makespan and electricity cost in two-machine flow shop scheduling problem under electricity pricing. We enhance the financial aspect of the optimal solution of 
 $F2|perm|C_{{\rm max}} $F2|perm|Cmax by minimising the electricity cost without increasing the makespan. Firstly, we show the contribution of the generation of several optimal equivalent solutions of 
 $F2|perm|C_{{\rm max}} $F2|perm|Cmax. The optimal equivalent solutions have different electricity costs but present the same makespan. Then, we determine the optimal starting time of jobs on several equivalent optimal solutions to get the best production plan. Finally, the numerical tests show that our proposed approach improves the electricity cost significantly under optimal makespan. The results provide good solutions to managers and decision makers to achieve energy cost savings without sacrificing the productivity which can contribute to sustainable development of the manufacturing industry.
Journal: International Journal of Production Research
Pages: 1041-1067
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1715504
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1715504
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Template-Type: ReDIF-Article 1.0
Author-Name: Marzieh Ghiyasinasab
Author-X-Name-First: Marzieh
Author-X-Name-Last: Ghiyasinasab
Author-Name: Nadia Lehoux
Author-X-Name-First: Nadia
Author-X-Name-Last: Lehoux
Author-Name: Sylvain Ménard
Author-X-Name-First: Sylvain
Author-X-Name-Last: Ménard
Author-Name: Caroline Cloutier
Author-X-Name-First: Caroline
Author-X-Name-Last: Cloutier
Title: Production planning and project scheduling for engineer-to-order systems- case study for engineered wood production
Abstract: 
 Small companies that prefabricate parts for the construction industry in the context of engineer-to-order (ETO) systems, often encounter production issues as they usually do not systematically optimise their planning. In this paper, a production planning method for a multi-project ETO system is proposed. Four optimisation models testing combinations of three objectives are proposed. The main objective present in all models is cost reduction. The other objectives considered are minimising project finish time and minimising set-up time of a bottleneck station. The models are applied in a case study with an engineered wood production firm considering fifteen construction projects over a period of forty weeks. Two scenarios for adding long and complex projects and projects with medium length and complexity are also tested to provide a decision support tool in the project acceptance phase. This article contributes to the scientific literature by providing four production scheduling models which integrate a multi-objective production scheduling approach in a multi-project context for the prefabrication of ETO parts in construction. Furthermore, the research applies the models to a real case which highlights empirical issues that had not been entirely explored in current literature.
Journal: International Journal of Production Research
Pages: 1068-1087
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1717009
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1717009
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:4:p:1068-1087




Template-Type: ReDIF-Article 1.0
Author-Name: Felipe Kesrouani Lemos
Author-X-Name-First: Felipe Kesrouani
Author-X-Name-Last: Lemos
Author-Name: Adriana Cristina Cherri
Author-X-Name-First: Adriana Cristina
Author-X-Name-Last: Cherri
Author-Name: Silvio Alexandre de Araujo
Author-X-Name-First: Silvio Alexandre
Author-X-Name-Last: de Araujo
Title: The cutting stock problem with multiple manufacturing modes applied to a construction industry
Abstract: 
 This paper addresses the problem of multiple manufacturing modes integrated into the cutting stock problem, based on a real-life application of the concrete pole manufacturing. The main aim is to propose, formulate and test this integrated problem, which can be applied to the construction industry and other contexts of multiple manufacturing modes with cutting processes. The motivation for this proposal is the construction industry, in which reinforced concrete structures can be reinforced by various combinations of one-dimensional steel bars of varying thicknesses and lengths. An integer programming mathematical formulation is proposed aiming to minimise the total cost and to meet a demand of final products with different possible configurations. A column generation procedure is used as the solution method together with a heuristic procedure to find an integer solution. Computational results were performed with practical instances in order to assess the value of the approach and with a set of random generated instances in order to explore the influence of parameters on the results. Some managerial insights are presented.
Journal: International Journal of Production Research
Pages: 1088-1106
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1720923
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1720923
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Template-Type: ReDIF-Article 1.0
Author-Name: Banu Yetkin Ekren
Author-X-Name-First: Banu
Author-X-Name-Last: Yetkin Ekren
Title: A multi-objective optimisation study for the design of an AVS/RS warehouse
Abstract: 
 This paper deals with a hierarchical solution approach for multi-objective optimisation of an autonomous vehicle-based storage and retrieval system (AVS/RS) warehouse design. As a result of recent technological and Industry 4.0 developments, industries tend to automise their facilities using systems such as AVS/RS, an intra-logistics system, mostly utilised by large distribution centres. Compared to a traditional crane-based automated storage and retrieval system (AS/RS), these systems are more advantageous for having a flexible travel pattern of autonomous vehicles, enabling the designer vary the number of vehicles in the system based on the changed demand environment. Since it may affect the initial and operational costs as well as the system efficiency significantly, it is important to decide on the right warehouse design at first for these systems. In this paper, a multi-objective optimisation solution procedure under a hierarchical approach for the design of an AVS/RS, by considering minimisation of two conflicting performance measures – average cycle time and average energy consumption per transaction – is presented. By this work, it is also aimed to attract the attention of practitioners for the significance of multi-objective performance optimisation. For the multi-objective optimisation, Pareto-optimal solutions are presented.
Journal: International Journal of Production Research
Pages: 1107-1126
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1720927
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1720927
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:4:p:1107-1126




Template-Type: ReDIF-Article 1.0
Author-Name: Y. Lahrichi
Author-X-Name-First: Y.
Author-X-Name-Last: Lahrichi
Author-Name: N. Grangeon
Author-X-Name-First: N.
Author-X-Name-Last: Grangeon
Author-Name: L. Deroussi
Author-X-Name-First: L.
Author-X-Name-Last: Deroussi
Author-Name: S. Norre
Author-X-Name-First: S.
Author-X-Name-Last: Norre
Title: A new split-based hybrid metaheuristic for the reconfigurable transfer line balancing problem
Abstract: 
 We consider the Reconfigurable Transfer Line Balancing Problem. This problem consists of allocating a set of operations (necessary to machine a single part) to different workstations placed into a serial line. Each workstation can contain multiple machines operating in parallel. The machines considered are mono-spindle head CNC machines which may imply sequence-dependent setup times between operations in order to perform tool changes. Therefore, the operations allocated to a workstation should be sequenced. Besides, accessibility, inclusion, exclusion and precedence constraints between operations are considered. In this article, we propose a polynomial exact algorithm that balances the transfer line provided the overall sequence of the operations (called ‘giant sequence’) is given. We use this algorithm to solve the balancing problem when the overall sequence of operations is not fixed by embedding it in a metaheuristic framework. We perform experimentation on literature instances. The results obtained show the effectiveness of the proposed approach compared to literature.
Journal: International Journal of Production Research
Pages: 1127-1144
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1720929
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1720929
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Template-Type: ReDIF-Article 1.0
Author-Name: Ting Chen
Author-X-Name-First: Ting
Author-X-Name-Last: Chen
Author-Name: Feng Yang
Author-X-Name-First: Feng
Author-X-Name-Last: Yang
Author-Name: Xiaolong Guo
Author-X-Name-First: Xiaolong
Author-X-Name-Last: Guo
Title: Optimal bundling in a distribution channel in the presence of substitutability and complementarity
Abstract: 
 This paper investigates the impact of product interrelatedness (substitutability and complementarity) on decision optimisation in a distribution channel consisting of a manufacturer and a retailer. The retailer purchases the manufacturer’s product and retails it with another product as a bundle. The retailer decides the bundling strategy as a choice between full mixed bundling, partial mixed bundling, and pure bundling. Based on analytical models, we reveal how the degree of substitutability and complementarity influences the channel members’ optimal bundling decisions. Considering substitutes, the retailer benefits from partial mixed bundling only when the substitutability is sufficiently high; otherwise, full mixed bundling dominates. The partial mixed bundling strategy outperforms full mixed bundling for the manufacturer when the substitutability is relatively high, but when it is not, full mixed bundling is better. Considering complements, the retailer will choose pure bundling as its optimal bundling strategy along with increasing complementarity. Otherwise, the retailer benefits from the partial mixed bundling with decreasing complementarity. The pure bundling strategy always improves the manufacturer’s profit by expanding market demand significantly.
Journal: International Journal of Production Research
Pages: 1145-1165
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1720930
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1720930
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:4:p:1145-1165




Template-Type: ReDIF-Article 1.0
Author-Name: Shiwang Hou
Author-X-Name-First: Shiwang
Author-X-Name-Last: Hou
Author-Name: Keming Yu
Author-X-Name-First: Keming
Author-X-Name-Last: Yu
Title: A non-parametric CUSUM control chart for process distribution change detection and change type diagnosis
Abstract: 
 Non-parametric control charts have been good alternatives to parametric control charts when little information is known about the type of process distribution or the value of parameters. Most approaches proposed by the current literature monitor either location or scale change in batch mode and their performance is discounted when monitoring distribution change in both location and scale simultaneously in a sequential pattern. This paper proposed a log-likelihood-ratio-based non-parametric cumulative sum (CUSUM) control chart to monitor arbitrary distribution change and diagnose the detailed change type simultaneously. By integrating the superiority of log-likelihood ratio test to detect any change of distribution and CUSUM chart to detect a small change, the proposed approach can detect small potential changes in location, scale and shape; and provide detailed information about change type when control chart gives a signal. Comparison results with many other non-parametric approaches were provided by numerical simulation and the results of an application case demonstrate the effectiveness of the proposed approach.
Journal: International Journal of Production Research
Pages: 1166-1186
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1721588
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1721588
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:4:p:1166-1186




Template-Type: ReDIF-Article 1.0
Author-Name: Dapei Jiang
Author-X-Name-First: Dapei
Author-X-Name-Last: Jiang
Author-Name: Xiangyong Li
Author-X-Name-First: Xiangyong
Author-X-Name-Last: Li
Title: Order fulfilment problem with time windows and synchronisation arising in the online retailing
Abstract: 
 In this paper, we study the order fulfilment problem with time windows and synchronisation, which arises in the online retailing environment. Given customer orders released in the time window of decision, the online retailer needs to decide which fulfilment centre should fulfil customer orders, how to rigidly coordinate and synchronise operations of different types of vehicles, and how to deliver orders while meeting customers' service time windows, to minimise expenses of order fulfilment. We first introduce a mixed-integer linear programming model, which faces a significant computation burden. To that end, we develop a decomposition-based approach. We conduct extensive experiments to verify the effectiveness of our approach by comparing it with a commercial solver, and a greedy heuristic. We also present managerial insights regarding how our approach could reduce the order transfer operations at the distribution centres and thereby optimise the e-order fulfilment expenses.
Journal: International Journal of Production Research
Pages: 1187-1215
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1721589
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1721589
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:4:p:1187-1215




Template-Type: ReDIF-Article 1.0
Author-Name: Yanhui Li
Author-X-Name-First: Yanhui
Author-X-Name-Last: Li
Author-Name: Lu Xu
Author-X-Name-First: Lu
Author-X-Name-Last: Xu
Title: Cybersecurity investments in a two-echelon supply chain with third-party risk propagation
Abstract: 
 Cybersecurity presents a monumental challenge for interconnected supply chains, as an attack on one node can compromise an entire business. In this paper, we propose a game theory model to investigate cybersecurity investments with third-party risk propagation in a two-echelon supply chain consisting of one retailer and n suppliers. The optimal investments and their responses to relevant security characteristics, such as intrinsic vulnerability, propagation probability, number of suppliers, and attack probability, are analysed and discussed both theoretically and numerically considering one-stage risk propagation. It is found that there are serious prisoners' dilemma and free-riding phenomena in such a scenario. To mitigate third-party risks and improve the investment efficiency, three coordination mechanisms, joint decision, security risk compensation, and security information sharing, are presented and compared numerically. The results indicate that joint decision-making and security risk compensation perform better on stimulating firms' investments and reducing expected costs both individually and collectively relative to security information sharing. Furthermore, the case of two-stage risk propagation is also supplemented and compared with one-stage case. Based on these findings, some management insights are recommended to cybersecurity managers in supply chains for designing more efficient cybersecurity mechanisms and investment strategies.
Journal: International Journal of Production Research
Pages: 1216-1238
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1721591
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1721591
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:4:p:1216-1238




Template-Type: ReDIF-Article 1.0
Author-Name: Yun Dong
Author-X-Name-First: Yun
Author-X-Name-Last: Dong
Author-Name: Ren Zhao
Author-X-Name-First: Ren
Author-X-Name-Last: Zhao
Author-Name: Wen Xu
Author-X-Name-First: Wen
Author-X-Name-Last: Xu
Author-Name: Miao Yang
Author-X-Name-First: Miao
Author-X-Name-Last: Yang
Author-Name: Wei Jiang
Author-X-Name-First: Wei
Author-X-Name-Last: Jiang
Title: Integrated optimisation of consolidation and stowage planning of steel coil ships using differential evolution
Abstract: 
 Consolidation plan (CP) and stowage plan (SP) of coil ships are to assign steel coils onto ships and decide specific loading location for each coil, respectively, which are two correlative and adjacent plans in the finished product logistics of iron and steel industry. In this paper, we focus on the problem of making an integrated plan of CP and SP (C&SPP), which is important and rarely studied, to try to achieve systematic optimisation from the perspectives of the product terminal, shipping companies, and customers, simultaneously. First, according to the practical situation, an integer programming (IP) model is established to optimise ship loading, transportation timeliness, and operation efficiency. Then, to improve calculating efficiency, the IP model is simplified (SIP) by reducing the dimensions of variables. After that, based on the problem features and algorithm behaviour, an improved differential evolution algorithm is proposed in which an element-dependent strategy is designed to set control parameter, a guided operator is constructed to generate mutant individual and an iteration-based mechanism is introduced to dynamically adjust the parameter and mutation strategy, respectively. Finally, extensive experiments are carried out to evaluate the proposed method, and the numerical results demonstrate its effectiveness in solving practical scale C&SPP.
Journal: International Journal of Production Research
Pages: 1239-1257
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1722323
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1722323
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:4:p:1239-1257




Template-Type: ReDIF-Article 1.0
Author-Name: Bikash Koli Dey
Author-X-Name-First: Bikash Koli
Author-X-Name-Last: Dey
Author-Name: Sarla Pareek
Author-X-Name-First: Sarla
Author-X-Name-Last: Pareek
Author-Name: Muhammad Tayyab
Author-X-Name-First: Muhammad
Author-X-Name-Last: Tayyab
Author-Name: Biswajit Sarkar
Author-X-Name-First: Biswajit
Author-X-Name-Last: Sarkar
Title: Autonomation policy to control work-in-process inventory in a smart production system
Abstract: 
 The necessity of optimum safety stock is really essential for any smart production system. For this reason, the effect of autonomation policy makes a big difference with the basic traditional automation policy. Basically, for a long-run production system, a process may transfer to an ‘out-of-control’ state from an ‘in-control’ state due to labour problems, machinery problems, or any kind of energy problems. During this ‘out-of-control’ state, machines produced imperfect items instead of perfect items. As a result, an inspection is required to identify the imperfect ones. Until now, this inspection has been utilised by human beings through the traditional automation policy and inspection errors may occur. To perform an error-free inspection, an autonomation policy is examined in this model to detect imperfect items from the production process, which makes the process smarter. The defective rate is random and follows a certain distribution. A budget and a space constraints are adopted, which makes the model non-linear with a constraint problem. Contradictory to the existing literature, the demand is price- and quality-sensitive together in a smart production system. To solve this non-linear problem with an optimised value of backorders, number of delivery lots, safety factors, and collection rate, a non-linear optimisation technique (Khun–Tucker optimisation technique) is employed. A numerical example and sensitivity analysis are provided to illustrate the model. The result finds that the optimum autonomation policy can save work-in-process inventory at the optimum value of the decision variable in the proposed model.
Journal: International Journal of Production Research
Pages: 1258-1280
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1722325
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1722325
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:4:p:1258-1280




Template-Type: ReDIF-Article 1.0
Author-Name: Weixiang Huang
Author-X-Name-First: Weixiang
Author-X-Name-Last: Huang
Author-Name: Wenhui Zhou
Author-X-Name-First: Wenhui
Author-X-Name-Last: Zhou
Author-Name: Pengfei Guo
Author-X-Name-First: Pengfei
Author-X-Name-Last: Guo
Author-Name: Han Zhu
Author-X-Name-First: Han
Author-X-Name-Last: Zhu
Title: Service segment competition: size or value, which matters?
Abstract: 
 We study a service market with two firms: one that provides regular and another that provides premium services. Customers are delay sensitive and heterogeneous in evaluating the service level. We study two competition games that differ in segmentation-marketing strategies. One is the size-based competition in which firms compete on the segment size dimension, and the other is the value-based competition in which firms compete on the segment target (regarding customer valuation) dimension. For both games, the Nash equilibrium always exists, and the (Pareto dominant) equilibrium is unique. Interestingly, the premium service provider's effective arrival rate can be increasing in its competitor's service rate in the value-based game. Moreover, we capture the conditions for the equilibrium market as either a monopoly or a duopoly and show that size-based competition helps sustain service variety. We also show that the prices are reduced in the value-based game; the premium (regular) service provider serves more (fewer) customers in the value-based game than in the size-based game. Our results show that value-based competition is more intensive in the sense that the number of customers who are served, customer surplus and social welfare are higher, while the total revenue of two firms is lower in the value-based competition than in the size-based competition.
Journal: International Journal of Production Research
Pages: 1281-1299
Issue: 4
Volume: 59
Year: 2021
Month: 2
X-DOI: 10.1080/00207543.2020.1722328
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1722328
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Template-Type: ReDIF-Article 1.0
Author-Name: Mark Baxendale
Author-X-Name-First: Mark
Author-X-Name-Last: Baxendale
Author-Name: James M. McGree
Author-X-Name-First: James M.
Author-X-Name-Last: McGree
Author-Name: Aaron Bellette
Author-X-Name-First: Aaron
Author-X-Name-Last: Bellette
Author-Name: Paul Corry
Author-X-Name-First: Paul
Author-X-Name-Last: Corry
Title: Machine-based production scheduling for rotomoulded plastics manufacturing
Abstract: 
 In this paper, production scheduling for rotomoulded plastics manufacturing in a multi-machine environment is considered. The objective is to minimise total tardiness. The problem has some commonality with hybrid flow shop scheduling with batching, where additional constraints are needed to control which machines may be used at each stage. The problem is shown to be NP-hard and is formulated as a mixed integer program. Given consequently large solve times to obtain optimal solutions, simulated annealing and tabu search algorithms were developed alongside a constructive heuristic to obtain near-optimal solutions within a practical time-frame. The solution algorithms were tuned and tested using randomly generated problem instances. The best results in terms of solution quality were generally obtained by simulated annealing. The problem instances were generated to be representative of a real production environment located in Queensland, Australia.
Journal: International Journal of Production Research
Pages: 1301-1318
Issue: 5
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1727046
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1727046
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1301-1318




Template-Type: ReDIF-Article 1.0
Author-Name: Yanhe Jia
Author-X-Name-First: Yanhe
Author-X-Name-Last: Jia
Author-Name: Zhe George Zhang
Author-X-Name-First: Zhe George
Author-X-Name-Last: Zhang
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Title: M/PH/C queue under a congestion-based staffing policy with applications in steel industry operations
Abstract: 
 To avoid either idle servers or an over-congested situation, we analyse a queueing system with a variable number of servers. Specifically, if the queue length exceeds an upper threshold, all of the servers are serving customers, and if the number of idle servers reaches a threshold (or the number of customers is below a lower threshold), these idle servers are turned off. We call this policy Congestion-Based Staffing (CBS) with two thresholds. Optimising these thresholds under a certain cost structure is the focus of this paper. The key factor in modelling a manufacturing or service system with random service requests by a queueing model is to realistically model the random service times. Although the exponential distribution has been used successfully to model the service times of a call centre, it is not appropriate for manufacturing or service systems. We propose to use a Phase-type (PH) distribution for modelling the service times in a manufacturing system, as it is more flexible and can fit any shape of distribution in theory. Therefore, we build an M/PH/C model with the CBS policy and develop a solution procedure for computing the queue length stationary distribution. Based on this stationary distribution, we investigate a real-world system in the Shanghai Baoshan Iron and Steel Complex. Using the real data and a realistic cost structure, we determine the optimal CBS policy in terms of minimising the operating cost. This policy yields an operating cost that is considerably smaller than the operating cost under a practical policy.
Journal: International Journal of Production Research
Pages: 1319-1330
Issue: 5
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1735656
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735656
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1319-1330




Template-Type: ReDIF-Article 1.0
Author-Name: Jafar Namdar
Author-X-Name-First: Jafar
Author-X-Name-Last: Namdar
Author-Name: S. Ali Torabi
Author-X-Name-First: S. Ali
Author-X-Name-Last: Torabi
Author-Name: Navid Sahebjamnia
Author-X-Name-First: Navid
Author-X-Name-Last: Sahebjamnia
Author-Name: Ninad Nilkanth Pradhan
Author-X-Name-First: Ninad
Author-X-Name-Last: Nilkanth Pradhan
Title: Business continuity-inspired resilient supply chain network design
Abstract: 
 Supply chains are prone to several operational and disruption risks. In order to design a resilient supply chain network capable of responding to such potential risks suitably, this paper proposes a novel framework for the business continuity-inspired resilient supply chain network design (BCRSCND) problem, which includes three steps. First, four resilience dimensions including Anticipation, Preparation, Robustness, and Recovery are considered to quantify the resilience score of each facility using a multi-criteria decision-making technique and considering a comprehensive set of resilience strategies. In the second step, the critical processes and their business continuity metrics (which are vital for supply chain continuity), are identified. The outputs of the first two steps provide the inputs of a novel two-stage mixed possibilistic-stochastic programing (TSMPSP) model. The model aims to design a multi-echelon, multi-product resilient supply chain network under both operational and disruption risks. The proposed TSMPSP model allows decision makers to incorporate their risk attitudes into the design process. After converting the original TSMPSP model into the crisp counterpart, several sensitivity analyses are conducted on different features of hypothetical disruptions (i.e. their severity, likelihood and location) and DM’s risk attitudes from which useful managerial insights are provided.
Journal: International Journal of Production Research
Pages: 1331-1367
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1798033
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1798033
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1331-1367




Template-Type: ReDIF-Article 1.0
Author-Name: Nguyen Quoc Viet
Author-X-Name-First: Nguyen Quoc
Author-X-Name-Last: Viet
Author-Name: Behzad Behdani
Author-X-Name-First: Behzad
Author-X-Name-Last: Behdani
Author-Name: Jacqueline Bloemhof
Author-X-Name-First: Jacqueline
Author-X-Name-Last: Bloemhof
Author-Name: Kai Hoberg
Author-X-Name-First: Kai
Author-X-Name-Last: Hoberg
Title: Value of data in multi-level supply chain decisions: a case study in the Dutch floriculture sector
Abstract: 
 While many supply chain decisions could take advantage of big data, firms struggle with investments into supply chain analytics since they are not able to assess the application areas and benefits of these initiatives. In this paper, we provide a multi-level perspective to assess the value of supply chain data. We develop a framework that highlights the connections between data characteristics and supply chain decisions with different time horizons (i.e. short- or long-term) as well as different supply chain levels (i.e. individual-firm level or supply-chain level). As data gets more complex in one or more of the 4 V dimensions (i.e. volume, variety, velocity, veracity), firms must assess how to best take advantage of the opportunities offered. We use the Dutch floriculture sector as a case study for our framework in which we highlight four data analytics applications to improve logistics processes. In the applications, we demonstrate how the data is used to support the decisions at different time horizons and supply-chain levels. We find that each of the big data’s Vs is required differently according to the decisions’ characteristics. Based on the findings, applications in other industries and promising directions for future research are discussed.
Journal: International Journal of Production Research
Pages: 1368-1385
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1821116
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1821116
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1368-1385




Template-Type: ReDIF-Article 1.0
Author-Name: Maria Pia Ciano
Author-X-Name-First: Maria Pia
Author-X-Name-Last: Ciano
Author-Name: Patrick Dallasega
Author-X-Name-First: Patrick
Author-X-Name-Last: Dallasega
Author-Name: Guido Orzes
Author-X-Name-First: Guido
Author-X-Name-Last: Orzes
Author-Name: Tommaso Rossi
Author-X-Name-First: Tommaso
Author-X-Name-Last: Rossi
Title: One-to-one relationships between Industry 4.0 technologies and Lean Production techniques: a multiple case study
Abstract: 
 Production research literature and industry practice have started to pay increasing attention to the Industry 4.0 (I4.0) phenomenon. Scholars and practitioners identified a strong link between this paradigm and the well-known Lean Production (LP) paradigm. Most studies consider LP as a prerequisite of I4.0 and I4.0 as a tool to overcome LP limits and boost its practices. However, so far, these effects have been studied only at a high level, without an in-depth and comprehensive pairwise analysis at a practice-technology level. Moreover, few empirical studies have been carried out on this topic. Our paper attempts to fill these gaps by conducting a multiple case studies research to explain the one-to-one relationships between LP techniques and I4.0 technologies, and vice versa. More specifically, the one-to-one analysis examines the enabling effect of LP on I4.0 and the empowering effect of I4.0 on LP. Based on the empirical analyses, we propose a framework on the relationships between the two paradigms structured into six areas drawn from previous research (i.e. manufacturing equipment and processes, shop-floor management, workforce management, new product development, supplier relationships, customer relationships). Such representation clarifies the interdependence of the two paradigms in the whole supply chain.
Journal: International Journal of Production Research
Pages: 1386-1410
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1821119
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1821119
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1386-1410




Template-Type: ReDIF-Article 1.0
Author-Name: Baofeng Huo
Author-X-Name-First: Baofeng
Author-X-Name-Last: Huo
Author-Name: Muhammad Zia Ul Haq
Author-X-Name-First: Muhammad Zia Ul
Author-X-Name-Last: Haq
Author-Name: Minhao Gu
Author-X-Name-First: Minhao
Author-X-Name-Last: Gu
Title: The impact of information sharing on supply chain learning and flexibility performance
Abstract: 
 Despite the importance of supply chain learning for competitiveness, little is known about how to enable such learning. This study empirically investigates the impact of information sharing on different types of supply chain learning (internal, supplier, and customer learning) and their influences on flexibility performance. Grounded in absorptive capacity theory, we use structural equation modelling to test the conceptual model based on data collected from 213 manufacturing firms in China. We find that supplier and customer learning improve internal learning. Further, our findings indicate that information sharing improves all three dimensions of supply chain learning. We also find that internal and customer learning have direct influences on flexibility performance, whereas internal learning mediates the relationship between supplier learning and flexibility performance. Moreover, information sharing moderates the relationship between supplier learning and flexibility performance. Our findings contribute to the literature and offer a new framework to understand the relationship between information sharing, supply chain learning and flexibility performance. The findings also furnish managers to seek competitive advantage through information sharing and supply chain learning.
Journal: International Journal of Production Research
Pages: 1411-1434
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1824082
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1824082
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1411-1434




Template-Type: ReDIF-Article 1.0
Author-Name: Alessandro Ancarani
Author-X-Name-First: Alessandro
Author-X-Name-Last: Ancarani
Author-Name: Carmela Di Mauro
Author-X-Name-First: Carmela Di
Author-X-Name-Last: Mauro
Author-Name: Yuan Virtanen
Author-X-Name-First: Yuan
Author-X-Name-Last: Virtanen
Author-Name: Weimu You
Author-X-Name-First: Weimu
Author-X-Name-Last: You
Title: From China to the West: why manufacturing locates in developed countries
Abstract: 
 This article analyses the competitive priorities underlying manufacturing location initiatives in developed economies. Specifically, building on secondary data, we compare and contrast manufacturing backshoring from China by companies headquartered in developed economies (308 cases) and Chinese foreign direct investment to developed economies (155 cases). Results suggest that both types of initiatives share some common priorities, such as exploiting the ‘country of origin’ effect and innovation opportunities in developed countries. At the same time, results highlight differences that may be attributed to the home country of the firm. In particular, cost priorities appear to be more important for Chinese companies than for backshoring ones. Findings offer insight into why manufacturing in developed economies may expand as a result of both repatriations and of foreign direct investments from emerging economies such as China, and point to potential areas of policy intervention.
Journal: International Journal of Production Research
Pages: 1435-1449
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1824083
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1824083
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1435-1449




Template-Type: ReDIF-Article 1.0
Author-Name: Yingli Wang
Author-X-Name-First: Yingli
Author-X-Name-Last: Wang
Author-Name: Catherine Huirong Chen
Author-X-Name-First: Catherine Huirong
Author-X-Name-Last: Chen
Author-Name: Ahmed Zghari-Sales
Author-X-Name-First: Ahmed
Author-X-Name-Last: Zghari-Sales
Title: Designing a blockchain enabled supply chain
Abstract: 
 While blockchain technologies are gaining momentum within supply chains, academic understanding of concrete, real-life design and implementation is still lagging, hence offering very limited insights into the true implications of blockchain technology on supply chains. This paper reports a two-year design science research (DSR) study of a smart contract initiative piloted by a consortium in the UK’s construction sector. We seek answers to the research question, ‘How should a blockchain enabled supply chain be designed?’ Guided by the theory of business model, we explore how a group of supply chain actors collectively designs and pilots a blockchain solution that addresses the supply chain transparency and provenance problem. Our research is one of the very few longitudinal empirical studies to offer in-depth evidence about how blockchain is deployed in complex multi-tier supply chain networks. In compliance with DSR research paradigm, we make contributions at three levels: designing and instantiating the blockchain architect and proving its utility in addressing the target problem; developing a set of design principles as a mid-range theory that can be applied and tested in different blockchain supply chain contexts; and refining and extending the kernel theory of business value at supply chain network level.
Journal: International Journal of Production Research
Pages: 1450-1475
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1824086
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1824086
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1450-1475




Template-Type: ReDIF-Article 1.0
Author-Name: Yutian Chen
Author-X-Name-First: Yutian
Author-X-Name-Last: Chen
Author-Name: Hui Xiong
Author-X-Name-First: Hui
Author-X-Name-Last: Xiong
Author-Name: Ying-Ju Chen
Author-X-Name-First: Ying-Ju
Author-X-Name-Last: Chen
Title: Should traditional retailers function as pre-warehouses of online retailers?
Abstract: 
 We construct a supply chain to investigate the reason why it is uncommon for the traditional retailer to function as the pre-warehouse of the online retailer. The product only offered by the traditional retailer is labelled as the differentiated product, while the product supplied by both the traditional retailer and the third-party suppliers is called the common product. As the online retailer' common product competes directly with the differentiated product, whether the traditional retailer should supply the common product becomes sophisticated. In this paper, we identify an intrinsic rationale for the traditional retailer not to supply the common product, even if he is unambiguously cost advantageous vis-a-vis the third-party suppliers. This is because the online retailer's order serves as a commitment device that puts the traditional retailer at the disadvantageous follower's position in the differentiated and common products competition; moreover, this quantity commitment allows the online retailer to clinch a better bargaining position on the differentiated product. We further show that it never pays the online retailer to split orders between the traditional retailer and the third-party suppliers. Our results are robust against the traditional retailer's capacity constraint, consumers' preference over differentiated and common products, and supply chain contractual form.
Journal: International Journal of Production Research
Pages: 1476-1495
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1825864
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1825864
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1476-1495




Template-Type: ReDIF-Article 1.0
Author-Name: V. L. Bittencourt
Author-X-Name-First: V. L.
Author-X-Name-Last: Bittencourt
Author-Name: A.C. Alves
Author-X-Name-First: A.C.
Author-X-Name-Last: Alves
Author-Name: C. P. Leão
Author-X-Name-First: C. P.
Author-X-Name-Last: Leão
Title: Industry 4.0 triggered by Lean Thinking: insights from a systematic literature review
Abstract: 
 Lean Thinking has successfully challenged mass production practices, by providing ‘leaner’ processes and supply chains, i.e. with less waste. Industry 4.0 has become an important strategic approach in the technological change of manufacturing and others. It aims to connect the physical and virtual worlds in industrial production. With such automation associated with Industry 4.0, questions arise about the synergy between this approach and the role of Lean in this ongoing industrial revolution. Therefore, a systematic literature review was carried out in order to identify the role of Lean in this scenario. The review was conducted from 2011 to 2019 timeframe and resulted in a total of 33 papers. This review demonstrated this as an emerging research area with most of the studies published in recent years (2017–2019). A deep analysis was undertaken to understand the Lean effect as a trigger for Industry 4.0. Main findings from a 15 out of the 33 papers revealed elements and facts found in sentences of such papers that act as this trigger. Additionally, a words count indicated that management, processes and people were the most cited words by the 15 papers, reinforcing the role of these key players in the companies’ transformation.
Journal: International Journal of Production Research
Pages: 1496-1510
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1832274
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1832274
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1496-1510




Template-Type: ReDIF-Article 1.0
Author-Name: Shanshan Li
Author-X-Name-First: Shanshan
Author-X-Name-Last: Li
Author-Name: Yong He
Author-X-Name-First: Yong
Author-X-Name-Last: He
Author-Name: Stefan Minner
Author-X-Name-First: Stefan
Author-X-Name-Last: Minner
Title: Dynamic compensation and contingent sourcing strategies for supply disruption
Abstract: 
 Alternative measures to deal with supply disruptions exist. We consider a make-to-order (MTO) supply chain with one manufacturer who sources from a single supplier. When a supply disruption occurs, the manufacturer can choose to satisfy some demand by either maintaining production through safety stocks or through a secondary contingent source, and turn some unmet demand into backorders on the basis of compensation. An optimal control model under consideration of the customers’ dynamic reactions to the joint implementation of these strategies is formulated with the objective of minimising the cost of disruption. Through the application of Pontryagin's Maximum Principle, optimal mitigation strategies are established in closed form. They provide analytical guidance on how to dynamically and jointly adapt the quantity of contingent sourcing, the price of compensation, and the speed of safety inventory consumption. The results indicate how cost and time-related factors impact these strategies. We also demonstrate that pure strategies are only effective in tackling short supply shortages. For long disruptions, it is superior to adopt combined strategies that simultaneously incorporate two countermeasures in certain periods.
Journal: International Journal of Production Research
Pages: 1511-1533
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1840643
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1840643
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1511-1533




Template-Type: ReDIF-Article 1.0
Author-Name: Y. P. Tsang
Author-X-Name-First: Y. P.
Author-X-Name-Last: Tsang
Author-Name: C. H. Wu
Author-X-Name-First: C. H.
Author-X-Name-Last: Wu
Author-Name: H. Y. Lam
Author-X-Name-First: H. Y.
Author-X-Name-Last: Lam
Author-Name: K. L. Choy
Author-X-Name-First: K. L.
Author-X-Name-Last: Choy
Author-Name: G. T. S. Ho
Author-X-Name-First: G. T. S.
Author-X-Name-Last: Ho
Title: Integrating Internet of Things and multi-temperature delivery planning for perishable food E-commerce logistics: a model and application
Abstract: 
 With the rapid growth of perishable food e-commerce businesses, there is a definite need for logistics services providers to manage parcel shipments with multi-temperature requirements. E-commerce characteristics, including time-critical delivery, fragmented orders, and high product variety, should be further considered to extend the ontology of multi-temperature joint distribution. However, traditional delivery route planning is insufficient because it merely minimises the cost of travelling between customer locations. Factors related to food quality and arrival time windows should also be considered. In addition, handling dynamic incident management, such as violations of handling requirements during delivery, is lacking. This leads to the likelihood of food deteriorating before it reaches the consumers, thereby impacting customer satisfaction. This paper proposes an Internet of Things–based multi-temperature delivery planning system (IoT-MTDPS), embedding a two-phase multi-objective genetic algorithm optimiser (2PMGAO). The formulation of delivery routing mainly considers product-dependent multi-temperature characteristics, service level, transportation cost, and number of trucks. Once there are unexpected incidents which are detected by Internet of Things technologies, 2PMGAO can optimise the membership functions of fuzzy logic for re-routing the e-commerce delivery plan. With using IoT-MTDPS, the capability of handling e-commerce orders is enhanced, while customer satisfaction can be maintained at a designated level.
Journal: International Journal of Production Research
Pages: 1534-1556
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1841315
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1841315
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Template-Type: ReDIF-Article 1.0
Author-Name: Juri Reich
Author-X-Name-First: Juri
Author-X-Name-Last: Reich
Author-Name: Aseem Kinra
Author-X-Name-First: Aseem
Author-X-Name-Last: Kinra
Author-Name: Herbert Kotzab
Author-X-Name-First: Herbert
Author-X-Name-Last: Kotzab
Author-Name: Xavier Brusset
Author-X-Name-First: Xavier
Author-X-Name-Last: Brusset
Title: Strategic global supply chain network design – how decision analysis combining MILP and AHP on a Pareto front can improve decision-making
Abstract: 
 Integrating a broad range of information types and finding trade-offs between conflicting goals is a challenge in global supply chain network design (GSCND). Effective decision support systems (DSS) should be user-friendly, provide transparency, and support human judgement. There is a wide range of optimisation models that aim to improve the outcome of network design decisions. However, their practical performance often remains unknown, as their implementation into the managerial decision process is largely neglected. Such theory-driven models usually focus on single aspects of the decision, without being able to accommodate the practical problem comprehensively. We employ the CIMO approach to resolve the issue and contribute by showing how an integration involving these methods can be useful for managers once the proper knowledge transfer has been effectuated. An innovative decision support framework, which combines mixed-integer linear programming, the Analytical Hierarchy Process, and the Pareto front is created and analysed during a case study in the med-tech industry. Results show that the framework accommodates managerial experience, integrates qualitative as well as quantitative criteria, and provides transparency over the entire range of efficient solutions. The framework and application results contribute towards the development of more flexible and easy-to-use decision support systems for GSCND.
Journal: International Journal of Production Research
Pages: 1557-1572
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1847341
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1847341
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Template-Type: ReDIF-Article 1.0
Author-Name: Jie Yang
Author-X-Name-First: Jie
Author-X-Name-Last: Yang
Author-Name: Hongming Xie
Author-X-Name-First: Hongming
Author-X-Name-Last: Xie
Author-Name: Guangsheng Yu
Author-X-Name-First: Guangsheng
Author-X-Name-Last: Yu
Author-Name: Mingyu Liu
Author-X-Name-First: Mingyu
Author-X-Name-Last: Liu
Title: Antecedents and consequences of supply chain risk management capabilities: an investigation in the post-coronavirus crisis
Abstract: 
 This study evaluates the antecedents and consequences of supply chain risk management capabilities. Informed by the information processing theory, we conceptualize supply chain disruption orientation as an organic control and supply chain visibility as a mechanistic control. Both control mechanisms build the information processing capacities, which need to fit with the information processing requirements imposed by disruption impact during the adverse supply chain disruptions in the wake of the Coronavirus Covid-19 pandemic. When the fit is realized, supply chain risk management capabilities will be improved. This study also examines the role of supply chain risk management capabilities in bolstering supply chain resilience to the catastrophic occurrence. Our findings indicate the fit between information processing capacities and requirements enhances supply chain risk management capabilities, which, in turn, result in enhanced supply chain resilience.
Journal: International Journal of Production Research
Pages: 1573-1585
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1856958
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856958
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Template-Type: ReDIF-Article 1.0
Author-Name: Rameshwar Dubey
Author-X-Name-First: Rameshwar
Author-X-Name-Last: Dubey
Author-Name: David J. Bryde
Author-X-Name-First: David J.
Author-X-Name-Last: Bryde
Author-Name: Cyril Foropon
Author-X-Name-First: Cyril
Author-X-Name-Last: Foropon
Author-Name: Manisha Tiwari
Author-X-Name-First: Manisha
Author-X-Name-Last: Tiwari
Author-Name: Yogesh Dwivedi
Author-X-Name-First: Yogesh
Author-X-Name-Last: Dwivedi
Author-Name: Sarah Schiffling
Author-X-Name-First: Sarah
Author-X-Name-Last: Schiffling
Title: An investigation of information alignment and collaboration as complements to supply chain agility in humanitarian supply chain
Abstract: 
 Our study examines the relationship between information alignment (IA), collaboration (CO) and supply chain agility (SCAG) under the moderating effects of artificial intelligence-driven big data analytics capability (AI-BDAC) and intergroup leadership (IGL). We have grounded our theoretical model in the resource-based view (RBV) and contingency theory and further tested our research hypotheses using multi-informant data collected using a web-based pre-tested instrument from 613 individuals working in 193 humanitarian organisations drawn from 24 countries located on various continents across the globe. We tested our research hypotheses using variance-based structural equation modelling (PLS-SEM). Our study offers interesting results which help to advance the theoretical debates surrounding technology-driven supply chain agility in the context of humanitarian settings. We further provide some directions to managers engaged in disaster relief operations, who are contemplating using emerging technologies to enhance collaboration and supply chain agility. Finally, we have outlined the limitations of our study and offer some future research directions.
Journal: International Journal of Production Research
Pages: 1586-1605
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1865583
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1865583
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Template-Type: ReDIF-Article 1.0
Author-Name: Zoé Krug
Author-X-Name-First: Zoé
Author-X-Name-Last: Krug
Author-Name: Romain Guillaume
Author-X-Name-First: Romain
Author-X-Name-Last: Guillaume
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Title: Exploring the opportunities in establishing a closed-loop supply chain under uncertainty
Abstract: 
 Reverse supply chains (RSC) may provide the benefits of reducing pollution, creating new jobs, and generating income from the recyclable materials. However, their implementation comes with risks and hardly predictable outcomes. The model presented in this paper aims to help managers to better evaluate risks and opportunities while deciding on the RSC design to manage the reverse flow of end-of-life (EOL) products in an existing supply chain. The goal is to set up the disassembly and recovery facilities and organize the flows between them while maximizing total network profit. We propose a two-stage multi-period mixed-integer program where the budget available for decisions at each period depends on the outcomes of previous periods. The demand for EOL products, the quantity of products returned and the time required to reprocess these products are considered uncertain. To incorporate this uncertainty into the decision making process, a discrete set of scenarios is defined. To take into account the decision maker's behavior in the areas of risks and opportunities, we propose to use 
$R_*$R∗ criterion to select the final solution. To demonstrate the relevance of 
$R_*$R∗ criterion, we conduct numerical investigations on an adapted case study from the literature and do a comparison with classic well-known criteria.
Journal: International Journal of Production Research
Pages: 1606-1625
Issue: 5
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1808259
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1808259
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Template-Type: ReDIF-Article 1.0
Author-Name: Tariq Masood
Author-X-Name-First: Tariq
Author-X-Name-Last: Masood
Author-Name: Maximilian Kern
Author-X-Name-First: Maximilian
Author-X-Name-Last: Kern
Author-Name: P. John Clarkson
Author-X-Name-First: P.
Author-X-Name-Last: John Clarkson
Title: Characteristics of changeable systems across value chains
Abstract: 
 Engineering changes (ECs) are inevitable for businesses due to increasing innovation, shorter lifecycles, technology and process improvements and cost reduction initiatives. The ECs could propagate and cause further changes due to existing system dependencies, which can be challenging. Hence, change management (CM) is a relevant discipline, which aims to reduce the impact of changes. EC assessment methods form the basis of CM that support in assessing system dependencies and the impact of changes. However, understanding of which factors influence the changeability across value chains (VCs) is limited. This research adopted a VC approach to EC assessment. Dependencies in products and processes were captured, followed by risk (i.e. likelihood x impact) assessment of ECs using change prediction method (CPM). Four industrial case studies were conducted (3x automotive, 1x furniture manufacturing) to identify design (product) and manufacturing (process) elements with high risk to be affected by ECs. Based on the case results, characteristics were identified that influence changeability across VC. This contributed to the CM domain while businesses could also use the results to assess ECs across VC, and improve the design of products and processes by increasing their changeability across VC e.g. by proactive decoupling or reactive handling of system dependencies.
Journal: International Journal of Production Research
Pages: 1626-1648
Issue: 6
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1791997
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1791997
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Template-Type: ReDIF-Article 1.0
Author-Name: Seyyed-Mahdi Hosseini-Motlagh
Author-X-Name-First: Seyyed-Mahdi
Author-X-Name-Last: Hosseini-Motlagh
Author-Name: Mohammadreza Nematollahi
Author-X-Name-First: Mohammadreza
Author-X-Name-Last: Nematollahi
Author-Name: Nazanin Nami
Author-X-Name-First: Nazanin
Author-X-Name-Last: Nami
Title: Drug recall management and channel coordination under stochastic product defect severity: a game-Theoretic analytical study
Abstract: 
 This paper analytically explores drug recall programmes in the pharmaceutical industry by considering the product defect severity as a source of uncertainty. Under the Stackelberg game model, a pharma-manufacturer outsources the drug recall management and pays collecting fees to a third party logistics provider (3PL) for collecting the defective medications. On the other side, the 3PL provides incentives to customers to facilitate product recall. In this research, we first analytically show the negative effect of lack of coordination between the pharma-manufacturer and 3PL. Then, a new coordination model, namely collecting fee agreement is proposed under which the pharma-manufacturer aims to motivate the 3PL to collect more defective medications. This research also analytically explores the effect of orchestrating the collecting fees and incentives under stochastic product defect severity. Finally, a Nash-bargaining game model is proposed to share the profits between the pharma-manufacturer and 3PL under the collecting fee agreement. Both analytical and numerical results reveal that the collecting fee agreement not only increases the collection rate of defective items and protects the patients from unsafe products, but also simultaneously improves the performances of whole pharmaceutical supply chain and its members while reducing the governmental penalties imposed on the pharma-manufacturer.
Journal: International Journal of Production Research
Pages: 1649-1675
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1723813
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1723813
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Template-Type: ReDIF-Article 1.0
Author-Name: Xin Liu
Author-X-Name-First: Xin
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Title: Service-oriented bi-objective robust collection-disassembly problem with equipment selection
Abstract: 
 The collection-disassembly problem plays an important role in a reverse supply chain. It coordinates the collection and disassembly activities for end-of-life (EOL) products. Most existing works consider the deterministic problems. However, in practice, demands of reusable components in EOL products may be uncertain. Besides, it is usually difficult to exactly obtain probability distributions of uncertain demands, due to inadequate historical data. This paper studies a collection-disassembly problem under partial known distributional information of component demands, in which equipments of the disassembly site, corresponding to different disassembly capacities, have to be selected. The objectives are to minimise the system cost and to maximise the customer service level. For the problem, a novel distributionally robust bi-objective formulation is proposed. Based on the Monte Carlo simulation and an ambiguity set, a sample average approximation (SAA) model and an approximated mixed integer programming (MIP) model are constructed, respectively. Then the two approximated formulations are solved, via the ε-constraint framework, and compared in numerical experiments.
Journal: International Journal of Production Research
Pages: 1676-1690
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1723815
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1723815
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Template-Type: ReDIF-Article 1.0
Author-Name: Weihua Liu
Author-X-Name-First: Weihua
Author-X-Name-Last: Liu
Author-Name: Wanying Wei
Author-X-Name-First: Wanying
Author-X-Name-Last: Wei
Author-Name: Meili Wang
Author-X-Name-First: Meili
Author-X-Name-Last: Wang
Author-Name: Ou Tang
Author-X-Name-First: Ou
Author-X-Name-Last: Tang
Author-Name: Li Zhou
Author-X-Name-First: Li
Author-X-Name-Last: Zhou
Title: Pricing decision with conspicuous customers: quick responses versus value-added services
Abstract: 
 In order to eliminate the negative effects of customer strategic behaviour, retailers often adopt quick response or value-added services. While in a luxury market with conspicuous customers, retailers’ pricing decisions of these two strategies become more complicated. This paper studies a supply chain with a retailer serving a mixture of conspicuous and ordinary strategic customers. We develop three models so that the retailer provides (i) neither quick response nor value-added services; (ii) only quick response; (iii) only value-added services. Subsequently, we analyse the impacts of conspicuous customers on quick response and value-added services by pricing and strategy comparisons. The model further extends to the situation including both strategies. The results show that, firstly, when the proportion is less than a threshold, the retailer should adopt a low price strategy, and vice versa. Besides, the quick response could induce the retailer to adopt high price while value-added services inhibit it. Secondly, the customer conspicuous behaviour can motivate retailers to provide quick response and inhibit their value-added services. Finally, by observing the retailer's decisions when they can adopt two strategies simultaneously, we find that the existence of quick response can amplify the benefits of value-added services.
Journal: International Journal of Production Research
Pages: 1691-1713
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1724341
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1724341
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Template-Type: ReDIF-Article 1.0
Author-Name: Lina He
Author-X-Name-First: Lina
Author-X-Name-Last: He
Author-Name: Zhenyong Wu
Author-X-Name-First: Zhenyong
Author-X-Name-Last: Wu
Author-Name: Wei Xiang
Author-X-Name-First: Wei
Author-X-Name-Last: Xiang
Author-Name: Mark Goh
Author-X-Name-First: Mark
Author-X-Name-Last: Goh
Author-Name: Zhitao Xu
Author-X-Name-First: Zhitao
Author-X-Name-Last: Xu
Author-Name: Wenyan Song
Author-X-Name-First: Wenyan
Author-X-Name-Last: Song
Author-Name: Xinguo Ming
Author-X-Name-First: Xinguo
Author-X-Name-Last: Ming
Author-Name: Xiao Wu
Author-X-Name-First: Xiao
Author-X-Name-Last: Wu
Title: A novel Kano-QFD-DEMATEL approach to optimise the risk resilience solution for sustainable supply chain
Abstract: 
 Sustainable supply chain management plays an important role in company’s sustainability success. As the frequently emerging disruptions may harm supply chain’s sustainable performance, managers need to design an effective sustainable supply chain (SSC) resilience solution to mitigate different risks. In addition, it is critical to integrate customer requirements (CRs) in SSC resilience solution design as SSC’s performance is highly determined by customer satisfaction (CS) in the customer-oriented market. This article proposes an integrative approach to achieve an effective design of SSC resilience solution, taking both CRs and risk factors (RFs) into consideration. In this study, the Kano model, decision-making and trial evaluation laboratory (DEMATEL) are integrated with quality function deployment (QFD) through nonlinear programming to guide companies’ design. Kano model is employed to analyse CRs qualitatively and quantitatively to determine each CR’s priority and CS. DEMATEL is adopted to determine the RFs’ interrelationships. The results obtained with the Kano model and DEMATEL are incorporated into QFD to transform CRs into RFs, and then into resilience measures. Furthermore, a nonlinear optimisation model is formulated to achieve the optimal resilience solution with maximised CS and risk mitigation under minimum cost investment. Finally, a case study is conducted to verify the methodology.
Journal: International Journal of Production Research
Pages: 1714-1735
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1724343
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1724343
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuchen Li
Author-X-Name-First: Yuchen
Author-X-Name-Last: Li
Author-Name: Ibrahim Kucukkoc
Author-X-Name-First: Ibrahim
Author-X-Name-Last: Kucukkoc
Author-Name: Xiaowen Tang
Author-X-Name-First: Xiaowen
Author-X-Name-Last: Tang
Title: Two-sided assembly line balancing that considers uncertain task time attributes and incompatible task sets
Abstract: 
 An assembly line is a serial production system that is meant to produce high-quality and usually complex products in mass quantities. Assembly lines play a crucial role in determining the profitability of a company, as they are utilised as the final stage of the system prior to shipping. In an assembly line balancing problem, the assembly tasks are allocated to workstations based on their processing times after considering the precedence relationships between them. There is a massive amount of research in the literature using deterministic task processing times, and many other works consider stochastic task times. This research utilises the uncertainty theory to model uncertain task times and considers incompatible task sets constraints. The problem is solved using a simulated annealing algorithm with problem-specific characteristics. Lower bounds are developed to accelerate the simulated annealing algorithm. A restart mechanism, which can escape the local optimum obtained by neighbourhood generation, is proposed. A repair mechanism is integrated to combine the workstations so as to further improve the quality of solutions. The numerical examples and experimental tests demonstrate the powerful solution-building capacity of the proposed simulated annealing algorithm over teaching–learning-based and genetic algorithms. The methodology proposed in this research is applicable to any industry (including the automotive industry) when the historical data on task processing times is very limited.
Journal: International Journal of Production Research
Pages: 1736-1756
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1724344
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1724344
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Template-Type: ReDIF-Article 1.0
Author-Name: Jessica Olivares-Aguila
Author-X-Name-First: Jessica
Author-X-Name-Last: Olivares-Aguila
Author-Name: Waguih ElMaraghy
Author-X-Name-First: Waguih
Author-X-Name-Last: ElMaraghy
Title: System dynamics modelling for supply chain disruptions
Abstract: 
 Unexpected events or black swan events could highly deteriorate supply chain performance. Hence, proactive and reactive strategies should be considered when planning for disruptions in a multi-echelon supply chain. In this study, a system dynamics framework is introduced to observe the supply chain behaviour and evaluate the impacts of disruptions. The model enables the examination of full and partial disruptions and the incorporation of expediting orders after a disturbance. The effects of disruptions on the service levels, costs, profits and inventory levels, of the supply chain are analysed. The usage of the framework and the findings can serve to define disruption policies, and assist in the decisions relating to the supply chain design. After running several scenarios, it was determined that the disruptions happening in the downstream levels have more impacts on the SC performance than the disruptions in the upstream levels. Hence, the disruption policies for the downstream levels should have higher priority. Moreover, the results suggest that expediting after disruptions do not offer benefits to the long-term supply chain performance.
Journal: International Journal of Production Research
Pages: 1757-1775
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1725171
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1725171
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaobing Li
Author-X-Name-First: Xiaobing
Author-X-Name-Last: Li
Author-Name: Zhen He
Author-X-Name-First: Zhen
Author-X-Name-Last: He
Title: An integrated approach for evaluating hospital service quality with linguistic preferences
Abstract: 
 Hospital service quality (HSQ) evaluation is seriously challenged due to the uncertainties of evaluators’ subjective perception and the choice of evaluation methods. A new HSQ evaluation framework using 2-tuple Borda method is presented to reduce uncertainty of evaluation information and diversity of evaluation results and to provide more consensus evaluation result. A detailed case study, involving 25 evaluation criteria and 5 public hospitals, is conducted to demonstrate the proposed approach.
Journal: International Journal of Production Research
Pages: 1776-1790
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1725681
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1725681
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Template-Type: ReDIF-Article 1.0
Author-Name: Luping Zhang
Author-X-Name-First: Luping
Author-X-Name-Last: Zhang
Author-Name: Sicheng Zhang
Author-X-Name-First: Sicheng
Author-X-Name-Last: Zhang
Author-Name: Chunxia Yu
Author-X-Name-First: Chunxia
Author-X-Name-Last: Yu
Title: Network optimisation for transporting liquefied natural gas from stations to end customers
Abstract: 
 This paper presents an approach to optimise the liquefied natural gas (LNG) transportation network. As the Chinese government put forward the coal to gas heating convention project in its Jing-Jin-Yi area, demands of LNG increased dramatically in 2017, rising an emergent need for optimisation of current LNG transportation network. A number of tanker trucks with limited capacity, parking at truck centres are available for LNG transportation. Each truck loads LNG at refuelling stations, transports LNG to customers, and returns to the truck centre after the delivery. According to the size of orders, the problem is divided into two sub-problems: a big order problem (BOP) to deal with integral trucks of LNG demands, and a small order problem to fulfil fractional demands. Trucks can be sent from multiple truck centres; and trucks need to move the LNG in gas stations – pickup locations – to a series of customers – delivery locations. We formulate the BOP with integer programming, and provide a decomposition approach. For small order problem, a network representation and a mathematical model are presented. A tailored object-coding genetic algorithm is developed to solve the small order problem. Four purposely designed experiments are conducted to test its performance.
Journal: International Journal of Production Research
Pages: 1791-1813
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1725682
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1725682
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Template-Type: ReDIF-Article 1.0
Author-Name: Rishabh Rathore
Author-X-Name-First: Rishabh
Author-X-Name-Last: Rathore
Author-Name: J. J. Thakkar
Author-X-Name-First: J. J.
Author-X-Name-Last: Thakkar
Author-Name: J. K. Jha
Author-X-Name-First: J. K.
Author-X-Name-Last: Jha
Title: Impact of risks in foodgrains transportation system: a system dynamics approach
Abstract: 
 The purpose of this paper is to model dynamic feedback effects and complex interactions among risks affecting foodgrains transportation using a system dynamics approach. The risk scenario is simulated using a system dynamics model considering risk index values. It has been observed that there is a significant increase in inventory level from 8.39% to 28.4% and vehicle capacity from 8.99% to 28.4% with a change in risk value by 30%. This can help managers to develop inventory and transportation policies. It will, therefore, help to generate risk reduction scenarios for better availability of foodgrains through integrated risk control and mitigation in a supply chain. The key findings drawn for transportation and inventory management of foodgrains will help policy-makers to improve the efficiency of foodgrains supply chain. This research uniquely analyses the dynamic implication of inventory-transportation policies on foodgrains transportation system using system dynamics modelling approach.
Journal: International Journal of Production Research
Pages: 1814-1833
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1725683
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1725683
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Template-Type: ReDIF-Article 1.0
Author-Name: Nabin Sen
Author-X-Name-First: Nabin
Author-X-Name-Last: Sen
Author-Name: Sudarshan Bardhan
Author-X-Name-First: Sudarshan
Author-X-Name-Last: Bardhan
Author-Name: Bibhas Chandra Giri
Author-X-Name-First: Bibhas Chandra
Author-X-Name-Last: Giri
Title: Effectiveness of consignment stock policy under space limitations and deterioration
Abstract: 
 In joint economic lot-sizing problem for a two-echelon supply chain, the vendor delivers the entire production lot to the buyer by dividing it into a number of sub-batches, and ships each batch as soon as the buyer's inventory reduces to zero. On the contrary, in a consignment stocking policy, the vendor ships each sub-batch as soon as it is produced. These two generalised situations are modelled in this paper considering warehouse space limitations for the channel members (i.e. vendor and buyer) under both n-shipment and consignment stock policies where the items suffer from deterioration. Optimal results obtained by Genetic Algorithms (GAs) are compared through numerical examples to establish the superiority of one model over the other. The situations are also identified when one of the strategies would outperform another.
Journal: International Journal of Production Research
Pages: 1834-1851
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1727040
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1727040
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Template-Type: ReDIF-Article 1.0
Author-Name: Christos Koulamas
Author-X-Name-First: Christos
Author-X-Name-Last: Koulamas
Author-Name: George J. Kyparisis
Author-X-Name-First: George J.
Author-X-Name-Last: Kyparisis
Title: The no-wait flow shop with rejection
Abstract: 
 We consider the no-wait flow shop scheduling problem with rejection. We first show how to augment the travelling salesman problem formulation for the no-wait flow shop minimum makespan problem to incorporate the rejection option. We then focus on polynomially solvable cases by considering problems with ordered jobs. We present a third-order polynomial-time dynamic programming algorithm to minimise the sum of makespan and total rejection cost and faster quadratic algorithms for two special cases. We also present a third-order polynomial-time dynamic programming algorithm to minimise the sum of total completion time and total rejection cost with ordered jobs. We also exploit the duality between no-wait and no-idle flow shops to determine which operations to outsource in a no-idle flow shop with an outsourcing option.
Journal: International Journal of Production Research
Pages: 1852-1859
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1727042
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1727042
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:6:p:1852-1859




Template-Type: ReDIF-Article 1.0
Author-Name: Weidong Chen
Author-X-Name-First: Weidong
Author-X-Name-Last: Chen
Author-Name: Liming Li
Author-X-Name-First: Liming
Author-X-Name-Last: Li
Title: Incentive contracts for green building production with asymmetric information
Abstract: 
 When creating a product, a supplier faces the problem of designing the optimal contract to screen the manufacturer's private information. In this paper, we consider a manufacturer with private information about the cost type of production (N types defined in this paper) and its unobservable effort. Aiming to eliminate the negative effects on the green building market development caused by these two kinds of private information, we build a principal-agent model with asymmetric information. The optimal subsidy of the model is obtained by introducing the ‘spot check mechanism’. The results show that manufacturers with reasonable subsidies will not defraud the public about the actual quality of green buildings. Moreover, we discuss the impact of the probability of spot checks and subsidies on the optimal solution. Finally, a numerical example is given to show the effectiveness of the obtained results.
Journal: International Journal of Production Research
Pages: 1860-1874
Issue: 6
Volume: 59
Year: 2021
Month: 3
X-DOI: 10.1080/00207543.2020.1727047
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1727047
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Template-Type: ReDIF-Article 1.0
Author-Name: Sumit Maheshwari
Author-X-Name-First: Sumit
Author-X-Name-Last: Maheshwari
Author-Name: Prerna Gautam
Author-X-Name-First: Prerna
Author-X-Name-Last: Gautam
Author-Name: Chandra K. Jaggi
Author-X-Name-First: Chandra K.
Author-X-Name-Last: Jaggi
Title: Role of Big Data Analytics in supply chain management: current trends and future perspectives
Abstract: 
 It is a widely accepted fact that almost every research or business revolves around Data. Data from various business sectors has been growing sharply and the management of this massive amount of data is the biggest professional crunch these days. The notion of Big Data Analytics (BDA) is a prominent facet that delivers the best possible solution to decision-makers for efficiently handling the problems related to huge data. The key role of BDA in the area of Supply Chain Management (SCM), Logistics Management (LM), and Inventory Management (IM) is of utmost significance as it optimises the business operations by analyzing customer behaviour. Motivated with the promising paybacks of the BDA, a recent review from the year 2015–2019 is presented in this paper. Further, the significance of BDA in SCM, LM, and IM has been highlighted by studying 58 papers, which have been sorted after a detailed study of 260 papers, collected through the Web of Science (WoS) database. The findings and observations give state-of-the-art insights to scientists and business professionals by presenting an exhaustive list of the progress made and challenges left untackled in the field of BDA in SCM, LM, and IM.
Journal: International Journal of Production Research
Pages: 1875-1900
Issue: 6
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1793011
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1793011
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Template-Type: ReDIF-Article 1.0
Author-Name: Noelia Garcia-Buendia
Author-X-Name-First: Noelia
Author-X-Name-Last: Garcia-Buendia
Author-Name: José Moyano-Fuentes
Author-X-Name-First: José
Author-X-Name-Last: Moyano-Fuentes
Author-Name: Juan Manuel Maqueira-Marín
Author-X-Name-First: Juan Manuel
Author-X-Name-Last: Maqueira-Marín
Author-Name: M. J. Cobo
Author-X-Name-First: M. J.
Author-X-Name-Last: Cobo
Title: 22 Years of Lean Supply Chain Management: a science mapping-based bibliometric analysis
Abstract: 
 This article examines how the research into Lean Supply Chain Management (LSCM) has evolved over the period 1996–2018 with the identification of the main issues explored and future trends. A performance bibliometric analysis has been conducted through a study of published documents, citations, journal impact factor, h-index, most cited papers and authors, and data on the geographic distribution of publications. More relevantly, a science mapping analysis has been performed with SciMAT bibliometric analysis software using co-word networks in a longitudinal overview. The large number of studies of LSCM published has enabled a conceptual evolution map to be constructed of the way that this research has developed. The results have enabled us to identify four thematic areas in the LSCM field: Methods, Key factors, Internal efficiency, and Performance.
Journal: International Journal of Production Research
Pages: 1901-1921
Issue: 6
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1794076
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1794076
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Template-Type: ReDIF-Article 1.0
Author-Name: Ting Zheng
Author-X-Name-First: Ting
Author-X-Name-Last: Zheng
Author-Name: Marco Ardolino
Author-X-Name-First: Marco
Author-X-Name-Last: Ardolino
Author-Name: Andrea Bacchetti
Author-X-Name-First: Andrea
Author-X-Name-Last: Bacchetti
Author-Name: Marco Perona
Author-X-Name-First: Marco
Author-X-Name-Last: Perona
Title: The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review
Abstract: 
 Industry 4.0 (I4.0) encompasses a plethora of digital technologies effecting on manufacturing enterprises. Most research on this topic examines the effects in the smart factory domain, focusing on production scheduling. However, there is still a lack of comprehensive research on the applications of I4.0 enabling technologies in manufacturing life-cycle processes. This paper is thus intended to provide a systematic literature review answering the following research question: What are the applications of I4.0 enabling technologies in the business processes of manufacturing companies? The study analyses 186 articles and the results show that production scheduling and control is the process most often investigated, while there is also an increasing trend in servitization and circular supply chain management. Moreover, there is extensive combined use of IoT, Big Data Analytics and Cloud, whose applications cover a wide range of processes. On the contrary, other technology like Blockchain is not as widely discussed in the domain of I4.0. This picture calls for a future research agenda extending the scope of investigation into I4.0 in manufacturing. Furthermore, the results of this research can prove extremely useful for practitioners who wish to implement one or more technologies, providing them with solutions for applications in manufacturing.
Journal: International Journal of Production Research
Pages: 1922-1954
Issue: 6
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1824085
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1824085
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: A Lagrangian heuristic for minimising risk using multiple heterogeneous metrology tools
Journal: International Journal of Production Research
Pages: 1955-1955
Issue: 6
Volume: 59
Year: 2021
Month: 03
X-DOI: 10.1080/00207543.2020.1853883
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1853883
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Template-Type: ReDIF-Article 1.0
Author-Name: Jafar Heydari
Author-X-Name-First: Jafar
Author-X-Name-Last: Heydari
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Zahra Basiri
Author-X-Name-First: Zahra
Author-X-Name-Last: Basiri
Title: Balancing price and green quality in presence of consumer environmental awareness: a green supply chain coordination approach
Abstract: 
 This study analyses the green channel coordination problem in a two-echelon supply chain where demand is a function of the selling price and the product’s green quality. The retailer decides on the selling price while the manufacturer regulates the green quality of the product. To initiate the channel coordination and to establish a win-win outcome for both parties, a hybrid of ‘greening cost sharing’ and ‘revenue sharing’ contract (HGRS) is developed. This study contributes to the literature by providing an analytical approach to address the channel coordination and pricing issues in a green supply chain under the consumer environmental awareness while the manufacturer has the ability of enhancing, with investments, the product’s green quality. Our study reveals that: (a) the proposed HGRS contract is capable of achieving channel coordination while both supply chain members gain more profit than in decentralised decision making, (b) the new suggested contract enhances the product’s green quality, reduces the selling price, and stimulates the market demand, and (c) HGRS contract results in more satisfied customers (by offering low prices) as well as more sustainable operations (by increasing greenness level) at the same time.
Journal: International Journal of Production Research
Pages: 1957-1975
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1771457
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1771457
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Template-Type: ReDIF-Article 1.0
Author-Name: Sven-Vegard Buer
Author-X-Name-First: Sven-Vegard
Author-X-Name-Last: Buer
Author-Name: Marco Semini
Author-X-Name-First: Marco
Author-X-Name-Last: Semini
Author-Name: Jan Ola Strandhagen
Author-X-Name-First: Jan Ola
Author-X-Name-Last: Strandhagen
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Title: The complementary effect of lean manufacturing and digitalisation on operational performance
Abstract: 
 The most recent trend manufacturers have embraced to seek operational performance improvements is the use of a wide range of digital technologies typically associated with Industry 4.0. However, few studies have investigated the relationship between such technologies and the long-established lean manufacturing domain, and how they, together, influence operational performance. Based on data from a cross-sectional survey of manufacturing companies, this study investigates the relationships between the use of lean manufacturing, factory digitalisation, and operational performance using hierarchical multiple regression analysis. While simultaneously controlling for the effects of production repetitiveness, company size, and length of lean manufacturing implementation, the findings show that both lean manufacturing and factory digitalisation individually contribute to improved operational performance. Furthermore, it is found that when used together, they have a complementary (or synergistic) effect that is greater than their individual effects combined. These research findings provide both theoretical and practical insights into how lean manufacturing and factory digitalisation affect the operational performance of manufacturing firms. In light of the upcoming fourth industrial revolution, these findings suggest that lean manufacturing is not obsolete but rather is more important than ever in order to reap the benefits from emerging technologies and translate them into improved operational performance.
Journal: International Journal of Production Research
Pages: 1976-1992
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1790684
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1790684
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Template-Type: ReDIF-Article 1.0
Author-Name: Sube Singh
Author-X-Name-First: Sube
Author-X-Name-Last: Singh
Author-Name: Ramesh Kumar
Author-X-Name-First: Ramesh
Author-X-Name-Last: Kumar
Author-Name: Rohit Panchal
Author-X-Name-First: Rohit
Author-X-Name-Last: Panchal
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Impact of COVID-19 on logistics systems and disruptions in food supply chain
Abstract: 
 An outbreak of deadly COVID-19 virus has not only taken the lives of people but also severely crippled the economy. Due to strict lockdown, the manufacturing and logistics activities have been suspended, and it has affected the demand and supply of various products as a result of restrictions imposed on shopkeepers and retailers. Impacts of COVID-19 are observed ubiquitously in every type of units from different sectors. In this study, a simulation model of the public distribution system (PDS) network is developed with three different scenarios to demonstrate disruptions in the food supply chain. Difficulties have been increased in matching supply and demand in a vast network of PDS because of changing scenarios with the growth of infected cases and recovery. This paper also highlights the importance of a resilient supply chain during a pandemic. Our proposed simulation model can help in developing a resilient and responsive food supply chain to match the varying demand, and then further assist in providing decision-making support for rerouting the vehicles as per travel restrictions in areas. Paper has been summarised with significant highlights and including future research scope for developing a more robust food supply chain network.
Journal: International Journal of Production Research
Pages: 1993-2008
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1792000
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1792000
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Template-Type: ReDIF-Article 1.0
Author-Name: Behdin Vahedi-Nouri
Author-X-Name-First: Behdin
Author-X-Name-Last: Vahedi-Nouri
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Author-Name: Zdeněk Hanzálek
Author-X-Name-First: Zdeněk
Author-X-Name-Last: Hanzálek
Author-Name: Hamidreza Arbabi
Author-X-Name-First: Hamidreza
Author-X-Name-Last: Arbabi
Author-Name: Mohammad Rohaninejad
Author-X-Name-First: Mohammad
Author-X-Name-Last: Rohaninejad
Title: Incorporating order acceptance, pricing and equity considerations in the scheduling of cloud manufacturing systems: matheuristic methods
Abstract: 
 Rooted from the Industry 4.0 principles, Cloud Manufacturing (CMfg) is a novel customer-oriented manufacturing norm, which can assist enterprises to withstand in the nowadays highly volatile and competitive market. CMfg systems comprise two separate parties, namely, customers and factories, with independent individuals. In this regard, considering the utilities of both customers and factories and establishing the equity amongst their individuals are of particular importance for the survival and flourishment of CMfg systems. Furthermore, due to the limited capacity of resources, tightness of due dates, and customers’ cost expectations, all orders may not be accepted in CMfg systems. Accordingly, this paper aims to explore a scheduling problem in a CMfg system. A multi-objective mathematical model is presented for the problem, which can determine the acceptance or rejection of orders, set prices, and schedule them in an integrated manner to maximise the customers and factories’ utilities, and enhance the equity among their members. Due to the high complexity of the problem, two matheuristic methods based on the Multi-Objective Grey Wolf Optimizer (MOGWO) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) are developed. An extensive computational experiment is carried out to validate the proposed matheuristic methods and evaluate their performance. Moreover, some guidance is presented for managers by conducting a sensitivity analysis.
Journal: International Journal of Production Research
Pages: 2009-2027
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1806370
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1806370
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Template-Type: ReDIF-Article 1.0
Author-Name: Jacob Lohmer
Author-X-Name-First: Jacob
Author-X-Name-Last: Lohmer
Author-Name: Rainer Lasch
Author-X-Name-First: Rainer
Author-X-Name-Last: Lasch
Title: Production planning and scheduling in multi-factory production networks: a systematic literature review
Abstract: 
 Multi-factory production planning and scheduling problems have been increasingly studied by scholars recently due to market uncertainty, technological trends like Industry 4.0 and increasing collaboration. Geographically dispersed factories may provide cost-saving potential and increase efficiency while also being subjected to varying capabilities and restrictions such as capacity constraints and labour costs. Traditional approaches in production planning and scheduling focus on the allocation of demand to a single factory and obtain sequences of operations on machines in this factory. In the multi-factory or distributed setting, an additional task includes assigning orders to potential factories beforehand. Starting with the first case studies in the late 1990s, research has increasingly been devoted to this research field and has considered numerous variations of the problem. We review 128 articles on multi-factory production planning and scheduling problems in this contribution and classify the literature according to shop configuration, network structure, objectives, and solution methods. Bibliometric analysis and network analysis are utilised to generate new findings. Research opportunities identified include integration with other planning stages, an investigation of key real-life objectives such as due date compliance and examining dynamic characteristics in the context of Industry 4.0. Besides, empirical studies are necessary to gain new practical insights.
Journal: International Journal of Production Research
Pages: 2028-2054
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1797207
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1797207
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Christopher S. Tang
Author-X-Name-First: Christopher S.
Author-X-Name-Last: Tang
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Ajay Das
Author-X-Name-First: Ajay
Author-X-Name-Last: Das
Title: Researchers' perspectives on Industry 4.0: multi-disciplinary analysis and opportunities for operations management
Abstract: 
 While Industry 4.0 has been trending in practice and research, operations management studies in this area remain nascent. Our intent is to understand the current state of research in Industry 4.0 in different disciplines and deduce insights and opportunities for future research in operations management. In this paper, we provide a focused analysis to examine the state-of-the-art research in Industry 4.0. To learn about researchers’ perspectives about Industry 4.0, we conducted a large-scale, cross-disciplinary and global survey on Industry 4.0 topics among researchers in industrial engineering, operations management, operations research, control and data science at the 9th IFAC MIM 2019 Conference in Berlin in August 2019. By using our survey findings and literature analysis, we build structural and conceptual frameworks to understand the current state of knowledge and to propose future research opportunities for operations management scholars.Glossary of AbbreviationsAGV: Automated guided vehicle; AI: Artificial intelligence; APS: Advanced planning system: a wide variety of software tools and techniques, with many applications in manufacturing and logistics (including the service sector); BDA: Big data analytics; CAS: Complex adaptive system: a system composed of many interacting parts that evolve and adapt over time; CIM: Computer integrated manufacturing; CPFR: Collaborative planning, forecasting and replenishment; CPS: Cyber-physical system: a seamless integration of computation and physical components; DAMCLS: Decision analysis, modelling, control and learning systems; ERP: Enterprise resource planning; FMS: Flexible manufacturing system; I4.0: Industry 4.0; IFAC: International Federation of Automatic Control: a federation is concerned with the impact of control technology on society; IME: Industrial and mechanical engineering; IoT: Internet-of-Things; IT: Information technology; M2M: Machine-to-machine; MAS: Multi-agent system: a loosely coupled network of software agents that interact to solve problems that are beyond the individual capacities or knowledge of each problem solver; OR: Operations research; RFID: Radio frequency identification: a technology that uses electromagnetic fields to automatically identify and track tags attached to objects; RMS: Reconfigurable manufacturing system: a manufacturing system that can change and evolve rapidly in order to adjust its productivity capacity and functionality; OM: Operations management; T&T: Track and trace system; VCA: VOS viewer co-occurrence analysis: a software tool for visualising bibliometric networks; VMI: Vendor-managed inventory.
Journal: International Journal of Production Research
Pages: 2055-2078
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1798035
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1798035
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Template-Type: ReDIF-Article 1.0
Author-Name: Shenle Pan
Author-X-Name-First: Shenle
Author-X-Name-Last: Pan
Author-Name: Wei Zhou
Author-X-Name-First: Wei
Author-X-Name-Last: Zhou
Author-Name: Selwyn Piramuthu
Author-X-Name-First: Selwyn
Author-X-Name-Last: Piramuthu
Author-Name: Vaggelis Giannikas
Author-X-Name-First: Vaggelis
Author-X-Name-Last: Giannikas
Author-Name: Chao Chen
Author-X-Name-First: Chao
Author-X-Name-Last: Chen
Title: Smart city for sustainable urban freight logistics
Abstract: 
 Sustainability has become an important objective of city logistics management. Smart city, being a technology and data driven paradigm for a city’s sustainable development, has entailed new research opportunities from different perspectives. It is foreseeable that smart city will keep evolving in the domain of city logistics, which plays a key role in this game changing evolution. Recent research in this field is characterised by interdisciplinary approaches and disruptive innovations. We review the state-of-the-art of this general area and conduct a bibliometric analysis. We conclude with a new conceptual framework of smart city for sustainable urban freight logistics and the relevant key perspectives.
Journal: International Journal of Production Research
Pages: 2079-2089
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2021.1893970
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1893970
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:7:p:2079-2089




Template-Type: ReDIF-Article 1.0
Author-Name: Shichang Pan
Author-X-Name-First: Shichang
Author-X-Name-Last: Pan
Author-Name: Lele Zhang
Author-X-Name-First: Lele
Author-X-Name-Last: Zhang
Author-Name: Russell G. Thompson
Author-X-Name-First: Russell G.
Author-X-Name-Last: Thompson
Author-Name: Hadi Ghaderi
Author-X-Name-First: Hadi
Author-X-Name-Last: Ghaderi
Title: A parcel network flow approach for joint delivery networks using parcel lockers
Abstract: 
 Current courier networks in metropolitan areas are characterised by utilising fleets of vans that perform collection and distribution routes independently. This results in long stem distances, low load factors and high environmental costs. Joint delivery systems have the potential to reduce the distances of pick-up and drop-off routes. In this context, parcel lockers can be utilised to transfer goods between vans, electrical vehicles and bikes to improve the efficiency and sustainability of courier networks. This paper presents a model for designing joint delivery networks in urban areas by utilising parcel lockers. This model has a two-level structure: the lower level dealing with multi-depot capacitated vehicle routing problems (MDCVRP) for a set of depots and lockers whilst the upper level being a (minimum-cost) parcel network flow problem (PNFP) considering goods delivered between depots and lockers and the selection of lockers’ positions and sizes. A hybrid algorithm integrating a Genetic Algorithm with the Lin-Kernighan Heuristic has been developed. The GA focuses on finding solutions for the PNFP. Once the paths of parcel flow are determined, the LKH optimises vehicle flow. This paper is the first to consider the use of parcel lockers for business-to-business networks in the form of MDCVRP.
Journal: International Journal of Production Research
Pages: 2090-2115
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1856440
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856440
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Template-Type: ReDIF-Article 1.0
Author-Name: Abood Mourad
Author-X-Name-First: Abood
Author-X-Name-Last: Mourad
Author-Name: Jakob Puchinger
Author-X-Name-First: Jakob
Author-X-Name-Last: Puchinger
Author-Name: Tom Van Woensel
Author-X-Name-First: Tom
Author-X-Name-Last: Van Woensel
Title: Integrating autonomous delivery service into a passenger transportation system
Abstract: 
 The increasing demand for goods, especially in urban areas, together with the technological advances are creating both opportunities and challenges for planning urban freight systems. One of these promising opportunities is to use the underused assets in people-based systems to transport goods. In this paper, we consider an integrated system in which a set of freight requests needs to be delivered using a fleet of grounded, and autonomous, pickup and delivery (PD) robots where a public transportation service (referred to as scheduled line (SL)) can be used as part of PD robot's journey. Passengers and PD robots (carrying freight) share the available capacity on SLs where passengers are prioritised, and their transport demand is stochastic. Thus the number of available places for PD robots is only revealed upon shuttle arrival to the corresponding SL station. We first formulate this problem as a Pickup and Delivery Problem with Time Windows and Scheduled Lines (PDPTW-SL). We then introduce a sample average approximation (SAA) method along with an Adaptive Large Neighbourhood Search (ALNS) algorithm for solving the stochastic optimization problem. Finally, we present an extensive computational study, analyse its results and give some directions for future research.
Journal: International Journal of Production Research
Pages: 2116-2139
Issue: 7
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1746850
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1746850
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Template-Type: ReDIF-Article 1.0
Author-Name: Yaohan Shen
Author-X-Name-First: Yaohan
Author-X-Name-Last: Shen
Author-Name: Xianhao Xu
Author-X-Name-First: Xianhao
Author-X-Name-Last: Xu
Author-Name: Bipan Zou
Author-X-Name-First: Bipan
Author-X-Name-Last: Zou
Author-Name: Hongwei Wang
Author-X-Name-First: Hongwei
Author-X-Name-Last: Wang
Title: Operating policies in multi-warehouse drone delivery systems
Abstract: 
 Drones are increasingly used to deliver packages with high efficiency in several areas. We study a multi-warehouse drone delivery system, considering the allocation rule that all warehouses share the drones and the allocation rule that each warehouse owns its drones. Both plug-in charge and battery swap strategies are investigated for battery management. We examine the random and closest drone to warehouse assignment rules, and design a heuristic to improve the drone to warehouse assignment rule. A closed queueing network is built to estimate the maximum throughput capacity and a cost minimisation model is developed for cost analysis. We validate the analytical model by simulation and conduct numerical experiments to analyse the operating polices. The results show that the closest drone to warehouse assignment rule outperforms the random drone to warehouse assignment rule when the number of drones is not large, and our heuristic can improve the throughput capacity by about 13.31%. The battery swap strategy provides a better throughput capacity than the plug-in charge strategy in most cases, while it needs more investment. Moreover, the shared allocation rule gives a larger throughput capacity than the dedicated allocation rule, and it reduces the operating cost by about 30.70%.
Journal: International Journal of Production Research
Pages: 2140-2156
Issue: 7
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1756509
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1756509
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Template-Type: ReDIF-Article 1.0
Author-Name: Xin Feng
Author-X-Name-First: Xin
Author-X-Name-Last: Feng
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Author-Name: Yufei Huang
Author-X-Name-First: Yufei
Author-X-Name-Last: Huang
Title: Crowdsource-enabled integrated production and transportation scheduling for smart city logistics
Abstract: 
 With city logistics becoming more and more important, increasing attention has been paid to the ‘last-mile delivery’ in urban areas. We investigate a novel crowdsource-enabled integrated production and transportation scheduling problem in the paper. The problem is first formulated into a mixed-integer linear program and its strong NP-hardness is proved. To better understand this complex problem, two sub-problems: a production and transportation scheduling problem and a crowdsourced bid selection problem are analysed. Based on problem properties, a Genetic Algorithm (GA) and a lower bound (LB) are developed to solve the original problem. Experimental results with up to 100 customers show that the GA outperforms the well-known commercial MIP solver CPLEX. Especially, (1) the GA can yield near-optimal solutions for all the tested instances with an average gap of 10.17% from the lower bound, while CPLEX provides feasible solutions only for instances with no more than 30 customers; (2) the average computation time of the GA is only 0.93% of that required by CPLEX; Besides, sensitivity analysis demonstrates advantages of introducing crowdsourced delivery into city logistics.
Journal: International Journal of Production Research
Pages: 2157-2176
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1808258
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1808258
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Template-Type: ReDIF-Article 1.0
Author-Name: Y. Gao
Author-X-Name-First: Y.
Author-X-Name-Last: Gao
Author-Name: J. W. Wang
Author-X-Name-First: J. W.
Author-X-Name-Last: Wang
Title: A resilience assessment framework for urban transportation systems
Abstract: 
 Unexpected disruptions in an urban transportation system may severely damage its structure and functionality. The resilience of urban transportation networks, i.e. the ability to recover from destroyed conditions, is thus significant for the mobility of passengers and freight in cities. However, its definition and measurement have been confused with robustness. This research advances a trackable assessment framework for the resilience of two typical urban transportation modes, i.e. road system and metro system, considering the characteristics of their structure and functionality. Individual vertex-based and edge-based failure models are established for the two transportation systems based on their network models. The proposed measurement approach is applied to an inner-city road freight system and the metro system in Hangzhou, China, to analyse their resilience, considering different combinations of vertex-based and edge-based failures. The proposed approach is compared with an efficiency-based resilience measurement method and outperforms in two parts. First, it has a broader application than previous related methods because it can describe disruptions occurring on one directed vertex or edge using a directed network model. Second, the new method outputs more reliable results due to considering more structural and functional characteristics of urban transportation systems than previous methods.
Journal: International Journal of Production Research
Pages: 2177-2192
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1847339
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1847339
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Template-Type: ReDIF-Article 1.0
Author-Name: Hao Luo
Author-X-Name-First: Hao
Author-X-Name-Last: Luo
Author-Name: Siyu Tian
Author-X-Name-First: Siyu
Author-X-Name-Last: Tian
Author-Name: Xiang T. R. Kong
Author-X-Name-First: Xiang T. R.
Author-X-Name-Last: Kong
Title: Physical Internet-enabled customised furniture delivery in the metropolitan areas: digitalisation, optimisation and case study
Abstract: 
 This article proposes a Physical Internet-enabled customized furniture delivery system (PI-CFDS) with the following contributions. First, a set of PI-enabled smart logistics facilities was adopted to transform the conventional operations. A PI decision support platform was designed to deal with resource planning. Second, since the classical methods cannot be applied directly, we developed a new approach, including both mathematical modelling and algorithm design. The optimal planning decision maximizes the shipper’s profits while providing a stable income for the carriers. Third, the proposed solution was verified via a real-life case study. The effects of geographical, cost, and demand parameters were also analyzed. Our results show that the PI-CFDS solution has advantageous over the traditional solution when considering the dispersed distribution of customer depots. We found that when the dispersion of customer locations increases, the fixed cost of vehicles increases, and the salary difference between drivers and movers increases; in this situation, the advantages of the PI-CFDS solution are more apparent. However, compared with the traditional solution, the PI-CFDS solution is more sensitive to the rise of fuel prices and the stability of demand. The results yield substantial insights and facilitate daily decision-making for managers.
Journal: International Journal of Production Research
Pages: 2193-2217
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1832271
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1832271
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingyi Chen
Author-X-Name-First: Jingyi
Author-X-Name-Last: Chen
Author-Name: Tijun Fan
Author-X-Name-First: Tijun
Author-X-Name-Last: Fan
Author-Name: Fei Pan
Author-X-Name-First: Fei
Author-X-Name-Last: Pan
Title: Urban delivery of fresh products with total deterioration value
Abstract: 
 The deterioration of fresh products is often severe during fresh product delivery in urban areas, which is a significant challenge. We propose a novel model for the urban delivery of fresh products with different perishability. The objective of this model is to minimise the total deterioration value (TDV) and distance travelled. The TDV is related to the perishability, deterioration rates and quantities of different fresh products. A customised genetic algorithm is proposed to solve the model. The fitness value is calculated according to the preferential delivery of fresh products with high deterioration rates. Finally, a case study of fresh product delivery for a company in Shanghai is explored to assess the effectiveness of the proposed model. The results show that the proposed approach can lead to the highest drop of 11.8% of TDV compared to that based on the traditional shortest-path model.
Journal: International Journal of Production Research
Pages: 2218-2228
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1828638
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1828638
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Template-Type: ReDIF-Article 1.0
Author-Name: Zonggui Tian
Author-X-Name-First: Zonggui
Author-X-Name-Last: Tian
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Author-Name: Ali Vatankhah Barenji
Author-X-Name-First: Ali
Author-X-Name-Last: Vatankhah Barenji
Author-Name: Y. T. Wang
Author-X-Name-First: Y. T.
Author-X-Name-Last: Wang
Author-Name: Zhi Li
Author-X-Name-First: Zhi
Author-X-Name-Last: Li
Author-Name: Yiming Rong
Author-X-Name-First: Yiming
Author-X-Name-Last: Rong
Title: A blockchain-based evaluation approach for customer delivery satisfaction in sustainable urban logistics
Abstract: 
 The rapid development of urbanisation and the ever-changing consumers’ demands are constantly changing the urban logistics industry, imposing challenges on logistics service providers to improve customer satisfaction which is one of the indicators for the sustainability of urban logistics. Existing customer satisfaction evaluations are based on a questionnaire survey, which is time-consuming and labour intensive. Moreover, the logistics data are confidential and can only be accessed by the stakeholders in existing logistics models, causing the problem of information non-transparency among logistics enterprises and the third authorities like banks and governments, which may hinder the sustainable development of urban logistics. In this paper, we propose a blockchain-based evaluation approach for customer satisfaction in the context of urban logistics. Four criteria affecting customer satisfaction in urban logistics are identified. A machine learning algorithm Long Short-Term Memory (LSTM) is adopted to predict customer satisfaction in the future period. The implementation is demonstrated to illustrate the proposed approach. A smart contract is designed for compensation and/or refund to customers when their satisfaction with the delivery services is at a low level.
Journal: International Journal of Production Research
Pages: 2229-2249
Issue: 7
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1809733
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1809733
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Template-Type: ReDIF-Article 1.0
Author-Name: Chenhao Zhou
Author-X-Name-First: Chenhao
Author-X-Name-Last: Zhou
Author-Name: Aloisius Stephen
Author-X-Name-First: Aloisius
Author-X-Name-Last: Stephen
Author-Name: Xinhu Cao
Author-X-Name-First: Xinhu
Author-X-Name-Last: Cao
Author-Name: Shuhong Wang
Author-X-Name-First: Shuhong
Author-X-Name-Last: Wang
Title: A data-driven business intelligence system for large-scale semi-automated logistics facilities
Abstract: 
 With the proliferation of e-commerce, the regional hub of a large-scale logistics company is required to sort and load a large number of packages into different delivery vehicles by dawn and deliver them to customers by noon on a daily basis. The efficiency of the sorting operation is thus a competitive advantage which directly impacts the company's service level. In this study, a data-driven business intelligence system for the semi-automated sorting facility is proposed for real-world implementation. To determine the cargo handling sequence, an information-based approach with a multi-criteria index function is developed. Then a simulation-based optimisation framework, which integrates a multi-objective search algorithm with a simulation model, is employed to fine-tune the parameters of the index function to perform optimally. The results of the numerical experiment show that the proposed technique is able to reduce 20% of the sorting operation duration, which equals a reduction of about 3600 man-hours per year. The study is a good example of applying emerging technologies in the logistics industry.
Journal: International Journal of Production Research
Pages: 2250-2268
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1727048
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1727048
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianjun Wang
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wang
Author-Name: Ting Mao
Author-X-Name-First: Ting
Author-X-Name-Last: Mao
Author-Name: Yiliu Tu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Tu
Title: Simultaneous multi-response optimisation for parameter and tolerance design using Bayesian modelling method
Abstract: 
 In the study of simultaneous optimisation of parameter and tolerance design with multiple quality characteristics, the existing modelling methods rarely consider the influence of the response variability related to the model parameter uncertainty and other random errors on the optimisation results. In this paper, an integrated total cost model, including the tolerance cost, quality loss, and rejection cost is proposed to deal with the above issue in a unified framework of Bayesian modelling and optimisation. The proposed method not only considers the model parameter uncertainty but also considers the change of design factors within the limited tolerances through using the Bayesian modelling method. Moreover, the quality loss function and the rejection cost (i.e. scrap cost and rework cost) function are established by using the posterior samples of simulated responses, respectively. Finally, the total cost function is minimised by using a hybrid genetic algorithm to find the optimal parameter settings and tolerance values. Two examples illustrate the advantages of the proposed method in this paper. The results show that the proposed approach may give more reasonable solutions than the existing approaches when considering the variability of predictive responses and the change of design factors.
Journal: International Journal of Production Research
Pages: 2269-2293
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1730011
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1730011
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Template-Type: ReDIF-Article 1.0
Author-Name: Ramez Kian
Author-X-Name-First: Ramez
Author-X-Name-Last: Kian
Author-Name: Emre Berk
Author-X-Name-First: Emre
Author-X-Name-Last: Berk
Author-Name: Ülkü Gürler
Author-X-Name-First: Ülkü
Author-X-Name-Last: Gürler
Author-Name: Hassan Rezazadeh
Author-X-Name-First: Hassan
Author-X-Name-Last: Rezazadeh
Author-Name: Baback Yazdani
Author-X-Name-First: Baback
Author-X-Name-Last: Yazdani
Title: The effect of economies-of-scale on the performance of lot-sizing heuristics in rolling horizon basis
Abstract: 
 In this article, we consider the production planning problem in the presence of (dis)economies-of-scale in production costs on a rolling horizon basis with a fixed forecast horizon. We propose variants of three well-known and commonly used heuristics (Wagner–Whitin, Silver–Meal and Least Unit Cost) adapted for this particular setting. In an extensive numerical study with demands exhibiting stationary, increasing and decreasing trends and seasonality, we demonstrate that having longer forecast horizon is less effective in obtaining more cost effective production plans when the production cost function is convex and also when fixed setup cost is lower, which both are proxy to lack of economies-of-scale.
Journal: International Journal of Production Research
Pages: 2294-2308
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1730464
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1730464
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Template-Type: ReDIF-Article 1.0
Author-Name: Silu Liu
Author-X-Name-First: Silu
Author-X-Name-Last: Liu
Author-Name: Zeqiang Zhang
Author-X-Name-First: Zeqiang
Author-X-Name-Last: Zhang
Author-Name: Chao Guan
Author-X-Name-First: Chao
Author-X-Name-Last: Guan
Author-Name: Lixia Zhu
Author-X-Name-First: Lixia
Author-X-Name-Last: Zhu
Author-Name: Min Zhang
Author-X-Name-First: Min
Author-X-Name-Last: Zhang
Author-Name: Peng Guo
Author-X-Name-First: Peng
Author-X-Name-Last: Guo
Title: An improved fireworks algorithm for the constrained single-row facility layout problem
Abstract: 
 The single-row facility layout problem (SRFLP) decides upon the arrangement of facilities in a straight row so as to minimise the material handling cost. Generally, this problem allows the placement of the facilities in any location in any order without any restriction, but some practical SRFLP cases are required to meet various types of constraints imposed on the placement of its facilities in the engineering of the placement of factory machinery and equipment. According to this new perspective, we studied the constrained SRFLP (cSRFLP) in this paper. In this problem, a few facilities need to be placed in certain positions or specified orders with or without the requirement to be located next to each other. To address this novel layout problem, related constraints are defined and classified, and novel mixed-integer programming models for the problem are formulated. Subsequently, the CPLEX software is employed to solve this problem. Then a constrained improved fireworks algorithm is presented, which is discretised to solve the considered cSRFLP. Our computational experiments demonstrate that the proposed algorithm performs better than the existing algorithms in solving the problem.
Journal: International Journal of Production Research
Pages: 2309-2327
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1730465
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1730465
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Template-Type: ReDIF-Article 1.0
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Xin Liu
Author-X-Name-First: Xin
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: E. Zhang
Author-X-Name-First: E.
Author-X-Name-Last: Zhang
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Service-oriented robust worker scheduling with motivation effects
Abstract: 
 Due to gradual disappearance of global demographic dividend, the improvement of workforce efficiency becomes increasingly important. It has been commonly recognised that workforce motivation can largely stimulate the workers, especially in manufacturing systems. This paper investigates a worker scheduling problem under given work shifts with workforce motivation effects, where motivation effects are characterised by motivation coefficients of job processing times. We focus on the situation where motivation coefficients are uncertain due to various factors, and only the mean vector and covariance matrix are known. The objective is to maximise the service level, measured by the probability of ensuring no tardy jobs. We first propose a distributionally robust chance constrained formulation with a probabilistic objective function. Then an adapted sample average approximation (SAA) method and a heuristic, based on an approximated mixed integer second-order cone programming (MI-SOCP) model and the idea of problem decomposition, is developed. Numerical results show that the decomposition-based heuristic is more efficient. We also draw some managerial insights.
Journal: International Journal of Production Research
Pages: 2328-2351
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1730998
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1730998
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Template-Type: ReDIF-Article 1.0
Author-Name: Amir Ahmadi-Javid
Author-X-Name-First: Amir
Author-X-Name-Last: Ahmadi-Javid
Author-Name: Amir Ardestani-Jaafari
Author-X-Name-First: Amir
Author-X-Name-Last: Ardestani-Jaafari
Title: The unequal area facility layout problem with shortest single-loop AGV path: how material handling method matters
Abstract: 
 This paper studies an unequal area layout problem whose objective is to find a flexible bay layout with the best shortest single loop. The problem can be used for production systems in which material handling is carried out by automated guided vehicles (AGVs) that move along a single-loop path. The designed layout is robust against future changes in material flows, which are caused by different factors such as demand fluctuations, technology advancement, and new product introduction. It is first proved that there exists a feasible single loop for any bay layout, which indicates the problem is well-defined and always has a feasible solution. Then, a powerful hybrid algorithm based on Memetic and Simulated Annealing is developed. The algorithm is tested on many randomly generated instances and well-known instances from the literature. The numerical experiment shows that the proposed heuristic is both efficient and effective. The new layout-design approach significantly improves the loop-length when compared with the traditional approach in which the layout is first determined based on rectilinear distances, and then the best single loop is found. Our study highlights the importance of adequately incorporating the material handling system into the layout design phase.
Journal: International Journal of Production Research
Pages: 2352-2374
Issue: 8
Volume: 59
Year: 2021
Month: 04
X-DOI: 10.1080/00207543.2020.1733124
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1733124
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingxiang Lv
Author-X-Name-First: Jingxiang
Author-X-Name-Last: Lv
Author-Name: Tao Peng
Author-X-Name-First: Tao
Author-X-Name-Last: Peng
Author-Name: Yingfeng Zhang
Author-X-Name-First: Yingfeng
Author-X-Name-Last: Zhang
Author-Name: Yuchang Wang
Author-X-Name-First: Yuchang
Author-X-Name-Last: Wang
Title: A novel method to forecast energy consumption of selective laser melting processes
Abstract: 
 As a promising additive manufacturing (AM) technology, the applications of selective laser melting (SLM) are expanding. Yet, due to the complex structure of SLM machines and low processing rates, the SLM process is highly energy-intensive. Energy forecasting is crucial for accurate evaluation and reduction of SLM energy consumption. However, due to the diversity of SLM machines and their various operating states, the energy consumption of SLM processes is difficult to predict. This article presents a novel method to forecast the energy consumption of SLM processes. The proposed approach is based on the power modelling of machine subsystems and the temporal modelling of sub-processes. Through identifying the working statuses of subsystems of SLM machines in each sub-process, forecast accuracy can be greatly improved. Two cases of aluminium components fabricated by an SLM process using an SLM 280HL facility are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method outperforms specific, stage-based and subsystem-based energy benchmark models in energy consumption forecasting.
Journal: International Journal of Production Research
Pages: 2375-2391
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1733126
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1733126
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Template-Type: ReDIF-Article 1.0
Author-Name: Xu Guo
Author-X-Name-First: Xu
Author-X-Name-Last: Guo
Author-Name: Martín Egozcue
Author-X-Name-First: Martín
Author-X-Name-Last: Egozcue
Author-Name: Wing Keung Wong
Author-X-Name-First: Wing Keung
Author-X-Name-Last: Wong
Title: Production theory under price uncertainty for firms with disappointment aversion
Abstract: 
 This paper studies the production theory of the competitive firm under price uncertainty by adopting four of the most well-established models of disappointment aversion. Our results show that a disappointment-averse firm will generally produce less than a risk-averse firm. Further, the disappointment-averse firm's optimal output level will surely decrease with an increase in the disappointment coefficients. Moreover, the optimal outputs among the four disappointment-averse models are not the same. As a real case example, we apply our models to determine the optimal building heights for new buildings in Punta del Este, Uruguay. In this example, our disappointment averse models' predictions are very close to the observed heights of these new projects.
Journal: International Journal of Production Research
Pages: 2392-2405
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1733699
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1733699
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:8:p:2392-2405




Template-Type: ReDIF-Article 1.0
Author-Name: Thomas B. Ladinig
Author-X-Name-First: Thomas B.
Author-X-Name-Last: Ladinig
Author-Name: Krishna S. Dhir
Author-X-Name-First: Krishna S.
Author-X-Name-Last: Dhir
Author-Name: Gyula Vastag
Author-X-Name-First: Gyula
Author-X-Name-Last: Vastag
Title: Sensemaking support system (S3) for manufacturing process improvement
Abstract: 
 Production management teams often face unfamiliar situations where each team member must understand new phenomena individually before the team can make mutually understandable and acceptable decisions. Contradicting subjective judgments can distort the group’s decision-making process because team members understand situations differently and are generally prone to behavioural biases. This paper presents the development of a sensemaking support system (S3,S cube) for selecting improvement projects in a complex,small-volume batch production system of a premium car manufacturer. All phases of the sensemaking process are facilitated by making various sources of information available to a team of managers and experts to reduce conflicts regarding the selection of improvement projects. S3 is based on a lens model which combines judgments of the management team with discrete event simulation and provides visual representations of the differences and misjudgements related to various improvement options. The results – that can easily be generalised to many similar settings – indicate different understanding and lack of coherence within the management team which prevents them from defining mutually acceptable actions. This is countered with the creation of an action proposal,summarising and visualising causal relationships,and connecting them to improvement options to improve performance of the production system.
Journal: International Journal of Production Research
Pages: 2406-2425
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1733700
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1733700
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Template-Type: ReDIF-Article 1.0
Author-Name: Chengyi Zhang
Author-X-Name-First: Chengyi
Author-X-Name-Last: Zhang
Author-Name: Jianbo Yu
Author-X-Name-First: Jianbo
Author-X-Name-Last: Yu
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Title: Fault detection and recognition of multivariate process based on feature learning of one-dimensional convolutional neural network and stacked denoised autoencoder
Abstract: 
 Multivariate process pattern recognition (MPPR) is essential towards continuous quality control task. A challenging problem is to extract effective features from complex process signals with high-dimensional and nonlinear characteristics. This affects effectiveness of various classifiers in process fault detection and diagnosis significantly. In this paper, we propose a hybrid deep learning model (i.e. 1-DCNN + SDAE) that integrates one-dimensional convolutional neural network (1-DCNN) and stacked denoising auto-encoders (SDAE) to extract high level features from complex process signals. In comparison with two-dimensional images, one-dimensional process signals allow not only to extract spatial features, but also reduce calculation cost. 1-DCNN is capable of extracting representative features from one-dimensional process signals and then improves MPPR performance of classifiers significantly. SDAE is embedded after fully connected layer of 1-DCNN for further dimension reduction and feature extraction. 1-DCNN + SDAE preserves advantages of 1-DCNN and SDAE for feature learning from high-dimensional data. This makes it be flexible for those process fault detection and diagnosis tasks. The effectiveness of 1-DCNN + SDAE is validated on a complex numerical process, two process benchmarks i.e. Tennessee Eastman process (TEP) and Fed-batch fermentation penicillin process (FBFP), and a real-life manufacturing case of industrial conveyor belt. The experimental results illustrate effectiveness of the proposed method for feature learning and fault diagnosis on multivariate manufacturing processes. The comparison between 1-DCNN + SDAE and other typical DNNs on these processes, indicates the effectiveness of the proposed method for process fault detection and diagnosis. This study will provide the guidance for development of hybrid deep learning-based multivariate control models.
Journal: International Journal of Production Research
Pages: 2426-2449
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1733701
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1733701
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Template-Type: ReDIF-Article 1.0
Author-Name: K. Nageswara Reddy
Author-X-Name-First: K. Nageswara
Author-X-Name-Last: Reddy
Author-Name: Akhilesh Kumar
Author-X-Name-First: Akhilesh
Author-X-Name-Last: Kumar
Title: Capacity investment and inventory planning for a hybrid manufacturing – remanufacturing system in the circular economy
Abstract: 
 Remanufacturing through circular economy conserves energy and materials while creating economic growth and employment. Thus, it is imperative to develop better systems that optimise the use of resources, maximise the value of the product, and minimise the total cost. Towards this, we present a two-stage stochastic linear model for a make-to-order hybrid manufacturing-remanufacturing production system by integrating capacity and inventory decisions. We consider the uncertainty in demand, core returns rate and yield to impose flexibility as both operations are considered with a collective production capacity on the same assembly line. We have considered a setting where demand for new and remanufactured products does not cannibalise each other’s demand (e.g. new parts for original equipment and remanufactured parts for independent aftermarket). Further, the capacity utilisation by core returns is considered in two ways: less capacity intensive case and more capacity intensive case. The developed model is solved for optimal inventory and capacity levels along with production quantities by maximising utilisation of resources and profit. We also present a closed-form solution by demand space partition to deduce the optimal policy of the firm. Based on our analysis, we have presented settings where remanufacturing can perfectly substitute manufacturing.
Journal: International Journal of Production Research
Pages: 2450-2478
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1734681
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1734681
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Template-Type: ReDIF-Article 1.0
Author-Name: Chuleeporn Kusoncum
Author-X-Name-First: Chuleeporn
Author-X-Name-Last: Kusoncum
Author-Name: Kanchana Sethanan
Author-X-Name-First: Kanchana
Author-X-Name-Last: Sethanan
Author-Name: Rapeepan Pitakaso
Author-X-Name-First: Rapeepan
Author-X-Name-Last: Pitakaso
Author-Name: Richard F. Hartl
Author-X-Name-First: Richard F.
Author-X-Name-Last: Hartl
Title: Heuristics with novel approaches for cyclical multiple parallel machine scheduling in sugarcane unloading systems
Abstract: 
 This paper focuses on a computational tool for scheduling sugarcane vehicles for dump tippler machines operating at a sugar mill. This problem was defined as scheduling M parallel capacitated machines with a cyclic sequence where machine restriction, and sequencing independent setup time are included with the objective to minimise makespan. To solve the problem, mathematical programing was developed to solve small-sized problems, while realistic-sized problems were solved by an effective metaheuristic called variable neighbourhood strategy adaptive search (VaNSAS). According to our literature review, it is the first time that VaNSAS has ever been proposed to solve the problem. The procedure, formulae and components of VaNSAS were first created based on the idea of increasing the search performance of existing heuristics. Additionally, K-variable move heuristics have been also first proposed. The VaNSAS was developed using the traditional Differential Evolution (DE) with heuristics embedded in it to obtain near optimal conditions for solving realistic-sized problems. The numerical results showed that the VaNSAS outperformed all other proposed methods, since it could often find new optimal solutions during the simulation, while the local search based heuristics were often trapped at some local optima and the DE lacked search intensification.
Journal: International Journal of Production Research
Pages: 2479-2497
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1734682
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1734682
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Template-Type: ReDIF-Article 1.0
Author-Name: Xu Chen
Author-X-Name-First: Xu
Author-X-Name-Last: Chen
Author-Name: Lian Qi
Author-X-Name-First: Lian
Author-X-Name-Last: Qi
Author-Name: Zuo-Jun Max Shen
Author-X-Name-First: Zuo-Jun Max
Author-X-Name-Last: Shen
Author-Name: Ye Xu
Author-X-Name-First: Ye
Author-X-Name-Last: Xu
Title: The value of trade credit under risk controls
Abstract: 
 Trade credit is widely used by companies to obtain external funds. The extant literature has demonstrated that trade credit benefits the buyer and the supplier in multiple ways, but might still induce various issues. In this paper, we focus on the impact of trade credit on growing small businesses and their suppliers. By looking into a one-supplier-one-retailer supply chain under a multiple-period setting, we study the expansion and inventory policies of the retailer with his consideration of risk control, which is critical for any small business. We also take into account the supplier's risk control decision on whether trade credit will be extended. We further numerically mimic various growth scenarios of the retailer. Interestingly, we find that, in contrast to the traditional wisdom, trade credit offered by the supplier not only increases the profits of both parties, but also reduces the retailer's default risk, as long as the supplier can apply appropriate risk controls. In addition, we show that offering trade credit does not necessarily attract retailers to act aggressively in general. Under the supplier's risk controls, the retailer's growth rate can be quite insensitive with the term of trade credit.
Journal: International Journal of Production Research
Pages: 2498-2521
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1735657
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735657
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Template-Type: ReDIF-Article 1.0
Author-Name: Lucia Botti
Author-X-Name-First: Lucia
Author-X-Name-Last: Botti
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Cristina Mora
Author-X-Name-First: Cristina
Author-X-Name-Last: Mora
Title: Modelling job rotation in manufacturing systems with aged workers
Abstract: 
 The increasing trend of retirement age in Europe represents a critical phenomenon for manufacturing and material handling activities, where repetitive activities, involving the handling of different loads at various frequencies, are usually required. These tasks can lead to occupational diseases and work-related musculoskeletal disorders, which can affect more heavily older workers, due to their decreased functional and physical capacities. On the other side, older workers positively contribute to the manufacturing processes through their expertise and their skills developed over time. This paper introduces a bi-objective mathematical model useful to assign different workers exposed to the risk of repetitive work to various workstations. A person-job fit approach is proposed, which analyses the workers’ physical capacities, competencies and mental and relational skills together with the requirements of each workstation in terms of capabilities and ergonomic load. The aim is to define the activities scheduling through two objectives: the first one considering the matches among workers abilities and workstations activities, the second one reducing the ergonomic risk of repetitive work by varying the assignments during the work shift. The method is also applied to an industrial case, whose results show its applicability and potential benefits, in terms of ergonomics and overall efficiency improvement.
Journal: International Journal of Production Research
Pages: 2522-2536
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1735659
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735659
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Template-Type: ReDIF-Article 1.0
Author-Name: J. Jiang
Author-X-Name-First: J.
Author-X-Name-Last: Jiang
Author-Name: X. Liu
Author-X-Name-First: X.
Author-X-Name-Last: Liu
Title: Bayesian Stackelberg game model for water supply networks against interdictions with mixed strategies
Abstract: 
 We address a problem of preventing an interdiction on water supply networks by building a Bayesian Stackelberg game model involving stakeholders of a defender and an interdictor. The defender initiates to allocate resource to network components to make a trade-off between network resilience measured by water satisfaction rate and the defender's cost, whereas the interdictor follows to interdict a component with the objectives of maximising the destruction level on the network structure and minimising the interdictor's cost. Specifically, the defender adopts mixed defence strategies, which implies that the interdictor is uncertain of the defender's resource allocation. Moreover, we propose sufficient conditions for the elimination of the dominated defence and interdiction strategies. A decomposed iterative learning algorithm (DILA) and a smallest-depth binary-partition based hierarchical algorithm (SBHA) are developed to reduce the sizes of the defence and interdiction strategy sets, respectively, thus analysing the optimal mixed defence strategies. Finally, a real case study with private information is conducted, thus providing valuable suggestions for the defender's resource allocation against interdictions.
Journal: International Journal of Production Research
Pages: 2537-2557
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1735661
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735661
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Lin Ma
Author-X-Name-First: Lin
Author-X-Name-Last: Ma
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Title: Workload Control order release in general and pure flow shops with limited buffer size induced blocking: an assessment by simulation
Abstract: 
 Most manufacturing shops in practice have limited physical space in front of each workstation, due, for example, to physical, economical or operational constraints. As a result, a job may cause blocking because it has to remain at a given station after an operation has been completed until space in front of the next station in its routing becomes available. Despite this practical reality, the Workload Control literature typically assumes infinite buffer limits and therefore neglects the impact of blocking. Using simulation, we highlight the direct, detrimental impact of blocking in both the pure and general flow shop. Workload Control order release dampens the effect of blocking and improves overall performance. This makes Workload Control order release even more important in the context of shops with blocking or physical space constraints. Further analysis reveals that the impact of blocking is less pronounced in the pure flow shop given its directed routing. Finally, most of the blocking that occurs is because jobs cannot enter the shop, i.e. there is no space in front of the gateway station. This re-emphasises the close relationship between blocking and release methods that limit the workload, and it highlights the importance of workload balancing.
Journal: International Journal of Production Research
Pages: 2558-2569
Issue: 8
Volume: 59
Year: 2021
Month: 4
X-DOI: 10.1080/00207543.2020.1735667
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735667
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Template-Type: ReDIF-Article 1.0
Author-Name: Zebiao Feng
Author-X-Name-First: Zebiao
Author-X-Name-Last: Feng
Author-Name: Jianjun Wang
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wang
Author-Name: Yizhong Ma
Author-X-Name-First: Yizhong
Author-X-Name-Last: Ma
Author-Name: Yiliu Tu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Tu
Title: Robust parameter design based on Gaussian process with model uncertainty
Abstract: 
 In robust parameter design, it is common to use computer models to simulate the relationships between input variables and output responses. However, for the contaminated experimental data, the model uncertainty between computer models and actual physical systems will seriously impair the robustness of the optimal input settings. In this paper, we propose a new weighted robust design approach concerning the model uncertainty from outliers based on the robust Gaussian process model with a Student-t likelihood (StGP). Firstly, to reduce the impact of outliers on the output means and variances, the StGP modelling technique is adopted to estimate the relationship models for contaminated data. Secondly, the Gibbs sampling technique is employed to estimate model parameters for better mixing and convergence. Finally, an optimisation scheme integrating the quality loss function and confidence interval analysis approach is built to find the feasible optimisation solution. Meanwhile, the hypersphere decomposition method and data-driven method are applied to determine the relative weights of objective functions. Two examples are used to demonstrate the effectiveness of the proposed approach. The comparison results show that the proposed approach can achieve better performance than other approaches by considering the model uncertainty from outliers.
Journal: International Journal of Production Research
Pages: 2772-2788
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1740344
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1740344
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Template-Type: ReDIF-Article 1.0
Author-Name: D. Manafi
Author-X-Name-First: D.
Author-X-Name-Last: Manafi
Author-Name: M. J. Nategh
Author-X-Name-First: M. J.
Author-X-Name-Last: Nategh
Title: Integrating the setup planning with fixture design practice by concurrent consideration of machining and fixture design principles
Abstract: 
 In the conventional setup planning methods, the required fixtures are planned in a sequential order relative to other activities of the setup planning. In the present study, a new approach has been developed and a concurrent method has been proposed for integrating the setup planning and fixture design practice, which paves the way for considering the fixture design principles in parallel to setup planning activities. This eliminates the need to revise the setup plans to remedy the possible conflicts which are common to conventional procedures. The fixture principles have been cast into mathematical relations as a means to developing the proposed method. In the present study, the locating surfaces are determined as the most important step of the fixture system design. The reference faces which cannot be used as locating surfaces are also distinguished, in order for the designer to revise the design of the workpiece.
Journal: International Journal of Production Research
Pages: 2647-2666
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1736357
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1736357
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Template-Type: ReDIF-Article 1.0
Author-Name: Ke Chen
Author-X-Name-First: Ke
Author-X-Name-Last: Chen
Author-Name: Danli Yao
Author-X-Name-First: Danli
Author-X-Name-Last: Yao
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Author-Name: Min Ji
Author-X-Name-First: Min
Author-X-Name-Last: Ji
Title: Production scheduling with autonomous and induced learning
Abstract: 
 The vast majority of scheduling research involving the learning effect only considers autonomous learning, i.e. learning by doing. Proactive investment in learning promotion, i.e. induced learning, is rarely considered. Nevertheless, induced learning is important for total production cost reduction and helping managers control the production systems, which can be interpreted as management or investment seeking to improve employees’ working efficiency. We consider in this paper scheduling models with both autonomous and induced learning. The objective is to find the optimal sequence and level of induced learning that optimise a scheduling criterion plus the investment cost. We propose polynomial-time algorithms to solve all the single-machine scheduling problems considered and the parallel-machine problem to minimise the total completion time plus the investment cost. We also propose an approximate algorithm for the parallel-machine problem to minimise the makespan plus the investment cost.
Journal: International Journal of Production Research
Pages: 2817-2837
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1740816
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1740816
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Template-Type: ReDIF-Article 1.0
Author-Name: Sungbum Jun
Author-X-Name-First: Sungbum
Author-X-Name-Last: Jun
Author-Name: Seokcheon Lee
Author-X-Name-First: Seokcheon
Author-X-Name-Last: Lee
Title: Learning dispatching rules for single machine scheduling with dynamic arrivals based on decision trees and feature construction
Abstract: 
 In this paper, we address the dynamic single-machine scheduling problem for minimisation of total weighted tardiness by learning of dispatching rules (DRs) from schedules. We propose a decision-tree-based approach called Generation of Rules Automatically with Feature construction and Tree-based learning (GRAFT) in order to extract dispatching rules from existing or good schedules. GRAFT consists of two phases: learning a DR from schedules, and improving the DR with feature-construction-based genetic programming. With respect to the process of learning DRs from schedules, we present an approach for transforming schedules into training data containing underlying scheduling decisions and generating a decision-tree-based DR. Thereafter, the second phase improves the learned DR by feature-construction-based genetic programming so as to minimise the average total weighted tardiness. We conducted experiments to verify the performance of the proposed approach, and the results showed that it outperforms the existing dispatching rules. Moreover, the proposed algorithm is effective in terms of extracting scheduling insights in such understandable formats as IF–THEN rules from existing schedules and improving DRs by grafting a new branch with a discovered attribute into a decision tree.
Journal: International Journal of Production Research
Pages: 2838-2856
Issue: 9
Volume: 59
Year: 2021
Month: 05
X-DOI: 10.1080/00207543.2020.1741716
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1741716
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Template-Type: ReDIF-Article 1.0
Author-Name: Diptiranjan Mahapatra
Author-X-Name-First: Diptiranjan
Author-X-Name-Last: Mahapatra
Author-Name: Rajesh Katiyar
Author-X-Name-First: Rajesh
Author-X-Name-Last: Katiyar
Author-Name: Ratri Parida
Author-X-Name-First: Ratri
Author-X-Name-Last: Parida
Author-Name: Divesh Kumar
Author-X-Name-First: Divesh
Author-X-Name-Last: Kumar
Title: A fuzzy multi-criteria approach for evaluating the contribution of freight transportation towards India’s Nationally Determined Contributions (NDCs)
Abstract: 
 Adoption of the Paris Agreement in December 2015 and its subsequent ratification through Nationally Determined Contribution (NDC) marked, among other things, India’s commitment to reduce the emission intensity of its GDP by 33–35 per cent by 2030 from 2005 level. The transport sector, being the prime conduit of production value-chain, has been a major contributor to global energy-related greenhouse gas (GHG) emissions. In this context, it is critical production research study that needs to evaluate the linkage of NDC with freight transport. The proposed framework consists of goal setting, seeking expert opinion and driving insights into the field of freight transport. First, goal and criteria or attribute for achieving NDC through the freight sector are identified. Next, expert opinions from transport and climate change specialists  are sought. Lastly, results and insights related to the most feasible alternatives, such as heavy road, heavy rail, hybrid, heavy waterborne, and heavy air with regard to the select attributes and its sub-attributes viz, slower growth, structural changes in sector and economy, strategic and operational choices, technology and innovation and regulatory and economic instruments with the help of fuzzy analytic hierarchy process (FAHP) are drawn. The strength of the proposed methodology is that it uses FAHP to prescribe definitive solutions to climate change policymakers and logistics and supply chain managers who otherwise would have found difficulties  with such an arcane subject having partial and little quantified information.
Journal: International Journal of Production Research
Pages: 2857-2884
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1743891
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1743891
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Template-Type: ReDIF-Article 1.0
Author-Name: Lu Chen
Author-X-Name-First: Lu
Author-X-Name-Last: Chen
Author-Name: Jinfeng Wang
Author-X-Name-First: Jinfeng
Author-X-Name-Last: Wang
Author-Name: Wenhui Yang
Author-X-Name-First: Wenhui
Author-X-Name-Last: Yang
Title: A single machine scheduling problem with machine availability constraints and preventive maintenance
Abstract: 
 Considering the impact of machine availability is essential in production scheduling, especially when the target is to minimise total tardiness. In this study, a single machine scheduling problem derived from a rotor production workshop is addressed. We evaluate machine availability by its reliability, which can be restored by preventive maintenance (PM). PM with different improvement effectiveness is considered in the problem formulation. A genetic algorithm (GA) is developed to solve the problem. Emmons dominance rules are applied in the mutation processes of the GA. Computational experiments demonstrate the effectiveness and efficiency of the algorithm. Sensitivity analyses have been conducted to provide useful managerial insights for real workshop scheduling.
Journal: International Journal of Production Research
Pages: 2708-2721
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1737336
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1737336
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Template-Type: ReDIF-Article 1.0
Author-Name: Debiao Li
Author-X-Name-First: Debiao
Author-X-Name-Last: Li
Author-Name: Jing Wang
Author-X-Name-First: Jing
Author-X-Name-Last: Wang
Author-Name: Rui Qiang
Author-X-Name-First: Rui
Author-X-Name-Last: Qiang
Author-Name: Raymond Chiong
Author-X-Name-First: Raymond
Author-X-Name-Last: Chiong
Title: A hybrid differential evolution algorithm for parallel machine scheduling of lace dyeing considering colour families, sequence-dependent setup and machine eligibility
Abstract: 
 Dyeing is the most time and energy-consuming process in textile production. Motivated by a dyeing overdue problem in a lace textile factory, we study a parallel machine scheduling problem with different colour families, sequence-dependent setup times, and machine eligibility restriction. An integer programming model is formulated to minimise the total tardiness. Given that the dyeing optimisation problem is strongly NP-hard, a hybrid differential evolution (HDE) algorithm embedded with chaos theory and two local search algorithms is proposed to solve real-world instances from the textile factory. In our proposed algorithm, a special encoding and decoding scheme is designed to deal with the machine eligibility constraint, and chaos theory is adopted to determine the parameter settings of the underlying differential evolution (DE) algorithm. To speed up convergence and improve search exploitation, two local search algorithms inspired by two dominance properties are developed to determine the optimal job sequence for parallel machines, such that the decision of the entire problem is simplified to the assignment of jobs among the machines, and the computational time required is significantly reduced. Comprehensive experiments based on 36 synthetically generated small to large-scale problem instances and 20 real-world industrial data sets confirm the efficacy of our proposed HDE over other DE variants.
Journal: International Journal of Production Research
Pages: 2722-2738
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1740341
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1740341
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Template-Type: ReDIF-Article 1.0
Author-Name: Bibekananda Mishra
Author-X-Name-First: Bibekananda
Author-X-Name-Last: Mishra
Author-Name: Biswajit Mahanty
Author-X-Name-First: Biswajit
Author-X-Name-Last: Mahanty
Author-Name: Jitesh J. Thakkar
Author-X-Name-First: Jitesh J.
Author-X-Name-Last: Thakkar
Title: A quantifiable quality enabled servitisation model: benchmarking Indian automobile manufacturers
Abstract: 
 In spite of increasing importance of servitisation for the success of automobile organisations, the factors that influence it are not well researched. In this paper, we discuss the important issue of computing service quality of an automobile organisation and put forward a graph theory-based methodology to evaluate the factors affecting the quality in the servitisation practices to propose a critical service quality index (CSQI) to measure the same. The application of the proposed methodology is demonstrated in three Indian automobile organisations. This ensures the validation of the proposed approach and also helps to evolve select key recommendations for improving servitisation quality in the Indian automobile organisation. This research advances the present body of knowledge by making three-fold contributions. First, it delivers an organised methodology for quantification of services on adoption of servitisation in an automobile manufacturer and integrates the results obtained in the form of a critical service quality index. The proposed methodology is equally beneficial for assessment and classification of a set of manufacturers. Second, it demonstrates an application of methodology for three Indian automobile organisations to develop select key recommendations which can be seen as a first attempt in the field of servitisation in the Indian context. Finally, the paper proposes a conceptual framework for addressing servitisation challenges and extends key recommendations for improving competitiveness of an automotive organisation through servitisation.
Journal: International Journal of Production Research
Pages: 2667-2689
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1736721
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1736721
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2667-2689




Template-Type: ReDIF-Article 1.0
Author-Name: Hasan Hüseyin Turan
Author-X-Name-First: Hasan Hüseyin
Author-X-Name-Last: Turan
Author-Name: Fuat Kosanoglu
Author-X-Name-First: Fuat
Author-X-Name-Last: Kosanoglu
Author-Name: Mahir Atmis
Author-X-Name-First: Mahir
Author-X-Name-Last: Atmis
Title: A multi-skilled workforce optimisation in maintenance logistics networks by multi-thread simulated annealing algorithms
Abstract: 
 The sustainability of service and manufacturing operations rely heavily on the availability of equipment and assets. High availability of assets can be achieved with effective maintenance strategies. In this direction, we study a multi-skilled workforce planning problem to establish a resilient maintenance service network for high-value assets. We improve the efficiency of the maintenance network by optimising the workforce capacity in repair shops and achieving workforce heterogeneity by cross-training. As a solution strategy, we develop a two-stage iterative heuristic algorithm. At the first stage, the set of all feasible cross-training policies is effectively and systematically searched via a state-of-art multi-thread simulated annealing (MTSA) metaheuristic to find a policy(ies) that achieves the minimum cost. Further, the developed MTSA algorithm is enhanced with the multi-neighbourhood feature to escape from local optimality and implemented via parallel programming techniques. In the second stage, workforce capacity and spare parts inventory levels are optimised for the cross-training policy found at the first stage by a queuing approximation and a greedy heuristic. The MTSA obtains the lowest cost in 91 cases out of 128 compared to genetic algorithm (GA), variable neighbourhood search (VNS), an improved single-thread simulated annealing algorithm (SA) and integer programming-based clustering (IPBC) algorithms.
Journal: International Journal of Production Research
Pages: 2624-2646
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1735665
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735665
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2624-2646




Template-Type: ReDIF-Article 1.0
Author-Name: Byung Cho Kim
Author-X-Name-First: Byung Cho
Author-X-Name-Last: Kim
Author-Name: Hosun Rhim
Author-X-Name-First: Hosun
Author-X-Name-Last: Rhim
Author-Name: Hongsuk Yang
Author-X-Name-First: Hongsuk
Author-X-Name-Last: Yang
Title: Price competition or technology improvement? An investigation of green car technology
Abstract: 
 Huge investments in green car research are being made in both the private and public sectors to cope with fuel shortage and environmental challenges. While the future of the green car industry is believed to be promising, its current status of technology is still remote from full-scale commercialisation. Interestingly, car manufacturers focus on different technologies for green car development, for instance, electric, fuel cells, and clean diesel. Given the platform characteristics of green car technology and the technology gap among manufacturers, an interesting question becomes whether both technologically superior and inferior green car manufacturers survive competition and if so, under what conditions. In this paper, we examine competing green car manufacturers’ strategic choice between price competition and technology improvement (e.g. R&D investment). Grounded in a stylised model, we find the profit- and welfare-maximising price levels and examine technology improvement effort. Next, we investigate how the scope of network externality and cost differential influence manufacturers’ strategic choices, and discuss the welfare implications.
Journal: International Journal of Production Research
Pages: 2800-2816
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1740347
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1740347
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2800-2816




Template-Type: ReDIF-Article 1.0
Author-Name: Abdolmajid Yolmeh
Author-X-Name-First: Abdolmajid
Author-X-Name-Last: Yolmeh
Author-Name: Ullah Saif
Author-X-Name-First: Ullah
Author-X-Name-Last: Saif
Title: Closed-loop supply chain network design integrated with assembly and disassembly line balancing under uncertainty: an enhanced decomposition approach
Abstract: 
 In recent years, environmental concerns have increased the need for design and optimisation of closed-loop supply chain (CLSC) networks. Majority of the existing research papers consider the CLSC network designing and line balancing decisions separately. However, this approach may lead to sub-optimal designs due to the interdependency of these decisions. To this end, this paper investigates a CLSC network designing problem integrated with assembly and disassembly line balancing under demand and return uncertainty. The proposed CLSC network contains manufacturers, remanufacturers, assembly centres, intermediate centres (where disassembly lines are located), and customer centres. A new mixed integer non-linear programming model for the proposed problem is developed. Furthermore, an enhanced decomposition approach is developed to solve the proposed model. Computational results, based on randomly generated problem instances, show the efficiency of proposed enhanced decomposition approach. Specifically, results shows that the proposed enhanced decomposition approach leads to significantly smaller running times in comparison with an existing decomposition approach. Results also highlight the importance of integrating supply chain network designing and line balancing decisions.
Journal: International Journal of Production Research
Pages: 2690-2707
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1736723
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1736723
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2690-2707




Template-Type: ReDIF-Article 1.0
Author-Name: Xiao Xu
Author-X-Name-First: Xiao
Author-X-Name-Last: Xu
Author-Name: Sang-Do Lee
Author-X-Name-First: Sang-Do
Author-X-Name-Last: Lee
Author-Name: Hwan-Seong Kim
Author-X-Name-First: Hwan-Seong
Author-X-Name-Last: Kim
Author-Name: Sam-Sang You
Author-X-Name-First: Sam-Sang
Author-X-Name-Last: You
Title: Management and optimisation of chaotic supply chain system using adaptive sliding mode control algorithm
Abstract: 
 This paper deals with adaptive super-twisting (STW) sliding mode control (SMC) algorithm to manage chaotic supply chain system. A multi-echelon supply chain system having parametric perturbations and disturbances is presented to demonstrate chaotic nonlinear dynamical behaviours. When changing input variables slightly in the supply chain system, the predicted outputs will be completely different due to chaotic behaviours with bifurcation. In addition, various uncertainties along with exogenous disturbances make the system dynamics more complex to manage as they propagate both upstream and downstream of the supply chain networks. Particularly, the adaptive STW SMC algorithm has been designed for chaos suppression and synchronisation of the supply chain system. Next, the robust control algorithm with adaptive law for the closed-loop system has been proved by using Lyapunov stability theorem. Then, extensive numerical simulations are conducted to demonstrate the validity of the active control synthesis for optimal operations management of chaotic supply chain networks. The control algorithm based on system theory provides satisfactory performance on achieving chaos suppression and synchronisation of the chaotic supply system. The control system theory can be expanded into new integration software applications for operations management of supply chain networks. Finally, the presented control synthesis with dynamical analysis is essential for strategic decision-makers in the modern supply chain management.
Journal: International Journal of Production Research
Pages: 2571-2587
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1735662
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735662
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2571-2587




Template-Type: ReDIF-Article 1.0
Author-Name: Xinwen Shang
Author-X-Name-First: Xinwen
Author-X-Name-Last: Shang
Author-Name: Jelena Milisavljevic-Syed
Author-X-Name-First: Jelena
Author-X-Name-Last: Milisavljevic-Syed
Author-Name: Sihan Huang
Author-X-Name-First: Sihan
Author-X-Name-Last: Huang
Author-Name: Guoxin Wang
Author-X-Name-First: Guoxin
Author-X-Name-Last: Wang
Author-Name: Janet K. Allen
Author-X-Name-First: Janet K.
Author-X-Name-Last: Allen
Author-Name: Farrokh Mistree
Author-X-Name-First: Farrokh
Author-X-Name-Last: Mistree
Title: A key feature-based method for the configuration design of a reconfigurable inspection system
Abstract: 
 A reconfigurable manufacturing system (RMS) can provide a customised manufacturing process to complete changes in operational requirements or machine status. The effective development of an RMS is supported by dynamic reconfiguration management that detects errors in the process and explores the reconfiguration strategy. However, existing studies on reconfiguration focus on production while ignoring inspection. In the RMS, a reconfigurable inspection system (RIS) is developed for data-oriented detection of product quality with the minimally sufficient number of inspection machines. We propose a key feature-based method for designing the RIS’s configuration to achieve a satisfactory RIS design, which detects different processes and satisfies the inspection requirement for each phase of the RMS’s lifecycle. The key features of the RIS (i.e. modularity, integrability, customisation, scalability, convertibility and diagnosability) are identified based on the RMS’s detection mechanism. An example of the RMS for a spindle box is presented to validate the method.
Journal: International Journal of Production Research
Pages: 2611-2623
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1735664
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735664
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2611-2623




Template-Type: ReDIF-Article 1.0
Author-Name: Marco Caserta
Author-X-Name-First: Marco
Author-X-Name-Last: Caserta
Author-Name: Stefan Voß
Author-X-Name-First: Stefan
Author-X-Name-Last: Voß
Title: Accelerating mathematical programming techniques with the corridor method
Abstract: 
 In this paper we investigate how the Benders decomposition, Lagrangean relaxation, and Dantzig–Wolfe reformulation techniques can be accelerated when intertwined with the corridor method. We test the approaches on the capacitated lot sizing problem with setups. Due to the computational complexity of this lot sizing problem, one would expect to find a number of approaches based on decomposition techniques in the literature. While this is true for Lagrangean relaxation and Dantzig–Wolfe reformulation, we could not find any paper proposing the use of Benders decomposition for the problem at hand. Consequently, with this study, we pursue a two-fold goal: First, and foremost, we want to determine how effective the corridor method is as acceleration scheme for these decomposition techniques; second, we aim at gaining some insight into why Benders has not been proposed for this class of problems. Our results shed light on both issues. On the one hand, we show that all the decomposition methods benefit from the hybridisation with the corridor method. On the other hand, a thorough analysis on the behaviour and limitations of Benders algorithm is provided. We conclude the study with a statistical analysis to determine whether significant differences in performance among the different implementations arise.
Journal: International Journal of Production Research
Pages: 2739-2771
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1740343
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1740343
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2739-2771




Template-Type: ReDIF-Article 1.0
Author-Name: Guodong Yu
Author-X-Name-First: Guodong
Author-X-Name-Last: Yu
Author-Name: Aijun Liu
Author-X-Name-First: Aijun
Author-X-Name-Last: Liu
Author-Name: Huiping Sun
Author-X-Name-First: Huiping
Author-X-Name-Last: Sun
Title: Risk-averse flexible policy on ambulance allocation in humanitarian operations under uncertainty
Abstract: 
 Proactive ambulance management is constructive to improve the response efficiency for emergency medical service (EMS) systems under uncertainty. In this paper, we present a dynamic optimisation model concerning the ambulance dispatching and relocation. We develop a flexible operation policy driven by the interval rolling to match vehicles with calls in batch. We formulate the problem in Markov Decision Process and incorporate 
 $M/G/c $M/G/c queues to minimise the average response and delay time. Considering the curse-of-dimensionality, we provide a simulation-based empirical dynamic programming with the state aggregation and post-decision state to solve the model. To further accelerate the computational efficiency, a greedy heuristic method is introduced to improve the quality of sampling operations. Then, a risk-averse model is developed based on the stochastic dominance strategy to improve operational reliability. We develop an equivalent linear programming to evaluate concave dominating functions. We test the performance by a numerical case and extract managerial insights for practitioners. Our results show that the proposed flexible and risk-averse solution outperforms the classic model on reducing the delay under uncertain calls. And the improvement is more active during peak hours, when real-time needs exceed available ambulances.
Journal: International Journal of Production Research
Pages: 2588-2610
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1735663
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1735663
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2588-2610




Template-Type: ReDIF-Article 1.0
Author-Name: S. S. Panwalkar
Author-X-Name-First: S. S.
Author-X-Name-Last: Panwalkar
Author-Name: Christos Koulamas
Author-X-Name-First: Christos
Author-X-Name-Last: Koulamas
Title: New results for minimising variation of flow time in two-machine proportionate no-wait flow shops
Abstract: 
 In this paper, the two-machine no-wait proportionate flow shop problem is analysed with the objective of minimising the total absolute deviation of job completion times. The optimality of V-shaped sequences is extended to problems with 12 jobs and it is shown that an optimal sequence may not be V-shaped with 13 jobs. For problems of larger size, the best V-shaped sequence is determined in linear time without resorting to dynamic programming. For larger size problems, it is shown that the number of non-dominated potentially optimal semi-V-shaped sequences increases rapidly. This indicates that derivation of optimal solutions in low order polynomial time is unlikely with a large number of jobs. Finally, the findings are extended to the corresponding problem with the objective of minimising the total absolute differences in waiting times.
Journal: International Journal of Production Research
Pages: 2789-2799
Issue: 9
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1740345
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1740345
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2789-2799




Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Fattahi
Author-X-Name-First: Mohammad
Author-X-Name-Last: Fattahi
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Mehdi Farhadkhani
Author-X-Name-First: Mehdi
Author-X-Name-Last: Farhadkhani
Title: Sustainable supply chain planning for biomass-based power generation with environmental risk and supply uncertainty considerations: a real-life case study
Abstract: 
 This paper addresses the design and planning of a supply chain (SC) system for power generation from biomass by using various technologies. A two-stage stochastic programming model is developed to find an effective design strategy under stochastic and highly seasonal biomass supply. The biomass usage, as a renewable energy source, for the power generation affects the environment and society in multiple ways, such as social expectations, life-threatening issues, and greenhouse gas emissions. As a consequence, in the stochastic model, by the social life cycle assessment (S-LCA) approach, the SC’s social impact is guaranteed to be larger than a minimum acceptable rate. Furthermore, the environmental risk of the SC is quantified based on its air pollutant and greenhouse gas emissions and mitigated. To deal with the biomass supply uncertainty, discrete scenarios are generated using a backward scenario reduction approach. Computational results are presented on a real-life case study in Iran to show the stochastic model’s applicability in evaluating the economic potential, the sustainability aspects, and the required infrastructure for the planning of the SC system. In addition, to drive managerial insights, sensitivity analysis on key parameters of the optimisation problem is done.
Journal: International Journal of Production Research
Pages: 3084-3108
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1746427
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1746427
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Template-Type: ReDIF-Article 1.0
Author-Name: Biao Xu
Author-X-Name-First: Biao
Author-X-Name-Last: Xu
Author-Name: Zhong Yao
Author-X-Name-First: Zhong
Author-X-Name-Last: Yao
Author-Name: Shin-yi Wu
Author-X-Name-First: Shin-yi
Author-X-Name-Last: Wu
Title: Pricing strategies for a bundled channel with services network effects
Abstract: 
 This paper examines the impact of channel contracts on pricing strategies and profitability with considering service network effects. Specifically, we model a bundled distribution channel that consists of a product manufacturer and a service operator under two popular channel contracts (the wholesale contract and the agency contract). The optimal pricing policies for the product manufacturer and service operator are derived under both contracts. We compare channel performance under two channel contacts, and we find that the marginal costs of manufacturer play a critical role. When the marginal manufacturing cost is relatively small, the agency bundled channel outperforms the wholesale bundled channel; when the marginal manufacturing cost is sufficiently large, the wholesale bundled channel is better. We further identify two conditions under which the agency contract is preferred over the wholesale contract. For service network externality, we show that it has a remarkable effect on pricing scheme, market demand and total channel performance. Our research thus is the first to investigate the influence of distribution contracts and service network externality on the bundled channel dynamics.
Journal: International Journal of Production Research
Pages: 3152-3168
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1746852
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1746852
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:3152-3168




Template-Type: ReDIF-Article 1.0
Author-Name: Katyanne Farias
Author-X-Name-First: Katyanne
Author-X-Name-Last: Farias
Author-Name: Khaled Hadj-Hamou
Author-X-Name-First: Khaled
Author-X-Name-Last: Hadj-Hamou
Author-Name: Claude Yugma
Author-X-Name-First: Claude
Author-X-Name-Last: Yugma
Title: Model and exact solution for a two-echelon inventory routing problem
Abstract: 
 The classic version of the Inventory Routing Problem considers a system with one supplier that manages the inventory level of a set of customers. The supplier defines when and how much products to supply and how to combine customers in routes while minimising storage and transportation costs. We present a new version of this problem that considers a two-echelon system with indirect deliveries and routing decisions at both levels. In this variant, the products are delivered to customers through distribution centres to meet demands with a minimum total cost. We propose a mathematical formulation and a branch-and-cut algorithm combined with a two-step matheuristic to solve the proposed problem for different inventory policies and routing configurations. Intrinsic new valid inequalities to the two-echelon system are introduced. We analyse the efficiency of the new valid inequalities as well as the already known valid inequalities from the literature. Computational experiments are presented for a new set of benchmark instances. The results show that, for the simplest inventory policy, the proposed method is able to solve small and some medium-scale instances to the proven optimality and find feasible solutions for all instances.
Journal: International Journal of Production Research
Pages: 3109-3132
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1746428
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1746428
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:3109-3132




Template-Type: ReDIF-Article 1.0
Author-Name: Qingxin Guo
Author-X-Name-First: Qingxin
Author-X-Name-Last: Guo
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Author-Name: Jiyin Liu
Author-X-Name-First: Jiyin
Author-X-Name-Last: Liu
Author-Name: Shengnan Zhao
Author-X-Name-First: Shengnan
Author-X-Name-Last: Zhao
Title: Continuous-time formulation and differential evolution algorithm for an integrated batching and scheduling problem in aluminium industry
Abstract: 
 This paper investigates an integrated batching and scheduling problem of electrolysis and caster in aluminium industry. The problem is to determine the assignment and scheduling of orders considering sequence-dependent setup times caused by technological and operational constraints of electrolysis cells, and determine the batching and scheduling of orders in the following casters. A novel unit-specific event-based continuous-time mixed integer linear programming model (MILP) is proposed to describe the problem. In this model, the event point is stage specific, and lower bounds are specified to tighten the model. A hybrid pointer-based differential evolution algorithm with new individual representation scheme is designed to solve the problem of industrial scale. An improved hybrid pointer-based mutation operator and a new point-cross crossover operator are proposed to enhance the performance of the algorithm. Computational experiments show that the proposed algorithm is more efficient when compared with CPLEX for medium and large size instances. Comparisons with the lower bound demonstrate that the algorithm is effective.
Journal: International Journal of Production Research
Pages: 3169-3184
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1747656
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1747656
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:3169-3184




Template-Type: ReDIF-Article 1.0
Author-Name: Daniel Barberato Henrique
Author-X-Name-First: Daniel Barberato
Author-X-Name-Last: Henrique
Author-Name: Moacir Godinho Filho
Author-X-Name-First: Moacir Godinho
Author-X-Name-Last: Filho
Author-Name: Giuliano Marodin
Author-X-Name-First: Giuliano
Author-X-Name-Last: Marodin
Author-Name: Ana Beatriz Lopes de Sousa Jabbour
Author-X-Name-First: Ana Beatriz Lopes de Sousa
Author-X-Name-Last: Jabbour
Author-Name: Charbel Jose Chiappetta Jabbour
Author-X-Name-First: Charbel Jose
Author-X-Name-Last: Chiappetta Jabbour
Title: A framework to assess sustaining continuous improvement in lean healthcare
Abstract: 
 Many hospitals have achieved high levels of lean performance only to lose it later on. This research develops a theoretical understanding of how organisations can sustain lean in healthcare, through a practical and innovative framework to assess the maturity level of lean in healthcare that can be used by both practitioners and academics. Through the analysis of the literature, it was possible to compile 22 main critical success factors of lean sustainability in hospitals. A comparative case study provides evidence to confirm these 22 theoretical propositions, and also to add other 3 new success factors to the framework. The proposed framework allows hospitals to conduct a structured process of change, with all the foundation needed to succeed and sustain the lean journey in the long-term. New insights are revealed by studying hospitals after minimum 18 months of lean implementation and comparing the ones that have achieved a high level of lean sustainability with those that did not. To the best of our knowledge, this article is the first to attempt to bring together the key factors that influence hospitals to sustain lean improvements in the long term.
Journal: International Journal of Production Research
Pages: 2885-2904
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1743892
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1743892
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:2885-2904




Template-Type: ReDIF-Article 1.0
Author-Name: James K. Starling
Author-X-Name-First: James K.
Author-X-Name-Last: Starling
Author-Name: Youngjun Choe
Author-X-Name-First: Youngjun
Author-X-Name-Last: Choe
Author-Name: Christina Mastrangelo
Author-X-Name-First: Christina
Author-X-Name-Last: Mastrangelo
Title: Identifying DMSMS availability risk at the system level
Abstract: 
 Many enterprise systems are comprised of parts with shorter product lifetimes than the system lifetime. Managing the availability of the parts in the supply chain to ensure uninterrupted operation of the system is non-trivial and can be costly in terms of capital and resources. A DMSMS (Diminishing Manufacturing Sources and Material Shortages) issue is the loss, or impending loss, of a manufacturer because the manufacturer discontinues production or support of needed parts. Proactive DMSMS requires the ability to forecast part availability in the marketplace under varying conditions. This paper goes beyond part-level forecasting by developing a framework to estimate availability risk at the system level. The proposed framework quantifies and compares availability risk for multiple parts in a system using a finite-source capacitated queuing model. Two availability risk metrics are defined: the fraction of time with no vendor parts available and the time until a part will be unavailable in the market. The metrics are demonstrated in scenarios that a DMSMS practitioner is likely to experience. The results demonstrate that the framework can be used to inform proactive DMSMS decisions by providing a measurement of the risk in the logistics system which supports cost and resource allocation trade-offs.
Journal: International Journal of Production Research
Pages: 2905-2925
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1743894
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1743894
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Template-Type: ReDIF-Article 1.0
Author-Name: Bingbing Liu
Author-X-Name-First: Bingbing
Author-X-Name-Last: Liu
Author-Name: Xiaolong Guo
Author-X-Name-First: Xiaolong
Author-X-Name-Last: Guo
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Lin Tian
Author-X-Name-First: Lin
Author-X-Name-Last: Tian
Title: Manufacturer's contract choice facing competing downstream online retail platforms
Abstract: 
 Reseller contract and online marketplace contract are two typical supply chain contracts provided by Online retail platforms (ORPs) in online retailing. Manufacturers can either wholesale their products to an ORP using the traditional reseller contract or choose an agency selling contract to sell their products directly to consumers through an online marketplace provided by the ORP. Based on a game model, this paper studies the contract choice strategy for a monopoly manufacturer facing two competing downstream ORPs. The results show that the competition intensity between the ORPs and the order-fulfilment costs critically moderates the choice decision. Specifically, for a given competition intensity (level of order-fulfilment costs), with rising order-fulfilment costs (the downstream competition intensity), the preferred mode for the manufacturer switches from the pure online marketplace mode to the hybrid mode and then to the pure reseller mode. The intuition of this lies in the interaction of the transfer of the pricing rights and the responsibility for order fulfilment. Meanwhile, the conditions to ensure the dominant equilibrium in the competition of ORPs are analysed. Finally, we extend the basic model by relaxing the assumptions about the same proportion fee rate and the fixed order-fulfilment cost.
Journal: International Journal of Production Research
Pages: 3017-3041
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1744767
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1744767
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:3017-3041




Template-Type: ReDIF-Article 1.0
Author-Name: Tong-Yuan Wang
Author-X-Name-First: Tong-Yuan
Author-X-Name-Last: Wang
Author-Name: Yan-Lai Li
Author-X-Name-First: Yan-Lai
Author-X-Name-Last: Li
Author-Name: Hong-Tai Yang
Author-X-Name-First: Hong-Tai
Author-X-Name-Last: Yang
Author-Name: Kwai-Sang Chin
Author-X-Name-First: Kwai-Sang
Author-X-Name-Last: Chin
Author-Name: Zeng-Qiang Wang
Author-X-Name-First: Zeng-Qiang
Author-X-Name-Last: Wang
Title: Information sharing strategies in a hybrid-format online retailing supply chain
Abstract: 
 This paper considers a hybrid-format online retailing supply chain in which a manufacturer sells products to an online retailer and an intermediary with a wholesale contract, the retailer sells them through the intermediary by paying a commission fee (i.e. agency selling format), and the intermediary resells products as an e-tailer (i.e. reselling format). We use a theoretical model to answer a key question: whether the intermediary has an incentive to share demand information with others, and if it shares, which strategy is most beneficial to each member? Four information-sharing models are established and the results show that the intermediary always has incentive to share information voluntarily, and the best strategy strongly depends on the channel competition intensity and proportional fee. In addition, the manufacturer (retailer) can obtain profit if the intermediary only shares information with him (her), and all members can achieve a Pareto improvement (i.e. win–win–win situation) when both the manufacturer and retailer are informed. We further examine the impact of platform cost to demonstrate the robustness of results. When manufacturer cooperates with the retailer, the intermediary always intends to share information, whereas it has no incentive to do so if the intermediary and retailer make a coalition.
Journal: International Journal of Production Research
Pages: 3133-3151
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1746851
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1746851
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Template-Type: ReDIF-Article 1.0
Author-Name: Qi Chen
Author-X-Name-First: Qi
Author-X-Name-Last: Chen
Author-Name: Zhengguo Wang
Author-X-Name-First: Zhengguo
Author-X-Name-Last: Wang
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: René B. M. De Koster
Author-X-Name-First: René B. M.
Author-X-Name-Last: De Koster
Author-Name: Wanying Chen
Author-X-Name-First: Wanying
Author-X-Name-Last: Chen
Title: Performance evaluation of compact automated parking systems with mobile application and customer service priority
Abstract: 
 We study a recently introduced smart compact automated parking system (CAPS), deploying straddle carriers, which require little footprint area. The straddle carriers can elevate and move a car over other cars in the horizontal direction in deep storage lanes, thereby considerably increasing the car storage capacity. Customers can reserve a parking space with a mobile application, or just drive in. Customers with booking by mobile application receive priority over the drive-in customers. We build priority queueing network models to evaluate the performance of a CAPS with priority booking under two storage policies. We then develop approximation methods to solve the analytical models and validate them through simulation. Numerical experiments show that the waiting time of a customer with booking can be reduced by 9.2% and 3.4%, respectively, for the dedicated and shared storage policies, compared with systems without priority booking. Then we compare the dedicated and shared storage policies and conduct a sensitivity analysis on the arrival rates of two types of cars. To minimise the expected retrieval time, the optimal ratio of width to height should be around 1.3. Finally, we calculate the investment cost of a CAPS and compare it with a competitive cylindrical automated parking tower.
Journal: International Journal of Production Research
Pages: 2926-2959
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1743895
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1743895
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Template-Type: ReDIF-Article 1.0
Author-Name: Stephen Mahar
Author-X-Name-First: Stephen
Author-X-Name-Last: Mahar
Author-Name: P. Daniel Wright
Author-X-Name-First: P. Daniel
Author-X-Name-Last: Wright
Author-Name: Peter A. Salzarulo
Author-X-Name-First: Peter A.
Author-X-Name-Last: Salzarulo
Author-Name: Kathleen Iacocca
Author-X-Name-First: Kathleen
Author-X-Name-Last: Iacocca
Title: Using transaction data and product margins to optimise weekly flyers
Abstract: 
 Customers increasingly expect companies to understand their wants and needs and to market to those desires. Unfortunately, such levels of personalisation can be difficult to accomplish for traditional brick-and-mortar retailers, particularly when the fixed cost of personalised marketing is significant. This paper considers methods for providing customised promotions to customers in the form of weekly flyers. We consider how multiple versions of a weekly flyer can be used by a retailer, which products should be included in each flyer version, and how customer preferences, markup, and inventory considerations impact these decisions. Specifically, transaction histories are used to estimate customer preferences for various product offerings using market basket analysis. These probabilities are then incorporated into an optimisation model for grouping customers into market segments and presenting option sets within each segment that maximise expected marginal profits across the flyers. A heuristic is proposed for solving larger problems and evaluated against lower and upper bounds on the optimal profit. Computational results indicate that leveraging customer transaction data to optimise the product selection and assignment of four unique flyers can increase profit by 7.7% over the optimal single-flyer solution.
Journal: International Journal of Production Research
Pages: 3185-3201
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1748905
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1748905
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Template-Type: ReDIF-Article 1.0
Author-Name: Jinjin Liu
Author-X-Name-First: Jinjin
Author-X-Name-Last: Liu
Author-Name: Hua Ke
Author-X-Name-First: Hua
Author-X-Name-Last: Ke
Title: Firms' preferences for retailing formats considering one manufacturer's emission reduction investment
Abstract: 
 Nowadays, many countries and governments implement the cap-and-trade regulation to curb carbon emissions. This study aims to explore how the regulation affects an e-tailer's choice of retailing formats between marketplace and reseller as well as its partner's response by considering a supply chain composed of an e-tailer and a manufacturer. We also take the manufacturer's investment strategy into account and then develop four models to examine the two members' preferences for retailing formats. First, our results demonstrate that if a product's emissions in the retail process are medium (low) or the platform fee rate is relatively low (high), the e-tailer and the manufacturer both prefer marketplace (reseller) mode. Second, the e-tailer prefers to offer reseller mode for one manufacturer with a strong ability of emission reduction and offer marketplace mode otherwise; but the manufacturer's preference is opposed to the e-tailer's. Third, the manufacturer always benefits from her investment, regardless of in marketplace or reseller modes; the e-tailer's attitude towards the manufacturer's investment varies with retailing formats. Specifically, the e-tailer under reseller mode always prefers the manufacturer to invest; but under marketplace mode, he prefers the manufacturer to invest only when the latter's ability of emission reduction is weak.
Journal: International Journal of Production Research
Pages: 3062-3083
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1745314
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1745314
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:3062-3083




Template-Type: ReDIF-Article 1.0
Author-Name: Xingwei Pan
Author-X-Name-First: Xingwei
Author-X-Name-Last: Pan
Author-Name: Na Geng
Author-X-Name-First: Na
Author-X-Name-Last: Geng
Author-Name: Xiaolan Xie
Author-X-Name-First: Xiaolan
Author-X-Name-Last: Xie
Title: A stochastic approximation approach for managing appointments in the presence of unpunctual patients, multiple servers and no-shows
Abstract: 
 Patient unpunctuality significantly disrupts the operations of healthcare facilities, reduces provider productivity, and increases healthcare costs. To alleviate the negative impact of unpunctual patients, this study addresses the appointment scheduling (AS) in the simultaneous presence of unpunctual patients, multiple servers, and no-shows. To determine the appointment schedule, we propose a two-stage stochastic mixed-integer programming model to minimise the total cost incurred by patient waiting and clinic overtime. It becomes challenging for a standard solver to solve this model due to the dynamic patient-to-server assignment decisions that are proactively anticipated in the determination of appointment times. To deal with this problem, a stochastic approximation algorithm is proposed under unbiased gradient estimators. The effectiveness and efficiency of this algorithm are validated in extensive numerical experiments that compare it with Benders decomposition and a heuristic algorithm. Further, the features of the optimal appointment schedule are analysed: (i) the shape of the appointment intervals relies on the number of servers; (ii) the length of intervals is sensitive to no-shows; (iii) the initial block size is greatly affected by patient unpunctuality. Managerial insights are also provided for hospital managers to schedule unpunctual patients in practice.
Journal: International Journal of Production Research
Pages: 2996-3016
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1744766
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1744766
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:2996-3016




Template-Type: ReDIF-Article 1.0
Author-Name: Qinxin Xiao
Author-X-Name-First: Qinxin
Author-X-Name-Last: Xiao
Author-Name: Xiuping Guo
Author-X-Name-First: Xiuping
Author-X-Name-Last: Guo
Author-Name: Dong Li
Author-X-Name-First: Dong
Author-X-Name-Last: Li
Title: Partial disassembly line balancing under uncertainty: robust optimisation models and an improved migrating birds optimisation algorithm
Abstract: 
 A partial disassembly line balancing problem under uncertainty is studied in this paper, which concerns the allocation of a sequence of tasks to workstations such that the overall profit is maximised. We consider the processing time uncertainty and develop robust solutions to accommodate it. The problem is formulated as a non-linear robust integer program, which is then converted into an equivalent linear program. Due to the intractability of such problems, the exact algorithms are only applicable to small-scale instances. We develop an improved migrating birds optimisation algorithm. Two enhancement techniques are proposed. The first one finds the optimal number of tasks to be performed for each sequence rather than random selection used in the literature; while the second one exploits the specific problem structure to construct effective neighbourhoods. The numerical results show the strong performance of our proposal compared to CPLEX and the improved gravitational search algorithm (IGSA), especially for large-scale problems. Moreover, the enhancement due to the proposed techniques is obvious across all instances considered.
Journal: International Journal of Production Research
Pages: 2977-2995
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1744765
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1744765
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Template-Type: ReDIF-Article 1.0
Author-Name: Liane Marcia Freitas Silva
Author-X-Name-First: Liane Marcia Freitas
Author-X-Name-Last: Silva
Author-Name: Ana Camila Rodrigues de Oliveira
Author-X-Name-First: Ana Camila Rodrigues
Author-X-Name-Last: de Oliveira
Author-Name: Maria Silene Alexandre Leite
Author-X-Name-First: Maria Silene Alexandre
Author-X-Name-Last: Leite
Author-Name: Fernando A. S. Marins
Author-X-Name-First: Fernando A. S.
Author-X-Name-Last: Marins
Title: Risk assessment model using conditional probability and simulation: case study in a piped gas supply chain in Brazil
Abstract: 
 The objective of this article is to present a proposed application for systematic risk assessment considering the dependence between risks. The proposal relies on a systematic literature review (SLR) as the initial phase, in which the risk classes, management phases and the tools that can be applied to the risk assessment are identified, considering the dependence between them. For this, the system adopted includes the identification and later evaluation of the risks. The evaluation involves the analytic network process (ANP), Monte Carlo Simulation and conditional probability by means of Bayes’ theorem. The identification and evaluation of the risks were applied to two links of a piped gas supply chain in Brazil, identified as company X and Y, where six specialists were interviewed in each company in the managerial areas. The ANP indicted that the most critical risk in the links is the demand risk. From this, it was possible through Monte Carlo Simulation to identify the probability of occurrence of events with connection to demand risk: demand (X) / demand risk (Y), with probability of 10%; price risk (X) / demand risk (Y), with probability of 0.64%; and risk of supply (Y) / demand risk (X), with a probability of 0%. This indicates that the highest risk is the risk of demand of firm Y, and therefore mitigation strategies should focus on this risk, as it represents the true cause of supply chain vulnerability, generating risk with the highest probability.
Journal: International Journal of Production Research
Pages: 2960-2976
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1744764
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1744764
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:2960-2976




Template-Type: ReDIF-Article 1.0
Author-Name: Lisha Wang
Author-X-Name-First: Lisha
Author-X-Name-Last: Wang
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Author-Name: Huaming Song
Author-X-Name-First: Huaming
Author-X-Name-Last: Song
Title: Manufacturer’s channel strategy with retailer’s store brand
Abstract: 
 This paper examines the manufacturer’s channel strategy as it considers introducing an online channel to sell its own national brand (NB) product, when the brick-and-mortar retailer sells both the NB and its own lower-quality store brand (SB) product. The manufacturer is motivated to introduce an online channel when the customers’ ‘hassle cost' of shopping online is relatively low and their transportation cost is relatively high. However, our results also demonstrate that when the online shopping hassle cost is high and the transportation cost is low, and even when there are very few sales in the online channel, the online-sales strategy can still contribute positively to the manufacturer’s profit. The introduction of the online channel by the manufacturer may result in a win-win situation for the manufacturer and the retailer. As a corollary effect, when the retailer is able to determine the SB quality, it should position the SB at a lower quality level to avoid competition with the manufacturer’s online channel.
Journal: International Journal of Production Research
Pages: 3042-3061
Issue: 10
Volume: 59
Year: 2021
Month: 5
X-DOI: 10.1080/00207543.2020.1745313
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1745313
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:3042-3061




Template-Type: ReDIF-Article 1.0
Author-Name: Bahadır Durak
Author-X-Name-First: Bahadır
Author-X-Name-Last: Durak
Author-Name: Dilek Tuzun Aksu
Author-X-Name-First: Dilek
Author-X-Name-Last: Tuzun Aksu
Title: Bun splitting: an online cutting problem with defects from the food industry
Abstract: 
 In this article we address an online cutting problem with defects that arises in the food industry originally proposed by Glass and van Oostrum ([2010]. “Bun Splitting: A Practical Cutting Stock Problem.” Annals of Operations Research 179: 15–33): the Bun Splitting Problem. The problem involves splitting buns that are baked in large trays into package-size blocks while removing defective buns. Removing defective buns results in small blocks of buns that need to be assembled into package-size blocks at the subsequent packing phase. The primary objective in this splitting process is the minimisation of packing time; however, reducing the number of small blocks awaiting assembly is also a secondary concern. In this study, we relax simplifying assumptions imposed in the previous work to allow for multiple defects in the tray, production switchovers between different package sizes as well as a general defect distribution on the tray. We solve the resulting online cutting problem using a dynamic programming-based algorithm and demonstrate that the algorithm is capable of producing locally optimal solutions in a real-time production environment. We also discuss how the same approach can be adopted to other cutting problems with defects from various industries.
Journal: International Journal of Production Research
Pages: 3202-3220
Issue: 10
Volume: 59
Year: 2021
Month: 05
X-DOI: 10.1080/00207543.2020.1803510
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1803510
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:3202-3220




Template-Type: ReDIF-Article 1.0
Author-Name: Deepak Mathivathanan
Author-X-Name-First: Deepak
Author-X-Name-Last: Mathivathanan
Author-Name: K. Mathiyazhagan
Author-X-Name-First: K.
Author-X-Name-Last: Mathiyazhagan
Author-Name: Nripendra P. Rana
Author-X-Name-First: Nripendra P.
Author-X-Name-Last: Rana
Author-Name: Sangeeta Khorana
Author-X-Name-First: Sangeeta
Author-X-Name-Last: Khorana
Author-Name: Yogesh K. Dwivedi
Author-X-Name-First: Yogesh K.
Author-X-Name-Last: Dwivedi
Title: Barriers to the adoption of blockchain technology in business supply chains: a total interpretive structural modelling (TISM) approach
Abstract: 
 Blockchain is an emerging technology with a wide array of potential applications. This technology, which underpins cryptocurrency, provides an immutable, decentralised, and transparent distributed database of digital assets for use by firms in supply chains. However, not all firms are appropriately suited to adopt blockchain in the existing supply chain primarily due to their lack of knowledge on the benefits of this technology. Using Total Interpretive Structural Modelling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC), this paper identifies the adoption barriers, examines the interrelationships between them to the adoption of blockchain technology, which has the potential to revolutionise supply chains. The TISM technique supports developing a contextual relationship-based structural model to identify the influential barriers. MICMAC classifies the barriers in blockchain adoption based on their strength and dependence. The results of this research indicate that the lack of business awareness and familiarity with blockchain technology on what it can deliver for future supply chains, are the most influential barriers that impede blockchain adoption. These barriers hinder and impact businesses decision to establish a blockchain-enabled supply chain and that other barriers act as secondary and linked variables in the adoption process.
Journal: International Journal of Production Research
Pages: 3338-3359
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1868597
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1868597
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:11:p:3338-3359




Template-Type: ReDIF-Article 1.0
Author-Name: Niloofar Katiraee
Author-X-Name-First: Niloofar
Author-X-Name-Last: Katiraee
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Serena Finco
Author-X-Name-First: Serena
Author-X-Name-Last: Finco
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Title: Consideration of workers’ differences in production systems modelling and design: State of the art and directions for future research
Abstract: 
 The effects of workforce differences on manufacturing systems have attracted the attention of a wide range of researchers in recent years. The differences between workers in terms of skills, age, gender and anthropometric measures have a large impact on production system performance. In this study, the workforce differences factors in production system design and modelling were investigated, with the aim of understanding how the differences between workers could influence a production system and how they had been considered in previous studies. The papers selected from the Scopus database were categorised based on whether how human factors are incorporated into manufacturing system optimisation and design approaches is discussed therein or is not. To find relevant papers, two sets of keywords were defined: (1) keywords relating to the differences between workers and (2) keywords relating to the kind of problem under study. Furthermore, the investigated papers helped highlight the strengths and weaknesses of the existing literature and derive a discussion on the possible future research steps.
Journal: International Journal of Production Research
Pages: 3237-3268
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1884766
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884766
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Template-Type: ReDIF-Article 1.0
Author-Name: Thomy Eko Saputro
Author-X-Name-First: Thomy Eko
Author-X-Name-Last: Saputro
Author-Name: Gonçalo Figueira
Author-X-Name-First: Gonçalo
Author-X-Name-Last: Figueira
Author-Name: Bernardo Almada-Lobo
Author-X-Name-First: Bernardo
Author-X-Name-Last: Almada-Lobo
Title: Integrating supplier selection with inventory management under supply disruptions
Abstract: 
 In the current global market, managing supply is not a straightforward process and it becomes even more complex as uncertainty and disruptions occur. In order to mitigate their impact, the selection of suppliers of strategic items should have a more holistic view of the operations in the supply chain. We propose an integrated model for supplier selection, considering inventory management and inbound transportation. We approach this problem, incorporating stochastic demand and suppliers' imperfect quality. Imperfect quality triggers additional costs, including external failure and holding costs. Supply disruptions also affect the suppliers' lead time, resulting in delivery delays. We develop a methodology to address this challenge with simulation-optimisation. A genetic algorithm determines supplier selection decisions, while inventory decisions are computed analytically. Discrete-event simulation is used to evaluate the overall performance, as well as to update the lead time dynamically, according to the disruptions. Finally, sensitivity analysis providing managerial insights reveals that criteria in supplier selection should be given a different priority depending on the characteristics of the items, and the effectiveness of disruption mitigation strategies depends on the disruption characteristics.
Journal: International Journal of Production Research
Pages: 3304-3322
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1866223
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1866223
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:11:p:3304-3322




Template-Type: ReDIF-Article 1.0
Author-Name: Manuel Schneckenreither
Author-X-Name-First: Manuel
Author-X-Name-Last: Schneckenreither
Author-Name: Stefan Haeussler
Author-X-Name-First: Stefan
Author-X-Name-Last: Haeussler
Author-Name: Christoph Gerhold
Author-X-Name-First: Christoph
Author-X-Name-Last: Gerhold
Title: Order release planning with predictive lead times: a machine learning approach
Abstract: 
 An essential task in manufacturing planning and control is to determine when to release orders to the shop floor. One key parameter is the lead time which is the planned time that elapses between the release of an order and its completion. Lead times are normally determined based on the observed time orders previously took to traverse the production system (flow times). Traditional order release models assume static lead times, although it has been shown that they should be set dynamically to reflect the dynamics of the system. Therefore, we present a flow time estimation procedure to set lead times dynamically using an artificial neural network. Additionally, we implement a safety lead time to incorporate the underlying cost ratio between finished inventory holding and backorder costs in the order release model. We test our proposed approach using a simulation model of a three-stage make-to-order flow-shop and compare the forecast accuracy and the cost performance to other forecast-based order release models from the literature. We show that our proposed model using artificial neural networks outperforms the other tested approaches, especially for scenarios with high utilisation and high variability in processing times.
Journal: International Journal of Production Research
Pages: 3285-3303
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1859634
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1859634
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:11:p:3285-3303




Template-Type: ReDIF-Article 1.0
Author-Name: Patrik Fager
Author-X-Name-First: Patrik
Author-X-Name-Last: Fager
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Title: Cost modelling of onboard cobot-supported item sorting in a picking system
Abstract: 
 For manual picking processes in warehouses and assembly line feeding, collaborative robots – cobots – hold a potential to support operators and, thereby, enhance performance. However, studies focused on the economic aspects of cobot applications have been scarce. The present paper aims at modelling a new picking system, in which human operators collaborate with cobots during picking (or kitting) activities. It is considered the case of having a cobot on board of the picking trolley or cart, working in parallel with the picker by performing sorting of the picked items. The paper focuses on the economic aspects of this application and presents a model of the relative cost difference between a manual and a cobot-supported process, accounting for the costs associated with operators, equipment, and quality. The relative cost difference is analysed in a numerical example. The findings suggest that the decision to use a cobot sorting mode is robust when there is considerable sorting work to carry out, for example, when there are higher yearly order volumes to handle, and when higher order commonality among orders processed as a batch can be achieved. Future research should focus on implementation challenges and safety issues associated with cobot-supported picking processes.
Journal: International Journal of Production Research
Pages: 3269-3284
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1854484
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1854484
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:11:p:3269-3284




Template-Type: ReDIF-Article 1.0
Author-Name: Shalini Talwar
Author-X-Name-First: Shalini
Author-X-Name-Last: Talwar
Author-Name: Puneet Kaur
Author-X-Name-First: Puneet
Author-X-Name-Last: Kaur
Author-Name: Samuel Fosso Wamba
Author-X-Name-First: Samuel
Author-X-Name-Last: Fosso Wamba
Author-Name: Amandeep Dhir
Author-X-Name-First: Amandeep
Author-X-Name-Last: Dhir
Title: Big Data in operations and supply chain management: a systematic literature review and future research agenda
Abstract: 
 In the era of digitalisation, the role of Big Data is proliferating, receiving considerable attention in all sectors and domains. The domain of operations and supply chain management (OSCM) is no different since it offers multiple opportunities to generate a large magnitude of data in real-time. Such extensive opportunities for data generation have attracted academics and practitioners alike who are eager to tap different elements of Big Data application in OSCM. Despite the richness of prior studies, there is limited research that extensively reviews the extant findings to present an overview of the different facets of this area. The current study addresses this gap by conducting a systematic literature review (SLR) to uncover the existing research trends, distil key themes, and identify areas for future research. For this purpose, 116 studies were identified through a stringent search protocol and critically analysed. The key outcome of this SLR is the development of a conceptual framework titled the Dimensions-Avenues-Benefits (DAB) model for BDA adoption as well as potential research questions to support novel investigations in the area, offering actionable implications for managers working in different verticals and sectors.
Journal: International Journal of Production Research
Pages: 3509-3534
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1868599
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1868599
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:11:p:3509-3534




Template-Type: ReDIF-Article 1.0
Author-Name: S. K. Ong
Author-X-Name-First: S. K.
Author-X-Name-Last: Ong
Author-Name: M. M. L. Chang
Author-X-Name-First: M. M. L.
Author-X-Name-Last: Chang
Author-Name: A. Y. C. Nee
Author-X-Name-First: A. Y. C.
Author-X-Name-Last: Nee
Title: Product disassembly sequence planning: state-of-the-art, challenges, opportunities and future directions
Abstract: 
 Disassembly sequence planning (DSP) has gained active research interest since the 90s due to increasing environmental awareness and stricter regulations regarding end-of-life (EOL) strategies of used products. DSP is a subset of disassembly research that focuses on the systematic separation of constituent parts in a product. Despite tremendous efforts from researchers worldwide, DSP remains a challenging research area due to a variety of reasons, e.g. vast variety and complexity of products and uncertainties in the EOL conditions of products. Numerous survey papers have been published from time to time to offer up-to-date insights into this field. Researchers have continuously proposed new solutions to solve the DSP problem in tandem with the advancements in computing and the introduction of new concepts, such as virtual reality. This paper aims to provide a state-of-the-art survey of DSP research in the last 12 years. The research progress and achievements in DSP are summarised from three perspectives, namely, product representation models, sequencing algorithms and methodology validation. Lastly, the challenges and potential research directions in DSP are elaborated followed by conclusion.
Journal: International Journal of Production Research
Pages: 3493-3508
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1868598
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1868598
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Template-Type: ReDIF-Article 1.0
Author-Name: Syed Abdul Rehman Khan
Author-X-Name-First: Syed Abdul Rehman
Author-X-Name-Last: Khan
Author-Name: Karim Zkik
Author-X-Name-First: Karim
Author-X-Name-Last: Zkik
Author-Name: Amine Belhadi
Author-X-Name-First: Amine
Author-X-Name-Last: Belhadi
Author-Name: Sachin S. Kamble
Author-X-Name-First: Sachin S.
Author-X-Name-Last: Kamble
Title: Evaluating barriers and solutions for social sustainability adoption in multi-tier supply chains
Abstract: 
 Multi-tier sustainable supply chain management (MT-SSCM) is increasingly attracting a great deal of interest in academia and practice. However, attention to social sustainability has been relatively limited, and the initiatives of implementing social sustainability, especially in low-tier suppliers in supply chains, are facing enormous barriers and obstacles. The central aim of this paper is to investigate the obstacles that hinder the adoption of social sustainability in the multi-tier supply chain (MT-SC) and prioritise the most effective solutions to promote the adoption of this critical concept. Therefore, we based an extensive literature review on identifying the most relevant barriers and solutions to social sustainability adoption in MT-SC. Moreover, we propose a hybrid and multi-context methodology based on hesitant fuzzy sets (HFS), cumulative prospect theory (CPT) along with VIKOR to identify the most prominent barriers and solutions for three supply-chain sectors, i.e. chemical, agri-food, and textile. The results indicate that solutions to social sustainability in MT-SC are sensitive to the supply chain sector. However, there is a general trend toward adopting emerging technologies and openness and transparency-based relationships with the external environment. Managers could use these results to redirect their strategies to promote social sustainability, particularly in low-tier suppliers in under-developed countries.
Journal: International Journal of Production Research
Pages: 3378-3397
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1876271
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1876271
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Template-Type: ReDIF-Article 1.0
Author-Name: Salvatore Cannella
Author-X-Name-First: Salvatore
Author-X-Name-Last: Cannella
Author-Name: Borja Ponte
Author-X-Name-First: Borja
Author-X-Name-Last: Ponte
Author-Name: Roberto Dominguez
Author-X-Name-First: Roberto
Author-X-Name-Last: Dominguez
Author-Name: Jose M. Framinan
Author-X-Name-First: Jose M.
Author-X-Name-Last: Framinan
Title: Proportional order-up-to policies for closed-loop supply chains: the dynamic effects of inventory controllers
Abstract: 
 Increasing the understanding of the management of closed-loop supply chains (CLSCs) is fundamental to accelerate the much-desired transition towards the circular economy. From this perspective, we investigate the value of proportional order-up-to policies (POUT) policies and the adjustment of their inventory controllers in these systems. These policies are often used to improve the performance of traditional supply chains due to their ability to cope with the damaging bullwhip effect; however, they have not been sufficiently studied in CLSCs. Through a difference equation modelling approach, we show that POUT policies are also a valuable instrument for enhancing the CLSC dynamics. Specifically, we find that the POUT model outperforms the traditional order-up-to policy in a hybrid manufacturing/remanufacturing system, yielding significant cost savings. To optimise the key trade-off between order and inventory variability, the tuning of the inventory controllers needs to consider not only the cost structure of the CLSC but also the average return rate. Specifically, managers should react to increasing levels of circularity by lowering the setting of the controllers’ time constant. In the light of our findings, we suggest two strategies for aligning the calibration of the POUT controllers and the forecasting methods to increase the economic performance of CLSCs.
Journal: International Journal of Production Research
Pages: 3323-3337
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1867924
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1867924
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Template-Type: ReDIF-Article 1.0
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Author-Name: Andrew Feldman
Author-X-Name-First: Andrew
Author-X-Name-Last: Feldman
Title: Assistive devices for manual materials handling in warehouses: a systematic literature review
Abstract: 
 This paper evaluates how technical assistive devices for manual materials handling were analysed in the literature in a warehousing context. Works that discuss the economic and/or human factors impact of assistive devices on the warehousing system or the people employed therein were identified in a systematic literature review. Building on a conceptual framework proposed in this paper, our evaluation of the literature shows which types of assistive devices were analysed in the past, and from which perspective these devices were examined. Some works studied the devices exclusively from an operator well-being or an efficiency perspective, while several works analysed the devices’ performance in terms of both dimensions. Several works contained in our literature sample highlighted trade-offs between both ergonomic and economic measures and, within the first category, between alternative ergonomic indicators, which shows that assistive devices have to be evaluated carefully in light of their intended application. The paper further identifies research gaps and emphasises the need to understand the interactions between human- and system-related variables that can be supported by assistive devices in designing effective manual materials handling systems.
Journal: International Journal of Production Research
Pages: 3446-3469
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1853845
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1853845
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Template-Type: ReDIF-Article 1.0
Author-Name: Junyoung Park
Author-X-Name-First: Junyoung
Author-X-Name-Last: Park
Author-Name: Jaehyeong Chun
Author-X-Name-First: Jaehyeong
Author-X-Name-Last: Chun
Author-Name: Sang Hun Kim
Author-X-Name-First: Sang Hun
Author-X-Name-Last: Kim
Author-Name: Youngkook Kim
Author-X-Name-First: Youngkook
Author-X-Name-Last: Kim
Author-Name: Jinkyoo Park
Author-X-Name-First: Jinkyoo
Author-X-Name-Last: Park
Title: Learning to schedule job-shop problems: representation and policy learning using graph neural network and reinforcement learning
Abstract: 
 We propose a framework to learn to schedule a job-shop problem (JSSP) using a graph neural network (GNN) and reinforcement learning (RL). We formulate the scheduling process of JSSP as a sequential decision-making problem with graph representation of the state to consider the structure of JSSP. In solving the formulated problem, the proposed framework employs a GNN to learn that node features that embed the spatial structure of the JSSP represented as a graph (representation learning) and derive the optimum scheduling policy that maps the embedded node features to the best scheduling action (policy learning). We employ Proximal Policy Optimization (PPO) based RL strategy to train these two modules in an end-to-end fashion. We empirically demonstrate that the GNN scheduler, due to its superb generalization capability, outperforms practically favoured dispatching rules and RL-based schedulers on various benchmark JSSP. We also confirmed that the proposed framework learns a transferable scheduling policy that can be employed to schedule a completely new JSSP (in terms of size and parameters) without further training.
Journal: International Journal of Production Research
Pages: 3360-3377
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1870013
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1870013
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Template-Type: ReDIF-Article 1.0
Author-Name: Zachary A. Collier
Author-X-Name-First: Zachary A.
Author-X-Name-Last: Collier
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: The zero trust supply chain: Managing supply chain risk in the absence of trust
Abstract: 
 The modern supply chain is characterised by an ill-defined and porous perimeter, allowing entry points for potential adversaries to intercept sensitive information and disrupt operations. Such supply chain attacks are increasing in frequency and their impacts can be costly to an organisation. Trust between supply chain partners is commonly thought to be a risk management tool, where increasing trust results in reduced risk. However, increased trust may actually expose the supply chain to more risk, not less. In this paper, we propose the concept of the zero trust supply chain. Originating in the field of information technology and cybersecurity, a zero trust philosophy assumes that all actors and activity are untrusted. In contrast to perimeter-based security, which attempts to keep adversarial actors out, a zero trust-based security posture assumes that adversaries are already inside the system, and therefore imposes strict access and authentication requirements. In this paper, we map zero trust concepts to the supply chain, and discuss the steps an organisation might take to transition to zero trust. We set forth a research agenda by examining zero trust through the lens of several organisational theories and propose a number of research propositions.
Journal: International Journal of Production Research
Pages: 3430-3445
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1884311
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884311
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Template-Type: ReDIF-Article 1.0
Author-Name: Zoé Krug
Author-X-Name-First: Zoé
Author-X-Name-Last: Krug
Author-Name: Romain Guillaume
Author-X-Name-First: Romain
Author-X-Name-Last: Guillaume
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Title: Design of reverse supply chains under uncertainty: the lexicographic R* criterion for exploring opportunities
Abstract: 
 Reverse supply chains (RSCs) have been increasingly implemented in recent years to manage the growing flow of solid waste generated by end-of-life (EOL) products and  to minimise their environmental impact. Furthermore, recent research has shown that the implementation of RSCs benefits job creation, enables savings in raw materials, and creates income from the sales of re-manufactured products. However, designing RSCs requires dealing with many sources of uncertaintydue to the reverse flow of EOL products. To model these uncertainties, we consider  a set of equally possible scenarios. In previous models for scenario sets, the decision often has been influenced by negative scenarios while neglecting opportunities. We propose a new risk/opportunity approach based on the 
 $R_* $R∗ criterion to give more weight to positive scenarios in the decision-making process. This criterion is used in order to distinguish zones of risk and opportunity and guide the decision-making process accordingly to the existing zones. We develop a lexicographic approach for the consideration of existing scenarios, and propose two methods to compute the optimal solution for lexicographic 
 $R_* $R∗ (
 $LexiR_* $LexiR∗) criterion: one  in the form of an algorithm and another in the form of a mixed-integer program (MIP). The performance of the developed approaches is demonstrated in a case study for a reverse facility location problem.
Journal: International Journal of Production Research
Pages: 3221-3236
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1866782
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1866782
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Template-Type: ReDIF-Article 1.0
Author-Name: Amit Karamchandani
Author-X-Name-First: Amit
Author-X-Name-Last: Karamchandani
Author-Name: Samir K. Srivastava
Author-X-Name-First: Samir K.
Author-X-Name-Last: Srivastava
Author-Name: Sushil Kumar
Author-X-Name-First: Sushil
Author-X-Name-Last: Kumar
Author-Name: Akhil Srivastava
Author-X-Name-First: Akhil
Author-X-Name-Last: Srivastava
Title: Analysing perceived role of blockchain technology in SCM context for the manufacturing industry
Abstract: 
 Blockchain is a disruptive technology that promises to embed visibility and trustworthiness in supply chains. This paper examines the perceived role of blockchain in improving SCM and profitability of organisations in the manufacturing industry. It establishes the blockchain benefits for the manufacturing industry using the process of scale development. The proposed hypotheses related to the indirect effects are based on the resource-based view of the firm. The conditional indirect effects for four organisational factors are tested. The research framework is operationalised based on data from 236 practitioners. The findings show that blockchain is perceived to drive improvement in six supply chain dimensions of the manufacturing industry. The breadth of organisation size and geographical dispersion moderate the mediation relationship between blockchain benefits and incremental profitability. Furthermore, the conditional indirect effects are found significant at mean and ±1σ values of integration intensity and IT integration. According to managers of manufacturing industry, blockchain can bring significant improvement in delivery reliability and mass customisation, which would result in increasing the profitability of the organisation. Organisations with low integration intensity, high IT integration and small size organisations are likely to be the early adopters of blockchain technology.
Journal: International Journal of Production Research
Pages: 3398-3429
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1883761
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1883761
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Template-Type: ReDIF-Article 1.0
Author-Name: Shashank Kumar
Author-X-Name-First: Shashank
Author-X-Name-Last: Kumar
Author-Name: Balkrishna E. Narkhede
Author-X-Name-First: Balkrishna E.
Author-X-Name-Last: Narkhede
Author-Name: Karuna Jain
Author-X-Name-First: Karuna
Author-X-Name-Last: Jain
Title: Revisiting the warehouse research through an evolutionary lens: a review from 1990 to 2019
Abstract: 
 A warehouse covers a wide spectrum of operations for the distribution of goods in a supply chain network. The advancement of technology and the changing global business environment have compelled the transformation of a warehouse. The present study attempts to revisit the warehouse transformation from 1990 to 2019 through an evolutionary lens. A systematic literature review is conducted to answer a few basic research questions: what were the issues that warehouses faced during the time period, and how did the academic world approach it? And what would be the research agenda for the warehousing in the era of Industry 4.0? The analysis of the literature shows that warehousing research has changed from a traditional storeroom to a more automated and integrated warehousing system characterised by better efficiency and effectiveness. This study contributes to the development of warehousing research by discussing the development trends, addressing the research gaps, and recommending future research directions. The study also reflects the dominance of developed countries in warehousing research and alludes to more opportunities for practitioners and academicians in developing countries. Based on the decade-wise analysis of literature, an evolutionary framework for warehouse research is proposed which is expected to ensure the supply chain resilience proactively.
Journal: International Journal of Production Research
Pages: 3470-3492
Issue: 11
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2020.1867923
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1867923
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Template-Type: ReDIF-Article 1.0
Author-Name: Haitao Li
Author-X-Name-First: Haitao
Author-X-Name-Last: Li
Author-Name: De Li
Author-X-Name-First: De
Author-X-Name-Last: Li
Author-Name: Dali Jiang
Author-X-Name-First: Dali
Author-X-Name-Last: Jiang
Title: Optimising the configuration of food supply chains
Abstract: 
 We study the food supply chain configuration problem (FSCCP) to optimise the tactical-level mode selection and inventory positioning decisions for a general multi-echelon food supply chain. A mixed-integer nonlinear programming (MINLP) model is developed for the FSCCP, with new building blocks to address the perishability issue in terms of both food loss and quality deterioration. Our model minimises the system-wide total supply chain costs and balances multiple supply chain performance metrics: cost, time and quality. Computational studies show that the optimal FSCCP solutions significantly outperform two heuristic solutions that focus solely on cost or quality. Additional insights are obtained on the impacts of key input parameters on the optimal configuration and performance metrics.
Journal: International Journal of Production Research
Pages: 3722-3746
Issue: 12
Volume: 59
Year: 2021
Month: 6
X-DOI: 10.1080/00207543.2020.1751337
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1751337
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Template-Type: ReDIF-Article 1.0
Author-Name: Ou Tang
Author-X-Name-First: Ou
Author-X-Name-Last: Tang
Author-Name: Yang Liu
Author-X-Name-First: Yang
Author-X-Name-Last: Liu
Author-Name: Zhengang Guo
Author-X-Name-First: Zhengang
Author-X-Name-Last: Guo
Author-Name: Shuoguo Wei
Author-X-Name-First: Shuoguo
Author-X-Name-Last: Wei
Title: Refund policies and core classification errors in the presence of customers’ choice behaviour in remanufacturing
Abstract: 
 In light of a circular economy, to encourage core returns, the remanufacturer charges a deposit and refund it to the customer based on quality inspection of cores. Generally, two types of classification errors exist and interact with each other during the inspection process: either low-quality cores are sorted as remanufacturable, or high-quality cores are sorted as non-remanufacturable. The remanufacturer needs to choose refund policies and determine a reasonable deposit value, considering customers’ potential responses. This paper firstly develops analytical solutions for these issues within a game theory framework. The effect of inspection information transparency is evaluated by comparing two settings: the information of inspection errors is available to customers or not. The study results show the advantage of inspection information transparency from the remanufacturer’s perspective. The analysis indicates the importance of avoiding overestimating customers’ payoff of products and the significance of inspection accuracy. The study also highlights that the salvage value of different cores significantly influences the remanufacturer’s profits, and the improvement of inspection accuracy does not necessarily reduce the customer’s return of low-quality cores.
Journal: International Journal of Production Research
Pages: 3553-3571
Issue: 12
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1894498
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1894498
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Template-Type: ReDIF-Article 1.0
Author-Name: Nidam Siawsh
Author-X-Name-First: Nidam
Author-X-Name-Last: Siawsh
Author-Name: Konrad Peszynski
Author-X-Name-First: Konrad
Author-X-Name-Last: Peszynski
Author-Name: Leslie Young
Author-X-Name-First: Leslie
Author-X-Name-Last: Young
Author-Name: Huan Vo-Tran
Author-X-Name-First: Huan
Author-X-Name-Last: Vo-Tran
Title: Exploring the role of power on procurement and supply chain management systems in a humanitarian organisation: a socio-technical systems view
Abstract: 
 As major disasters vary in both severity and incidence, making appropriate humanitarian responses critical, disaster relief supply chains increasingly incorporate both social and technical aspects into their operations. Power relations and their implications appear to have been overlooked in existing research into humanitarian supply chain management systems; thus, this research examines the extent to which power influences the decision-making process of the purchasing function. We use socio-technical systems theory to uncover the role of power in this context. As a result of this research, a new framework is developed to provide a concise yet holistic approach to understanding power using a real-life case study from the humanitarian realm. The outcomes suggest that local culture can determine power relations in disaster relief operations via vested interests and lobbying with foreign donors.
Journal: International Journal of Production Research
Pages: 3591-3616
Issue: 12
Volume: 59
Year: 2021
Month: 6
X-DOI: 10.1080/00207543.2019.1634293
File-URL: http://hdl.handle.net/10.1080/00207543.2019.1634293
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Template-Type: ReDIF-Article 1.0
Author-Name: Pablo Pérez-Gosende
Author-X-Name-First: Pablo
Author-X-Name-Last: Pérez-Gosende
Author-Name: Josefa Mula
Author-X-Name-First: Josefa
Author-X-Name-Last: Mula
Author-Name: Manuel Díaz-Madroñero
Author-X-Name-First: Manuel
Author-X-Name-Last: Díaz-Madroñero
Title: Facility layout planning. An extended literature review
Abstract: 
 Facility layout planning (FLP) involves a set of design problems related to the arrangement of the elements that shape industrial production systems in a physical space. The fact that they are considered one of the most important design decisions as part of business operation strategies, and their proven repercussion on production systems’ operation costs, efficiency and productivity, mean that this theme has been widely addressed in science. In this context, the present article offers a scientific literature review about FLP from the operations management perspective. The 232 reviewed articles were classified as a large taxonomy based on type of problem, approach and planning stage and characteristics of production facilities by configuring the material handling system and methods to generate and assess layout alternatives. We stress that the generation of layout alternatives was done mainly using mathematical optimisation models, specifically discrete quadratic programming models for similar sized departments, or continuous linear and non-linear mixed integer programming models for different sized departments. Other approaches followed to generate layout alternatives were expert’s knowledge and specialised software packages. Generally speaking, the most frequent solution algorithms were metaheuristics.
Journal: International Journal of Production Research
Pages: 3777-3816
Issue: 12
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1897176
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1897176
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Template-Type: ReDIF-Article 1.0
Author-Name: Abdolreza Roshani
Author-X-Name-First: Abdolreza
Author-X-Name-Last: Roshani
Author-Name: Massimo Paolucci
Author-X-Name-First: Massimo
Author-X-Name-Last: Paolucci
Author-Name: Davide Giglio
Author-X-Name-First: Davide
Author-X-Name-Last: Giglio
Author-Name: Flavio Tonelli
Author-X-Name-First: Flavio
Author-X-Name-Last: Tonelli
Title: A hybrid adaptive variable neighbourhood search approach for multi-sided assembly line balancing problem to minimise the cycle time
Abstract: 
 Multi-sided assembly line balancing problems usually occur in plants producing big-sized products such as buses, trucks, and helicopters. In this type of assembly line, in each workstation, it is possible to install several workplaces, in which a single operator performs his/her own set of tasks at an individual mounting position. In this way, the operators can work simultaneously on the same product without hindering each other. This paper considers for the first time the multi-sided assembly line balancing problem with the objective of minimising the cycle time, proposing a new mathematical formulation to solve small-sized instances of this problem. Besides, a metaheuristic algorithm based on variable neighbourhood search hybridised with simulated annealing is developed to solve large-sized instances. The algorithm is called adaptive because of the adopted neighbourhood selection mechanism. A novel three-string representation is introduced to encode the problem solutions and six different neighbourhood generation structures are presented. The developed approach is compared to other meta-heuristics, considering some well-known in literature test instance and a real world assembly line balancing problem arising in a car body assembly line. The experimental results validate the effectiveness of the proposed algorithm.
Journal: International Journal of Production Research
Pages: 3696-3721
Issue: 12
Volume: 59
Year: 2021
Month: 6
X-DOI: 10.1080/00207543.2020.1749958
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1749958
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Template-Type: ReDIF-Article 1.0
Author-Name: Kaveh Amouzgar
Author-X-Name-First: Kaveh
Author-X-Name-Last: Amouzgar
Author-Name: Amir Nourmohammadi
Author-X-Name-First: Amir
Author-X-Name-Last: Nourmohammadi
Author-Name: Amos H.C. Ng
Author-X-Name-First: Amos H.C.
Author-X-Name-Last: Ng
Title: Multi-objective optimisation of tool indexing problem: a mathematical model and a modified genetic algorithm
Abstract: 
 Machining process efficiencies can be improved by minimising the non-machining time, thereby resulting in short operation cycles. In automatic-machining centres, this is realised via optimum cutting tool allocation on turret-magazine indices – the “tool-indexing problem”. Extant literature simplifies TIP as a single-objective optimisation problem by considering minimisation of only the tool-indexing time. In contrast, this study aims to address the multi-objective optimisation tool-indexing problem (MOOTIP) by identifying changes that must be made to current industrial settings as an additional objective. Furthermore, tool duplicates and lifespan have been considered. In addition, a novel mathematical model is proposed for solving MOOTIP. Given the complexity of the problem, the authors suggest the use of a modified strength Pareto evolutionary algorithm combined with a customised environment-selection mechanism. The proposed approach attained a uniform distribution of solutions to realise the above objectives. Additionally, a customised solution representation was developed along with corresponding genetic operators to ensure the feasibility of solutions obtained. Results obtained in this study demonstrate the realization of not only a significant (70%) reduction in non-machining time but also a set of tradeoff solutions for decision makers to manage their tools more efficiently compared to current practices.
Journal: International Journal of Production Research
Pages: 3572-3590
Issue: 12
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1897174
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1897174
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Template-Type: ReDIF-Article 1.0
Author-Name: Abderahman Rejeb
Author-X-Name-First: Abderahman
Author-X-Name-Last: Rejeb
Author-Name: John G. Keogh
Author-X-Name-First: John G.
Author-X-Name-Last: Keogh
Author-Name: G. Keong Leong
Author-X-Name-First: G. Keong
Author-X-Name-Last: Leong
Author-Name: Horst Treiblmaier
Author-X-Name-First: Horst
Author-X-Name-Last: Treiblmaier
Title: Potentials and challenges of augmented reality smart glasses in logistics and supply chain management: a systematic literature review
Abstract: 
 This study investigates the potentials and challenges of applying augmented reality (AR) smart glasses in logistics and supply chain management (SCM). A systematic literature review on AR smart glasses was conducted to provide a comprehensive synthesis of what has been published in the literature to capture the dynamics surrounding this technology and identify areas deserving of further academic attention. To summarise the latest developments in this field, eighty-two (82) publications were selected and thoroughly analysed. In terms of research findings, four main clusters of potential benefits were identified: visualisation, interaction, user convenience, and navigation. In contrast, the challenges posed by smart glasses in the logistics field were clustered around technical, organisational, and ergonomic considerations. The accumulation of knowledge and actionable insights in this study will benefit both academics and practitioners interested in this emerging wearable technology segment. As the first attempt to explore the importance of smart glasses in logistics and SCM activities, this study offers significant contributions to the literature by codifying extant knowledge on AR smart glasses and setting forth an agenda for future research.
Journal: International Journal of Production Research
Pages: 3747-3776
Issue: 12
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1876942
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1876942
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Template-Type: ReDIF-Article 1.0
Author-Name: Marc Füchtenhans
Author-X-Name-First: Marc
Author-X-Name-Last: Füchtenhans
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Title: Smart lighting systems: state-of-the-art and potential applications in warehouse order picking
Abstract: 
 Artificial lighting is a constant companion in everyday private and working life, influencing visibility in interior spaces as well as outdoors. In recent years, new technical solutions have extended traditional lighting systems to become ‘smart’. Different types of smart lighting systems are available on the market today, and researchers have concentrated on analysing their usability and efficiency, especially for private households, office buildings and public streets. This paper presents a systematic literature review to analyse the state-of-knowledge of technologies and applications for smart lighting systems. The results of the review show that smart lighting systems have been frequently discussed in the literature, but that their potentials in industrial environments, such as production and logistics, has rarely been addressed in the literature so far. Lighting systems for industrial environments often have very different requirements depending on the working environment and operating conditions. Based on the results of the literature review, this paper contributes to closing this research gap by discussing the usage potential of smart lighting systems to improve the efficiency of warehouse order picking, which is an application that may benefit from various functions smart lighting systems provide. Several propositions are developed that emphasise research opportunities and managerial implications in this context.
Journal: International Journal of Production Research
Pages: 3817-3839
Issue: 12
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1897177
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1897177
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Template-Type: ReDIF-Article 1.0
Author-Name: Le Van Dang
Author-X-Name-First: Le
Author-X-Name-Last: Van Dang
Author-Name: Stanislav Makhanov
Author-X-Name-First: Stanislav
Author-X-Name-Last: Makhanov
Title: Enhanced vector flow of significant directions for five-axis machining of STL surfaces
Abstract: 
 Matching a five-axis toolpath and a vector field (VF) of preferred directions (VFPD) is increasingly popular in the five-axis machining industry. However, surfaces represented by industrial formats often produce irregular non-homogeneous VFPD. The current methods are often unable to match such complicated VFs.We propose a new technique based on an enhanced vector flow (EVF), similar to the gradient flow by Xu and Prince (1998. “Generalized Gradient Vector Flow External Forces for Active Contours.” Signal Processing 71 (2): 131–139) for image processing. The EVF keeps the high-rank vectors unchanged while extending them to unimportant regions, using a diffusion process based on a system of parabolic equations. The resulting enhanced vector field of statistically significant directions (EVFSD) is close to the original VFPD but is characterised by better continuity and regularity.Our second contribution is the clustering of the EVFSD using a prescribed library of templates by means of complex moments. The library includes three basic patterns: ‘parallel’-zigzag, ‘circular’-contour, and ‘star’-radial patterns. The toolpaths are generated by an extension of transfinite interpolation (TFI). Virtual and real machining shows the advantages of EVFSD with reference to the standard iso-parametric paths and several state-of-the-art VF-based methods. The experiments have been performed on a five-axis machining centre, Haas VF-2TR. A video, illustrating the proposed procedure is at https://drive.google.com/open?id=1qCrLZSSNKOpURs0JmbGpqV2oeJEUhBmT.
Journal: International Journal of Production Research
Pages: 3664-3695
Issue: 12
Volume: 59
Year: 2021
Month: 6
X-DOI: 10.1080/00207543.2020.1749325
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1749325
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Template-Type: ReDIF-Article 1.0
Author-Name: Dujuan Wang
Author-X-Name-First: Dujuan
Author-X-Name-Last: Wang
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Yunqiang Yin
Author-X-Name-First: Yunqiang
Author-X-Name-Last: Yin
Author-Name: Tai Chiu Edwin Cheng
Author-X-Name-First: Tai Chiu Edwin
Author-X-Name-Last: Cheng
Title: Multi-agent scheduling problems under multitasking
Abstract: 
 We consider a multitasking scheduling model with multiple agents, each of which has a set of tasks to perform on a cloud manufacturing platform on a competitive basis. Each agent wishes to minimise its desirable objective function related to the completion times of its own tasks only. However, the cloud manufacturing platform wishes to minimise the objective of one agent (being long-term critical agent), while keeping the objective of each of the other agents (being short-term one-off agents) within a given limit. The objective functions considered are the maximum of a regular function (associated with each task), the total completion time, and the weighted number of late jobs. Cloud manufacturing enables multitasking scheduling, under which the processing of a selected task may be interrupted by other tasks that are available but unfinished. We ascertain the computational complexity status of each of the problems we consider and devise solution procedures, if viable, for them. We also conduct numerical studies to generate insights into the effects of multitasking on scheduling outcomes, with which the decision maker can justify making investments to adopt or avoid multitasking.
Journal: International Journal of Production Research
Pages: 3633-3663
Issue: 12
Volume: 59
Year: 2021
Month: 6
X-DOI: 10.1080/00207543.2020.1748908
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1748908
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Template-Type: ReDIF-Article 1.0
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies
Abstract: 
 The COVID-19 pandemic has challenged supply chains (SC) on an unprecedented scale testing viability and adaptation under severe uncertainty. However, the literature on the adaptation strategies and quantification of their impacts is still scarce. Mixing literature analysis, case study approach, and quantitative techniques for performance assessment under disruptions, our study generalises four adaptations strategies – intertwining, scalability, substitution, and repurposing – to maintain SC viability when facing a pandemic, and offers a model to analyse and quantify deployment and impact of adaptation. First, we analyse the recent literature and identify some of the general characteristics of adaptation strategies during the COVID-19 pandemic. We then describe case studies to illustrate the practical context and supplement the literature analysis in order to derive relevant determinants for building of a conceptual framework and construction of a formal model. In the conceptual framework, we show how the adaptation strategies can be aligned with the SC viability, encompassing the levels of the ecosystem, network, and resources. In the generalised model, we formalise the impacts and efforts in deploying and assessing the adaptation strategies as both a process and an outcome. We close by proposing some open research questions and outline several future research directions.
Journal: International Journal of Production Research
Pages: 3535-3552
Issue: 12
Volume: 59
Year: 2021
Month: 06
X-DOI: 10.1080/00207543.2021.1890852
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1890852
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Template-Type: ReDIF-Article 1.0
Author-Name: Tiago Tiburcio da Silva
Author-X-Name-First: Tiago Tiburcio
Author-X-Name-Last: da Silva
Author-Name: Antônio Augusto Chaves
Author-X-Name-First: Antônio Augusto
Author-X-Name-Last: Chaves
Author-Name: Horacio Hideki Yanasse
Author-X-Name-First: Horacio Hideki
Author-X-Name-Last: Yanasse
Title: A new multicommodity flow model for the job sequencing and tool switching problem
Abstract: 
 In this paper a new multicommodity flow mathematical model for the Job Sequencing and Tool Switching Problem (SSP) is presented. The proposed model has an LP relaxation lower bound equal to the number of tools minus the tool machine's capacity. Computational tests were performed comparing the new model with the models of the literature. The proposed model performed better, both in execution time and in the number of instances solved to optimality.
Journal: International Journal of Production Research
Pages: 3617-3632
Issue: 12
Volume: 59
Year: 2021
Month: 6
X-DOI: 10.1080/00207543.2020.1748906
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1748906
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Template-Type: ReDIF-Article 1.0
Author-Name: Prince Pal Singh
Author-X-Name-First: Prince
Author-X-Name-Last: Pal Singh
Author-Name: Jatinder Madan
Author-X-Name-First: Jatinder
Author-X-Name-Last: Madan
Author-Name: Harwinder Singh
Author-X-Name-First: Harwinder
Author-X-Name-Last: Singh
Title: Composite performance metric for product flow configuration selection of reconfigurable manufacturing system (RMS)
Abstract: 
 This paper proposes a new metric for product flow configuration selection for reconfigurable manufacturing system (RMS) that considers nine industrially relevant important factors. The metrics for the identified factors are first proposed and a composite performance metric (CPM) that accounts for the nine factors is proposed to assess RMS performance. The developed methodology of CPM provides the user to opt either a subjective or an objective approach to assign suitable weights for each of the nine performance metrics. Developed CPM has been applied in an industrial environment with the support of a manufacturing company by taking two case study parts and alternate configurations to conduct the study. The research work presented in the paper presents a novel approach to identify the most suitable configuration in a RMS addressing a major challenge faced by the industry.
Journal: International Journal of Production Research
Pages: 3996-4016
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1756511
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1756511
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Template-Type: ReDIF-Article 1.0
Author-Name: Fahian Huq
Author-X-Name-First: Fahian
Author-X-Name-Last: Huq
Author-Name: Kulwant S. Pawar
Author-X-Name-First: Kulwant S.
Author-X-Name-Last: Pawar
Author-Name: Nachiappan Subramanian
Author-X-Name-First: Nachiappan
Author-X-Name-Last: Subramanian
Title: Disturbances to the supply chains of high-value manufacturing firms: comparison of the perceptions of product managers and supply chain managers
Abstract: 
 We draw on the literature to categorise the supply chain disturbances (risks and uncertainties) that affect high-value manufacturing (HVM) firms when adopting the following two sourcing strategies: (a) insourcing/nearshore outsourcing, and (b) outsourcing/offshoring. We build a hierarchy structure of disturbances, which was tested in a case study of a European HVM operating in the aerospace industry. A novelty of this study is the quantitative prioritisation and comparison, using the analytic hierarchy process (AHP) method, of the disturbances reported by two groups of managers: three product managers (internally facing) and four supply chain managers (externally facing). Our findings show that managers’ perceptions of firm-related, network-related and location-related disturbances can be prejudiced by their functional boundaries. We show that both product and supply chain managers prefer the insource/nearshore outsource strategy, as they feel that the disturbances while outsourcing/offshoring are significantly greater and offset the benefits of low-cost production – a counterintuitive finding. Through in-depth interviews with both groups of managers, we found the mitigation strategies are reshoring, full consideration to the total cost of acquisition (including hidden costs of distant operations) and building clusters in emerging markets to support the firm’s regional hub by partnering with its existing suppliers from developed countries.
Journal: International Journal of Production Research
Pages: 3916-3934
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1756503
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Template-Type: ReDIF-Article 1.0
Author-Name: Tong Wu
Author-X-Name-First: Tong
Author-X-Name-Last: Wu
Author-Name: Sebastian Stemmler
Author-X-Name-First: Sebastian
Author-X-Name-Last: Stemmler
Author-Name: Maximilian Kemper
Author-X-Name-First: Maximilian
Author-X-Name-Last: Kemper
Author-Name: Dirk Abel
Author-X-Name-First: Dirk
Author-X-Name-Last: Abel
Author-Name: Thomas Gries
Author-X-Name-First: Thomas
Author-X-Name-Last: Gries
Title: Model-based predictive brake control during weft insertion in air-jet weaving
Abstract: 
 Air-jet weaving is one of the most efficient manufacturing processes for producing textile fabrics. During weft insertion, a yarn brake influences the quality of textile fabrics significantly. This brake is set up manually by a machine operator and the duration of the set-up process depends essentially on his experience. Furthermore, an inappropriate braking process might induce high tension in the weft thread which could cause backward movements of the thread as well as a defect in the fabric. For this reason, a braking system is developed which consists of a camera-based sensor and a continuously adjustable brake. The camera-based sensor enables the estimation of the weft velocity which is then controlled by a Model-based Predictive Controller (MPC). In this contribution, a weft insertion model is derived and validated experimentally. After that, this model is reduced in order to ensure real-time capability for its application in a Kalman filter as well as in the MPC. Finally, an MPC based on piecewise linearisation is proposed and implemented on an air-jet weaving machine. The presented experimental results show that yarn braking system compensates the changing behaviour of weft threads in different machine cycles and brakes the weft thread appropriately without a backward movement.
Journal: International Journal of Production Research
Pages: 4090-4107
Issue: 13
Volume: 59
Year: 2021
Month: 07
X-DOI: 10.1080/00207543.2020.1824087
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1824087
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaohuan Wang
Author-X-Name-First: Xiaohuan
Author-X-Name-Last: Wang
Author-Name: Jingchao Xie
Author-X-Name-First: Jingchao
Author-X-Name-Last: Xie
Author-Name: Zhi-Ping Fan
Author-X-Name-First: Zhi-Ping
Author-X-Name-Last: Fan
Title: B2C cross-border E-commerce logistics mode selection considering product returns
Abstract: 
 Long delivery lead times and costly transportation postage are significant characteristics of B2C cross-border e-commerce and logistics. They engender preference inconsistencies and reversals in customers, which can lead to product returns. The aim of this study is to enable retailers to select the optimal cross-border logistics mode that fulfils their marketing strategies while taking product returns into consideration. We propose a novel way to describe customer utility by incorporating customer time preferences, and construct three cross-border logistics models. The theoretical and numerical analyses indicate that, if retailers want to eliminate or reduce their product return rates, they can adjust their delivery lead times in each logistics mode under various product procurement and sales prices, commodity tariffs, international and domestic postage and operating costs. In particular, the O2O mode is always a better option for retailers than the O2D mode, and under certain conditions, the D2D mode is better for retailers than the O2O mode. To increase market demand, the O2O mode is optimal for retailers selling high-priced products, while the O2D mode is optimal for retailers selling low-priced products. This study also provides suggestions for overseas manufacturers. These findings are applicable to B2C cross-border e-commerce, cross-border logistics, and overseas production.
Journal: International Journal of Production Research
Pages: 3841-3860
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1752949
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1752949
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Template-Type: ReDIF-Article 1.0
Author-Name: Serena Finco
Author-X-Name-First: Serena
Author-X-Name-Last: Finco
Author-Name: Mohammed-Amine Abdous
Author-X-Name-First: Mohammed-Amine
Author-X-Name-Last: Abdous
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Xavier Delorme
Author-X-Name-First: Xavier
Author-X-Name-Last: Delorme
Title: A bi-objective model to include workers’ vibration exposure in assembly line design
Abstract: 
 In several occupational sectors, workers are daily exposed to vibrations induced by automatic, pneumatic, or electric tools, with a consequent increase of musculoskeletal disorders. In this paper, a bi-objective manual assembly line design model is proposed, aiming to avoid excessive daily vibration exposures. The developed model allows to minimise both total equipment costs and vibration levels by respecting the threshold values defined in the ISO 5349-1. The ϵ-constraint approach is used to address both objectives and to find the Pareto frontier. The model is applied to several instances to evaluate the computational limit of the solving method, as well as to an industrial case to provide managerial guidelines. The results show that the method can solve small and medium size instances. Moreover, the case study points out that safe vibration exposure levels can be achieved also with a low additional investment and that solutions equal from an economic point of view can be different from a vibrations exposure one.
Journal: International Journal of Production Research
Pages: 4017-4032
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1756512
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1756512
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Template-Type: ReDIF-Article 1.0
Author-Name: Shengluo Yang
Author-X-Name-First: Shengluo
Author-X-Name-Last: Yang
Author-Name: Zhigang Xu
Author-X-Name-First: Zhigang
Author-X-Name-Last: Xu
Title: The distributed assembly permutation flowshop scheduling problem with flexible assembly and batch delivery
Abstract: 
 The scheduling problems of distributed production have received increasing attention in recent years. To coordinate the scheduling of production and transportation, we propose a novel distributed assembly permutation flowshop scheduling problem with flexible assembly and batch delivery (DAPFSP-FABD). The objective is to minimise the total cost of delivery and tardiness. Given that the problem involves six successive decisions, several batch allocation strategies for both production and distribution are proposed, and four neighbourhood structures are designed to search for the best batch sequence, batch allocation, product sequence, and job sequence. Seven algorithms, including four heuristics, a variable neighbourhood descent (VND) algorithm, and two iterated greedy (IG) algorithms, are proposed. In the IG, two types of destruction and construction operations are present to facilitate escape from local optima, thereby resulting in two IG algorithms: IG_desP and IG_desJ. Finally, extensive computational and statistical experiments are carried out. The results show that the proposed batch allocation strategies can improve the solution significantly. Additionally, the heuristics can obtain reasonable solutions in a short time, while IG_desJ performs the best regarding the quality of solutions. This study can help cross-regional companies coordinate the scheduling of production and transportation and enhance the performance of supply chains.
Journal: International Journal of Production Research
Pages: 4053-4071
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1757174
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1757174
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Template-Type: ReDIF-Article 1.0
Author-Name: Tatiana Romanova
Author-X-Name-First: Tatiana
Author-X-Name-Last: Romanova
Author-Name: Alexander Pankratov
Author-X-Name-First: Alexander
Author-X-Name-Last: Pankratov
Author-Name: Igor Litvinchev
Author-X-Name-First: Igor
Author-X-Name-Last: Litvinchev
Author-Name: Sergiy Plankovskyy
Author-X-Name-First: Sergiy
Author-X-Name-Last: Plankovskyy
Author-Name: Yevgen Tsegelnyk
Author-X-Name-First: Yevgen
Author-X-Name-Last: Tsegelnyk
Author-Name: Olga Shypul
Author-X-Name-First: Olga
Author-X-Name-Last: Shypul
Title: Sparsest packing of two-dimensional objects
Abstract: 
 The concept of the sparsest packing is introduced in this paper. The sparsest packing is aimed to place the objects in the container as distant as possible. More specifically, the minimal Euclidean distance between the objects, as well as, between the objects and the boundary of the container is maximised. This new problem statement is motivated by modern clean and energy-saving technologies such as ultrasonic hardening and finishing by detonating gas mixtures. The sparsest packing of two-dimensional objects in a circular container is considered subject to balancing conditions. The objects may have regular or irregular shapes bounded by arcs and line segments. Using the phi-function technique a mathematical model is formulated and a corresponding nonlinear programming problem is stated. A solution algorithm is proposed and computational results are presented to illustrate the approach.
Journal: International Journal of Production Research
Pages: 3900-3915
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1755471
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1755471
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Template-Type: ReDIF-Article 1.0
Author-Name: Kun Wang
Author-X-Name-First: Kun
Author-X-Name-Last: Wang
Author-Name: Guilong Li
Author-X-Name-First: Guilong
Author-X-Name-Last: Li
Author-Name: Shichang Du
Author-X-Name-First: Shichang
Author-X-Name-Last: Du
Author-Name: Lifeng Xi
Author-X-Name-First: Lifeng
Author-X-Name-Last: Xi
Author-Name: Tangbin Xia
Author-X-Name-First: Tangbin
Author-X-Name-Last: Xia
Title: State space modelling of variation propagation in multistage machining processes for variable stiffness structure workpieces
Abstract: 
 Satisfying the quality requirement of products in multistage machining processes (MMPs) is significant and challenging nowadays. In spite of the success of the stream of variation (SoV) theory in variation propagation modelling for MMPs, the absence of elastic deformation variations could be an important factor that limits its application in variable stiffness structure (VSS) workpieces. To this end, a generic variation propagation framework in MMPs for VSS workpieces is established, incorporating the induction and propagation of elastic deformation variations. Region division strategy is adopted according to the characteristics of VSS workpieces, and the analytic solutions of elastic deformation in different regions are solved by contact theory and elastic theory. The effectiveness and accuracy of the proposed model are verified by a six-stage machining process on a four-cylinder engine block, and the proposed model is compared with the conventional SoV model resulting in a significant improvement on quality prediction.
Journal: International Journal of Production Research
Pages: 4033-4052
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1757173
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1757173
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Template-Type: ReDIF-Article 1.0
Author-Name: Yishu Bai
Author-X-Name-First: Yishu
Author-X-Name-Last: Bai
Author-Name: Jiachen Tu
Author-X-Name-First: Jiachen
Author-X-Name-Last: Tu
Author-Name: Mengzhuo Yang
Author-X-Name-First: Mengzhuo
Author-X-Name-Last: Yang
Author-Name: Liang Zhang
Author-X-Name-First: Liang
Author-X-Name-Last: Zhang
Author-Name: Peter Denno
Author-X-Name-First: Peter
Author-X-Name-Last: Denno
Title: A new aggregation algorithm for performance metric calculation in serial production lines with exponential machines: design, accuracy and robustness
Abstract: 
 Performance metric calculation is one of the most important problems in production system research. In this paper, we consider serial production lines with finite buffers and machines following the exponential reliability model. Analytical formulas are first given for performance analysis of two-machine lines. Based on these formulas, a throughput-equivalent aggregation procedure is derived to represent a two-machine exponential line by a single exponential machine. Following this approach, we propose a new aggregation-based iterative algorithm to calculate the performance metrics of a multi-machine serial line by representing it using a group of virtual two-machine lines. Numerical experiments are used to justify the convergence of the algorithm and to evaluate the accuracy of the calculated performance metrics. The results show that the proposed algorithm significantly improves the performance metric approximation accuracy, compared with two commonly used aggregation-based methods in the literature, without incurring additional computational burden. The improvement is even more prominent for systems with relatively small buffers. We believe that this work makes an important contribution to the field of Production Systems Engineering and has the potential to generate great impact as the new algorithm replaces the existing ones in future research and applications by scholars and practitioners.
Journal: International Journal of Production Research
Pages: 4072-4089
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1757777
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1757777
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:13:p:4072-4089




Template-Type: ReDIF-Article 1.0
Author-Name: Yasamin Eslami
Author-X-Name-First: Yasamin
Author-X-Name-Last: Eslami
Author-Name: Mario Lezoche
Author-X-Name-First: Mario
Author-X-Name-Last: Lezoche
Author-Name: Hervé Panetto
Author-X-Name-First: Hervé
Author-X-Name-Last: Panetto
Author-Name: Michele Dassisti
Author-X-Name-First: Michele
Author-X-Name-Last: Dassisti
Title: On analysing sustainability assessment in manufacturing organisations: a survey
Abstract: 
 Manufacturing organisations are now facing unexpected challenges due to scarcity of the natural resources and consequent governmental rules that urge to adopt new organisational or even manufacturing strategies. Adopting the sustainability paradigm at the present seems to be the only viable strategy to respond appropriately to this changed market conditions and customer’s demand. As the pressure for changing the traditional manufacturing approach to reach a sustainable operating condition increases, the urge for assessing their sustainability performance has been reinforced accordingly. Various methods have been accomplished so far, trying to find a way to assess the sustainability state of companies, to select among sustainable solutions, to define and to solve practical problems and to identify potential sustainable solutions. Due to this abundance, the present study is cantered by a systematic literature review based on sustainable manufacturing and sustainability assessment to explore questions on sustainable manufacturing: ‘How can sustainable manufacturing be achieved?’ and ‘How can sustainable manufacturing be assessed?’ The study led to stipulation of the true essence of sustainable manufacturing and sustainability assessment. It also brought new hints on the sustainability assessment of manufacturing recognising true gaps needed to be filled. Furthermore, to investigate the regularity of the methods and tools of sustainability assessment, a Formal Concept Analysis (FCA) was adopted. At the end, a new holistic framework for sustainability assessment in a manufacturing organisation is proposed.
Journal: International Journal of Production Research
Pages: 4108-4139
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1755066
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1755066
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:13:p:4108-4139




Template-Type: ReDIF-Article 1.0
Author-Name: L. M. Daphne Yiu
Author-X-Name-First: L. M. Daphne
Author-X-Name-Last: Yiu
Author-Name: Andy C. L. Yeung
Author-X-Name-First: Andy C. L.
Author-X-Name-Last: Yeung
Author-Name: T. C. Edwin Cheng
Author-X-Name-First: T. C. Edwin
Author-X-Name-Last: Cheng
Title: The impact of business intelligence systems on profitability and risks of firms
Abstract: 
 Researchers in the field of operations management (OM) have long advocated fact-based decision-making. The use of business intelligence (BI) systems represents a great opportunity for manufacturers to improve profitability and reduce firm risks. However, the actual business value of BI systems has remained highly controversial because integrating BI systems into production and manufacturing operations is difficult. In particular, the informational sources and operational use of BI systems require substantial internal support from employees and institutionalised incorporation of BI into operations. Using a sample of 278 manufacturing firms in the US that had used BI systems from 2005 to 2014, we examine the impact of BI systems on firms’ profitability and risks. We show that firms improve their profitability and reduce risks in profit returns directly after the operational use of BI systems. Firms with superior employee relationships and higher process institutionalisation (i.e. firms that are ISO 9000 certified) benefit more from the operational use of BI systems. We provide a resource orchestration perspective (ROP) of the resource-based view (RBV) of firms for the competitive advantage derived from the operational use of BI systems; and we ascertain the circumstances in which manufacturers are more likely to benefit from BI systems.
Journal: International Journal of Production Research
Pages: 3951-3974
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1756506
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1756506
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:13:p:3951-3974




Template-Type: ReDIF-Article 1.0
Author-Name: Budhi Wibowo
Author-X-Name-First: Budhi
Author-X-Name-Last: Wibowo
Author-Name: Jan Fransoo
Author-X-Name-First: Jan
Author-X-Name-Last: Fransoo
Title: Joint-optimization of a truck appointment system to alleviate queuing problems in chemical plants
Abstract: 
 Numerous studies have proposed the use of a Truck Appointment System (TAS) to alleviate traffic congestion at logistics sites. Unfortunately, the implementation of such a system was often optimised based on the interest of a single stakeholder. Meanwhile, long truck queues have been observed in many chemical plants. This study aims to evaluate the TAS performances to mitigate traffic congestion in chemical plants from the multi-stakeholder perspective. We proposed a joint-optimization model to accommodate various interests on the site. An improved fluid-flow approximation was developed to estimate the time-dependent performance of the system. The results suggest that the benefit of TAS is mostly enjoyed by the site manager through the reduction of site overtime, while the benefits for trucking companies are found to be marginal. Through numerical experiments, we show that the proposed joint-optimization model is effective in redistributing the benefits of TAS across the stakeholders, while keeping the total logistics costs to a minimum.
Journal: International Journal of Production Research
Pages: 3935-3950
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1756505
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1756505
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:13:p:3935-3950




Template-Type: ReDIF-Article 1.0
Author-Name: Roberto Pinto
Author-X-Name-First: Roberto
Author-X-Name-Last: Pinto
Author-Name: Alexandra Lagorio
Author-X-Name-First: Alexandra
Author-X-Name-Last: Lagorio
Title: Supporting the decision making process in the urban freight fleet composition problem
Abstract: 
 The Urban Freight Fleet Composition (UFFC) problem addresses the need of a logistics service provider to define the optimal fleet mix in terms of types and number of vehicles to serve the demand for goods delivery in an urban area. Urban areas can be subject to access restrictions (e.g. based upon the time of the day or vehicles’ characteristics) that could affect the performance of transport assets. In this paper, we consider time-window access restrictions based upon the characteristics of the vehicles, and we propose a human-in-the-loop decision support system (HIL-DSS) architecture using optimisation and simulation models to address the trade-off between vehicles characteristics, revenues, costs, and performance. We formulate both a deterministic and a stochastic optimisation decision model addressing the problem in the context of the HIL-DSS. In doing this, we emphasise the role of the human decision maker in tackling a complex problem affected by variability and uncertainty, and to overcome the rigidity of optimisation models thanks to the possibility to include qualitative information into the process.
Journal: International Journal of Production Research
Pages: 3861-3879
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1753896
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1753896
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:13:p:3861-3879




Template-Type: ReDIF-Article 1.0
Author-Name: Yingli Li
Author-X-Name-First: Yingli
Author-X-Name-Last: Li
Author-Name: Xinyu Li
Author-X-Name-First: Xinyu
Author-X-Name-Last: Li
Author-Name: Liang Gao
Author-X-Name-First: Liang
Author-X-Name-Last: Gao
Author-Name: Biao Zhang
Author-X-Name-First: Biao
Author-X-Name-Last: Zhang
Author-Name: Quan-Ke Pan
Author-X-Name-First: Quan-Ke
Author-X-Name-Last: Pan
Author-Name: M. Fatih Tasgetiren
Author-X-Name-First: M. Fatih
Author-X-Name-Last: Tasgetiren
Author-Name: Leilei Meng
Author-X-Name-First: Leilei
Author-X-Name-Last: Meng
Title: A discrete artificial bee colony algorithm for distributed hybrid flowshop scheduling problem with sequence-dependent setup times
Abstract: 
 With the development of global and decentralised economies, distributed production emerges in large manufacturing firms. A distributed production model exists with hybrid flowshops. As an extension of the hybrid flowshop scheduling problem (HFSP), the distributed hybrid flowshop scheduling problem (DHFSP) with sequence dependent setup times (SDST) is a new challenging project. The DHFSP involves three sub-problems: the first one is to allocate a factory for each job; the second one is to determine job sequence in each factory; the third one is to allocate a machine for each job at each stage. This paper presents a machine position-based mathematical model and a discrete artificial bee colony algorithm (DABC) for the DHFSP-SDST to optimise the makespan. The proposed DABC employs a two-level encoding to ensure an initiative scheduling. Decoding method combines with the earliest available machine and earliest completion time rule for feasible schedules. The proposed DABC also employ effective solutions update techniques: the hybrid neighbourhood operators, and many times of Critical Factory Swap to enhance exploitation. 780 benchmarks in total are generated. Extensive experiments are carried out to test the performance of the DABC. Computational results and statistical analyses validate that the DABC outperforms the best performing algorithm in the literature.
Journal: International Journal of Production Research
Pages: 3880-3899
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1753897
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1753897
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:13:p:3880-3899




Template-Type: ReDIF-Article 1.0
Author-Name: Jianping Dou
Author-X-Name-First: Jianping
Author-X-Name-Last: Dou
Author-Name: Jun Li
Author-X-Name-First: Jun
Author-X-Name-Last: Li
Author-Name: Dan Xia
Author-X-Name-First: Dan
Author-X-Name-Last: Xia
Author-Name: Xia Zhao
Author-X-Name-First: Xia
Author-X-Name-Last: Zhao
Title: A multi-objective particle swarm optimisation for integrated configuration design and scheduling in reconfigurable manufacturing system
Abstract: 
 To provide accurate capacity and functionality needed for each demand period (DP), a reconfigurable manufacturing system (RMS) is able to change its configuration with time. For the RMS with multi-part flow line configuration that concurrently produces multiple parts within the same family, the cost and delivery time are dependent on its configuration and relating scheduling for any DP. So far, the study on solution method for the integrated optimisation problem of configuration design and scheduling for RMS is scarce. To efficiently find solutions with tradeoffs between total cost and tardiness, a multi-objective particle swarm optimisation (MoPSO) based on crowding distance and external Pareto solution archive is presented to solve practical-sized problems. The devised encoding and decoding methods along with the particle updating mechanism of MoPSO ensure any particle a feasible solution. The comparison between MoPSO and ε-constraint method versus small-sized cases illustrates the effectiveness of MoPSO. The comparative results between MoPSO and nondominated sorting genetic algorithm II (NSGA-II) against eight problems show that the MoPSO outperforms the NSGA-II in both solution quality and computation efficiency for the integrated optimisation problem.
Journal: International Journal of Production Research
Pages: 3975-3995
Issue: 13
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1756507
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1756507
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:13:p:3975-3995




Template-Type: ReDIF-Article 1.0
Author-Name: Mahdi Yousefi Nejad Attari
Author-X-Name-First: Mahdi
Author-X-Name-Last: Yousefi Nejad Attari
Author-Name: Ali Ebadi Torkayesh
Author-X-Name-First: Ali
Author-X-Name-Last: Ebadi Torkayesh
Author-Name: Behnam Malmir
Author-X-Name-First: Behnam
Author-X-Name-Last: Malmir
Author-Name: Ensiyeh Neyshabouri Jami
Author-X-Name-First: Ensiyeh
Author-X-Name-Last: Neyshabouri Jami
Title: Robust possibilistic programming for joint order batching and picker routing problem in warehouse management
Abstract: 
 Decisions made for designing and operating a warehouse system are of great significance. These operational decisions are strongly affected by total logistics costs, including investment and direct operating costs. The number of orders made by customers in the logistics section of warehouse management is very high because the number, type of products and items ordered by different customers vary broadly. However, machines layout for picking up products at logistics centres is minimal, inflexible, and, in some cases, inconclusive. In this study, we address joint order batching procedures of orders considering picker routing problem as a mixed-integer programming model. Extensive numerical experiments were generated in small, medium, and large sizes. In order to consider the uncertainty of parameters, we applied robust possibilistic programming for this problem. Three different meta-heuristic algorithms; genetic algorithm, particle swarm optimisation algorithm, and honey artificial bee colony algorithms are used as solution approaches to solve the formulated model. The performance of solution approaches over the problem was analysed using several test indexes. In all three group examples, there was no significant difference among mean values of the objective function, while there was a remarkable difference among computing times.
Journal: International Journal of Production Research
Pages: 4434-4452
Issue: 14
Volume: 59
Year: 2021
Month: 07
X-DOI: 10.1080/00207543.2020.1766712
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766712
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4434-4452




Template-Type: ReDIF-Article 1.0
Author-Name: Shih-Wei Lin
Author-X-Name-First: Shih-Wei
Author-X-Name-Last: Lin
Author-Name: Kuo-Ching Ying
Author-X-Name-First: Kuo-Ching
Author-X-Name-Last: Ying
Title: Minimising makespan in job-shops with deterministic machine availability constraints
Abstract: 
 This paper proposes an effective and efficient multi-temperature simulated annealing (MTSA) algorithm to minimise the makespan of a job-shop under the constraint that machines are not continuously available for processing during the whole scheduling horizon. The proposed MTSA algorithm uses an embedded multi-temperature mechanism to vary the thermal transition probabilities of the simulated annealing algorithm. This mechanism can help prevent the algorithm from becoming trapped in a local minimum and ensures its movement towards a broad region of the search space containing optimal solutions. An effective and robust lower bound is developed for the problem to evaluate the quality of solutions. Extensive computational results show that the proposed MTSA algorithm significantly outperforms the state-of-the-art meta-heuristic algorithms reported in the literature. The proposed algorithm and lower bound can assist further research in the scheduling research field as it is both effective and efficient in handling job-shop scheduling problems with machine availability constraints.
Journal: International Journal of Production Research
Pages: 4403-4415
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1764125
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1764125
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4403-4415




Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Yuan Huang
Author-X-Name-First: Yuan
Author-X-Name-Last: Huang
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Title: Workload control in additive manufacturing shops where post-processing is a constraint: an assessment by simulation
Abstract: 
 Additive Manufacturing (AM) shops typically produce high variety, low volume products on a to-order basis. Products are first created in parallel batches at a single AM station before being subjected to several post-processing operations. While there exists an emerging literature on AM station scheduling and order book smoothing, this literature has largely neglected downstream post-processing operations, which also affect overall performance. Workload Control provides a unique production control solution for these post-processing operations, but the specific AM shop structure has been neglected in the literature. Using simulation, this study shows that load balancing via the use of workload norms, as is typical for Workload Control, becomes ineffective since the norm must allow for the operation throughput time at the AM station and for its variability. A sequencing rule for the jobs waiting to be released that inherently creates a mix of jobs that balances the workload is therefore identified as the best-performing rule. These findings reinforce the principle that load limiting should be used at upstream stations whereas sequencing should be applied at downstream stations. Finally, although the focus is on AM shops, the findings have implications for other shops with similar structures, e.g. in the steel and semi-conductor industries.
Journal: International Journal of Production Research
Pages: 4268-4286
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1761038
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1761038
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4268-4286




Template-Type: ReDIF-Article 1.0
Author-Name: Morteza Ghomi-Avili
Author-X-Name-First: Morteza
Author-X-Name-Last: Ghomi-Avili
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Author-Name: Seyed Gholamreza Jalali Naeini
Author-X-Name-First: Seyed Gholamreza
Author-X-Name-Last: Jalali Naeini
Author-Name: Armin Jabbarzadeh
Author-X-Name-First: Armin
Author-X-Name-Last: Jabbarzadeh
Title: Competitive green supply chain network design model considering inventory decisions under uncertainty: a real case of a filter company
Abstract: 
 A robust bi-level model of the single-product multi-period network design problem is proposed for a competitive green supply chain considering pricing and inventory decisions under uncertainty and disruption risks. The bi-level programming approach is used through this model to demonstrate the competition among two supply chains; the leader and the follower, respectively. After modelling the competition and applying pricing decisions by defining a price-dependent demand, disruption risks are analysed through the model. The proposed model simultaneously considers demand uncertainty and disruption risks and is capable of dealing with such uncertainties by implementing resilience strategies including, inventory decisions, and having a contract with reliable suppliers. Moreover, to consider the environmental issues, controlling CO2 emissions and managing the reverse flow were added to the model. Our approach to mitigate the problem uncertainties is to use the possibilistic programming method. The Karush-Kuhan-Tucker (K-K-T) optimality conditions are deployed to make a single-level equivalent form. Since the integrated model was bi-objective, the ϵ-constraint method is implemented to make a single objective integrated model. Finally, some managerial implications are discussed through an industrial case example.
Journal: International Journal of Production Research
Pages: 4248-4267
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1760391
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1760391
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4248-4267




Template-Type: ReDIF-Article 1.0
Author-Name: Bin Shen
Author-X-Name-First: Bin
Author-X-Name-Last: Shen
Author-Name: Chen Zhu
Author-X-Name-First: Chen
Author-X-Name-Last: Zhu
Author-Name: Qingying Li
Author-X-Name-First: Qingying
Author-X-Name-Last: Li
Author-Name: Xiaofeng Wang
Author-X-Name-First: Xiaofeng
Author-X-Name-Last: Wang
Title: Green technology adoption in textiles and apparel supply chains with environmental taxes
Abstract: 
 Sustainability is crucially important in the textiles and apparel (TA) supply chains. In this paper, we evaluate the impact of clean technology adoption and environmental taxes on the TA supply chains. First, we consider a monopoly case, where a two-echelon supply chain consists of one buyer and one manufacturer. We find that raising the environmental tax rate motivates the manufacturer to invest in green technologies. We then extend our model to examine the duopoly case. We find that in the duopoly case, if the buyer's market share is sufficiently small (large), the optimal greenness level for this buyer's product decreases (increases) in the environmental tax rate; whereas if the two products market shares are relatively equal, the optimal greenness levels for both products buyers increase in the environmental tax rate. The existence of the spillover effect reduces the cost and improves the product greenness. Consumer welfare can be improved if the efficiency of green technology adoption and the coefficient of greenness level on market demand are sufficiently high. This result implies that if the government cares about consumers, the manufacturer should be encouraged to enhance the cost reduction ability in terms of green technology, and consumer education about sustainability consciousness should be enhanced.
Journal: International Journal of Production Research
Pages: 4157-4174
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1758354
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1758354
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4157-4174




Template-Type: ReDIF-Article 1.0
Author-Name: Shuguang He
Author-X-Name-First: Shuguang
Author-X-Name-Last: He
Author-Name: Lisha Song
Author-X-Name-First: Lisha
Author-X-Name-Last: Song
Author-Name: Yanfen Shang
Author-X-Name-First: Yanfen
Author-X-Name-Last: Shang
Author-Name: Zhiqiong Wang
Author-X-Name-First: Zhiqiong
Author-X-Name-Last: Wang
Title: Change-point detection in Phase I for autocorrelated Poisson profiles with random or unbalanced designs
Abstract: 
 The quality of some products or processes can be characterised by the functional relationship referred to as a profile. Profile monitoring aims to check the stability of this relationship over time. In some applications, the response variable of interest in profiles follows a Poisson distribution and the observations within each profile are autocorrelated. Besides, the design points and/or the number of measurements are not the same for different profiles. However, most existing studies on monitoring Poisson profiles have not incorporated the correlation, and the design points within a profile are fixed. It has been shown in many studies that ignoring correlations may lead to poor performance or even misleading results in profile monitoring. Therefore, this article proposes a Phase I scheme to detect and estimate the change-point of autocorrelated Poisson profiles with random or unbalanced design points. The proposed method uses the generalised estimating equation (GEE) approach to model the within-profile correlation and then integrates the change-point algorithm with the modified score test to detect the change-point. Numerical simulations are conducted to investigate the detection effectiveness and diagnostic accuracy of the proposed scheme. Finally, an application to warranty claims is presented to illustrate the implementation of the proposed method.
Journal: International Journal of Production Research
Pages: 4306-4323
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1762017
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1762017
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4306-4323




Template-Type: ReDIF-Article 1.0
Author-Name: Zhongrui Wang
Author-X-Name-First: Zhongrui
Author-X-Name-Last: Wang
Author-Name: Qinghua Wu
Author-X-Name-First: Qinghua
Author-X-Name-Last: Wu
Title: Carbon emission reduction and product collection decisions in the closed-loop supply chain with cap-and-trade regulation
Abstract: 
 Governments’ emission policies and consumers’ increasing environmental awareness have brought pressure on manufacturers. Particularly, governments are requiring manufacturers to manage their end-of-life products. Hence, the supply chain should consider environmental and economic performance comprehensively. This study considers strategies on carbon emission reduction and used product collection on the basis of cap-and-trade regulation in the closed-loop supply chain. Decentralised and centralised decision models are formulated, and the equilibrium solutions of these models are then derived. The impact of used product collection on carbon emission reduction is further analysed. Findings show that when the parameters meet a certain condition, the scenario where the manufacturer leads the collection is optimal for carbon emission reduction, used product collection, and profit generation; otherwise, the supply chain will select the retailer to collect used products. Under the special collection model with a fixed return rate, used product collection is beneficial for reducing carbon emissions. High initial carbon emissions are inconducive to carbon emission reduction and used product collection. Moreover, the government can affect supply chain decisions by regulating and controlling carbon trading prices.
Journal: International Journal of Production Research
Pages: 4359-4383
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1762943
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1762943
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4359-4383




Template-Type: ReDIF-Article 1.0
Author-Name: Marco Caserta
Author-X-Name-First: Marco
Author-X-Name-Last: Caserta
Author-Name: Stefan Voß
Author-X-Name-First: Stefan
Author-X-Name-Last: Voß
Title: A note on: “A hybrid Benders approach for coordinated capacitated lot-sizing of multiple product families with set-up times,” by T. Bayley, H. Süral, and J. Bookbinder
Abstract: 
 In a recent paper by Bayley et al. [2018. “A Hybrid Benders Approach for Coordinated Capacitated Lot-Sizing of Multiple Product Families with Set-Up Times.” International Journal of Production Research 56 (3): 1326–1344] on a capacitated lot-sizing problem, a Benders-based approach is described. Strengthening the master problem is based on inequalities that should be valid. We provide insight indicating that this is not the case for those inequalities proposed by Bayley et al. (2018).
Journal: International Journal of Production Research
Pages: 4453-4456
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1764127
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1764127
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4453-4456




Template-Type: ReDIF-Article 1.0
Author-Name: Yuxiang Cheng
Author-X-Name-First: Yuxiang
Author-X-Name-Last: Cheng
Author-Name: Desheng Dash Wu
Author-X-Name-First: Desheng Dash
Author-X-Name-Last: Wu
Author-Name: David L. Olson
Author-X-Name-First: David L.
Author-X-Name-Last: Olson
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Financing the newsvendor with preferential credit: bank vs. manufacturer
Abstract: 
 This paper examines how preferential credit based on retailers’ credit line impacts on capital-constraint retailer’s operational decisions. We consider a condition of loan competition when banks and manufacturers offer preferential credit to capital-constraint retailers in the newsvendor model. Different credit lines and discounted rates of preferential credit mainly involve in retailers’ exogenous collateral and risk preference of banks and manufacturers in our model. We investigate impacts of bank financing, trade credit, and portfolio credit (financing from both bank credit and trade credit with different ratios) on retailer’s inventory decision with different cases that the retailer’s financing amounts exceed credit line or not. We derive the equilibrium wholesale price, expected sale price, and order quantity when retailers face with different conditions of collaterals and institutes’ risk preferences facing with market risk. A debt-financed retailer favours items with trade credit compared to bank financing, especially in conditions when its sourcing demand is great and when it finances from high-risk preference institutes. Retailer prefers to using the loan with high trade credit ratio when he opts portfolio credit conditions.
Journal: International Journal of Production Research
Pages: 4228-4247
Issue: 14
Volume: 59
Year: 2021
Month: 07
X-DOI: 10.1080/00207543.2020.1759839
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1759839
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4228-4247




Template-Type: ReDIF-Article 1.0
Author-Name: Zhongyi Wu
Author-X-Name-First: Zhongyi
Author-X-Name-Last: Wu
Author-Name: Weidong Liu
Author-X-Name-First: Weidong
Author-X-Name-Last: Liu
Author-Name: Weijie Zheng
Author-X-Name-First: Weijie
Author-X-Name-Last: Zheng
Author-Name: Wenbin Nie
Author-X-Name-First: Wenbin
Author-X-Name-Last: Nie
Author-Name: Zhenzhen Li
Author-X-Name-First: Zhenzhen
Author-X-Name-Last: Li
Title: Manufacturing process similarity measurement model and application based on process constituent elements
Abstract: 
 Planners and designers of production systems must frequently evaluate the similarities in the manufacturing process of various products to achieve efficient and economical production. The purpose is to reasonably arrange mixed production. The similarity of manufacturing technique processes is an important basis for classifying product manufacturing processes. This study proposes an innovative method based on process constituent elements model to objectively calculate the similarity of product manufacturing processes. Firstly, the similarity model of the manufacturing technique process is established on the basis of six dimensions of process constituent elements, namely, input, output, resource, environment, value-added processing activity and quality control & inspection. Secondly, the characteristics of the six dimensions of the process constituent elements are determined. Corresponding methods are applied to solve the similarity of process constituent elements in each dimension on the basis of the characteristic attributes of process constituent elements of different dimensions. Thirdly, extended interval analytic hierarchy process and quantitative calculation method based on angle information entropy are integrated to determine the weights of dimensions of the six elements. Lastly, the proposed method is applied to the process classification of a group of product manufacturing technique processes, and the feasibility and effectiveness of the method are proven.
Journal: International Journal of Production Research
Pages: 4205-4227
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1759838
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1759838
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Template-Type: ReDIF-Article 1.0
Author-Name: Xinrui Zhan
Author-X-Name-First: Xinrui
Author-X-Name-Last: Zhan
Author-Name: Yinping Mu
Author-X-Name-First: Yinping
Author-X-Name-Last: Mu
Author-Name: Manpreet Hora
Author-X-Name-First: Manpreet
Author-X-Name-Last: Hora
Author-Name: Vinod R. Singhal
Author-X-Name-First: Vinod R.
Author-X-Name-Last: Singhal
Title: Service excellence and market value of a firm: an empirical investigation of winning service awards and stock market reaction
Abstract: 
 Service excellence is viewed as firms providing high levels of service quality that in turn generate high customer satisfaction. Studies have empirically linked service excellence and firm performance. We add to the understanding of this link by examining the association between delivering service excellence and shareholder value. Delivering service excellence is proxied by announcements of winning service awards and shareholder value is assessed by the stock market reaction to such announcements. Our empirical analyses are based on a sample of 316 announcements by firms winning service awards between 2001 and 2016. We find that the average market reaction to winning service awards is 0.42%. The market reaction depends both on prior performance and firm size. Growth prospects of firms is not a significant factor in determining the market reaction. Interestingly, we find that firms operating in less competitive industries have a higher market reaction compared to firms operating in more competitive industries. We also find that winning a service award is associated with subsequent improvements in operating performance measured as return on assets (ROA), return on sales (ROS) and total cost over sales (TCOS).
Journal: International Journal of Production Research
Pages: 4188-4204
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1759837
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1759837
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Template-Type: ReDIF-Article 1.0
Author-Name: Gabi Hanukov
Author-X-Name-First: Gabi
Author-X-Name-Last: Hanukov
Author-Name: Tal Avinadav
Author-X-Name-First: Tal
Author-X-Name-Last: Avinadav
Author-Name: Tatyana Chernonog
Author-X-Name-First: Tatyana
Author-X-Name-Last: Chernonog
Author-Name: Uri Yechiali
Author-X-Name-First: Uri
Author-X-Name-Last: Yechiali
Title: A multi-server system with inventory of preliminary services and stock-dependent demand
Abstract: 
 This study is motivated by industries in which products can be partially prepared and stored before demand occurs, while demand is stock-dependent. We study a multi-server system in which the servers utilise their idle time to produce and store ‘preliminary services’ (PSs) in order to reduce customers’ sojourn time and, as a result, stimulating demand by creating the anticipation of a shorter sojourn time. In order to facilitate closed-form solutions, we analyse a Markovian queueing-inventory model and apply matrix geometric (MG) methods. In contrast to most applications in which the rate matrix R of the MG analysis is calculated numerically, our analysis enables derivation of explicit solutions for the entries of R and discovers their relation to Catalan numbers, allowing a rapid solution for large systems. Consequently, the system’s stability condition is readily obtained and shown to be identical to that of a regular M/M/s queue. Two models are developed: one for non-perishable PSs, the other for perishable ones. An economic analysis is provided for two case studies: a bike store and a pizza store. We observe that the reward has low sensitivity to deviation from the optimal PSs capacity and high sensitivity to deviation from the optimal promotional level.
Journal: International Journal of Production Research
Pages: 4384-4402
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1762945
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1762945
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Template-Type: ReDIF-Article 1.0
Author-Name: Lei Xie
Author-X-Name-First: Lei
Author-X-Name-Last: Xie
Author-Name: Junhai Ma
Author-X-Name-First: Junhai
Author-X-Name-Last: Ma
Author-Name: Mark Goh
Author-X-Name-First: Mark
Author-X-Name-Last: Goh
Title: Supply chain coordination in the presence of uncertain yield and demand
Abstract: 
 This paper focuses on a two-echelon supply chain consisting of a seller and a buyer. Considering the case where the buyer faces uncertain demand and yield, the paper investigates the buyback contract for the supply chain and studies how the yield uncertainty and the relative bargaining power affect the performance of buyback contract. The results suggest that when the seller's bargaining power is relatively high and can control the uncertain yield, the buyback contract is sufficient to coordinate the supply chain. Conversely, when the seller's bargaining power is relatively low or cannot guarantee yield stability, the buyback contract does not work. To coordinate such a supply chain, a combined contract named Buy-Back-Revenue-Sharing contract is proposed. Furthermore, this paper presents the optimal orders to maximize the profits of the buyer and the whole supply chain and it finds that if the seller cannot control the yield, the buyer will place fewer orders and both parties will gain lower profit with supply chain coordination.
Journal: International Journal of Production Research
Pages: 4342-4358
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1762942
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1762942
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4342-4358




Template-Type: ReDIF-Article 1.0
Author-Name: Jie Wei
Author-X-Name-First: Jie
Author-X-Name-Last: Wei
Author-Name: Weiyu Chen
Author-X-Name-First: Weiyu
Author-X-Name-Last: Chen
Author-Name: Guoxin Liu
Author-X-Name-First: Guoxin
Author-X-Name-Last: Liu
Title: How manufacturer's integration strategies affect closed-loop supply chain performance
Abstract: 
 This paper considers a manufacturer's optimal integration strategy in a three-level closed-loop supply chain including one manufacturer, one retailer and two competing collectors. We study how the manufacturer's integration strategies of retailing and collecting channels affect the closed-loop supply chain members' optimal decisions and maximum profits, and also investigate the interaction between the collection competition and the manufacturer's integration strategies. Through comparing various integration strategies, some new and interesting management insights are obtained: to improve collection rate of the whole closed-loop supply chain and maximise the surplus profit of integration strategy, the manufacturer's best opt is to integrate the retailer and only one collector when the collection competition is intense.
Journal: International Journal of Production Research
Pages: 4287-4305
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1762016
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1762016
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenguang Tang
Author-X-Name-First: Wenguang
Author-X-Name-Last: Tang
Author-Name: Haitao Li
Author-X-Name-First: Haitao
Author-X-Name-Last: Li
Author-Name: Kaihao Cai
Author-X-Name-First: Kaihao
Author-X-Name-Last: Cai
Title: Optimising the credit term decisions in a dual-channel supply chain
Abstract: 
 We study the problem of credit term optimisation in a dual-channel supply chain setting, where a manufacturer serves as the leader in a Stackelberg game to determine the credit term and wholesale price for its retailer, in conjunction with the pricing decision for its direct sales channel. The retailer optimises its retail price given the credit term and wholesale price prescribed by the manufacturer. Decentralised optimal solutions are obtained to optimise the manufacturer's credit term decision while anticipating the retailer's autonomous price optimisation decision. Then a centralised decision paradigm is analysed to show the increase of total profitability through cooperation. In order to incentivise both parties to cooperate, we propose a new credit term-based contract for coordinating the dual-channel supply chain and devise a profit-sharing scheme for the manufacturer and retailer to achieve a win-win. Numerical studies are performed to obtain additional managerial insights.
Journal: International Journal of Production Research
Pages: 4324-4341
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1762018
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1762018
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:14:p:4324-4341




Template-Type: ReDIF-Article 1.0
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Author-Name: Amy H. I. Lee
Author-X-Name-First: Amy H. I.
Author-X-Name-Last: Lee
Author-Name: Yi-San Huang
Author-X-Name-First: Yi-San
Author-X-Name-Last: Huang
Title: A variable-type skip-lot sampling plan for products with a unilateral specification limit
Abstract: 
 Acceptance sampling plans are practical quality management tools for lot sentencing. The rapid advancement of manufacturing technologies has reduced the defective rate substantially, and as a result, variables sampling plans with process capability indices (PCIs) have been adopted widely so that the required sample size can be decreased. Skip-lot sampling plan (SkSP), which evolved from the continuous sampling plan type-1, is applicable to bulk materials or products manufactured in successive batches or lots. It requires a smaller fraction of lots being examined, and the cost of inspection thus can be reduced. Hence, this paper consolidates the advantages of PCIs and SkSP, and proposes a skip-lot sampling plan of type-2, called SkSP-2, based on the one-sided PCIs for products with a unilateral specification limit. The proposed plan uses the exact sampling distribution of the estimators to develop a mathematical model for determining plan parameters, and the research prepares tables of plan parameters under different combinations of quality requirements and risk levels for quick reference in real applications. In addition, the results are compared with a conventional sampling plan to examine the contribution of the approach, and extensions to two types of SkSP are also presented. Finally, a graphical user interface is constructed to facilitate data input, criteria calculation and decision-making in practice.
Journal: International Journal of Production Research
Pages: 4140-4156
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1757778
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1757778
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Template-Type: ReDIF-Article 1.0
Author-Name: Klaus Altendorfer
Author-X-Name-First: Klaus
Author-X-Name-Last: Altendorfer
Author-Name: Andreas Schober
Author-X-Name-First: Andreas
Author-X-Name-Last: Schober
Author-Name: Johannes Karder
Author-X-Name-First: Johannes
Author-X-Name-Last: Karder
Author-Name: Andreas Beham
Author-X-Name-First: Andreas
Author-X-Name-Last: Beham
Title: Service level improvement due to worker cross training with stochastic worker absence
Abstract: 
 To react on increasing customer demand uncertainty, production systems have to be flexible concerning the provided capacity. With respect to labour, one opportunity to gain such flexibility is to assign workers to different work stations which often require different skills to be operated. Therefore, cross-trained workers are needed to enable this flexibility. Since the qualifying workforce implies costs, a relevant problem is how much skills and what mix of skills is optimal for a production system. In addition, the workforce may be on vacation or have a sick leave and hence is not always available. In this paper, we study the effect of different predefined workforce qualification profiles for a streamlined production system with simulation and compare the results with simulation-based optimisation using a genetic algorithm. Specifically the effect of stochastic worker absence, in comparison to workers being always available, is evaluated for different production system scenarios. The results show that cross-trained workers can significantly improve the service level achieved and that simulation-based optimisation can provide a much better worker specific mix of skills than predefined qualification profiles. Another managerial insight is that there is a trade-off between number of skills and number of workers needed to obtain the same service level.
Journal: International Journal of Production Research
Pages: 4416-4433
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1764126
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1764126
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Template-Type: ReDIF-Article 1.0
Author-Name: Cai Wen Zhang
Author-X-Name-First: Cai Wen
Author-X-Name-Last: Zhang
Author-Name: Rong Pan
Author-X-Name-First: Rong
Author-X-Name-Last: Pan
Author-Name: Thong Ngee Goh
Author-X-Name-First: Thong Ngee
Author-X-Name-Last: Goh
Title: Reliability assessment of high-Quality new products with data scarcity
Abstract: 
 This study concerns the reliability assessment in high-quality new product development in which there is scarcity of data resulting from few or zero failures or the unavailability of failure time information. In such circumstances, traditional reliability assessment methods tend to be inadequate and ineffective. This paper describes a pragmatic approach adopted to address this practical issue. A Bayesian method using reparameterization of the Weibull distribution is proposed, which elicits priors in a meaningful way from technical experts and based on historical data. Unlike existing procedures found in the literature, the method here is developed from the perspective of availability of failure time data. Through a case study from the hard disk drive industry, it is demonstrated that the proposed method can provide an effective and practical solution to the challenging real-life problem. Furthermore, it is shown that failure time information has a significant effect on the inference about the Weibull shape parameter.
Journal: International Journal of Production Research
Pages: 4175-4187
Issue: 14
Volume: 59
Year: 2021
Month: 7
X-DOI: 10.1080/00207543.2020.1758355
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1758355
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Template-Type: ReDIF-Article 1.0
Author-Name: Omar Al-Araidah
Author-X-Name-First: Omar
Author-X-Name-Last: Al-Araidah
Author-Name: Gul Okudan-Kremer
Author-X-Name-First: Gul
Author-X-Name-Last: Okudan-Kremer
Author-Name: Elif Elcin Gunay
Author-X-Name-First: Elif Elcin
Author-X-Name-Last: Gunay
Author-Name: Chih-Yuan Chu
Author-X-Name-First: Chih-Yuan
Author-X-Name-Last: Chu
Title: A Monte Carlo simulation to estimate fatigue allowance for female order pickers in high traffic manual picking systems
Abstract: 
 The paper presents a Monte Carlo simulation model to estimate the average rate of energy expenditure (Kcal/min) and, consequently, fatigue allowance in manual order picking systems with high demand rates. The study is limited to picking a low number of low weight items per order in a compact warehouse system with traditional layout configuration of parallel racks with equal size storage cubicles. Replicates of 10,000 orders with random order sizes and random locations of items per order are used to estimate the average rate of energy expenditure for female pickers with various combinations of body mass and walking speeds. Design for the average and design for percentile are investigated to estimate a maintainable work standard to maximise productivity while maintaining energy expenditure within acceptable limits. Results illustrate the significant impacts of body mass and walking speed on the productivity and rate of energy expenditure, especially for the above average weight picker. Moreover, results reveal the difficulty of adopting recommendations on limitations on energy input and degrade in aerobic capacity with age and health conditions when setting productivity limits for pickers with a wide range of weights.
Journal: International Journal of Production Research
Pages: 4711-4722
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1770357
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1770357
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Template-Type: ReDIF-Article 1.0
Author-Name: Claire (Wan-Chuan) Chan
Author-X-Name-First: Claire
Author-X-Name-Last: (Wan-Chuan) Chan
Author-Name: Emel Arıkan
Author-X-Name-First: Emel
Author-X-Name-Last: Arıkan
Title: Differentiation vs. standardisation in supply chain segmentation: a quantitative study
Abstract: 
 The key value proposition of supply chain segmentation is to differentiate supply chains through a reasonable number of segments in order to gain a level of standardisation and avoid managerial complexity incurred in fully customised supply chains. The decision on how products are grouped into segments is at the core of a successful implementation. A fundamental trade-off in this decision-making process is between higher differentiation by having small group sizes and higher standardisation from a smaller number of groups. In this manuscript, we implement segmentation on supply chain configurations and investigate the trade-off by analysing several network scenarios. We use optimisation models for each scenario to align decisions of segment formation and supply chain configurations. We show that divergences in demand characteristics, geographic difference, and cost synergy such as pooling effect have impacts on the balance of standardisation and differentiation.
Journal: International Journal of Production Research
Pages: 4593-4614
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1767311
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1767311
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:15:p:4593-4614




Template-Type: ReDIF-Article 1.0
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Author-Name: Zhongwei Tian
Author-X-Name-First: Zhongwei
Author-X-Name-Last: Tian
Author-Name: Wei Hang
Author-X-Name-First: Wei
Author-X-Name-Last: Hang
Title: Optimal ordering and pricing policies in managing perishable products with quality deterioration
Abstract: 
 We consider a monopoly grocery retailer that procures from a far away supplier a batch of a perishable product. A random part of this batch has quality deterioration before entering the market during a long-distance transportation. With the stochastic freshness-keeping ratio, i.e. the ratio of products preserved in high quality after transportation, the grocery retailer has to determine its ordering batch size and selling prices to alleviate cannibalisation caused by quality segmentation. We find that when the realised size of the high-quality product exceeds half of the maximum market potential after the transportation, it is optimal to sell high-quality products only to avoid cannibalisation. Otherwise, it is optimal to sell the high-quality and low-quality products simultaneously to extend sales. We also find that, when more customers arrive or the difference of two quality levels becomes larger, it is optimal to order more to gain more profit. Finally, we investigate the role of freshness-keeping effort on the optimal pricing and ordering policy and further characterise the optimal freshness-keeping effort under various structures of the freshness-keeping cost.
Journal: International Journal of Production Research
Pages: 4472-4494
Issue: 15
Volume: 59
Year: 2021
Month: 8
X-DOI: 10.1080/00207543.2020.1766715
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766715
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:15:p:4472-4494




Template-Type: ReDIF-Article 1.0
Author-Name: Adil Baykasoğlu
Author-X-Name-First: Adil
Author-X-Name-Last: Baykasoğlu
Title: Optimising cutting conditions for minimising cutting time in multi-pass milling via weighted superposition attraction-repulsion (WSAR) algorithm
Abstract: 
 Milling is one of the most frequently used machining operations in manufacturing industry. In order to remove cutting stocks economically and effectively, it is typically necessary to employ a multi-pass milling plan. Nevertheless, an optimisation practice is desirable in order to decide the most appropriate cutting plan (cutting speeds and feed rates) in each cutting pass to minimise the total machining time. In this study, optimisation of cutting conditions in multi-pass milling is achieved by utilising an improved version of a recently developed swarm intelligence based metaheuristic algorithm, which is known as a weighted superposition attraction algorithm. All of the cutting constraints are successfully satisfied and the results obtained from the proposed optimisation algorithm are compared with other optimisation approaches. The proposed optimisation algorithm is able to provide the best solutions for all test cases with reasonable computational time.
Journal: International Journal of Production Research
Pages: 4633-4648
Issue: 15
Volume: 59
Year: 2021
Month: 8
X-DOI: 10.1080/00207543.2020.1767313
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1767313
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:15:p:4633-4648




Template-Type: ReDIF-Article 1.0
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Author-Name: Wenli Cui
Author-X-Name-First: Wenli
Author-X-Name-Last: Cui
Title: Approximation algorithms for the min-max regret identical parallel machine scheduling problem with outsourcing and uncertain processing time
Abstract: 
 We consider the robust (min-max regret) version of identical parallel machine scheduling problem, in which jobs may be outsourced to balance total cost against production efficiency. The total cost is measured in terms of the total completion time of jobs processed in-house and the cost of outsourcing the rest. Processing times of in-house jobs are uncertain and they are described as two types of scenarios: discrete and interval. The objective is to obtain a robust (min-max regret) decision that minimises the absolute deviation of total cost from the optimal solution under the worst-case scenario. We first prove the worst-case scenario for any feasible solution. For the interval scenario, we further prove that the maximum regret value can be obtained in polynomial time for any feasible schedule. We also prove that for any discrete scenario, the minimum total cost can be obtained in polynomial time. Since the problem with the interval scenario is strongly NP-hard, we then transform the problem into an equivalent robust single machine scheduling problem. Finally, we develop 2-approximation algorithms for the problem with discrete and interval scenarios, respectively. These results are helpful for bridging the scheduling theory and practice in identical parallel machining environments with outsourcing and uncertain processing times.
Journal: International Journal of Production Research
Pages: 4579-4592
Issue: 15
Volume: 59
Year: 2021
Month: 8
X-DOI: 10.1080/00207543.2020.1766721
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766721
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:15:p:4579-4592




Template-Type: ReDIF-Article 1.0
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Ganquan Huang
Author-X-Name-First: Ganquan
Author-X-Name-Last: Huang
Author-Name: Xiaolong Guo
Author-X-Name-First: Xiaolong
Author-X-Name-Last: Guo
Title: Financing strategy analysis for a multi-sided platform with blockchain technology
Abstract: 
 Thanks to the credibility and transparency of blockchain technology, small and medium enterprises (SMEs) can use self-guarantee to obtain loans from financial institutions. Unlike the well-developed supply chain finance (SCF) using guarantees provided by a core enterprise, the effectiveness of SCF with self-guarantee is unclear, especially in a multi-sided market setting. The current paper explores this effectiveness by building an analytical model involving four kinds of players: a multi-sided platform, a customer, a bank, and multiple transportation service providers. In this setting, a traditional SCF model with Platform Undertakes Guarantee (PUG) and a novel SCF strategy with self-guarantee (i.e. Customer Undertakes Guarantee (CUG)) are analysed. The results indicate that CUG can bring a Pareto improvement for the market compared to PUG. Although CUG displays higher efficiency, it is not always beneficial to the platform when the customer's opportunity cost rate is higher than the platform's. Furthermore, to mitigate credit risk caused by a low-credit customer, the platform may employ a prepayment strategy. Analytical results of this study indicate that the prepayment ratio does not affect the customer's cost, and thus, providing a high prepayment ratio but a relatively low service fee rate to low-credit customers is suggested to the platform.
Journal: International Journal of Production Research
Pages: 4513-4532
Issue: 15
Volume: 59
Year: 2021
Month: 8
X-DOI: 10.1080/00207543.2020.1766718
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766718
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Template-Type: ReDIF-Article 1.0
Author-Name: Hongwei Zhu
Author-X-Name-First: Hongwei
Author-X-Name-Last: Zhu
Author-Name: Zhiqiang Lu
Author-X-Name-First: Zhiqiang
Author-X-Name-Last: Lu
Author-Name: Chenyao Lu
Author-X-Name-First: Chenyao
Author-X-Name-Last: Lu
Author-Name: Yifei Ren
Author-X-Name-First: Yifei
Author-X-Name-Last: Ren
Title: A reactive scheduling method for disturbances in aircraft moving assembly line
Abstract: 
 Aircraft assembly requires a large number of materials from hundreds of suppliers, and the uncertainty in material delivery has a negative impact on the assembly schedule. Existing researches stop short of introducing how to reschedule assembly activities in this context, so this paper addresses a reactive scheduling problem of aircraft moving assembly line with uncertain material delivery, and a bi-objective model is established. To absorb the advantage of machine learning-based method, we present a SVDD-based reactive scheduling method (SVDD-RS). Firstly, the models under different settings of disturbances in material delivery are solved, and the obtained policies are used to train the SVDD classification model in the offline training phase. In the online reactive scheduling phase, the trained SVDD classification model is used to make a preliminary decision for unstarted activities, and exact start-times are further determined by the local forward-looking algorithm. Computational experiments are carried out over practical cases generated from an aircraft assembly line to evaluate the performance of SVDD-RS. The results show that the SVDD classification model can quickly select policies with reasonable accuracy, and SVDD-RS can guarantee a quick response to the disturbance and produce a high-quality solution, compared to other existing reactive scheduling methods.
Journal: International Journal of Production Research
Pages: 4756-4772
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1771456
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1771456
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:15:p:4756-4772




Template-Type: ReDIF-Article 1.0
Author-Name: Linhan Ouyang
Author-X-Name-First: Linhan
Author-X-Name-Last: Ouyang
Author-Name: Chanseok Park
Author-X-Name-First: Chanseok
Author-X-Name-Last: Park
Author-Name: Yan Ma
Author-X-Name-First: Yan
Author-X-Name-Last: Ma
Author-Name: Yizhong Ma
Author-X-Name-First: Yizhong
Author-X-Name-Last: Ma
Author-Name: Min Wang
Author-X-Name-First: Min
Author-X-Name-Last: Wang
Title: Bayesian hierarchical modelling for process optimisation
Abstract: 
 Many industrial process optimisation methods rely on empirical models that relate output responses to a set of design variables. One of the most crucial problems in process optimisation is how to efficiently implement model selection and model estimation. This paper presents a Bayesian hierarchical modelling approach to process optimisation based on the seemingly unrelated regression (SUR) models. This approach can estimate a set of predictors to be included in a model based on a Bayesian hierarchical procedure (i.e. model selection) and then give model prediction based on a Bayesian SUR model (i.e. model estimation). Meanwhile, a two-stage optimisation strategy considering practitioners’ preference information is proposed in process optimisation, which initially finds a set of non-dominated input settings and then determines the best one based on the similarity to an ideal solution method. The performance and effectiveness of the proposed method are illustrated with both simulation studies and a case study. The comparison results demonstrate that the proposed method can be a good alternative to existing process optimisation methods.
Journal: International Journal of Production Research
Pages: 4649-4669
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1769873
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1769873
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Template-Type: ReDIF-Article 1.0
Author-Name: Maher A. N. Agi
Author-X-Name-First: Maher A. N.
Author-X-Name-Last: Agi
Author-Name: Sohrab Faramarzi-Oghani
Author-X-Name-First: Sohrab
Author-X-Name-Last: Faramarzi-Oghani
Author-Name: Öncü Hazır
Author-X-Name-First: Öncü
Author-X-Name-Last: Hazır
Title: Game theory-based models in green supply chain management: a review of the literature
Abstract: 
 This paper provides a systematic review and analysis of the game-theroy-based research in Green Supply Chains Management (GSCM). Based on a rigorous content analysis of 108 papers carefully selected from the literature, we present a detailed picture of the current state of this research and point to the promising future directions. Our analysis shows a rapid increase in the number of publications during the last three years, with an imbalance in the contribution of the publishing outlets, as nearly two third of the reviewed papers are published by only four journals. Results also show the dominance of deterministic static models and simple two-level SC structures. Developing stochastic models, considering the risk and the evolutionary nature that inherently characterise the business environment and investigating more complex multi-level SC structures are among the promising future research opportunities.
Journal: International Journal of Production Research
Pages: 4736-4755
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1770893
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1770893
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Template-Type: ReDIF-Article 1.0
Author-Name: Wei Jiang
Author-X-Name-First: Wei
Author-X-Name-Last: Jiang
Author-Name: Jiyin Liu
Author-X-Name-First: Jiyin
Author-X-Name-Last: Liu
Author-Name: Yun Dong
Author-X-Name-First: Yun
Author-X-Name-Last: Dong
Author-Name: Li Wang
Author-X-Name-First: Li
Author-X-Name-Last: Wang
Title: Assignment of duplicate storage locations in distribution centres to minimise walking distance in order picking
Abstract: 
 With the rapid development of e-commerce, the orders processed in B2C warehouses are characterised by heterogeneous and small volume. The traditional storage assignment strategies used in the picker-to-parts warehouses do not have advantage any more. In this case, the scattered storage strategy is a good alternative. In this paper, we study a new scattered storage strategy that allows the same product to be placed in multiple storage locations. The correlation between products which reflects how frequently any two products will be ordered together in the same order is considered. The problem is formulated as a 0-1 integer programming model to minimise the weighted sum of distances between the products, with weight being the elements of the correlation matrix. To solve large-scale problems, a GA and a basic PSO algorithm are developed. To improve solution quality, a new PSO algorithm based on the problem characteristic is designed and a hybrid algorithm combing it with GA is proposed. Experiments show that the solutions of these algorithms are close to the optimal solutions for the small-sale problems. For larger problems, the specially designed new PSO greatly improves solution quality as compared to the basic algorithms and the hybrid algorithm makes further improvement.
Journal: International Journal of Production Research
Pages: 4457-4471
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1766714
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766714
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Template-Type: ReDIF-Article 1.0
Author-Name: Amirhossein Khezri
Author-X-Name-First: Amirhossein
Author-X-Name-Last: Khezri
Author-Name: Hichem Haddou Benderbal
Author-X-Name-First: Hichem Haddou
Author-X-Name-Last: Benderbal
Author-Name: Lyes Benyoucef
Author-X-Name-First: Lyes
Author-X-Name-Last: Benyoucef
Title: Towards a sustainable reconfigurable manufacturing system (SRMS): multi-objective based approaches for process plan generation problem
Abstract: 
 Nowadays to meet the continuously growing worldwide demand for capital and consumer goods while considering the associated economic, environmental, and social aspects, new generation of manufacturing systems are developed and adopted. The goal is to respond to changing market needs while minimising adverse effects on the environment. Reconfigurable manufacturing system (RMS) – due to its flexibility and characteristics – can increase the system sustainability and responsiveness to satisfy the market needs. This paper considers an environmental oriented multi-objective process plan generation problem for a sustainable reconfigurable manufacturing system (SRMS). Three criteria are minimised respectively the sustainability-metric value, the total production time and the total production cost. As a new criterion, the sustainability-metric value considers both liquid hazardous waste and greenhouse gas emissions (GHG). First, a multi-objective integer linear programming (MOILP) model is proposed. Second, due to the problem complexity, three approaches are adapted respectively a posteriori approach called augmented ε-constraint (AUGECON) and two evolutionary approaches namely, non-dominated sorting genetic algorithm II (NSGA-II) and strength Pareto evolutionary algorithm II (SPEA-II). Finally, due to the lack of real world data and to illustrate the applicability of the three approaches, a simple numerical example is presented and the obtained numerical results are analysed.
Journal: International Journal of Production Research
Pages: 4533-4558
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1766719
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766719
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Template-Type: ReDIF-Article 1.0
Author-Name: Tobias Mönch
Author-X-Name-First: Tobias
Author-X-Name-Last: Mönch
Author-Name: Arnd Huchzermeier
Author-X-Name-First: Arnd
Author-X-Name-Last: Huchzermeier
Author-Name: Peter Bebersdorf
Author-X-Name-First: Peter
Author-X-Name-Last: Bebersdorf
Title: Variable takt times in mixed-model assembly line balancing with random customisation
Abstract: 
 In turbulent times featuring increased customisation, higher demand volatility, and shortened product life cycles, companies gain a competitive advantage by adopting a single yet highly flexible assembly line. A cornerstone of today's production systems is determining the optimal takt time (or cycle time) by aligning the assembly pace with the desired level of output. In practice, most companies rely on a fixed takt time, even when the work content between models varies considerably. We show that, in contrast to a fixed takt system, variable takt times reduce not only labour inefficiencies but also the complexity of the mixed-model assembly line balancing problem. Inspired by our industry partner Fendt, an innovation leader in the global agricultural machinery market and benchmark for a wide range of industries, we define a generalisable mixed-integer programming model that accounts for key conditions neglected in previous research – in particular, random customisation through configuration-specific task times and assembly quality by assigning operator workloads to ‘zones’. Introducing such operator work zones reveals that firms need not face a time–quality trade-off whereby takt time must be prioritised over how well work is performed. Our numerical study and takt time sensitivity analysis document the effectiveness of this approach when its results are compared with those under Fendt's current takt times.
Journal: International Journal of Production Research
Pages: 4670-4689
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1769874
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1769874
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Template-Type: ReDIF-Article 1.0
Author-Name: Timo Busert
Author-X-Name-First: Timo
Author-X-Name-Last: Busert
Author-Name: Alexander Fay
Author-X-Name-First: Alexander
Author-X-Name-Last: Fay
Title: Information quality focused value stream mapping for the coordination and control of production processes
Abstract: 
 Manufacturing companies become more and more dependent on reliable information from the shop floor. This information represents the current state of the shop floor and is often the basis for control decisions. By relying on this information, the quality of the information becomes a crucial factor, as it may decisively influence the result of the control decision. To ensure sufficient information quality, a six-staged method, called ‘Information Quality focused Value Stream Mapping for the Control of Production Processes', is introduced in this paper. It is based on the value stream mapping (VSM) and extends parts of the value stream analysis (VSA) to capture relevant information needed within the value stream design (VSD). Furthermore, the method extends the VSD to select and develop methods for the coordination and control of the production processes and to harmonise the necessary information flows for coordination and control. The application of the method and the relevance of harmonising information quality is illustrated by an industrial application at an automotive supplier.
Journal: International Journal of Production Research
Pages: 4559-4578
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1766720
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766720
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhi-chao Zhang
Author-X-Name-First: Zhi-chao
Author-X-Name-Last: Zhang
Author-Name: Hai-yan Xu
Author-X-Name-First: Hai-yan
Author-X-Name-Last: Xu
Author-Name: Ke-bing Chen
Author-X-Name-First: Ke-bing
Author-X-Name-Last: Chen
Title: Operational decisions and financing strategies in a capital-constrained closed-loop supply chain
Abstract: 
 This paper aims to find operational decisions and financing strategies in a closed-loop supply chain (CLSC) consisting of a financially constrained manufacturer and a retailer. Based on a benchmark model without financing, three different financing strategies for the capital-constrained manufacturer, bank financing (BF), retailer credit financing (RCF), and hybrid financing (HF), are respectively incorporated and investigated. Analytical results show that: (a) Depending on the initial working capital /and the increased cost of financing from the bank, the manufacturer will change remanufacturing strategy from Partial remanufacturing to Complete remanufacturing for capital constrained CLSC when the relative unit cost of the remanufactured product is moderate; RCF strategy only revises and charges a higher wholesale price of new and remanufactured products; (b) For a financially constrained manufacturer in the CLSC, it holds the prerequisite to implement external financing and a higher financing rate to bank clearly cuts down the profits of the manufacturer and the channel but improves the retailer’s profit under certain conditions; RCF strategy always redistributes the channel profit compared with the non-capital-constrained CLSC; c) A feasible financing rate to the bank of the manufacturer and an appropriate interest rate threshold of the retailer are potentially confirmed.
Journal: International Journal of Production Research
Pages: 4690-4710
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1770356
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1770356
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Template-Type: ReDIF-Article 1.0
Author-Name: Yongjing Wang
Author-X-Name-First: Yongjing
Author-X-Name-Last: Wang
Author-Name: Feiying Lan
Author-X-Name-First: Feiying
Author-X-Name-Last: Lan
Author-Name: Jiayi Liu
Author-X-Name-First: Jiayi
Author-X-Name-Last: Liu
Author-Name: Jun Huang
Author-X-Name-First: Jun
Author-X-Name-Last: Huang
Author-Name: Shizhong Su
Author-X-Name-First: Shizhong
Author-X-Name-Last: Su
Author-Name: Chunqian Ji
Author-X-Name-First: Chunqian
Author-X-Name-Last: Ji
Author-Name: Duc Truong Pham
Author-X-Name-First: Duc Truong
Author-X-Name-Last: Pham
Author-Name: Wenjun Xu
Author-X-Name-First: Wenjun
Author-X-Name-Last: Xu
Author-Name: Quan Liu
Author-X-Name-First: Quan
Author-X-Name-Last: Liu
Author-Name: Zude Zhou
Author-X-Name-First: Zude
Author-X-Name-Last: Zhou
Title: Interlocking problems in disassembly sequence planning
Abstract: 
 Remanufacturing is the rebuilding of a product to specifications of the original manufactured product using a combination of directly reused, repaired and new parts. Disassembly, the first and arguably most important process in remanufacturing, tends to be labour-intensive due to complexities in the conditions of end-of-life products returned for remanufacture. Robotic disassembly is an attractive alternative to manual disassembly but robotic systems cannot plan disassembly sequences automatically and manual planning is still necessary. Planning requires machines to interpret physical space using a suitable representation to reflect physical contacts and constraints as well as rules for deciding the sequences of disassembly operations. This paper proposes a representation to describe physical contacts and constraints, and a new approach allowing machines to plan disassembly using the representation. The approach involves employing an assembly matrix and simple logic gates to generate a contact matrix, a space interference matrix and a relation matrix. Rules and algorithms are discussed to explain the calculation of sequences through manipulating the three matrices. A key benefit is that the proposed method can deal with interlocked mechanical structures which cannot be handled using conventional methods. The proposed method is also flexible and is suitable for either selective or complete disassembly.
Journal: International Journal of Production Research
Pages: 4723-4735
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1770892
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1770892
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Template-Type: ReDIF-Article 1.0
Author-Name: Fereshteh Mafakheri
Author-X-Name-First: Fereshteh
Author-X-Name-Last: Mafakheri
Author-Name: Dotun Adebanjo
Author-X-Name-First: Dotun
Author-X-Name-Last: Adebanjo
Author-Name: Audley Genus
Author-X-Name-First: Audley
Author-X-Name-Last: Genus
Title: Coordinating biomass supply chains for remote communities: a comparative analysis of non-cooperative and cooperative scenarios
Abstract: 
 The absence of economies of scale is a major barrier in use of renewable energy sources in small and dispersed off-grid remote communities. For example, in northern Canada, diesel is currently the main source of electricity and heat generation. Coordination of biomass supply chains could play a key role in improving the cost efficiency and reliability of bioenergy generation through bundled ordering and creation of storage hubs. In this study, a supply chain management model with multiple suppliers and multiple end-user communities is formulated. The proposed model enables us to analyse and compare the outcomes of adopting a cooperative coordination strategy (with a joint pay-off for communities) versus a non-cooperative coordination strategy (with individual payoffs for communities). Other peculiar attributes of the proposed model rest in the addressing of restricted ordering schedules and quantities (due to unavailability of pathways) by advocating nonlinear ordering and distribution costs (to incorporate quantity discounts) achieved through coordinated and/or collective inventories. A real biomass supply chain case study of three northernmost Nunavik communities in Quebec is considered to show the applicability of the model and provide insights for uptake of bioenergy sources in remote off-grid communities.
Journal: International Journal of Production Research
Pages: 4615-4632
Issue: 15
Volume: 59
Year: 2021
Month: 8
X-DOI: 10.1080/00207543.2020.1767312
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1767312
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Template-Type: ReDIF-Article 1.0
Author-Name: Bocewicz Grzegorz
Author-X-Name-First: Bocewicz
Author-X-Name-Last: Grzegorz
Author-Name: Nielsen Izabela
Author-X-Name-First: Nielsen
Author-X-Name-Last: Izabela
Author-Name: Gola Arkadiusz
Author-X-Name-First: Gola
Author-X-Name-Last: Arkadiusz
Author-Name: Banaszak Zbigniew
Author-X-Name-First: Banaszak
Author-X-Name-Last: Zbigniew
Title: Reference model of milk-run traffic systems prototyping
Abstract: 
 A declarative model is developed in this study. It allows us to formulate a constraint satisfaction problem that supports making decisions in the process of seeking a periodic distribution policy with a plan of whom to serve, how much to deliver, by which fleet of logistic trains travelling regularly, and on which routes. Implemented through a constrained, programming-driven solver, it allows for the formulation of forward and reverse milk-run vehicle routing and scheduling problems, subject to the constraints imposed by an in-plant distribution network. Consequently, it can be used to determine the number of transport trips and their organisation in time and space needed for the timely delivery of material to specific loading/unloading points. In this context, the proposed model meets the needs of an interactive search for solutions by the alternate and iterative formulation of successive forward and reverse decision problems.
Journal: International Journal of Production Research
Pages: 4495-4512
Issue: 15
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1766717
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766717
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Template-Type: ReDIF-Article 1.0
Author-Name: Francesco Zangaro
Author-X-Name-First: Francesco
Author-X-Name-Last: Zangaro
Author-Name: Stefan Minner
Author-X-Name-First: Stefan
Author-X-Name-Last: Minner
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Title: A supervised machine learning approach for the optimisation of the assembly line feeding mode selection
Abstract: 
 The Line Feeding Problem (LFP) involves the delivery of components to the production area. Previous models minimise the delivery costs and optimally assign each component to a line feeding mode between line stocking, kitting, and sequencing but cannot provide easily comprehensible guidelines. We use the Classification And Regression Tree (CART) algorithm to develop, in a supervised way, a decision tree based on problems that are solved with a Mixed Integer Programming (MIP) model for training purposes. Based on selected attributes of the components and the manufacturing environment, the decision tree suggests a line feeding mode for every component. For a synthetically determined training and evaluation data set, we find that the classification tree can predict the line feeding mode with an average classification accuracy of 78.49%. After the decision tree is implemented and a line feeding mode is selected for each component, an infeasible solution might occur. We develop a repair approach that solves this problem with an average cost deviation from the optimal solution of 0.38%.
Journal: International Journal of Production Research
Pages: 4881-4902
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1851793
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1851793
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:16:p:4881-4902




Template-Type: ReDIF-Article 1.0
Author-Name: Bongjun Ji
Author-X-Name-First: Bongjun
Author-X-Name-Last: Ji
Author-Name: Farhad Ameri
Author-X-Name-First: Farhad
Author-X-Name-Last: Ameri
Author-Name: Hyunbo Cho
Author-X-Name-First: Hyunbo
Author-X-Name-Last: Cho
Title: A non-conformance rate prediction method supported by machine learning and ontology in reducing underproduction cost and overproduction cost
Abstract: 
 Nonconformities are the major sources of waste in manufacturing process. Nonconformities cannot be fully eliminated but their occurrence rate can be predicted. This paper proposes a hybrid approach based on ontological modelling and machine learning for predicting the non-conformance rates of a manufacturing process and minimising its associated costs. Based on the proposed approach, the work orders, that are represented semantically using a formal ontology, are first clustered according to their semantic similarities and then, for each cluster, the appropriate models that predict the probability distribution of non-conformance rates are developed. When a new work order is created, the most similar work order is retrieved from historical records, and the probability distribution of its non-conformance rate is estimated by applying the predictive model of the cluster to which the work order belongs. The probability distribution is used to calculate the expected underproduction and overproduction cost and to determine the amount of production that minimises the expected costs. The proposed method was validated using a dataset obtained from a manufacturer of packaging for cosmetics. Compared to the expert’s opinions and other machine learning algorithms, the proposed method demonstrated better performance with respect to cost reduction.
Journal: International Journal of Production Research
Pages: 5011-5031
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2021.1933237
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1933237
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Template-Type: ReDIF-Article 1.0
Author-Name: Ajit Sharma
Author-X-Name-First: Ajit
Author-X-Name-Last: Sharma
Author-Name: Zhibo Zhang
Author-X-Name-First: Zhibo
Author-X-Name-Last: Zhang
Author-Name: Rahul Rai
Author-X-Name-First: Rahul
Author-X-Name-Last: Rai
Title: The interpretive model of manufacturing: a theoretical framework and research agenda for machine learning in manufacturing
Abstract: 
 Manufacturing is undergoing a paradigmatic shift as it assimilates and is transformed by machine learning and other cognitive technologies. A new paradigm usually necessitates a new framework to comprehend it fully, organise extant knowledge, identify gaps in knowledge, guide future research and practice, and synthesise new knowledge. Paradoxically, such a framework to guide the research and practice of ML in manufacturing remains absent. This paper attempts to fill this gap by presenting the interpretive model of manufacturing as an integrative framework for ML in manufacturing. A systematic hybrid literature review approach has been adopted to conduct both thematic and conceptual synthesis of the literature. The descriptive literature review method has been used to conduct a thematic synthesis of the literature. The framework synthesis method has been used to complete a conceptual synthesis of the literature. The resultant framework, the interpretive model of manufacturing, is articulated as consisting of scan, store, interpret, execute, and learn as its purposive components. Research questions have been identified for each of these components, as well as at their interfaces, to develop a comprehensive and systematic research agenda. Additional areas for extending research have also been identified. Implications for manufacturing operations, manufacturing strategy, and manufacturing policy have been drawn out for practitioners and policy makers.
Journal: International Journal of Production Research
Pages: 4960-4994
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2021.1930234
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1930234
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Template-Type: ReDIF-Article 1.0
Author-Name: Bart L. MacCarthy
Author-X-Name-First: Bart L.
Author-X-Name-Last: MacCarthy
Author-Name: Robert C. Pasley
Author-X-Name-First: Robert C.
Author-X-Name-Last: Pasley
Title: Group decision support for product lifecycle management
Abstract: 
 Product Lifecycle Management (PLM) systems support industrial organisations in managing their product portfolios and related data across all phases of the product lifecycle. PLM seeks to enhance an organisation's ability to manage its product development activities and support collaboration across organisational functions and business units, and between organisations. Effective decision-making is vital for the successful management of products over their lifecycle. However, decision-making is an under-researched area in PLM. We argue that decision-making theory and group decision support concepts can be brought to bear to enhance PLM decision-making processes. We present and justify a set of six principles to support decision-making in a PLM context. The paper highlights the need to consider and capture decisions as distinct units of PLM knowledge to support product lifecycle management. We derive a generic information flow and a group decision support structure for PLM decision-making that encapsulates the six principles. Three industrial cases are analysed to illustrate the application and value of the principles in supporting decision-making. The principles enable PLM decisions to be codified, recorded, and reviewed. Decision-making processes can be reused where appropriate. The principles can support future innovations that may affect PLM, such as ontological and semantic reasoning and Artificial Intelligence.
Journal: International Journal of Production Research
Pages: 5050-5067
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1779372
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1779372
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Template-Type: ReDIF-Article 1.0
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Mingzhou Jin
Author-X-Name-First: Mingzhou
Author-X-Name-Last: Jin
Author-Name: Zhe Yuan
Author-X-Name-First: Zhe
Author-X-Name-Last: Yuan
Title: Robotic mobile fulfilment systems considering customer classes
Abstract: 
 This paper studies a Robotic Mobile Fulfilment System (RMFS), featured by a number of robots lifting and transporting movables storage shelves from storage grids to order pickers. In such systems, online retailers often classify their customers by two major classes ‘expedited shipping’ and ‘standard shipping’. We build high-dimension Markov models to describe this system with customer classes, calculate the throughput of this system given the number of robots and provide design rules to determine the optimal number of robots and their capacities considering the trade-off between capacities of picker stations and robots. We verify the analytic results of Markov models with simulations. We further consider multiple-picker RMFS and study its optimal design.
Journal: International Journal of Production Research
Pages: 5032-5049
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1779370
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1779370
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Template-Type: ReDIF-Article 1.0
Author-Name: Rahul Rai
Author-X-Name-First: Rahul
Author-X-Name-Last: Rai
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Machine learning in manufacturing and industry 4.0 applications
Abstract: 
 The machine learning (ML) field has deeply impacted the manufacturing industry in the context of the Industry 4.0 paradigm. The industry 4.0 paradigm encourages the usage of smart sensors, devices, and machines, to enable smart factories that continuously collect data pertaining to production. ML techniques enable the generation of actionable intelligence by processing the collected data to increase manufacturing efficiency without significantly changing the required resources. Additionally, the ability of ML techniques to provide predictive insights has enabled discerning complex manufacturing patterns and offers a pathway for an intelligent decision support system in a variety of manufacturing tasks such as intelligent and continuous inspection, predictive maintenance, quality improvement, process optimisation, supply chain management, and task scheduling. While different ML techniques have been used in a variety of manufacturing applications in the past, many open questions and challenges remain, from Big data curation, storage, and understanding, data reasoning to enable real-time actionable intelligence to topics such as edge computing and cybersecurity aspects of smart manufacturing. Hence, this special issue is focused on bringing together a wide range of researchers to report the latest efforts in the fundamental theoretical as well as experimental aspects of ML and their applications in manufacturing and productionsystems.
Journal: International Journal of Production Research
Pages: 4773-4778
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2021.1956675
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1956675
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Template-Type: ReDIF-Article 1.0
Author-Name: M. E. Sharp
Author-X-Name-First: M. E.
Author-X-Name-Last: Sharp
Author-Name: T. D. Hedberg
Author-X-Name-First: T. D.
Author-X-Name-Last: Hedberg
Author-Name: W. Z. Bernstein
Author-X-Name-First: W. Z.
Author-X-Name-Last: Bernstein
Author-Name: S. Kwon
Author-X-Name-First: S.
Author-X-Name-Last: Kwon
Title: Feasibility study for an automated engineering change process
Abstract: 
 Engineering change is a significant cost for projects. While avoiding and mitigating the risk of change is ideal, mistakes and improvements are recognised as more is learned about the decisions made in a design. This paper presents a feasibility and performance analysis of automating engineering change requests to demonstrate the promise for increasing speed, efficiency, and effectiveness of product-lifecycle-wide engineering-change-requests. A comparatively simple case is examined to mimic the reduced set of alterable aspects of a typical change request and to highlight the need of appropriate search algorithms as brute force methods are prohibitively resource intensive. Although such cases may seem trivial for human agents, with the volume of expected change requests in a typical facility, the potential opportunity gain by eliminating or reducing the amount of human effort in low-level changes accumulate into significant returns for the industry on time and money. Herein, the genetic algorithm is selected to demonstrate feasibility with its broad scope of applicability and low barriers to deployment. Future refinement of this or other sophisticated algorithms leveraging the nature of the standard representations and qualities of alterable design features could produce tools with strong implications for process efficiency and industry competitiveness in its projects execution.
Journal: International Journal of Production Research
Pages: 4995-5010
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2021.1893900
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1893900
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Template-Type: ReDIF-Article 1.0
Author-Name: Rafael Lorenz
Author-X-Name-First: Rafael
Author-X-Name-Last: Lorenz
Author-Name: Julian Senoner
Author-X-Name-First: Julian
Author-X-Name-Last: Senoner
Author-Name: Wilfried Sihn
Author-X-Name-First: Wilfried
Author-X-Name-Last: Sihn
Author-Name: Torbjørn Netland
Author-X-Name-First: Torbjørn
Author-X-Name-Last: Netland
Title: Using process mining to improve productivity in make-to-stock manufacturing
Abstract: 
 This paper proposes a data-driven procedure to improve productivity in make-to-stock manufacturing. By leveraging recent developments in information systems research, the paper addresses manufacturing systems with high process complexity and variety. Specifically, the proposed procedure draws upon process mining to dynamically map and analyse manufacturing processes in an automated manner. This way, manufacturers can leverage data to overcome the limitations of existing process mapping methods, which only provide static snapshots of process flows. By bridging data and process science, process mining can exploit hitherto untapped potential for productivity improvement. The proposed procedure is empirically validated at a leading manufacturer of sanitary products. The field test leads to three concrete improvement suggestions for the company. This research contributes to the literature on production research by demonstrating a novel use of process mining in manufacturing and by guiding practitioners in its implementation.
Journal: International Journal of Production Research
Pages: 4869-4880
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2021.1906460
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1906460
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Template-Type: ReDIF-Article 1.0
Author-Name: G. Ø. Rønsch
Author-X-Name-First: G. Ø.
Author-X-Name-Last: Rønsch
Author-Name: M. Kulahci
Author-X-Name-First: M.
Author-X-Name-Last: Kulahci
Author-Name: M. Dybdahl
Author-X-Name-First: M.
Author-X-Name-Last: Dybdahl
Title: An investigation of the utilisation of different data sources in manufacturing with application in injection moulding
Abstract: 
 This work focuses on the effective utilisation of varying data sources in injection moulding for process improvement through a close collaboration with an industrial partner. The aim is to improve productivity in an injection moulding process consisting of more than 100 injection moulding machines. It has been identified that predicting quality through Machine Process Data is the key to increase productivity by reducing scrap. The scope of this work is to investigate whether a sufficient prediction accuracy (less than 10% of the specification spread) can be achieved by using readily available Machine Process Data or additional sensor signals obtained at a higher cost are needed. The latter comprises Machine Profile and Cavity Profile Data. One of the conclusions is that the available Machine Process Data does not capture the variation in the raw material that impacts element quality and therefore fails to meet the required prediction accuracy. Utilising Machine Profiles or Cavity Profiles have shown similar results in reducing the prediction error. Since the cost of implementing cavity sensors in the entire production is higher than utilising the Machine Profiles, further exploration around improving the utilisation of Machine Profile Data in a setting where process variation and labelled data are limited is proposed.
Journal: International Journal of Production Research
Pages: 4851-4868
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2021.1893853
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1893853
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian Wang
Author-X-Name-First: Jian
Author-X-Name-Last: Wang
Author-Name: Xue-Cheng Xi
Author-X-Name-First: Xue-Cheng
Author-X-Name-Last: Xi
Author-Name: Ling Qin
Author-X-Name-First: Ling
Author-X-Name-Last: Qin
Author-Name: Ya-Ou Zhang
Author-X-Name-First: Ya-Ou
Author-X-Name-Last: Zhang
Author-Name: Wan-Sheng Zhao
Author-X-Name-First: Wan-Sheng
Author-X-Name-Last: Zhao
Title: Non-productive time optimization for 5-axis EDM drilling using HVNTS algorithm
Abstract: 
 This paper presents a hybrid variable neighbourhood search/tabu search (HVNTS) method and a neighbourhood generation strategy called pairwise inter-reshuffle (PIR) for process planning of 5-axis electrical discharge machining (EDM) drilling processes, which aims to minimize the total non-productive time of the machining process, including tool travelling time, tool switching time and Z-axis compensation moving time. To obtain a mathematical model of the non-productive time, a kinematic transformation and a Chebyshev distance function are then utilized. To solve the mathematical model efficiently, an HVNTS algorithm is applied as the model has a large number of 0–1variables. To improve the solution quality, the PIR method and a dynamic neighbourhood strategy are applied simultaneously and verified. The obtained simulation results demonstrate that the proposed basic and the improved HVNTS have a significant contribution in optimizing the non-productive time of the 5-axis EDM drilling process effectively.
Journal: International Journal of Production Research
Pages: 5068-5082
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1779961
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1779961
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Glaeser
Author-X-Name-First: Andrew
Author-X-Name-Last: Glaeser
Author-Name: Vignesh Selvaraj
Author-X-Name-First: Vignesh
Author-X-Name-Last: Selvaraj
Author-Name: Sooyoung Lee
Author-X-Name-First: Sooyoung
Author-X-Name-Last: Lee
Author-Name: Yunseob Hwang
Author-X-Name-First: Yunseob
Author-X-Name-Last: Hwang
Author-Name: Kangsan Lee
Author-X-Name-First: Kangsan
Author-X-Name-Last: Lee
Author-Name: Namjeong Lee
Author-X-Name-First: Namjeong
Author-X-Name-Last: Lee
Author-Name: Seungchul Lee
Author-X-Name-First: Seungchul
Author-X-Name-Last: Lee
Author-Name: Sangkee Min
Author-X-Name-First: Sangkee
Author-X-Name-Last: Min
Title: Applications of deep learning for fault detection in industrial cold forging
Abstract: 
 The feasibility of using deep learning techniques in industrial cold forging for fault detection was investigated. In this work, vibration data were collected from an industrial setting to detect machine conditions resulting in defective products (faults). After collecting data from several commonly encountered faults, a Convolutional Neural Network classifier detected fault conditions with 99.02% accuracy and further classified each fault with 92.66% accuracy. A decision tree (DT) model was also used in an attempt to detect and classify faults using time domain features. The model was able to detect faults with 92.5% accuracy but was unable to classify them. In addition, DT feature importance analysis was performed to understand how various faults impacted the machine signal for future refinement of the proposed system. The results suggest that the proposed deep learning method has the potential to detect faults in cold forging, but future work is required to validate the method.
Journal: International Journal of Production Research
Pages: 4826-4835
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2021.1891318
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1891318
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Template-Type: ReDIF-Article 1.0
Author-Name: Zheng Wang
Author-X-Name-First: Zheng
Author-X-Name-Last: Wang
Author-Name: Qingxiu Liu
Author-X-Name-First: Qingxiu
Author-X-Name-Last: Liu
Author-Name: Hansi Chen
Author-X-Name-First: Hansi
Author-X-Name-Last: Chen
Author-Name: Xuening Chu
Author-X-Name-First: Xuening
Author-X-Name-Last: Chu
Title: A deformable CNN-DLSTM based transfer learning method for fault diagnosis of rolling bearing under multiple working conditions
Abstract: 
 Machine learning methods are widely used for rolling bearing fault diagnosis. Most of them are based on a basic assumption that training and testing data are adequate and follow the same distribution. However, for bearings working under multiple working conditions, dynamic changes are inevitable and labelled vibration data are usually insufficient. To deal with the issues, a new fault diagnosis method using deformable convolutional neural network (CNN), deep long short-term memory (DLSTM) and transfer learning strategies is designed. Specifically, a model is constructed by integrating deformable CNN, DLSTM and dense layers. Among them, deformable CNN enhances the ability of standard CNNs for local feature extraction using fixed geometric structures. DLSTM further encodes the sequential information contained in the output of deformable CNN. Dense layers are applied to capture high-level features then classify the data samples as each fault type. The model is firstly pre-trained using data samples under one working condition. Then, transfer learning strategies are implemented to fine-tune the pre-trained model utilising very few samples of another working condition, enabling it to identify fault types of bearing under new condition. Experiments are conducted and results show that the presented model yields higher than comparative performance compared with state-of-the-art methods.
Journal: International Journal of Production Research
Pages: 4811-4825
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1808261
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1808261
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Template-Type: ReDIF-Article 1.0
Author-Name: Junlong Chen
Author-X-Name-First: Junlong
Author-X-Name-Last: Chen
Author-Name: Zijun Zhang
Author-X-Name-First: Zijun
Author-X-Name-Last: Zhang
Author-Name: Feng Wu
Author-X-Name-First: Feng
Author-X-Name-Last: Wu
Title: A data-driven method for enhancing the image-based automatic inspection of IC wire bonding defects
Abstract: 
 Visually inspecting integrated circuit (IC) wire bonding defects is important to ensuring the product quality after the packaging process. The availability of IC X-ray images offers an unprecedented opportunity of studying the image-based automatic IC wire inspection. In this paper, a data-driven method consists of data pre-processing, feature engineering, and classification is developed to address such problem. The data pre-processing is composed of a chip identification algorithm for locating and separating IC chip image patches from the raw images as well as a wire segmentation algorithm for obtaining the wire region. Next, geometric features extracted from the segmented wires are fed into classification models for identifying defects. Five data mining methods are utilised to develop classification models. The vision detection system (VDS) and convolutional neural networks (CNN) are considered as benchmarks. In computational studies, the effectiveness of the developed method is validated by using X-ray images collected from a semiconductor back-end factory in Mainland China. A comparative analysis is conducted to determine the most suitable classifier for the developed method in the chip classification and the SVM model is finally selected. Advantages of the developed method are verified by benchmarking against the VDS and CNN.
Journal: International Journal of Production Research
Pages: 4779-4793
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1821928
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1821928
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Template-Type: ReDIF-Article 1.0
Author-Name: Chandan K. Sahu
Author-X-Name-First: Chandan K.
Author-X-Name-Last: Sahu
Author-Name: Crystal Young
Author-X-Name-First: Crystal
Author-X-Name-Last: Young
Author-Name: Rahul Rai
Author-X-Name-First: Rahul
Author-X-Name-Last: Rai
Title: Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review
Abstract: 
 Augmented reality (AR) has proven to be an invaluable interactive medium to reduce cognitive load by bridging the gap between the task-at-hand and relevant information by displaying information without disturbing the user's focus. AR is particularly useful in the manufacturing environment where a diverse set of tasks such as assembly and maintenance must be performed in the most cost-effective and efficient manner possible. While AR systems have seen immense research innovation in recent years, the current strategies utilised in AR for camera calibration, detection, tracking, camera position and orientation (pose) estimation, inverse rendering, procedure storage, virtual object creation, registration, and rendering are still mostly dominated by traditional non-AI approaches. This restricts their practicability to controlled environments with limited variations in the scene. Classical AR methods can be greatly improved through the incorporation of various AI strategies like deep learning, ontology, and expert systems for adapting to broader scene variations and user preferences. This research work provides a review of current AR strategies, critical appraisal for these strategies, and potential AI solutions for every component of the computational pipeline of AR systems. Given the review of current work in both fields, future research work directions are also outlined.
Journal: International Journal of Production Research
Pages: 4903-4959
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1859636
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1859636
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Template-Type: ReDIF-Article 1.0
Author-Name: Dingsen Zhang
Author-X-Name-First: Dingsen
Author-X-Name-Last: Zhang
Author-Name: Xianwen Gao
Author-X-Name-First: Xianwen
Author-X-Name-Last: Gao
Title: Soft sensor of flotation froth grade classification based on hybrid deep neural network
Abstract: 
 In recent years, the technology of deep learning has made great achievements in the field of machine learning. In this study, with the help of the transfer learning method, a kind of soft sensor is designed for the classification of iron ore tailings grade. Firstly, a sample database of froth images of flotation tailings was established. Secondly, the three most reliable models are determined after comparing the accuracy of 13 deep neural network models applied in the flotation froth image. A more accurate hybrid deep neural network model is established, with an accuracy of 97%. Finally, a software system is designed and developed, which can operate stably in the flotation plant. The experimental results show the effectiveness of the proposed hybrid deep neural network in the field of iron ore froth flotation.
Journal: International Journal of Production Research
Pages: 4794-4810
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2021.1894366
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1894366
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Template-Type: ReDIF-Article 1.0
Author-Name: Chengfeng Jian
Author-X-Name-First: Chengfeng
Author-X-Name-Last: Jian
Author-Name: Jing Ping
Author-X-Name-First: Jing
Author-X-Name-Last: Ping
Author-Name: Meiyu Zhang
Author-X-Name-First: Meiyu
Author-X-Name-Last: Zhang
Title: A cloud edge-based two-level hybrid scheduling learning model in cloud manufacturing
Abstract: 
 In the Industry 4.0, edge industrial services such as smart robotic services are widely used in smart factory. The workflow of these services mainly consists of task decomposition and resource allocation. The long scheduling time, high communication delay and load imbalance among edge nodes are the challenging problems. Traditional cloud manufacturing platforms are difficult to meet the new requirements. It is hard for the existing scheduling methods to maintain a balance between algorithm complexity and performance. Training scheduling data by deep learning has become a feasible method to achieve fast prediction of the scheduling results. In this paper, a cloud edge-based two-level hybrid scheduling learning model is put forward at first. Then an improved bat scheduling algorithm with interference factors and variable step size (VSSBA) is proposed. And then, according to the historical scheduling data, the improved long and short-term memory networks (LSTM) model is put forward for fast prediction of the cloud-edge collaborative scheduling results. Experiments show that our proposed learning model can improve the performance of the cloud manufacturing platform in real-life applications efficiently. Finally, future research issues and challenges are identified.
Journal: International Journal of Production Research
Pages: 4836-4850
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1779371
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1779371
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Template-Type: ReDIF-Article 1.0
Author-Name: Dehua Xu
Author-X-Name-First: Dehua
Author-X-Name-Last: Xu
Author-Name: Limin Xu
Author-X-Name-First: Limin
Author-X-Name-Last: Xu
Author-Name: Zhijun Xu
Author-X-Name-First: Zhijun
Author-X-Name-Last: Xu
Author-Name: Xianyu Yu
Author-X-Name-First: Xianyu
Author-X-Name-Last: Yu
Title: A note on scheduling on uniform parallel machines with unavailability constraints
Abstract: 
 We show by counterexample that the binary integer quadratic programming model proposed by Kaabi and Harrath [2019. “Scheduling on Uniform Parallel Machines with Periodic Unavailability Constraints.” International Journal of Production Research 57: 216–227] is incorrect. We fix this model and propose two linear ones.
Journal: International Journal of Production Research
Pages: 5083-5086
Issue: 16
Volume: 59
Year: 2021
Month: 08
X-DOI: 10.1080/00207543.2020.1788739
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1788739
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianxin Deng
Author-X-Name-First: Jianxin
Author-X-Name-Last: Deng
Author-Name: Haiping Zhang
Author-X-Name-First: Haiping
Author-X-Name-Last: Zhang
Author-Name: Shifeng Wei
Author-X-Name-First: Shifeng
Author-X-Name-Last: Wei
Title: Prediction of vehicle-cargo matching probability based on dynamic Bayesian network
Abstract: 
 Matching status (failure or success) between logistics vehicles and cargoes during transport operation influences the decisions of the owners of vehicles and cargoes on scheduling. It is therefore essential to predict the specific matching status probability of vehicle-cargo matching (VCM). This paper defines the VCM probability, formulates the VCM probability problem, and proposes a method to predict this probability based on Bayesian network. The business (vehicle and goods resources) distribution, VCM degree, and business priority are introduced. By mapping business distribution and matching results to network nodes and matching degree as conditional probability, static and dynamic Bayesian networks for single-time sequence and multi-time sequence VCM probability prediction are constructed. A recursive algorithm is also developed to efficiently solve the dynamic Bayesian network model. The results of a prediction example demonstrate that the proposed method and model are valid and efficient. The model shows that VCM probability increases with time, but there is no obvious rule and uncertainty exists, whereas the increase rate gradually decreases with time. Further, adjusting business distribution and priorities can change the VCM probability. The proposed method provides support for the logistics information platform for scheduling decision and controlling strategy and logistics resource selection services.
Journal: International Journal of Production Research
Pages: 5164-5178
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1774677
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1774677
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Template-Type: ReDIF-Article 1.0
Author-Name: Chin-Chia Wu
Author-X-Name-First: Chin-Chia
Author-X-Name-Last: Wu
Author-Name: Jatinder N. D. Gupta
Author-X-Name-First: Jatinder N. D.
Author-X-Name-Last: Gupta
Author-Name: Shuenn-Ren Cheng
Author-X-Name-First: Shuenn-Ren
Author-X-Name-Last: Cheng
Author-Name: Bertrand M. T. Lin
Author-X-Name-First: Bertrand M. T.
Author-X-Name-Last: Lin
Author-Name: Siu-Hung Yip
Author-X-Name-First: Siu-Hung
Author-X-Name-Last: Yip
Author-Name: Win-Chin Lin
Author-X-Name-First: Win-Chin
Author-X-Name-Last: Lin
Title: Robust scheduling for a two-stage assembly shop with scenario-dependent processing times
Abstract: 
 Recently, finding solutions to assembly flowshop scheduling problems is a topic of extensive discussion in research communities. While existing research assumes that job processing times are constant numbers, in several practical situations, due to several external factors like machine breakdowns, working environment changes, worker performance instabilities, and tool quality variations and unavailability, job processing times may vary. In this study, therefore, we address a two-stage assembly flowshop scheduling problem with two scenario-dependent jobs processing times to minimise the maximum makepsan among both scenarios (called robust makespan) In view of the NP-hard nature, we first derive a dominance property and a lower bound to propose a branch-and-bound algorithm to find a permutation schedule with minimum makespan. Following that, we use Johnson’s rule to propose eight polynomial heuristics for finding near-optimal solutions. Furthermore, we propose four cloud theory-based simulated annealing (CSA) hyper-heuristic algorithms incorporating seven low level heuristics to solve a robust two-stage assembly flowshop problem with scenario-dependent processing times. Finally, we empirically evaluate the effectiveness of all the proposed algorithms in minimising the robust makespan.
Journal: International Journal of Production Research
Pages: 5372-5387
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1778208
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1778208
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Template-Type: ReDIF-Article 1.0
Author-Name: Deming Lei
Author-X-Name-First: Deming
Author-X-Name-Last: Lei
Author-Name: Yue Yuan
Author-X-Name-First: Yue
Author-X-Name-Last: Yuan
Author-Name: Jingcao Cai
Author-X-Name-First: Jingcao
Author-X-Name-Last: Cai
Title: An improved artificial bee colony for multi-objective distributed unrelated parallel machine scheduling
Abstract: 
 Distributed scheduling has been frequently investigated with the increasing applications of multi-factory production; however, distributed unrelated parallel machine scheduling problem (DUPMSP) is seldom considered. In this study, multi-objective DUPMSP is considered and an improved artificial bee colony (IABC) is presented to minimise makespan and total tardiness simultaneously. Problem-related knowledge is proved and knowledge-based neighbourhood search is proposed. Employed bees and onlooker bees are decided dynamically and not given fixed numbers in the search process. Different combinations of global search and neighbourhood search are used in employed bee phase and onlooker bee phase. A new way is applied to execute scout phase. Extensive experiments are conducted on the effect of new strategies and performances of IABC. Computational results demonstrate that IABC has reasonable and effective strategies and very competitive performances on solving the considered DUPMSP.
Journal: International Journal of Production Research
Pages: 5259-5271
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1775911
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1775911
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Template-Type: ReDIF-Article 1.0
Author-Name: Flavio Soares de Oliveira Junior
Author-X-Name-First: Flavio Soares
Author-X-Name-Last: de Oliveira Junior
Author-Name: Elton Fernandes
Author-X-Name-First: Elton
Author-X-Name-Last: Fernandes
Author-Name: Laura Bahiense
Author-X-Name-First: Laura
Author-X-Name-Last: Bahiense
Author-Name: Carlos Moacir Grandi
Author-X-Name-First: Carlos Moacir
Author-X-Name-Last: Grandi
Title: A practical approach to support end-of-life commercial aircraft parking, market relocation, retirement and decommissioning strategic decisions
Abstract: 
 This research effort is dedicated to develop and test a mathematical approach to estimate the optimal aircraft age to make decisions about its withdrawn from service, market relocation, or starting its retirement and decommissioning processes. Our method consists of a cost-benefit financial analysis based on the expected revenue from the aircraft returning to operations and the aircraft recovery process to support end-of-life decisions. The core contribution of this research is the possibility of systematically analyse opportunities to return parked aircraft to active service, considering reasonable scenarios of operating revenue improvements or operating cost reductions, postponing the aircraft retirement and decommissioning decision. It is important to highlight that only financial concerns of the end-of-life aircraft problem were analysed. Considering this managerial context, the estimation of the aircraft parking and retirement costs, the recovery of the operating revenues from its market relocation and the recovered values from its disassembly and dismantling may influence these companies' aircraft fleet planning in a well-supported manner. This research intends to fulfill the gaps in the literature regarding commercial aircraft costs and revenues incurred during its end-of-life phase, aiming to estimate how much they affect its total cost of ownership, considering aircraft owners' and operators' decision-making contexts.
Journal: International Journal of Production Research
Pages: 5144-5163
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1774091
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1774091
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Template-Type: ReDIF-Article 1.0
Author-Name: Kebing Chen
Author-X-Name-First: Kebing
Author-X-Name-Last: Chen
Author-Name: Tiaojun Xiao
Author-X-Name-First: Tiaojun
Author-X-Name-Last: Xiao
Author-Name: Shengbin Wang
Author-X-Name-First: Shengbin
Author-X-Name-Last: Wang
Author-Name: Dong Lei
Author-X-Name-First: Dong
Author-X-Name-Last: Lei
Title: Inventory strategies for perishable products with two-period shelf-life and lost sales
Abstract: 
 We develop an inventory model for perishable products with a two-period shelf-life. The demand during a stock out in either period is treated as lost sales. Besides the initial regular order, the manager also has an opportunity to adjust the mid-cycle inventory with either expedited order or returns. An expedited order plan allows the manager to place an emergency order if the mid-cycle leftover inventory is low, while a returns plan offers the manager a chance to return some units within the validity period to suppliers if the leftover inventory is high. We show that both adjustment plans have their own thresholds, which exhibit a similar policy to that in the classical newsvendor model. Due to the dynamics of inventory, we investigate how the regular order is affected by each adjustment plan. Our findings indicate that the expedited order plan has a better performance in controlling the wastage risk, but it results in a higher shortage risk than the returns plan. Considering the respective advantages of the two plans, we show the existence of a new plan that is the combination of the two and justify the motivation for the manager to use it in the perishable inventory management.
Journal: International Journal of Production Research
Pages: 5301-5320
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1777480
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1777480
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Template-Type: ReDIF-Article 1.0
Author-Name: Carmen González-Zapatero
Author-X-Name-First: Carmen
Author-X-Name-Last: González-Zapatero
Author-Name: Javier González-Benito
Author-X-Name-First: Javier
Author-X-Name-Last: González-Benito
Author-Name: Gustavo Lannelongue
Author-X-Name-First: Gustavo
Author-X-Name-Last: Lannelongue
Author-Name: Luis Miguel Ferreira
Author-X-Name-First: Luis Miguel
Author-X-Name-Last: Ferreira
Title: Using fit perspectives to explain supply chain risk management efficacy
Abstract: 
 Supply chain risk management (SCRM) literature acknowledges that the choice of SCRM strategies should fit with contextual factors. Yet empirical support for this premise is scarce, mainly relies on just a single type of fit analysis, and lacks any consideration of organisational structures. Accordingly, this article combines two perspectives of fit analysis: ‘fit as profile deviation’ and ‘fit as moderation’. The former supports the introduction of two concepts: risk management incoherence (RMI) and risk management efficacy (RME). Whereas RMI refers to the lack of fit between the perceived usefulness of different mitigation strategies and their degree of implementation; RME pertains to the fit between the perceived relevance of different SCRM objectives and the degree to which they are achieved. The latter allows us to posit a negative effect of RMI on RME and a negative moderation of the time assigned to a Risk Manager on that effect. A sample of 106 companies confirms the proposed model. Therefore, this study expands existing literature on contingent SCRM and on organisational structures for SCRM.
Journal: International Journal of Production Research
Pages: 5272-5283
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1776412
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1776412
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Template-Type: ReDIF-Article 1.0
Author-Name: Seyyed-Mahdi Hosseini-Motlagh
Author-X-Name-First: Seyyed-Mahdi
Author-X-Name-Last: Hosseini-Motlagh
Author-Name: Maryam Johari
Author-X-Name-First: Maryam
Author-X-Name-Last: Johari
Author-Name: Roza Zirakpourdehkordi
Author-X-Name-First: Roza
Author-X-Name-Last: Zirakpourdehkordi
Title: Grain production management to reduce global warming potential under financial constraints and time value of money using evolutionary game theory
Abstract: 
 With the increase of global warming, grain producers should consider emission reduction in their production activities to move towards sustainable development. Besides the challenges of environmental sustainability, grain producers in developing countries face budget constraints for promoting their sustainability level. Moreover, sustainability strategies made by grain producers are not stable and are continually changing over time. This study proposes an evolutionary game model to investigate the evolutionary behaviours of a population of financially constrained producers in Iran who gain financial support from one dominant distributor based on their sustainability investment in the long term. This study develops a one-population evolutionary game model to investigate different strategies of producers towards sustainability, considering the time value of money. Moreover, using SimaPro 8.0.3 software, the impacts of non-renewable and renewable electricity consumption on global warming potential are evaluated through life cycle assessment for grain production. Results reveal that using biomass as the source of electricity instead of natural gas in the grain production reduces contribution to global warming potential from 269 kg CO2-eq to 18 kg CO2-eq. This study provides stakeholders who have environmental and social concerns (i.e. grain producers and agricultural production management entities) with insights into keeping their supply chain sustainable.
Journal: International Journal of Production Research
Pages: 5108-5129
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1773562
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1773562
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoli Wang
Author-X-Name-First: Xiaoli
Author-X-Name-Last: Wang
Author-Name: Zhiyong Zhang
Author-X-Name-First: Zhiyong
Author-X-Name-Last: Zhang
Author-Name: Lei Yang
Author-X-Name-First: Lei
Author-X-Name-Last: Yang
Author-Name: Jun Zhao
Author-X-Name-First: Jun
Author-X-Name-Last: Zhao
Title: Price and capacity decisions in a telemedicine service system under government subsidy policy
Abstract: 
 With the development of information and communication technologies, telemedicine has been widely used in different healthcare sectors. In this paper, we study a telemedicine service system consisting of a non-profit general hospital (GH) and a for-profit telemedicine firm (TF). The GH is subsidised by the government, which aims at maximising social welfare. We adopt a mixed duopoly game to obtain the optimal price and capacity decisions of the GH and the TF. The interaction between the GH and the TF is specifically examined. Nash equilibrium strategies of the telemedicine service system are discussed under the government subsidy policy. Results show that the influence between the GH and the TF is unilateral. The service price and capacity decisions of the TF will not affect the capacity decision of the GH. Besides, the government subsidy policy on the GH can improve the total patients' utility in the GH and the profit of the TF, but the impacts become insignificant as the subsidy budget increasing. Numerical experiments further demonstrate that the introduction of telemedicine is effective in reducing patients' waiting times and improving social welfare, especially in rural areas that lack medical resources.
Journal: International Journal of Production Research
Pages: 5130-5143
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1774090
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1774090
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Template-Type: ReDIF-Article 1.0
Author-Name: Young-In Kim
Author-X-Name-First: Young-In
Author-X-Name-Last: Kim
Author-Name: Hyun-Jung Kim
Author-X-Name-First: Hyun-Jung
Author-X-Name-Last: Kim
Title: Rescheduling of unrelated parallel machines with job-dependent setup times under forecasted machine breakdown
Abstract: 
 We address a rescheduling problem of unrelated parallel machines with job-dependent setup times where a machine breakdown is known in advance. Typical rescheduling methods usually re-assign or re-sequence jobs from a given schedule after machines break down. Recently, machine breakdowns can be forecasted with high accuracy before their actual occurrences from IoT sensors or artificial intelligence methods. We therefore define a new rescheduling problem in which jobs are re-assigned before machine breakdowns occur, and propose a mathematical programming model with three objective measures, makespan, stability and penalty cost. We then develop a simulated annealing (SA) algorithm combined with a fuzzy logic controller for adjusting the parameters in SA. We demonstrate the performance of the proposed algorithm with extensive experiments.
Journal: International Journal of Production Research
Pages: 5236-5258
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1775910
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1775910
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:17:p:5236-5258




Template-Type: ReDIF-Article 1.0
Author-Name: Ethem Çanakoğlu
Author-X-Name-First: Ethem
Author-X-Name-Last: Çanakoğlu
Author-Name: İbrahim Muter
Author-X-Name-First: İbrahim
Author-X-Name-Last: Muter
Title: Identical parallel machine scheduling with discrete additional resource and an application in audit scheduling
Abstract: 
 Resource scheduling has been one of the most prominent problems due to its technical challenges and prevalence in real-life. In this paper, we focus on an extension of the parallel machine scheduling problem with additional resources, which can be classified as a static resource-constrained parallel machine scheduling problem with unspecified job-machine assignment. The novelty of the problem we tackle stems from the additional resource that consists of components with discrete levels. The allocation of this resource to machines induces general covering constraints. This distinct characteristic of the additional resource also arises in a real-life audit scheduling problem, in which local branches of a financial firm are to be audited by a set of auditors with different experience levels. The quantification of the auditor experience and the branch experience requirement enable us to model this problem as an extension of the aforementioned scheduling problem with extra constraints related to the auditing process. We propose mathematical models for these problems and two constructive heuristic algorithms. The upper bounds attained by these algorithms are improved by a tabu-search algorithm, and an efficient lower bounding technique is developed for comparative purposes. We conduct extensive computational experiments to assess the performance of the proposed algorithms.
Journal: International Journal of Production Research
Pages: 5321-5336
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1777481
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1777481
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Template-Type: ReDIF-Article 1.0
Author-Name: Yiyong Xiao
Author-X-Name-First: Yiyong
Author-X-Name-Last: Xiao
Author-Name: Yue Zhang
Author-X-Name-First: Yue
Author-X-Name-Last: Zhang
Author-Name: Sadan Kulturel-Konak
Author-X-Name-First: Sadan
Author-X-Name-Last: Kulturel-Konak
Author-Name: Abdullah Konak
Author-X-Name-First: Abdullah
Author-X-Name-Last: Konak
Author-Name: Yuchun Xu
Author-X-Name-First: Yuchun
Author-X-Name-Last: Xu
Author-Name: Shenghan Zhou
Author-X-Name-First: Shenghan
Author-X-Name-Last: Zhou
Title: The aperiodic facility layout problem with time-varying demands and an optimal master-slave solution approach
Abstract: 
 In many seasonal industries, customer demands are constantly changing over time, and accordingly the facility layout should be re-optimized in a timely manner to adapt to changing material handling patterns among manufacturing departments. This paper investigates the aperiodic facility layout problem (AFLP) that involves arranging facilities layout and re-layout aperiodically in a dynamic manufacturing environment during a given planning horizon. The AFLP is decomposed into a master problem and a combination set of static facility layout problems (FLPs, the slave problems) without loss of optimality, and all problems are formulated as mixed-integer linear programming (MILP) models that can be solved by MIP solvers for small-sized problems. An exact backward dynamic programming (BDP) algorithm with a computational complexity of O(n2) is developed for the master problem, and an improved linear programming based problem evolution algorithm (PEA-LP) is developed for the traditional static FLP. Computational experiments are conducted on two new problems and twelve well-known benchmark problems from the literature, and the experimental results show that the proposed solution approach is promising for solving the AFLP with practical sizes of problem instances. In addition, the improved PEA-LP found new best solutions for five benchmark problems.
Journal: International Journal of Production Research
Pages: 5216-5235
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1775909
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1775909
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Template-Type: ReDIF-Article 1.0
Author-Name: Oluwole Olufayo
Author-X-Name-First: Oluwole
Author-X-Name-Last: Olufayo
Author-Name: Victor Songmene
Author-X-Name-First: Victor
Author-X-Name-Last: Songmene
Author-Name: Jean-Pierre Kenné
Author-X-Name-First: Jean-Pierre
Author-X-Name-Last: Kenné
Author-Name: Michael Ayomoh
Author-X-Name-First: Michael
Author-X-Name-Last: Ayomoh
Title: Modelling for cost and productivity optimisation in sustainable manufacturing: a case of dry versus wet machining of mould steels
Abstract: 
 Under certain conditions, dry machining has been known to offer improved efficiency. To determine the effectiveness of dry machining in the production of steel, it is necessary to identify optimal machinability conditions for commonly used mould steel products and their economic aspects. The present study expands on a comparative analysis of dry and wet optimum machinability conditions for universally used industrial mould steels; SF-5, SF-2312, SF-2-000, and SP-300. In this study, the newly developed MICO (Machining Inventory and Cost Optimisation) tool was used to determine the machining related production cost and identify optimal productivity parameters for these mould steels. The MICO analysis presented utilised the established tool wear equations for both dry and wet milling conditions to determine machining costs and productivity. The results of the case study revealed that during dry machining, materials with lower-hardness steels (SF-5 and SF-2312) saw increased productivity and a reduction of total costs with optimal conditions. In wet milling operations, the added use of lubrication increased costs by 5–8% at optimal machining conditions. The overall cost was found to be more sensitive to the influence of lubrication than were the tool usage and inventory costs.
Journal: International Journal of Production Research
Pages: 5352-5371
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1778207
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1778207
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Template-Type: ReDIF-Article 1.0
Author-Name: Abderrahim Ait-Alla
Author-X-Name-First: Abderrahim
Author-X-Name-Last: Ait-Alla
Author-Name: Markus Kreutz
Author-X-Name-First: Markus
Author-X-Name-Last: Kreutz
Author-Name: Daniel Rippel
Author-X-Name-First: Daniel
Author-X-Name-Last: Rippel
Author-Name: Michael Lütjen
Author-X-Name-First: Michael
Author-X-Name-Last: Lütjen
Author-Name: Michael Freitag
Author-X-Name-First: Michael
Author-X-Name-Last: Freitag
Title: Simulated-based methodology for the interface configuration of cyber-physical production systems
Abstract: 
 Besides managing accruing data in production systems, Digital Twins provide additional services like the simulation or control of production systems. The Digital Twin and its real-world physical counterpart need to be interconnected using sensors and actuators to enable such services. This article proposes a simulation-based method to design and evaluate such an interface. Applying concepts from the area of software-in-the-loop, it proposes the use of a so-called Physical Twin: a simulation model which mimics the abilities of the physical system but allows simulation-based experiments to optimise the interface. After presenting the general approach, the article provides an application example of the proposed procedure. A Digital and a Physical Twin are implemented for an application scenario and connected using a simple TCP/IP interface. By varying the number of sensors as well as considering component breakdowns in the Physical Twin, this setup allows evaluating different configurations in terms of production performance. The evaluation confirms that configurations with more sensors result in higher production performance of the system. However, a saturation of the performance gain is also observable when exceeding a certain number of sensors. Therefore, determining the optimal configuration is vital to optimise the interface from a financial point of view.
Journal: International Journal of Production Research
Pages: 5388-5403
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1778209
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1778209
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Template-Type: ReDIF-Article 1.0
Author-Name: Daniel Ramón-Lumbierres
Author-X-Name-First: Daniel
Author-X-Name-Last: Ramón-Lumbierres
Author-Name: F. Javier Heredia Cervera
Author-X-Name-First: F. Javier
Author-X-Name-Last: Heredia Cervera
Author-Name: Joaquim Minguella-Canela
Author-X-Name-First: Joaquim
Author-X-Name-Last: Minguella-Canela
Author-Name: Asier Muguruza-Blanco
Author-X-Name-First: Asier
Author-X-Name-Last: Muguruza-Blanco
Title: Optimal postponement in supply chain network design under uncertainty: an application for additive manufacturing
Abstract: 
 This study presents a new two-stage stochastic programming decision model for assessing how to introduce some new manufacturing technology into any generic supply and distribution chain. It additionally determines the optimal degree of postponement, as represented by the so-called customer order decoupling point (CODP), while assuming uncertainty in demand for multiple products. To this end, we propose here the formulation of a generic supply chain through an oriented graph that represents all the deployable alternative technologies, which are defined through a set of operations that are characterised by lead times and cost parameters. Based on this graph, we develop a mixed integer two-stage stochastic programme that finds the optimal manufacturing technology for meeting each market’s demand, each operation’s optimal production quantity, and each selected technology’s optimal CODP. We also present and analyse a case study for introducing additive manufacturing technologies.
Journal: International Journal of Production Research
Pages: 5198-5215
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1775908
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1775908
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Template-Type: ReDIF-Article 1.0
Author-Name: Abderrahman Abbassi
Author-X-Name-First: Abderrahman
Author-X-Name-Last: Abbassi
Author-Name: Said Kharraja
Author-X-Name-First: Said
Author-X-Name-Last: Kharraja
Author-Name: Ahmed El Hilali Alaoui
Author-X-Name-First: Ahmed
Author-X-Name-Last: El Hilali Alaoui
Author-Name: Jaouad Boukachour
Author-X-Name-First: Jaouad
Author-X-Name-Last: Boukachour
Author-Name: Denis Paras
Author-X-Name-First: Denis
Author-X-Name-Last: Paras
Title: Multi-objective two-echelon location-distribution of non-medical products
Abstract: 
 Distribution of non-medical products is a very interesting problem in healthcare supply chain logistics. It has a considerable impact on profit, especially when products have to be transported firstly from the manufacturing centres to intermediate healthcare facilities then to the final healthcare establishments. This transportation is ensured at two levels by selecting the best intermediate facilities and the best trips. In this paper, we address the two-echelon location-distribution problem and we develop a multi-objective mathematical formulation for minimising two objective functions. The first is the total distribution cost which is the sum of transportation costs, the opening cost of intermediate healthcare facilities and the usage cost of vehicles. The second is the total horizon time of the distribution of products. For solving this new problem, we propose two solution approaches, the multi-objective particle swarm optimisation algorithm improved by variable neighbourhood search heuristics and the non-dominated sorting genetic algorithm combined also with the same heuristics. They are tested on thirty problems and compared with different related works. Moreover, a real case study of non-medical products distribution is studied. The validation and efficiency of the algorithms are based on several performance metrics which are presented later.
Journal: International Journal of Production Research
Pages: 5284-5300
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1777479
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1777479
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Template-Type: ReDIF-Article 1.0
Author-Name: Fei Wang
Author-X-Name-First: Fei
Author-X-Name-Last: Wang
Author-Name: Yuanjun Laili
Author-X-Name-First: Yuanjun
Author-X-Name-Last: Laili
Author-Name: Lin Zhang
Author-X-Name-First: Lin
Author-X-Name-Last: Zhang
Title: A many-objective memetic algorithm for correlation-aware service composition in cloud manufacturing
Abstract: 
 Service composition is a core issue of cloud manufacturing (CMfg) to integrate distributed manufacturing services for customised manufacturing tasks. Existing studies focus on the quality of service (QoS) in composition by assuming that each service is independent with each other. However, the correlation between services determines whether a composition is feasible in practice and is a primary factor of its QoS. This paper considers two typical correlations, composability-oriented correlation and quality-oriented correlation. The composability-oriented correlation is modelled as a group of constraints to decide whether a solution is feasible. The influence of the quality-oriented correlation between two services on the overall QoS of a composition is quantified by a discount percentage based on their correlation degrees. A mathematical model of correlation-aware service composition is then established. To solve this problem, a many-objective memetic algorithm termed HypE-C (Hypervolume Estimation Algorithm for Multiobjective Optimisation involving Correlation) is designed. Three correlation-based local search strategies are established in the frame of HypE (Hypervolume Estimation Algorithm for Multiobjective Optimisation) to achieve better trade-off among multiple conflicting QoS criteria. Experiments demonstrate the effectiveness of the proposed algorithm HypE-C compared with five many-objective algorithms on eliminating infeasible search space and providing high QoS service composition solutions.
Journal: International Journal of Production Research
Pages: 5179-5197
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1774678
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1774678
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Template-Type: ReDIF-Article 1.0
Author-Name: Dariush Tavaghof-Gigloo
Author-X-Name-First: Dariush
Author-X-Name-Last: Tavaghof-Gigloo
Author-Name: Stefan Minner
Author-X-Name-First: Stefan
Author-X-Name-Last: Minner
Title: Planning approaches for stochastic capacitated lot-sizing with service level constraints
Abstract: 
 We investigate a stochastic capacitated lot-sizing problem whose optimal solution requires the integration of dynamic safety stock planning into lot-sizing. Then, we introduce an integrated mixed-integer linear program with service-level constraints. The integrated model endogenously sets dynamic safety stocks over replenishment cycles of different lengths determined by the model. Since there is limited capacity, soft service-level constraints are introduced to guarantee a feasible solution. In the experimental study, we compare the performance of the integrated model to the stochastic dynamic program and the widely-used sequential approach. If available capacity increases, the integrated model closes the gap to the lower bound approximated by using a stochastic dynamic program. If capacity is limited, the integrated model outperforms the sequential approach because it yields identical service levels with lower inventories. However, in the case of sufficient flexibility (capacity), we identify a major shortcoming of the integrated models: They can generate excessive safety stock if the re-planning opportunities under rolling horizon planning are ignored. To overcome this problem, we extend the integrated model to account for those re-planning opportunities.
Journal: International Journal of Production Research
Pages: 5087-5107
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1773003
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1773003
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:17:p:5087-5107




Template-Type: ReDIF-Article 1.0
Author-Name: Hiroki Sano
Author-X-Name-First: Hiroki
Author-X-Name-Last: Sano
Author-Name: Kazuo Yamada
Author-X-Name-First: Kazuo
Author-X-Name-Last: Yamada
Title: Prediction accuracy of sales surprise for inventory turnover
Abstract: 
 Sales surprise, the ratio of actual sales to forecasted sales for a year, is a key determinant of firms’ inventory turnover. While the previous literature on empirical inventory management frequently uses Holt's double exponential smoothing method for obtaining future sales forecasts, this method suffers from measurement error. In contrast, we directly use the data on management forecasts publicised by listed companies in manufacturing and retail industries for the fiscal years 1997 through 2014, which are available in Japan, and evaluate the adequacy of the exponential smoothing sales forecasts. Our analysis reveals that sales surprise measured via both means positively relates to inventory turnover in the majority of industries, consistent with previous literature; however, the two variables imply discrepancies, particularly when economic conditions change.
Journal: International Journal of Production Research
Pages: 5337-5351
Issue: 17
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1778205
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1778205
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:17:p:5337-5351




Template-Type: ReDIF-Article 1.0
Author-Name: Jun Kim
Author-X-Name-First: Jun
Author-X-Name-Last: Kim
Author-Name: Hyun-Jung Kim
Author-X-Name-First: Hyun-Jung
Author-X-Name-Last: Kim
Title: Parallel machine scheduling with multiple processing alternatives and sequence-dependent setup times
Abstract: 
 This paper examines a parallel machine scheduling problem in which jobs can be processed either in multiple parts or in a complete form and the number of possible job splitting alternatives of jobs is more than one. There are sequence-dependent setup times between different jobs (or parts), and the objective is to minimise makespan by choosing an appropriate processing alternative for each job, assigning parts (or jobs) to machines, and determining the sequence of parts on the machines. This work is motivated from a 3D printer-based manufacturing system that produces customised products for individuals or start-up companies. When 3D printers are used as processing machines, a product can be printed in diverse forms composed of different parts. To address the problem, we first propose a mixed integer programming model and then develop a hybrid genetic algorithm which is combined with a travelling salesman problem-based heuristic algorithm. The experimental results show that the average gap between a solution from the proposed algorithm and an optimal one solved with CPLEX or a lower bound is very small. The paired t-test shows that there is a significant improvement for processing jobs with multiple alternatives.
Journal: International Journal of Production Research
Pages: 5438-5453
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1781278
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1781278
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Template-Type: ReDIF-Article 1.0
Author-Name: Munira Mohd Ali
Author-X-Name-First: Munira
Author-X-Name-Last: Mohd Ali
Author-Name: Ruoyu Yang
Author-X-Name-First: Ruoyu
Author-X-Name-Last: Yang
Author-Name: Binbin Zhang
Author-X-Name-First: Binbin
Author-X-Name-Last: Zhang
Author-Name: Francesco Furini
Author-X-Name-First: Francesco
Author-X-Name-Last: Furini
Author-Name: Rahul Rai
Author-X-Name-First: Rahul
Author-X-Name-Last: Rai
Author-Name: J. Neil Otte
Author-X-Name-First: J. Neil
Author-X-Name-Last: Otte
Author-Name: Barry Smith
Author-X-Name-First: Barry
Author-X-Name-Last: Smith
Title: Enriching the functionally graded materials (FGM) ontology for digital manufacturing
Abstract: 
 Functionally graded materials (FGMs) have been used in many different kinds of applications in recent years and have attracted significant research attention. However, we do not yet have a commonly accepted way of representing the various aspects of FGMs. Lack of standardised vocabulary creates obstacles to the extraction of useful information relating to pertinent aspects of different applications. A standard resource is needed for describing various elements of FGMs, including existing applications, manufacturing techniques, and material characteristics. This motivated the creation of the FGM Ontology (FGMO) in 2016. Here, we present a revised and expanded version of the FGM Ontology, which includes enrichments along four dimensions: (1) documenting recent FGMs applications; (2) reorganising the framework to incorporate an updated representation of types of manufacturing processes; (3) enriching the axioms of the ontology; and (4) importing mid-level ontologies from the Common Core Ontologies (CCO) and Product Life Cycle (PLC) Ontologies. The work is being carried out within the framework of the Industry Ontology Foundry (IOF), and the ontology is conformant to Basic Formal Ontology (BFO).
Journal: International Journal of Production Research
Pages: 5540-5557
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1787534
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1787534
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Template-Type: ReDIF-Article 1.0
Author-Name: R. Ghasemy Yaghin
Author-X-Name-First: R.
Author-X-Name-Last: Ghasemy Yaghin
Author-Name: M Goh
Author-X-Name-First: M
Author-X-Name-Last: Goh
Title: Procurement, production, and price planning under visibility and risk: a generalised Benders decomposition method
Abstract: 
 This paper addresses the aggregate production, procurement, and pricing planning problem of a supply chain network involving suppliers, manufacturer, and retailers in a multi-product and multi-period environment, with supply chain risk and visibility considerations. A supply chain product visibility index comprising multiple attributes is developed to capture the features of information sharing. We formulate the problem as a non-convex mixed integer programme and tailor a generalised Benders decomposition for solution. Computational experiments are conducted to validate the proposed approach.
Journal: International Journal of Production Research
Pages: 5626-5646
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1788735
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1788735
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Template-Type: ReDIF-Article 1.0
Author-Name: Cuiwen Cao
Author-X-Name-First: Cuiwen
Author-X-Name-Last: Cao
Author-Name: Yao Zhang
Author-X-Name-First: Yao
Author-X-Name-Last: Zhang
Author-Name: Xingsheng Gu
Author-X-Name-First: Xingsheng
Author-X-Name-Last: Gu
Author-Name: Dan Li
Author-X-Name-First: Dan
Author-X-Name-Last: Li
Author-Name: Jie Li
Author-X-Name-First: Jie
Author-X-Name-Last: Li
Title: An improved gravitational search algorithm to the hybrid flowshop with unrelated parallel machines scheduling problem
Abstract: 
 The hybrid ﬂowshop scheduling problem with unrelated parallel machines exists in many industrial manufacturers, which is an NP-hard combinatorial optimisation problem. To solve this problem more effectively, an improved gravitational search (IGS) algorithm is proposed which combines three strategies: generate new individuals using the mutation strategy of the standard differential evolution (DE) algorithm and preserve the optimal solution via a greedy strategy; substitute the exponential gravitational constant of the standard gravitational search (GS) algorithm with a linear function; improve the velocity update formula of the standard GS algorithm by mixing an adaptive weight and the global search strategy of the standard particle swarm optimisation (PSO) algorithm. Benchmark examples are solved to demonstrate the proposed IGS algorithm is superior to the standard genetic algorithm, DE, GS, DE with local search, estimation of distribution algorithm and artificial bee colony algorithms. Two more examples from a real-world water-meter manufacturing enterprise are effectively solved.
Journal: International Journal of Production Research
Pages: 5592-5608
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1788732
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1788732
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingcao Cai
Author-X-Name-First: Jingcao
Author-X-Name-Last: Cai
Author-Name: Deming Lei
Author-X-Name-First: Deming
Author-X-Name-Last: Lei
Author-Name: Ming Li
Author-X-Name-First: Ming
Author-X-Name-Last: Li
Title: A shuffled frog-leaping algorithm with memeplex quality for bi-objective distributed scheduling in hybrid flow shop
Abstract: 
 Hybrid flow shop scheduling problem has been extensively considered in single factory; however, distributed hybrid flow shop scheduling problem (DHFSP) is seldom investigated in multiple factories and should be studied fully with the applications of distributed manufacturing. In this study, DHFSP with sequence-dependent setup times is considered, in which factory assignment and machine assignment of first stage are integrated together. A new shuffled frog-leaping algorithm with memeplex quality (MQSFLA) is proposed to minimise total tardiness and makespan simultaneously. Solution quality of memeplex is measured and new search process is implemented according to solution quality. Evolution quality is evaluated for each memeplex and adopted for dynamically selecting memeplexes in a novel memeplex shuffling. A number of experiments are conducted to test the new strategies and performances of MQSFLA. The computational results demonstrate the effectiveness of the new strategies and the promising advantages of MQSFLA.
Journal: International Journal of Production Research
Pages: 5404-5421
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1780333
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1780333
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Template-Type: ReDIF-Article 1.0
Author-Name: Jing Zhang
Author-X-Name-First: Jing
Author-X-Name-Last: Zhang
Author-Name: Zi-You Gao
Author-X-Name-First: Zi-You
Author-X-Name-Last: Gao
Author-Name: Yu-Gang Yu
Author-X-Name-First: Yu-Gang
Author-X-Name-Last: Yu
Author-Name: Tao Wang
Author-X-Name-First: Tao
Author-X-Name-Last: Wang
Title: Travel time model for a tower-based automated parking system
Abstract: 
 This paper aims to investigate a tower-based automated parking system, with the appearance of a cylinder. The tower crane can simultaneously implement two types of movement: (1) ascending/descending in the vertical direction and (2) rotating counter clockwise/clockwise. The shuttle can move along the diameter to the opposite parking slot. Using the characteristics of the device, we first deduce a travel time model of the system. Then, we obtain the optimal system sizes by solving the model. We further discuss minimising the maximum travel time and the dwelling point of the crane. Finally, sensitivity analyses are also conducted, in order to demonstrate the optimal value of the proposed system. We have varied the height (in time unit) for a fixed area of the system and found that, when the system configuration deviates from the optimal value, the travel time of the parking system increases greatly. We also investigate how and to what degree the different ratio of the parameters affects the expected travel time of a tower-based system. In addition, we investigate the influence of different system configurations (in the light of travel time and footprint) on system performance. The corresponding analysis results can provide the designer the required system size.
Journal: International Journal of Production Research
Pages: 5422-5437
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1780334
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1780334
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Template-Type: ReDIF-Article 1.0
Author-Name: Limeng Chai
Author-X-Name-First: Limeng
Author-X-Name-Last: Chai
Author-Name: Desheng Dash Wu
Author-X-Name-First: Desheng Dash
Author-X-Name-Last: Wu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Yongrui Duan
Author-X-Name-First: Yongrui
Author-X-Name-Last: Duan
Title: Pricing strategy for B&M store in a dual-channel supply chain based on hotelling model
Abstract: 
 We use hotelling model to analyse store brands as a strategy for B&M (brick-and-mortar) retailers to combat showrooming. We investigate how national-brand product mismatch and store-brand awareness affect supply chain’s performance. We reach four major conclusions. First, store-brand strategy may be an effective means for B&M stores to mitigate showrooming. However, it’s better to introduce premium store brands. Second, the B&M store’s profit grows – and the online store’s profit declines – as national-brand product mismatch increases in breadth. When many consumers feel the national-brand product does not match their needs, a product positioning strategy for the store brand can help B&M retailers improve profit margins. Third, as national-brand product mismatch increases in depth, the B&M store’s profit rises and online store’s profit falls. If national-brand products lack many features that consumers need, a product differentiation strategy can be implemented to use store brands to fill in the gaps left by national brands. Finally, the growth of store-brand awareness will not necessarily benefit the B&M store. The impact of store-brand awareness on the B&M store’s profit depends on the hassle cost factor t, and a brand promotion strategy will reduce the loss of B&M retailer’s profit.
Journal: International Journal of Production Research
Pages: 5578-5591
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1787536
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1787536
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Template-Type: ReDIF-Article 1.0
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Author-Name: Wenli Cui
Author-X-Name-First: Wenli
Author-X-Name-Last: Cui
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Jianbo Yu
Author-X-Name-First: Jianbo
Author-X-Name-Last: Yu
Title: The interval min–max regret knapsack packing-delivery problem
Abstract: 
 This paper studies an interval data min–max regret (IDMR) version of the packing-delivery problem, in which a 0-1 knapsack problem is for parcel packing and a capacitated travelling salesman problem is for parcel delivery. The parcel profits for the courier and the tour costs are uncertain and they can take any value from a specific interval with lower and upper bound values. The problem is how to select and deliver a subset of parcels to minimise the maximum regret of net profit which is the difference between the total profits of the selected parcels and the total delivery costs, to deal with the trade-off of the solution robustness and performance. To tackle the problem effectively, we first prove the worst-case scenario of a solution to the problem, based on which, a mixed integer linear programming is formulated. A Benders-like decomposition algorithm is then developed to solve small-scale problems to optimality within the manageable computation time. For medium- and large-scale problems, a simulated-annealing-based heuristic method with a local search procedure is designed. Extensive computational experiments show the efficiency and effectiveness of the proposed methods.
Journal: International Journal of Production Research
Pages: 5661-5677
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1789235
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1789235
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Template-Type: ReDIF-Article 1.0
Author-Name: Ankita Ray
Author-X-Name-First: Ankita
Author-X-Name-Last: Ray
Author-Name: Arijit De
Author-X-Name-First: Arijit
Author-X-Name-Last: De
Author-Name: Sandeep Mondal
Author-X-Name-First: Sandeep
Author-X-Name-Last: Mondal
Author-Name: Junwei Wang
Author-X-Name-First: Junwei
Author-X-Name-Last: Wang
Title: Selection of best buyback strategy for original equipment manufacturer and independent remanufacturer – game theoretic approach
Abstract: 
 The study considers two supply chain members, an original equipment manufacturer (OEM) producing new and remanufactured products and an independent remanufacturer (IR) collecting used products of OEM and producing remanufactured products. Furthermore, OEM and IR are involved in competition to collect the used products by providing various exciting offers to the customers. A two period analytical model is developed to investigate the profitable buyback strategy for OEM and IR under low and high pricing strategy. In first period, OEM performs remanufacturing and considers a strategy to collect the product cores from end users under a certain pricing strategy. Under extensive game format, IR joins in the remanufacturing business to compete with OEM and based on OEM's attractive buyback strategy, IR adopts a profitable pricing strategy. The research addresses oligopoly market where OEM is not the single seller of new product and other sellers are interested in remanufacturing. In such scenario, OEM has less control over used products collection of other brand and OEM cannot restrict independent remanufacturer to venture within remanufacturing business. The findings of the study depicted that low pricing strategy “exchange offer” is profitable buyback decision for OEM and “incentive offer” is profitable buyback decision for independent remanufacturer.
Journal: International Journal of Production Research
Pages: 5495-5524
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1784486
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1784486
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Template-Type: ReDIF-Article 1.0
Author-Name: Sinan Obaidat
Author-X-Name-First: Sinan
Author-X-Name-Last: Obaidat
Author-Name: Haitao Liao
Author-X-Name-First: Haitao
Author-X-Name-Last: Liao
Title: Integrated decision making for attributes sampling and proactive maintenance in a discrete manufacturing system
Abstract: 
 An integrated optimal design of attributes sampling and proactive maintenance for a discrete manufacturing system is studied in this paper. In the system, the failure of a critical component causes the process to shift. The new mathematical model for online sampling of the discrete manufacturing system is based on the binomial and truncated negative binomial distributions. In addition to performing scheduled maintenance and unscheduled corrective maintenance at the time of a true alarm, an additional maintenance opportunity when a false alarm occurs is also considered. The optimal scheduled maintenance time and sampling parameters are determined by solving a mixed integer nonlinear programming problem to minimise the long-run cost rate. A numerical example is provided to illustrate the proposed integrated attributes sampling and maintenance plan. The results show that the integrated approach outperforms the alternatives that consider different models separately. More importantly, showing the benefit of doing maintenance upon a false alarm provides a stakeholder with a new idea in managing a deteriorating manufacturing system.
Journal: International Journal of Production Research
Pages: 5454-5476
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1781280
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1781280
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:18:p:5454-5476




Template-Type: ReDIF-Article 1.0
Author-Name: Yupeng Li
Author-X-Name-First: Yupeng
Author-X-Name-Last: Li
Author-Name: Yu Wang
Author-X-Name-First: Yu
Author-X-Name-Last: Wang
Author-Name: Nailiang Li
Author-X-Name-First: Nailiang
Author-X-Name-Last: Li
Title: Abnormal operation status identification in warehousing based on neighborhood information entropy considering mixed-valued attributes
Abstract: 
 A warehousing system is critical to enterprises, as a connection between supply and demand in a supply chain. However, an abnormal operation status (AS) may appear in actual production operations, especially in a developing warehousing system. In this study, to identify an AS in a warehousing system, mixed-valued attributes are used to describe the warehousing operation status, and an integration method is performed based on neighbourhood information entropy. First, the neighbourhood information system is structured. A distance function and neighbourhood radius are defined for numeric data and categorical data, respectively, to eliminate information loss from transforming different types of attributes. Second, the relative neighbourhood information entropy, abnormal degree, and abnormal factor are gradually defined. Third, an evaluation index is defined to measure the identification accuracy in parameter adjustment for two key parameters: the adjustment parameter for the neighbourhood radius (λ), and the discrimination threshold for AS (μ). Finally, a real case study of AS identification in a manufacturing enterprise is implemented to demonstrate the effectiveness of the proposed method, and the identification results are analysed from the practical point of view.
Journal: International Journal of Production Research
Pages: 5647-5660
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1788736
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1788736
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Template-Type: ReDIF-Article 1.0
Author-Name: Patrik Fager
Author-X-Name-First: Patrik
Author-X-Name-Last: Fager
Author-Name: Robin Hanson
Author-X-Name-First: Robin
Author-X-Name-Last: Hanson
Author-Name: Lars Medbo
Author-X-Name-First: Lars
Author-X-Name-Last: Medbo
Author-Name: Mats I. Johansson
Author-X-Name-First: Mats I.
Author-X-Name-Last: Johansson
Title: Links between kit quality and kit preparation design
Abstract: 
 Kitting is a materials-feeding principle commonly used with mixed-model assembly, but literature is lacking with respect to how kit quality can be supported. The purpose of this paper is to create an understanding of the links between kit preparation design aspects and kit preparation error types, that can be useful to support kit quality. The paper draws on empirical data from a multiple case study in the automotive industry to study how typical kit errors are linked to eight kit preparation design aspects: location, work organisation, storage policy, batching policy, storage packaging, kit carrier and container, picking information system, and error communication. The findings suggest several opportunities related to kit preparation design aspects for preventing kit errors and facilitating kit error corrections. The paper extends earlier knowledge and can support kit quality of industrial kit preparation.
Journal: International Journal of Production Research
Pages: 5525-5539
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1785035
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1785035
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Template-Type: ReDIF-Article 1.0
Author-Name: Jian Chen
Author-X-Name-First: Jian
Author-X-Name-Last: Chen
Author-Name: Jun-Qiang Wang
Author-X-Name-First: Jun-Qiang
Author-X-Name-Last: Wang
Author-Name: Xiang-Yang Du
Author-X-Name-First: Xiang-Yang
Author-X-Name-Last: Du
Title: Shifting bottleneck-driven TOCh for solving product mix problems
Abstract: 
 Product mix optimisation is one of the most important strategic decisions determining the product type and the corresponding quantity to maximise the system throughput. This paper proposes a new heuristic named shifting bottleneck-driven TOC heuristic (STOCh) for solving product mix problems with multiple bottleneck resources. STOCh is comprised of master product schedule (MPS) generation and its local adjustment. The major improvement is that STOCh dynamically identifies and utilises shifting bottlenecks, rather than fixed bottlenecks commonly used in the existing literature, to avoid being caught in a local optimum. Besides, local adjustment strategy can refine neighbourhood space and limit the search in a high-quality solution space to gain better solutions. Numerical studies show that STOCh outperforms three most famous TOC heuristics in the existing literature, i.e. RTOCh, TOC_AK and TOC_SN. The average relative deviation of the solutions by STOCh from the optimal solutions by CPLEX is only around 3%. Further results show that STOCh performs particularly well when facing multiple bottleneck scenarios, especially when the capacity of bottleneck resource is very scarce. A case study based on real data from a SME in China demonstrates the effectiveness of the proposed STOCh.
Journal: International Journal of Production Research
Pages: 5558-5577
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1787535
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1787535
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Template-Type: ReDIF-Article 1.0
Author-Name: Jing Guo
Author-X-Name-First: Jing
Author-X-Name-Last: Guo
Author-Name: Qingjin Peng
Author-X-Name-First: Qingjin
Author-X-Name-Last: Peng
Author-Name: Liyan Zhang
Author-X-Name-First: Liyan
Author-X-Name-Last: Zhang
Author-Name: Runhua Tan
Author-X-Name-First: Runhua
Author-X-Name-Last: Tan
Author-Name: Jianyu Zhang
Author-X-Name-First: Jianyu
Author-X-Name-Last: Zhang
Title: Estimation of product success potential using product value
Abstract: 
 New product development (NPD) provides an opportunity for companies in the market, but there is a risk of failure if the product cannot satisfy customers. It is therefore important to estimate the success potential of a new product during NPD. According to the product value used in Value Engineering (VE) and product ideality in TRIZ (a Russian acronym for Theory of Inventive Problem Solving), this paper proposes a new structure of product value for NPD. Key factors that affect product value are identified. Methods are proposed to measure changes in the product value comparing a new product with existing products. The analysis of changes in the product value is a way to estimate new products’ success potential, which helps companies make decisions on whether a design should go for production. Four gas cooktop products are used to verify the feasibility and effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 5609-5625
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1788733
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1788733
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Template-Type: ReDIF-Article 1.0
Author-Name: Mahmure Övül Arıoğlu
Author-X-Name-First: Mahmure Övül
Author-X-Name-Last: Arıoğlu
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Author-Name: Dileep G. Dhavale
Author-X-Name-First: Dileep G.
Author-X-Name-Last: Dhavale
Title: Selection of suppliers using Bayesian estimators: a case of concrete ring suppliers to Eurasia Tunnel of Turkey
Abstract: 
 This work introduces a methodology to evaluate, rank, and select suppliers for an organisation managing a large and complex construction project. The company’s procedure to complete a supplier evaluation is conflated with other supplier features such as product type and complexity, delivery characteristics and requirements, and geographic location of the project. The introduced model segregates the effects of each feature and then aids supplier selection on various criteria without the confounding effects. Model parameters are determined using Bayesian estimators allowing for information integration from prior periods. The estimation approach provides rich model parameter data, allowing for use in additional analysis. This work advances the research in supplier selection by illustrating a practical forecasting and predictive technique for supplier selection. One result is that the separability of factors in a multiple criteria decision environment can prove valuable for managers to help decipher and isolate factors in a complex decision environment. The technique is feasible for smaller problem sets and provides a robust solution. Past performance and future performance potential are both considered. Analysis and future research directions allow for further development.
Journal: International Journal of Production Research
Pages: 5678-5689
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1789236
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1789236
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:18:p:5678-5689




Template-Type: ReDIF-Article 1.0
Author-Name: Haibo Wang
Author-X-Name-First: Haibo
Author-X-Name-Last: Wang
Author-Name: Bahram Alidaee
Author-X-Name-First: Bahram
Author-X-Name-Last: Alidaee
Author-Name: Jaime Ortiz
Author-X-Name-First: Jaime
Author-X-Name-Last: Ortiz
Author-Name: Wei Wang
Author-X-Name-First: Wei
Author-X-Name-Last: Wang
Title: The multi-skilled multi-period workforce assignment problem
Abstract: 
 Seasonal business operations hire workers depending on environmental conditions and market prices. For example, during the growing and harvest seasons, agricultural businesses employ multiple workers to perform activities such as tilling soil, sowing seed, spreading fertiliser, spraying pesticides, removing weeds, and threshing crops. This study proposes two mixed-integer programming (MIP) models with an effective heuristic to solve the problem of simultaneously assigning multiple multi-skilled workers to the numerous tasks that require different skill sets during single-and multiple-period operations. The multi-skilled workforce management (MSWM) problem is NP hard in the strong sense, and it seems unlikely that large-sized realistic instances could be solved efficiently by exact algorithms directly except for some instances with very sparse tasks and skill sets. Thus, this study presents a heuristic algorithm using k-Opt as a diversification strategy embedded within the Tabu search for this complex problem. To assess the solution quality of the k-Opt heuristic, we solved two sets of instances with different sizes by running the exact solver Gurobi and the proposed heuristic algorithm with a single processor as well as running Gurobi with multiple processors. This heuristic is applicable to other multitasking situations where many workers with multiple capabilities are deployed.
Journal: International Journal of Production Research
Pages: 5477-5494
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1783009
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1783009
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Template-Type: ReDIF-Article 1.0
Author-Name: Fusheng Liang
Author-X-Name-First: Fusheng
Author-X-Name-Last: Liang
Author-Name: Chengwei Kang
Author-X-Name-First: Chengwei
Author-X-Name-Last: Kang
Author-Name: Fengzhou Fang
Author-X-Name-First: Fengzhou
Author-X-Name-Last: Fang
Title: A review on tool orientation planning in multi-axis machining
Abstract: 
 Tool path planning is critical to fully realise the producing capabilities of multi-axis machine tools and improve the precision and efficiency in multi-axis machining. Up to now, more than 400 articles have been published for tool path planning of multi-axis machine tools. Among them, most of the articles mainly focus on the topology of tool path while few studies are conducted for planning of tool orientation. Moreover, the factors that affect the planning of tool orientation are derived from multiple aspects, such as interference, collision and cutting strip width, which poses great challenges on tool orientation planning. To generate a time-optimal tool path with high machining precision, there is an urgent need to ascertain the influences of tool orientation arrangement on the multi-axis machining process. Therefore, in this work, a literature review on tool orientation planning of multi-axis machine tools is implemented. The main factors that influence the planning of tool orientations are systematically summarised, and the advantages and disadvantages of the corresponding methods related to these factors are discussed. Some research issues and challenges encountered in the tool orientation planning are identified. Furthermore, the methodologies that have potential to address the research issues in the future are prospected.
Journal: International Journal of Production Research
Pages: 5690-5720
Issue: 18
Volume: 59
Year: 2021
Month: 09
X-DOI: 10.1080/00207543.2020.1786187
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1786187
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoyan Qian
Author-X-Name-First: Xiaoyan
Author-X-Name-Last: Qian
Author-Name: Tava Lennon Olsen
Author-X-Name-First: Tava Lennon
Author-X-Name-Last: Olsen
Title: Financial and risk management in agricultural cooperatives with application to the milk industry in New Zealand
Abstract: 
 This paper studies the financial and risk management specific to agricultural cooperatives (co-ops). In order to acquire the necessary risk capital to implement competitive strategies, like value-added processing, many agricultural co-ops are adopting capital structure innovations. Fonterra, a leading and dominant company in the New Zealand dairy industry, is one such typical case. We propose a Markov decision process (MDP) model for Fonterra to make better decisions, taking into account uncertain information on milk supply, share price, milk price and farmers' investment behaviour.The objectives are to maximise equity holders' returns over time and also to minimise financial risks. Themodel is solved through an approximate dynamic programming algorithm. We also investigate the efficiency of several risk management policies through numerical experiments. The results reflect the trade-offs involved in the financial decisions, show the importance of designing effective risk management policies and yield some suggestions to mitigate financial risk.
Journal: International Journal of Production Research
Pages: 5913-5943
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1797204
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1797204
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Template-Type: ReDIF-Article 1.0
Author-Name: B. Mihoubi
Author-X-Name-First: B.
Author-X-Name-Last: Mihoubi
Author-Name: B. Bouzouia
Author-X-Name-First: B.
Author-X-Name-Last: Bouzouia
Author-Name: M. Gaham
Author-X-Name-First: M.
Author-X-Name-Last: Gaham
Title: Reactive scheduling approach for solving a realistic flexible job shop scheduling problem
Abstract: 
 Reactive Scheduling (RS) and the realistic Flexible Job Shop Scheduling Problem (FJSSP) are of major importance for the implementation of real-world manufacturing systems. The present study proposes a scheduling rules-based surrogate assisted simulation-optimisation approach for solving a combinatorial optimisation problem related to a realistic FJSSP. The proposed approach aims to capture the dynamic nature of the FJSSP and to balance both short-term reactivity facing repetitive perturbations and the overall performance of manufacturing systems. Besides and to enhance the optimisation process, a GA-based computational procedure allows managing the use of a hybrid neuronal surrogate and DES model for the accurate and fast calculation of the fitness function, considering the Makespan minimisation criterion and dealing with rush orders. The approach is applied to a highly automated Flexible robotised Manufacturing System (FMS) integrating different realistic and representative constraints to the classical FJSSP. Computational simulations and comparisons demonstrate that the proposed approach shows competitive performances compared to other resolution models, considering obtained solutions quality and short-term reactivity. The proposed resolution model provides technical tools for future control systems and allows for the practical implementation of customised assembly systems in Industry 4.0, relying on innovative emerging technologies.
Journal: International Journal of Production Research
Pages: 5790-5808
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1790686
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1790686
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Template-Type: ReDIF-Article 1.0
Author-Name: Feng Ma
Author-X-Name-First: Feng
Author-X-Name-Last: Ma
Author-Name: Hua Zhang
Author-X-Name-First: Hua
Author-X-Name-Last: Zhang
Author-Name: Qingshan Gong
Author-X-Name-First: Qingshan
Author-X-Name-Last: Gong
Author-Name: K. K. B. Hon
Author-X-Name-First: K. K. B.
Author-X-Name-Last: Hon
Title: A novel energy efficiency grade evaluation approach for machining systems based on inherent energy efficiency
Abstract: 
 Characterising the energy efficiency grades of machining systems (MS) is an effective analytical methodology or management tool that helps to establish the high energy-efficient MS. However, the current MS energy efficiency approaches still lack scientific and practical formulation strategies to addresses this issue due to its multi-source and variable energy consumption characteristics. Focusing on this challenge, a new concept of inherent energy efficiency (IEE), which is formed in the design and formation phases of the MS, is proposed. Meanwhile, a novel energy efficiency grade evaluation (EEGE) approach based on IEE is also presented. The proposed EEGE approach not only can evaluate the MS energy efficiency grades, but also can reveal the MS high energy-efficient intervals. According to the analysis of IEE in MS, the EEGE approach is developed in three steps: (i) the establishment of IEE evaluating indicator system from both inherent energy utilisation (IEU) and inherent specific energy (ISE), (ii) the acquisition of the IEE, and (iii) the development of a quantitative method for the EEGE in MS. Finally, a case study of energy efficiency grade evaluation and analysis for an XK714D CNC milling machining centre is examined, illustrating the practicability of the proposed method.
Journal: International Journal of Production Research
Pages: 6022-6033
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1799104
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1799104
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Template-Type: ReDIF-Article 1.0
Author-Name: Chang Fang
Author-X-Name-First: Chang
Author-X-Name-Last: Fang
Author-Name: Xiuyan Ma
Author-X-Name-First: Xiuyan
Author-X-Name-Last: Ma
Author-Name: Jin Zhang
Author-X-Name-First: Jin
Author-X-Name-Last: Zhang
Author-Name: Xide Zhu
Author-X-Name-First: Xide
Author-X-Name-Last: Zhu
Title: Personality information sharing in supply chain systems for innovative products in the circular economy era
Abstract: 
 This research explores the value of personality information sharing in a two-tier supply chain of innovative products that have a short life cycle and no pollution to the environment. We analyse the behaviour of supply chain participants with one-shot decision theory and present an analysis of wholesale pricing for these products. We introduce the retailer's personality information sharing into our models and show the importance of personality information sharing in the wholesale price contract of the supply chain system. Theoretical analysis gains managerial insights into the strategic selection of the manufacturer when facing retailers with different personalities.
Journal: International Journal of Production Research
Pages: 5992-6001
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1798032
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1798032
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Template-Type: ReDIF-Article 1.0
Author-Name: Philipp Neuner
Author-X-Name-First: Philipp
Author-X-Name-Last: Neuner
Author-Name: Stefan Haeussler
Author-X-Name-First: Stefan
Author-X-Name-Last: Haeussler
Title: Rule based workload control in semiconductor manufacturing revisited
Abstract: 
 An essential task in manufacturing planning and control is to determine when to release orders to the shop floor. A prominent approach is the workload control (WLC) concept which originated from the idea of controlling flow times by controlling order releases. Despite recent advances in rule based WLC models, the recent semiconductor literature has neglected them, although it has been shown that they outperform most other periodic and continuous order release models. Therefore, we adapt the most successful rule based WLC model, the LUMS-COR approach and compare it with two approaches from the semiconductor manufacturing literature: Starvation Avoidance (SA) and ConLOAD approach. We include three pool sequencing rules, namely First-Come First-Served (FCFS), Earliest Due Date (EDD) and Critical Ratio (CR). We analyse their performance using a simulation model of a scaled-down wafer fabrication facility. The results show that, in comparison to the other two order release approaches, the LUMS-COR model yields lower total costs due to a more balanced shop and better timing performance which is robust across different settings. This suggests that the adapted LUMS-COR model has high potential to become a viable alternative to the rule based order release mechanisms used in semiconductor industry to date.
Journal: International Journal of Production Research
Pages: 5972-5991
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1797208
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1797208
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Template-Type: ReDIF-Article 1.0
Author-Name: Abhishek Shinde
Author-X-Name-First: Abhishek
Author-X-Name-Last: Shinde
Author-Name: Peeyush Mehta
Author-X-Name-First: Peeyush
Author-X-Name-Last: Mehta
Author-Name: R. K. Amit
Author-X-Name-First: R. K.
Author-X-Name-Last: Amit
Title: An experimental investigation of newsvendor decisions under ambiguity
Abstract: 
 The literature on decision biases in the newsvendor model assumes classical version of the problem where the distribution of random demand is known. This context is decision-making under risk. In many real-life settings, firms are not able to elicit complete and exact information about the demand distribution. This results in decision-making under ambiguity. We examine the newsvendor ordering preferences under ambiguity. Our study is the first attempt in behavioural operations management research to examine the biases in newsvendor decisions under ambiguity. We design experiments to understand the ordering preferences under ambiguity and risk. The experimental results show that subjects deviate from the normative benchmarks. We observe ‘pull-to-center’ bias in newsvendor decisions under ambiguity. We also observe that subjects exhibit ‘asymmetry in ordering’. Both these biases have significant implications for both theory and practice. Our research is a building block for research in a variety of normative models in operations management literature where ambiguity in demand is a highly relevant context for decision-making.
Journal: International Journal of Production Research
Pages: 5960-5971
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1797206
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1797206
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaojun Zhou
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Zhou
Author-Name: Mixin Zhu
Author-X-Name-First: Mixin
Author-X-Name-Last: Zhu
Author-Name: Wenli Yu
Author-X-Name-First: Wenli
Author-X-Name-Last: Yu
Title: Maintenance scheduling for flexible multistage manufacturing systems with uncertain demands
Abstract: 
 This paper proposes a maintenance scheduling method for the flexible multistage manufacturing system in multi-specification and small-batch production. The bi-directional interactions between the production and the deterioration of the station, and the uncertainty of the future production demands are mainly involved. The workload of each station changes with the dynamic production schedule, which will have a marked impact on the deterioration of the station. Meanwhile, the deterioration state of the station will in turn influence the selection of the station to complete the production tasks. Based on this interaction, a load integrated deterioration model is established, and then a cost-effective maintenance scheduling model is proposed for the system. Because of the uncertainty of the future production demands, the optimal preventive maintenance scheme for the system is obtained by minimizing the expected total maintenance cost per unit time within the next uncertain production period. To simplify the solving process, a greedy constraint algorithm is developed, with the duration of preventive maintenance being as the constraint. Numerical comparisons show that the expected total maintenance cost under the proposed maintenance scheduling model is always lower than the one under the full load model and the average load model.
Journal: International Journal of Production Research
Pages: 5831-5843
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1791998
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1791998
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Template-Type: ReDIF-Article 1.0
Author-Name: Haoxiang Wang
Author-X-Name-First: Haoxiang
Author-X-Name-Last: Wang
Author-Name: Bhaba R. Sarker
Author-X-Name-First: Bhaba R.
Author-X-Name-Last: Sarker
Author-Name: Jing Li
Author-X-Name-First: Jing
Author-X-Name-Last: Li
Author-Name: Jian Li
Author-X-Name-First: Jian
Author-X-Name-Last: Li
Title: Adaptive scheduling for assembly job shop with uncertain assembly times based on dual Q-learning
Abstract: 
 To address the uncertainty of production environment in assembly job shop, in combination of the real-time feature of reinforcement learning, a dual Q-learning (D-Q) method is proposed to enhance the adaptability to environmental changes by self-learning for assembly job shop scheduling problem. On the basis of the objective function of minimising the total weighted earliness penalty and completion time cost, the top level Q-learning is focused on localised targets in order to find the dispatching policy which can minimise machine idleness and balance machine loads, and the bottom level Q-learning is focused on global targets in order to learn the optimal scheduling policy which can minimise the overall earliness of all jobs. Some theoretical results and simulation experiments indicate that the proposed algorithm achieves generally better results than the single Q-learning (S-Q) and other scheduling rules, under the arrival frequency of product with different conditions, and show good adaptive performance.Abbreviations: AFSSP, assembly flow shop scheduling problem; AJSSP, assembly job shop scheduling problem; RL, reinforcement learning; TASP, two-stage assembly scheduling problem
Journal: International Journal of Production Research
Pages: 5867-5883
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1794075
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1794075
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Template-Type: ReDIF-Article 1.0
Author-Name: Stephen M. Disney
Author-X-Name-First: Stephen M.
Author-X-Name-Last: Disney
Author-Name: Borja Ponte
Author-X-Name-First: Borja
Author-X-Name-Last: Ponte
Author-Name: Xun Wang
Author-X-Name-First: Xun
Author-X-Name-Last: Wang
Title: Exploring the nonlinear dynamics of the lost-sales order-up-to policy
Abstract: 
 With most inventory theory investigating linear models, the dynamics of nonlinear inventory systems is not well understood. We explore the dynamics of the order-up-to policy under lost-sales for the case of i.i.d. normally distributed demand and unit lead times. We consider the ideal minimum mean-squared error forecast and two alternative scenarios: partial demand observation and dynamic demand forecasting, providing a broad understanding of the operational performance of lost-sales systems. In each scenario, we obtain analytical expressions for the order, inventory, and satisfied demand distributions. This allows us to quantify the Bullwhip and inventory variance amplification ratios as well as the fill rate and the inventory cover. We show the lost sales nonlinearity induces complex behaviours in inventory systems. Interestingly, lost sales smooth supply chain dynamics, significantly affecting the trade-off between service level and average inventory holding. We also reveal the inventory downsides of demand censoring and the production damages induced by dynamic forecasts. We identify a key parameter, the relative safety margin, that characterises the performance of lost-sales systems. We finish by offering some prescriptive results for the optimal safety stock and capacity level in both a retail and a manufacturing lost-sales setting.
Journal: International Journal of Production Research
Pages: 5809-5830
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1790687
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1790687
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Template-Type: ReDIF-Article 1.0
Author-Name: Jaouad Abisourour
Author-X-Name-First: Jaouad
Author-X-Name-Last: Abisourour
Author-Name: Mohsine Hachkar
Author-X-Name-First: Mohsine
Author-X-Name-Last: Hachkar
Author-Name: Badia Mounir
Author-X-Name-First: Badia
Author-X-Name-Last: Mounir
Author-Name: Abdelmajid Farchi
Author-X-Name-First: Abdelmajid
Author-X-Name-Last: Farchi
Title: ISO 14001 combined to cost deployment (EMS-CD): a new financial vision
Abstract: 
 The aim of this work is to study the improvement of the performance of ISO 14001 environment management system (EMS) by deploying a tool from world-class manufacturing: Cost Deployment (CD). The EMS-CD proposed framework is meant to overcome the traditional limits presented by the implementation of ISO 14001 standards especially the lack of financial dimension. It integrates concepts from EMS (ISO 14001) and Cost Deployment tool. This approach allows the company to identify impacts and environmental aspects and implement appropriate improvement actions to ensure financial gains. The proposed framework allows critical issues to be analysed and estimates of potential savings in terms of costs. A case study applying the EMS-CD framework within a certified ISO 14001 chemical fertiliser company is presented with the aim to illustrate the proposed methodology.
Journal: International Journal of Production Research
Pages: 5771-5789
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1790683
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1790683
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Template-Type: ReDIF-Article 1.0
Author-Name: Feng Zhang
Author-X-Name-First: Feng
Author-X-Name-Last: Zhang
Author-Name: Hong Chen
Author-X-Name-First: Hong
Author-X-Name-Last: Chen
Author-Name: Yu Xiong
Author-X-Name-First: Yu
Author-X-Name-Last: Xiong
Author-Name: Wei Yan
Author-X-Name-First: Wei
Author-X-Name-Last: Yan
Author-Name: Meilian Liu
Author-X-Name-First: Meilian
Author-X-Name-Last: Liu
Title: Managing collecting or remarketing channels: different choice for cannibalisation in remanufacturing outsourcing
Abstract: 
 Cannibalisation is still a concern for original equipment manufacturers (OEMs) when they outsource remanufacturing operations to the authorised remanufacturers (ARs). In dealing with the cannibalisation in remanufacturing outsourcing, many OEMs (such as Sun, Apple, Hewlett Packard, Bosch Tools, and Gateway) use core collecting or remanufactured product remarketing. Motivated by examples from industry, we develop two models in which an OEM produces new products but outsources remanufacturing operations to a AR. The two potential strategies for dealing with the cannibalisation from remanufacturing outsourcing are: (1) collecting used cores from consumers, or (2) remarketing all remanufactured products to consumers. Among other results, we find that minimising cannibalisation problems does not equate with maximising profits. In particular, if the collection cost coefficient is not pronounced, the aggressive response by the OEM can effectively minimise the cannibalisation problems, but will reduce the profitability for the OEM on the other hand. Further, as the collection cost coefficient is moderate, remarketing remanufactured products can secure Pareto improvements. As such, we suggest that, practising managers should combine the cannibalisation problems of remanufacturing with the costs of collecting used cores.
Journal: International Journal of Production Research
Pages: 5944-5959
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1797205
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1797205
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Template-Type: ReDIF-Article 1.0
Author-Name: Taebok Kim
Author-X-Name-First: Taebok
Author-X-Name-Last: Kim
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: Simon Emde
Author-X-Name-First: Simon
Author-X-Name-Last: Emde
Title: Production planning for a ramp-up process in a multi-stage production system with worker learning and growth in demand
Abstract: 
 In a response to changes in customer requirements and environmental dynamics, product lifecycles have become shorter and shorter over the last decades. As a result, production ramp-ups have become more frequent in many industries, and they now often account for a significant share of the entire product lifecycle. Due to the prominent role production ramp-ups play in the lifecycle of a product, efficient production ramp-ups are now an important determinant of business success. This work proposes a mathematical model for managing production ramp-ups in a serial multi-stage production system. In the scenario considered here, both the productivity of workers and demand increase over time until a steady-state phase is reached at the end of the ramp-up. The model proposed in this paper supports the assignment of workers to the different stages of the production system and the balancing of production and demand to ensure a smooth transition from the production ramp-up to steady-state production. The model is analysed in numerical experiments to illustrate its potential for managing the production ramp-up. Our experiments show that high learning rates can have drawbacks in terms of large inventories if learning is not aligned with demand growth and across production stages.
Journal: International Journal of Production Research
Pages: 6002-6021
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1798034
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1798034
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Template-Type: ReDIF-Article 1.0
Author-Name: Dong-Young Kim
Author-X-Name-First: Dong-Young
Author-X-Name-Last: Kim
Author-Name: Bruce Fortado
Author-X-Name-First: Bruce
Author-X-Name-Last: Fortado
Title: Outcomes of supply chain dependence asymmetry: a systematic review of the statistical evidence
Abstract: 
 This literature review scrutinises 41 quantitative studies dealing with dependence asymmetry in supply chains. Strategically, behaviours ranging from exploitation to win-win problem solving can arise. Five research questions are explored. The systematic literature review method and a content analysis was applied to articles from premier journals in operations management and supply chain management. We found the number of studies markedly rose over the past 15 years. Five outcome categories (i.e. performance, relationship characteristics, practice and process, information sharing, and innovation) and three subcategories (i.e. supplier, customer and partner dependence) were identified that encompass each of the sample studies. The most commonly used theories proved to be resource dependence theory and transaction cost theory. We examined whether dependence asymmetry resulted in overall benefits or detriments. There were largely positive significant results in performance, practice and process, and information sharing. The results in relationship characteristics and innovation were mixed. The overall picture was more complex than the stronger firm simply taking advantage of the weaker firm.
Journal: International Journal of Production Research
Pages: 5844-5866
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1791999
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1791999
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Template-Type: ReDIF-Article 1.0
Author-Name: In-Jae Jeong
Author-X-Name-First: In-Jae
Author-X-Name-Last: Jeong
Author-Name: Sumin Jeon
Author-X-Name-First: Sumin
Author-X-Name-Last: Jeon
Title: Balanceability of a work-sharing line using floating workers and its comparison with floating work strategy
Abstract: 
 This study deals with a long-term design issue of dynamic line balancing (DLB) when work- sharing is allowed among stations. The work-sharing can be implemented by floating works or floating workers where a portion of tasks or workers is shifted to the succeeding station respectively. We suggest a mathematical model to minimise line cycle time in floating-worker environments. The line considered in this study is a 2-skill chaining line where each worker can help only the immediately downstream station. We suggest a closed form condition of balanceable floating-worker lines (FRL) in case of straight line configuration and U-shaped line configurations along with a comparison with floating-work lines (FKL). We could prove that the FRL is more efficient than the FKL as long as the floating line is balanceable. In case of a U-shaped line, we find that both the FKL and the FRL are always balanceable with the minimum cycle time, which is the total task time divided by the number of stations.
Journal: International Journal of Production Research
Pages: 5903-5912
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1795291
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1795291
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen Zheng
Author-X-Name-First: Chen
Author-X-Name-Last: Zheng
Author-Name: Zhanxi Wang
Author-X-Name-First: Zhanxi
Author-X-Name-Last: Wang
Author-Name: Xiansheng Qin
Author-X-Name-First: Xiansheng
Author-X-Name-Last: Qin
Author-Name: Benoît Eynard
Author-X-Name-First: Benoît
Author-X-Name-Last: Eynard
Author-Name: Peter Hehenberger
Author-X-Name-First: Peter
Author-X-Name-Last: Hehenberger
Author-Name: Jing Li
Author-X-Name-First: Jing
Author-X-Name-Last: Li
Author-Name: Jing Bai
Author-X-Name-First: Jing
Author-X-Name-Last: Bai
Author-Name: Yicha Zhang
Author-X-Name-First: Yicha
Author-X-Name-Last: Zhang
Title: Integrated design for product–service systems: a focus on multi-disciplinary interface
Abstract: 
 The increased competitive pressure forces companies to cease distinguishing products and services, and to provide customers with highly individualised solutions. To meet this requirement, it has been proposed the concept of product–service system (PSS) that is not simply an extension of physical products by delivering non-physical services to customers, but a systematic combination of products and services. However, most current studies do not consider the multi-disciplinary integration relating to the PSS design process, during which the collaboration within the product and service design teams should be achieved. Otherwise, the large number of iterative design activities resulting from poor multi-disciplinary collaboration may lead to long development lead-times and high development cost.To achieve the multi-disciplinary integration during the PSS design process, the authors propose an integrated design method using an improved interface modelling approach that provides a structural form to represent the information transfer between product and service components. The proposed PSS design method enables the product and service design teams to decrease the iterative design activities and improve their collaboration so that a more integrated design process can be accomplished. To demonstrate its effectiveness, the design method is applied to a design case of an industrial PSS.
Journal: International Journal of Production Research
Pages: 5884-5902
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1794077
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1794077
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Template-Type: ReDIF-Article 1.0
Author-Name: Fran Casino
Author-X-Name-First: Fran
Author-X-Name-Last: Casino
Author-Name: Venetis Kanakaris
Author-X-Name-First: Venetis
Author-X-Name-Last: Kanakaris
Author-Name: Thomas K. Dasaklis
Author-X-Name-First: Thomas K.
Author-X-Name-Last: Dasaklis
Author-Name: Socrates Moschuris
Author-X-Name-First: Socrates
Author-X-Name-Last: Moschuris
Author-Name: Spiros Stachtiaris
Author-X-Name-First: Spiros
Author-X-Name-Last: Stachtiaris
Author-Name: Maria Pagoni
Author-X-Name-First: Maria
Author-X-Name-Last: Pagoni
Author-Name: Nikolaos P. Rachaniotis
Author-X-Name-First: Nikolaos P.
Author-X-Name-Last: Rachaniotis
Title: Blockchain-based food supply chain traceability: a case study in the dairy sector
Abstract: 
 Traceability has become a critical element in supply chain management, particularly in safety-sensitive sectors like food, pharmaceuticals, etc. Upstream (manufacturers, producers, etc.) and downstream (distributors, wholesalers, etc.) supply chain members need to store and handle traceability-related information for providing proof of regulatory compliance to both state authorities and more demanding customers. Consumers also place high expectations on food supply chains (FSC) with specific emphasis on facets related to safety. However, the complexity of modern FSC networks and their fragmentation act as barriers for the development of sound traceability mechanisms. In this paper a distributed trustless and secure architecture for FSC traceability is developed and tested. For assessing the feasibility of the proposed approach, a food traceability case study from a dairy company is presented. The applicability of the model is further illustrated by the development of fully functional smart contracts and a local private blockchain. Moreover, the various links between the proposed blockchain-based model and its managerial implications are presented. The overall benefits of the proposed model are discussed along with fruitful areas for future research. The results are of significant value to both practitioners and researchers.
Journal: International Journal of Production Research
Pages: 5758-5770
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1789238
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1789238
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Template-Type: ReDIF-Article 1.0
Author-Name: Jia Song
Author-X-Name-First: Jia
Author-X-Name-Last: Song
Author-Name: Juliang Zhang
Author-X-Name-First: Juliang
Author-X-Name-Last: Zhang
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Title: Inventory management and the value of quick response to the retailer facing boundedly rational strategic customers
Abstract: 
 We consider a two-stage newsvendor model in which the retailer orders a product and sells it at the full price in the first stage, and sells the leftover stock, if any, at a discounted price in the second stage. The customers are strategic, who are boundedly rational and risk averse, and their valuations of the product decrease with time. The customers make purchase decisions based on their beliefs of the product’s availability and their expected utility in the two stages. The customers who purchase in the second stage may not get the product. Characterising the retailer’s optimal inventory policy, we show that the retailer’s optimal profit decreases with the rate of the customers’ decreasing product valuation. Moreover, as the customers become less rational or more risk averse, the retailer’s profit vary with the model parameters. We conduct numerical studies to examine the impacts of the customers’ bounded rationality on the retailer’s order quantity and optimal profit. In addition, considering the value of the quick response (QR) strategy, we show that the QR strategy can increase the retailer’s profit, while the customers’ bounded rationality may increase or decrease the value of QR to the retailer.
Journal: International Journal of Production Research
Pages: 5743-5757
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1789237
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1789237
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Template-Type: ReDIF-Article 1.0
Author-Name: Kyu Tae Park
Author-X-Name-First: Kyu Tae
Author-X-Name-Last: Park
Author-Name: Yoo Ho Son
Author-X-Name-First: Yoo Ho
Author-X-Name-Last: Son
Author-Name: Sang Do Noh
Author-X-Name-First: Sang Do
Author-X-Name-Last: Noh
Title: The architectural framework of a cyber physical logistics system for digital-twin-based supply chain control
Abstract: 
 Personalised production allows the supply chain (SC) to exist in various dynamic fluctuations within a make-to-order (MTO) environment. An SC for personalised production has redundant inventory and operation capacity; therefore, it requires a system that can achieve recoverability for operation resilience. Thus, a standalone cyber physical system (CPS) has limitation for SC control with MTO. To solve this problem, the CPS must be coordinated, and a systematic approach is required. This study proposes a cyber physical logistics system (CPLS) that is coordinated with the agent cyber physical production systems in a multi-level CPS structure. This multi-level architectural framework is designed to provide technical functionalities for resilient SC control. The service composition procedures of technical functionalities on the distributed digital twin (DT) simulation are divided into type and instance stages. The operation procedures of the DT application and technical functionality of the DT engine are suggested. The proposed CPLS has appropriate service composition and operation for the bullwhip and ripple effects, which are the two main SC-related problems. This study illustrates an early case of CPLS that can minimise differences among assets using distributed DT simulation; furthermore, the study establishes an SC and production plan based on the DT simulation results.
Journal: International Journal of Production Research
Pages: 5721-5742
Issue: 19
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1788738
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1788738
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Template-Type: ReDIF-Article 1.0
Author-Name: C. R. Vishnu
Author-X-Name-First: C. R.
Author-X-Name-Last: Vishnu
Author-Name: Sangeeth P. Das
Author-X-Name-First: Sangeeth P.
Author-X-Name-Last: Das
Author-Name: R. Sridharan
Author-X-Name-First: R.
Author-X-Name-Last: Sridharan
Author-Name: P. N. Ram Kumar
Author-X-Name-First: P. N.
Author-X-Name-Last: Ram Kumar
Author-Name: N. S. Narahari
Author-X-Name-First: N. S.
Author-X-Name-Last: Narahari
Title: Development of a reliable and flexible supply chain network design model: a genetic algorithm based approach
Abstract: 
 Enhancing the proactive strategic capabilities to withstand the most unfavourable circumstances is always appreciated as a long-term policy rather than incident-based responses. The present research is positioned on this fundamental notion of supply chain risk management with a particular focus on strategic capabilities like reliability and flexibility that often conflict with cost. Accordingly, the authors propose a multi-objective mathematical model for designing a four-echelon supply chain that optimises cost, reliability, and volume flexibility. Interestingly, this research is the maiden effort to optimise the supply chain with these trifold objectives and herein lies the novelty as well as the challenges. Consequently, a genetic algorithm based approach is utilised as the solution methodology. To demonstrate the effectiveness of the proposed method, the small problem instances and the four-echelon problems have also been validated through exact methods and simulated annealing algorithm, respectively. A case study on a footwear supply chain involving three echelons is also presented to showcase the industrial applicability and adaptability of the proposed model. A fuzzy TOPSIS method has been adopted in the case study to incorporate the expert opinion for assigning priorities to the objectives. Supply chain professionals can leverage this methodology to establish a risk resistant supply chain.
Journal: International Journal of Production Research
Pages: 6185-6209
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1808256
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1808256
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Template-Type: ReDIF-Article 1.0
Author-Name: Wendong Li
Author-X-Name-First: Wendong
Author-X-Name-Last: Li
Author-Name: Chi Zhang
Author-X-Name-First: Chi
Author-X-Name-Last: Zhang
Author-Name: Fugee Tsung
Author-X-Name-First: Fugee
Author-X-Name-Last: Tsung
Author-Name: Yajun Mei
Author-X-Name-First: Yajun
Author-X-Name-Last: Mei
Title: Nonparametric monitoring of multivariate data via KNN learning
Abstract: 
 Process monitoring of multivariate quality attributes is important in many industrial applications, in which rich historical data are often available thanks to modern sensing technologies. While multivariate statistical process control (SPC) has been receiving increasing attention, existing methods are often inadequate as they are sensitive to the parametric model assumptions of multivariate data. In this paper, we propose a novel, nonparametric k-nearest neighbours empirical cumulative sum (KNN-ECUSUM) control chart that is a machine-learning-based black-box control chart for monitoring multivariate data by utilising extensive historical data under both in-control and out-of-control scenarios. Our proposed method utilises the k-nearest neighbours (KNN) algorithm for dimension reduction to transform multivariate data into univariate data and then applies the CUSUM procedure to monitor the change on the empirical distribution of the transformed univariate data. Extensive simulation studies and a real industrial example based on a disk monitoring system demonstrate the robustness and effectiveness of our proposed method.
Journal: International Journal of Production Research
Pages: 6311-6326
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1812750
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1812750
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Template-Type: ReDIF-Article 1.0
Author-Name: Giovanni Celano
Author-X-Name-First: Giovanni
Author-X-Name-Last: Celano
Author-Name: Subhabrata Chakraborti
Author-X-Name-First: Subhabrata
Author-X-Name-Last: Chakraborti
Title: A distribution-free Shewhart-type Mann–Whitney control chart for monitoring finite horizon productions
Abstract: 
 Distribution-free control charts have been proposed in recent years to monitor processes with insufficient information about the distribution of observations. A promising field of application of these charts is the small production of finite batches of products, where the number of scheduled inspections is limited to a few tens. Following the machine reconfiguration after a process set-up, the quality practitioner cannot rely on past production runs to get knowledge about the distribution of the observations: this scenario can be referred to as the Case U (Unknown) condition in statistical process monitoring. Here, we investigate the issues related to the implementation of Mann–Whitney (MW) type control charts for monitoring the location in a finite horizon production (FHP) process. The practitioner-to-practitioner variability is considered while designing the control limits. The in-control and out-of-control chart performances are investigated over a wide set of scenarios and some graphical tools are proposed to help practitioners during the decision-making process. A comparison with the Shewhart Sign control chart for FHP processes is also presented. An illustrative example is provided to demonstrate the implementation of the proposed chart on a real industrial dataset.
Journal: International Journal of Production Research
Pages: 6069-6086
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1802079
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1802079
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Template-Type: ReDIF-Article 1.0
Author-Name: Abdelhak Elidrissi
Author-X-Name-First: Abdelhak
Author-X-Name-Last: Elidrissi
Author-Name: Rachid Benmansour
Author-X-Name-First: Rachid
Author-X-Name-Last: Benmansour
Author-Name: Mohammed Benbrahim
Author-X-Name-First: Mohammed
Author-X-Name-Last: Benbrahim
Author-Name: David Duvivier
Author-X-Name-First: David
Author-X-Name-Last: Duvivier
Title: Mathematical formulations for the parallel machine scheduling problem with a single server
Abstract: 
 This paper addresses the problem of scheduling independent jobs on identical parallel machines with a single server to minimise the makespan. We propose mixed integer programming (MIP) formulations to solve this problem. Each formulation reflects a specific concept on how the decision variables are defined. Moreover, we present inequalities that can be used to improve those formulations. A computational study is performed on benchmark instances from the literature to compare the proposed MIP formulations with other known formulations from the literature. It turns out that our proposed time-indexed variables formulation outperforms by far the other formulations. In addition, we propose a very efficient MIP formulation to solve a particular case of the problem with a regular job set. This formulation is able to solve all regular instances for the case of 500 jobs and 5 machines in less than 5.27 min, where all other formulations are not able to produce a feasible solution within 1 h.
Journal: International Journal of Production Research
Pages: 6166-6184
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1807637
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1807637
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Template-Type: ReDIF-Article 1.0
Author-Name: Chaaben Kouki
Author-X-Name-First: Chaaben
Author-X-Name-Last: Kouki
Author-Name: Christian Larsen
Author-X-Name-First: Christian
Author-X-Name-Last: Larsen
Title: Rationing policies in a spare parts inventory system with customers differentiation
Abstract: 
 We consider a spare parts inventory system controlled by a base-stock policy. We assume several demand classes, where the demands of each class follow a compound Poisson process, and a stochastic replenishment lead-time common to all classes. For this inventory system, we investigate two rationing policies that can be employed when the inventory level is critically low. The first policy is the reservation policy, where a part of the stock is reserved for high priority demand classes, whereas the second one is new, which we call a threshold policy, and accepts demands of a given class until the pipeline stock caused by the particular class (plus the amount of the incoming order) reaches a critical level. On average, for 8% (12%) of all instances, the threshold policy performs better than the reservation policy under the full (partial) lost sales case and when the objective is to minimise the average on-hand inventory subject to fill rate service requirements. Furthermore, in many cases where the reservation policy outperforms the threshold policy, the gap between the two policies is small under both service requirements and total cost minimisation criteria. This suggests that a trade-off between ‘fairness’ and ‘cost’ is required, and that when the performance of two policies are similar, the threshold policy is generally favoured.
Journal: International Journal of Production Research
Pages: 6270-6290
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1811418
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1811418
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Template-Type: ReDIF-Article 1.0
Author-Name: Miguel Vieira
Author-X-Name-First: Miguel
Author-X-Name-Last: Vieira
Author-Name: Helena Paulo
Author-X-Name-First: Helena
Author-X-Name-Last: Paulo
Author-Name: Tânia Pinto-Varela
Author-X-Name-First: Tânia
Author-X-Name-Last: Pinto-Varela
Author-Name: Ana Paula Barbosa-Póvoa
Author-X-Name-First: Ana Paula
Author-X-Name-Last: Barbosa-Póvoa
Title: Assessment of financial risk in the design and scheduling of multipurpose plants under demand uncertainty
Abstract: 
 Industrial companies are seeking for highly flexible strategic and operational solutions to face the requirements of current dynamic markets. The aim of this work is to provide a decision support assessment for the design and scheduling of a multipurpose plant under demand uncertainty, allowing the assessment of alternative risk profile solutions. A general two-stage mixed-integer linear programming (MILP) model is proposed with the goal to maximise the annualised profit of the plant operation under a set of scenarios while minimising the associated financial risk. Considering the long-term investment perspective, the Conditional Value at Risk (CVaR) measure is used to evaluate the likelihood that a specific loss or gain will exceed a certain value at risk. A bi-objective model is formulated using the augmented ε-constraint method to generate an approximation to the Pareto-optimal curve, illustrating the trade-offs between plant profit (with the corresponding design and scheduling decisions) and the associated financial risk. Addressing a set of propositions regarding a case-study, the conclusions highlight the advantages of the risk measure integration in support of the decision-making process, discussing the managerial insights in the assessment of diverse financial outcomes for the solution optimisation.
Journal: International Journal of Production Research
Pages: 6125-6145
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1804638
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1804638
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Template-Type: ReDIF-Article 1.0
Author-Name: Maciel M. Queiroz
Author-X-Name-First: Maciel M.
Author-X-Name-Last: Queiroz
Author-Name: Samuel Fosso Wamba
Author-X-Name-First: Samuel
Author-X-Name-Last: Fosso Wamba
Author-Name: Marc De Bourmont
Author-X-Name-First: Marc
Author-X-Name-Last: De Bourmont
Author-Name: Renato Telles
Author-X-Name-First: Renato
Author-X-Name-Last: Telles
Title: Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy
Abstract: 
 The adoption of technologies by the operations and supply chain management (OSCM) field is leading to extraordinary disruptions. And with the rapid emergence of cutting-edge and more disruptive technologies, the OSCM is striving to take advantage of such innovations, but they are bringing in their wake a number of challenges. One of those disruptive technologies is blockchain, which is increasingly accepted in virtually all industries. This study aims to investigate the blockchain technology (BCT) adoption behaviour and possible barriers in the Brazilian OSCM context. We developed a model drawing on the unified theory of acceptance and use of technology (UTAUT) model, the supply chain literature, and the emerging literature on BCT. We empirically validated the proposed model with Brazilian operations and supply chain professionals by using the partial least squares structural equation modelling (PLS-SEM). Our findings revealed that facilitating conditions, trust, social influence, and effort expectancy are the most critical constructs that directly affect BCT adoption. Unexpectedly, performance expectancy appeared not decisive in terms of predicting BCT adoption. This study contributes to advancing and stimulating the theory about BCT adoption behaviour in supply chains, as well as important managerial implications, which may be more critical for emerging economies.
Journal: International Journal of Production Research
Pages: 6087-6103
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1803511
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1803511
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrea Grassi
Author-X-Name-First: Andrea
Author-X-Name-Last: Grassi
Author-Name: Guido Guizzi
Author-X-Name-First: Guido
Author-X-Name-Last: Guizzi
Author-Name: Liberatina Carmela Santillo
Author-X-Name-First: Liberatina Carmela
Author-X-Name-Last: Santillo
Author-Name: Silvestro Vespoli
Author-X-Name-First: Silvestro
Author-X-Name-Last: Vespoli
Title: Assessing the performances of a novel decentralised scheduling approach in Industry 4.0 and cloud manufacturing contexts
Abstract: 
 The increasing globalisation process has led to a radical change in the production concept, moving from a mass production paradigm towards one of mass customisation (MC), and focusing on value creation by pursuing customers’ needs and increasing responsiveness. The rapid development of information technologies has also made it possible to create new manufacturing paradigms, such as Industry 4.0 and cloud manufacturing, in which the increased level of autonomy is one of the key concepts for tackling new market challenges. This paper proposes a decentralised scheduling approach that improves the performance of production systems while minimising the usually high work-in-progress (WIP) requirements of the classic centralised scheduling and inventory production control system. Using a semi-heterarchical Manufacturing Planning and Control (MPC) architecture and integrating the Industry 4.0 innovation in a cloud manufacturing environment, this work contributes to the design of the lower level of the MPC architecture. The resulting production controller can allocate jobs following different dispatching rules dynamically. The performances of the proposed approach were assessed for different production scenarios and control parameter settings through an exhaustive experimental campaign based on hybrid simulation tools. The results showed that the proposed low-level controller led to a productivity increase while delivering increased responsiveness.
Journal: International Journal of Production Research
Pages: 6034-6053
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1799105
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1799105
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Template-Type: ReDIF-Article 1.0
Author-Name: Mengdi Zhang
Author-X-Name-First: Mengdi
Author-X-Name-Last: Zhang
Author-Name: Saurabh Pratap
Author-X-Name-First: Saurabh
Author-X-Name-Last: Pratap
Author-Name: Zhiheng Zhao
Author-X-Name-First: Zhiheng
Author-X-Name-Last: Zhao
Author-Name: D. Prajapati
Author-X-Name-First: D.
Author-X-Name-Last: Prajapati
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Forward and reverse logistics vehicle routing problems with time horizons in B2C e-commerce logistics
Abstract: 
 This research addresses a vehicle routing problem with simultaneous pickup and delivery with time windows from multiple depots (MVRPSPDTW) over a time horizon in the B2C e-commerce logistics system. We consider an e-commerce logistics system with a multi-period, which consists of customers, logistics service providers (LSPs), suppliers, and a decision-making platform. A mixed-integer non-linear programming (MINLP) model is developed and tested on small- and large-scale instances. To handle more realistic large-scale problems, we have used two approaches (i) exact optimisation approach using (i.e. CPLEX tool) and metaheuristic algorithms (i.e. Differential Evolutionary Algorithm (DE), Parallel Differential Evolutionary Algorithm (Par-DE), Genetic Algorithm (GA), and Block-based Genetic Algorithm (BBGA)) to minimise the total transportation cost and penalty due to the delay by logistics service providers. The computation experiment is conducted on the real practical scenario data and the comparative result is demonstrated.
Journal: International Journal of Production Research
Pages: 6291-6310
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1812749
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1812749
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Template-Type: ReDIF-Article 1.0
Author-Name: Roberta Pellegrino
Author-X-Name-First: Roberta
Author-X-Name-Last: Pellegrino
Author-Name: Nicola Costantino
Author-X-Name-First: Nicola
Author-X-Name-Last: Costantino
Author-Name: Danilo Tauro
Author-X-Name-First: Danilo
Author-X-Name-Last: Tauro
Title: The value of flexibility in mitigating supply chain transportation risks
Abstract: 
 This paper investigates the value of the flexibility created by the transportation options in mitigating supply chain transportation risks. We accomplish this aim by developing an innovative computational model which uses the Real Option Valuation method to model the inner flexibility mechanism of the transportation options to choose between the Safety Net carrier and the spot market carrier on the basis of the actual conditions of the spot market (price, service level, and required transportation capacity), which is the foundation of the mitigation capability of transportation options. Through the case of a real supply chain of a large Fortune 100 multinational leader in the Fast Mover Consumer Goods (FMCG) industry, we also investigate the implications of a transportation options response in case of several sources of uncertainties, namely transportation capacity shortage, price volatility and service level reliability. Findings of the application support the understanding of which conditions increase the value of flexibility of the transportation options and how much flexibility is attractive given the initial sunk cost to acquire it.
Journal: International Journal of Production Research
Pages: 6252-6269
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1811417
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1811417
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:20:p:6252-6269




Template-Type: ReDIF-Article 1.0
Author-Name: Xin Liu
Author-X-Name-First: Xin
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Title: Parallel machine scheduling with stochastic release times and processing times
Abstract: 
 Stochastic scheduling has received much attention from both industry and academia. Existing works usually focus on random job processing times. However, the uncertainty existing in job release times may largely impact the performance as well. This work investigates a stochastic parallel machine scheduling problem, where job release times and processing times are uncertain. The problem consists of a two-stage decision-making process: (i) assigning jobs to machines on the first stage before the realisation of uncertain parameters (job release times and processing times) and (ii) scheduling jobs on the second stage given the job-to-machine assignment and the realisation of uncertain parameters. The objective is to minimise the total cost, including the setup cost on machines (induced by job-to-machine assignment) and the expected penalty cost of jobs' earliness and tardiness. A two-stage stochastic program is proposed, and the sample average approximation (SAA) method is applied. A scenario-reduction-based decomposition approach is further developed to improve the computational efficiency. Numerical results show that the scenario-reduction-based decomposition approach performs better than the SAA, in terms of solution quality and computation time.
Journal: International Journal of Production Research
Pages: 6327-6346
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1812752
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1812752
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhe Wang
Author-X-Name-First: Zhe
Author-X-Name-Last: Wang
Author-Name: Yue Wang
Author-X-Name-First: Yue
Author-X-Name-Last: Wang
Author-Name: Zhi Liu
Author-X-Name-First: Zhi
Author-X-Name-Last: Liu
Author-Name: Jinshi Cheng
Author-X-Name-First: Jinshi
Author-X-Name-Last: Cheng
Author-Name: Xintong Chen
Author-X-Name-First: Xintong
Author-X-Name-Last: Chen
Title: Strategic management of product recovery and its environmental impact
Abstract: 
 Facing a huge number and variety of discarded products, how to conduct strategic management of product recovery and gain better economic and environmental performances are people's concerns. In this paper, a stylised model of a monopoly manufacturer who implements product recovery management under the voluntary mechanism is considered. The manufacturer can recycle, remanufacture and properly dispose of used cores after collecting. The condition under which the manufacturer gives up product recovery management is discussed and four different product recovery strategies portfolios are characterised according to profitable trade-offs between available product recovery options. Under each product recovery strategies portfolio, the product recovery strategies are determined corresponding to different cost intervals of new product and optimal solutions under per product recovery strategy are displayed. Then, how different revenue and cost parameters influence the optimal production and recovery decisions and economic profits is analysed. To evaluate the environmental impact of per product recovery strategies portfolio, product life-cycle assessment approach is adopted to analyse changes in environmental impacts after incorporating product recovery management. Implementing product recovery management does not always make the environment better and the condition under which implementing product recovery management brings a better environmental impact is determined.
Journal: International Journal of Production Research
Pages: 6104-6124
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1804637
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1804637
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Template-Type: ReDIF-Article 1.0
Author-Name: Fei Yuan
Author-X-Name-First: Fei
Author-X-Name-Last: Yuan
Author-Name: Kai Feng
Author-X-Name-First: Kai
Author-X-Name-Last: Feng
Author-Name: Shi-jing Lin
Author-X-Name-First: Shi-jing
Author-X-Name-Last: Lin
Author-Name: An-jun Xu
Author-X-Name-First: An-jun
Author-X-Name-Last: Xu
Title: A study on DAA-based crane scheduling models for steel plant
Abstract: 
 Crane scheduling tasks in steelworks are a matter of uncertainty scheduling with certain probability distribution pattern. To better schedule tasks with this feature, this paper proposes a Dynamic Area Allocation (DAA)-based crane scheduling model according to the following steps. First, Bayesian network, according to the time sequence of crane transportation tasks, is constructed. Then, conditional probability for each network node on the basis of actual crane operating data is calculated for getting the corresponding time–space probability distribution, and then obtaining the spatial distribution by superposing of all crane transportation tasks in the space domain at certain time. At last, tasks are assigned to cranes based on their spatial distribution and the equal probability partition. Simulation testing on the scheduling model is carried out using practical crane transportation tasks in steelworks. Results show that the model based on the dynamic area allocation, with its scheduling period of 15 min, can greatly shorten transportation time and reduce times of collision resulted from crane interference, after compared with the current widely used crane scheduling programme based on the fixed area allocation (FAA).
Journal: International Journal of Production Research
Pages: 6241-6251
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1809732
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1809732
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Template-Type: ReDIF-Article 1.0
Author-Name: Zikai Zhang
Author-X-Name-First: Zikai
Author-X-Name-Last: Zhang
Author-Name: Qiuhua Tang
Author-X-Name-First: Qiuhua
Author-X-Name-Last: Tang
Author-Name: Dayong Han
Author-X-Name-First: Dayong
Author-X-Name-Last: Han
Author-Name: Xinbo Qian
Author-X-Name-First: Xinbo
Author-X-Name-Last: Qian
Title: An enhanced multi-objective JAYA algorithm for U-shaped assembly line balancing considering preventive maintenance scenarios
Abstract: 
 Given that a U-shaped assembly line is usually regarded as a serial flow production system, preventive maintenance (PM) on machines in any station of the line may lead to stoppage of the whole line and sequentially cause great loss of production cost. To improve production continuity during PM, this paper proposes multiple alternative assignment plans with interchangeable abilities to ascertain the production recovery from changes of line structure. A mixed-integer mathematical model is further formulated to make decisions on alternative assignment plans. In this model, cycle time and total assignment plan alteration cost are minimised simultaneously. And an enhanced JAYA algorithm is developed to obtain well-distributed Pareto frontier solutions effectively and efficiently. The proposed algorithm suggests a similarity-based selection and various crossover/neighbourhood search operators to enhance its search ability for global optima. Numerical experiment results prove the effectiveness of the proposed model and enhanced JAYA. This novel methodology of integration optimisation bridges assembly line balancing and PM, and thus promotes production continuity and achieves economic benefits under maintenance within large-scaled assembly lines in real situations. Furthermore, a real-world case study is conducted to illustrate the significance of this novel methodology.
Journal: International Journal of Production Research
Pages: 6146-6165
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1804639
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1804639
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Template-Type: ReDIF-Article 1.0
Author-Name: Chun Su
Author-X-Name-First: Chun
Author-X-Name-Last: Su
Author-Name: Xiaotian Yang
Author-X-Name-First: Xiaotian
Author-X-Name-Last: Yang
Title: Two-stage renewing warranty policy with the threshold of maintenance times
Abstract: 
 Compared with non-renewing warranty, renewing warranty is more attractive to the customers. To reduce the possible cost pressure of the manufacturers, this study proposes a novel two-stage renewing warranty model with a threshold of maintenance times. Based on a preset allocation ratio, the warranty period is divided into two stages, i.e. the renewing warranty stage and the minimal repair warranty stage. In the first stage, when the number of maintenance actions exceeds the given threshold, the failed item will be replaced with a new one and attached with a new warranty period; otherwise, the product will enter the second stage when its operating time exceeds the time span of the renewing warranty stage. When the product fails in the second stage, only minimal repair is performed. On this basis, four types of maintenance schemes are proposed, and the corresponding warranty cost and profit models are developed to optimise the warranty policy. A numerical example is provided to illustrate the effectiveness of the proposed model, and sensitivity analysis is conducted. The results show that by considering the threshold of maintenance times, the warranty cost can be reduced and the manufacturer's expected profit can be improved simultaneously.
Journal: International Journal of Production Research
Pages: 6210-6222
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1808260
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1808260
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiawei Tao
Author-X-Name-First: Jiawei
Author-X-Name-Last: Tao
Author-Name: Hongyan Dai
Author-X-Name-First: Hongyan
Author-X-Name-Last: Dai
Author-Name: Hai Jiang
Author-X-Name-First: Hai
Author-X-Name-Last: Jiang
Author-Name: Weiwei Chen
Author-X-Name-First: Weiwei
Author-X-Name-Last: Chen
Title: Dispatch optimisation in O2O on-demand service with crowd-sourced and in-house drivers
Abstract: 
 O2O (Online to Offline) services enable customers to place orders online and receive products/services offline. In addition to traditional in-house drivers, the emergence of crowd-sourced drivers provides an opportunity to re-organise offline delivery services. In practice, three types of workforce, namely, in-house, full-time, and part-time crowd-sourced drivers, coexist in the system while exhibiting different characteristics. This situation creates challenges for the management of order assignment and routing. In particular, we study three settings in response to different driver preferences: the guaranteed minimum daily number of orders for full-time drivers; the maximally allowed number of orders per trip; and the detour proportion for part-time drivers. This paper aims to provide a method for O2O platforms to optimise order assignment and routing, considering these designs about driver preferences. We further validate our model and study managerial insights using real datasets. Specifically, the results show that among all designed parameters for the O2O on-demand delivery system, two parameters – the maximally allowed number of orders per trip and the detour proportion – are critical for the design. Moreover, we find that incentive mechanisms for inexperienced and experienced drivers are different because of their service capacities. The managerial insights are expected to guide practitioners.
Journal: International Journal of Production Research
Pages: 6054-6068
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1800120
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1800120
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoyue Li
Author-X-Name-First: Xiaoyue
Author-X-Name-Last: Li
Author-Name: Yinfei Yang
Author-X-Name-First: Yinfei
Author-X-Name-Last: Yang
Author-Name: Liang Li
Author-X-Name-First: Liang
Author-X-Name-Last: Li
Author-Name: Yaowen Shi
Author-X-Name-First: Yaowen
Author-X-Name-Last: Shi
Author-Name: Guolong Zhao
Author-X-Name-First: Guolong
Author-X-Name-Last: Zhao
Author-Name: Ning He
Author-X-Name-First: Ning
Author-X-Name-Last: He
Author-Name: Ning Qian
Author-X-Name-First: Ning
Author-X-Name-Last: Qian
Author-Name: Zhuang Mu
Author-X-Name-First: Zhuang
Author-X-Name-Last: Mu
Title: An approach for optimising the fixturing configuration in flexible machining fixtures
Abstract: 
 Optimal fixture configuration is critical to minimise the machining distortion of the workpiece. This study presented an approach for optimisation of fixturing configuration in flexible machining fixtures. Herein, a flexible fixture system composed of adaptive clamping unit, locating unit, and auxiliary locating unit was investigated. Response surface methodology (RSM) was employed to describe the relationship between fixturing parameters (distance between two zero-point fixtures m1, the clamping force of float fixture m2, and quantity of float fixture m3) and machining distortion. Furthermore, sensitivity analysis was implemented to evaluate the effects of fixturing parameters on machining distortion. Adaptive penalty function (APF) was constructed to search optimal settings of fixturing parameters. Comparative analysis of different optimal fixturing parameters obtained by RSM and APF was conducted. Single-sided component was adopted to validate the effectiveness of the proposed approach. Machining distortion was found to first decrease and then increase with the augment of m1 and it reduced with the increment of m2 and m3. Besides, m3 exhibited the greatest influence on machining distortion, 61.78%. The interaction between m2 and m3 resulted in the lowest influence, 0.019003%. Furthermore, the maximum machining distortion through optimised flexible clamping was only 0.312 mm, which reduced by 57.6% compared to traditional clamping.
Journal: International Journal of Production Research
Pages: 6223-6240
Issue: 20
Volume: 59
Year: 2021
Month: 10
X-DOI: 10.1080/00207543.2020.1808262
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1808262
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Template-Type: ReDIF-Article 1.0
Author-Name: Abdourahim Sylla
Author-X-Name-First: Abdourahim
Author-X-Name-Last: Sylla
Author-Name: Thierry Coudert
Author-X-Name-First: Thierry
Author-X-Name-Last: Coudert
Author-Name: Elise Vareilles
Author-X-Name-First: Elise
Author-X-Name-Last: Vareilles
Author-Name: Laurent Geneste
Author-X-Name-First: Laurent
Author-X-Name-Last: Geneste
Author-Name: Michel Aldanondo
Author-X-Name-First: Michel
Author-X-Name-Last: Aldanondo
Title: Possibilistic Pareto-dominance approach to support technical bid selection under imprecision and uncertainty in engineer-to-order bidding process
Abstract: 
 Successful bidding involves defining relevant technical bid solutions that conform to the customers' requirements, then selecting the most interesting one for the commercial offer. However, in Engineer-To-Order (ETO) industrial contexts, this selection process is complicated by issues of imprecision, uncertainty and confidence regarding the values of the decision criteria. To address this complexity, a Multi-Criteria Decision Making (MCDM) support approach is proposed in this study. This approach is based on possibility theory and the Pareto-dominance principle. It involves three main stages. First, a method is proposed to automatically model the values of the decision criteria by possibility distributions. Second, four possibilistic mono-criterion dominance relations are developed to compare two solutions with respect to a single decision criterion. Finally, an interactive method is devised to determine the most interesting technical bid solutions with respect to all the decision criteria. The method is applied to the design of a technical bid solution of a crane. The results show that this approach enables bidders to select the most interesting solution during a bidding process, while taking into account imprecision, uncertainty and their own confidence regarding the values of the decision criteria.
Journal: International Journal of Production Research
Pages: 6361-6381
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1812754
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1812754
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Template-Type: ReDIF-Article 1.0
Author-Name: Zheyuan Chen
Author-X-Name-First: Zheyuan
Author-X-Name-Last: Chen
Author-Name: Ying Liu
Author-X-Name-First: Ying
Author-X-Name-Last: Liu
Author-Name: Agustin Valera-Medina
Author-X-Name-First: Agustin
Author-X-Name-Last: Valera-Medina
Author-Name: Fiona Robinson
Author-X-Name-First: Fiona
Author-X-Name-Last: Robinson
Author-Name: Michael Packianather
Author-X-Name-First: Michael
Author-X-Name-Last: Packianather
Title: Multi-faceted modelling for strip breakage in cold rolling using machine learning
Abstract: 
 In the cold rolling process of steel strip products, strip breakage is an undesired production failure which can lead to yield loss, reduced work speed and equipment damage. To perform a root cause analysis, conventional physics-based approaches which focus on mechanical and metallurgical principles have been applied in a retrospective manner. With the advancement of data acquisition technologies, numerous process monitoring data is collected by various sensors deployed along this process; however, conventional approaches cannot take advantage of these data. In this paper, a machine learning-based approach is proposed to characterise and model strip breakage in a predictive manner. First, to match the temporal characteristic of strip breakage which occurs instantaneously, historical multivariate time-series data of a cold rolling process were extracted in a run-to-failure manner, and a sliding window strategy was adopted for data annotation. Second, breakage-centric features were identified from three facets – physics-based approaches, empirical knowledge and data-driven features. Finally, these features were used as inputs for strip breakage modelling using recurrent neural networks (RNNs), which are specialised in discovering underlying patterns embedded in time-series data. An experimental study using real-world data collected from a cold-rolled electrical steel strip manufacturer revealed the effectiveness of the proposed approach.
Journal: International Journal of Production Research
Pages: 6347-6360
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1812753
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1812753
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Template-Type: ReDIF-Article 1.0
Author-Name: Eduardo Álvarez-Miranda
Author-X-Name-First: Eduardo
Author-X-Name-Last: Álvarez-Miranda
Author-Name: Sebastián Chace
Author-X-Name-First: Sebastián
Author-X-Name-Last: Chace
Author-Name: Jordi Pereira
Author-X-Name-First: Jordi
Author-X-Name-Last: Pereira
Title: Assembly line balancing with parallel workstations
Abstract: 
 The simple assembly line balancing problem (SALBP) considers work division among different workstations of a serially arranged assembly process to maximise its efficiency under workload (cumulative) and technological (precedence) constraints. In this work, we consider a variant of the SALBP which allows parallel workstations. To study the effect of parallel stations, we propose a new problem (the parallel station assembly line balancing problem or PSALBP) in which the objective is to minimise the number of parallel stations required to obtain the maximum theoretical efficiency of the assembly process. We study the complexity of the problem and identify a polynomially solvable case. This result is then used as a building block for the development of a heuristic solution procedure. Finally, we carry out a computational experiment to identify the characteristics of assembly lines that may benefit from station paralleling and to evaluate the performance of the proposed heuristic.
Journal: International Journal of Production Research
Pages: 6486-6506
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1818000
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1818000
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:21:p:6486-6506




Template-Type: ReDIF-Article 1.0
Author-Name: Silviya Valeva
Author-X-Name-First: Silviya
Author-X-Name-Last: Valeva
Author-Name: Mike Hewitt
Author-X-Name-First: Mike
Author-X-Name-Last: Hewitt
Author-Name: Barrett W. Thomas
Author-X-Name-First: Barrett W.
Author-X-Name-Last: Thomas
Title: Managing uncertainty in demand through inventory and workforce development
Abstract: 
 This paper studies whether and how a manufacturer can mitigate the effects of demand uncertainty during production ramp up by jointly managing inventory and capacity development, determined by the productivity of a heterogeneous workforce. One way the manufacturer can direct its capacity development is by recognising that workers become more productive as they gain experience when making scheduling decisions. We consider a situation in which demands for multiple products are periodically revealed and a manufacturer must decide what each individual does in the production process, how much inventory is accumulated, and how demands are met. To study the potential benefits, we formulate a Markov decision process model which we solve using a one-step lookahead approximation. Results of an extensive computational study show that, given the effectiveness associated with both directing capacity and holding inventory, manufacturers should consider the workforce's capacity to learn when making job assignments during production ramp up. Analysis of the results suggests that inventory and capacity building patterns depend on product value and the workforce's experience levels. Further analysis shows that slower learners and those with the potential to achieve higher productivity should specialise more. Faster learners, on the other hand, are best suited for cross training.
Journal: International Journal of Production Research
Pages: 6507-6527
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1818861
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1818861
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Template-Type: ReDIF-Article 1.0
Author-Name: Ahlam Azzamouri
Author-X-Name-First: Ahlam
Author-X-Name-Last: Azzamouri
Author-Name: Mouna Bamoumen
Author-X-Name-First: Mouna
Author-X-Name-Last: Bamoumen
Author-Name: Hajar Hilali
Author-X-Name-First: Hajar
Author-X-Name-Last: Hilali
Author-Name: Vincent Hovelaque
Author-X-Name-First: Vincent
Author-X-Name-Last: Hovelaque
Author-Name: Vincent Giard
Author-X-Name-First: Vincent
Author-X-Name-Last: Giard
Title: Flexibility of dynamic blending with alternative routings combined with security stocks: a new approach in a mining supply chain
Abstract: 
 In the OCP phosphate supply chain, source ores (SOs) are extracted according to a tactical extraction programme, constrained by geological conditions that constantly limit and modify the variety of available SOs. Then SOs are blended to get merchantable ores (MOs) respecting composition constraints and ordered by internal (phosphoric acid plant) or external (export) customers. The blending process is performed in a dry blending plant, possibly followed by treatments in a washing plant which modifies the SOs weights and compositions. The choice of alternative routings and blends depends on orders book and SOs availability in the dry blending area or present on mine. To improve the performance in meeting a rolling 4-weeks orders book, a quadratic model was created and implemented. It optimises jointly: (i) for each order, the routing and the SOs quantities used in the dry blending plant; (ii) the SOs quantities transferred from the mine; (iii) security stocks to face some unforeseen change in the MO book order, and the slight instability of the SO chemical composition that triggers a SO multiplication to be contained. The performance of the linearised model has led the relevant OCP site to develop and use an extended version of this model.
Journal: International Journal of Production Research
Pages: 6419-6436
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1814443
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1814443
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Template-Type: ReDIF-Article 1.0
Author-Name: Najat Almasarwah
Author-X-Name-First: Najat
Author-X-Name-Last: Almasarwah
Author-Name: Gürsel A. Süer
Author-X-Name-First: Gürsel A.
Author-X-Name-Last: Süer
Title: Consideration of processing time dissimilarity in batch-cyclic scheduling of flowshop cells
Abstract: 
 Flowshop scheduling methods that appear in the literature assume that products are processed in either batch mode or cyclic mode. In batch mode, a product starts after another product is completely processed. On the other hand, in cyclic mode, products are run in mixed mode with unit transfer. In this paper, a new scheduling method, the batch-cyclic scheduling method, is proposed to schedule the products. In the proposed method, multiple sets of products (Cyclic Sets) are selected first and then products in each cyclic set are run in mixed mode. Overall, the general solution approach consists of three phases: (1) family formation based on processing similarity; (2) subfamily formulation based on a processing time dissimilarity (proposed mathematical model); (3) product scheduling using the batch-cyclic method (proposed mathematical model). As in the cyclic method, batch-cyclic scheduling is feasible when setup times are negligible. Due to the lack of work in this newly proposed batch-cyclic method, it is compared with the batch method. Additionally, the performance of the three-phase approach is compared with the two-phase approach using 27 scenarios. The results show that the proposed three-phase approach minimises the number of machines and lowers makespan when the bottleneck machine shifts.
Journal: International Journal of Production Research
Pages: 6544-6563
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1818863
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1818863
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Template-Type: ReDIF-Article 1.0
Author-Name: Qinyu Song
Author-X-Name-First: Qinyu
Author-X-Name-Last: Song
Author-Name: Yaodong Ni
Author-X-Name-First: Yaodong
Author-X-Name-Last: Ni
Author-Name: Dan A. Ralescu
Author-X-Name-First: Dan A.
Author-X-Name-Last: Ralescu
Title: Product configuration using redundancy and standardisation in an uncertain environment
Abstract: 
 Product configuration involves selecting common components/modules of individualised products. This is done according to customer requirements under mass customisation. However, the strategies adopted by most existing product configurators are often extreme, with either total diversity (mass personalisation) or standardised products (a limited set of products). In order to investigate the intermediate case in this situation, a new uncertain decision model is proposed in this paper. The aim is to find the optimal product configuration using a redundancy and standardisation strategy that minimises the total costs. In this model, customer requirements are defined and assembly sequences are initially constructed. Then, a manufacturing approach of modular multi-platform assembly is employed to increase uniqueness in mass customisation. Next, the uncertain decision model for product configuration is linearised and solved by uncertainty theory using CPLEX 12.8. Finally, a sensitivity analysis is conducted to suggest optimal platform number and producing strategies and determine the final customised product specification. From a case study of the mobile phone, we found that standardisation performs better than the redundancy strategy and a flexible platform strategy effectively reduces production costs.
Journal: International Journal of Production Research
Pages: 6451-6470
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1815888
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1815888
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:21:p:6451-6470




Template-Type: ReDIF-Article 1.0
Author-Name: Abdelkrim R. Yelles-Chaouche
Author-X-Name-First: Abdelkrim R.
Author-X-Name-Last: Yelles-Chaouche
Author-Name: Evgeny Gurevsky
Author-X-Name-First: Evgeny
Author-X-Name-Last: Gurevsky
Author-Name: Nadjib Brahimi
Author-X-Name-First: Nadjib
Author-X-Name-Last: Brahimi
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Reconfigurable manufacturing systems from an optimisation perspective: a focused review of literature
Abstract: 
 The concept of reconfigurable manufacturing systems (RMSs) is a current subject that has attracted intensive research. This latter covers the entire RMS life cycle, from the design to the exploitation phase, and includes several important problems requiring the use of optimisation. The objective of this paper is to survey research publications related to RMS optimisation problems and their solution methods. For this, the types of RMS and their components are described. Subsequently, relevant objective functions and performance indicators of RMS are presented. In addition, an overview of the most used solution approaches and a classification of optimisation problems are proposed. Finally, a detailed analysis, our conclusions, and suggestions for future research are provided.
Journal: International Journal of Production Research
Pages: 6400-6418
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1813913
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1813913
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Template-Type: ReDIF-Article 1.0
Author-Name: Mejdal A. Alqahtani
Author-X-Name-First: Mejdal A.
Author-X-Name-Last: Alqahtani
Author-Name: Myong K. Jeong
Author-X-Name-First: Myong K.
Author-X-Name-Last: Jeong
Author-Name: Elsayed A. Elsayed
Author-X-Name-First: Elsayed A.
Author-X-Name-Last: Elsayed
Title: Spatially weighted graph theory-based approach for monitoring faults in 3D topographic surfaces
Abstract: 
 Three-dimensional (3D) optical systems have been recently deployed for the assessment of 3D topography of finished products during manufacturing processes. Although the 3D topographic data contain rich information about the product and manufacturing processes, existing monitoring approaches are incapable of capturing the complex characteristics between the topographic values, which makes them ineffective in detecting local and spatial surface faults. We develop a spatially weighted graph theory-based approach for accurate monitoring of 3D topographic surfaces. We imporove the representation of surface characteristicsby proposing the in-control multi-region surface segmentation algorithm, which segments the observed topographic pixels into clusters according to the information learned from in-control surfaces. We propose the maximum local spatial randomness feature for the effective description of local and spatial topographic characteristics. After representing the surface characteristics as a spatially weighted graph network, we monitor its connectivity through the developed spatial graph connectivity statistic. The proposed approach is robust in detecting and locating different forms of local and spatial faults that appear on simulated and real-life topographic surfaces and outperforms the existing monitoring approaches.
Journal: International Journal of Production Research
Pages: 6382-6399
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1812755
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1812755
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Template-Type: ReDIF-Article 1.0
Author-Name: Kung-Jeng Wang
Author-X-Name-First: Kung-Jeng
Author-X-Name-Last: Wang
Author-Name: Ying-Hao Lee
Author-X-Name-First: Ying-Hao
Author-X-Name-Last: Lee
Author-Name: Septianda Angelica
Author-X-Name-First: Septianda
Author-X-Name-Last: Angelica
Title: Digital twin design for real-time monitoring – a case study of die cutting machine
Abstract: 
 Digital twin (DT) is a core technology that enables the integration among physical machines, tools, material handling and warehousing, and real-time manufacturing decisions. In this study, a DT framework is proposed for the real-time monitoring of conventional machines to connect isolated machines to an interconnected system and monitor machine conditions in real-time. We implement a DT for a die cutting machine. A dashboard-based mission centre is created to display the real-time condition of the machine. The mission centre is composed of three main functions: real-time machine monitoring, overall equipment effectiveness, and order scheduling. Compared with existing approaches with a barrier of high investment and/or high design complexity, this study proposes an economic DT framework composed of conventional machine structure but has a tolerable level of industrial Internet of things capability.
Journal: International Journal of Production Research
Pages: 6471-6485
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1817999
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1817999
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Template-Type: ReDIF-Article 1.0
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Yaxin Pang
Author-X-Name-First: Yaxin
Author-X-Name-Last: Pang
Author-Name: Yinfeng Xu
Author-X-Name-First: Yinfeng
Author-X-Name-Last: Xu
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Title: Heuristic algorithms for truck scheduling of cross-docking operations in cold-chain logistics
Abstract: 
 Nowadays cross-docking operations play a significant role in the cold-chain logistics. This paper addresses the cold-chain cross-docking truck scheduling problem where two types of products, i.e. refrigerated and frozen ones, demand separate trucks and storage areas with distinct temperature settings during their storage and transportation. We present a mixed-integer linear programming model with the objective of minimising the total operational costs that consist of inbound truck arrival penalties for violating contracted time windows, product delivery tardiness penalties, inventory costs and outbound truck transportation costs. Due to the strong NP-hardness of the considered problem, we solve it in two phases where the inbound truck arrival schedule and the schedule of outbound truck departure together with product processing are produced, respectively. Four heuristic algorithms are proposed to generate complete solutions of the considered two-stage problem, which are the combinations of two solution frameworks for the first stage and two methods for the second stage. Computational experiments are carried out to verify the effectiveness and efficiency of the proposed heuristic algorithms in terms of the solution quality and running time, respectively.
Journal: International Journal of Production Research
Pages: 6579-6600
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1821118
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1821118
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanju Zhou
Author-X-Name-First: Yanju
Author-X-Name-Last: Zhou
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Author-Name: Yumei Zeng
Author-X-Name-First: Yumei
Author-X-Name-Last: Zeng
Title: Borrowing or crowdfunding: a comparison of poverty alleviation participation modes considering altruistic preferences
Abstract: 
 In developing countries, farmers lack capital for market-oriented production and information for making informed production and sales decisions. To alleviate poverty, many enterprises, such as JD Finance, have developed crowdfunding poverty alleviation initiatives for poor farmers. In this mode, although enterprises provide a crowdfunding platform for farmers to raise production funds, farmers may incur sales losses. In this study, we investigate a fundamental question: how can we choose an optimal mode between crowdfunding and the traditional mode? Our analysis reveals that the optimal selection depends on the interaction of the consumer's willingness-to-pay and the cost coefficient for quality investment. Additionally, the degree of risk aversion, the lending rate, demand uncertainty and crowdfunding risk affect farmer selection. We demonstrate that when the scale of altruistic consumers is relatively small, the proportion of altruistic consumers and their motivation intensity are two interacting forces that steer the farmer's mode choice. Otherwise, a farmer's preferred mode choice relates only to the latter, and the former affects only the pricing strategy under the crowdfunding mode. Our study not only contributes to the emerging poverty alleviation literature but also provides managerial insights regarding the selection of the optimal mode for poverty alleviation for farmers.
Journal: International Journal of Production Research
Pages: 6564-6578
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1821117
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1821117
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Template-Type: ReDIF-Article 1.0
Author-Name: Haitao Liu
Author-X-Name-First: Haitao
Author-X-Name-Last: Liu
Author-Name: Zhaoxia Guo
Author-X-Name-First: Zhaoxia
Author-X-Name-Last: Guo
Author-Name: Zhengzhong Zhang
Author-X-Name-First: Zhengzhong
Author-X-Name-Last: Zhang
Title: A hybrid multi-level optimisation framework for integrated production scheduling and vehicle routing with flexible departure time
Abstract: 
 This paper investigates an integrated scheduling problem of production and outbound distribution with flexible vehicle departure time in a time-sensitive make-to-order supply chain. We develop a hybrid multi-level optimisation framework by decomposing the problem into three sub-problems, including vehicle assignment, parallel machines scheduling and distribution scheduling. In this framework, we propose an efficient procedure to obtain the optimal vehicle departure time and utilise metaheuristics and heuristics to obtain the values of other decision variables. Results from extensive numerical experiments indicate that the proposed framework can solve small-scale instances optimally, and for large-scale instances it also shows the better performance than the compared genetic algorithm in terms of convergence and solution quality. Besides, the distribution cost can be reduced by setting flexible vehicle departure time.
Journal: International Journal of Production Research
Pages: 6615-6632
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1821927
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1821927
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanyan Zheng
Author-X-Name-First: Yanyan
Author-X-Name-Last: Zheng
Author-Name: Yingxue Zhao
Author-X-Name-First: Yingxue
Author-X-Name-Last: Zhao
Author-Name: Xiaoge Meng
Author-X-Name-First: Xiaoge
Author-X-Name-Last: Meng
Title: Market entrance and pricing strategies for a capital-constrained remanufacturing supply chain: effects of equity and bank financing on circular economy
Abstract: 
 This paper examines market entrance and pricing strategies for a remanufacturer with capital constraint and competition from an original equipment manufacturer. In the study, the remanufacturer is divided into two types, namely the H-type and L-type, and is assumed to have access to bank loans and equity financing to ease the capital constraint. With the Nash game, it is found that (i) if remanufacturing is costly, the remanufacturer will choose partial remanufacturing and not enter into the remanufacturing market until the equity financing ratio excesses a certain threshold. (ii) A H-type remanufacturer is more flexible in term of market entrance than a L-type remanufacturer. (iii) The remanufacturer’s profit increases first and then decreases in the equity ratio. (iv) Equity ratio and interest rate have opposite effects on the pricing of the new and remanufactured products. Furthermore, with some research extensions, it is exhibited that the results and managerial implications developed in the paper hold well for different financing modes and the random demand setting, and hence are robust to a good extent.
Journal: International Journal of Production Research
Pages: 6601-6614
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1821926
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1821926
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Template-Type: ReDIF-Article 1.0
Author-Name: Jin Wang
Author-X-Name-First: Jin
Author-X-Name-Last: Wang
Author-Name: Hainan Guo
Author-X-Name-First: Hainan
Author-X-Name-Last: Guo
Author-Name: Kwok-Leung Tsui
Author-X-Name-First: Kwok-Leung
Author-X-Name-Last: Tsui
Title: Two-stage robust optimisation for surgery scheduling considering surgeon collaboration
Abstract: 
 Operating rooms (ORs) account for a significant proportion of the costs of maintaining a hospital. Surgery scheduling is optimised to reduce the costs in ORs. However, an important issue that directly affects surgery scheduling is often neglected, i.e. surgeon collaboration. In reality, a surgery requires two surgeons: the main surgeon and an assistant. The surgeon of one surgery might be assigned as the assistant of another surgery. Thus, this paper proposes a two-stage robust model that considers such collaborations. In Stage 1, it determines surgery allocations and surgeon assignments, while in Stage 2, the start time of each surgery is decided. The properties of the solutions are detected, based on which we develop a simple algorithm to solve the two-stage model. In addition, the column-and-constraint generation algorithm is applied to solve the model with a large number of surgeries. The numerical experimentation shows the good performances of the proposed models and algorithms.
Journal: International Journal of Production Research
Pages: 6437-6450
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1815887
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1815887
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Template-Type: ReDIF-Article 1.0
Author-Name: Zsuzsanna Hauck
Author-X-Name-First: Zsuzsanna
Author-X-Name-Last: Hauck
Author-Name: Boualem Rabta
Author-X-Name-First: Boualem
Author-X-Name-Last: Rabta
Author-Name: Gerald Reiner
Author-X-Name-First: Gerald
Author-X-Name-Last: Reiner
Title: Analysis of screening decisions in inventory models with imperfect quality items
Abstract: 
 We consider an Economic Order Quantity (EOQ) model with imperfect quality items. All the items undergo a quality screening process for which both the cost and the defect detection rate depend on the time devoted to this operation. Contrary to most previous research in the field, the speed of screening is taken as a decision variable in the presented model jointly with the order quantity. Additionally, we introduce various functional forms for the screening cost and defect detection functions. In particular, nonlinear forms lead to nonconvexities in the total cost function consisting of multiple cost components, e.g. inspection cost, penalty costs, etc. We solve the model analytically for a selected set of assumptions and provide numerical examples and sensitivity analysis. The results provide interesting insights. While lower screening costs motivate longer screening times, the effectiveness of this operation is only obtained in combination with the reliability of the defect detection method. It is also observed that reducing return rates and improving customer satisfaction can be achieved by adjusting the operational parameters, without a significant increase in system cost or new investments.
Journal: International Journal of Production Research
Pages: 6528-6543
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1818862
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1818862
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Template-Type: ReDIF-Article 1.0
Author-Name: Nelly Bart
Author-X-Name-First: Nelly
Author-X-Name-Last: Bart
Author-Name: Tatyana Chernonog
Author-X-Name-First: Tatyana
Author-X-Name-Last: Chernonog
Author-Name: Tal Avinadav
Author-X-Name-First: Tal
Author-X-Name-Last: Avinadav
Title: Revenue-sharing contracts in supply chains: a comprehensive literature review
Abstract: 
 Revenue sharing contracts (RSCs) have gained considerable popularity over the past two decades—particularly among prominent platform distributors such as the Apple App Store, Google Play, and Amazon— and have therefore attracted a great deal of research attention in the domain of supply-chain management. This study is the first to review the literature dealing with RSCs, a literature in which the number of articles has been growing consistently over the years. Specifically, we aim to provide a comprehensive overview of the state of the art of the research field, and to identify potentially fruitful areas for further exploration. To this end, we have carried out a content analysis of 148 carefully selected papers that address various aspects of RSCs in the domains of operations research and operations management. Our survey classifies and discusses the reviewed papers along numerous dimensions of interest, including the types of contract they incorporate and the research questions they address. We provide mathematical formulations of the two RSC structures that are most prevalent in research and in practice: (i) a wholesale-price contract that incorporates an added revenue-sharing mechanism; and (ii) a consignment contract with revenue sharing.
Journal: International Journal of Production Research
Pages: 6633-6658
Issue: 21
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1821929
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1821929
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Template-Type: ReDIF-Article 1.0
Author-Name: Meisam Pour-Massahian-Tafti
Author-X-Name-First: Meisam
Author-X-Name-Last: Pour-Massahian-Tafti
Author-Name: Matthieu Godichaud
Author-X-Name-First: Matthieu
Author-X-Name-Last: Godichaud
Author-Name: Lionel Amodeo
Author-X-Name-First: Lionel
Author-X-Name-Last: Amodeo
Title: New models and efficient methods for single-product disassembly lot-sizing problem with surplus inventory decisions
Abstract: 
 This paper addresses the problem of disassembly lot-sizing for the single-product type. Due to some specific characteristics of disassembly systems, surplus inventory can be generated while satisfying the demand for the components. Disposal decisions are considered here to avoid inventory accumulations throughout the planning horizon. Three new mixed-integer programming (MIP) formulations are proposed to model the problem. The formulations differ from each other concerning the quality of the lower bound provided by their linear relaxation, which is an important issue in MIP resolution methods. Two efficient heuristics are also investigated for real-case applications when MIP algorithms are not relevant. The three formulations and the performance of the heuristics are compared based on new randomly generated instances for disassembly lot-sizing problems. As a managerial insight, the disposal decisions in disassembly lot-sizing models are relevant to save inventory costs.
Journal: International Journal of Production Research
Pages: 6898-6918
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1829148
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1829148
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:22:p:6898-6918




Template-Type: ReDIF-Article 1.0
Author-Name: Yaroslav Garashchenko
Author-X-Name-First: Yaroslav
Author-X-Name-Last: Garashchenko
Author-Name: Miroslaw Rucki
Author-X-Name-First: Miroslaw
Author-X-Name-Last: Rucki
Title: Part decomposition efficiency expectation evaluation in additive manufacturing process planning
Abstract: 
 In this paper, research results are presented and discussed on the efficient use of additive manufacturing (AM) machine workspace with a specific focus on the features of part construction and decomposition, which provide savings of material and energy. Statistical analysis of the distribution of material by subspaces revealed some relationship between construction features and the effectiveness of part decomposition. The initial triangulated model was converted into a voxel model, and the latter is analyzed with the proposed algorithm. The workspace of an AM machine was divided into subspaces of the same volume with parallel steadily distributed planes perpendicular to the coordinate axes. Based on the models of typical industrial parts, it was proving that the algorithm was able to analyze the effectiveness of part decomposition. Moreover, some indexes were proposed to allow the quantitative analysis of part decomposition and packing (workspace planning task) effectiveness. The proposed index of the specific volume of utilised workspace enabled the minimising of the cost of given parts by using AM processes.
Journal: International Journal of Production Research
Pages: 6745-6757
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1824084
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1824084
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Template-Type: ReDIF-Article 1.0
Author-Name: Alnour Ribault
Author-X-Name-First: Alnour
Author-X-Name-Last: Ribault
Author-Name: Samuel Vercraene
Author-X-Name-First: Samuel
Author-X-Name-Last: Vercraene
Author-Name: Sébastien Henry
Author-X-Name-First: Sébastien
Author-X-Name-Last: Henry
Author-Name: Yacine Ouzrout
Author-X-Name-First: Yacine
Author-X-Name-Last: Ouzrout
Title: Economic optimisation of cold production: a matheuristic with artificial neural network approach
Abstract: 
 In this paper, the economic optimisation of cold storage is studied. A modern cold room is mainly composed of compressors, a tank to store heat-transfer fluid and cold rooms. The main cost is incurred by energy consumption and maintenance. The price of electricity, which is known in advance, varies during the day. Production schedules that entail higher risks of compressor wear, and thus high maintenance costs, have to be avoided. The temperature inside the cold rooms must be maintained within the allowed range, and complex thermodynamic processes make it difficult to predict temperature. The tank has a limited capacity. This paper presents the first model optimising the management cost of a cold store with a tank. Maintenance costs are considered for compressors, and Artificial Neural Networks are used to forecast the temperatures in the cold rooms. An optimal Dynamic Programme is designed for the case with one cold room and a matheuristic algorithm is presented for the general case with several cold rooms. A comparison with a classical hysteresis controller shows significant savings. The impact of storage capacity on operating costs is evaluated, after which the influence of the maintenance cost value is discussed.
Journal: International Journal of Production Research
Pages: 6941-6962
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1831705
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1831705
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Template-Type: ReDIF-Article 1.0
Author-Name: Yang Song
Author-X-Name-First: Yang
Author-X-Name-Last: Song
Author-Name: Tijun Fan
Author-X-Name-First: Tijun
Author-X-Name-Last: Fan
Author-Name: Yuewu Tang
Author-X-Name-First: Yuewu
Author-X-Name-Last: Tang
Author-Name: Fengli Zou
Author-X-Name-First: Fengli
Author-X-Name-Last: Zou
Title: Quality information acquisition and ordering decisions with risk aversion
Abstract: 
 This paper investigates a retailer’s quality information acquisition and ordering decisions in the presence of risk aversion. We formulate a newsvendor model and derive the retailer’s optimal order quantity under two scenarios, one with and one without quality information acquisition, by minimising expected risk based on the CVaR criterion. Then, we compare the optimal ordering quantities and the profits under the two scenarios and discuss the quality information acquisition decision. Our results show that it will be more effective for the retailer to acquire quality information if the retailer exhibits greater risk aversion or the information is more precise; the retailer would order less when she is more risk-averse and the impact of risk aversion would be reduced by quality information acquisition. Interestingly, the retailer’s profits may decrease even when the quality information is more precise.
Journal: International Journal of Production Research
Pages: 6864-6880
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1828640
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1828640
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhongjun Tang
Author-X-Name-First: Zhongjun
Author-X-Name-Last: Tang
Author-Name: Shunpeng Dong
Author-X-Name-First: Shunpeng
Author-X-Name-Last: Dong
Title: A total sales forecasting method for a new short life-cycle product in the pre-market period based on an improved evidence theory: application to the film industry
Abstract: 
 It is challenging to forecast total sales of short life-cycle products due to a lack of historical sales data. Multi-source information combination methods make it possible to depict different kinds of characteristics and features, given a limited volume of samples. Evidence theory is a common approach used for multi-source combinations. This paper proposes a new method, named ‘Multi-Evidence Dynamic Weighted Combination Forecasting (MEDWCF)’, based on improvements in the application of Evidence theory. Two kinds of machine learning methods are used to solve the basic probability assignment generation problem pertaining to Evidence theory, so a dynamic update combination algorithm is proposed. These innovations improve the classical one-step static combination rules. Samples of 313 films launched within 2016 and 2017 proved that compared with other forecasting methods, MEDWCF has more effectiveness and better generalisation ability. Effective product sales forecast by MEDWCF may help managers make correct decisions in manufacturing and marketing before the product launched.
Journal: International Journal of Production Research
Pages: 6776-6790
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1825861
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1825861
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:22:p:6776-6790




Template-Type: ReDIF-Article 1.0
Author-Name: Utku Girit
Author-X-Name-First: Utku
Author-X-Name-Last: Girit
Author-Name: Meral Azizoğlu
Author-X-Name-First: Meral
Author-X-Name-Last: Azizoğlu
Title: Rebalancing the assembly lines with total squared workload and total replacement distance objectives
Abstract: 
 Assembly line balancing is an important and well recognised operations research problem. The current line balance may not stay optimal, even feasible, due to the disruptions in one or more workstations. In this study, after the disruption, we aim to rebalance the assembly line by considering the trade-off between workload balancing (fairness measure) and total replacement distance for the tasks assigned to the different workstations (stability measure).We try to generate all non-dominated objective function vectors for the defined fairness and stability measures. Two algorithms are developed: exact algorithm (classical approach) and tabu search algorithm. The results of the experiments have shown that the classical approach returns exact non-dominated objective vectors with up to 40 tasks and 7 workstations in one hour, and the tabu search algorithm returns approximate non-dominated objective vectors that are very close to their exact counterparts and can solve large sized instances with up to 94 tasks and 7 workstations in less than 10 s.
Journal: International Journal of Production Research
Pages: 6702-6720
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1823027
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1823027
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:22:p:6702-6720




Template-Type: ReDIF-Article 1.0
Author-Name: Desheng Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Wu
Author-Name: Chenghao Zhang
Author-X-Name-First: Chenghao
Author-X-Name-Last: Zhang
Author-Name: Yuchen Pan
Author-X-Name-First: Yuchen
Author-X-Name-Last: Pan
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: The supply chain effects on order strategy of cross-shareholdings
Abstract: 
 This study examines the joint impact of the vertical cross-shareholdings and external financing, including trade credit and bank loans, on the order strategy of a capital-constrained retailer. We set the target retailer and his supplier, which are connected with vertical cross-shareholdings, in the extended Cournot and Stackelberg game. The capital-constrained retailer could raise external financing when he has exhausted his own cash. Besides, the retailer may be faced with the random shock result from the other business. We use optimal response function to model how the capital-constrained retailer determines his order quantity under cross-shareholdings in response to different market conditions (such as his own cash level and other competitor’s order strategy). We find that, the retailer orders more under cross-shareholdings if the retailer is well-funded with his own cash or external financing, resulting in a win-win situation for the supplier and retailer. However, if the retailer has run out of all his cash and credit, the cross-shareholdings have no effect on the retailer’s order strategy. Thus, it helps the capital-constrained retailer to acquire competitive advantage that he could be well-funded with external financing under cross-shareholdings.
Journal: International Journal of Production Research
Pages: 6848-6863
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1828639
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1828639
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Template-Type: ReDIF-Article 1.0
Author-Name: Yahel Giat
Author-X-Name-First: Yahel
Author-X-Name-Last: Giat
Author-Name: Michael Dreyfuss
Author-X-Name-First: Michael
Author-X-Name-Last: Dreyfuss
Title: The window fill rate in a periodic review inventory system with order crossover
Abstract: 
 Many periodic review inventory studies make the simplifying assumption that orders do not crossover, that is, that they are delivered in the same sequence as they were issued. In many real-life situations, however, long international shipping routes result with frequent crossovers. Accordingly, we investigate a periodic review inventory system with backlogged compound Poisson demand in which order may crossover. We develop an exact formula for the window fill rate, i.e. the probability for customers to receive service within their tolerable wait. Evaluating the window fill rate using the exact formula is very time consuming and therefore an efficient approximation formula that assumes that orders do not crossover is considered. Lead times of actual global supply lines demonstrate that this approximation results in considerable overstocking when customers' tolerable wait is high, or understocking when the tolerable wait is low. Replacing the actual lead times distribution with the effective lead times distribution improves the approximation formula's accuracy considerably. This result allows us to show how the window fill rate depends on the model parameters and make practical observations about the trade-off between the tolerable wait and stock levels needed to maintain a required level of window fill rate.
Journal: International Journal of Production Research
Pages: 6791-6808
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1825863
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1825863
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Template-Type: ReDIF-Article 1.0
Author-Name: Chung-Chi Hsieh
Author-X-Name-First: Chung-Chi
Author-X-Name-Last: Hsieh
Author-Name: Hung-Lin Chang
Author-X-Name-First: Hung-Lin
Author-X-Name-Last: Chang
Title: Sourcing with recycled materials: a contingent sourcing model with supply unavailability and setup time uncertainty for ripple effect mitigation
Abstract: 
 In this study, a multi-period contingent sourcing model for sustainable sourcing is developed to mitigate the ripple effect caused by supply disruption. In this model, the manufacturer's main supplier is a recycled materials supplier who is subject to random disruptions and whose materials have setup time uncertainty. His backup supplier is a virgin materials supplier who is reliable. We investigate how the manufacturer's attitude towards risk affects his absorptive-capacity decision making and his sourcing strategy, both of which have not been addressed in the related literature. Our analyses reveal that the manufacturer's decisions are strategic substitutes as cost-related parameters (except the product holding cost) vary when he is risk-neutral and can become strategic complements when he is averse to risk. Furthermore, the manufacturer can improve contingent sourcing performance by leveraging adaptive capacity through choosing the proper timing at which to switch to the backup supplier. Finally, the manufacturer's sourcing strategy is sensitive to attitude towards risk when the cost difference between virgin and recycled materials is within a specific range over which higher restorative capacity from the main supplier and lower setup time uncertainty with recycled materials are required to justify a more risk-averse manufacturer's adoption of contingent sourcing.
Journal: International Journal of Production Research
Pages: 6677-6701
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1822558
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1822558
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuchen Pan
Author-X-Name-First: Yuchen
Author-X-Name-Last: Pan
Author-Name: Shuzhen Chen
Author-X-Name-First: Shuzhen
Author-X-Name-Last: Chen
Author-Name: Desheng Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Wu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: CF-NN: a novel decision support model for borrower identification on the peer-to-peer lending platform
Abstract: 
 With the prevalence of online individual micro-loans, an increasing number of peer-to-peer lending platforms have been established during the last ten years. One main problem for these platforms is to accurately identify the ‘bad’ applicants with high default risk. In this paper, we propose a CF-NN model that combines neural network and collaborative filtering for identifying high-risk borrowers. It is demonstrated in the experimental analysis that the CF-NN model significantly outperforms other widely used data mining models on the identification of bad borrowers. Moreover, the experimental results show that, to achieve the best performance in borrower identification, the CF-NN model should be equipped with parameters of intermediate values.
Journal: International Journal of Production Research
Pages: 6963-6974
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1832270
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1832270
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Template-Type: ReDIF-Article 1.0
Author-Name: André Felipe Henriques Librantz
Author-X-Name-First: André Felipe Henriques
Author-X-Name-Last: Librantz
Author-Name: Ivanir Costa
Author-X-Name-First: Ivanir
Author-X-Name-Last: Costa
Author-Name: Mauro de Mesquita Spinola
Author-X-Name-First: Mauro de Mesquita
Author-X-Name-Last: Spinola
Author-Name: Geraldo Cardoso de Oliveira Neto
Author-X-Name-First: Geraldo Cardoso
Author-X-Name-Last: de Oliveira Neto
Author-Name: Leandro Zerbinatti
Author-X-Name-First: Leandro
Author-X-Name-Last: Zerbinatti
Title: Risk assessment in software supply chains using the Bayesian method
Abstract: 
 In recent years, the software production industry has experienced significant changes largely caused by extensive growth of globalisation, outsourcing, and competitive pressure. With these changes, risks in the software supply chain (SSC) have become a growing concern. Such risks include product tampering during development or delivery, potential compromises in quality and assurance due to software defects, production delays, and increased production costs. In this context, this study is aimed at evaluating the primary risks in the software supply chain using Bayesian belief networks combined with the analytic hierarchy process and noisy-OR (a generalisation of the logical OR) techniques to reduce the number of queries required of a given decision maker. A numerical example was presented to illustrate the application in which software suppliers were ranked according to their level of risk. The results indicated that, by using the proposed model, decision makers would be able to select a low-risk supplier by evaluating the probability of system failure caused by tampering or the introduction of defective code in the software. In addition, the proposed approach contributes to a better understanding of the risk main factors in an SSC and could be used to support managerial decision-making related to software products.
Journal: International Journal of Production Research
Pages: 6758-6775
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1825860
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1825860
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Template-Type: ReDIF-Article 1.0
Author-Name: Nadjib Brahimi
Author-X-Name-First: Nadjib
Author-X-Name-Last: Brahimi
Author-Name: Ali Cheaitou
Author-X-Name-First: Ali
Author-X-Name-Last: Cheaitou
Author-Name: Pierre Cariou
Author-X-Name-First: Pierre
Author-X-Name-Last: Cariou
Author-Name: Dominique Feillet
Author-X-Name-First: Dominique
Author-X-Name-Last: Feillet
Title: An exact algorithm for the single liner service design problem with speed optimisation
Abstract: 
 This paper models a single liner service design and operations problem. The model selects the ports to be included, their sequence, the sailing speed of vessels, the number of vessels and the amounts of cargo to transport by the service. The objective is to maximise profit. First, a relaxation with a mixed-integer nonlinear programming (MINLP) formulation is proposed. We show how to obtain the optimal speed value. Once this value is obtained, the mathematical programming formulation becomes a mixed-integer linear program (MILP). Then, a two-step exact algorithm is presented to solve the problem. Using real data, the optimal solution was found in less than 1 min for small-size problems and in few hours for relatively large-size problems. More tests were carried out on randomly generated data sets with up to 25 ports. The results of these tests are rather promising, and they enabled us to identify the performance limits of the algorithm.
Journal: International Journal of Production Research
Pages: 6809-6832
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1828636
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1828636
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Template-Type: ReDIF-Article 1.0
Author-Name: Oussama Meski
Author-X-Name-First: Oussama
Author-X-Name-Last: Meski
Author-Name: Farouk Belkadi
Author-X-Name-First: Farouk
Author-X-Name-Last: Belkadi
Author-Name: Florent Laroche
Author-X-Name-First: Florent
Author-X-Name-Last: Laroche
Author-Name: Mathieu Ritou
Author-X-Name-First: Mathieu
Author-X-Name-Last: Ritou
Author-Name: Benoit Furet
Author-X-Name-First: Benoit
Author-X-Name-Last: Furet
Title: A generic knowledge management approach towards the development of a decision support system
Abstract: 
 The fourth industrial revolution is increasingly implemented in most fields and categories of industry. The use of several highly developed technologies generates huge amounts of heterogeneous data and knowledge, hence the need to manage it in order to facilitate its reuse. This article proposes a global approach of knowledge management, from the analysis and development of the knowledge base structuring models, to the implementation phase using knowledge engineering tools. This research work is part of a global knowledge-based decision support framework that ensures several axes of decision support, this article deals with the diagnosis axis. It provides analysis and comprehension of the failures occurring during production. The approach has been implemented as a first demonstrator tested in a real case study: the aeronautical mechanical machining industry. This article details the issues of this implementation and its interest for the validation of the approach.
Journal: International Journal of Production Research
Pages: 6659-6676
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1821930
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1821930
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Template-Type: ReDIF-Article 1.0
Author-Name: Yangyang Sun
Author-X-Name-First: Yangyang
Author-X-Name-Last: Sun
Author-Name: Chuangyin Dang
Author-X-Name-First: Chuangyin
Author-X-Name-Last: Dang
Author-Name: Gengzhong Feng
Author-X-Name-First: Gengzhong
Author-X-Name-Last: Feng
Title: Optimal versioning strategies for software firms in the competitive environment
Abstract: 
 Software-as-a-service (SaaS) is gaining tremendous popularity in the enterprise software releases, which has brought the growing challenge for the incumbent used to adopt the on-premise licensing model. In this paper, we focus on the optimal versioning strategy problem of the incumbent when he faces the competition from the entrant who releases the SaaS software. He can choose from providing the upgraded on-premise software, turning to offer the SaaS version of the software, and releasing both the versions. We indicate that releasing both versions won't be the optimal choice in the competitive environment. When the upgrade cost is above a certain value, and the gap of value is below a threshold positively linear correlated with the upgrade cost, the incumbent prefers the SaaS strategy. Otherwise, the on-premise strategy generates the highest profit. A special case is that in the medium switching cost environment, the SaaS strategy can be optimal for all possible values of upgrade cost. Finally, We consider the problem in the presence of network effect and in the uncovered market setting. The results provide effective managerial insights into the strategy selection for the incumbent.
Journal: International Journal of Production Research
Pages: 6881-6897
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1828641
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1828641
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Template-Type: ReDIF-Article 1.0
Author-Name: Qiangqiang Wang
Author-X-Name-First: Qiangqiang
Author-X-Name-Last: Wang
Author-Name: Bin Zhang
Author-X-Name-First: Bin
Author-X-Name-Last: Zhang
Title: A guarantee credit model with substitutable product competition
Abstract: 
 To understand how retailer competition affects supply chain partners’ operational and financial decisions under guarantee credit financing (GCF), we examine a supply chain system composed of a capital-constrained retailer, a capital-abundant retailer and a manufacturer in the presence of substitutable product competition. By identifying the strategic interaction among the retailers and the manufacturer, we find that when the production cost is low, the retailers’ equilibrium order quantities depend on their optimal equilibrium profits, otherwise on the dominant retailer's and the manufacturer's optimal equilibrium profits. If both GCF and BCF are viable, then when the production cost is smaller than a certain threshold, GCF is the unique financing equilibrium, and BCF otherwise. We also analyse the extensions of general demand distribution and positive risk-free rate under GCF. We also find that competition hurts the weak retailer's profit but increases the dominant retailer's profit if the manufacturer's production cost exceeds a certain threshold.
Journal: International Journal of Production Research
Pages: 6919-6940
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1830195
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1830195
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Template-Type: ReDIF-Article 1.0
Author-Name: Sricharan Chirra
Author-X-Name-First: Sricharan
Author-X-Name-Last: Chirra
Author-Name: Rakesh D. Raut
Author-X-Name-First: Rakesh D.
Author-X-Name-Last: Raut
Author-Name: Dinesh Kumar
Author-X-Name-First: Dinesh
Author-X-Name-Last: Kumar
Title: Barriers to sustainable supply chain flexibility during sales promotions
Abstract: 
 In today’s market, sales promotional schemes have spun out to be essential for promoting outfits. Nonetheless, due to the sudden ascent in sales, the subsequent demand uncertainty calls for the high flexibility in supply chains. The present work examines the barriers to flexibility in the Indian automobile supply chains under such an environment from a sustainability viewpoint, an indispensable element of the present-day supply chains. In view of the literature and the descriptive survey led, 20 barriers have been identified. Through the analytical investigation directed, a numerical index value for the sustainable supply chain flexibility barriers is developed via graph-theoretical and matrix approach. Findings, along with the sensitivity analysis, conducted establish that the barriers at the supply chain’s procurement function have the highest impact in inhibiting the sustainable supply chain flexibility, thus significantly affecting the firm performance during sales promotional schemes. The obtained barrier index can be utilised for assessing the performance of all the companies across the industry. The model proposed offers valuable discernments to practicing officials in focusing on the significant barriers. This study augments the existing literature by linking the supply chain flexibility, Sustainability, and Sales promotions and thus clubs the three independent research streams.
Journal: International Journal of Production Research
Pages: 6975-6993
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1832272
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1832272
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Template-Type: ReDIF-Article 1.0
Author-Name: Victor Abu-Marrul
Author-X-Name-First: Victor
Author-X-Name-Last: Abu-Marrul
Author-Name: Rafael Martinelli
Author-X-Name-First: Rafael
Author-X-Name-Last: Martinelli
Author-Name: Silvio Hamacher
Author-X-Name-First: Silvio
Author-X-Name-Last: Hamacher
Title: Scheduling pipe laying support vessels with non-anticipatory family setup times and intersections between sets of operations
Abstract: 
 In this paper, we deal with a problem that arises from the oil industry with the need to schedule a pipe laying support vessel fleet responsible for connecting oil wells to production platforms. We model it as an identical parallel machine scheduling problem, considering a particular case where jobs are composed of intersecting sets of operations and with operations partitioned into families. A non-anticipatory family setup time is incurred on three occasions: when a machine changes the execution of operations from one family to another, when the machine reaches its capacity, and before the first operation on each machine. These considerations, along with other scheduling features, make the problem more challenging and attractive to the scheduling literature. We propose three mathematical formulations to solve 72 generated instances, based on actual data, with up to 50 operations to schedule. Among the formulations, the Batch Scheduling presents better results with the smallest gaps, when compared to the best lower bounds obtained. This formulation considers a dispatching rule to sequence operations within batches, generating better solutions in 22 of the 24 largest instances, dominating the other formulations. A Brazilian oil company currently uses this approach in a production system for its tactical planning.
Journal: International Journal of Production Research
Pages: 6833-6847
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1828637
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1828637
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:22:p:6833-6847




Template-Type: ReDIF-Article 1.0
Author-Name: S. Ehsan Hashemi-Petroodi
Author-X-Name-First: S. Ehsan
Author-X-Name-Last: Hashemi-Petroodi
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Sergey Kovalev
Author-X-Name-First: Sergey
Author-X-Name-Last: Kovalev
Author-Name: Mikhail Y. Kovalyov
Author-X-Name-First: Mikhail Y.
Author-X-Name-Last: Kovalyov
Author-Name: Simon Thevenin
Author-X-Name-First: Simon
Author-X-Name-Last: Thevenin
Title: Workforce reconfiguration strategies in manufacturing systems: a state of the art
Abstract: 
 This paper provides a literature review and an analysis of the studies related to workforce reconfiguration strategies as a part of workforce planning for various production environments. The survey demonstrates that these strategies play a crucial role in the resilience and flexibility of manufacturing systems since they help industrial companies to quickly adapt to frequent changes in demand both in terms of volume and product mix. Five strategies are considered: the use of utility, temporary, walking, cross-trained workers, and bucket brigades. They are analysed in the context of mixed and multi-model manual assembly lines, dedicated, cellular, flexible, and reconfigurable manufacturing systems. The review shows that most of the researches on these reconfiguration strategies focus on multi- or mixed-model assembly lines. At the same time, few studies consider workers team reconfiguration in flexible and reconfigurable manufacturing systems. Finally, this paper reveals several promising research directions in workforce reconfiguration planning, namely, the use of both machine and workforce reconfigurations, consideration of the ergonomic aspects, the combination of multiple workforce reconfiguration strategies, the study of workforce reconfiguration in human-robot collaborative systems, and the use of new technologies in human-machine industrial environments.
Journal: International Journal of Production Research
Pages: 6721-6744
Issue: 22
Volume: 59
Year: 2021
Month: 11
X-DOI: 10.1080/00207543.2020.1823028
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1823028
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:22:p:6721-6744




Template-Type: ReDIF-Article 1.0
Author-Name: Fei Qiao
Author-X-Name-First: Fei
Author-X-Name-Last: Qiao
Author-Name: Juan Liu
Author-X-Name-First: Juan
Author-X-Name-Last: Liu
Author-Name: Yumin Ma
Author-X-Name-First: Yumin
Author-X-Name-Last: Ma
Title: Industrial big-data-driven and CPS-based adaptive production scheduling for smart manufacturing
Abstract: 
 Smart manufacturing that involves tight integration of the physical system and cyber system is a hot topic in both industry and academia in the era of the Internet and big data. However, the dynamic and uncertain manufacturing environment introduces a significant adaptive issue of production scheduling, which is one of the pivotal tasks for smart manufacturing. This paper focuses on this problem and proposes a closed-loop adaptive scheduling solution based on the Cyber-Physical Production System (CPPS) with four phases: production data acquisition (PDA), dynamic disturbance identification (DDI), scheduling strategy adjustment (SSA), and schedule scheme generation (SSG). In the DDI phase, in view of the disturbance classification, a disturbance identification procedure based on CPPS monitoring is studied to ensure real-time response. In the SSA phase, an industrial big-data-driven scheduling strategy adjustment method is proposed, which consists of GA-based offline knowledge learning and KNN-based online adjustment, to enhance the system adaptability. We apply and verify the proposed adaptive scheduling solution on an experimental semiconductor manufacturing system, and the results demonstrate that the proposed method outperforms the dynamic scheduling method in terms of multiple objectives under different disturbance levels.
Journal: International Journal of Production Research
Pages: 7139-7159
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1836417
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1836417
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:23:p:7139-7159




Template-Type: ReDIF-Article 1.0
Author-Name: E. Traini
Author-X-Name-First: E.
Author-X-Name-Last: Traini
Author-Name: G. Bruno
Author-X-Name-First: G.
Author-X-Name-Last: Bruno
Author-Name: F. Lombardi
Author-X-Name-First: F.
Author-X-Name-Last: Lombardi
Title: Tool condition monitoring framework for predictive maintenance: a case study on milling process
Abstract: 
 In metal cutting processes, tool condition monitoring has a great importance to prevent surface damage and maintaining the quality of surface finishing. With the development of digitalisation and connection of industrial machines, it has become possible to collect real-time data from various types of sensors (e.g. vibration, acoustic or emission) during the process execution. However, information fusion from multiple sensor signals and tool health prediction still present a big challenge. The aim of this paper is to present a data-driven framework to estimate the tool wear status and predict its remaining useful life by using machine learning techniques. The first part of the framework is dedicated to sensor data preprocessing and feature engineering, while the second part deals with the development of prediction models. Different types of machine learning algorithms are used and compared to find the best result. A case study in a milling process is presented to illustrate the potentialities of the proposed framework for tool condition monitoring.
Journal: International Journal of Production Research
Pages: 7179-7193
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1836419
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1836419
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:23:p:7179-7193




Template-Type: ReDIF-Article 1.0
Author-Name: M. Ostanin
Author-X-Name-First: M.
Author-X-Name-Last: Ostanin
Author-Name: R. Yagfarov
Author-X-Name-First: R.
Author-X-Name-Last: Yagfarov
Author-Name: D. Devitt
Author-X-Name-First: D.
Author-X-Name-Last: Devitt
Author-Name: A. Akhmetzyanov
Author-X-Name-First: A.
Author-X-Name-Last: Akhmetzyanov
Author-Name: A. Klimchik
Author-X-Name-First: A.
Author-X-Name-Last: Klimchik
Title: Multi robots interactive control using mixed reality
Abstract: 
 The paper presents a framework for interactive control of multi robots using mixed reality interfaces. The proposed approach can operate with both single and multi-robot systems, including interaction with industrial manipulators, mobile robots, and unmanned aerial vehicles (UAV). The human–robot interface allows both interactive and physical interaction with the robot. Particular attention is paid to a visualisation of the robots' intent during control. The presented framework has Robotic Operation System (ROS) as a core that can be connected to any robot and mixed reality interface. This allows us to make framework scalable and connect several different mixed reality devices and multiple heterogeneous robots. In the implementation part we connected our framework with Microsoft HoloLens, collaborative robot KUKA IIWA, mobile platform Plato, UAV designed on the basis of dji f450. The proposed framework was tested experimentally with real experimental setups mentioned above. The results showed the capabilities of the mixed reality system for interactive control of different robots' type.
Journal: International Journal of Production Research
Pages: 7126-7138
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1834640
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1834640
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:23:p:7126-7138




Template-Type: ReDIF-Article 1.0
Author-Name: Ana Beatriz Lopes de Sousa Jabbour
Author-X-Name-First: Ana Beatriz
Author-X-Name-Last: Lopes de Sousa Jabbour
Author-Name: Charbel Jose Chiappetta Jabbour
Author-X-Name-First: Charbel Jose
Author-X-Name-Last: Chiappetta Jabbour
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Author-Name: Hengky Latan
Author-X-Name-First: Hengky
Author-X-Name-Last: Latan
Author-Name: David Roubaud
Author-X-Name-First: David
Author-X-Name-Last: Roubaud
Author-Name: Moacir Godinho Filho
Author-X-Name-First: Moacir
Author-X-Name-Last: Godinho Filho
Author-Name: Maciel Queiroz
Author-X-Name-First: Maciel
Author-X-Name-Last: Queiroz
Title: Fostering low-carbon production and logistics systems: framework and empirical evidence
Abstract: 
 This work proposes and empirically tests a new framework for evaluating the relationship between stakeholder pressures, the adoption of low-carbon operations practices and firms’ carbon performance. It seeks to expand upon stakeholder theory and the natural-resource-based view (NRBV) to understand further the role of operations management in a low-carbon environment. Our theoretical hypotheses were tested through the Partial Least Squares method with bias-corrected and accelerated (BCA) bootstrap confidence intervals. The key findings encapsulate a mixture of expected and unexpected research results: (i) stakeholder pressures influence both barriers and motivators for decarbonising operations management practices; (ii) a variety of barriers and motivators significantly affect the adoption of low-carbon operations management practices; (iii) developing positive relationships with stakeholders is important to overcome barriers from the external environment and enhance organisational competitiveness; (iv) low-carbon operations management has an overall effect on firms’ carbon performance; However, unexpectedly: (v) firms seem to face difficulties in understanding stakeholder pressures when developing low-carbon products and logistics, due to a lack of awareness of the sources of barriers to the adoption of low-carbon management practices; (vi) in terms of stakeholders, competitors tend to exert significant pressure towards the adoption of low-carbon operations, while government does not; (vii) more research is necessary to better understand the apparent weak link between low-carbon logistics and firms’ low-carbon performance.
Journal: International Journal of Production Research
Pages: 7106-7125
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1834639
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1834639
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:23:p:7106-7125




Template-Type: ReDIF-Article 1.0
Author-Name: Debiao Li
Author-X-Name-First: Debiao
Author-X-Name-Last: Li
Author-Name: Siping Chen
Author-X-Name-First: Siping
Author-X-Name-Last: Chen
Author-Name: Raymond Chiong
Author-X-Name-First: Raymond
Author-X-Name-Last: Chiong
Author-Name: Liting Wang
Author-X-Name-First: Liting
Author-X-Name-Last: Wang
Author-Name: Sandeep Dhakal
Author-X-Name-First: Sandeep
Author-X-Name-Last: Dhakal
Title: Predicting the printed circuit board cycle time of surface-mount-technology production lines using a symbiotic organism search-based support vector regression ensemble
Abstract: 
 This paper presents a symbiotic organism search (SOS)-based support vector regression (SVR) ensemble for predicting the printed circuit board (PCB) cycle time of surface-mount-technology (SMT) production lines. Being able to predict the PCB cycle time accurately is essential for optimising the SMT production schedule. Although a machine simulator can be reliably used for single-type PCB production, it is time-consuming and often inaccurate for the simulator to be applied for highly mixed orders in multiple flexible SMT production lines. Due to the dynamic changes in both PCB orders and SMT production lines, there is a diverse set of samples, but the size of similar samples is relatively small. An SVR model is therefore used to estimate the PCB cycle time, and the SOS algorithm is employed to optimise the SVR parameters. We assume that uncertainties during the assembly process can be captured by the characteristics of PCB and SMT lines, which are utilised as features to train the SVR model. To enhance the performance of the prediction accuracy, an SOS-SVR ensemble is proposed. Experiments based on datasets collected from a leading global electronics manufacturer confirm the efficiency of the proposed approach compared to industrial solutions currently in place and other machine learning methods.
Journal: International Journal of Production Research
Pages: 7246-7265
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1837407
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1837407
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Template-Type: ReDIF-Article 1.0
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Yanjun Wang
Author-X-Name-First: Yanjun
Author-X-Name-Last: Wang
Author-Name: Yan Liu
Author-X-Name-First: Yan
Author-X-Name-Last: Liu
Title: Product quality and quantity with responsive pricing
Abstract: 
 In this paper, we study a firm's optimal joint product quality and quantity decisions when the consumers' utilities change with the market environment. We develop a model framework to study a monopolist firm's decisions about product quality and related production quantity planning when responsive pricing is implemented. Consumers are heterogeneous in their marginal valuations of the product quality but homogeneous in their reservation utility. Considering a utility function incorporating the reservation utility, quality, and price, consumers make their purchase decisions. We find that as the reservation utility increases or the quality valuation decreases, the optimal quantity increases. However, counterintuitively, the optimal quality decreases when the reservation utility becomes higher. Furthermore, the product quality and quantity are substitutes in the context of responsive pricing. We also investigate the optimal quality and quantity for a product line that is vertically differentiated. Compared to a firm offering a single product, a firm offering a product line is more likely to alter its quality investment decisions due to changes in reservation utility, whereas the optimal investment decisions are less sensitive to changes in quality valuation.
Journal: International Journal of Production Research
Pages: 7160-7178
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1836418
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1836418
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Template-Type: ReDIF-Article 1.0
Author-Name: Weibo Ren
Author-X-Name-First: Weibo
Author-X-Name-Last: Ren
Author-Name: Jingqian Wen
Author-X-Name-First: Jingqian
Author-X-Name-Last: Wen
Author-Name: Yan Yan
Author-X-Name-First: Yan
Author-X-Name-Last: Yan
Author-Name: Yaoguang Hu
Author-X-Name-First: Yaoguang
Author-X-Name-Last: Hu
Author-Name: Yu Guan
Author-X-Name-First: Yu
Author-X-Name-Last: Guan
Author-Name: Jinliang Li
Author-X-Name-First: Jinliang
Author-X-Name-Last: Li
Title: Multi-objective optimisation for energy-aware flexible job-shop scheduling problem with assembly operations
Abstract: 
 There is a lack of studies on joint optimisation of flexible job-shop scheduling problem (FJSP) considering energy consumption and production efficiency in the machining-assembly system. Thus, in this paper, we propose a methodology for multi-objective optimisation of energy-aware flexible job-shop scheduling during machining and assembly operations. First, a mixed integrated mathematical model is developed to improve production efficiency and minimise energy consumption. Then, a novel heuristic algorithm integrated particle swarm optimisation (PSO) and genetic algorithm (GA) is developed to address the established multi-objective problem. Moreover, numerical examples are carried out to verify the validity and performance of the solving methods in achieving energy awareness in the manufacturing system. Computational results are presented to demonstrate the advantage of solving the problem compared with the exact method and common heuristic algorithms, and the trade-off between production efficiency and energy efficiency is analysed to make the final decision for managers.
Journal: International Journal of Production Research
Pages: 7216-7231
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1836421
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1836421
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohamed Larbi Rebaiaia
Author-X-Name-First: Mohamed
Author-X-Name-Last: Larbi Rebaiaia
Author-Name: Daoud Ait-kadi
Author-X-Name-First: Daoud
Author-X-Name-Last: Ait-kadi
Title: Maintenance policies with minimal repair and replacement on failures: analysis and comparison
Abstract: 
 The main objective of a maintenance policy consists of conducting maintenance actions at lower costs. This paper proposes an approach for comparing numerically three maintenance strategies, involving minimal repairs at failure, replacement with complete renewal only at the first failure, and replacement with complete renewal at each failure. These strategies are integrated into a modified block replacement policy that includes corrective and preventive maintenances. The approach proceeds by presenting the mathematical models at the component level and at the system level. As the renewal function for generalised Weibull distributions is impossible to obtain, a novel asymptotic algorithm is introduced for estimating the replacements number. However, a multi-component industrial example is proposed for selecting the strategy that minimises the maintenance costs. A sensitivity analysis is performed for comparing an opportunistic maintenance policy with the proposed replacement policy to check if substantial cost reduction still possible. The experiment results show clearly that the third strategy is the most efficient and reduces maintenance costs to a very low level. Finally, we think that the developed study provides a flexible and less costly solution to deal with maintenance decision-making for systems that do not have modern technological equipment to collect data from system breakdowns.
Journal: International Journal of Production Research
Pages: 6995-7017
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1832275
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1832275
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Template-Type: ReDIF-Article 1.0
Author-Name: Deming Lei
Author-X-Name-First: Deming
Author-X-Name-Last: Lei
Author-Name: Bin Su
Author-X-Name-First: Bin
Author-X-Name-Last: Su
Author-Name: Ming Li
Author-X-Name-First: Ming
Author-X-Name-Last: Li
Title: Cooperated teaching-learning-based optimisation for distributed two-stage assembly flow shop scheduling
Abstract: 
 Two-stage assembly flow shop scheduling problem with 
$DPm \to 1$DPm→1 layout has been extensively considered in single factory; however, distributed two-stage assembly flow shop scheduling problem (DTAFSP) with 
$DPm \to 1$DPm→1 layout in each factory is not studied fully; moreover, teaching-learning-based optimisation is seldom used to solve DTAFSP. In this paper, a cooperated teaching-learning-based optimisation (CTLBO) is proposed to minimise makespan. Multiple classes are constructed. The whole search procedure consists of two stages and each stage possesses two teacher's phases and a learner phase. Class cooperation between the best class and the worst one is implemented by exchanging search times and search ability at the second stage and seldom adopted in the existing works. Extensive experiments are conducted and CTLBO is compared with the existing methods to test its performances. Computational results demonstrate that CTLBO has very competitive performances on solving the considered DTAFSP.
Journal: International Journal of Production Research
Pages: 7232-7245
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1836422
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1836422
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Template-Type: ReDIF-Article 1.0
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Sarat Kumar Jena
Author-X-Name-First: Sarat Kumar
Author-X-Name-Last: Jena
Author-Name: Sachin Kamble
Author-X-Name-First: Sachin
Author-X-Name-Last: Kamble
Author-Name: Dheeraj Misra
Author-X-Name-First: Dheeraj
Author-X-Name-Last: Misra
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Impact of financial risk on supply chains: a manufacturer-supplier relational perspective
Abstract: 
 This study aims to analyse the manufacturer-supplier relational perspective under the influence of exogenous financial risk. Following corporate finance theory, a multi-objective decision model for supplier selection and order allocation is developed to maximise the total profit of the manufacturer, and minimise the implicit equity stake and financial risk faced by selected suppliers. A two-echelon supply chain is explored under the influence of foreign exchange risk, default risk, market risk and price fluctuation risk, and solved using an NSGA-III algorithm. Three case scenarios are analysed to explore the influence of a set of financial risk on the manufacturer-supplier relationship and the behaviour of suppliers concerning risk profile, both in the short and long-term horizon. The results are analysed from both the manufacturer as well as supplier perspective, and the optimal conditions are discussed under the cascading risk circumstances. The study provides multiple insights into the impact of financial risk on supply chain relationship and will be valuable for dealing with similar uncertain economic environment. The research is likely to be of benefit beyond supply chain managers, like investors and financial risk managers in making informed decisions. The need to focus on systemic risk in supply chains is evident from the study.
Journal: International Journal of Production Research
Pages: 7090-7105
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1834638
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1834638
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianjun Wang
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wang
Author-Name: Yanan Tu
Author-X-Name-First: Yanan
Author-X-Name-Last: Tu
Author-Name: Yan Ma
Author-X-Name-First: Yan
Author-X-Name-Last: Ma
Author-Name: Linhan Ouyang
Author-X-Name-First: Linhan
Author-X-Name-Last: Ouyang
Author-Name: Yiliu Tu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Tu
Title: A novel approach for non-normal multi-response optimisation problems
Abstract: 
 Various creative multi-response optimisation approaches have been developed in the literature. Most of these researches are based on the normality assumption of the response distribution. However, this assumption does not necessarily hold in some real cases, such as non-normal multiple responses. Also, the reproducibility of optimisation results does not hold in some practical applications due to the variability of predicted responses associated with model uncertainty. In this paper, a novel approach is proposed to address the issues for non-normal multi-response optimisation. The proposed method not only identifies significant effects for each response by incorporating factorial effect principles into the framework of the Bayesian generalised linear models (GLMs) but also takes into account the model uncertainty and the variability of predicted responses by using the Bayesian sampling technique and Pareto optimal strategy. Furthermore, the optimal parameter settings are found by using grey incidence analysis (GIA). Besides, two examples are used to illustrate the effectiveness of the proposed method. The results show that the proposed method not only effectively identify significant factors but also find more satisfactory parameter settings when the reliability and reproducibility of optimisation results are considered simultaneously.
Journal: International Journal of Production Research
Pages: 7194-7215
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1836420
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1836420
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Template-Type: ReDIF-Article 1.0
Author-Name: Yang Xu
Author-X-Name-First: Yang
Author-X-Name-Last: Xu
Author-Name: Wen Song
Author-X-Name-First: Wen
Author-X-Name-Last: Song
Author-Name: Gong-bing Bi
Author-X-Name-First: Gong-bing
Author-X-Name-Last: Bi
Title: The roles of crowdfunding: financing, point provision and ex-post production
Abstract: 
 While most researches focus on the financing role of crowdfunding, the functions of ex-post production and point provision have not been deeply investigated yet. In this paper, we reveal the three roles of crowdfunding from the perspective of operations management, wherein the ex-post production role can ensure the on-demand production, and the point provision mechanism can alleviate the risk of demand uncertainty. We construct mathematical models to derive the maximised performance of crowdfunding with the three roles in a holistic framework. Our results show that the synthetic of three roles can achieve maximisation performance, and crowdfunding also can improve consumer welfare by lowering the price or raising product quality. To prevent moral hazard, we further illustrate the existence of separate equilibrium by introducing partial pre-payment contract in the asymmetrical information situation. However, the separation cost is high when the initial capital is limited. Our research can shed light on crowdfunding operations.
Journal: International Journal of Production Research
Pages: 7037-7056
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1832277
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1832277
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Template-Type: ReDIF-Article 1.0
Author-Name: Ankit Khare
Author-X-Name-First: Ankit
Author-X-Name-Last: Khare
Author-Name: Sunil Agrawal
Author-X-Name-First: Sunil
Author-X-Name-Last: Agrawal
Title: Effective heuristics and metaheuristics to minimise total tardiness for the distributed permutation flowshop scheduling problem
Abstract: 
 During recent years, the distributed permutation flowshop scheduling problem (DPFSP) has become a very active area of research. However, minimising total tardiness in DPFSP, a very essential and relevant objective for today's customer-orientated market, has not been studied much. In this paper, we address the DPFSP with the total tardiness criterion. We present a mixed-integer linear programming model, two heuristics, hybrid discrete Harris hawks optimisation and an enhanced variant of iterated greedy algorithm to solve the considered problem. Problem-specific knowledge is explored and effective technologies, such as path relinking and random sub-sequence/single-point local search, are employed to improve the presented algorithms. The operators and parameters of the algorithms are analysed and calibrated using the design of experiments. To evaluate the performance, the well-known benchmark problem set of Naderi and Ruiz for DPFSP is extended with due dates. We compare the presented algorithms against seven other well-known meta-heuristics from the literature. Statistically sound results demonstrate the effectiveness of the presented algorithms for the considered problem.
Journal: International Journal of Production Research
Pages: 7266-7282
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1837982
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1837982
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Template-Type: ReDIF-Article 1.0
Author-Name: Royston Meriton
Author-X-Name-First: Royston
Author-X-Name-Last: Meriton
Author-Name: Rajinder Bhandal
Author-X-Name-First: Rajinder
Author-X-Name-Last: Bhandal
Author-Name: Gary Graham
Author-X-Name-First: Gary
Author-X-Name-Last: Graham
Author-Name: Anthony Brown
Author-X-Name-First: Anthony
Author-X-Name-Last: Brown
Title: An examination of the generative mechanisms of value in big data-enabled supply chain management research
Abstract: 
 Big data technologies (BDT) are the latest instalments in a long line of technological disruptions credited with advancing the field of supply chain management (SCM) from a purely clerical function to a strategic necessity. Yet, despite the wave of optimism about the utility of BDT in SCM, the origins of value in a BDT-enabled supply chain are not well understood. This study examines the generative mechanisms of value creation in such a supply chain by a two-pronged approach. First, we interrogate the theoretical raisons d’être of BDT in SCM. Second, we examine the evidence that support the value-added potential of BDT in SCM informed by extant empirical and quantitative studies (EQS). Taken together, our analyses reveal three key findings. First, in extending the dynamic capabilities perspective, we deduced that micro-founded rather than macro-founded studies tend to be more instructive to practice. Second, we discovered that the generative mechanisms of value in a BDT-enabled supply chain operate at the level of supply chain processes. And thirdly, we found that resilience and agility are the most important dynamic capabilities that have emerged from current BDT-enabled SCM research. Insights for policy, practice, theory, and future research are discussed.
Journal: International Journal of Production Research
Pages: 7283-7310
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1832273
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1832273
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Template-Type: ReDIF-Article 1.0
Author-Name: Yimeng Niu
Author-X-Name-First: Yimeng
Author-X-Name-Last: Niu
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Author-Name: Na Geng
Author-X-Name-First: Na
Author-X-Name-Last: Geng
Author-Name: Shan Jiang
Author-X-Name-First: Shan
Author-X-Name-Last: Jiang
Title: Disclosing the formation and value creation of servitization through influential factors: a systematic review and future research agenda
Abstract: 
 Servitization refers to the phenomenon in which manufacturers increasingly focus on services in tandem with the sale of their products. Despite the growing scholarly awareness of servitization, systematic reviews are lacking to clarify how its value can be created through different relevant factors. Based on a conceptual framework, this study fills the gap by examining 213 empirical research papers published between 2005 and 2019. Descriptive and thematic analyses on servitization are presented for its definitions, prerequisites, performances, and intermediate factors of the value creation in servitization. Findings and research streams are synthesised in a causal graph and a mechanism matrix to offer suggestions and research directions for future practitioners and researchers. The results have specified key factors from different levels, such as firm attributes, operations, networking, and the environment, each of which functions in the link of the formation and value creation of servitization. The results further revealed that the existing literature has emphasised the absolute benefits of servitization and predominantly investigated intermediate factors of its value creation. This study offers literature-based insights to enrich the theory-building of servitization and to develop insightful instruments for practitioners.
Journal: International Journal of Production Research
Pages: 7057-7089
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1834158
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1834158
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Template-Type: ReDIF-Article 1.0
Author-Name: Chao-Bo Yan
Author-X-Name-First: Chao-Bo
Author-X-Name-Last: Yan
Author-Name: Ziqian Zheng
Author-X-Name-First: Ziqian
Author-X-Name-Last: Zheng
Title: An effective and efficient divide-and-conquer algorithm for energy consumption optimisation problem in long Bernoulli serial lines
Abstract: 
 Reducing energy consumption in the energy-intensive production systems is of great significance and attracts more and more attention. Although a lot of efforts have been devoted to formulate and solve the energy consumption optimisation problem in the Bernoulli serial lines, existing methods for solving the problem in long Bernoulli lines either cannot obtain the optimal solution or are time-consuming. For this purpose, this paper divides the problem in the long line into a set of problems in two-machine lines and proposes a computationally efficient and globally convergent algorithm to solve it. Extensive numerical experiments show that the proposed algorithm not only can optimally (in the numerical way) solve the energy consumption optimisation problem in long Bernoulli serial lines, but also is orders of magnitude more efficient than existing algorithms.
Journal: International Journal of Production Research
Pages: 7018-7036
Issue: 23
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1832276
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1832276
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Template-Type: ReDIF-Article 1.0
Author-Name: Alireza Khamseh
Author-X-Name-First: Alireza
Author-X-Name-Last: Khamseh
Author-Name: Ebrahim Teimoury
Author-X-Name-First: Ebrahim
Author-X-Name-Last: Teimoury
Author-Name: Kamran Shahanaghi
Author-X-Name-First: Kamran
Author-X-Name-Last: Shahanaghi
Title: A new dynamic optimisation model for operational supply chain recovery
Abstract: 
 This paper focuses on the problem of dynamic supply chain (SC) recovery. We consider effectiveness and efficiency of various reactive measures to recover the SC with the minimum cost at the operational level. For this purpose, a new general model based on bounded optimal control theory is developed to determine the type, the extent, and the timing of reactive measures. We demonstrate its application using an example of a two-echelon poultry SC. The intention of the proposed model is to optimise both the recovery and its costs simultaneously. The developed model is solved exactly using the Pontryagin’s maximum principle. We performed a set of sensitivity analyses to illustrate the model's behaviour. The results obtained from applying the dynamic recovery model in the case study show that the proposed model can help SC managers to deal with disruptions by comparing alternative recovery options, based on two important criteria of the time and cost of SC's recovery. The findings of this research advocate the consideration of dynamic SC characteristics and the need for simultaneous attention to the effectiveness and efficiency of reactive measures in recovery planning.
Journal: International Journal of Production Research
Pages: 7441-7456
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1842937
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1842937
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Template-Type: ReDIF-Article 1.0
Author-Name: Henry J. Liu
Author-X-Name-First: Henry J.
Author-X-Name-Last: Liu
Author-Name: Peter E.D. Love
Author-X-Name-First: Peter E.D.
Author-X-Name-Last: Love
Author-Name: Le Ma
Author-X-Name-First: Le
Author-X-Name-Last: Ma
Author-Name: Michael C.P. Sing
Author-X-Name-First: Michael C.P.
Author-X-Name-Last: Sing
Title: Predicting production-output performance within a complex business environment: from singular to multi-dimensional observations in evaluation
Abstract: 
 Performance evaluation (also measurement) provides a mechanism to ensure that organisations thrive in today’s complex and dynamic business environment. Performance evaluation is widely used for not only interpreting present performance but also for examining the future production output. An understanding of the ‘future’ is reliant on ‘prediction’, which should consider potential uncertainties as a result of the change of time or the variations between organisations, sectors or regions. However, the development of the epistemology of prediction has been overlooked within the context of performance evaluation. This paper develops and expands an existing paradigm of prediction by addressing the multi-dimensional observation for predicting an organisation’s production performance under the auspices of evaluation and specifically in the context of a construction organisation that delivers infrastructure projects, which are acknowledged as being dynamic, uncertain and complex. Three advanced econometric models are applied by using the production-related data provided by a construction organisation to test the developed paradigm. The managerial implications of the research are discussed to ensure their relevance to practice. The empirical study presented in this paper provides a significant contribution to improving the practice of performance evaluation, which is essential for construction organisations to ensure positive business outcomes can be achieved.
Journal: International Journal of Production Research
Pages: 7390-7399
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1841316
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Template-Type: ReDIF-Article 1.0
Author-Name: Qiang Zou
Author-X-Name-First: Qiang
Author-X-Name-Last: Zou
Title: Robust and efficient tool path generation for machining low-quality triangular mesh surfaces
Abstract: 
 This paper presents a new method to generate iso-scallop tool paths for triangular mesh surfaces. With the popularity of 3D scanning techniques, scanning-derived mesh surfaces have seen a significant increase in their application to machining. Quite often, such mesh surfaces exhibit defects such as noises, which differentiate them from the good-quality mesh surfaces previous research work focuses on. To generate tool paths for such low-quality mesh surfaces, the primary challenge lies in robustness against the defects. In this work, a robust tool path generation method is proposed for low-quality mesh surfaces. In addition to robustness, the method is quite efficient, providing the benefit of faster iterations and improved integration between scanning and machining. The fundamental principle of the method is to convert the tool path generation problem to the heat diffusion problem that has robust and efficient algorithms available. The effectiveness of the method will be demonstrated by a series of case studies and comparisons.
Journal: International Journal of Production Research
Pages: 7457-7467
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1842939
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1842939
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Template-Type: ReDIF-Article 1.0
Author-Name: Serena Finco
Author-X-Name-First: Serena
Author-X-Name-Last: Finco
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Ilenia Zennaro
Author-X-Name-First: Ilenia
Author-X-Name-Last: Zennaro
Title: Including rest allowance in mixed-model assembly lines
Abstract: 
 Ergonomics has a significant impact on productivity and human safety in manual assembly lines. For this reason, several studies in recent years have proposed including ergonomics in assembly lines. However, most works are focused on simple assembly lines, while only a few studies exist for mixed-model assembly lines (MMALs). Thus, in this paper, we propose a new methodological approach to include physical fatigue and rest allowance (RA) as ergonomic parameters in MMAL problems. For the balancing problem, we propose a linear mathematical model that minimises the cycle time by including RA. For the sequencing decision, we develop a heuristic approach that assigns workers to workstations according to the workers’ age and their related maximum physical capacity. Then, we propose a linear sequencing model that minimises the work-overload by also evaluating RA to assign each worker according to her or his features. Finally, to complete the study, we test the mathematical models in a real case application and provide a detailed discussion of the results to highlight the benefits we can achieve with this approach.
Journal: International Journal of Production Research
Pages: 7468-7490
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1843731
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1843731
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Template-Type: ReDIF-Article 1.0
Author-Name: Mike Bourne
Author-X-Name-First: Mike
Author-X-Name-Last: Bourne
Title: Performance measurement and management in a VUCA world
Journal: International Journal of Production Research
Pages: 7311-7316
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2021.2004042
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2004042
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:24:p:7311-7316




Template-Type: ReDIF-Article 1.0
Author-Name: Wanjie Hu
Author-X-Name-First: Wanjie
Author-X-Name-Last: Hu
Author-Name: Jianjun Dong
Author-X-Name-First: Jianjun
Author-X-Name-Last: Dong
Author-Name: Bon-gang Hwang
Author-X-Name-First: Bon-gang
Author-X-Name-Last: Hwang
Author-Name: Rui Ren
Author-X-Name-First: Rui
Author-X-Name-Last: Ren
Author-Name: Zhilong Chen
Author-X-Name-First: Zhilong
Author-X-Name-Last: Chen
Title: A preliminary prototyping approach for emerging metro-based underground logistics systems: operation mechanism and facility layout
Abstract: 
 Developing a metro-based underground logistics system (M-ULS) to integrate freight activities into passenger rail transit networks is a sustainable option to improve urban traffic and mobility. This paper proposes innovative concepts for M-ULS prototypes. The system design uses knowledge from engineering practice, emerging initiatives, literature, and experts’ viewpoints. First, demand flows, hierarchies, and facility features of an M-ULS network are described, based on which the collaborative mechanism of shared metro passenger-goods transport, along with specialised packing and transportation strategies, are modelled and compared. Both overground and underground measures are envisaged for last-mile deliveries from metro to customers. Second, a hierarchical framework incorporating 37 key technologies that are necessary for M-ULS development is organised and evaluated. Third, interior layout schemes of a specific interchange metro station with logistics functions are designed. Underground space partitions at the platform layer and the station hall layer are visualised. The logistics workflows of the station are described in full. Evidence from literature and surveys indicates that the proposed M-ULS models are technically feasible, and their advantages and disadvantages are clear. This study contributes to providing a holistic decision support tool for the future planning and design of M-ULS and other rail-based freight transportation systems.
Journal: International Journal of Production Research
Pages: 7516-7536
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1844333
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1844333
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Template-Type: ReDIF-Article 1.0
Author-Name: Cássia Taisy Alencar de Andrade
Author-X-Name-First: Cássia Taisy Alencar
Author-X-Name-Last: de Andrade
Author-Name: Ana Paula Henriques de Gusmão
Author-X-Name-First: Ana Paula Henriques de
Author-X-Name-Last: Gusmão
Author-Name: Wladson Silva
Author-X-Name-First: Wladson
Author-X-Name-Last: Silva
Title: World Class Manufacturing performance measurement using a maturity model and the FlowSort method
Abstract: 
 The World Class Manufacturing (WCM) system is a set of best management practices that can provide organisations with significant performance results. At the same time, since organisations are in a volatile, uncertain, complex, and ambiguous (VUCA) environment, it is important that they continually assess this environment and, thereby, gain situational understanding to perceive and seize opportunities and threats, and consequently apply management practices strategically. Therefore, this paper proposes and empirically validates a model for evaluating the maturity of organisations when applying the WCM system. The authors combined the insights they had from the literature with opinions of WCM experts to develop the model. To support the problem of classifying organisations into the maturity levels defined, the FlowSort multicriteria method was used. The proposed model was applied in four companies and received a good evaluation and acceptance by those involved. This corroborated with the feasibility and usability of this instrument, in addition to which this method by proposing a new tool for evaluating the performance of production systems of companies that use WCM, in a VUCA environment, is intended as a contribution to the literature.
Journal: International Journal of Production Research
Pages: 7374-7389
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2021.1970845
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1970845
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Template-Type: ReDIF-Article 1.0
Author-Name: Nihat Öner
Author-X-Name-First: Nihat
Author-X-Name-Last: Öner
Author-Name: Hakan Gultekin
Author-X-Name-First: Hakan
Author-X-Name-Last: Gultekin
Author-Name: Çağrı Koç
Author-X-Name-First: Çağrı
Author-X-Name-Last: Koç
Title: The airport shuttle bus scheduling problem
Abstract: 
 This paper introduces the airport shuttle bus scheduling problem (ASBSP) as a new practical scheduling variant. In this problem, a number of identical vehicles that have a specific number of available seats provides transfer service between the airport and the city centre. After making a transfer in one direction, the vehicle can either make a new transfer in the opposite direction depending on the availability and the schedule of the passengers or make an empty return to make a new transfer in the same direction. The vehicles can wait in either location until their next transfer. The passengers have certain time windows for the transfer in relation to their flight times and operational rules to satisfy customer satisfaction. This is a profit-seeking service where transfer requests can also be rejected. The ASBSP aims to prepare a daily schedule for the available vehicles and to assign passengers to these vehicles with the objective of maximising the total profit. This paper presents two alternative mixed integer programming formulations and proposes two valid inequalities to get better bounds. Furthermore, it develops a hybrid metaheuristic that integrates multi-start, simulated annealing and large neighbourhood search for its solution. Extensive computational experiments on real-life benchmark instances have been made to test the performances of the formulations and the hybrid metaheuristic. Furthermore, the impacts of several problem parameters including the number of vehicles, vehicle capacity, transfer fee, transportation time and allowable passenger waiting times on the problem complexity and results have been investigated.
Journal: International Journal of Production Research
Pages: 7400-7422
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1841317
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1841317
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Template-Type: ReDIF-Article 1.0
Author-Name: Peng Jiang
Author-X-Name-First: Peng
Author-X-Name-Last: Jiang
Author-Name: Yibin Huang
Author-X-Name-First: Yibin
Author-X-Name-Last: Huang
Author-Name: Xiao Liu
Author-X-Name-First: Xiao
Author-X-Name-Last: Liu
Title: Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model
Abstract: 
 Intermittent demand occurs commonly for spare parts in the heavy-duty vehicle industry. Demand uncertainty and intermittency pose challenges to demand forecasting by conventional models. Support vector machine (SVM) models have been observed to yield competitive accuracy with existing models. However, there are still limitations for basic SVM models. First, the time-consuming computation does not bring a statistically significant accuracy improvement. Second, the forecasting-based inventory performance has not been sufficiently explored. Third, scarce explanations of model robustness are offered for demand forecasting. We build an adaptive univariate SVM (AUSVM) model to forecast intermittent demand. Its effectiveness, compared to 12 existing models and an improved neural-network, is demonstrated by real-world data from a heavy-duty vehicle spare-part company. AUSVM has an apparent advantage in computation time over basic SVM and neural networks. The computational results of the heavy-duty vehicle case indicate that, compared to well-known parametric models, AUSVM achieves a statistically significant accuracy improvement and better inventory performance for the group of non-smooth demand series. Discussions are presented on why AUSVM works for demand forecasting and inventory control of heavy-duty vehicle spare parts. Several insights are revealed for practitioners in the heavy-duty vehicle industry.
Journal: International Journal of Production Research
Pages: 7423-7440
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1842936
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1842936
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Template-Type: ReDIF-Article 1.0
Author-Name: Merve Er Kara
Author-X-Name-First: Merve
Author-X-Name-Last: Er Kara
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Umit Sezer Bititci
Author-X-Name-First: Umit Sezer
Author-X-Name-Last: Bititci
Title: Modelling the impact of climate change risk on supply chain performance
Abstract: 
 Climate change is among the top global risks due to its growing adverse impact on businesses. However, few empirical studies address this imminent risk from a supply chain perspective. Due to a lack of established approaches for capturing complex interaction between climate change risk and supply chain performance, a three-phase mixed methodology approach was attempted. A cognitive map first captured the inter-relationships based on a mental model established by a group of experts. Later, a survey gathered from industry practitioners assessing causal relationships identified key climate change factors and most influenced supply chain performance dimensions. Finally, a system dynamics model supported by multiple case scenarios assessed the implications of climate change on supply chain performance. The results indicated a significant reduction in the availability of natural resources/raw material and capacity, leading to increase in stock-outs, inventory costs and bottlenecks disrupting procurement, manufacturing and logistics functions. Supply chain performance captured through efficiency and effectiveness shows a negative trend with increasing climate change consequences. The systems approach followed in this paper contributes by providing a quantitative model for assessing the impact of climate change risk on supply chain performance.
Journal: International Journal of Production Research
Pages: 7317-7335
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1849844
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1849844
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhiping Zhou
Author-X-Name-First: Zhiping
Author-X-Name-Last: Zhou
Author-Name: Jun Pei
Author-X-Name-First: Jun
Author-X-Name-Last: Pei
Author-Name: Xinbao Liu
Author-X-Name-First: Xinbao
Author-X-Name-Last: Liu
Author-Name: Hong Fu
Author-X-Name-First: Hong
Author-X-Name-Last: Fu
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Title: Effects of resource occupation and decision authority decentralisation on performance of the IoT-based virtual enterprise in central China
Abstract: 
 Enterprises in China are extensively involved in collaborative virtual enterprise (VE) supported by the internet of things (IoT). This paper investigates the effects of member enterprises’ resource occupation on performance of the IoT-based VE, and examines how such effects are moderated by decision authority decentralisation. We obtained the research data from a survey administered to 141 small- and medium-sized enterprises (SMEs) that participate in IoT-based VEs. Hierarchical regression analysis was adopted to test the proposed hypotheses. Our findings suggest that information and operational resources are positively associated with both business and market performance. Strategic decision authority decentralised to SMEs with superior information or operational resources enhances the overall performance, whereas decentralisation of operational decision authority facilitates the positive effects of operational resource on performance. Our study provides directive guidance for IoT-based VEs to cultivate and acquire specific superior resources, and allocate decision authorities reasonably for effective resource utilisation and collaboration.
Journal: International Journal of Production Research
Pages: 7357-7373
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1806369
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1806369
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Template-Type: ReDIF-Article 1.0
Author-Name: The Editors
Title: Correction
Journal: International Journal of Production Research
Pages: (i)-(i)
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2021.1886436
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1886436
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:24:p:(i)-(i)




Template-Type: ReDIF-Article 1.0
Author-Name: Ming-Chuan Chiu
Author-X-Name-First: Ming-Chuan
Author-X-Name-Last: Chiu
Author-Name: Kai-Hsiang Chuang
Author-X-Name-First: Kai-Hsiang
Author-X-Name-Last: Chuang
Title: Applying transfer learning to achieve precision marketing in an omni-channel system – a case study of a sharing kitchen platform
Abstract: 
 Omni-channel marketing is an enhanced cross-channel business model involving shared data that allows enterprises to enhance and facilitate customer experience. Omni-channel opportunities shape retail business and shopper behaviours by coordinating data across all channel platforms while enabling their simultaneous use. Artificial intelligence (AI) has played an increasingly critical role in marketing analysis. With the proper training, AI can predict consumer preferences and provide recommendations based on historical data to achieve precision marketing in e-commerce. At present, however, the existent chatbots on many product-ordering platforms lack AI refinement, resulting in the need to ask customers multiple questions before generating a reliable suggestion, yet an effective way to incorporate AI in an omni-channel platform has remained vague. Hence, the aim of this study was to develop an omni-channel chatbot that incorporates iOS, Android, and web components. The chatbot was designed to achieve personalised service and precision marketing using convolutional neural networks (CNNs). A shared kitchen case study demonstrates the advantages of the proposed method, which is transferable to other consumer applications such as clothing selection or personalised services. The number of food offerings and the quality of image classifiers set the research limitations, pointing toward the direction of future research.
Journal: International Journal of Production Research
Pages: 7594-7609
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1868595
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1868595
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Template-Type: ReDIF-Article 1.0
Author-Name: Soroush Fatemi-Anaraki
Author-X-Name-First: Soroush
Author-X-Name-Last: Fatemi-Anaraki
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Author-Name: Dorsa Abdolhamidi
Author-X-Name-First: Dorsa
Author-X-Name-Last: Abdolhamidi
Author-Name: Behdin Vahedi-Nouri
Author-X-Name-First: Behdin
Author-X-Name-Last: Vahedi-Nouri
Title: Simultaneous waterway scheduling, berth allocation, and quay crane assignment: A novel matheuristic approach
Abstract: 
 Maritime shipment plays a pivotal role in goods transportation worldwide. Ships intending to load/unload a cargo should visit a port. Three main steps are taken during this process. Firstly, ships go through a waterway to reach the berthing area. Secondly, they are allocated to eligible wharves, and quay cranes are assigned to them. At last, ships leave the port area through the waterway. In this paper, the three mentioned stages are considered and solved in an integrated manner. A two-way waterway is deemed with the width limitation for ships moving in opposite directions. Furthermore, ships may arrive during the planning horizon. Tidal impacts, draft limit, and safety distance between ships are prominent maritime limitations included in this paper. As the three stages take place consecutively, the problem appears to resemble a hybrid flow shop scheduling problem with unrelated parallel machines, machine eligibility constraint, and shared resources. Following this attitude, a mathematical model is developed. Due to the problem complexity, three distinct matheuristic approaches are developed by combining the genetic algorithm, discrete differential evolution, and grey wolf optimiser with a mathematical model and tested using randomly-generated numerical instances. At last, developed matheuristics are compared, and some managerial insights are provided.
Journal: International Journal of Production Research
Pages: 7576-7593
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1845412
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1845412
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Template-Type: ReDIF-Article 1.0
Author-Name: Mareike Müller
Author-X-Name-First: Mareike
Author-X-Name-Last: Müller
Author-Name: Marcel Lehmann
Author-X-Name-First: Marcel
Author-X-Name-Last: Lehmann
Author-Name: Heinrich Kuhn
Author-X-Name-First: Heinrich
Author-X-Name-Last: Kuhn
Title: Measuring sequence stability in automotive production lines
Abstract: 
 We consider the question of how stability in automotive manufacturing systems should be analysed. This topic is motivated by the need of original equipment manufacturers to evaluate the performance of their production system to ensure efficiency and long-term competitiveness. In order to deal with the increasing complexity of the manufacturing process, original equipment manufacturers need to focus on efficiency in the manufacturing process and supply chain. Since stability is one determining factor of efficiency they need to implement indicators to quantify and visualise stability. While the overall target for the long-, mid- and short-term planning processes remain the same, the application of and specifications for performance measures differ. We present, analyse and evaluate different indicators and reveal their capability to represent the status of stabilised production facilities. We also describe the challenges that arise when implementing these performance measures in real-world production facilities and give recommendations on how to manage these challenges. We provide a framework to assign indicators to planning problems. The transparency provided by accurately chosen indicators fosters understanding of the overall performance of the system and enhances the management of stabilised production.
Journal: International Journal of Production Research
Pages: 7336-7356
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1790685
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1790685
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Template-Type: ReDIF-Article 1.0
Author-Name: Anirut Kantasa-ard
Author-X-Name-First: Anirut
Author-X-Name-Last: Kantasa-ard
Author-Name: Maroua Nouiri
Author-X-Name-First: Maroua
Author-X-Name-Last: Nouiri
Author-Name: Abdelghani Bekrar
Author-X-Name-First: Abdelghani
Author-X-Name-Last: Bekrar
Author-Name: Abdessamad Ait el cadi
Author-X-Name-First: Abdessamad
Author-X-Name-Last: Ait el cadi
Author-Name: Yves Sallez
Author-X-Name-First: Yves
Author-X-Name-Last: Sallez
Title: Machine learning for demand forecasting in the physical internet: a case study of agricultural products in Thailand
Abstract: 
 Supply chains are complex, stochastic systems. Nowadays, logistics managers face two main problems: increasingly diverse and variable customer demand that is difficult to predict. Classical forecasting methods implemented in many business units have limitations with the fluctuating demand and the complexity of fully connected supply chains. Machine Learning methods have been proposed to improve prediction. In this paper, a Long Short-Term Memory (LSTM) is proposed for demand forecasting in a physical internet supply chain network. A hybrid genetic algorithm and scatter search are proposed to automate tuning of the LSTM hyperparameters. To assess the performance of the proposed method, a real-case study on agricultural products in a supply chain in Thailand was considered. Accuracy and coefficient of determination were the key performance indicators used to compare the performance of the proposed method with other supervised learnings: ARIMAX, Support Vector Regression, and Multiple Linear Regression. The results prove the better forecasting efficiency of the LSTM method with continuous fluctuating demand, whereas the others offer greater performance with less varied demand. The performance of hybrid metaheuristics is higher than with trial-and-error. Finally, the results of forecasting model are effective in transportation and holding costs in the distribution process of the Physical Internet.
Journal: International Journal of Production Research
Pages: 7491-7515
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1844332
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1844332
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Template-Type: ReDIF-Article 1.0
Author-Name: Daria Leiber
Author-X-Name-First: Daria
Author-X-Name-Last: Leiber
Author-Name: Gunther Reinhart
Author-X-Name-First: Gunther
Author-X-Name-Last: Reinhart
Title: A bi-level optimisation approach for assembly line design using a nested genetic algorithm
Abstract: 
 This article presents a novel approach for the automated design of assembly lines that combines the assembly line balancing problem with resource selection and the positioning of the chosen resources into one single optimisation problem. Existing approaches for the automated planning of assembly plants either focus on one planning step or work through different planning steps sequentially. So far, no method exists that sufficiently takes into account the interdependency between the selection and positioning of resources. This article addresses this problem by presenting a bi-level optimisation approach for the automated design of assembly lines. A nested genetic algorithm is used to solve an assembly line balancing problem that includes the selection of production resources while simultaneously considering the layouting options for the chosen resources. Three examples for the evaluation and validation of the algorithm are presented. The presented approach is economically promising as the design of assembly lines requires a lot of expert knowledge and is still mostly done manually.
Journal: International Journal of Production Research
Pages: 7560-7575
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1845411
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1845411
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Handle: RePEc:taf:tprsxx:v:59:y:2021:i:24:p:7560-7575




Template-Type: ReDIF-Article 1.0
Author-Name: Bin Liu
Author-X-Name-First: Bin
Author-X-Name-Last: Liu
Author-Name: Xiujie Zhao
Author-X-Name-First: Xiujie
Author-X-Name-Last: Zhao
Author-Name: Yiqi Liu
Author-X-Name-First: Yiqi
Author-X-Name-Last: Liu
Author-Name: Phuc Do
Author-X-Name-First: Phuc
Author-X-Name-Last: Do
Title: Maintenance optimisation for systems with multi-dimensional degradation and imperfect inspections
Abstract: 
 In this paper, we develop a maintenance model for systems subjected to multiple correlated degradation processes, where a multivariate stochastic process is used to model the degradation processes, and the covariance matrix is employed to describe the interactions among the processes. The system is considered failed when any of its degradation features hits the pre-specified threshold. Due to the dormancy of degradation-based failures, inspection is implemented to detect the hidden failures. The failed systems are replaced upon inspection. We assume an imperfect inspection, in such a way that a failure can only be detected with a specific probability. Based on the degradation processes, system reliability is evaluated to serve as the foundation, followed by a maintenance model to reduce the economic losses. We provide theoretical boundaries of the cost-optimal inspection intervals, which are then integrated into the optimisation algorithm to relieve the computational burden. Finally, a fatigue crack propagation process is employed as an example to illustrate the effectiveness and robustness of the developed maintenance policy. Numerical results imply that the inspection inaccuracy contributes significantly to the operating cost and it is suggested that more effort should be paid to improve the inspection accuracy.
Journal: International Journal of Production Research
Pages: 7537-7559
Issue: 24
Volume: 59
Year: 2021
Month: 12
X-DOI: 10.1080/00207543.2020.1844919
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1844919
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Template-Type: ReDIF-Article 1.0
Author-Name: Yue Wang
Author-X-Name-First: Yue
Author-X-Name-Last: Wang
Author-Name: Joseph Geunes
Author-X-Name-First: Joseph
Author-X-Name-Last: Geunes
Author-Name: Xiaofeng Nie
Author-X-Name-First: Xiaofeng
Author-X-Name-Last: Nie
Title: Optimising inventory placement in a two-echelon distribution system with fulfillment-time-dependent demand
Abstract: 
 We study a two-echelon, single-product fulfillment system where a regional fulfillment center (FC) replenishes multiple independent local distribution center (LDC) orders within an internal committed resupply leadtime, and LDCs serve end customers within a committed demand fulfillment time, or committed delivery time. Expected system-wide demand depends on the product's price, the committed delivery time, and the number of LDCs in the system. Our proposed model determines the values of product price, committed resupply time, and committed delivery time that maximise expected system-wide profit per period, while accounting for product holding costs and fixed facility costs. We characterise key properties of optimal solutions that permit an efficient solution for a fixed number of LDCs, and consider the impacts of several proposed demand growth models as the number of LDCs increases. The results of a computational study provide interesting managerial insights on how operational constraints and the scale of the distribution system influence strategic stock placement and distribution system structure.
Journal: International Journal of Production Research
Pages: 48-72
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1985737
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1985737
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:1:p:48-72




Template-Type: ReDIF-Article 1.0
Author-Name: Jan Olhager
Author-X-Name-First: Jan
Author-X-Name-Last: Olhager
Author-Name: Andreas Feldmann
Author-X-Name-First: Andreas
Author-X-Name-Last: Feldmann
Title: Linking plant roles and operations strategy decision-making autonomy in international manufacturing networks
Abstract: 
 This paper is concerned with the management of multi-plant manufacturing networks. Two key concepts in this domain are plant roles and plant autonomy in the context of operations strategy decision-making. We investigate the relationship between these two concepts and their impact on plant performance. We use data from 102 manufacturing plants belonging to multi-plant networks. The results suggest a relationship between plant roles and operations strategy decision-making structures. Plants with high levels of decision-making autonomy typically have high levels of production, supply chain, and development competences, while plants with a low level of decision-making autonomy are primarily those with only production site competences. Integrated structures for operations strategy decision-making, which include both the network level and the plant level, exist for all plant types and are thus not restricted to plants with a certain set of site competences. In accounting for both the plant type and decision-making structure, we were unable to detect any significant differences between groups in terms of performance effects. Instead, it seems that the fit between plant type and decision-making structure is important and that choosing the right type of operations strategy decision-making structure moderates the performance of plants with low site competence levels.
Journal: International Journal of Production Research
Pages: 242-255
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1991026
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1991026
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Marco Simonetto
Author-X-Name-First: Marco
Author-X-Name-Last: Simonetto
Title: Design and management of assembly systems 4.0: systematic literature review and research agenda
Abstract: 
 Assembly systems (ASs) have moved into the era of mass customisation and Industry 4.0 (I4.0). Mass customisation involves a shift from the production of high quantities of the same product to the production of low quantities of a high number of different products. This is changing the way in which companies assemble their products and has introduced a certain number of challenges. For example, there are increases in the numbers of parts to be moved, the quantities of data to be collected, and the skills of the human workers that companies must manage to meet their customers' demand. The adoption of I4.0 technologies can help companies to face these challenges. However, although companies and researchers have studied possible solutions based on I4.0 technologies for ASs and have introduced the concept of Assembly System 4.0 (AS4.0), no studies have tried to understand how these technologies impact on decision areas at the strategic, tactical, and operational levels. In this paper, we attempt to fill this gap through a systematic literature review that not only offers the opportunity to understand the current situation and the state of the art in this field but also gives an overview of possible future research challenges.
Journal: International Journal of Production Research
Pages: 184-210
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1990433
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1990433
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Template-Type: ReDIF-Article 1.0
Author-Name: Sezgi Tekil-Ergün
Author-X-Name-First: Sezgi
Author-X-Name-Last: Tekil-Ergün
Author-Name: Erwin Pesch
Author-X-Name-First: Erwin
Author-X-Name-Last: Pesch
Author-Name: Katarzyna Anna Kuzmicz
Author-X-Name-First: Katarzyna Anna
Author-X-Name-Last: Kuzmicz
Title: Solving a hybrid mixed fleet heterogeneous dial-a-ride problem in delay-sensitive container transportation
Abstract: 
 The intensity of local truck container transport results from the ubiquitous development of container shipping. Optimal routing of container trucks contributes to cost savings of the service provider but also the reduction of traffic and detrimental emissions. In this paper, a variant of a Mixed Fleet Heterogeneous Dial-a-Ride Problem is proposed for a container truck routing problem. Our aim is an optimal routing of trucks carrying full and empty 20-foot and 40-foot containers, with multiple pick-ups and deliveries. Transportation is performed by alternatively fuelled vehicles (AFVs) for environmental reasons. The AFVs have a limited driving range and are allowed to refuel in any alternative fuel station. The main objective is minimising the total distance subject to matching the empty container demand and supply, necessary refuelling of the trucks, and service time windows.
Journal: International Journal of Production Research
Pages: 297-323
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2000658
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2000658
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Template-Type: ReDIF-Article 1.0
Author-Name: Kathryn E. Stecke
Author-X-Name-First: Kathryn E.
Author-X-Name-Last: Stecke
Author-Name: Mahdi Mokhtarzadeh
Author-X-Name-First: Mahdi
Author-X-Name-Last: Mokhtarzadeh
Title: Balancing collaborative human–robot assembly lines to optimise cycle time and ergonomic risk
Abstract: 
 Human–robot collaboration can enhance productivity of production lines and reduce human ergonomic risk. The numbers and types of robots and stations in which robots are allocated need to be determined. Operations should be scheduled carefully when a human and robot work on a part in a station to obtain a feasible operation allocation with the highest efficiency and lowest ergonomic risk. A mixed-integer linear programming model, constraint programming model, and Benders decomposition algorithm were developed to analyse advantages of collaborative robots in assembly lines. An energy expenditure method was used to evaluate ergonomic risk. By scheduling and balancing collaborative human–robot assembly lines, operational advantages and scheduling constraints from human–robot collaboration were studied when immobile and mobile robots are used. Regression lines were developed that can help managers determine how many and what types of robots are best for a line and what the impact of robot mobility on robot and line performance can be. The best configuration for equipping a line with collaborative robots is when (number of robots)/(number of stations) is near .7 and about 37% of robots are mobile. Robots can be efficiently used in lines with both a small and large number of passive resources and in simple and mixed-model lines.
Journal: International Journal of Production Research
Pages: 25-47
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1989077
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1989077
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Template-Type: ReDIF-Article 1.0
Author-Name: M. Zied Babai
Author-X-Name-First: M. Zied
Author-X-Name-Last: Babai
Author-Name: John E. Boylan
Author-X-Name-First: John E.
Author-X-Name-Last: Boylan
Author-Name: Bahman Rostami-Tabar
Author-X-Name-First: Bahman
Author-X-Name-Last: Rostami-Tabar
Title: Demand forecasting in supply chains: a review of aggregation and hierarchical approaches
Abstract: 
 Demand forecasts are the basis of most decisions in supply chain management. The granularity of these decisions lead to different forecast requirements. For example, inventory replenishment decisions require forecasts at the individual SKU level over lead time, whereas forecasts at higher levels, over longer horizons, are required for supply chain strategic decisions. The most accurate forecasts are not always obtained from data at the 'natural' level of aggregation. In some cases, forecast accuracy may be improved by aggregating data or forecasts at lower levels, or disaggregating data or forecasts at higher levels, or by combining forecasts at multiple levels of aggregation. Temporal and cross-sectional aggregation approaches are well established in the literature. More recently, it has been argued that these two approaches do not make the fullest use of data available at the different hierarchical levels of the supply chain. Therefore, consideration of forecasting hierarchies (over time and other dimensions), and combinations of forecasts across hierarchical levels, have been recommended. This paper provides a comprehensive review of research dealing with aggregation and hierarchical forecasting in supply chains, based on a systematic search. The review enables the identification of major research gaps and the presentation of an agenda for further research.
Journal: International Journal of Production Research
Pages: 324-348
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2005268
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2005268
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Template-Type: ReDIF-Article 1.0
Author-Name: Stephen C. Graves
Author-X-Name-First: Stephen C.
Author-X-Name-Last: Graves
Title: How to think about planned lead times
Abstract: 
 A fundamental construct of most planning systems is the planned lead time. A planned lead time is a control parameter that refers to the planned amount of time for a production, transportation or replenishment activity. The intent of this article is to provide a brief, critical examination of planned lead times. We first discuss why planned lead times are used and why they are important. We then discuss the trade-offs to be considered in setting the planned lead times. We follow this with a review of the research literature on how to specify the planned lead times. Finally, we offer a simple model to provide some insight on how the planned lead time for an activity depends on the stochastic variability of the resource requirements for the activity, and on the flexibility and utilisation of the resource associated with the activity.
Journal: International Journal of Production Research
Pages: 231-241
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1991025
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1991025
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Template-Type: ReDIF-Article 1.0
Author-Name: Hubert Missbauer
Author-X-Name-First: Hubert
Author-X-Name-Last: Missbauer
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Title: Order release in production planning and control systems: challenges and opportunities
Abstract: 
 Production planning and control (PPC) systems are important to the competitiveness of manufacturing firms and their ability to benefit from recent technological advances. We give an overview of research and unsolved research questions in PPC systems related to the order release function that sets output targets for autonomous production units that manage production at the shop-floor level. We describe the hierarchical Manufacturing Planning and Control (MPC) and Advanced Planning and Scheduling (APS) architectures for PPC systems prevalent in practice and the positioning of the order release task within these frameworks. We then describe the research streams relevant to order release, optimisation models for order release planning, and the relation of these models to the overall PPC system. Modelling the dynamic response of production units to time-varying work input, which represents an extension of classical production theory by incorporating the time dimension, is identified as the major modelling challenge. We conclude by suggesting several unsolved research questions that should encourage researchers to work on this topic which is far from mature.
Journal: International Journal of Production Research
Pages: 256-276
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1994165
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1994165
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Template-Type: ReDIF-Article 1.0
Author-Name: Nan Chen
Author-X-Name-First: Nan
Author-X-Name-Last: Chen
Author-Name: Ningjian Huang
Author-X-Name-First: Ningjian
Author-X-Name-Last: Huang
Author-Name: Robert Radwin
Author-X-Name-First: Robert
Author-X-Name-Last: Radwin
Author-Name: Jingshan Li
Author-X-Name-First: Jingshan
Author-X-Name-Last: Li
Title: Analysis of assembly-time performance (ATP) in manufacturing operations with collaborative robots: a systems approach
Abstract: 
 Reducing station processing times has a significant importance in manufacturing assembly systems. In recent years, there has been a growing interest in using collaborative robots to assist human operators in many manufacturing systems, which can not only improve ergonomics measures but also reduce processing time and increase throughput. In this paper, a system-theoretic approach is introduced to analyse the assembly-time performance (ATP) of assembly systems with collaborative robots, where ATP is defined as the probability to finish all the assembly operations in a station within a desired time interval. Specifically, the assembly operations are described by stochastic processes with both individual (human operator and robot) preparation tasks and joint collaboration tasks, characterised by general or arbitrary distributions of task times. Then an efficient algorithm is presented by using gamma distributions to approximate task times and aggregate multiple interacting tasks to calculate ATP. High accuracy in ATP evaluation is obtained through such an approximation method. In addition, system properties, such as monotonicity and sensitivity, i.e. bottlenecks, are investigated. Finally, a case study at an automotive powertrain assembly plant is introduced to illustrate the applicability of the method and the effectiveness for assembly time reduction through using collaborative robots.
Journal: International Journal of Production Research
Pages: 277-296
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2000060
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2000060
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Template-Type: ReDIF-Article 1.0
Author-Name: Mark L. Spearman
Author-X-Name-First: Mark L.
Author-X-Name-Last: Spearman
Author-Name: David L. Woodruff
Author-X-Name-First: David L.
Author-X-Name-Last: Woodruff
Author-Name: Wallace J. Hopp
Author-X-Name-First: Wallace J.
Author-X-Name-Last: Hopp
Title: CONWIP Redux: reflections on 30 years of development and implementation
Abstract: 
 This work is a supplement to earlier literature reviews of research on the production control scheme known as CONWIP. In this paper, we chronicle the origins of CONWIP and address many of the issues and misunderstandings that have appeared over the past 30+ years.
Journal: International Journal of Production Research
Pages: 381-387
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1954713
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1954713
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Template-Type: ReDIF-Article 1.0
Author-Name: Yaqiong Liu
Author-X-Name-First: Yaqiong
Author-X-Name-Last: Liu
Author-Name: Shudong Sun
Author-X-Name-First: Shudong
Author-X-Name-Last: Sun
Author-Name: Xi Vincent Wang
Author-X-Name-First: Xi Vincent
Author-X-Name-Last: Wang
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Title: An iterative combinatorial auction mechanism for multi-agent parallel machine scheduling
Abstract: 
 This paper focuses on the multi-agent parallel machines scheduling problem with consumer agents and resource agents. Within the context, all the agents are self-interested aiming at maximising their profits, and have private information, precluding the use of the centralised scheduling approaches that require complete information of all the consumer agents. Therefore, an iterative combinatorial auction mechanism based on a decentralised decision procedure is proposed to generate a collaborative scheduling scheme without violating information privacy. The developed approach adopts flexible bidding strategies to reduce the conflict in resource allocation, and a hybrid auction termination condition is developed to ensure the convergence of the approach while guaranteeing sufficient competition among agents. Experimental results show the developed approach generates high-quality solutions with a small price of anarchy compared with centralised approaches and outperforms the state-of-the-art decentralised scheduling approach in improving social welfare, especially for problems with a large number of consumer agents.
Journal: International Journal of Production Research
Pages: 361-380
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1950938
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1950938
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Editorial board contributions celebrating the 60th anniversary of IJPR: parts 1 and 2
Abstract: 
 The International Journal of Production Research with this issue starts its 60th volume after celebrating in 2021 its 60th Anniverary. This special issue is dedicated to these anniversaries and composed of invited articles by the members of the Editorial Board of the journal.
Journal: International Journal of Production Research
Pages: 1-7
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2022.2028990
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2028990
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Template-Type: ReDIF-Article 1.0
Author-Name: Arunmozhi Manimuthu
Author-X-Name-First: Arunmozhi
Author-X-Name-Last: Manimuthu
Author-Name: V. G. Venkatesh
Author-X-Name-First: V. G.
Author-X-Name-Last: Venkatesh
Author-Name: Yangyan Shi
Author-X-Name-First: Yangyan
Author-X-Name-Last: Shi
Author-Name: V. Raja Sreedharan
Author-X-Name-First: V. Raja
Author-X-Name-Last: Sreedharan
Author-Name: S. C. Lenny Koh
Author-X-Name-First: S. C. Lenny
Author-X-Name-Last: Koh
Title: Design and development of automobile assembly model using federated artificial intelligence with smart contract
Abstract: 
 With smart sensors and embedded drivers, today’s automotive industry has taken a giant leap in emerging technologies like Machine learning, Artificial intelligence, and the Internet of things and started to build data-driven decision-making strategies to compete in global smart manufacturing. This paper proposes a novel design framework that uses Federated learning-Artificial intelligence (FAI) for decision-making and Smart Contract (SC) policies for process execution and control in a completely automated smart automobile manufacturing industry. The proposed design introduces a novel element called Trust Threshold Limit (TTL) that helps moderate the excess usage of embedded equipment, tools, energy, and cost functions, limiting wastages in the manufacturing processes. This research highlights the use cases of AI in decentralised Blockchain with smart contracts, the company’s trading policies, and its advantages for effectively handling market risk assessments during socio-economic crisis. The developed model supported by real-time cases incorporated cost functions, delivery time and energy evaluations. Results spotlight the use of FAI in decision accuracy for the developed smart contract-based Automobile Assembly Model (AAM), thereby qualitatively limiting the threshold level of cost, energy and other control functions in procurement assembly and manufacturing. Customisation and graphical user interface with cloud integration are some challenges of this model.
Journal: International Journal of Production Research
Pages: 111-135
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1988750
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1988750
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Template-Type: ReDIF-Article 1.0
Author-Name: Josef Svoboda
Author-X-Name-First: Josef
Author-X-Name-Last: Svoboda
Author-Name: Stefan Minner
Author-X-Name-First: Stefan
Author-X-Name-Last: Minner
Title: Tailoring inventory classification to industry applications: the benefits of understandable machine learning
Abstract: 
 Supply chain segmentation and inventory classification, specifically, are considered a competitive advantage in many industries. Approaches like the ABC-XYZ analysis are commonly used in practice to classify SKUs based on simple rules for ranking even though simplified rules-of-thumb may lead to sub-optimal decisions and higher costs. We thus propose a cost-based, multi-dimensional inventory classification scheme for assigning SKUs to classes of replenishment policies that prescribe a group service level, a demand distribution, and an inventory control rule. We further provide an extension for classification under an overall service constraint. Our methodological approach is based on machine learning classifiers and we employ a genetic algorithm to train cost-minimising decision trees which allow for easy understanding and reproduction of classification decisions. Cost- and operational focus, simple application, and interpretability are our main contributions to the inventory classification literature. We evaluate the approach on three industry data sets and show that the classification trees result in an average cost increase of only 1.01% (3.70% with an overall service constraint) over the cost-optimal classification, where no tree structure is enforced. Once trees are constructed, unseen data can be classified out-of-sample with an average cost increase of 1.85% (7.68%) over the optimal cost of classification.
Journal: International Journal of Production Research
Pages: 388-401
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1959078
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1959078
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Kusiak
Author-X-Name-First: Andrew
Author-X-Name-Last: Kusiak
Title: From digital to universal manufacturing
Abstract: 
 The transformation of the manufacturing industry over the last two decades has been largely inspired by data. Digitisation has made its mark in different areas of manufacturing, from digital materials and processes to data science in decision-making. The digital manufacturing is evolving towards universal manufacturing that is highlighted in this paper. Different manufacturing initiatives are benchmarked and their relationship to universal manufacturing is demonstrated. The representation of enterprises in the universal manufacturing cloud is discussed. Product- and process-based specifications of digital enterprises are defined. Using these specifications, the enterprise configuration algorithm proposed in the paper is applied for the selection of component models. Two different representations, a node–node and an input–output matrix, of the digital component models are considered. The extended topological sorting algorithm is applied to construct an integrated digital model.
Journal: International Journal of Production Research
Pages: 349-360
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1948137
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1948137
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Template-Type: ReDIF-Article 1.0
Author-Name: Qingyun Zhu
Author-X-Name-First: Qingyun
Author-X-Name-Last: Zhu
Author-Name: Mahtab Kouhizadeh
Author-X-Name-First: Mahtab
Author-X-Name-Last: Kouhizadeh
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: Formalising product deletion across the supply chain: blockchain technology as a relational governance mechanism
Abstract: 
 Companies manage their product portfolios to create value. Products and associated materials are important flows that link supply chains entities from upstream to downstream. Product deletion is a critical decision in product portfolio management. Current product management literature has predominantly targeted product proliferation, growth, and extension. Product deletion research is relatively and severely limited. Product deletion decisions are less appealing to managers; often due to significant operational changes and disruptions deletion creates within the firm and along the supply chain. Quality information and data can support sound product deletion decision making. Blockchain technology is a valuable tool that can effectively address information governance challenges in supply chains. To this end, we theoretically position blockchain technology as a governance mechanism supporting supply chain relational governance using relational view theory. This paper provides insights into the practice of blockchain and product deletion within a supply chain context. Theoretical and managerial implications are provided as we seek to link supply chain-related product deletion decision processes within blockchain technology supported information governance. There are promising potentials in both fields, Additional research development is needed to effectively manage in this environment and has broader implications for product portfolio management in the supply chain.
Journal: International Journal of Production Research
Pages: 92-110
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1987552
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1987552
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Template-Type: ReDIF-Article 1.0
Author-Name: Foivos Psarommatis
Author-X-Name-First: Foivos
Author-X-Name-Last: Psarommatis
Author-Name: João Sousa
Author-X-Name-First: João
Author-X-Name-Last: Sousa
Author-Name: João Pedro Mendonça
Author-X-Name-First: João Pedro
Author-X-Name-Last: Mendonça
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Zero-defect manufacturing the approach for higher manufacturing sustainability in the era of industry 4.0: a position paper
Abstract: 
 For manufacturing companies, quality management is a key feature for increasing the competitiveness, productivity, profitability, and sustainability of their systems. Quality improvement (QI) methods aim to achieve high-quality parts without reducing performance. The Industry 4.0 framework brought technological developments that cannot be used by traditional QI methods, such as Six Sigma, Lean, Lean Six, the Theory of Constraints, and Total Quality Management, which are widely used in manufacturing companies. The need for higher manufacturing sustainability and market requirements has led to the search for alternative QI methods with superior performance to traditional QI methods such as Zero-Defect Manufacturing (ZDM). The current paper is a position paper with a goal to present the ZDM approach and providing a clear definition about ZDM to align everyone in one common understanding of ZDM. Many researchers and manufactures are skeptical about ZDM, therefore, numerous argumentative questions have been created and answered, to convince them why they should migrate from traditional QI methods to ZDM. The migration to ZDM has already started, to support this statement numerous facts from the literature have been presented. Finally, several directions were identified, demonstrating that there is still plenty of room for research in several domains.
Journal: International Journal of Production Research
Pages: 73-91
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1987551
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1987551
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Template-Type: ReDIF-Article 1.0
Author-Name: A. Serasu Duran
Author-X-Name-First: A. Serasu
Author-X-Name-Last: Duran
Author-Name: Atalay Atasu
Author-X-Name-First: Atalay
Author-X-Name-Last: Atasu
Author-Name: Luk N. Van Wassenhove
Author-X-Name-First: Luk N.
Author-X-Name-Last: Van Wassenhove
Title: Cleaning after solar panels: applying a circular outlook to clean energy research
Abstract: 
 In this paper, we study the link between renewable technology adoption and the resulting waste, drawing parallels from our experience with the WEEE Directive to suggest policy recommendations and highlight future research directions. Our ideas are driven by the observation that the sharp reduction in solar panel installation costs along with improvements in their energy conversion efficiency has driven a rapid growth in the adoption of this technology. We note a potential caveat to such rapid growth in adoption: existing installations being retired earlier than their projected 30-year lifetime. In this context, we build a model of the technology adoption and replacement behaviour of solar panel end-users. We conduct a numerical analysis to calculate the solar panel replacement incentives of US residential households, and project the resulting waste from residential panels. We find that annual new waste introduced into the market can exceed the volume of new installations within the next decade, which can more than double the levelized cost of energy for solar generation and jeopardise the cost competitiveness of this technology in the foreseeable future. These observations reflect the importance of a circular economy outlook in renewable energy system design and call for further research in this area.
Journal: International Journal of Production Research
Pages: 211-230
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1990434
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1990434
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:1:p:211-230




Template-Type: ReDIF-Article 1.0
Author-Name: Panos Kouvelis
Author-X-Name-First: Panos
Author-X-Name-Last: Kouvelis
Author-Name: Yunzhe Qiu
Author-X-Name-First: Yunzhe
Author-X-Name-Last: Qiu
Title: Financing inventories with an investment efficiency objective: ROI-maximising newsvendor, bank loans and trade credit contracts
Abstract: 
 Our work offers an understanding of how capital efficiency metrics, such as Return-on-Investment (ROI), affect orders at a stand-alone single stocking stage under demand uncertainty or within bilateral supply chains of a supplier and buyer interacting with the use of a trade-credit-contract. In both environments, the buyer is looking for financing its inventories either through a bank or through the supplier via extended payment terms. In the single stocking stage case, our buyer – the newsvendor – exhibits conservative behaviour and orders less than the traditional quantity. The analysis of the bilateral supply chain of our newsvendor buyer and a supplier, who is willing to finance the buyer's inventories via trade-credit contract, continues to support the low interest rate of such contracts. Interestingly now the buyer orders more than under profit optimisation. The ROI-driven buyer enjoys higher margins due to unusually low supplier financing rates even at slightly increased wholesale. The overall supply chain efficiency improves, and the supplier increases her percentage of the chain profit by offering higher wholesale prices but accepting some inventory financing risk. Using ROI to make ordering decisions better aligns these decisions with sound working capital management metrics while accounting in a balanced way for profit margins.
Journal: International Journal of Production Research
Pages: 136-161
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1987555
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1987555
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:1:p:136-161




Template-Type: ReDIF-Article 1.0
Author-Name: Steven A. Melnyk
Author-X-Name-First: Steven A.
Author-X-Name-Last: Melnyk
Author-Name: Tobias Schoenherr
Author-X-Name-First: Tobias
Author-X-Name-Last: Schoenherr
Author-Name: Cheri Speier-Pero
Author-X-Name-First: Cheri
Author-X-Name-Last: Speier-Pero
Author-Name: Chris Peters
Author-X-Name-First: Chris
Author-X-Name-Last: Peters
Author-Name: Jeff F. Chang
Author-X-Name-First: Jeff F.
Author-X-Name-Last: Chang
Author-Name: Derek Friday
Author-X-Name-First: Derek
Author-X-Name-Last: Friday
Title: New challenges in supply chain management: cybersecurity across the supply chain
Abstract: 
 Recent cybersecurity breaches have highlighted the resulting economic, political, and social effects. These incidents highlight that cybersecurity is now a supply chain issue. This should not be surprising given the interconnected digital world that defines organisational ecosystems. Due to their relative ‘newness’, coupled with the complexity of both supply chains and cybersecurity, there is lack of clarity and gaps in the current knowledge base regarding cybersecurity across the supply chain. At the same time, this issue is of critical importance to both practitioners and researchers, and thus needs to be structured in such a way to facilitate a common understanding of what cybersecurity across the supply chain cybersecurity entails and the subsequent research opportunities. Thus, the primary objective of this paper is to develop a research framework for cybersecurity across the supply chain to guide future research. An exploratory research methodology was applied, which relied on multiple sources to develop the research framework, including structured literature reviews, anecdotal evidence, interviews with subject matter experts, and external validation by both practitioners and researchers. The paper concludes by identifying areas that demand further research and with a call for more research on cybersecurity across the supply chain.
Journal: International Journal of Production Research
Pages: 162-183
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1984606
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1984606
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:1:p:162-183




Template-Type: ReDIF-Article 1.0
Author-Name: Song-Man Wu
Author-X-Name-First: Song-Man
Author-X-Name-Last: Wu
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: S.H. Chung
Author-X-Name-First: S.H.
Author-X-Name-Last: Chung
Title: A study on green supply chain under capital constraint considering time-varying salvage value
Abstract: 
 To reduce environmental pollution and promote sustainable development, more and more suppliers are committed to producing more environmentally friendly products such as green electrical appliances through a green supply chain (GSC) system. However, some suppliers are often limited by a lack of funds in the production and supply process. In this paper, buyer-supported purchase order financing (BPOF) and advance payment discount (APD) are adopted to help the supplier successfully produce green products in a GSC system consisting of a financially constrained supplier and a reputable retailer. Moreover, the salvage values of unsold inventory in most traditional models are fixed, but in real life, the salvage value tends to be time dependent. Therefore, how the time-varying salvage value affects the operation and financing decisions as well as the profit risks is studied. We find that the clearance time of the unsold items affects the optimal order quantity and the supplier's discount rate and the financial institution's optimal interest rate. In addition, the financing equilibrium is BPOF under certain conditions, and the profit risks of the retailer and the entire supply chain are increasing with the order quantity and the clearance time. Finally, our results are verified through numerical analysis.
Journal: International Journal of Production Research
Pages: 8-24
Issue: 1
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1982153
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1982153
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:1:p:8-24




Template-Type: ReDIF-Article 1.0
Author-Name: Liping Zhou
Author-X-Name-First: Liping
Author-X-Name-Last: Zhou
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Author-Name: Na Geng
Author-X-Name-First: Na
Author-X-Name-Last: Geng
Author-Name: Yimeng Niu
Author-X-Name-First: Yimeng
Author-X-Name-Last: Niu
Author-Name: Feng Cui
Author-X-Name-First: Feng
Author-X-Name-Last: Cui
Author-Name: Kefei Liu
Author-X-Name-First: Kefei
Author-X-Name-Last: Liu
Author-Name: Nanshan Qi
Author-X-Name-First: Nanshan
Author-X-Name-Last: Qi
Title: Production and operations management for intelligent manufacturing: a systematic literature review
Abstract: 
 In the context of Industry 4.0, the manufacturing sector is moving from automation towards intelligence. The application of new generation information and communication technologies (ICTs) improves the interconnection and transparency of intelligent manufacturing (IM) systems, which will change how information interacts and work is done, thus changing how work should be managed. These changes require the following characteristics for IM production and operations management (POM): integration, flexibility and networking, autonomous and collaborative decision-making, learning-based operations management, self-optimisation and adaptability, and proactive decision-making. This paper presents the state of the art, current challenges, and future directions of IM-related POM research from the perspectives of these characteristics through a systematic literature review. Descriptive and thematic analyses of 208 research articles published between 2005 and 2020 are provided. The review and discussions focus on five research themes, i.e. value creation mechanisms, resource configuration and capacity planning, production planning, scheduling, and logistics.
Journal: International Journal of Production Research
Pages: 808-846
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2017055
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2017055
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:808-846




Template-Type: ReDIF-Article 1.0
Author-Name: Chaorui Huang
Author-X-Name-First: Chaorui
Author-X-Name-Last: Huang
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Author-Name: S. H. Chung
Author-X-Name-First: S. H.
Author-X-Name-Last: Chung
Title: Recent contributions to supply chain finance: towards a theoretical and practical research agenda
Abstract: 
 Supply chain finance (SCF) is an innovative solution dedicated to optimising financial flows in supply chains, and has drawn tremendous attention from academia and industry. Considering the ever-evolving nature of SCF, the existing literature reviews in this field are limited due to a lack of integration of recent findings. Motivated by the limitation, we attempt to fill this gap by investigating the novel achievements that have been reported in the current literature. By conducting a systematic literature review, we selected 99 qualified papers published between 2010 and the first quarter of 2021, and then used descriptive analysis to identify the literature characteristics, followed by in-depth content analysis. We synthesised nine research dimensions in the selected SCF literature. By virtue of comprehensive analysis, we illustrated the embedded mechanisms among all participants in SCF practices, updated the SCF research framework, summarised the most dominant methods applied in current research, made two classifications of the financial service providers (FSPs) and SCF instruments, and provided five future research directions. The significance of this paper lies in providing both a novel theoretical foundation for academic researchers and a practical guide for industrial practitioners.
Journal: International Journal of Production Research
Pages: 493-516
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1964706
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1964706
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:493-516




Template-Type: ReDIF-Article 1.0
Author-Name: Jože M. Rožanec
Author-X-Name-First: Jože M.
Author-X-Name-Last: Rožanec
Author-Name: Jinzhi Lu
Author-X-Name-First: Jinzhi
Author-X-Name-Last: Lu
Author-Name: Jan Rupnik
Author-X-Name-First: Jan
Author-X-Name-Last: Rupnik
Author-Name: Maja Škrjanc
Author-X-Name-First: Maja
Author-X-Name-Last: Škrjanc
Author-Name: Dunja Mladenić
Author-X-Name-First: Dunja
Author-X-Name-Last: Mladenić
Author-Name: Blaž Fortuna
Author-X-Name-First: Blaž
Author-X-Name-Last: Fortuna
Author-Name: Xiaochen Zheng
Author-X-Name-First: Xiaochen
Author-X-Name-Last: Zheng
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Actionable cognitive twins for decision making in manufacturing
Abstract: 
 Actionable Cognitive Twins are the next generation Digital Twins enhanced with cognitive capabilities through a knowledge graph and artificial intelligence models that provide insights and decision-making options to the users. The knowledge graph describes the domain-specific knowledge regarding entities and interrelationships related to a manufacturing setting. It also contains information on possible decision-making options that can assist decision-makers, such as planners or logisticians. This paper proposes a knowledge graph modelling approach to construct actionable cognitive twins for capturing specific knowledge related to production planning and demand forecasting in a manufacturing plant. The knowledge graph provides semantic descriptions and contextualisation of the production lines and processes, including data identification and simulation or artificial intelligence algorithms and forecasts used to support them. Such semantics provide ground for inferencing, relating different knowledge types: creative, deductive, definitional, and inductive. To develop the knowledge graph models for describing the use case thoroughly, systems thinking approach is proposed to design and verify the ontology, develop a knowledge graph and build an actionable cognitive twin. Finally, we evaluate our approach in two use cases developed for a European original equipment manufacturer related to the automotive industry as part of the European Horizon 2020 project FACTLOG.
Journal: International Journal of Production Research
Pages: 452-478
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2002967
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002967
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:452-478




Template-Type: ReDIF-Article 1.0
Author-Name: Xiang Ji
Author-X-Name-First: Xiang
Author-X-Name-Last: Ji
Author-Name: Guo Li
Author-X-Name-First: Guo
Author-X-Name-Last: Li
Author-Name: Suresh P. Sethi
Author-X-Name-First: Suresh P.
Author-X-Name-Last: Sethi
Title: How social communications affect product line design in the platform economy
Abstract: 
 The booming platform economy has made it very convenient for consumers to communicate with each other through social media whenever and wherever they want. As industry and academia have repeatedly confirmed, such social communications are now significantly changing firms' business and management practices. This paper studies how social communications affect an upstream firm's product line design in the platform economy when an online platform makes strategic contract choices. We show that for both wholesale and agency contracts, social communications increase the product line length while decreasing the product price and quality. We also identify the conditions under which social communications provide a firm with fewer incentives for product line extension under a wholesale contract than under an agency contract. On the platform side, we show that an agency contract can be preferred in the presence of social communications over a wholesale contract if and only if the commission rate is sufficiently high or both the commission rate and the product line extension fee are moderate.
Journal: International Journal of Production Research
Pages: 686-703
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2013562
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2013562
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:686-703




Template-Type: ReDIF-Article 1.0
Author-Name: Masoud Mirzaei
Author-X-Name-First: Masoud
Author-X-Name-Last: Mirzaei
Author-Name: Nima Zaerpour
Author-X-Name-First: Nima
Author-X-Name-Last: Zaerpour
Author-Name: René B.M. de Koster
Author-X-Name-First: René B.M.
Author-X-Name-Last: de Koster
Title: How to benefit from order data: correlated dispersed storage assignment in robotic warehouses
Abstract: 
 In e-commerce fulfilment centres, storage assignment is critical to ensure short response times. To achieve this, many online retailers have moved to product dispersion in combination with product turnover-based slotting. However, commonly used policies do not fully utilise the historical customer demand information to optimise the storage assignment. This paper addresses a comprehensive approach to estimate the joint effects of ‘turnover frequency’, ‘product correlation’, and ‘inventory dispersion’ storage strategies on the expected order picking travel time in automated (robotic), parts-to-picker systems. Additionally, it provides a thorough analysis of the impact of product correlation and turnover frequency on storage policies’ performance. We develop a mixed-integer linear program for optimal product-to-cluster and cluster-to-zone allocation to minimise the robot's expected travel time. The travel time expressions are developed for different zone and station configurations. An efficient construction and improvement heuristic method is proposed and applied to a real dataset of a personal care products distributor. The analytical results show that the correlated dispersed assignment leads to a shorter expected travel time than the benchmark policies for order sets with sufficiently large order size. The demand correlation plays a major role in the performance of the models in the cases we tested.
Journal: International Journal of Production Research
Pages: 549-568
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1971787
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1971787
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:549-568




Template-Type: ReDIF-Article 1.0
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Title: Balancing cybersecurity in a supply chain under direct and indirect cyber risks
Abstract: 
 Cybersecurity is an essential requirement for the sustainability of global supply chains. In this paper, a stochastic programming formulation is presented for optimisation of cybersecurity investment and selection of security controls to mitigate and balance the impact of direct and indirect (propagated) cyber risks in a multi-tier supply chain. Using a network transformation combined with the first-order Taylor series approximation of natural logarithm to linearise the nonlinear constraints, a nonlinear stochastic combinatorial optimisation model is approximated by its linear equivalent. The problem objective is to determine an optimal cybersecurity investment under limited budget and portfolio of security controls for each supply chain node to balance the cybersecurity over the entire supply chain. The minmax objective functions are applied to minimise either the maximum breach probability or the maximum loss of supply chain nodes. Alternatively, maxmin objectives are used to maximise either the minimum non-breach probability or the minimum saving of loss. The proposed integrated modelling approach is illustrated with results of computational study and a comparison of approximated and exact solution values is presented. The decision-making insights are provided and discussed.
Journal: International Journal of Production Research
Pages: 766-782
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1914356
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1914356
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:766-782




Template-Type: ReDIF-Article 1.0
Author-Name: Christian Ruf
Author-X-Name-First: Christian
Author-X-Name-Last: Ruf
Author-Name: Jonathan F. Bard
Author-X-Name-First: Jonathan F.
Author-X-Name-Last: Bard
Author-Name: Rainer Kolisch
Author-X-Name-First: Rainer
Author-X-Name-Last: Kolisch
Title: Workforce capacity planning with hierarchical skills, long-term training, and random resignations
Abstract: 
 This paper addresses a multistage capacity planning problem for a hierarchically skilled workforce in a production environment. Recruits are hired with little or no experience and are trained over multiple periods to perform jobs that require increasing levels of skill. Training can take place either off-the-job, on-the-job or a combination thereof. The problem is complicated by random resignations that can lead to labor shortfalls that jeopardise continuous operations. The objective is to balance workforce costs with penalty costs associated with skill shortages. The problem is modelled as a Markov decision process for which several parameterised decision rules are proposed to find solutions. A large-scale neighbourhood search is developed to deal with ‘noisy’ cost function measurements. Experiments show that good parameter values can be found in less than four hours using real-world data. When training requires extensive supervision, the results indicate that the number of workers concurrently in training should be limited. They also show that a shorter, intense training period during which employees do not perform regular tasks is generally preferable to a longer training period where employees spend time both on and off the job. Finally, we demonstrate the value of worker flexibility when downgrading is applied.
Journal: International Journal of Production Research
Pages: 783-807
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2017058
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2017058
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:783-807




Template-Type: ReDIF-Article 1.0
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: 5G in digital supply chain and operations management: fostering flexibility, end-to-end connectivity and real-time visibility through internet-of-everything
Abstract: 
 5G technology enables end-to-end connectivity in real time at a highly granular level along with the associated end-to-end visibility through the Internet-of-Everything. While some potential benefits of 5G for digital supply chain and operations management have been declared, literature is still silent about theoretical underpinning and structured conceptualisation of application areas, underlying implementation challenges, and the role of 5G in future transformations of value creation. This paper aims to offer some directions of how to close this research gap. We organise the discussion around five major capabilities of the digital supply chain and smart operations which can be enhanced by 5G, i.e. intelligence, visibility, transparency, dynamic networking, and connectivity. We delineate possible future research topics related to 5G in different areas of Industry 4.0-driven, digital supply chain and operations management which can be useful for researchers and practitioners alike when seeking to understand the impact of 5G on both short-term and long-term time scales. Our analysis encompasses both operational processes (e.g. transformations of manufacturing and warehouse operations by end-to-end connectivity of devices) and strategic perspectives (e.g. transformations of business models and supply network structures through end-to-end real-time visibility and connectivity of industry, public infrastructure, and consumers). Finally, cost-benefits trade-offs are discussed.
Journal: International Journal of Production Research
Pages: 442-451
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2002969
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002969
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:442-451




Template-Type: ReDIF-Article 1.0
Author-Name: Juntaek Hong
Author-X-Name-First: Juntaek
Author-X-Name-Last: Hong
Author-Name: Kyungduk Moon
Author-X-Name-First: Kyungduk
Author-X-Name-Last: Moon
Author-Name: Kangbok Lee
Author-X-Name-First: Kangbok
Author-X-Name-Last: Lee
Author-Name: Kwansoo Lee
Author-X-Name-First: Kwansoo
Author-X-Name-Last: Lee
Author-Name: Michael L. Pinedo
Author-X-Name-First: Michael L.
Author-X-Name-Last: Pinedo
Title: An iterated greedy matheuristic for scheduling in steelmaking-continuous casting process
Abstract: 
 Steelmaking-Continuous Casting (SCC) is a bottleneck in the steel production process and its scheduling has become more challenging over time. In this paper, we provide an extensive literature review that highlights challenges in the SCC scheduling and compares existing solution methods. From the literature review, we collect the essential features of an SCC process, such as unrelated parallel machine environments, stage skipping, and maximum waiting time limits in between successive stages. We consider an SCC scheduling problem with as objective the minimisation of the weighted sum of cast break penalties, total waiting time, total earliness, and total tardiness. We formulate the problem as a mixed-integer linear programming model and develop an iterated greedy matheuristic that solves its subproblems to find a near-optimal solution. Through numerical experiments, we show that our algorithm outperforms two types of genetic algorithms when applied to test instances.
Journal: International Journal of Production Research
Pages: 623-643
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1975839
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1975839
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Template-Type: ReDIF-Article 1.0
Author-Name: Paul-Arthur Dreyfus
Author-X-Name-First: Paul-Arthur
Author-X-Name-Last: Dreyfus
Author-Name: Foivos Psarommatis
Author-X-Name-First: Foivos
Author-X-Name-Last: Psarommatis
Author-Name: Gokan May
Author-X-Name-First: Gokan
Author-X-Name-Last: May
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Virtual metrology as an approach for product quality estimation in Industry 4.0: a systematic review and integrative conceptual framework
Abstract: 
 Virtual metrology (VM) involves estimating a product’s quality directly from production process data without physically measuring it. This enables the product quality of each unit of production to be monitored in real time, while preserving the process efficiency. Initially developed for the semiconductor industry, VM has recently been examined for use in other industrial fields. VM is enabled by components such as quality estimators and drift detectors. It enhances various industrial applications such as machine control and sampling decision systems. The literature lacks a comprehensive summary and a systematic review of the state of the art in VM. To fill this gap, this study followed a systematic methodology to conduct a complete and structured literature review of VM. This paper presents a detailed analysis of the 199 papers that we identified based on our search and selection criteria. Following our methodological framework, we assigned these papers to categories and highlighted shortcomings. Finally, we discussed VM’s use in various industrial fields, underlining its potential for every manufacturing industry. This study and the proposed framework are useful for both practitioners and academicians since they raise crucial theoretical and managerial questions as well as provide suggestions for further research on this critical topic.
Journal: International Journal of Production Research
Pages: 742-765
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1976433
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1976433
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:742-765




Template-Type: ReDIF-Article 1.0
Author-Name: Yao Cheng
Author-X-Name-First: Yao
Author-X-Name-Last: Cheng
Author-Name: Elsayed A. Elsayed
Author-X-Name-First: Elsayed A.
Author-X-Name-Last: Elsayed
Author-Name: Zhiyi Huang
Author-X-Name-First: Zhiyi
Author-X-Name-Last: Huang
Title: Systems resilience assessments: a review, framework and metrics
Abstract: 
 The past several decades have witnessed an increasing number of natural and manmade hazards with a dramatic impact on the normal operations of the society. The occurrences of these hazards manifest a growing trend of uncertainty. Assessing the performance of systems under such hazards is a salient concern of researchers and practitioners. The notion of ‘resilience’ has been proposed and popularised to characterise system performance deterioration and restoration due to different hazards and threats. Substantial effort has been devoted to quantify and describe resilience from different perspectives. However, there is no generic metric for assessing the resilience of different systems under different hazards. This paper provides a review of existing approaches that quantitatively assess resilience, along with their applicable scenarios and limitations. New general and generic resilience metrics for systems with multimodal performance are proposed. Opportunities for multi-hazard resilience modelling and enhancements are presented.
Journal: International Journal of Production Research
Pages: 595-622
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1971789
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1971789
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:595-622




Template-Type: ReDIF-Article 1.0
Author-Name: Vivek Vijayakumar
Author-X-Name-First: Vivek
Author-X-Name-Last: Vijayakumar
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Author-Name: Ahmad Sobhani
Author-X-Name-First: Ahmad
Author-X-Name-Last: Sobhani
Title: Framework for incorporating human factors into production and logistics systems
Abstract: 
 Many companies, despite there being opportunities for automation in production and logistics (P&L) systems, still rely on human workers due to their cognitive and motor skills. Taking Human Factor (HF) aspects into consideration when making P&L system design and management decisions is therefore important, an ignorance of HF potentially resulting in operator fatigue, discomfort, subsequent injuries and negative consequences for operator performance and the P&L system. A review of the literature shows that the majority of studies that take HF into consideration focus either on designing the workplace or on operation planning activities. There is also still a gap in the literature. Little has been published on P&L systems that incorporate HF and that combine different levels of short-term operational policy decisions (e.g. job allocation) and long-term system characteristic decisions (e.g. layout design). Current state-of-the-art frameworks that support the design and management of P&L systems and that take HF into consideration rarely consider different decision levels. This study proposes a new framework that incorporates HF into P&L systems by combining different levels of decisions to improve performance, quality, and well-being.
Journal: International Journal of Production Research
Pages: 402-419
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1983225
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Template-Type: ReDIF-Article 1.0
Author-Name: Rosalin Sahoo
Author-X-Name-First: Rosalin
Author-X-Name-Last: Sahoo
Author-Name: Ajit Kumar Pasayat
Author-X-Name-First: Ajit Kumar
Author-X-Name-Last: Pasayat
Author-Name: Bhaskar Bhowmick
Author-X-Name-First: Bhaskar
Author-X-Name-Last: Bhowmick
Author-Name: Kiran Fernandes
Author-X-Name-First: Kiran
Author-X-Name-Last: Fernandes
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: A hybrid ensemble learning-based prediction model to minimise delay in air cargo transport using bagging and stacking
Abstract: 
 Manufacturing productivity is inextricably linked to air freight handling for the global delivery of finished and semi-finished goods. In this article, our focus is to capture the transport risk associated with air freight which is the difference between the actual and the planned time of arrival of a shipment. To mitigate the time-related uncertainties, it is essential to predict the delays with adequate precision. Initially, data from a case study in the transportation and logistics sector were pre-processed and divided into categories based on the duration of the delays in various legs. Existing datasets are transformed into a series of features, followed by extracting important features using a decision tree-based algorithm. To predict the delay with maximum accuracy, we used an improved hybrid ensemble learning-based prediction model with bagging and stacking enabled by characteristics like time, flight schedule, and transport legs. We also calculated the dependency of accuracy on the point in time during business process execution is examined while predicting. Our results show all predictive methods consistently have a precision of at least 70 per cent, provided a lead-time of half the duration of the process. Consistently, the proposed model provides strategic and sustainable insights to decision-makers for cargo handling.
Journal: International Journal of Production Research
Pages: 644-660
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2013563
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2013563
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:644-660




Template-Type: ReDIF-Article 1.0
Author-Name: Jafar Namdar
Author-X-Name-First: Jafar
Author-X-Name-Last: Namdar
Author-Name: Jennifer Blackhurst
Author-X-Name-First: Jennifer
Author-X-Name-Last: Blackhurst
Author-Name: Arash Azadegan
Author-X-Name-First: Arash
Author-X-Name-Last: Azadegan
Title: On synergistic effects of resilience strategies: developing a layered defense approach
Abstract: 
 Supply chain literature has amply explored the effect of different resilience strategies in the face of supply chain disruptions. Firms often apply a multitude of resilience strategies in tandem. Such strategies can vary from slack inventory to volume flexibility and responsiveness to backup capacity. Yet, there is a lack of empirical or analytical evidence in how the combination of resilience strategies affects firm capabilities in the face of supply chain disruptions. In this paper, we use simulation modelling techniques to determine the effect of different combinations of resilience strategies in a systematic and stepwise manner. Our modelling considers different disruption attributes (capacity or delay), their effect (severity and likelihood), and their origin (i.e. upstream or downstream). A number of interesting observations are made. First, combining resilience strategies is not always beneficial and can occasionally have detrimental effects. Moreover, resilience strategies that are beneficial at the node (firm) level may prove ineffective at the system level. We also find that inventory and volume flexibility are strategies that combine well with others. The study offers several contributions to research and management in supply chain disruption and the study of resilience.
Journal: International Journal of Production Research
Pages: 661-685
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2013561
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2013561
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Template-Type: ReDIF-Article 1.0
Author-Name: Shiquan Ling
Author-X-Name-First: Shiquan
Author-X-Name-Last: Ling
Author-Name: Daqiang Guo
Author-X-Name-First: Daqiang
Author-X-Name-Last: Guo
Author-Name: Yiming Rong
Author-X-Name-First: Yiming
Author-X-Name-Last: Rong
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Spatio-temporal synchronisation for human-cyber-physical assembly workstation 4.0 systems
Abstract: 
 Assembly workstation converges various resources, typically including humans to carry out parts combination activities with the performances determined by the interactions among the resources. In the Industry 4.0 (I4.0) era, the penetration of emerging technologies leads to the intelligent networking of hyper objects with hyper-automation and hyper-connectivity that fundamentally change the organisation of an assembly workstation and brings it into the era of ‘Assembly Workstation 4.0 (AW4.0)’. However, the volatile market demands and the autonomy of the hyper objects with human integration bring new challenges in reducing the uncertainty and complexity of AW4.0 systems. In order to achieve an effective and efficient orchestration among hyper objects by fully harnessing enabling technologies of I4.0, a humancyber- physical system (HCPS) framework for AW4.0 systems is proposed to support the intelligent networking of hyper objects and to leverage the strengths and compensate the limitations of humans. Based on this, a spatio-temporal synchronisation (ST-Sync) strategy is introduced to achieve coordinated decision-making with consideration of customer requirements and spatio-temporal constraints of hyper objects with enhanced flexibility and responsiveness. Finally, a full-scale prototype is developed, and a real-life case is used to validate the potential benefits of AW4.0 systems in the overall performance improvement.
Journal: International Journal of Production Research
Pages: 704-722
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2010826
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2010826
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Template-Type: ReDIF-Article 1.0
Author-Name: Hakan Yildiz
Author-X-Name-First: Hakan
Author-X-Name-Last: Yildiz
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Author-Name: Xiulin Xie
Author-X-Name-First: Xiulin
Author-X-Name-Last: Xie
Author-Name: Jiho Yoon
Author-X-Name-First: Jiho
Author-X-Name-Last: Yoon
Author-Name: Peihua Qiu
Author-X-Name-First: Peihua
Author-X-Name-Last: Qiu
Author-Name: John M. Wassick
Author-X-Name-First: John M.
Author-X-Name-Last: Wassick
Title: Evaluating and monitoring distribution network efficiency with multivariate process control methods
Abstract: 
 In this paper, we present a methodology, by utilising a nonparametric multivariate cumulative sum control chart and data envelopment analysis in tandem, to evaluate and monitor distribution network performance by simultaneously considering multiple performance factors and their interrelationships. While these methods were previously applied individually, we demonstrate that their combined use can provide more powerful results in performance assessment, monitoring and improvement. Our approach contributes to the domain of supply chain analytics and risk management as it can provide new insights into network performance based on real time and past data. We present the application of our approach on data obtained from The Dow Chemical Company.
Journal: International Journal of Production Research
Pages: 517-533
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1964707
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1964707
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Template-Type: ReDIF-Article 1.0
Author-Name: Farhad Ameri
Author-X-Name-First: Farhad
Author-X-Name-Last: Ameri
Author-Name: Dusan Sormaz
Author-X-Name-First: Dusan
Author-X-Name-Last: Sormaz
Author-Name: Foivos Psarommatis
Author-X-Name-First: Foivos
Author-X-Name-Last: Psarommatis
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Industrial ontologies for interoperability in agile and resilient manufacturing
Abstract: 
 Ontologies provide an opportunity to tackle the interoperability challenge in digital manufacturing. Although ontologies have been used in numerous industrial projects, the problem of semantic interoperability in the industry is still unresolved. One reason for the lack of success of ontologies in the industry is that most industrial ontologies have been developed based on local needs without taking wider applications into account or attempting to learn from earlier ontology initiatives or reuse the existing ontologies. In this position paper, we argue that for widespread adoption and implementation of ontologies, more systematic and coordinated efforts are needed with the participation of industry, academia, and government at an international level. We also hypothesise that a coordinated and systematic ontology development effort will incrementally lead to the creation of an ecosystem of interoperable software applications that support consistent data access and reasoning across the product life cycle. We discuss why efforts such as Industrial Ontology Foundry (IOF) can promote a methodological ontology development process by introducing modular, and reusable ontologies. We draw examples from two domain areas, namely supply chain management and production planning and scheduling, to demonstrate how industrial notions can be analysed ontologically according to IOF procedures and methods.
Journal: International Journal of Production Research
Pages: 420-441
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1987553
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1987553
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Template-Type: ReDIF-Article 1.0
Author-Name: Win P. V. Nguyen
Author-X-Name-First: Win P. V.
Author-X-Name-Last: Nguyen
Author-Name: Puwadol Oak Dusadeerungsikul
Author-X-Name-First: Puwadol Oak
Author-X-Name-Last: Dusadeerungsikul
Author-Name: Shimon Y. Nof
Author-X-Name-First: Shimon Y.
Author-X-Name-Last: Nof
Title: Plant stress propagation detection and monitoring with disruption propagation network modelling and Bayesian network inference
Abstract: 
 Plant stresses and diseases cause major losses to agricultural productivity and quality. Left unchecked, stresses and diseases can spread and propagate to nearby plants, causing even more damage, necessitating early detection. To address this challenge, the Agricultural Robotic System for Plant Stress Propagation Detection (ARS/PSPD) is developed. In this cyber-physical system, the robot agents are assigned scanning tasks to detect stresses in greenhouse plants. The problem of plant stress propagation detection is formulated with disruption propagation network modelling, which captures the plant stress occurrence and propagation mechanisms. The network modelling enables better situation awareness and augments the development of advanced collaborative scanning protocols. Five collaborative scanning protocols are designed and implemented in this research, with one protocol serving as a baseline, three protocols utilising disruption propagation network analysis, and one protocol utilising Bayesian network inference. The scanning protocols minimise errors and conflicts in scanning task allocation and enable better plant stress detection. The five ARS/PSPD collaborative scanning protocols are validated with numerical experiments, using agricultural greenhouses as experiment settings. The experiments show that the scanning protocol using Bayesian network inference outperforms all other protocols in all scenarios, with 16.92% fewer undetected plant stresses and 12.28% fewer redundant scans.
Journal: International Journal of Production Research
Pages: 723-741
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.2009139
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2009139
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Template-Type: ReDIF-Article 1.0
Author-Name: Michela Magas
Author-X-Name-First: Michela
Author-X-Name-Last: Magas
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Industry Commons: an ecosystem approach to horizontal enablers for sustainable cross-domain industrial innovation (a positioning paper)
Abstract: 
 This paper introduces the background, concept and definition of the Industry Commons. It initiates a discussion on the positioning of the Industry Commons Ecosystem (ICE) with respect to current research directions in advanced manufacturing and production systems that shape advances in engineering and technology, novel business models and innovation breakthroughs. The potential value of data sharing across industrial domains is estimated at over $100 billion, particularly in view of optimising manufacturing processes. Data sharing across domains however faces a series of well-documented challenges associated with the lack of semantic interoperability and related standards, management of trust and sustainability. Solving bottlenecks in data sharing requires a systemic approach to data management, which can account for all aspects of data use, levels of application, attribution and dynamic exchanges. In this paper we propose a high-level ecosystem approach that integrates societal values with digital affordances of industry’s cognitive-assisted processes, remote interfacing, hybrid applications and large-scale value networks. Early development of an Ontology Commons EcoSystem (OCES) is presented as the key enabling framework for Industry Commons interoperability and a series of enabling frameworks form the basis of future research directions in Trusted Data Sharing and Closed-Loop Lifecycle Management for greater sustainability.Abbreviations: AI – Artificial Intelligence; AIOTI – Alliance of Internet-of-Things Innovation; ALM – Asset Lifecycle Management; ALO – Application-Level Ontology; AP – Application Protocol; API – Application Programming Interface; B2B – Business-to-Business; B2C – Business-to-Customer; CDE – Cross-Domain Ecosystem; CDEI – Cross-Domain Ecosystem Interoperability; CL2M – Closed-Loop Lifecycle Management; CNO – Collaborative Networked Organisations; CPS – Cyber-Physical Systems; CSR – Corporate Social Responsibility; DLO – Domain-Level Ontology; DLT – Distributed Ledger Technology; EM – Enterprise Modelling; FAIR – Findable, Accessible, Interoperable and Reusable; GUI – Graphical User Interface; ICE, Industry Commons Ecosystem; IOF – Industrial Ontology Foundry; IP – Intellectual Property; IPR – Intellectual Property Rights; ISN – Intertwined Supply Network; MIR – Music Information Retrieval; MLO – Middle-Level Ontology; MO – Meta-Ontology; OCES – Ontology Commons EcoSystem; PI – Physical Internet; PLM – Product Lifecycle Management; ROI – Return-on-Investment; SC – Supply Chain; SCM – Supply Chain Management; SOS – System-of-Systems; TDS – Trusted Data Sharing; TLO – Top-Level Ontology; TRO – Top Reference Ontology; TUI – Tangible User Interface.
Journal: International Journal of Production Research
Pages: 479-492
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1989514
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1989514
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Template-Type: ReDIF-Article 1.0
Author-Name: Vishwas Dohale
Author-X-Name-First: Vishwas
Author-X-Name-Last: Dohale
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Milind Madhukarro Akarte
Author-X-Name-First: Milind Madhukarro
Author-X-Name-Last: Akarte
Author-Name: Priyanka Verma
Author-X-Name-First: Priyanka
Author-X-Name-Last: Verma
Title: 52 Years of manufacturing strategy: an evolutionary review of literature (1969–2021)
Abstract: 
 Manufacturing strategy is an essential aspect of production and operations management discipline. It plays a crucial role in the success of business strategy by configuring manufacturing decisions effectively to achieve the firm's competitive advantage in the marketplace. From the advent of the manufacturing strategy concept, it has advanced immensely through the contribution of researchers in scholarly outlets. This paper provides an evolutionary overview of the literature on the manufacturing strategy domain to provide the scientific landscape of existing studies for exploring the progression of the domain over five decades. In this study, 1034 articles published from 1969-2021 are selected, reviewed, and analysed. We critically explored the evolution in the publication trend, usage of keywords, and identified the prominent themes of manufacturing strategy. Based on the thematic analysis of literature, a systemic manufacturing strategy formulation framework is proposed. Further, we determined the critical strategies considered in the manufacturing domain and mapped their evolution according to the industrial revolutions. This study provides significant contributions to the progression of the manufacturing strategy domain by recommending future research opportunities identified through the literature analysis. The practitioners and policymakers can utilise the proposed systemic manufacturing strategy framework to formulate the strategy at their firm.
Journal: International Journal of Production Research
Pages: 569-594
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1971788
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1971788
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Template-Type: ReDIF-Article 1.0
Author-Name: Yongsoon Eun
Author-X-Name-First: Yongsoon
Author-X-Name-Last: Eun
Author-Name: Kang Liu
Author-X-Name-First: Kang
Author-X-Name-Last: Liu
Author-Name: Semyon M. Meerkov
Author-X-Name-First: Semyon M.
Author-X-Name-Last: Meerkov
Title: Production systems with cycle overrun: modelling, analysis, improvability and bottlenecks
Abstract: 
 Production systems literature usually attributes throughput losses to two reasons: unreliable equipment and random part processing time (also referred to as machine cycle time). In practice, however, one more reason for throughput losses is observed: cycle overrun. The specificity of cycle overrun is that not all parts may require more time than allotted by a fixed cycle time and, if the overrun does occur, its duration is coupled with the part processing time: typically, it is a fraction or a small multiple of the cycle time. This paper is indented to develop methods for analysis and improvement of production systems with unreliable machines and cycle overrun. Specifically, it introduces a mathematical model of an unreliable machine with cycle overrun, develops its simplified version, explores the efficacy of machines' improvability by reducing either downtime or cycle overrun, and discusses the issue of bottleneck identification. These results are obtained under the exponential assumption on machine reliability and overruns and then extended to the non-exponential case. Finally, the methods developed are illustrated by a case study based on an automotive transmission case machining line.
Journal: International Journal of Production Research
Pages: 534-548
Issue: 2
Volume: 60
Year: 2022
Month: 01
X-DOI: 10.1080/00207543.2021.1968528
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1968528
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Template-Type: ReDIF-Article 1.0
Author-Name: Antonio Costa
Author-X-Name-First: Antonio
Author-X-Name-Last: Costa
Author-Name: Salvatore Cannella
Author-X-Name-First: Salvatore
Author-X-Name-Last: Cannella
Author-Name: Roberto R. Corsini
Author-X-Name-First: Roberto R.
Author-X-Name-Last: Corsini
Author-Name: Jose M. Framinan
Author-X-Name-First: Jose M.
Author-X-Name-Last: Framinan
Author-Name: Sergio Fichera
Author-X-Name-First: Sergio
Author-X-Name-Last: Fichera
Title: Exploring a two-product unreliable manufacturing system as a capacity constraint for a two-echelon supply chain dynamic problem
Abstract: 
 In this paper, we investigate a two-echelon, two-product Supply Chain (SC) inspired by a real-world production/distribution firm, in which the product change-over time, necessary to switch from a product to another, induces a variable capacity in the factory. Such a varying production capacity is further exacerbated by the machine breakdowns that may occur in the manufacturing system. Since the two products share the same production system, a production planning rule has to be executed to decide the change-over, i.e. to select the product to be manufactured over time. An extended experimental campaign has been performed to investigate how the fill rate and the standard deviation of inventories vary as a series of operational and tactical parameters changes. Several ANOVA analyses revealed a strong interaction between the production planning model and the adopted smoothing replenishment strategy, which remarkably affects the performance of the SC. Interestingly, a higher value of the proportional controller negatively affects the service levels since the adopted production planning policy, under these circumstances, tends to encourage longer production runs for a certain product and, consequently, persistent stock outs for the other one.
Journal: International Journal of Production Research
Pages: 1105-1133
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1852480
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1852480
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Template-Type: ReDIF-Article 1.0
Author-Name: Sihan Huang
Author-X-Name-First: Sihan
Author-X-Name-Last: Huang
Author-Name: Guoxin Wang
Author-X-Name-First: Guoxin
Author-X-Name-Last: Wang
Author-Name: Yan Yan
Author-X-Name-First: Yan
Author-X-Name-Last: Yan
Title: Building blocks for digital twin of reconfigurable machine tools from design perspective
Abstract: 
 Reconfigurable machine tool (RMT) is the core facility of the reconfigurable manufacturing system (RMS), which can provide customised flexibility for RMS through reconfiguration. The reconfiguration of RMT is complicated due to unpredictable changes in demand and the flexibility of RMT, where new RMT should be designed to satisfy the new demand. The concept of digital twin of RMT is introduced to solve complex reconfiguration problems by executing reconfiguration experiments on high-fidelity virtual RMT. Considering the design processes of RMT during reconfiguration, three building blocks for digital twin of RMT should be studied thoroughly, including structure design, configuration generation, and configuration evaluation. First, the structure design of RMT for multi-part families is studied, including the design principles, module division, and design method. Second, the configuration generation process of RMT based on the results of the structure design is analysed, where quantitative description of configuration is proposed to facilitate the generation process. Third, configuration evaluation is presented to confirm the performance of each configuration based on kinematics analysis. Finally, a case study is provided to demonstrate the effectiveness of the proposed three building blocks for digital twin of RMT during reconfiguration to obtain suitable design scheme of RMT.
Journal: International Journal of Production Research
Pages: 942-956
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1847340
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1847340
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Template-Type: ReDIF-Article 1.0
Author-Name: Yipei Zhang
Author-X-Name-First: Yipei
Author-X-Name-Last: Zhang
Author-Name: Ada Che
Author-X-Name-First: Ada
Author-X-Name-Last: Che
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Title: Improved model and efficient method for bi-objective closed-loop food supply chain problem with returnable transport items
Abstract: 
 Closed-loop supply chains (CLSC) for food products mostly focus on the recovery of the residual value of food itself. Food packaging that plays an important role in food supply chain has rarely been studied. This paper aims to investigate an integrated multi-period closed-loop food supply chain planning problem with returnable transport items (RTIs) in which the total profit and the environmental impact are simultaneously considered. For the problem, an improved bi-objective mixed-integer linear program is formulated with obtained valid inequalities. Especially, the model with valid inequalities can reduce nearly 50% of the average computation time compared with the initial one. To solve the problem, a kernel-search heuristic based ε-constraint method is developed to obtain an approximate Pareto front. Finally, a fuzzy logic-based technique is adapted to help decision makers select a preferred solution according to his/her preference. A real case study from a slaughterhouse illustrates that the proposed method can improve the company’s current strategy for a 7-day planning. Computational results of randomly generated instances demonstrate that the proposed method outperforms the exact ε-constraint method in terms of computational time while providing good approximation.
Journal: International Journal of Production Research
Pages: 1051-1068
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1851057
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1851057
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Template-Type: ReDIF-Article 1.0
Author-Name: Frederik Ferid Ostermeier
Author-X-Name-First: Frederik Ferid
Author-X-Name-Last: Ostermeier
Title: On the trade-offs between scheduling objectives for unpaced mixed-model assembly lines
Abstract: 
 Scheduling decisions in mixed-model assembly lines are frequently multi-objective. No work till date has jointly examined the impact of the production sequence in unpaced manual mixed-model assembly lines operated as permutation flow shops concerning a set of objectives broad enough to capture the interests of its customers and suppliers as well as the manufacturer’s interests related to productivity, production flow and human aspects. This work sets up a simulation study based on a real unpaced mixed-model assembly line with seven products to analyse the impact of five different sequence types on objectives from all these interest fields while modelling human learning and deterioration effects explicitly. The results show that considerable trade-offs exist as different sequence types are preferred for the various scheduling objectives. For makespan and mean flow time as widely used productivity– and flow-related objectives, cases of conflicts and complementarity can be found depending on the actual operational conditions in terms of product and volume mix. A strong dilemma emerges between supplier– and human-related objectives favouring different sequence types. Concerning due date based customer-related objectives, the preferred sequence type varies with the operational conditions. The observed trade-offs confirm the multi-objective nature of the scheduling decision.
Journal: International Journal of Production Research
Pages: 866-893
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1845914
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1845914
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Template-Type: ReDIF-Article 1.0
Author-Name: Xing Wan
Author-X-Name-First: Xing
Author-X-Name-Last: Wan
Author-Name: Xingquan Zuo
Author-X-Name-First: Xingquan
Author-X-Name-Last: Zuo
Author-Name: Xiaodong Li
Author-X-Name-First: Xiaodong
Author-X-Name-Last: Li
Author-Name: Xinchao Zhao
Author-X-Name-First: Xinchao
Author-X-Name-Last: Zhao
Title: A hybrid multiobjective GRASP for a multi-row facility layout problem with extra clearances
Abstract: 
 The multi-row facility layout problem (MRLP) is an important design problem often encountered in real life. Existing studies on MRLPs typically either ignore clearances between adjacent machines or consider only the minimum clearances. However, separating adjacent machines with clearances greater than the minimum ones may achieve lower material flow cost. In addition, current studies on MRLPs ignore the optimisation of layout area. In this paper, we study a multi-row facility layout problem with extra clearances (MRLP-EC), with the objectives of minimising material flow cost and layout area. A mixed integer programming formulation is established for MRLP-EC. A hybrid approach combining an improved multi-objective greedy randomised adaptive search procedure (mGRASP) and linear programming (LP) is proposed for the problem. The mGRASP is used to optimise machine sequences to obtain a set of non-dominated machine sequences. A segments-based dominance method is suggested to measure the dominance relationship of any pair of machine sequences. LP is used to optimise extra clearances between adjacent machines (i.e. the exact location of each machine) for each non-dominated machine sequence. The proposed approach is compared against an exact method and two multi-objective heuristics. Experiments show that the approach is effective for MRLP-EC and outperforms comparative approaches.
Journal: International Journal of Production Research
Pages: 957-976
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1847342
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1847342
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Template-Type: ReDIF-Article 1.0
Author-Name: Stephan Dreyer
Author-X-Name-First: Stephan
Author-X-Name-Last: Dreyer
Author-Name: Andreas Egger
Author-X-Name-First: Andreas
Author-X-Name-Last: Egger
Author-Name: Louis Püschel
Author-X-Name-First: Louis
Author-X-Name-Last: Püschel
Author-Name: Maximilian Röglinger
Author-X-Name-First: Maximilian
Author-X-Name-Last: Röglinger
Title: Prioritising smart factory investments – A project portfolio selection approach
Abstract: 
 Industry 4.0, which describes the transformation of existing production environments toward smart factories, is implemented in ever more manufacturing companies. Smart factories offer diverse advantages such as high flexibility, dynamic scheduling, as well as accurate fault diagnosis and prediction. Hence, manufacturing companies need support for assessing which projects they should implement to transform their production environment. As no such guidance exists in the literature, we propose a multi-dimensional decision model that accounts for interdependencies among production components, for projects with different performance effects, and for digital capabilities constitutive of smart factories (i.e., real-time ability, interoperability, virtualisation and decentralisation). The decision model schedules smart factory projects over multiple planning periods and assesses project roadmaps in line with objectives that comply with established performance measures and the digital capabilities of smart factories. We evaluate and discuss the decision model in interviews with two factory managers and three researchers with great experience in the smart factory domain. Based on a software prototype, we also successfully applied the decision model at a manufacturing company based on real-world data.
Journal: International Journal of Production Research
Pages: 999-1015
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1849845
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1849845
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiuyi Zhang
Author-X-Name-First: Xiuyi
Author-X-Name-Last: Zhang
Author-Name: Wenhua Hou
Author-X-Name-First: Wenhua
Author-X-Name-Last: Hou
Author-Name: Wenqing Zhang
Author-X-Name-First: Wenqing
Author-X-Name-Last: Zhang
Title: Simultaneous or sequential? Multihoming launch strategies for mobile applications with consideration of promotion and switching costs
Abstract: 
 As the number of apps in mobile application markets soars, platforms make significant promotion efforts to help new apps stand out. Some app developers adopt a sequential launch strategy with which they postpone launching the app in other platforms to be eligible for free promotion on the first-launch platform. We model an app developer that considers two platforms. Our results show that for the sequential launch strategy, the developer’s optimal pricing decisions rely on the switching costs to motivate users to adopt different purchase options. Surprisingly, if the switching costs are extremely high, the price on the second launch platform could exceed that on the first launch platform. In addition, we compare the sequential and simultaneous launch strategies and find that switching costs always play a vital role in developers’ launch decisions even when no user switches. Furthermore, developers may prefer the sequential strategy when the app quality is low due to low quality decay. Besides, we extend our model to a situation in which the app is free of charge. While this study focuses on the app market, our results can also be applied to game or video markets where similar phenomena exist.
Journal: International Journal of Production Research
Pages: 977-998
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1847343
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1847343
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Template-Type: ReDIF-Article 1.0
Author-Name: Haoxun Chen
Author-X-Name-First: Haoxun
Author-X-Name-Last: Chen
Author-Name: Bo Dai
Author-X-Name-First: Bo
Author-X-Name-Last: Dai
Author-Name: Yuan Li
Author-X-Name-First: Yuan
Author-X-Name-Last: Li
Author-Name: Yidong Zhang
Author-X-Name-First: Yidong
Author-X-Name-Last: Zhang
Author-Name: Xiaoqing Wang
Author-X-Name-First: Xiaoqing
Author-X-Name-Last: Wang
Author-Name: Yuming Deng
Author-X-Name-First: Yuming
Author-X-Name-Last: Deng
Title: Stock allocation in a two-echelon distribution system controlled by (s, S) policies
Abstract: 
 Stock allocation is an important decision in distribution systems, which determines how the on-hand inventory of an upstream stock is allocated to its immediate downstream stocks if their replenishment orders cannot be fulfilled completely. In the literature, almost all studies assume each stock in a distribution system is controlled by a base stock policy, although a real system may be controlled by (s, S) policies because of the existence of fixed ordering costs. In this paper, we study stock allocation in a real distribution system of Alibaba and propose two easy-to-implement Allocation-to-S methods that are more effective than three well-known rationing rules and a rationing rule currently used in Alibaba. For the 300 instances tested, one of the methods can reduce the expected cost per period by more than 1.5% and improve the service level by more than 1.3% on average with respect to the best of the four rules. In addition, a general procedure is provided to solve the imbalance problem of linear rationing rules which include the rules.
Journal: International Journal of Production Research
Pages: 894-911
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1845915
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1845915
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Template-Type: ReDIF-Article 1.0
Author-Name: Yunxia Han
Author-X-Name-First: Yunxia
Author-X-Name-Last: Han
Author-Name: Yiliu Tu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Tu
Author-Name: Linhan Ouyang
Author-X-Name-First: Linhan
Author-X-Name-Last: Ouyang
Author-Name: Jianjun Wang
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wang
Author-Name: Yizhong Ma
Author-X-Name-First: Yizhong
Author-X-Name-Last: Ma
Title: Economic quality design under model uncertainty in micro-drilling manufacturing process
Abstract: 
 Integrated parameter design and tolerance design (IPTD) is an effective way to improve product quality and reduce manufacturing cost in micro-manufacturing processes. However, the current modeling techniques rarely analyze the influence of model uncertainty on the optimal machining parameters. It may not obtain the robust optimal machining parameters due to model uncertainty. This paper proposes a novel economically integrated design method which considers the correlations among quality characteristics, the variability of manufacturing process, and uncertainty in the model predictions. First, a new rework and scrap cost functions are established via Monte Carlo simulation. Meanwhile, an integrative expected quality loss function is constructed based on interval analysis theory for quantifying model uncertainty. Second, to make the proposed method closer to the practical micro-manufacturing problem, we consider the trade-offs among cost, time, and success rate in the modeling process. Finally, a total cost model is proposed to take into account the quality loss, tolerance cost, unit manufacturing cost, and scrap cost. The effectiveness of the proposed modeling method is verified by a laser beam micro-drilling manufacturing. The results illustrate that the proposed method can achieve better robustness property and economically than the traditional method that does not consider model uncertainty.
Journal: International Journal of Production Research
Pages: 1086-1104
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1851792
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1851792
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Nuno O. Fernandes
Author-X-Name-First: Nuno O.
Author-X-Name-Last: Fernandes
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Title: Production planning and control in multi-stage assembly systems: an assessment of Kanban, MRP, OPT (DBR) and DDMRP by simulation
Abstract: 
 Multi-stage assembly systems where the demand for components depends on the market-driven demand for end products, are commonly encountered in practice. Production Planning and Control (PPC) systems for this production context include Kanban, Materials Requirement Planning (MRP), Optimised Production Technology (OPT), and Demand Driven MRP (DDMRP). All four of these PPC systems are widely applied in practice and literature abounds on each of these systems. Yet, studies comparing these systems are scarce and remain largely inconclusive. In response, this study uses simulation to assess the performance of all four PPC systems under different levels of bottleneck severity and due date tightness. Results show that MRP performs the worst, which can be explained by the enforcement of production start dates. Meanwhile, Kanban and DDMRP perform the best if there is no bottleneck. If there is a bottleneck then DDMRP and OPT perform the best, with DDMRP realising lower inventory levels. If there is a severe bottleneck, then the performance results for DDMRP and OPT converge. This identification of contingency factors not only resolves some of the inconsistencies in the literature but also has important implications for the applicability of these four PPC systems in practice.
Journal: International Journal of Production Research
Pages: 1036-1050
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1849847
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1849847
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhengmin Zhang
Author-X-Name-First: Zhengmin
Author-X-Name-Last: Zhang
Author-Name: Zailin Guan
Author-X-Name-First: Zailin
Author-X-Name-Last: Guan
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Dan Luo
Author-X-Name-First: Dan
Author-X-Name-Last: Luo
Author-Name: Lei Yue
Author-X-Name-First: Lei
Author-X-Name-Last: Yue
Title: Improved multi-fidelity simulation-based optimisation: application in a digital twin shop floor
Abstract: 
 In recent years, the literature has paid considerable attention to digital twin technology for the implementation of Industry 4.0 and intelligent manufacturing. Most of the literature argues that simulation models are a key platform for digital twins and considers discrete-event simulation to be a suitable method to model real dynamic manufacturing systems. However, the discrete-event simulation of complex manufacturing systems is a time-consuming process. Therefore, it is difficult to deal with the large-scale discrete optimisation problems in digital twin shop floors. To bridge this research gap, we propose an improved multi-fidelity simulation-based optimisation method based on multi-fidelity optimisation with ordinal transformation and optimal sampling (MO2TOS) in the current research. The proposed method embeds heuristic algorithms to accelerate the solution space search efficiency in MO2TOS. Moreover, we develop an improved multi-fidelity simulation-based optimisation system by integrating the proposed method with discrete-event simulation tools and apply this system to a digital twin-based aircraft parts production workshop. Based on this digital twin shop floor, we conduct different production planning experiments to evaluate the performance of the proposed method. The experimental results demonstrate that the proposed improved multi-fidelity simulation-based optimisation method is well-applied in solving large-scale problems and outperforms other simulation-based optimisation methods.
Journal: International Journal of Production Research
Pages: 1016-1035
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1849846
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1849846
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Template-Type: ReDIF-Article 1.0
Author-Name: Iracyanne Retto Uhlmann
Author-X-Name-First: Iracyanne Retto
Author-X-Name-Last: Uhlmann
Author-Name: Renata Mariani Zanella
Author-X-Name-First: Renata Mariani
Author-X-Name-Last: Zanella
Author-Name: Enzo Morosini Frazzon
Author-X-Name-First: Enzo Morosini
Author-X-Name-Last: Frazzon
Title: Hybrid flow shop rescheduling for contract manufacturing services
Abstract: 
 Several approaches for strategic and tactical integration of supply chains considering the demand management process have been proposed in the literature. However, in the context of Industry 4.0, there is a lack of studies related to the scheduling and rescheduling process integrating industries on the operational level. This paper proposes a novel hybrid flow shop rescheduling procedure to address the integration, on the operational level, of a contract manufacturer, who handles production execution and inventory control, and their industrial customers, who are in charge of the delivery planning process. The research question emerged from the empirical problem of connecting a contract manufacturer with its industrial customers. In alignment with the findings in the literature review, based on an updated conceptual model, a real hybrid flow shop was modelled using a multi-method approach that combines discrete event and agent-based simulation. The results show improvements in overall production and delivery performance. One can say that this is the first time that a production rescheduling problem is handled considering industries’ integration at the operational level. Even though the primary motivation of this research was to solve a production rescheduling issue in a Contract Manufacturer, the developed approach allows application in any B2B partnership.
Journal: International Journal of Production Research
Pages: 1069-1085
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1851422
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1851422
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Template-Type: ReDIF-Article 1.0
Author-Name: Kai Wang
Author-X-Name-First: Kai
Author-X-Name-Last: Wang
Author-Name: Fugee Tsung
Author-X-Name-First: Fugee
Author-X-Name-Last: Tsung
Title: Bayesian cross-product quality control via transfer learning
Abstract: 
 Quality control is essential for modern business success. The traditional statistical process control (SPC), however, lacks efficacy in current high-variety low-volume industrial practices since the historical reference data in Phase I are usually too scarce to infer the in-control process parameters accurately. To solve this ‘small data’ challenge, a novel Bayesian process monitoring scheme via transfer learning is proposed to facilitate a cross-product data sharing. In particular, a joint prior distribution is taken to explicitly capture the relatedness between the process data of two similar products, through which the process information can be transferred from one product (source domain) to improve the Bayesian inference for the other product (target domain). The posteriors can be derived analytically in closed forms by using generalised hypergeometric functions, thereby leading to a computationally efficient control chart for the online real-time monitoring in Phase II. A user-specified parameter is also provided to enable a better theoretical understanding of the transferability matter and a free practical control of the transferred information across domains. Extensive numerical simulations and real example studies of an assembly process validate the superiority of our proposed scheme in terms of both the false alarm rate and detection capability.
Journal: International Journal of Production Research
Pages: 847-865
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1845413
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1845413
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Template-Type: ReDIF-Article 1.0
Author-Name: Jabir E.
Author-X-Name-First: Jabir
Author-X-Name-Last: E.
Author-Name: Vinay V. Panicker
Author-X-Name-First: Vinay V.
Author-X-Name-Last: Panicker
Author-Name: R. Sridharan
Author-X-Name-First: R.
Author-X-Name-Last: Sridharan
Title: Environmental friendly route design for a milk collection problem: the case of an Indian dairy
Abstract: 
 The green vehicle routing problem advised by the global sustainability conscience is a seminal work on the contemporary green research in supply chain management. Inspired by the replete, pollution routing literature, the present work acknowledges the significance of redesigning the logistic networks in a low emission perspective. The present research proposes three logistic models to address the vehicle routing problem of a dairy plant for collecting milk from chilling centres. The first model generates classical, distance centric and economically viable milk pickup plans. In the second model, the environmental friendly routes are generated. The third model is slated to bring a tradeoff between the first two models. The three models are formulated as integer linear programming models and are solved with branch-and-bound based exact algorithm. Owing to the complexity of the NP-hard problem for generating time-bound results, an ant colony optimisation algorithm is designed to solve the models. The performance of the algorithm is further enhanced by introducing a powerful variable neighbourhood search. The computational study on hybrid algorithm reports an average 0.25% improvement from a time interrupted solution of the exact algorithm. The study recommends decisive managerial insights for implementing green principles to the dairy industry.
Journal: International Journal of Production Research
Pages: 912-941
Issue: 3
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1846219
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1846219
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Template-Type: ReDIF-Article 1.0
Author-Name: Miaohui Zhu
Author-X-Name-First: Miaohui
Author-X-Name-Last: Zhu
Author-Name: Frank Y. Chen
Author-X-Name-First: Frank Y.
Author-X-Name-Last: Chen
Author-Name: Xiang T. R. Kong
Author-X-Name-First: Xiang T. R.
Author-X-Name-Last: Kong
Author-Name: Kaida Qin
Author-X-Name-First: Kaida
Author-X-Name-Last: Qin
Title: Data-driven storage location method for put system in Chinese flower auction centres
Abstract: 
 The rapid increase in daily transactions poses severe challenges for Chinese flower auction centres, including more frequent travels for distribution workers and longer waiting times for buyers. Two distinctive features of Chinese flower auctions further complicate the studied process: buyer identities and purchased volumes of present buyers are not known in advance. Buyer identities become known only after their first bid and purchased volumes by present buyers remain uncertain until the end of the auction. To address these problems, we propose a data-driven storage location method for put systems in Chinese flower auction centres which reserves predetermined locations near the distribution I/O point to large potential buyers before their actual arrival and the remaining locations to other arriving buyers according to the closest open location policy. We use the mesh adaptive direct search algorithm to determine the size of the reserved area and release time of any unoccupied locations to later arriving buyers. The proposed method is verified via a case study, and results show that it outperforms the existing method by a fairly large margin.
Journal: International Journal of Production Research
Pages: 1231-1244
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1856434
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856434
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Template-Type: ReDIF-Article 1.0
Author-Name: Ilaria Giannoccaro
Author-X-Name-First: Ilaria
Author-X-Name-Last: Giannoccaro
Author-Name: Anas Iftikhar
Author-X-Name-First: Anas
Author-X-Name-Last: Iftikhar
Title: Mitigating ripple effect in supply networks: the effect of trust and topology on resilience
Abstract: 
 The ripple effect refers to disruption propagation across the supply network affecting its global performance. To cope with it, supply networks should be resilient. This study investigates the drivers of supply network resilience, viewed as adaptive capacity to disruptions, focusing on trust and investigating the moderating role of network topology on the relationship between trust and resilience. We first develop an NK agent-based model of the supply network to simulate resilient performance. Then, a simulation analysis is carried out, to assess the effect of trust on the resilience of supply networks displaying different complex topologies. Our results confirm that trust positively affects supply network resilience; however, across the different topologies, the beneficial effect of trust varies. In particular, we find that trust is beneficial at most for the following topologies: local, small-world, block-diagonal, and random. For centralised, diagonal, and hierarchical topologies improving trust increases resilience at a moderat e level. We also find that, as the frequency of disruptions rises, the positive effect of trust on resilience decreases. Managerial implications of the main findings are finally discussed.
Journal: International Journal of Production Research
Pages: 1178-1195
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1853844
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1853844
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:4:p:1178-1195




Template-Type: ReDIF-Article 1.0
Author-Name: Shouting Zhao
Author-X-Name-First: Shouting
Author-X-Name-Last: Zhao
Author-Name: Juliang Zhang
Author-X-Name-First: Juliang
Author-X-Name-Last: Zhang
Author-Name: T. C. E. Cheng
Author-X-Name-First: T. C. E.
Author-X-Name-Last: Cheng
Title: Coordinating supply chains with uncertain production cost by incomplete contracts
Abstract: 
 Production cost affects heavily supply chain coordination, but it is uncertain in many cases. We consider a supply chain consisting of a manufacturer and a retailer, where the unit production cost is uncertain when the firms sign a procurement contract. We derive the optimal decisions and profits for the centralised and decentralised cases. We show that production cost uncertainty exaggerates the supply chain’s incentive conflict, but may increase the expected profit in the centralised decision case. Then we design an incomplete contract, which sets a wholesale price and an order quantity in the first stage, which the firms can re-negotiate after the production cost is realised in the second stage. We prove that such an incomplete contract can lead to the first best outcome. We further consider the case with asymmetric cost information and show that the incomplete contract can also coordinate the supply chain. Furthermore, we discuss how the degree of contract incompleteness, re-negotiation freedom, and residual control rights affect the supply chain performance. The results reveal that the hold-up problem is prone to occur with improper contract incompleteness, re-negotiation freedom, and residual control rights, while the incomplete contract we propose can effectively avoid the problem.
Journal: International Journal of Production Research
Pages: 1386-1410
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1856957
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856957
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Template-Type: ReDIF-Article 1.0
Author-Name: Francisco J. Aldarondo
Author-X-Name-First: Francisco J.
Author-X-Name-Last: Aldarondo
Author-Name: Yavuz A. Bozer
Author-X-Name-First: Yavuz A.
Author-X-Name-Last: Bozer
Title: Expected distances and alternative design configurations for automated guided vehicle-based order picking systems
Abstract: 
 Automated Guided Vehicle (AGV)-based order picking (OP) systems, also known as Robotic Mobile Fulfilment Systems, continues to receive attention in industry and academia since their introduction as Kiva systems. A key component of AGV-based OP systems is the ‘robots’ (or AGVs) that pick up the ‘pods’ and transport them to the appropriate pick station (PS), where a picker picks the items ordered by customers. The performance of such systems depends on the shape of the forward area (FA) and the number of AGVs, which in turn depends on the time it takes an AGV to retrieve a pod. To aid system designers, we explore alternative shapes for the FA and we derive closed-form expressions for the expected AGV travel distances under two possible order assignment rules. Under the random assignment rule, an order is assigned to any PS with equal probability. Under the closest assignment rule, the order is assigned to the closest PS. We also examine the impact of alternative PS configurations for different shapes of the FA. The results offer valuable insights concerning expected travel distances under alternative design configurations. The results would also be useful when building design and performance evaluation models for AGV-based OP systems.
Journal: International Journal of Production Research
Pages: 1298-1315
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1856438
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856438
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Template-Type: ReDIF-Article 1.0
Author-Name: Nuno O. Fernandes
Author-X-Name-First: Nuno O.
Author-X-Name-Last: Fernandes
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Title: Direct Workload Control: simplifying continuous order release
Abstract: 
 Workload Control withholds orders from the shop floor in a backlog from which they are released to meet certain performance metrics. This release decision precedes the execution of orders at shop floor stations. For each station there are consequently three types of workload: indirect, released work that is still upstream of the station; direct, work that is currently at the station; and, completed, work that is still on the shop floor but is downstream of the station. Most release methods control an aggregate workload made up of some representation of at least two of these three workload types. Yet the core objective of Workload Control release methods relates to only one of the three types – that is, to create a small, stable direct load in front of each station. Clearly, order release would be greatly simplified if only the direct load had to be considered. Using discrete event simulation, we show that Direct Workload Control leads to performance levels that match those of more complex and sophisticated approaches to Workload Control. Further, it greatly simplifies continuous order release, decentralising the release decision by allowing it to be executed at each gateway station. This has important implications for research and practice.Highlights
Presents a new Workload Control release method that controls the direct load only.The new method significantly simplifies workload calculations.The new method can be decentralised with control exercised locally at gateway stations.Simulation results demonstrate comparable performance to more sophisticated methods.The new method improves the performance of large jobs.
Journal: International Journal of Production Research
Pages: 1424-1437
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1857451
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1857451
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Template-Type: ReDIF-Article 1.0
Author-Name: Wanying (Amanda) Chen
Author-X-Name-First: Wanying (Amanda)
Author-X-Name-Last: Chen
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: René B. M. de Koster
Author-X-Name-First: René B. M.
Author-X-Name-Last: de Koster
Title: Performance estimation of a passing-crane automated storage and retrieval system
Abstract: 
 Storage and retrieval automation has progressed rapidly. One such popular storage and retrieval system deploys two passing aisle-bound cranes. Each crane can access every location in the rack. To pass the other crane and prevent collision, each crane has to timely move the platform to an appropriate level and simultaneously rotate it. We develop a queuing model with preemptive-resume interrupted service to estimate the system response time (and hence throughput capacity) while considering two I/O point positions, random storage, and a crane assignment policy where all requests are shared between the cranes. The analytical models are validated with simulation based on the data from real cases. We find that a design with I/O points located in the middle of the rack will increase the interference, but it has a high relative throughput because of the reduced expected travel time. Compared with a system with one crane, a two-crane system has interference, but it can improve the system efficiency, especially in large systems with high job arrival rates. The model can be extended to other systems where multiple cranes are used in a single travel aisle with crane interference, e.g. passing cranes operating in a container stack lane.
Journal: International Journal of Production Research
Pages: 1210-1230
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1854886
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1854886
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:4:p:1210-1230




Template-Type: ReDIF-Article 1.0
Author-Name: Mirco Peron
Author-X-Name-First: Mirco
Author-X-Name-Last: Peron
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Jan Ola Strandhagen
Author-X-Name-First: Jan Ola
Author-X-Name-Last: Strandhagen
Title: Decision support model for implementing assistive technologies in assembly activities: a case study
Abstract: 
 The use of assistive technologies, such as digital instructions (DIs) and collaborative robots (cobots), can improve the productivity of assembly system. However, their implementation remains arbitrary. In this study, a decision support system based on tactical-level variables (i.e. throughput, operator and equipment cost, operation time and type) was proposed with the aim of suggesting when the introduction of assistive technologies becomes profitable. Four different assembly system configurations (i.e. manual assembly, manual assembly with the implementation of DIs, manual assembly with the implementation of cobots and manual assembly with the implementation of both DIs and cobots) were modelled by means of four different cost models and analysed in depth with a parametric analysis carried out by varying the tactical-level variables. The results suggested that, when the throughput is low, the introduction of cobots should be considered only in cases of high operation times, while the introduction of DIs and/or cobots is the best alternative when the throughput is high. Finally, the validity of the approach is proved by comparing the results suggested by the decision support system with those obtained from a case study.
Journal: International Journal of Production Research
Pages: 1341-1367
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1856441
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856441
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Template-Type: ReDIF-Article 1.0
Author-Name: Bo Yang
Author-X-Name-First: Bo
Author-X-Name-Last: Yang
Author-Name: Shilong Wang
Author-X-Name-First: Shilong
Author-X-Name-Last: Wang
Author-Name: Shi Li
Author-X-Name-First: Shi
Author-X-Name-Last: Li
Author-Name: Tianguo Jin
Author-X-Name-First: Tianguo
Author-X-Name-Last: Jin
Title: A robust service composition and optimal selection method for cloud manufacturing
Abstract: 
 During the process of cloud manufacturing, various uncertainties in the real world could have a significant impact on the smooth execution of task, and could render the planned composite manufacturing service (CMS) inefficient or even ineffective. Therefore, this paper proposes an optimal selection method to enhance the robustness of CMS during the planning stage. Firstly, the structure of robust CMS is proposed by arranging the preferred and alternative services for each subtask, and a robust service composition and optimal selection (rSCOS) model of cloud manufacturing is constructed by defining the expected Quality of Service. Then, the gABC-GWO (guiding artificial bee colony – grey wolf optimisation) algorithm is proposed to solve the rSCOS model efficiently, in which three improvement strategies for ABC algorithm are designed according to the characteristics of GWO. Finally, two experiments are implemented and the results show that QoS of the preferred scheme of robust CMS is approximately 1.29% lower than that of CMS on average, while its robustness is improved by 1.81% and 13.14% depending on the two robustness indexes. Compared with other commonly-used intelligence optimisation algorithms, gABC-GWO algorithm possesses better search performance without significantly increasing time consumption, which makes it more suitable for solving rSOCS problems.
Journal: International Journal of Production Research
Pages: 1134-1152
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1852481
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1852481
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:4:p:1134-1152




Template-Type: ReDIF-Article 1.0
Author-Name: Mehmet Ali Soytaş
Author-X-Name-First: Mehmet Ali
Author-X-Name-Last: Soytaş
Author-Name: Damla Durak Uşar
Author-X-Name-First: Damla
Author-X-Name-Last: Durak Uşar
Author-Name: Meltem Denizel
Author-X-Name-First: Meltem
Author-X-Name-Last: Denizel
Title: Estimation of the static corporate sustainability interactions
Abstract: 
 The empirical literature considers firm-specific aspects affecting corporate sustainability decisions but generally omits the influence of the competition. We advocate that sustainability actions of a company impact its marketplace and vice versa. Therefore, the sustainability return of the single firm is a function of the other firms’ sustainability decisions. We approach sustainability decisions as strategic decisions and evaluate the effect of competition and spillovers in a static market entry game. We estimate the parameters of the discrete choice model using the social performance ratings from MSCI KLD 400 Social Index as proxy for sustainability decisions and financial information from Wharton Research Data Services’ COMPUSTAT dataset. When strategic interaction is not accounted for, we find that an increase in the number of competitors increases the likelihood of sustainability investments, seemingly shows the spillover effect dominates the competition. When we apply the multi-stage approach, which incorporates competitive interaction, we provide empirical evidence that the effect of competition on the likelihood of entry into the sustainability market dominates the effect of spillover. We find that strategic motives, typically ignored in the empirical literature, appear to be an important factor in understanding sustainability-related decisions.
Journal: International Journal of Production Research
Pages: 1245-1264
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1856435
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856435
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:4:p:1245-1264




Template-Type: ReDIF-Article 1.0
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Title: A linear model for optimal cybersecurity investment in Industry 4.0 supply chains
Abstract: 
 This paper presents a mixed integer linear programming formulation for optimisation of cybersecurity investment in Industry 4.0 supply chains. Using a recursive linearisation procedure, a complex nonlinear stochastic combinatorial optimisation model with a classical exponential function of breach probability is transformed into its linear equivalent. The obtained linear optimisation model is capable of selecting optimal portfolio of security safeguards to minimise cybersecurity investment and expected cost of losses from security breaches in a supply chain. The new efficiency measures of cybersecurity investment are introduced: cybersecurity value and cybersecurity ratio. In addition, the proposed linear model has been enhanced for the Hurwicz-type, best–worst criterion to minimise a convex combination of the minimal and the maximal supply chain node vulnerability, under limited budget. The resulting compromise cybersecurity investment aims at balancing vulnerability over the entire supply chain, independent of cyberattack probabilities and potential losses by security breaches, thereby hardening the weaker critical nodes. The findings indicate a crucial role of intrinsic vulnerability, determined by the architecture of Industry 4.0 supply chain, and highlight ‘design for cybersecurity’ as an important emerging area of research.
Journal: International Journal of Production Research
Pages: 1368-1385
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1856442
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856442
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:4:p:1368-1385




Template-Type: ReDIF-Article 1.0
Author-Name: Ugur Satic
Author-X-Name-First: Ugur
Author-X-Name-Last: Satic
Author-Name: Peter Jacko
Author-X-Name-First: Peter
Author-X-Name-Last: Jacko
Author-Name: Christopher Kirkbride
Author-X-Name-First: Christopher
Author-X-Name-Last: Kirkbride
Title: Performance evaluation of scheduling policies for the dynamic and stochastic resource-constrained multi-project scheduling problem
Abstract: 
 In this study, we consider the dynamic and stochastic resource-constrained multi-project scheduling problem where projects generate rewards at their completion, completions later than a due date cause tardiness costs, task duration is uncertain, and new projects arrive randomly during the ongoing project execution both of which disturb the existing project scheduling plan. We model this problem as a discrete-time Markov decision process and explore the performance and computational limitations of solving the problem by dynamic programming. We run and compare five different solution approaches, which are: a dynamic programming algorithm to determine a policy that maximises the time-average profit, a genetic algorithm and an optimal reactive baseline algorithm, both generate a schedule to maximise the total profit of ongoing projects, a rule-based algorithm which prioritises processing of tasks with the highest processing durations, and a worst decision algorithm to seek a non-idling policy that minimises the time-average profit. The performance of the optimal reactive baseline algorithm is the closest to the optimal policies of the dynamic programming algorithm, but its results are suboptimal, up to 37.6%. Alternative scheduling algorithms are close to optimal with low project arrival probability but quickly deteriorate their performance as the probability increases.
Journal: International Journal of Production Research
Pages: 1411-1423
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1857450
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1857450
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Template-Type: ReDIF-Article 1.0
Author-Name: Tarik Chargui
Author-X-Name-First: Tarik
Author-X-Name-Last: Chargui
Author-Name: Abdelghani Bekrar
Author-X-Name-First: Abdelghani
Author-X-Name-Last: Bekrar
Author-Name: Mohamed Reghioui
Author-X-Name-First: Mohamed
Author-X-Name-Last: Reghioui
Author-Name: Damien Trentesaux
Author-X-Name-First: Damien
Author-X-Name-Last: Trentesaux
Title: Scheduling trucks and storage operations in a multiple-door cross-docking terminal considering multiple storage zones
Abstract: 
 Cross-docking is a logistics process in which products are unloaded through receiving docks and then transferred to shipping docks with almost no storage in between. In this paper, a mixed integer linear programming model (MILP) is proposed to optimise the scheduling, storage, assignment and sequencing of trucks at receiving and shipping docks for a problem inspired from a multiple-door cross-dock facility of an industrial partner with multiple temporary storage zones. The multiple storage zones are separated and located in the centre of the cross-dock handling different types of products. The objective is to minimise the total tardiness of inbound and outbound trucks. A heuristic (H) is proposed to find an initial solution. Then, three meta-heuristics are developed, namely Random Search (RS), Tabu Search (TS) and Simulated Annealing (SA) to improve the scheduling of trucks in order to minimise the tardiness of inbound and outbound trucks. Experimental results indicate that the three meta-heuristics (RS, TS and SA) are able to find good quality results within reasonable computational times. Finally, since SA showed the best performance compared to RS and TS, it was chosen to be compared to the current manual method using discrete event simulation.
Journal: International Journal of Production Research
Pages: 1153-1177
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1853843
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1853843
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:4:p:1153-1177




Template-Type: ReDIF-Article 1.0
Author-Name: Peiyu Zhang
Author-X-Name-First: Peiyu
Author-X-Name-Last: Zhang
Author-Name: Yankui Liu
Author-X-Name-First: Yankui
Author-X-Name-Last: Liu
Author-Name: Guoqing Yang
Author-X-Name-First: Guoqing
Author-X-Name-Last: Yang
Author-Name: Guoqing Zhang
Author-X-Name-First: Guoqing
Author-X-Name-Last: Zhang
Title: A distributionally robust optimisation model for last mile relief network under mixed transport
Abstract: 
 The last mile relief network is the final stage of the relief chain but the most critical stage for ensuring the timely delivery of relief supplies after a disaster. Due to the suddenness of the disaster, balancing the shortages of relief supplies and the high demands of victims is a serious problem. We introduce a mixed transport way of relief supply transportation between points of distributions and demand nodes in our problem to face the manpower and resource limitations. We establish a bi-objective distributionally robust optimisation model to balance transportation time and transportation safety, where the demand, transportation time, freight and safety coefficient are assumed to be uncertain variables with partial distribution information. We also deduce the refinement robust counterparts under the ambiguous sets to prove the safe tractable approximations of chance constraints. Finally, we conduct a case study of Tonghai county earthquake to illustrate the efficiency of our proposed distributionally robust model.
Journal: International Journal of Production Research
Pages: 1316-1340
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1856439
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856439
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Template-Type: ReDIF-Article 1.0
Author-Name: Ping Zhang
Author-X-Name-First: Ping
Author-X-Name-Last: Zhang
Author-Name: King-Wah Pang
Author-X-Name-First: King-Wah
Author-X-Name-Last: Pang
Author-Name: Hong Yan
Author-X-Name-First: Hong
Author-X-Name-Last: Yan
Title: Coordinating inventory sharing with retailer's return in the consignment contracts
Abstract: 
 Hospitals purchase medical supplies from the dealer on consignment contracts. Dealer provides a return policy for unused inventory but charging a return fee. Two hospitals could share inventory which reduces the amount of return to the dealer. Motivated by this consignment contract policy for the medical supply chain, we develop a common dealer and two independent retailers framework that considers retailers' sharing action and return problem. We aim at developing a coordinating mechanism to manage the retailers' sharing and return action that benefits both the dealer and retailers. Dealer-dominated sharing and retailer-dominated sharing are compared from the perspective of sharing performance and expected profits. We also analyse the condition that the dealer is better off from retailers' sharing when the dealer has the power to encourage retailers' sharing, and the dealer's trading preference for a non-cooperative retailer or cooperative retailers when the dealer has no power to encourage retailers' sharing. Numerical experiments are conducted to examine the sensitivity of retailers' sharing decisions, retailers' and dealer's profit to the return price.
Journal: International Journal of Production Research
Pages: 1196-1209
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1854485
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1854485
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:4:p:1196-1209




Template-Type: ReDIF-Article 1.0
Author-Name: E. Bourreau
Author-X-Name-First: E.
Author-X-Name-Last: Bourreau
Author-Name: T. Garaix
Author-X-Name-First: T.
Author-X-Name-Last: Garaix
Author-Name: M. Gondran
Author-X-Name-First: M.
Author-X-Name-Last: Gondran
Author-Name: P. Lacomme
Author-X-Name-First: P.
Author-X-Name-Last: Lacomme
Author-Name: N. Tchernev
Author-X-Name-First: N.
Author-X-Name-Last: Tchernev
Title: A constraint-programming based decomposition method for the Generalised Workforce Scheduling and Routing Problem (GWSRP)
Abstract: 
 This paper deals with the Generalised Workforce Scheduling and Routing Problem (GWSRP) where 9 temporal constraints ensuring visit dependencies are all together taken into account and where customer and worker’s quality of service are taken into consideration. A Constraint-Programming based Decomposition Method (CPDM) is proposed, firstly based on a relaxation of coordination constraints and a column generation, and secondly with an iterative insertion of coordination constraint by constraint programming solver. Numerical experiments are achieved on huge instances derived from WSRP benchmark instances with up to 177 customers, 59 vehicles and coordination constraints. The CPDM is able to find nearly optimal solution for medium-size instances and find high-quality solution for huge-size instances whereas CPLEX solver applied to a mixed integer linear model is not able to give a solution in this case.
Journal: International Journal of Production Research
Pages: 1265-1283
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1856436
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856436
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:4:p:1265-1283




Template-Type: ReDIF-Article 1.0
Author-Name: Te Xu
Author-X-Name-First: Te
Author-X-Name-Last: Xu
Author-Name: Yongxia Liu
Author-X-Name-First: Yongxia
Author-X-Name-Last: Liu
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Author-Name: Chang Liu
Author-X-Name-First: Chang
Author-X-Name-Last: Liu
Title: Improvement of Kriging interpolation with learning kernel in environmental variables study
Abstract: 
 Kriging interpolation is a spatial interpolation method widely employed in the field of data analytics and prediction of environmental variables, which provides the best linear unbiased prediction of intermediate values. The core principle of Kriging interpolation is searching for data distribution regularity and predicting regionalised variable value, and it can be transferred into two descriptions of learning process: function fitting problem and coefficient optimisation problem. Although these two problems could be solved by many traditional algorithms like multiple linear regression method, the parameter estimation of variogram model becomes quite difficult when there are drifts or noises in the raw data. The purpose of this paper is to improve the Kriging interpolation algorithm with learning kernels based on Estimation of Distribution Algorithms (EDAs) and Least-Squares Support Vector Machine (LSSVM). The experiments have been carried out based on a real-world case with environmental variables. Compared with other machine learning methods, experimental results verify the effectiveness of the proposed algorithm.
Journal: International Journal of Production Research
Pages: 1284-1297
Issue: 4
Volume: 60
Year: 2022
Month: 02
X-DOI: 10.1080/00207543.2020.1856437
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1856437
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:4:p:1284-1297




Template-Type: ReDIF-Article 1.0
Author-Name: M. P. Doan
Author-X-Name-First: M. P.
Author-X-Name-Last: Doan
Author-Name: J. Fondrevelle
Author-X-Name-First: J.
Author-X-Name-Last: Fondrevelle
Author-Name: V. Botta-Genoulaz
Author-X-Name-First: V.
Author-X-Name-Last: Botta-Genoulaz
Author-Name: J. F. F. Ribeiro
Author-X-Name-First: J. F. F.
Author-X-Name-Last: Ribeiro
Title: Impact of flexible work contracts and multi-skilled agents on a multi-objective workforce planning problem
Abstract: 
 This article studies the impact of flexible work contracts and multi-skilled agents on a multi-objective workforce planning problem. Each agent has a work contract with a weekly and daily work capacity. The company has to create a planning for its agents to fulfil the customers’ demands. When assigning agents to specific demands, three different objectives have to be attained, including minimising the travel costs between agents’ home and their workplace, and maximising agents’ satisfaction related to the workload balance between them, and to their preferences for certain working periods. In the context of the evolution of the demands over time, the company has to introduce different levers to increase the level of workforce flexibility. Flexible work contracts and multiple skills are the two levers that are focused on here. The mixed integer linear programming method is used to model and solve the problem. Numerical experiments with real data provided by a Brazilian company show the positive impact of these two levers on the feasibility of problem solving and on the quality of the solutions obtained. Different managerial recommendations based on these results are proposed to companies to help improve their strategy for workforce development.
Journal: International Journal of Production Research
Pages: 1650-1665
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1867922
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1867922
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:5:p:1650-1665




Template-Type: ReDIF-Article 1.0
Author-Name: Lei Guan
Author-X-Name-First: Lei
Author-X-Name-Last: Guan
Author-Name: Jun Pei
Author-X-Name-First: Jun
Author-X-Name-Last: Pei
Author-Name: Xinbao Liu
Author-X-Name-First: Xinbao
Author-X-Name-Last: Liu
Author-Name: Zhiping Zhou
Author-X-Name-First: Zhiping
Author-X-Name-Last: Zhou
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Title: Ridesharing in urban areas: multi-objective optimisation approach for ride-matching and routeing with commuters’ dynamic mode choice
Abstract: 
 The daily home-office commute of millions of people in crowded cities strains air quality and increases travel time, which motivates the generation of ridesharing. Ridesharing offers many benefits, such as reducing travel costs, congestion, and pollution. Commuter ridesharing is an important theme of urban transportation. This paper studies a ridesharing problem aiming at enlarging the ridesharing market at a limited cost, which enlighten the decision-making problem in city logistics. We establish a novel multi-objective optimisation model based on cumulative prospect theory (CPT) to address the preferred travel mode of commuters. The commuters’ perceived value influences their choice of travel mode. Meanwhile, the perceived value changes with the commuters’ experience of travel mode choice. We give the NP-hardness proof of the ridesharing scheduling problem and develop a heuristic algorithm to solve it in a small-scale scenario. For large-scale problems, a hybrid VNS-NSGAII algorithm combining variable neighbourhood search (VNS) with NSGAII (Non-dominated Sorting Genetic Algorithm II) is proposed to generate an approximate optimal Pareto front. A series of computational experiments are conducted to demonstrate the effectiveness and efficiency of the proposed algorithm based on the actual traffic data in Beijing, China.
Journal: International Journal of Production Research
Pages: 1439-1457
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1859635
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1859635
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:5:p:1439-1457




Template-Type: ReDIF-Article 1.0
Author-Name: Merve Ozen
Author-X-Name-First: Merve
Author-X-Name-Last: Ozen
Author-Name: Ananth Krishnamurthy
Author-X-Name-First: Ananth
Author-X-Name-Last: Krishnamurthy
Title: G-network models to support planning for disaster relief distribution
Abstract: 
 One of the key activities during disaster response is distributing relief items to victims. This is a challenging task due to dynamically changing victim needs and disaster aftermath conditions. We model the distribution operations where items like tarpaulins and blankets are distributed by volunteers, to victims at temporary distribution areas called relief centers (RC). We investigate the impact victim movements have on the distribution performance. We model each RC as a queue, and the distribution operation as a generalised queuing network (G-network). We investigate product form solutions for the proposed G-network model, and prove a new product form result for G-networks with signals and batch transfer under certain conditions. We leverage this result to develop product form approximations that apply across a broad range of settings. We apply the G-network model to a case study using the Nepal earthquake relief distribution data, and quantify the impact of victim movement on network performance.
Journal: International Journal of Production Research
Pages: 1621-1632
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1867920
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1867920
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:5:p:1621-1632




Template-Type: ReDIF-Article 1.0
Author-Name: Jun Wang
Author-X-Name-First: Jun
Author-X-Name-Last: Wang
Author-Name: Rahul Rai
Author-X-Name-First: Rahul
Author-X-Name-Last: Rai
Title: Generative design of conformal cubic periodic cellular structures using a surrogate model-based optimisation scheme
Abstract: 
 Cellular structures (CSs) exhibit unique combinations of physical properties, including low weight, high structural strength, and substantial energy absorption, which could be useful in a variety of applications. Further, with the advent of additive manufacturing (AM), CSs are now easier to fabricate. While CSs and AM open up transformative opportunities, their potential for everyday use in industrial practice still lies largely idle. One of the major reasons is the lack of computational tools that allow us to automatically explore, verify, and optimise CSs and skin elements to create an optimised component that meets the exact specification. In this paper, we outline a periodic CS-based generative design pipeline that offers automated modelling, analysis, and inverse design solving of CS through the use of an integrated optimisation and finite-element analysis (FEA) framework. Specifically, a surrogate model-based optimisation scheme is proposed to design light-weight and high-strength functional parts by taking advantage of spatially varying conformal cubic periodic cellular structures.
Journal: International Journal of Production Research
Pages: 1458-1477
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1859637
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1859637
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:5:p:1458-1477




Template-Type: ReDIF-Article 1.0
Author-Name: Xuehong Gao
Author-X-Name-First: Xuehong
Author-X-Name-Last: Gao
Author-Name: Guozhong Huang
Author-X-Name-First: Guozhong
Author-X-Name-Last: Huang
Author-Name: Qiuhong Zhao
Author-X-Name-First: Qiuhong
Author-X-Name-Last: Zhao
Author-Name: Cejun Cao
Author-X-Name-First: Cejun
Author-X-Name-Last: Cao
Author-Name: Huiling Jiang
Author-X-Name-First: Huiling
Author-X-Name-Last: Jiang
Title: Robust optimization model for medical staff rebalancing problem with data contamination during COVID-19 pandemic
Abstract: 
 After the outbreak of the COVID-19 pandemic, the naturally dissimilar prevalence of infection resulted in a growing imbalance between supply and demand for medical staff. Rebalancing the medical staff seems a pressing task following the uncertain environment. However, once the collected data are contaminated, the optimal solution obtained through traditional methods may be located far away from the true one. In this sense, finding a robust optimization method that is less sensitive to outliers and accounts for uncertain future events is warranted. Consequently, this study deeply investigates the medical staff rebalancing problem with data contamination and proposes two robust optimization models to cure the detrimental consequences caused by contaminated data. Due to the nonlinearity of the proposed robust models, the corresponding linearisation approaches are developed to determine the unique medical staff rebalancing scheme. To validate the proposed models and methods, a real case study from the U.S. is implemented. Finally, study results indicate that the proposed methods can overcome the effects of data contamination, and deep managerial implications and actionable insights from theory and practice regarding the cooperation mechanism and medical staff rebalancing strategies are drawn from the case study, which provides the main needs and benefits of this study.
Journal: International Journal of Production Research
Pages: 1737-1766
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1995793
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1995793
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:5:p:1737-1766




Template-Type: ReDIF-Article 1.0
Author-Name: Shayan Tavakoli Kafiabad
Author-X-Name-First: Shayan
Author-X-Name-Last: Tavakoli Kafiabad
Author-Name: Masoumeh Kazemi Zanjani
Author-X-Name-First: Masoumeh Kazemi
Author-X-Name-Last: Zanjani
Author-Name: Mustapha Nourelfath
Author-X-Name-First: Mustapha
Author-X-Name-Last: Nourelfath
Title: Workforce training and operations planning for maintenance centres under demand uncertainty
Abstract: 
 Companies that provide repair & overhaul services to the users of complex technical systems are confronted with uncertain volume of demand when making tactical decisions such as workforce training and planning of repair operations over an annual planning horizon. Given the high importance of equipment availability (e.g. gas turbines) to the users (e.g, power plants), any delay in the delivery of repaired equipment caused by demand uncertainty would lead to significant penalties and loss of customer goodwill. In this paper, a two-stage stochastic programming model is proposed to obtain the optimal number of items to repair, spare part inventory, and the number of operators to train with the goal of minimising the total expected cost of maintenance operations and late delivery. Outsourcing and borrowing strategies are adopted as corrective measures to reduce the probability of late delivery in the emerge of demand uncertainty. Numerical findings illustrate the importance of integrating uncertainty into these operations planning decisions as well as the mitigation strategies in handling the cost of the system.
Journal: International Journal of Production Research
Pages: 1587-1599
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1866781
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1866781
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Template-Type: ReDIF-Article 1.0
Author-Name: Junkai He
Author-X-Name-First: Junkai
Author-X-Name-Last: He
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Title: Integrated stochastic disassembly line balancing and planning problem with machine specificity
Abstract: 
 The disassembly is a fundamental basis in converting End-of-Life (EOL) products into useful components. Related research becomes popular recently due to the increasing awareness of environmental protection and energy conservation. Yet, there are many opening questions needed to be investigated, especially the efficient coordination of different-level decisions under uncertainty is a big challenge. In this paper, a novel integrated stochastic disassembly line balancing and planning problem is studied to minimise the system cost, where component yield ratios and demands are assumed to be uncertain. In this work, machine specificities are considered for task processing, such as price, ability, and capacity. For the problem, a two-stage non-linear stochastic programming model is first constructed. Then, it is further transformed into a linear formulation. Based on problem property analysis, a valid inequality is proposed to reduce the search space of optimal solutions. Finally, a sample average approximation (SAA) and an L-shaped algorithm are adopted to solve the problem. Numerical experiments on randomly generated instances demonstrate that the valid inequality can save around 11% of average computation time, and the L-shaped algorithm can save around 64% of average computation time compared with the SAA algorithm without a big sacrifice of the solution quality.
Journal: International Journal of Production Research
Pages: 1688-1708
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1868600
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1868600
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Template-Type: ReDIF-Article 1.0
Author-Name: Yong Jae Kim
Author-X-Name-First: Yong Jae
Author-X-Name-Last: Kim
Author-Name: Jae Won Jang
Author-X-Name-First: Jae Won
Author-X-Name-Last: Jang
Author-Name: David S. Kim
Author-X-Name-First: David S.
Author-X-Name-Last: Kim
Author-Name: Byung Soo Kim
Author-X-Name-First: Byung Soo
Author-X-Name-Last: Kim
Title: Batch loading and scheduling problem with processing time deterioration and rate-modifying activities
Abstract: 
 This research addresses a single machine batch loading and scheduling problem. Jobs in the same family are processed as a batch in the machine with a known family-specific processing time. Each job in a batch requires a known volume or space, and the total batch volume cannot exceed the available volume/capacity of the machine. Batch processing times increase proportionately with the time since the most recent rate-modifying activity and the starting time of a batch. A rate-modifying activity can be executed which restores original batch processing times. In this research, a solution procedure is proposed that simultaneously determines the appropriate batching of jobs and the number of rate-modifying activities. Job batches and the rate-modifying activities are then sequenced to minimise the makespan. To develop a solution procedure, a mixed integer linear programming model is formulated and a tight lower bound is proposed. Three genetic algorithms (GAs), including batch loading and sequencing heuristics, are proposed. The performance of the three GAs is compared, and the best GA is compared to other meta-heuristic algorithms.
Journal: International Journal of Production Research
Pages: 1600-1620
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1866783
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1866783
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Template-Type: ReDIF-Article 1.0
Author-Name: Thiago Cantos Lopes
Author-X-Name-First: Thiago Cantos
Author-X-Name-Last: Lopes
Author-Name: Nadia Brauner
Author-X-Name-First: Nadia
Author-X-Name-Last: Brauner
Author-Name: Leandro Magatão
Author-X-Name-First: Leandro
Author-X-Name-Last: Magatão
Title: Assembly line balancing with fractional task allocations
Abstract: 
 Assembly line balancing usually presupposes binary task-station assignments. Some authors have previously described efficiency increases due to fractional task allocations or work-sharing. However, the internal storage requirements for such efficiency increases have not been analytically described. This paper defines the Fractional Allocation Assembly Line Balancing Problem and presents mixed-integer linear programming models to bridge that gap. The main opportunity afforded by the studied flexibility is increased throughput, which is associated to higher internal storage costs. Worst-case analyses define mathematical expressions for these costs both for paced (line length) and unpaced lines (buffers). A screening on a 1050-instance dataset is conducted. Results suggest that fractional allocations can often allow better resource utilisation with relatively low costs: the higher space requirement costs are often one-time investments, while lower cycle time represents fundamentally continuous gains. Lastly, the proposed formulation was adapted and applied to industrial data. This mixed-model assembly line case study suggests that fractional allocations can also lead to more robust balancing regarding demand uncertainty.
Journal: International Journal of Production Research
Pages: 1569-1586
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1866224
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1866224
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Template-Type: ReDIF-Article 1.0
Author-Name: Tobias Mönch
Author-X-Name-First: Tobias
Author-X-Name-Last: Mönch
Author-Name: Arnd Huchzermeier
Author-X-Name-First: Arnd
Author-X-Name-Last: Huchzermeier
Author-Name: Peter Bebersdorf
Author-X-Name-First: Peter
Author-X-Name-Last: Bebersdorf
Title: Variable takt time groups and workload equilibrium
Abstract: 
 Natural disasters, pandemics, and political nationalism force companies toward more responsive, flexible, and resilient assembly systems. For manufacturers, adaptability of the assembly process and local production ensure short product lead times even during supply chain disruptions. Yet one downside of regional production is that fixed takt time assembly lines become overburdened, especially when customisation is unlimited. In this context, variable takt time groups (VTGs) are a major competitive lever. We introduce the notion of a workload equilibrium balancing overload and underutilization. This preliminary stage of the assembly line balancing and sequencing problem significantly reduces the planning effort. Moreover, we present a model for minimising (i) the number of VTGs for a given maximum operator drift per unit or (ii) the maximum operator drift per unit for a given number of VTGs. We solve these dynamic problems by developing a heuristic approach: the variable takt time groups algorithm (VTGA). In our analysis of three real-world data sets from two German manufacturers—Fendt and Rolls-Royce Power Systems—we benchmark the VTGA against existing takt times. We find that VTGs result in higher labour efficiency than a fixed takt time and that the VTGs segmentation level plays an important role in reducing operator inefficiencies.
Journal: International Journal of Production Research
Pages: 1535-1552
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1864836
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1864836
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Template-Type: ReDIF-Article 1.0
Author-Name: Qiao Wu
Author-X-Name-First: Qiao
Author-X-Name-Last: Wu
Author-Name: Naiming Xie
Author-X-Name-First: Naiming
Author-X-Name-Last: Xie
Author-Name: Shaoxiang Zheng
Author-X-Name-First: Shaoxiang
Author-X-Name-Last: Zheng
Title: Integrated cross-supplier order and logistic scheduling in cloud manufacturing
Abstract: 
 In the cloud manufacturing environment, integrated cross-supplier order and logistic scheduling can benefit both suppliers and third-party logistics, significantly reduce their production and transport costs to improve the overall efficiency of the supply chain. This paper aims to construct a hybrid solution with both cross-supplier order assignments and third-party logistics scheduling under a centralised scheduling mode of cloud manufacturing platform, which is defined as an integrated cross-supplier order and logistic scheduling (ICSOLS) problem. Since the problem is NP-hard, a strategy based on an improved shuffled frog-leaping algorithm was developed for solving the model. A numerical case was designed for demonstrating the modelling process and analysing results. Different scales of simulations are designed to verify validity and robustness. Results show the proposed approach and algorithm can solve the defined problem efficiently.
Journal: International Journal of Production Research
Pages: 1633-1649
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1867921
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1867921
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Template-Type: ReDIF-Article 1.0
Author-Name: Chen Hu
Author-X-Name-First: Chen
Author-X-Name-Last: Hu
Author-Name: Yongbo Xiao
Author-X-Name-First: Yongbo
Author-X-Name-Last: Xiao
Author-Name: Jianbin Li
Author-X-Name-First: Jianbin
Author-X-Name-Last: Li
Title: Immediate sale or stock-up: value of rent-to-own contracts for experience goods
Abstract: 
 Many high-value experience goods, such as pianos and Chinese zithers, are usually characterized by uncertain future values. As such, a portion of customers (called ‘consumers’) may hesitate to buy the product because they are unsure of the product’s actual value and/or they may expect to buy the product at a lower price in the future. Moreover, the fluctuating future value creates arbitrage opportunities for another group of customers (called ‘speculators’) who may benefit from stocking up a product and reselling it at a higher price at a future time. Considering a firm that sells a limited number of high-value experience goods over two periods, this paper investigates the profitability of a rent-to-own (R2O) contract, under which a consumer can return the product in the future period (e.g. when it turns out to be inappropriate) or buy the product at the realised future price. We study the optimal pricing decisions involved in the R2O contract for two scenarios. In the base model, the uncertain future price is exogenously given, and in the extended model, the future price is endogenously determined by the firm and speculators. Numerical experiments are conducted to evaluate the value of R2O contracts.
Journal: International Journal of Production Research
Pages: 1709-1736
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1869342
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1869342
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Template-Type: ReDIF-Article 1.0
Author-Name: Timothy L. Urban
Author-X-Name-First: Timothy L.
Author-X-Name-Last: Urban
Title: Component ordering policies for selective assembly
Abstract: 
 Selective assembly is an approach in which high-precision assemblies can be produced from relatively low-precision components or subassemblies. This research investigates component ordering policies for fixed-bin selective-assembly processes that consider the stochastic nature of the binning process as well as stochastic demand. The distributional aspects of the assembly process are identified, and an approximation of the number of assemblies completed is provided utilising extreme-value theory. The order quantity can then be determined to meet demand with a given service level; an implicit-enumeration procedure is presented to illustrate this process. Computational results illustrate that this is an effective approach for controlling component inventories.
Journal: International Journal of Production Research
Pages: 1520-1534
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1864674
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1864674
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Template-Type: ReDIF-Article 1.0
Author-Name: Hongping Li
Author-X-Name-First: Hongping
Author-X-Name-Last: Li
Author-Name: Gongbing Bi
Author-X-Name-First: Gongbing
Author-X-Name-Last: Bi
Author-Name: Wen Song
Author-X-Name-First: Wen
Author-X-Name-Last: Song
Author-Name: Xiaoyong Yuan
Author-X-Name-First: Xiaoyong
Author-X-Name-Last: Yuan
Title: Trade credit insurance: insuring strategy of the retailer and the manufacturer
Abstract: 
 This study analyses the role of trade credit insurance and the insuring strategy of the retailer and the manufacturer in a capital-constrained supply chain with one retailer, one manufacturer, and one insurer. We model the interaction among these three participants as a two-level Stackelberg game and explore their operational and financial decisions. We find that trade credit insurance is adopted when the manufacturer's loss aversion is high or the retailer's initial capital is low. The adoption of trade credit insurance improves the order quantity of the retailer, the performance of each supply chain participant, and supply chain efficiency. However, it also increases the bankruptcy risk of the retailer and the instability of the entire supply chain. In addition, the application of trade credit insurance by the manufacturer alone is more beneficial to the manufacturer, insurer, and entire supply chain as it creates better performance for them. Conversely, the purchase of trade credit insurance by the retailer is more desirable to the retailer as it yields not only a higher profit but also a lower bankruptcy risk.
Journal: International Journal of Production Research
Pages: 1478-1499
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1861358
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1861358
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Template-Type: ReDIF-Article 1.0
Author-Name: Shenghai Zhou
Author-X-Name-First: Shenghai
Author-X-Name-Last: Zhou
Author-Name: Qing Yue
Author-X-Name-First: Qing
Author-X-Name-Last: Yue
Title: Sequencing and scheduling appointments for multi-stage service systems with stochastic service durations and no-shows
Abstract: 
 In this work, we consider a joint sequencing and scheduling appointments problem with stochastic service times and no-shows in multi-stage service systems. The objective is to minimise the total expected weighted costs of customers' waiting times and service providers' idle times over multiple stages. For the problem, we first formulate it as a stochastic program and exploit the sample average approximation approach to reformulate it as a mixed-integer program in further. Then we transform the stochastic program into a two-stage optimisation problem and develop a standard Benders decomposition algorithm. To overcome the long running time of Benders decomposition, we simplify the master problem in the algorithm and propose a Benders decomposition-based algorithm to find a near-optimal solution. Finally, we conduct a series of numerical experiments to illustrate the efficiency of our proposed algorithm, examine the impact of the number of stages, stochastic service times and no-shows on the optimal job allowances and performance indicators (i.e. waiting times and idle times) and investigate two easy-to-implement sequence rules. The computational results show that both our proposed Benders decomposition-based algorithm and easy-to-implement sequence rules perform well.
Journal: International Journal of Production Research
Pages: 1500-1519
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1862431
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1862431
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Template-Type: ReDIF-Article 1.0
Author-Name: Vincent Hovelaque
Author-X-Name-First: Vincent
Author-X-Name-Last: Hovelaque
Author-Name: Jean-Laurent Viviani
Author-X-Name-First: Jean-Laurent
Author-X-Name-Last: Viviani
Author-Name: Mohamed Ait Mansour
Author-X-Name-First: Mohamed
Author-X-Name-Last: Ait Mansour
Title: Trade and bank credit in a non-cooperative chain with a price-sensitive demand
Abstract: 
 The purpose of this article is to examine the impact of the working capital in the borrowing decision of a retailer. The proposed analysis is based on a model with a retailer, a supplier and a bank in a non-cooperative game with price-sensitive demand. The retailer, the supplier and the bank (if concerned) determine, respectively, the ordering quantity, the wholesale price and the interest rate. A Stackelberg game-theoretic approach is employed where the retailer is a follower and either the supplier or the bank is the leader. Some structural properties are first derived from the mathematical models. Then, some numerical simulations show that: (i) a trade credit guarantees the same profits for the retailer and the supplier as in the case where the retailer has sufficient cash holdings, (ii) there exist some situations where the retailer has a better profit with a borrow than with sufficient cash holdings, and (iii) borrowing decision depends on both retailer's and supplier's discount rate and the retailer's cash holdings.
Journal: International Journal of Production Research
Pages: 1553-1568
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1866222
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1866222
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Template-Type: ReDIF-Article 1.0
Author-Name: Lama Moussawi-Haidar
Author-X-Name-First: Lama
Author-X-Name-Last: Moussawi-Haidar
Author-Name: Hoda Daou
Author-X-Name-First: Hoda
Author-X-Name-Last: Daou
Author-Name: Khalil Khalil
Author-X-Name-First: Khalil
Author-X-Name-Last: Khalil
Title: Joint reserve stock and just-in-time inventory under regular preventive maintenance and random disruptions
Abstract: 
 We study a repairable production-inventory system with a constant demand rate subject to random disruptions, which supplies an assembly line according to a just-in-time configuration. Preventive maintenance (PM) actions are regularly performed on the production unit at fixed time instants. We assume that the time between breakdowns is constant and the PM and corrective actions have random durations that follow a general probability distribution. We propose the following policy to cope with production interruptions: A buffer stock is built up at the maximum production rate at the beginning of each PM cycle. At the same time, a reserve stock is maintained to hedge against random disruptions and shortages during planned maintenance. The joint convexity of the cost function is established and optimality conditions for the optimal policy parameters are derived. We perform numerical and sensitivity analyses under the exponential and Asymmetric Laplace distributions. The results suggest that: (i) The proposed policy performs better than traditional models that consider these two strategies separately; (ii) As the shortage cost increases, it is optimal to increase the reserve level; (iii) Higher reserve stock levels allow to hedge against the increased duration and rate of preventive maintenance and random disruptions.
Journal: International Journal of Production Research
Pages: 1666-1687
Issue: 5
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1868596
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1868596
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Template-Type: ReDIF-Article 1.0
Author-Name: Li-Hao Zhang
Author-X-Name-First: Li-Hao
Author-X-Name-Last: Zhang
Author-Name: Lin Tian
Author-X-Name-First: Lin
Author-X-Name-Last: Tian
Author-Name: Lu-Yu Chang
Author-X-Name-First: Lu-Yu
Author-X-Name-Last: Chang
Title: Equilibrium strategies of channel structure and RFID technology deployment in a supply chain with manufacturer encroachment
Abstract: 
 The rapid growth of online marketplaces and the advance of Internet technology have enabled manufacturers to more easily engage in direct selling through their own online stores. However, as any retail channel suffers misplacements, the manufacturer's direct sales channel will also face a critical inventory misplacement problem if it chooses encroachment. Radio-frequency identification (RFID) proven to be the most effective technology to eliminate the inventory misplacement problem. This paper investigates the strategic interaction between manufacturer encroachment and RFID deployment decisions in a supply chain consisting of a manufacturer and a reseller. We find that the manufacturers’ encroachment strategies are determined by channels’ misplacement rates, RFID deployment decisions and channel competition intensity. Specifically, the retail (direct) channel's misplacement problem encourages (discourages) the manufacturer to encroach; in addition, if only the retail (if it is direct) channel employs RFID, the encroachment cost threshold increases (decreases) with the RFID tag price; moreover, the more intense the channel competition is, the less likely the manufacturer will be to encroach. Further, when encroachment has occurred, channel competition will be a crucial factor in the direct channel's RFID deployment decision, but it will not affect the deployment of RFID in the retail channel.
Journal: International Journal of Production Research
Pages: 1890-1912
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1876943
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1876943
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Template-Type: ReDIF-Article 1.0
Author-Name: Masoud Kamalahmadi
Author-X-Name-First: Masoud
Author-X-Name-Last: Kamalahmadi
Author-Name: Mansoor Shekarian
Author-X-Name-First: Mansoor
Author-X-Name-Last: Shekarian
Author-Name: Mahour Mellat Parast
Author-X-Name-First: Mahour
Author-X-Name-Last: Mellat Parast
Title: The impact of flexibility and redundancy on improving supply chain resilience to disruptions
Abstract: 
 This paper examines the relative impact on supply chain responsiveness of adding flexibility and redundancy. We seek to investigate the effectiveness of flexibility and redundancy in terms of minimising expected supply chain cost and maximizing expected service delivery when a supply chain is exposed to supplier and environmental disruptions. Compared to a supply chain that uses neither strategy and is exposed to supplier and environmental disruptions, both practices reduce expected lost sales, reduce expected total cost, and increase the expected service level. Our results show that the backup-suppliers practice is more effective than the flexible-suppliers practice, as measured by cost reduction and service-level improvement. In addition, we show that a hybrid practice created by adding some level of flexibility to a backup-suppliers practice is more desirable in terms of lowering pre-disruption investment, increasing the responsiveness of the supply chain, and lowering the expected total cost. Moreover, the result of the simulation shows that on average, the proposed stochastic model could decrease the company's total cost by 5.51%. It also shows that planning and investing in proactive demand management could decrease the company's total cost by 7.87%. Our findings provide insights into the contingencies that support implementation of each practice.
Journal: International Journal of Production Research
Pages: 1992-2020
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1883759
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1883759
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Template-Type: ReDIF-Article 1.0
Author-Name: Athanasios Rentizelas
Author-X-Name-First: Athanasios
Author-X-Name-Last: Rentizelas
Author-Name: Nikoletta Trivyza
Author-X-Name-First: Nikoletta
Author-X-Name-Last: Trivyza
Author-Name: Sarah Oswald
Author-X-Name-First: Sarah
Author-X-Name-Last: Oswald
Author-Name: Stefan Siegl
Author-X-Name-First: Stefan
Author-X-Name-Last: Siegl
Title: Reverse supply network design for circular economy pathways of wind turbine blades in Europe
Abstract: 
 Wind energy installations are increasing rapidly and so is their end-of-life waste. Wind turbine blades consist primarily of glass fibers and are usually landfilled. Given the significant amounts of blade waste expected in the future, circular economy pathways need to be identified for this waste stream. This study investigates the feasibility of the circular economy pathway of mechanical recycling for reuse of end-of-life blades at composite material manufacturing, while optimising the required reverse supply network design in Europe, for 2020 and for 2050. This is achieved through formulating and solving to optimality a Mixed Integer Linear Programming model for the wind blades Supply Chain Network Design problem. The findings indicate a semi-decentralised optimal network design, with 3–4 processing facilities proposed around Europe in all scenarios. The proposed circular economy pathway is economically viable without additional policy support only in 2050; while focusing the efforts only in more favourable areas of end-of-life blade availability can reduce system-wide costs. This study contributes to academic knowledge by formulating and solving for the first time the Supply Chain Network Design problem for end-of-life wind blades and to practice and policy-making by providing insights on the optimal network design, its feasibility and the related implications.
Journal: International Journal of Production Research
Pages: 1795-1814
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1870016
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1870016
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Template-Type: ReDIF-Article 1.0
Author-Name: Haixia Zhao
Author-X-Name-First: Haixia
Author-X-Name-Last: Zhao
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Author-Name: Xingzheng Ai
Author-X-Name-First: Xingzheng
Author-X-Name-Last: Ai
Title: Contract strategy in the presence of chain to chain competition
Abstract: 
 This paper studies contract strategy for two competing supply chains selling a substitutable product under demand uncertainty. Each supply chain consists of a risk neutral manufacturer and a risk averse retailer. As Stackelberg leader in each supply chain, each manufacturer needs to decide which type of contract to provide to its retailer, either a revenue sharing contract or a wholesale price contract. We identify the conditions under which each type of contract should be offered in a competitive market, and which type of contract is preferred by manufacturers only, or by both manufacturers and retailers. We show that wholesale price contracts may be a better choice than revenue sharing contracts for the manufacturers, to mitigate fierce chain-to-chain competition. Wholesale price contracts are preferred by the manufacturers over revenue sharing contracts when the price competition is moderate and demand variation is significant. A revenue sharing contract is the dominant choice for both the manufacturers and the retailers when the price competition is weak and demand uncertainty is low, as long as a revenue sharing ratio is negotiated in a proper range, a win-win outcome for all supply chain members.
Journal: International Journal of Production Research
Pages: 1913-1931
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1876945
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1876945
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:6:p:1913-1931



Template-Type: ReDIF-Article 1.0
Author-Name: Arrate Llaguno
Author-X-Name-First: Arrate
Author-X-Name-Last: Llaguno
Author-Name: Josefa Mula
Author-X-Name-First: Josefa
Author-X-Name-Last: Mula
Author-Name: Francisco Campuzano-Bolarin
Author-X-Name-First: Francisco
Author-X-Name-Last: Campuzano-Bolarin
Title: State of the art, conceptual framework and simulation analysis of the ripple effect on supply chains
Abstract: 
 Supply chains are becoming increasingly sophisticated and vital for many firms’ competetiveness. Nevertheless, their interrelated, complex and global nature also makes them more vulnerable to the risk of their operations being interrupted. This article analyzes the ripple effect on supply chains, which occurs when disruption in one node spreads throughout the supply chain and impacts its performance, design and planning parameters. This article offers a systematic review of the existing literature that covers the ripple effect in the supply chain context. It structures and classifies existing research currents and application areas in this context by presenting and analyzing the obtained results. Based on the conclusions obtained with the literature review, a conceptual framework is proposed and includes the main characteristics and perspectives of the ripple effect on supply chains, and the possible proactive and reactive measures to mitigate its effects and to recover from serious disruptions. The conceptual framework is also analyzed and validated by a system dynamics simulation model.
Journal: International Journal of Production Research
Pages: 2044-2066
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1877842
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1877842
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:6:p:2044-2066



Template-Type: ReDIF-Article 1.0
Author-Name: Mateus Martin
Author-X-Name-First: Mateus
Author-X-Name-Last: Martin
Author-Name: Reinaldo Morabito
Author-X-Name-First: Reinaldo
Author-X-Name-Last: Morabito
Author-Name: Pedro Munari
Author-X-Name-First: Pedro
Author-X-Name-Last: Munari
Title: Two-stage and one-group two-dimensional guillotine cutting problems with defects: a CP-based algorithm and ILP formulations
Abstract: 
 We address two variants of the two-dimensional guillotine cutting problem that appear in different manufacturing settings that cut defective objects. Real-world applications include the production of flat glass in the glass industry and the cutting of wooden boards with knotholes in the furniture industry. These variants assume that there are several defects in the object, but the items cut should be defective-free; the cutting pattern is limited to two guillotine stages; and the maximum number of copies per item type in the pattern can be limited. The first variant deals with exact 2-stage patterns, while the second with exact 1-group patterns. To effectively solve these problems, we propose a Constraint Programming (CP) based algorithm as well as different Integer Linear Programming (ILP) formulations. The first presented formulations are extensions of the modelling approach of [Martin, M., E. G. Birgin, R. D. Lobato, R. Morabito, and P. Munari. 2020. “Models for the Two-Dimensional Rectangular Single Large Placement Problem with Guillotine Cuts and Constrained Pattern.” International Transactions in Operational Research 27: 767–793. doi:10.1111/itor.12703] for the case with defects, while the others are novel and more elaborate formulations based on the relative position of the items. We evaluate these three approaches with computational experiments using a set of benchmark instances from the literature. The results show that the approaches find optimal and near-optimal solutions in short processing times for several types of problem instances.
Journal: International Journal of Production Research
Pages: 1854-1873
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1876270
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1876270
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Template-Type: ReDIF-Article 1.0
Author-Name: Yuval Cohen
Author-X-Name-First: Yuval
Author-X-Name-Last: Cohen
Author-Name: Shraga Shoval
Author-X-Name-First: Shraga
Author-X-Name-Last: Shoval
Author-Name: Maurizio Faccio
Author-X-Name-First: Maurizio
Author-X-Name-Last: Faccio
Author-Name: Riccardo Minto
Author-X-Name-First: Riccardo
Author-X-Name-Last: Minto
Title: Deploying cobots in collaborative systems: major considerations and productivity analysis
Abstract: 
 Collaborative robots (cobots) are important components of the Industry 4.0 paradigm and smart manufacturing. Cobots are known for their ability to interact with the operators in a shared workspace. Due to their spread in the last decade, cobot research proliferated. However, most individual studies focused on specific aspects of cobot deployment, and only scant attention was given to their evaluation (mostly not based on productivity criteria). Thus, better support is needed for cobot acquisition and deployment decisions. This paper answers this need by presenting a summary of the major considerations related to cobots acquisition and deployment, and providing a productivity analysis procedure that supports cobot acquisition and deployment decisions. Defining the cobots’ required characteristics and capabilities, effectively narrows the possible selection of cobots. However, it does not give information as to the economic value of acquiring and deploying a specific cobot. So, in addition to cobots’ characteristics and capabilities, this paper presents computational techniques to analyse and support this decision for a single workstation per se, and for a station in an assembly line. The difference between these two cases is discussed and analysed, and corresponding models are presented with computational examples.
Journal: International Journal of Production Research
Pages: 1815-1831
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1870758
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1870758
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Template-Type: ReDIF-Article 1.0
Author-Name: Peixin Ge
Author-X-Name-First: Peixin
Author-X-Name-Last: Ge
Author-Name: Ren Zhao
Author-X-Name-First: Ren
Author-X-Name-Last: Zhao
Author-Name: Defeng Sun
Author-X-Name-First: Defeng
Author-X-Name-Last: Sun
Author-Name: Yun Dong
Author-X-Name-First: Yun
Author-X-Name-Last: Dong
Title: Integrated optimisation of storage and pre-marshalling moves in a slab warehouse
Abstract: 
 In the slab warehouses of iron and steel enterprises, the slabs are stacked on top of others. Thus, some slabs will be blocked by others from being retrieved directly. In this study, we focus on optimising slab storage and pre-marshalling moves in advance so as to minimise the numbers of slabs which may block retrieval slab, the number of stacks occupied by slabs, and the number of required moves. We also address the practical concern of moving no more than two slabs together. To solve this problem, we present an integer linear programming model and further propose valid inequalities to enhance the model. Based on the labelled data from this modelling approach, a self-training technique is applied to train two functions which can predict the optimal following pre-marshalling move and storage move. By combining these functions, heuristics and branch-and-bound algorithm with the dominance rules, a multi-stage hybrid algorithm is proposed to solve practical problems. The experimental results show the effectiveness of the model, the valid inequalities, and the different components of hybrid algorithm which can produce high-quality solutions within seconds.
Journal: International Journal of Production Research
Pages: 2021-2043
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1883760
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1883760
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Template-Type: ReDIF-Article 1.0
Author-Name: Kuo-Hao Chang
Author-X-Name-First: Kuo-Hao
Author-X-Name-Last: Chang
Author-Name: Yi-Jyun Sun
Author-X-Name-First: Yi-Jyun
Author-X-Name-Last: Sun
Author-Name: Chi-An Lai
Author-X-Name-First: Chi-An
Author-X-Name-Last: Lai
Author-Name: Li-Der Chen
Author-X-Name-First: Li-Der
Author-X-Name-Last: Chen
Author-Name: Chih-Hung Wang
Author-X-Name-First: Chih-Hung
Author-X-Name-Last: Wang
Author-Name: Chung-Jung Chen
Author-X-Name-First: Chung-Jung
Author-X-Name-Last: Chen
Author-Name: Chih-Ming Lin
Author-X-Name-First: Chih-Ming
Author-X-Name-Last: Lin
Title: Big data analytics energy-saving strategies for air compressors in the semiconductor industry – an empirical study
Abstract: 
 Industry 4.0, smart manufacturing and its related technologies are now becoming the leading trend in the development of the manufacturing industry. One of the key drivers of Industry 4.0 is big data analytics, which can transform large amounts of data into useful information, enabling astute and rapid decision-making strategies when combined with expert domain knowledge. The semiconductor industry is the most important high-tech industry in Taiwan, but it is also one of the most energy-consuming industries in the country. Therefore, it is critical to improve the efficiency of the manufacturing process and reduce the overall energy consumption of facility systems. This research demonstrates how to apply big data analytics in the semiconductor industry to explore the relationships of various machine parameters, develop predictive models for machine energy efficiency and apply optimisation tools to minimise energy consumption, while meeting the production demands. An empirical study is conducted in conjunction with a semiconductor corporation in Taiwan, targeting the air compressor system in its factory. The research framework is shown to be capable of assisting semiconductor fabrication plant decision-makers in optimising machine configurations, resulting in more than 10% savings on energy consumption and significantly decreased manufacturing costs.
Journal: International Journal of Production Research
Pages: 1782-1794
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1870015
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1870015
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Template-Type: ReDIF-Article 1.0
Author-Name: Ting Yu
Author-X-Name-First: Ting
Author-X-Name-Last: Yu
Author-Name: Kudret Demirli
Author-X-Name-First: Kudret
Author-X-Name-Last: Demirli
Author-Name: Nadia Bhuiyan
Author-X-Name-First: Nadia
Author-X-Name-Last: Bhuiyan
Title: Lean transformation framework for treatment-oriented outpatient departments
Abstract: 
 Long wait times and low resource utilisation are the most critical issues in treatment-oriented outpatient departments. While Lean has been utilised to resolve similar issues in healthcare, the literature provides no structured means of implementing Lean in outpatient departments. This study establishes a Lean transformation framework to identify a balanced patient demand by determining proper patient compositions, to schedule non-specialists to increase resource utilisation, and to level patient schedule throughout the day to reduce wait times. This framework includes a series of activities and Lean tools that are specifically adapted for use in outpatient departments. A case study is presented to illustrate the implementation of the proposed framework and its possible impacts, using data from a community hospital oncology department in Montreal, Canada. Results suggests that this framework reduces patient visit time by 36% and increases daily treatments by 39% and utilisation of chemotherapy chairs by 22%, with a possibility to implement a one-day treatment regime. The proposed framework can assist treatment-oriented outpatient departments to overcome their operational challenges and to serve as an effective guideline in their Lean transformation.
Journal: International Journal of Production Research
Pages: 1767-1781
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2020.1870014
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1870014
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:6:p:1767-1781



Template-Type: ReDIF-Article 1.0
Author-Name: Peiyang He
Author-X-Name-First: Peiyang
Author-X-Name-Last: He
Author-Name: Kunpeng Li
Author-X-Name-First: Kunpeng
Author-X-Name-Last: Li
Author-Name: P. N. Ram Kumar
Author-X-Name-First: P. N. Ram
Author-X-Name-Last: Kumar
Title: An enhanced branch-and-price algorithm for the integrated production and transportation scheduling problem
Abstract: 
 Industry 4.0 technologies, such as artificial intelligence, the internet of things and 3D printing are aiding the manufacturers by complementing their skilled workforce and transforming the way factories are run. This paper studies an integrated production and transportation scheduling problem in the context of the spare parts supply chain by integrating 3D printing with JIT delivery systems. This work aims to find a synchronised production and distribution schedule that minimises the weighted sum of delivery times and transportation costs. Based on the characteristics of the problem, we propose a new set-covering formulation. An enhanced branch-and-price algorithm is designed to solve the problem instances to optimality. To expedite the column generation process, two acceleration strategies are also used. The computational results are in favour of the proposed algorithm and the acceleration strategies. Further, the results indicate that integrating the production and transportation scheduling decisions leads to an average savings of about 16.27% of the total costs.
Journal: International Journal of Production Research
Pages: 1874-1889
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1876941
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1876941
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Template-Type: ReDIF-Article 1.0
Author-Name: Xin Liu
Author-X-Name-First: Xin
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Title: Distributionally robust and risk-averse optimisation for the stochastic multi-product disassembly line balancing problem with workforce assignment
Abstract: 
 Existing works usually focus on the single-product disassembly line balancing problem (DLBP). In practice, end-of-life (EOL) products to be disassembled may be heterogeneous, and the actual processing time of each task may vary with its assigned worker. This work studies a stochastic multi-product DLBP with workforce assignment, to minimise the system cost. Due to historical data scarcity, we assume that only partial distributional information of uncertain task processing times is known. Exceeding the preset cycle time may lead to a disassembly performance reduction, thus we control the cycle time violation via conditional Value-at-Risk (CVaR) constraints, i.e. in a risk-averse fashion. For the problem, we first propose a novel formulation with distributionally robust CVaR constraints. Then some valid inequalities are proposed, leading to an improved model. Two solution approaches, i.e. an exact cutting-plane method and an approximation method, are further proposed and compared, via numerical experiments. Some managerial insights are also drawn.
Journal: International Journal of Production Research
Pages: 1973-1991
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1881648
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1881648
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:6:p:1973-1991



Template-Type: ReDIF-Article 1.0
Author-Name: Changhui Liu
Author-X-Name-First: Changhui
Author-X-Name-Last: Liu
Author-Name: Kun Chen
Author-X-Name-First: Kun
Author-X-Name-Last: Chen
Author-Name: Sun Jin
Author-X-Name-First: Sun
Author-X-Name-Last: Jin
Author-Name: Yuan Qu
Author-X-Name-First: Yuan
Author-X-Name-Last: Qu
Author-Name: Jianbo Yu
Author-X-Name-First: Jianbo
Author-X-Name-Last: Yu
Author-Name: Binghai Zhou
Author-X-Name-First: Binghai
Author-X-Name-Last: Zhou
Title: An integrated method for variation pattern recognition of BIW OCMM online measurement data
Abstract: 
 In order to improve the quality of the body-in-white (BIW), optical coordination measurement machines (OCMM) are used to measure the dimensional variation for BIW. The big OCMM online measurement data with low signal-to-noise ratio makes the variation patterns recognition to be difficult and challenges the traditional statistical process control (SPC) technology and the common variation recognition approaches. In this paper, we propose an automatic and integrated method to recognise the control chart patterns (CCPs), which includes three main modules. The Jarque-Bera test is applied in the wavelet denoising module. The feature extraction module extracts a combination set of shape features and statistical features. In the classifier module, a two-hidden-layer Backpropagation neural network (BPN) is trained and tested. In the experiment, the proposed method is also compared with other CCPs recognition methods. Finally, a practice case is studied to show the application of the integrated method and validate the high recognition accuracy of the integrated system.
Journal: International Journal of Production Research
Pages: 1932-1953
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1877841
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1877841
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:6:p:1932-1953



Template-Type: ReDIF-Article 1.0
Author-Name: Yuhan Guo
Author-X-Name-First: Yuhan
Author-X-Name-Last: Guo
Author-Name: Yu Zhang
Author-X-Name-First: Yu
Author-X-Name-Last: Zhang
Author-Name: Youssef Boulaksil
Author-X-Name-First: Youssef
Author-X-Name-Last: Boulaksil
Author-Name: Ning Tian
Author-X-Name-First: Ning
Author-X-Name-Last: Tian
Title: Multi-dimensional spatiotemporal demand forecasting and service vehicle dispatching for online car-hailing platforms
Abstract: 
 Forecasting transportation demands can aid online car-hailing platforms to dispatch their service vehicles in advance to areas with more potential orders. This results in a reduction in passengers’ waiting time and better utilisation of transportation resources. However, the complexity and dynamics of multi-dimensional influential factors make the forecasting and dispatching procedures challenging. This paper addresses these issues by using machine learning techniques and an effective probabilistic dispatching strategy. Multiple influential factors were identified in spatial, temporal, and meteorological dimensions, and effective machine learning algorithms were applied to predict the number of passenger orders. The fusion of the multi-dimensional features enables the proposed algorithms to better reveal the spatiotemporal characteristics and their correlations. A sensing-area-based strategy was introduced to dispatch available service vehicles to high demand-intensity regions efficiently with respect to the global demand-supply-balance and the individual probability of receiving orders. Finally, extensive experiments with large-scale real-world datasets were conducted to evaluate the performance of the machine learning algorithms and the effectiveness of the dispatching strategy. Overall, this paper extensively studies the forecasting of the spatiotemporal demand in multiple cities using point-of-interest data and the dispatching of available service vehicles based on such information for online car-hailing platforms.
Journal: International Journal of Production Research
Pages: 1832-1853
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1871675
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1871675
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:6:p:1832-1853



Template-Type: ReDIF-Article 1.0
Author-Name: Alex J. Ruiz-Torres
Author-X-Name-First: Alex J.
Author-X-Name-Last: Ruiz-Torres
Author-Name: Giuseppe Paletta
Author-X-Name-First: Giuseppe
Author-X-Name-Last: Paletta
Author-Name: Belarmino Adenso-Díaz
Author-X-Name-First: Belarmino
Author-X-Name-Last: Adenso-Díaz
Title: Hybrid two stage flowshop scheduling with secondary resources based on time buckets
Abstract: 
 This work studies a two-stage hybrid flowshop problem with secondary resources (workers). The goal is to minimise the average tardiness. The workers are assigned to the workstations by time buckets (work shifts), and the assignment changes during the planning horizon. Two versions of the problem are studied: (i) the case where the average efficiency of the workers determines the time to process jobs; (ii) the case where the efficiency of the slowest worker assigned to a workstation determines the time to process jobs. The problem is NP hard and a set of heuristics are proposed to generate job sequences and worker assignments. Computational experiments are performed on randomly generated test problems. The experiments revealed that the proposed heuristics are able to find a large percentage of the optimal solutions for small sized instances, while on large sized instances the heuristic performance depended on experimental factors.
Journal: International Journal of Production Research
Pages: 1954-1972
Issue: 6
Volume: 60
Year: 2022
Month: 03
X-DOI: 10.1080/00207543.2021.1880656
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1880656
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:6:p:1954-1972

Template-Type: ReDIF-Article 1.0
Author-Name: Nícolas P. Campana
Author-X-Name-First: Nícolas P.
Author-X-Name-Last: Campana
Author-Name: Manuel Iori
Author-X-Name-First: Manuel
Author-X-Name-Last: Iori
Author-Name: Mayron César O. Moreira
Author-X-Name-First: Mayron César O.
Author-X-Name-Last: Moreira
Title: Mathematical models and heuristic methods for the assembly line balancing problem with hierarchical worker assignment
Abstract: 
 This paper proposes new algorithms for the assembly line balancing problem with hierarchical worker assignment (ALBHW). The ALBHW appears in real industrial contexts, where companies deal with a multi-skilled workforce. It considers task execution times that vary depending on the worker type to whom the task is assigned. Qualification levels among workers are ranked hierarchically, where a lower qualified worker costs less but requires larger execution times then a higher qualified one. The aim is to assign workers and tasks to the stations of an assembly line, in such a way that cycle time and precedence constraints are satisfied, and the total cost is minimised. In this paper, we first present a mathematical model and improve it with preprocessing techniques. Then, we propose a constructive heuristic and a variable neighbourhood descent that are useful to solve large instances. Extensive computational experiments on benchmark instances prove the effectiveness of the algorithms.
Journal: International Journal of Production Research
Pages: 2193-2211
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1884767
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884767
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Template-Type: ReDIF-Article 1.0
Author-Name: Pinar Yunusoglu
Author-X-Name-First: Pinar
Author-X-Name-Last: Yunusoglu
Author-Name: Seyda Topaloglu Yildiz
Author-X-Name-First: Seyda
Author-X-Name-Last: Topaloglu Yildiz
Title: Constraint programming approach for multi-resource-constrained unrelated parallel machine scheduling problem with sequence-dependent setup times
Abstract: 
 This paper studies the multi-resource-constrained unrelated parallel machine scheduling problem under various operational constraints with the objective of minimising maximum completion time among the scheduled jobs. Sequence-dependent setup times, precedence relations, machine eligibility restrictions and release dates are incorporated into the problem as operational constraints to reflect real-world manufacturing environments. The considered problem is in NP-hard class of problems, which cannot be solved in deterministic polynomial time. Our aim in this study is to develop an exact solution approach based on constraint programming (CP), which shows good performance in solving scheduling problems. In this regard, we propose a CP model and enrich this model by adding lower bound restrictions and redundant constraints. Moreover, to achieve a reduction in computation time, we propose two branching strategies for the proposed CP model. The performance of the CP model is tested using randomly generated and benchmark instances from the literature. The computational results indicate that the proposed CP model outperforms the best solutions with an average gap of 15.52%.
Journal: International Journal of Production Research
Pages: 2212-2229
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1885068
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1885068
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Template-Type: ReDIF-Article 1.0
Author-Name: Peng He
Author-X-Name-First: Peng
Author-X-Name-Last: He
Author-Name: Yong He
Author-X-Name-First: Yong
Author-X-Name-Last: He
Author-Name: Henry Xu
Author-X-Name-First: Henry
Author-X-Name-Last: Xu
Title: Product variety and recovery strategies for a manufacturer in a personalised and sustainable consumption era
Abstract: 
 Personalised consumption and sustainable development are increasingly gaining people’s attention. To meet consumers’ individualised needs and achieve sustainable development, it is very important and urgent for manufacturers to make operations decisions on whether to implement a product variety and/or a product recovery programme. To explore some management implications for firms making those decisions, we develop three analytical game-theoretical models: (1) Model V where the manufacturer only adopts a product variety strategy; (2) Model R where he only adopts a product recovery strategy; (3) Model VR where both the product variety and recovery strategies are implemented. By comparing the equilibrium outcomes of these three models, we find that the manufacturer’s optimal operations strategy largely depends on the market recoverable rate, the cost spillover effect, and the manufacturer’s product variety efficiency. Through numerical examples and sensitivity analyses, we further examine the impacts of some key factors on the manufacturer’s optimal operations strategy choice. With two model extensions, we find that the manufacturer’s environmental preference and the government’s tax and subsidy policy could motivate the manufacturer to adopt Strategy R or VR instead of Strategy V.
Journal: International Journal of Production Research
Pages: 2086-2102
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1884305
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884305
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Template-Type: ReDIF-Article 1.0
Author-Name: Amirhossein Kazemisaboor
Author-X-Name-First: Amirhossein
Author-X-Name-Last: Kazemisaboor
Author-Name: Abdollah Aghaie
Author-X-Name-First: Abdollah
Author-X-Name-Last: Aghaie
Author-Name: Hamed Salmanzadeh
Author-X-Name-First: Hamed
Author-X-Name-Last: Salmanzadeh
Title: A simulation-based optimisation framework for process plan generation in reconfigurable manufacturing systems (RMSs) in an uncertain environment
Abstract: 
 Reconfigurable manufacturing system (RMS) is a manufacturing paradigm which is proven to be time and cost-effectively adaptable to a wide range of market changes due to its customisable capacity and functionality. In this paper, a two-step framework is proposed for the process plan generation in RMS. The first step, aimed at solving the multi-objective part-family Single-Unit Process Plan (SUPP) generation problem, involves a comparative approach using three metaheuristics, namely: The Non-Dominated Sorting Genetic Algorithm (NSGA-II), the Archived Multi-Objective Simulated Annealing (AMOSA) and the Multi-Objective Particle Swarm Optimisation (MOPSO) as well as a simulation-based optimisation method. The second step is designed to solve the multi-objective part-family Multi-Unit Process Plan (MUPP) generation problem with unpredictable demands in different periods using a combination of the answers of the algorithms in step 1. The number of units is also optimised using the NSGA-II. Finally, a novel heuristic algorithm named Designed Periods Algorithm (DPA) is proposed in the second step to meet the unpredictable demands in different periods. To illustrate the applicability of the framework, an example is presented, the results of which have shown the superiority of the MUPP over the SUPP in response to unpredictable demands according to the periods designed by DPA.
Journal: International Journal of Production Research
Pages: 2067-2085
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1883762
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1883762
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Template-Type: ReDIF-Article 1.0
Author-Name: Thiam-Soon Gan
Author-X-Name-First: Thiam-Soon
Author-X-Name-Last: Gan
Author-Name: Moritz Steffan
Author-X-Name-First: Moritz
Author-X-Name-Last: Steffan
Author-Name: Martin Grunow
Author-X-Name-First: Martin
Author-X-Name-Last: Grunow
Author-Name: Renzo Akkerman
Author-X-Name-First: Renzo
Author-X-Name-Last: Akkerman
Title: Concurrent design of product and supply chain architectures for modularity and flexibility: process, methods, and application
Abstract: 
 Product design and supply chain design are two key determinants of company competitiveness. However, they follow different design objectives and thus require a systematic trade-off. Although methodologies for product design and supply chain design are well established within each domain in research and industry, an integrated methodology that bridges both design domains is still lacking. Based on a recently introduced concurrent product and supply chain design process, we contribute to this underdeveloped research area with a generic approach towards exploring design tradespace. We introduce a detailed operational process for the concurrent design of product and supply chain architectures. To apply this generic process to the specific trade-off between the product-related objective of modularity and the supply-chain-related objective of sourcing flexibility, we also develop new methods for key steps of the process. We demonstrate the application of the process and the developed methods using an industrial case study of a new product (electric-vehicle battery module). The case shows that our methodology was able to structure the concurrent design process. It hereby ensured an efficient trade-off and led to high-quality designs.
Journal: International Journal of Production Research
Pages: 2292-2311
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1886370
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1886370
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Template-Type: ReDIF-Article 1.0
Author-Name: Jan Hochdörffer
Author-X-Name-First: Jan
Author-X-Name-Last: Hochdörffer
Author-Name: Felix Klenk
Author-X-Name-First: Felix
Author-X-Name-Last: Klenk
Author-Name: Thomas Fusen
Author-X-Name-First: Thomas
Author-X-Name-Last: Fusen
Author-Name: Benjamin Häfner
Author-X-Name-First: Benjamin
Author-X-Name-Last: Häfner
Author-Name: Gisela Lanza
Author-X-Name-First: Gisela
Author-X-Name-Last: Lanza
Title: Approach for integrated product variant allocation and configuration adaption of global production networks featuring post-optimality analysis
Abstract: 
 Given today’s demand shift for product variants triggered by different market segments, manufacturing companies are facing high degrees of complexity, when utilising their global production networks. To remain competitive, companies need to prepare proactively for increasing demand dynamics by using the adaptability of their production network and planning their product allocation to production network entities comprehensively. In this paper, a mixed-integer linear programme (MILP) is proposed for the integrated product variant allocation and configuration adaption of global production networks. Further improvement potential for the optimal solution is identified and evaluated by means of post-optimality analysis, i.e. an analysis of shadow prices and slack variables is conducted. This approach contributes towards decision-making in the context of strategic production network design. Its application may reduce the risk of disadvantages decisions and supports the identification of further improvement measures in complex decision-making problems while improving decision transparency. The approach is applied at a global production network for final assembly in the aeronautics industry.
Journal: International Journal of Production Research
Pages: 2168-2192
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1884765
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884765
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Template-Type: ReDIF-Article 1.0
Author-Name: Rachel Campos Sabioni
Author-X-Name-First: Rachel
Author-X-Name-Last: Campos Sabioni
Author-Name: Joanna Daaboul
Author-X-Name-First: Joanna
Author-X-Name-Last: Daaboul
Author-Name: Julien Le Duigou
Author-X-Name-First: Julien
Author-X-Name-Last: Le Duigou
Title: Concurrent optimisation of modular product and Reconfigurable Manufacturing System configuration: a customer-oriented offer for mass customisation
Abstract: 
 Reconfigurable Manufacturing Systems (RMS) emerged from companies’ needs to increase their responsiveness to an uncertain market, in which customers are increasingly demanding mass-customised products. Companies focused on mass customisation mainly use the modular product design (MPD) strategy to cost-effectively provide a large product variety. Hence, coupling the MPD with the manufacturing in RMS seems to be a good strategy to effectively provide mass-customised products with lower costs. However, few papers have concurrently optimised the modular products’ and RMS’s configurations for that end. Further, very few papers have explored the RMS’s layout configuration. In order to fill these gaps, this paper proposes a Nonlinear Integer Programming model that integrates the configuration of modular products and RMS, driven by individual customer requirements, to minimise manufacturing costs of mass-customised products. An approach combining a Modified Brute-Force Algorithm (MBFA) and a genetic algorithm (GA) is proposed and compared with a CPLEX-based approach for a small-sized problem, proving its ability to find an optimal solution in lower computation time. An illustrative example of modular smartphones confirms the MBFA-GA’s ability to solve medium/large-sized problems in a reasonable amount of time while ensuring an optimal product configuration that meets customer requirements.
Journal: International Journal of Production Research
Pages: 2275-2291
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1886369
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1886369
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Template-Type: ReDIF-Article 1.0
Author-Name: Pooya Alavian
Author-X-Name-First: Pooya
Author-X-Name-Last: Alavian
Author-Name: Yongsoon Eun
Author-X-Name-First: Yongsoon
Author-X-Name-Last: Eun
Author-Name: Kang Liu
Author-X-Name-First: Kang
Author-X-Name-Last: Liu
Author-Name: Semyon M. Meerkov
Author-X-Name-First: Semyon M.
Author-X-Name-Last: Meerkov
Author-Name: Liang Zhang
Author-X-Name-First: Liang
Author-X-Name-Last: Zhang
Title: The (αX, βX)-precise estimates of production systems performance metrics
Abstract: 
 Estimates of production systems performance metrics, such as machine efficiency, e, system throughput, TP, lead time, LT, and work-in-process, WIP, are necessary for evaluating effectiveness of potential system modifications. Calculating these estimates requires machines MTBF and MTTR, which can be obtained by measuring up- and downtime realizations on the factory floor. A question arises: What is the smallest number of measurements required to ensure the desired accuracy of the induced estimates 
 ${\hat {e}} $eˆ, (
 ${\widehat {TP}} $TPˆ), (
 ${\widehat {LT}} $LTˆ) and (
 ${\widehat {WIP}} $WIPˆ)? This paper provides an answer to this question in terms of serial lines with exponential machines. The approach is based on the theory of (
 $\alpha, \beta $α,β)-precise estimates (
 ${\widehat {MTBF}} $MTBFˆ) and (
 ${\widehat {MTTR}} $MTTRˆ), where 
 $\alpha $α represents estimate's accuracy and 
 $\beta $β its probability. Specifically, the paper calculates (
 $\alpha_X,\beta_X $αX,βX)-precise estimates of 
 $X\in\{e,TP,LT,WIP\} $X∈{e,TP,LT,WIP} induced by (
 ${\widehat {MTBF}} $MTBFˆ) and (
 ${\widehat {MTTR}} $MTTRˆ), and evaluates the smallest number of machines' up- and downtime measurements, which ensure the desired precision of 
 $\hat{X} \in \{\hat{e},\widehat{TP},\widehat{LT},\widehat{WIP}\} $Xˆ∈{eˆ,TPˆ,LTˆ,WIPˆ}. In addition, the paper develops a method for evaluating the smallest number of parts quality measurements to ensure (
 $\alpha_q,\beta_q $αq,βq)-precise estimate of machines' quality parameter q and the desired (
 $\alpha_{TP_q},\beta_{TP_q} $αTPq,βTPq)-precise estimate of good parts throughput, 
 $\widehat{TP}_q $TPˆq. The results obtained are intended for production systems managerial/engineering/research personnel as a tool for designing continuous improvement projects with analytically predicted outcomes.
Journal: International Journal of Production Research
Pages: 2230-2253
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1886367
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1886367
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Template-Type: ReDIF-Article 1.0
Author-Name: Jinsheng Gao
Author-X-Name-First: Jinsheng
Author-X-Name-Last: Gao
Author-Name: Xiaomin Zhu
Author-X-Name-First: Xiaomin
Author-X-Name-Last: Zhu
Author-Name: Kaiyuan Bai
Author-X-Name-First: Kaiyuan
Author-X-Name-Last: Bai
Author-Name: Runtong Zhang
Author-X-Name-First: Runtong
Author-X-Name-Last: Zhang
Title: New controllable processing time scheduling with subcontracting strategy for no-wait job shop problem
Abstract: 
 This paper addresses the no-wait job shop scheduling problem with due date and subcontracting cost constraints. For the no-wait job shop problem, it does not allow for waiting or interruption between any two consecutive operations of the same job. Considering the deadline and controllable processing time requirements in the real world, due date and subcontracting cost constraints are integrated into the problem as a new extension. The problem has two objectives which are associated with makespan and subcontracting cost. The extended problem focuses on a special case that some jobs cannot satisfy their deadlines no matter how they are scheduled. To satisfy the deadlines, a subcontracting strategy, i.e. buying semi-finished products for processing, is put forward. Two mathematical models are proposed. One is an integrated MILP (MILP-IS), and the other is a rolling time line MILP (MILP-RTL). According to the idea of rolling time line, an artificial bee colony algorithm based on rolling time line (RTL-ABC) is developed. Comprehensive computational analysis is carried out. For small size problems, the optimal solutions are obtained by using these two mathematical models. For large size problems, RTL-ABC is able to find good-quality solutions in a reasonable time and improves the best-found solutions.
Journal: International Journal of Production Research
Pages: 2254-2274
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1886368
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1886368
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Template-Type: ReDIF-Article 1.0
Author-Name: Jun-Ho Lee
Author-X-Name-First: Jun-Ho
Author-X-Name-Last: Lee
Author-Name: Hyun-Jung Kim
Author-X-Name-First: Hyun-Jung
Author-X-Name-Last: Kim
Title: Reinforcement learning for robotic flow shop scheduling with processing time variations
Abstract: 
 We address a robotic flow shop scheduling problem where two part types are processed on each given set of dedicated machines. A single robot moving on a fixed rail transports one part at a time, and the processing times of the parts vary on the machines within a given time interval. We use a reinforcement learning (RL) approach to obtain efficient robot task sequences to minimise makespan. We model the problem with a Petri net used for a RLenvironment and develop a lower bound for the makespan. We then define states, actions, and rewards based on the Petri net model; further, we show that the RL approach works better than the first-in-first-out (FIFO) rule and the reverse sequence (RS), which is extensively used for cyclic scheduling of a robotic flow shop; moreover, the gap between the makespan from the proposed algorithm and a lower bound is not large; finally, the makespan from the RL method is compared to an optimal solution in a relaxed problem. This research shows the applicability of RL for the scheduling of robotic flow shops and its efficiency by comparing it to FIFO, RS and a lower bound. This work can be easily extended to several other variants of robotic flow shop scheduling problems.
Journal: International Journal of Production Research
Pages: 2346-2368
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1887533
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1887533
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Template-Type: ReDIF-Article 1.0
Author-Name: Shaohui Xi
Author-X-Name-First: Shaohui
Author-X-Name-Last: Xi
Author-Name: James MacGregor Smith
Author-X-Name-First: James MacGregor
Author-X-Name-Last: Smith
Author-Name: Qingxin Chen
Author-X-Name-First: Qingxin
Author-X-Name-Last: Chen
Author-Name: Ning Mao
Author-X-Name-First: Ning
Author-X-Name-Last: Mao
Author-Name: Huiyu Zhang
Author-X-Name-First: Huiyu
Author-X-Name-Last: Zhang
Author-Name: Ailin Yu
Author-X-Name-First: Ailin
Author-X-Name-Last: Yu
Title: Simultaneous machine selection and buffer allocation in large unbalanced series-parallel production lines
Abstract: 
 Simultaneous optimisation of machines and buffers in a large series-parallel production line is an NP-hard problem. The formulated optimisation model in this study is used to minimise the total investment cost subject to the desired throughput rate and cycle time by optimising the machine types, number of parallel machines, and buffer capacities. To solve this kind of design problem, a decomposition-coordination method is proposed to efficiently and accurately generate allocation solutions for large production lines. The proposed method includes two iterative processes: the decomposition process decouples the original line into several small lines and optimises them separately, while the coordination process ensures that the optimisation problems of the decomposed lines are similar to the corresponding part of the original. The performance of this approach is demonstrated through numerical experiments by comparisons with the simulated annealing algorithm and non-dominated sorting genetic algorithm-II. Finally, the sets of numerical results and a multi-factorial experimental analysis illustrate the influences of target system parameters on the resource configurations.
Journal: International Journal of Production Research
Pages: 2103-2125
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1884306
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884306
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:7:p:2103-2125



Template-Type: ReDIF-Article 1.0
Author-Name: Jinfeng Liu
Author-X-Name-First: Jinfeng
Author-X-Name-Last: Liu
Author-Name: Peng Zhao
Author-X-Name-First: Peng
Author-X-Name-Last: Zhao
Author-Name: Xuwen Jing
Author-X-Name-First: Xuwen
Author-X-Name-Last: Jing
Author-Name: Xuwu Cao
Author-X-Name-First: Xuwu
Author-X-Name-Last: Cao
Author-Name: Sushan Sheng
Author-X-Name-First: Sushan
Author-X-Name-Last: Sheng
Author-Name: Honggen Zhou
Author-X-Name-First: Honggen
Author-X-Name-Last: Zhou
Author-Name: Xiaojun Liu
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Liu
Author-Name: Feng Feng
Author-X-Name-First: Feng
Author-X-Name-Last: Feng
Title: Dynamic design method of digital twin process model driven by knowledge-evolution machining features
Abstract: 
 Machining plan is the core of guiding manufacturing production and is regarded as one of the keys to ensure the quality of product processing. Existing process design methods are inefficient to quickly handle the machining plan changed induced by the unpredictable events in real-time production. It inevitably causes time and economic losses for the enterprise. In order to express the evolutionary characteristics of product processing, the construction method of digital twin process model (DTPM) is proposed based on the knowledge-evolution machining features. Three key technologies include correlation structure of process knowledge, expression method of the evolution geometric features and the association mechanism between two are solved. On this basis, the construction framework of DTPM is illustrated. Then, the organisation and management mechanism of multi-source heterogeneous data is discussed in detail. At last, a case study of the complex machined part is researched, the results show that the processing time reduced by about 7% and the processing stability improved by 40%. Meanwhile, the implementation scheme, application process and effect of this case are described in detail to provide reference for enterprises.
Journal: International Journal of Production Research
Pages: 2312-2330
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1887531
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1887531
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Template-Type: ReDIF-Article 1.0
Author-Name: Bei Wu
Author-X-Name-First: Bei
Author-X-Name-Last: Wu
Author-Name: Lirong Cui
Author-X-Name-First: Lirong
Author-X-Name-Last: Cui
Title: On reliability analysis of a load-sharing k-out-of-n: G system with interacting Markov subsystems
Abstract: 
 Dependency plays a key role in the design stage of multi-component manufacturing systems. To capture stochastic dependencies between subsystems, this paper considers a load-sharing 
 $k $k-out-of-
 $n $n: G system which contains non-identical multi-state subsystems. The state evolution of each subsystem follows a continuous-time homogeneous Markov chain. Most existing research on 
 $k $k-out-of-
 $n $n: G systems focuses on independent subsystems. However, a subsystem failure usually leads to a higher failure rate for each surviving subsystem within the system. This paper aims to study the interaction among subsystems and analyse the system reliability performance. The transition rate matrix for a given subsystem is assumed to depend on the total number of the remaining surviving subsystems, which can be represented as the sum of a baseline transition rate matrix and a stochastic dependency matrix. This paper proves that the transition rate matrix of the system is the generalised Kronecker sum of transition rate matrices of subsystems, and develops an explicit method to calculate the generalised Kronecker sum. The theory of aggregated stochastic processes is employed to obtain closed-form formulas for reliability indexes. A case study of multi-engine aircraft systems is provided where numerical examples are given to illustrate the developed model and obtained results.
Journal: International Journal of Production Research
Pages: 2331-2345
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1887532
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1887532
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Template-Type: ReDIF-Article 1.0
Author-Name: Sarah Vanheusden
Author-X-Name-First: Sarah
Author-X-Name-Last: Vanheusden
Author-Name: Teun van Gils
Author-X-Name-First: Teun
Author-X-Name-Last: van Gils
Author-Name: Kris Braekers
Author-X-Name-First: Kris
Author-X-Name-Last: Braekers
Author-Name: Katrien Ramaekers
Author-X-Name-First: Katrien
Author-X-Name-Last: Ramaekers
Author-Name: An Caris
Author-X-Name-First: An
Author-X-Name-Last: Caris
Title: Analysing the effectiveness of workload balancing measures in order picking operations
Abstract: 
 An intensified competition forces warehouses to handle more orders in shorter time windows. This complicates the timely retrieval of these customer orders. Planning order picking operations, thereby aiming to increase efficiency, inevitably results in balancing concerns, such as imbalances among pick areas, pickers or time periods. Reducing workload imbalances, therefore anticipating on workload peaks, results in a more stable order picking process. However, there exist several measures that can be used to evaluate and correct existing imbalances. This study contributes to academic literature by analysing, explaining and evaluating the effectiveness of various workload balancing approaches (e.g. Rawlsian's approach, range, mean-based) in order picking operations, more specifically in the context of balancing workload over time in case of restricted time windows for retrieving customer orders. Results show that the effect of warehouse layout characteristics and customer order parameters on the effectiveness of balancing measures is very limited. However, the underlying managerial reason (e.g. workforce allocation, transportation schedule or human well-being) for solving the operational workload balancing problem does significantly impact the effectiveness and choice of an appropriate balancing measure.
Journal: International Journal of Production Research
Pages: 2126-2150
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1884307
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884307
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Template-Type: ReDIF-Article 1.0
Author-Name: Kyu Tae Park
Author-X-Name-First: Kyu Tae
Author-X-Name-Last: Park
Author-Name: Seung-Woo Jeon
Author-X-Name-First: Seung-Woo
Author-X-Name-Last: Jeon
Author-Name: Sang Do Noh
Author-X-Name-First: Sang Do
Author-X-Name-Last: Noh
Title: Digital twin application with horizontal coordination for reinforcement-learning-based production control in a re-entrant job shop
Abstract: 
 In a re-entrant job shop (RJS), an entity can visit the same resource type multiple times; this is called re-entrancy, which occurs frequently in actual industries. Re-entrancy causes an NP-hard problem and is dominated by heuristics-based production control. The stochastic arrivals due to re-entrancy require the design of an appropriate dispatching rule. Reinforcement learning (RL) is an efficient technique for establishing robust dispatching rules; however, only a few cases that coordinate RL-based production control with a digital twin (DT) have been reported. This study proposes a novel production control model that applies a DT and horizontal coordination with RL-based production control. The requirements for dispatching in the RJS and coordination between RL and the DT were defined. A suitable architectural framework, service composition, and systematic logic library schema were developed to exploit the advanced characteristics of the DT and improve the existing production control methods. This study is an early case of coordinating RL and DT, and the findings revealed that RL policy networks should be imported in the creation procedures rather than being synchronised to the DT. The results should be a valuable reference for research on other types of RL-based production control with regard to horizontal coordination.
Journal: International Journal of Production Research
Pages: 2151-2167
Issue: 7
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1884309
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884309
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhaofu Hong
Author-X-Name-First: Zhaofu
Author-X-Name-Last: Hong
Author-Name: Hongyan Zhang
Author-X-Name-First: Hongyan
Author-X-Name-Last: Zhang
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Title: Towards a multi-party interaction framework: state-of-the-art review in sustainable operations management
Abstract: 
 Sustainability, which inspires the inclusive development of economy, environment and society, has received extensive attention from practical and academic communities. Existing review literature on sustainable operations management (SOM) mainly focuses on firms' sustainable operations with the impact of regulators and consumers. However, the comprehensive interactions among three agents (firms, regulators and consumers) playing increasingly important roles in sustainable development are rarely investigated in SOM. This study proposes a novel firm–regulator–consumer (FRC) interaction framework to study operations decisions and interactive cooperation considering the interactions among three agents through a comprehensive literature review on SOM. We find that conflicts may exist between profits and sustainability goals, but can be balanced by the regulators' policies and consumers' green behaviours. The framework provides support for exploring some future research opportunities. Further attention could be paid to the interactions among firms (F–F), among regulators (R–R), among consumers (C–C) and social performance improvement. In particular, innovative business models (e.g. sharing economy, social media) and new disruptive technologies (e.g. artificial intelligence, blockchain, cloud computing, big data and 5G) play vital roles in achieving sustainability.
Journal: International Journal of Production Research
Pages: 2625-2661
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1894368
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1894368
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Template-Type: ReDIF-Article 1.0
Author-Name: Yumin He
Author-X-Name-First: Yumin
Author-X-Name-Last: He
Author-Name: Kathryn E. Stecke
Author-X-Name-First: Kathryn E.
Author-X-Name-Last: Stecke
Title: Simultaneous part input sequencing and robot scheduling for mass customisation
Abstract: 
 In contemporary manufacturing environments, companies face various challenges in trying to meet customer demand in a timely manner. This paper investigates simultaneous part input sequencing and robot scheduling of flexible manufacturing systems for mass customisation. A mathematical model is formulated for this simultaneous and continuous time-based decision-making problem. A segment set-based approach is proposed to solve the problem. Numerical studies are performed by simulation and statistical analyses to evaluate the approach. The proposed approach is compared to different approaches and analysed under various conditions. Conclusions, managerial implications, and future research suggestions are provided.
Journal: International Journal of Production Research
Pages: 2481-2496
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1894369
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1894369
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Template-Type: ReDIF-Article 1.0
Author-Name: Dejan Mircetic
Author-X-Name-First: Dejan
Author-X-Name-Last: Mircetic
Author-Name: Bahman Rostami-Tabar
Author-X-Name-First: Bahman
Author-X-Name-Last: Rostami-Tabar
Author-Name: Svetlana Nikolicic
Author-X-Name-First: Svetlana
Author-X-Name-Last: Nikolicic
Author-Name: Marinko Maslaric
Author-X-Name-First: Marinko
Author-X-Name-Last: Maslaric
Title: Forecasting hierarchical time series in supply chains: an empirical investigation
Abstract: 
 Demand forecasting is a fundamental component of efficient supply chain management. An accurate demand forecast is required at several different levels of a supply chain network to support the planning and decision-making process in various departments. In this paper, we investigate the performance of bottom-up, top-down and optimal combination forecasting approaches in a supply chain. We first evaluate their forecast performance by means of a simulation study and an empirical investigation in a multi-echelon distribution network from a major European brewery company. For the latter, the grouped time series forecasting structure is designed to support managers’ decisions in manufacturing, marketing, finance and logistics. Then, we examine the forecast accuracy of combining forecasts of these approaches. Results reveal that forecast combinations produce forecasts that are more accurate and less biased than individual approaches. Moreover, we develop a model to analyse the association between time series characteristics and the effectiveness of each approach. Results provide insights into the interaction among time series characteristics and the performance of these approaches at the bottom level of the hierarchy. Valuable insights are offered to practitioners and the paper closes with final remarks and agenda for further research in this area.
Journal: International Journal of Production Research
Pages: 2514-2533
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1896817
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1896817
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Template-Type: ReDIF-Article 1.0
Author-Name: Yujie Ma
Author-X-Name-First: Yujie
Author-X-Name-Last: Ma
Author-Name: Gang Du
Author-X-Name-First: Gang
Author-X-Name-Last: Du
Author-Name: Yingying Zhang
Author-X-Name-First: Yingying
Author-X-Name-Last: Zhang
Title: Dynamic hierarchical collaborative optimisation for process planning and scheduling using crowdsourcing strategies
Abstract: 
 Platform-based crowdsourcing manufacturing has recently garnered wide attention as it is a business model that facilitates economies of scale and cost efficiency in production. The inherent coupling of process planning and production scheduling (PPPS) in a platform-based crowdsourcing manufacturing environment necessitates collaborative optimisation of PPPS decisions. Existing research that assumes PPPS decisions are integrated into one static single-level optimisation problem becomes no longer applicable with the arrival of the crowdsourcing mode. This paper presents a dynamic hierarchical collaborative optimisation (DHCO) mechanism that considers a process planning to interact with scheduling according to the optimal decision of the open manufacturing platform. A bilevel mixed 0-1 nonlinear programming model is established with the platform acting as the leader and the manufacturing enterprises serving as the follower. It is solved by a nested genetic algorithm (NGA). A case study of a part family is presented to illustrate feasibility of DHCO. Through comparative experiments, it is found that integrating crowdsourcing strategies into process planning activities is advisable for a platform to increase competitive advantages. The proposed model can manage well the conflict and collaboration between PPPS and balances the benefits of a platform with the manufacturing enterprise impacts triggered by planning activities. Abbreviations: DHCO: Dynamic Hierarchical Collaborative Optimisation; IOM: Integrated Optimisation Method; KKT: Karush-Kuhn-Tucker; MNL: Multinomial Logit; NGA: Nested Genetic Algorithm; PFI: Process Flexibility Index; PPPS: Process Planning and Production Scheduling; PSI: Process Similarity Index; TOM: Two-stage Optimisation Method.
Journal: International Journal of Production Research
Pages: 2404-2424
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1892230
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1892230
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Template-Type: ReDIF-Article 1.0
Author-Name: Lisi Liu
Author-X-Name-First: Lisi
Author-X-Name-Last: Liu
Author-Name: Yingxue Yao
Author-X-Name-First: Yingxue
Author-X-Name-Last: Yao
Author-Name: Jianguang Li
Author-X-Name-First: Jianguang
Author-X-Name-Last: Li
Title: Service-oriented invisible numerical control application: architecture, implementation, and test
Abstract: 
 CNC system has improved greatly upon machining precision and speed over the past six decades but remains vendor-proprietary and working in a stand-alone pattern. Open CNC aims to deal with the vendor-proprietary issue and numerous open CNC prototypes have been developed in the past three decades. But they are heterogeneous, low-flexible, and remain working in a stand-alone pattern. In today's Internet era, the stand-alone working pattern tends to evolve into cloud-based control pattern (cloud-CNC). On the basis of open CNC and cloud-CNC, our team proposes a novel CNC prototype called Invisible Numerical Control (INC). This paper aims to develop the INC application within the constraints of open CNC and cloud-CNC. Service-oriented paradigm is utilised to develop INC application at three levels. First, INC application is a software-as-a-service-style application. Second, CNC modules are exposed as services and CNC functionality is determined by service-oriented architecture. Third, INC application is developed using microservices architecture. Four autonomous INC microservices are defined and their mapping relationships are determined. All INC microservices are implemented as RESTful services and two complex INC microservices are implemented based on domain-driven design. A desktop client and its corresponding API gateway have been developed to test INC application.
Journal: International Journal of Production Research
Pages: 2534-2552
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1896818
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1896818
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Template-Type: ReDIF-Article 1.0
Author-Name: Caroline de Arruda Signorini
Author-X-Name-First: Caroline de Arruda
Author-X-Name-Last: Signorini
Author-Name: Silvio Alexandre de Araujo
Author-X-Name-First: Silvio Alexandre
Author-X-Name-Last: de Araujo
Author-Name: Gislaine Mara Melega
Author-X-Name-First: Gislaine Mara
Author-X-Name-Last: Melega
Title: One-dimensional multi-period cutting stock problems in the concrete industry
Abstract: 
 This research looks at the production planning of hollow-core slabs integrated to the optimisation problem of the use of moulds. Considering the production process of these structures, two mathematical models are proposed for the arising problem, which consists of a one-dimensional multi-period cutting stock problem with innovative aspects regarding the multiple manufacturing modes that can be used to produce the slabs. In addition, a theoretical analysis of the proposed models is presented. These models are solved using heuristic methods, both aiming to minimise production and inventory costs. Using data based on real information provided by a company, the computational results showed that the heuristic based on the compact model performed better than the one based on the extended model, due to some characteristics specific to the problem being studied.
Journal: International Journal of Production Research
Pages: 2386-2403
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1890261
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1890261
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrés Muñoz-Villamizar
Author-X-Name-First: Andrés
Author-X-Name-Last: Muñoz-Villamizar
Author-Name: Josué C. Velázquez-Martínez
Author-X-Name-First: Josué C.
Author-X-Name-Last: Velázquez-Martínez
Author-Name: Christopher Mejía-Argueta
Author-X-Name-First: Christopher
Author-X-Name-Last: Mejía-Argueta
Author-Name: Karla Gámez-Pérez
Author-X-Name-First: Karla
Author-X-Name-Last: Gámez-Pérez
Title: The impact of shipment consolidation strategies for green home delivery: a case study in a Mexican retail company
Abstract: 
 The growth of e-commerce has increased the number of home deliveries that need to be made in retail operations. Strategies such as reducing routing distance using optimisation models have been the most popular approaches to enhancing the efficiency of the delivery process and reducing its environmental burden. However, recently, customer purchasing behaviour has become relevant in understanding demand trends and increasing the effectiveness of the supply chain process. Customers are subject to different incentives to drive them to wait longer for their home deliveries. These incentives allow companies to pool and ship in more cost-efficient and energy-friendly alternatives. In this article, we present a methodology that uses a mixed-integer-linear programming model to evaluate the impact of extending delivery slots. We use real data from one of the largest retail companies in Mexico to analyse the impact of different time slot extensions for three different criteria: distance, transport costs and CO2 emissions. Our results show that the common approach of minimising distance is not recommended for any of the scenarios under study. On average, having up to 4 days for deliveries leads to savings of 57% in total distance, 61% in total costs and 56% in fuel consumption and/or CO2 emissions.
Journal: International Journal of Production Research
Pages: 2443-2460
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1893852
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1893852
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Template-Type: ReDIF-Article 1.0
Author-Name: Andrew Kusiak
Author-X-Name-First: Andrew
Author-X-Name-Last: Kusiak
Title: Universal manufacturing: enablers, properties, and models
Abstract: 
 Globalisation of the manufacturing and service industry has increased complexity of the flow of materials and goods, magnified dependency on the underlying network, and made the industry more vulnerable to the changing market conditions. As manufacturing and service industry undergo transformation, an opportunity to rethink the design of future enterprises has emerged. Six enablers of miniversal manufacturing are discussed: digitisation, open manufacturing, service orientation, shared manufacturing, sustainability, and resilience. These enablers will form properties of universal manufacturing, with adaptability and affinity that are emerging. A universal manufacturing enterprise will be formed based on the distributed manufacturing facilities. The emerging standards for interoperability of systems needed for universal enterprises are discussed. The data and modelling standards will enable the synthesis of digital models into universal enterprises. Though there is no global standard for the representation of digital manufacturing models in a cloud, the existing process modelling methodologies and languages may offer the solutions needed. The evolution of production systems is illustrated with three snapshots, dedicated manufacturing, distributed manufacturing, and universal manufacturing. The modelling approach followed in this paper is bottom-up rather than top-down followed in the literature on modern manufacturing.
Journal: International Journal of Production Research
Pages: 2497-2513
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1894370
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1894370
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Template-Type: ReDIF-Article 1.0
Author-Name: Tianri Wang
Author-X-Name-First: Tianri
Author-X-Name-Last: Wang
Author-Name: Pengzhi Zhang
Author-X-Name-First: Pengzhi
Author-X-Name-Last: Zhang
Author-Name: Juan Liu
Author-X-Name-First: Juan
Author-X-Name-Last: Liu
Author-Name: Liqing Gao
Author-X-Name-First: Liqing
Author-X-Name-Last: Gao
Title: Multi-user-oriented manufacturing service scheduling with an improved NSGA-II approach in the cloud manufacturing system
Abstract: 
 Manufacturing service scheduling (MSS) is an important step in managing the social resource services in the cloud manufacturing (CMfg) system. However, recent research investigates the problem almost from the task level, and little research considers the demands of multiple users in MSS problem. In this paper, the obvious characteristics of multi-user-oriented MSS are analysed by comparing with the multi-task-oriented MSS problem, and then a multi-user-oriented MSS mathematical model is built to cater to the practical demands of multiple users. In order to solve the proposed model, an improved NSGA-II (INSGA-II), integrating k-means algorithm and local search strategy, is developed to improve the quality of solutions. Six scenarios are given to verify the effectiveness of the proposed algorithm by comparing with other three algorithms from four metrics. The flexibility and universality of the proposed model is examined and the effect of user requirements on the Pareto solution is analysed. The results present the efficiency of k-means cluster and local search in the INSGA-II algorithm and provide a practical solution to select the better schedule for users.
Journal: International Journal of Production Research
Pages: 2425-2442
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1893851
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1893851
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Template-Type: ReDIF-Article 1.0
Author-Name: Pankaj Gupta
Author-X-Name-First: Pankaj
Author-X-Name-Last: Gupta
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Mukesh Kumar Mehlawat
Author-X-Name-First: Mukesh Kumar
Author-X-Name-Last: Mehlawat
Author-Name: Anisha Khaitan
Author-X-Name-First: Anisha
Author-X-Name-Last: Khaitan
Title: Multiobjective capacitated green vehicle routing problem with fuzzy time-distances and demands split into bags
Abstract: 
 Real-life challenges require proactive measures. Good transportation services and greener alternatives demand steadfast research in the area. Here, an attempt has been made to address such a problem. A particular case of VRP, with deliveries split into bags and triangular fuzzy travel times, has been modelled to minimise fuel emissions. The concepts of fuzzy rule-based implication for ranking and for comparing fuzzy numbers with numeric values, an expected value model, have been drawn upon. A discrete fuzzy-hybridised GA has been developed. Multiple experiments on data in existing works, parameter tuning, and comparative analysis have been performed, thereby corroborating the model's efficacy.
Journal: International Journal of Production Research
Pages: 2369-2385
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1888392
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1888392
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Template-Type: ReDIF-Article 1.0
Author-Name: Bilin Yu
Author-X-Name-First: Bilin
Author-X-Name-Last: Yu
Author-Name: Hu Yu
Author-X-Name-First: Hu
Author-X-Name-Last: Yu
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Title: Within-aisle or across-aisle? Optimisation and comparison of two class-based storage policies in multi-dock unit-load warehouses
Abstract: 
 As E-Commerce develop, customers' tight delivery requirements are driving warehouses to operate more efficiently. This paper studies two types of class-based storage policies for a multi-dock unit-load warehouse: the within-aisle policy and the across-aisle policy. The aim is to determine the optimal class boundary and explore the dominance situation (i.e. which policy performs better in which situation). We first develop an expected response distance model for each policy based on a general layout of multiple docks. Then, closed-form optimal first zone boundary and warehouse dimension are given for the across-aisle policy. For within-aisle policy, an efficient algorithm is developed (based on the proved unimodality property) for obtaining its optimal first zone boundary. Besides, each policy's dominance situation is analysed for two typical situations. Numerical results show that both policies can bring up to 60% performance improvement compared with the random storage policy. Impacts of docks layout and warehouse dimensions on each policy's dominance situations are illustrated. It shows that the across-aisle policy performs better in the situation where the docks' and wall's centrelines are adjacent, and in the situation where the warehouse is narrow and deep. Managerial insights on policy selection and dock layout design are presented for warehouse managers.
Journal: International Journal of Production Research
Pages: 2572-2597
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1898060
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1898060
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Template-Type: ReDIF-Article 1.0
Author-Name: Changbai Tan
Author-X-Name-First: Changbai
Author-X-Name-Last: Tan
Author-Name: Kira Barton
Author-X-Name-First: Kira
Author-X-Name-Last: Barton
Author-Name: S. Jack Hu
Author-X-Name-First: S. Jack
Author-X-Name-Last: Hu
Author-Name: Theodor Freiheit
Author-X-Name-First: Theodor
Author-X-Name-Last: Freiheit
Title: Integrating optimal process and supplier selection in personalised product architecture design
Abstract: 
 A key enabler for personalised product design is an open product architecture that allows the integration of personalised modules to create unique products. Decisions regarding product variety, module combinations, and configurations for personalised modules need to be coordinated with the decisions of manufacturing process and supplier selection when developing personalised product architectures. Conventionally, product architecture, processes, and suppliers are independently determined at different product development stages. However, this sequential design process lacks connection between product architecture, process, and supplier, and may lead to suboptimal or even infeasible design solutions with compromised performance. In this study, a concurrent optimisation approach is proposed to integrate manufacturing process and supplier selection into personalised product architecture design. A cost model is developed as a nexus of product architecture, process, and supplier. Then, a mixed-integer optimisation model is established to maximise the potential profit of a product family based on a profit formulation that incorporates customer preference, process resource, supplier, and manufacturing cost. A genetic algorithm is utilised to solve this optimisation problem. The method is demonstrated on the architecture design for a family of personalised bicycles. The result shows that concurrent optimisation can achieve design solutions with higher profitability compared to sequential design strategies.
Journal: International Journal of Production Research
Pages: 2461-2480
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1893901
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1893901
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Template-Type: ReDIF-Article 1.0
Author-Name: Yu Zhang
Author-X-Name-First: Yu
Author-X-Name-Last: Zhang
Author-Name: Zeqiang Zhang
Author-X-Name-First: Zeqiang
Author-X-Name-Last: Zhang
Author-Name: Chao Guan
Author-X-Name-First: Chao
Author-X-Name-Last: Guan
Author-Name: Peiyu Xu
Author-X-Name-First: Peiyu
Author-X-Name-Last: Xu
Title: Improved whale optimisation algorithm for two-sided disassembly line balancing problems considering part characteristic indexes
Abstract: 
 An effective method for disassembling large-sized waste products is to utilise two-sided disassembly lines. A mixed-integer programming model for two-sided disassembly lines is constructed in this study. The model considers four optimisation objectives: the number of mated-stations, idle index, demand index, and hazard index. The model redefines the hazard and demand indexes and adds new time constraints to the mated-station. In view of the complexity of the problem, a multi-objective improved whale algorithm is proposed, in which two different crossover operators are designed to simulate the predatory behaviour of whales to improve the efficiency of the solution. Then, a disturbance factor is introduced to reduce the probability of the population falling into a local optimum. The validity of the model and the effectiveness of the algorithm are verified by comparing the calculation results of the GUROBI solver with those of the proposed algorithm for two-sided disassembly line examples of different sizes. Subsequently, the algorithm is used to solve large-scale linear problems, and the results are compared with those of other algorithms to verify the superiority of the proposed algorithm. Finally, the model and algorithm are applied to a two-sided disassembly of an engine, and several optimal allocation schemes are obtained.
Journal: International Journal of Production Research
Pages: 2553-2571
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1897178
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1897178
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Template-Type: ReDIF-Article 1.0
Author-Name: Carlos Henrique dos Santos
Author-X-Name-First: Carlos Henrique
Author-X-Name-Last: dos Santos
Author-Name: José Arnaldo Barra Montevechi
Author-X-Name-First: José Arnaldo Barra
Author-X-Name-Last: Montevechi
Author-Name: José Antônio de Queiroz
Author-X-Name-First: José Antônio
Author-X-Name-Last: de Queiroz
Author-Name: Rafael de Carvalho Miranda
Author-X-Name-First: Rafael
Author-X-Name-Last: de Carvalho Miranda
Author-Name: Fabiano Leal
Author-X-Name-First: Fabiano
Author-X-Name-Last: Leal
Title: Decision support in productive processes through DES and ABS in the Digital Twin era: a systematic literature review
Abstract: 
 The use of simulation to support decision-making in productive processes (goods and services) is already an established research field. However, with the availability of solutions and technologies, simulation is no longer a tool with limited scope and analysis. In this case, the integration of simulation with physical systems is considered to allow virtual models to be sensitive to physical changes and aligned with the current state of processes, forming the so-called Digital Twin. Therefore, the main purpose of this article is to present a systematic literature review of the use of simulation as Digital Twin to support decision-making. We considered studies published in scientific journals and conference proceedings that include the use of Discrete Event Simulation (DES) and/or Agent-Based Simulation (ABS). Although the Digital Twin concept has appeared in recent years, we noted that its principle has been used for decades when it comes to decision-making through simulation. Moreover, there are still many discussions and uncertainties regarding the simulation model in this research field, such as the degree of autonomy, synchronisation, and connection. These and other key issues are discussed and some research opportunities are highlighted, such as the need for constant model validation and integration between various models.
Journal: International Journal of Production Research
Pages: 2662-2681
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1898691
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1898691
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:8:p:2662-2681



Template-Type: ReDIF-Article 1.0
Author-Name: Dian Huang
Author-X-Name-First: Dian
Author-X-Name-Last: Huang
Author-Name: Zhaofang Mao
Author-X-Name-First: Zhaofang
Author-X-Name-Last: Mao
Author-Name: Kan Fang
Author-X-Name-First: Kan
Author-X-Name-Last: Fang
Author-Name: Biao Yuan
Author-X-Name-First: Biao
Author-X-Name-Last: Yuan
Title: Combinatorial Benders decomposition for mixed-model two-sided assembly line balancing problem
Abstract: 
 In this work, we consider a mixed-model two-sided assembly line balancing problem for a given cycle time (MTALBP-I), in which the primary objective is to minimise the number of mated-stations (i.e. the length of the two-sided assembly line), while the number of stations, which describes the total number of operators, is also concerned. To solve this problem, we propose a combinatorial Benders decomposition-based exact algorithm, and develop a sequence-based enumerative search method to calculate effective combinatorial Benders cuts. To evaluate the performance of our proposed solution approach, we conduct extensive computational experiments on a set of benchmark instances, and the results demonstrate its efficiency of finding exact solutions even for large-sized instances.
Journal: International Journal of Production Research
Pages: 2598-2624
Issue: 8
Volume: 60
Year: 2022
Month: 04
X-DOI: 10.1080/00207543.2021.1901152
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1901152
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiansong Wan
Author-X-Name-First: Jiansong
Author-X-Name-Last: Wan
Author-Name: Hayong Shin
Author-X-Name-First: Hayong
Author-X-Name-Last: Shin
Title: Predictive vehicle dispatching method for overhead hoist transport systems in semiconductor fabs
Abstract: 
 We propose to use information regarding the fab's future state for Overhead Hoist Transport (OHT) dispatching, which is named as ‘predictive dispatching’ in this paper. Unlike conventional dispatching methods, two kinds of information are additionally considered in our proposed methods: the expected arrival time of jobs in the near future and the time needed for occupied vehicles to become idle. We firstly develop Basic Predictive Dispatching (BPD) under the assumption that job arrival time prediction is error-free. We demonstrate that BPD consistently surpasses conventional benchmark dispatching methods, even when job arrival time prediction contains a certain level of error. However, as the level of error increases, the performance of BPD deteriorates. To improve BPD's performance in the environment with prediction error, we take the certainty level of job arrival time prediction into consideration in our second method called Certainty Weighted Predictive Dispatching (CWPD). Both BPD and CWPD formulate the OHT dispatching problem as a linear assignment problem, but two different matching cost functions are employed separately. By conducting experiments on a sample semiconductor fab, we validate the effectiveness of our proposed approaches. The superiority of CWPD over BPD in the environment with prediction error is also verified.
Journal: International Journal of Production Research
Pages: 3063-3077
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1910870
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1910870
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Template-Type: ReDIF-Article 1.0
Author-Name: Gréanne Leeftink
Author-X-Name-First: Gréanne
Author-X-Name-Last: Leeftink
Author-Name: Gabriela Martinez
Author-X-Name-First: Gabriela
Author-X-Name-Last: Martinez
Author-Name: Erwin W. Hans
Author-X-Name-First: Erwin W.
Author-X-Name-Last: Hans
Author-Name: Mustafa Y. Sir
Author-X-Name-First: Mustafa Y.
Author-X-Name-Last: Sir
Author-Name: Kalyan S. Pasupathy
Author-X-Name-First: Kalyan S.
Author-X-Name-Last: Pasupathy
Title: Optimising the booking horizon in healthcare clinics considering no-shows and cancellations
Abstract: 
 Patient no-shows and cancellations are a significant problem to healthcare clinics, as they compromise a clinic's efficiency. Therefore, it is important to account for both no-shows and cancellations into the design of appointment systems. To provide additional empirical evidence on no-show and cancellation behaviour, we assess outpatient clinic data from two healthcare providers in the USA and EU: no-show and cancellation rates increase with the scheduling interval, which is the number of days from the appointment creation to the date the appointment is scheduled for. We show the temporal cancellation behaviour for multiple scheduling intervals is bimodally distributed. To improve the efficiency of clinics at a tactical level of control, we determine the optimal booking horizon such that the impact of no-shows and cancellations through high scheduling intervals is minimised, against a cost of rejecting patients. Where the majority of the literature only includes a fixed no-show rate, we include both a cancellation rate and a time-dependent no-show rate. We propose an analytical queuing model with balking and reneging, to determine the optimal booking horizon. Simulation experiments show that the assumptions of this model are viable. Computational results demonstrate general applicability of our model by case studies of two hospitals.
Journal: International Journal of Production Research
Pages: 3201-3218
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1913292
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1913292
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Template-Type: ReDIF-Article 1.0
Author-Name: Kaiping Luo
Author-X-Name-First: Kaiping
Author-X-Name-Last: Luo
Title: A sequence learning harmony search algorithm for the flexible process planning problem
Abstract: 
 Flexible process planning involves selecting and sequencing the requisite operations, and assigning the right machine, tool and access direction to each selected operation for minimising the production cost or the completion time. It is one of the challenging combinatorial optimisation problems due to sequencing flexibility, processing flexibility and operation flexibility. A sequence learning harmony search algorithm is accordingly proposed. Distinctively, the well-designed algorithm searches for the optimal process plan by intelligently finding the proper immediate successor for each selected operation in turn rather than resorting to the common shifting and swapping operators in sequencing. The innovative algorithm does not also require extra efforts to plot the operational precedence graph or the AND/OR-network graph. The experimental results indicate that the proposed algorithm significantly outperforms other heuristics in terms of the quality of solution found and the convergence rate of the algorithm. For the large-scale complicated instances, the proposed algorithm establishes a challenging flag.
Journal: International Journal of Production Research
Pages: 3182-3200
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1912432
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1912432
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Template-Type: ReDIF-Article 1.0
Author-Name: Eda Goksoy Kalaycilar
Author-X-Name-First: Eda
Author-X-Name-Last: Goksoy Kalaycilar
Author-Name: Sakine Batun
Author-X-Name-First: Sakine
Author-X-Name-Last: Batun
Author-Name: Meral Azizoğlu
Author-X-Name-First: Meral
Author-X-Name-Last: Azizoğlu
Title: A stochastic programming approach for the disassembly line balancing with hazardous task failures
Abstract: 
 We consider a partial disassembly line balancing problem with hazardous tasks whose successful completions are uncertain. When any hazardous task fails, it causes damages of the tasks on the workstation that it is performed on and all remaining tasks to be performed in the succeeding workstations. We attribute probabilities for the successful completion and failure of the hazardous tasks and aim to maximise the total expected net revenue. We formulate the problem as a two-stage stochastic mixed-integer programme where the assignment of the tasks to the workstations is decided in the first-stage, before the resolution of the uncertainty. We give the formulation for one, two and three hazardous tasks, and then extend to the arbitrary number of hazardous tasks. Our numerical results reveal that proposed stochastic programming models return satisfactory performance and can solve instances with up to 73 tasks very quickly. We observe that the number of tasks, number of hazardous tasks and success probabilities are the most significant parameters that affect the performance. We quantify the value of capturing uncertainty using the expected objective values attained by the solution of the stochastic model and that of the expected value model, and obtain very satisfactory results.
Journal: International Journal of Production Research
Pages: 3237-3262
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1916119
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1916119
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Template-Type: ReDIF-Article 1.0
Author-Name: Shubhendu Kumar Singh
Author-X-Name-First: Shubhendu Kumar
Author-X-Name-Last: Singh
Author-Name: Raj Pradip Khawale
Author-X-Name-First: Raj Pradip
Author-X-Name-Last: Khawale
Author-Name: Haiyong Chen
Author-X-Name-First: Haiyong
Author-X-Name-Last: Chen
Author-Name: Haolong Zhang
Author-X-Name-First: Haolong
Author-X-Name-Last: Zhang
Author-Name: Rahul Rai
Author-X-Name-First: Rahul
Author-X-Name-Last: Rai
Title: Personal protective equipments (PPEs) for COVID-19: a product lifecycle perspective
Abstract: 
 Recently, we are witnessing an emerging global public health crisis with the inception and outspread of the 2019 novel Coronavirus Disease (2019-nCoV), causing respiratory illness termed as COVID-19. The COVID-19 virus is transmitted between people when they are in close proximity to each other. Preventive and mitigation measures are critical in the fight against COVID-19 disruptions. Personal Protective Equipment, also known as PPE, is a crucial effective measure against the virus. PPEs are the dedicated equipment or clothing worn by an individual for protection against infectious diseases. However, surging demand, low product quality standards, and disruptions in the global supply chain of PPEs amid the COVID-19 pandemic are putting the lives of public and frontline healthcare workers at risk. Hence it becomes crucial to retrospect the lifecycle of PPEs. This paper attempts to present a discussion of PPEs from the product lifecycle perspective, beginning at its conception, after that traversing through various stages of design and manufacturing, and then finally ending with end-of-life issues such as disposal and recycling. Additionally, we also critically outline things that went wrong recently in PPE supply chain management and propose possible productive measures for future pandemics of this nature.
Journal: International Journal of Production Research
Pages: 3282-3303
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1915511
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1915511
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Template-Type: ReDIF-Article 1.0
Author-Name: Xingdong Zhao
Author-X-Name-First: Xingdong
Author-X-Name-Last: Zhao
Author-Name: Qianwang Deng
Author-X-Name-First: Qianwang
Author-X-Name-Last: Deng
Author-Name: Xiahui Liu
Author-X-Name-First: Xiahui
Author-X-Name-Last: Liu
Author-Name: Like Zhang
Author-X-Name-First: Like
Author-X-Name-Last: Zhang
Author-Name: Shengcong Wu
Author-X-Name-First: Shengcong
Author-X-Name-Last: Wu
Author-Name: Chao Jiang
Author-X-Name-First: Chao
Author-X-Name-Last: Jiang
Title: Integrated scheduling of distributed service resources for complex equipment considering multiple on-site MRO tasks
Abstract: 
 The previous studies on service resource scheduling for maintenance, repair and operation (MRO) ignore the diverse service processes from different complex equipment and the coordination of task scheduling and resource allocation, which is less realistic when multiple tasks exist. In this work, we propose an integrated scheduling model of distributed service resources for on-site MRO, which simultaneously considers different service processes, service teams and material resources. The MRO service process is decomposed into multiple subtasks with hierarchical relationships (dependency and independency). Within the duration of the subtask, all multi-skill technicians in service team stay together and material resources are delivered from service providers. Resource allocation and task scheduling are integrated to minimise the makespan, the excessive human resources and the cost performance index of material resources. Further, we introduce six classic multi-objective evolutionary algorithms (MOEAs) to solve the scheduling problem, in which a novel and practical encoding method mixed with integers and decimals is developed. The design-of-experiment (DOE) method is used to determine the optimal combination of crucial parameters. Finally, 20 benchmark instances of multiple MRO tasks are tested. Experiment results show MOEA/D-DU could obtain higher quality scheduling solutions with relatively low computational costs in the integrated scheduling model.
Journal: International Journal of Production Research
Pages: 3219-3236
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1916117
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1916117
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Template-Type: ReDIF-Article 1.0
Author-Name: Wenhui Yang
Author-X-Name-First: Wenhui
Author-X-Name-Last: Yang
Author-Name: Lu Chen
Author-X-Name-First: Lu
Author-X-Name-Last: Chen
Author-Name: Stèphane Dauzère-Pèrés
Author-X-Name-First: Stèphane
Author-X-Name-Last: Dauzère-Pèrés
Title: A dynamic optimisation approach for a single machine scheduling problem with machine conditions and maintenance decisions
Abstract: 
 In modern production systems, considering machine conditions is becoming essential to achieving an overall optimisation of the production schedule. This paper studies a single machine scheduling problem, where the actual processing times of jobs depend on their position in the production sequence and maintenance is considered. Moreover, the machine is subject to an uncertain condition variation. There is a trade-off between rejecting a maintenance action, resulting in longer processing times, and accepting a maintenance action, leading to higher processing efficiency for future jobs. The problem is formulated as a finite-horizon Markov Decision Process. The objective is to minimise the makespan. Optimality properties are analysed, based on which a dynamic optimisation approach is developed. Computational experiments demonstrate the effectiveness of the proposed approach.
Journal: International Journal of Production Research
Pages: 3047-3062
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1910746
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1910746
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Template-Type: ReDIF-Article 1.0
Author-Name: Daniel Y. Mo
Author-X-Name-First: Daniel Y.
Author-X-Name-Last: Mo
Author-Name: Yue Wang
Author-X-Name-First: Yue
Author-X-Name-Last: Wang
Author-Name: Danny C. K. Ho
Author-X-Name-First: Danny C. K.
Author-X-Name-Last: Ho
Author-Name: K. H. Leung
Author-X-Name-First: K. H.
Author-X-Name-Last: Leung
Title: Redeploying excess inventories with lateral and reverse transshipments
Abstract: 
 Service parts management has the potential to generate high profits for companies that deliver superior service parts services in the after-sale market. However, a big challenge in managing service parts operations is to meet the high expectations of service levels and to reduce excess inventories caused by fluctuating demand and a complex service parts logistics network structure. By expanding the conventional inventory management that passively focuses on the forward and lateral flows of service parts deployment, we propose a crucial but overlooked practice of inventory redeployment as an integral part of the operations that allow the proactive management of lateral and reverse flows of service parts. We formulate the service parts inventory problem with the application of an excess inventory redeployment strategy in a multi-echelon service network as a multi-period integer programming model. This optimisation model is evaluated using a case study of an international company’s service parts operations and demonstrates a higher cost-saving potential. Our novel, integrated approach confers the advantage of redeploying excess inventories in a closed-loop service parts logistics network with a higher cost-saving potential that could not have been achieved in a conventional approach.
Journal: International Journal of Production Research
Pages: 3031-3046
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1910360
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1910360
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Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Namakshenas
Author-X-Name-First: Mohammad
Author-X-Name-Last: Namakshenas
Author-Name: Aleida Braaksma
Author-X-Name-First: Aleida
Author-X-Name-Last: Braaksma
Author-Name: Mohammad Mahdavi Mazdeh
Author-X-Name-First: Mohammad
Author-X-Name-Last: Mahdavi Mazdeh
Title: Minimising total earliness and tardiness with periodically supplied non-renewable resource profiles
Abstract: 
 We consider a special class of resource-constrained single machine scheduling problems. In the classical scheduling context, resource types are classified into renewable and non-renewable; however, a large variety of real-world problems may not fit into one of these classes, e.g. labour regulations in project scheduling, budget allocation to different phases of a construction project, and dose management in a medical imaging centre. In this study, we address a class of non-renewable resources supplied, not necessarily immediately, in different periods of the planning horizon. The objective is to assign the jobs to the supply periods and schedule them such that the sum of total tardiness and total earliness is minimised. Several properties and complexity results of the optimal schedules are discussed, then they are used to develop a tractable algorithm. First, we decompose the problem into several single supply problems and then decide the optimal schedule through a polynomial-time optimal algorithm for each single supply problem. The scalability tests indicate the promising performance guarantee of the algorithm compared to provably optimal schedules in the integrated framework.
Journal: International Journal of Production Research
Pages: 3170-3181
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1912430
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1912430
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Template-Type: ReDIF-Article 1.0
Author-Name: Massimo Bertolini
Author-X-Name-First: Massimo
Author-X-Name-Last: Bertolini
Author-Name: Marcello Braglia
Author-X-Name-First: Marcello
Author-X-Name-Last: Braglia
Author-Name: Leonardo Marrazzini
Author-X-Name-First: Leonardo
Author-X-Name-Last: Marrazzini
Author-Name: Mattia Neroni
Author-X-Name-First: Mattia
Author-X-Name-Last: Neroni
Title: Project Time Deployment: a new lean tool for losses analysis in Engineer-to-Order production environments
Abstract: 
 This paper presents a novel lean tool called Project Time Deployment (PTD) whose objectives are to classify, analyse, and eliminate losses in order to reduce production lead time in Engineer-to-Order (ETO) environments. By combining two already known approaches, i.e. the Manufacturing Critical-path Time and the Manufacturing Cost Deployment, PTD identifies the critical losses affecting the project, focusing on the business processes where causal losses occur, and providing opportunities for greater efficiency and effectiveness by reducing or even eliminating them.In ETO projects, the lead time and respecting deadlines are of paramount importance and they are often threatened by several different losses that are difficult to compare. Companies thus need a tool to identify the losses and the tasks where they occur, quantifying them in terms of a single dimension: the time.PTD was designed using a methodology based on four steps: analysis of current solutions, concept design and prototype, proof of concept and validation, and definition of future researches. It was also validated in an industrial implementation concerning an Engineering, Procurement & Construction company operating in the steel industry, and led to an approximate 24% reduction in lead time.
Journal: International Journal of Production Research
Pages: 3129-3146
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1912428
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1912428
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Template-Type: ReDIF-Article 1.0
Author-Name: Fernando Tubilla
Author-X-Name-First: Fernando
Author-X-Name-Last: Tubilla
Author-Name: Stanley B. Gershwin
Author-X-Name-First: Stanley B.
Author-X-Name-Last: Gershwin
Title: Dynamic scheduling in make-to-stock production systems with setup times and random breakdowns: performance analysis and improved policies
Abstract: 
 We study the scheduling of production in a multi-item, failure-prone machine with setup times, with the objective of minimising long-run average inventory and backlog costs. We make two contributions to this problem, which has received significantly less attention compared to the standard stochastic economic lot scheduling problem (with random demand and production times). First, we adapt and implement a variety of existing scheduling policies and compare their performance through a set of numerical experiments spanning a wide range of operating conditions. This analysis allows us to identify important shortcomings of the policies, including their poor performance when items have widely different priorities (as dictated by the product of their cost and production rate parameters). Second, we leverage these insights to develop and analyse a new, easy-to-implement policy. This policy tightly controls the surplus of the highest-priority items using fixed base-stock levels and, for all other items, it determines their run lengths dynamically in such a way that long production runs become decreasingly likely with decreasing item priority. Our experiments show that our new policy greatly outperforms the benchmarking policies over a large and important set of operating regimes, comprising high-utilisation systems where the machine cycles through all items at a frequency comparable to or greater than the frequency of failure events.
Journal: International Journal of Production Research
Pages: 3263-3281
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1917013
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1917013
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:10:p:3263-3281



Template-Type: ReDIF-Article 1.0
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Author-Name: Amy H. I. Lee
Author-X-Name-First: Amy H. I.
Author-X-Name-Last: Lee
Author-Name: Yi-San Huang
Author-X-Name-First: Yi-San
Author-X-Name-Last: Huang
Title: Developing a skip-lot sampling scheme by variables inspection using repetitive sampling as a reference plan
Abstract: 
 In today’s manufacturing environment, the rate of defective products has been continuously decreasing; thus, variables sampling plans with process capability indices (PCIs) have been recommended to gather more information about a manufacturing process and reduce required sample sizes for inspection. In particular, skip-lot sampling plan (SkSP) is suitable for a series of lots having stable and excellent product quality. Moreover, the concept of repetitive group sampling (RGS), which can allow the use of less samples to maintain desired protection to producers and consumers, is especially appropriate where inspection or testing is costly or destructive. This study, by incorporating the advantages of PCIs, SkSP, and RGS, constructs a variables SkSP with RGS as the reference plan (called SkSP-RGS) based on one-sided PCIs for products with a unilateral specification limit. The proposed plan reduces the sample size while achieving a similar discriminatory power, compared with a conventional variables single sampling plan (SSP), a RGS plan (RGSP), and a SkSP of type 2 (SkSP-2). Tables of plan parameters are provided for frequently applied quality and risk requirements so that practitioners can easily apply the proposed plan.
Journal: International Journal of Production Research
Pages: 3018-3030
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1909768
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1909768
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:10:p:3018-3030



Template-Type: ReDIF-Article 1.0
Author-Name: Siamak Khayyati
Author-X-Name-First: Siamak
Author-X-Name-Last: Khayyati
Author-Name: Barış Tan
Author-X-Name-First: Barış
Author-X-Name-Last: Tan
Title: A machine learning approach for implementing data-driven production control policies
Abstract: 
 Given the extensive data being collected in manufacturing systems, there is a need for developing a systematic method to implement data-driven production control policies. For an effective implementation, first, the relevant information sources must be selected. Then, a control policy that uses the real-time signals collected from these sources must be implemented. We analyse the production control policy implementation problem in three levels: choosing the information sources, forming clusters of information signals to be used by the policy and determining the optimal policy parameters. Due to the search-space size, a machine-learning-based framework is proposed. Using machine learning speeds up optimisation and allows utilising the collected data with simulation. Through two experiments, we show the effectiveness of this approach. In the first experiment, the problem of selecting the right machines and buffers for controlling the release of materials in a production/inventory system is considered. In the second experiment, the best dispatching policy based on the selected information sources is identified. We show that selecting the right information sources and controlling a production system based on the real-time signals from the selected sources with the right policy improve the system performance significantly. Furthermore, the proposed machine learning framework facilitates this task effectively.
Journal: International Journal of Production Research
Pages: 3107-3128
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1910872
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1910872
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:10:p:3107-3128



Template-Type: ReDIF-Article 1.0
Author-Name: Khelil Kassoul
Author-X-Name-First: Khelil
Author-X-Name-Last: Kassoul
Author-Name: Naoufel Cheikhrouhou
Author-X-Name-First: Naoufel
Author-X-Name-Last: Cheikhrouhou
Author-Name: Nicolas Zufferey
Author-X-Name-First: Nicolas
Author-X-Name-Last: Zufferey
Title: Buffer allocation design for unreliable production lines using genetic algorithm and finite perturbation analysis
Abstract: 
 The buffer allocation problem in production lines is an NP-hard combinatorial optimisation problem. This paper proposes a new hybrid optimisation approach (using simulation) relying on genetic algorithm (GA) and finite perturbation analysis (FPA). Unlike the infinitesimal perturbation analysis, which deals with small (infinitesimal variation) perturbations for estimating gradients of the performance measure, FPA deals with larger (finite) or more lasting perturbations. It is an extension specifically dedicated to discrete decision variables and applicable to most discrete-event dynamic systems. The proposed method allows a global search using GA, with refinement in specific solution-space regions using FPA. The main objective is to maximise the average production rate of a production line with unreliable machines, by allocating the total buffer capacity in locations between machines. Extensive numerical experiments show that: (1) the proposed hybrid GA-FPA method clearly outperforms the state-of-the-art methods from the literature; (2) combining FPA and GA is beneficial when compared to employing GA or FPA independently.
Journal: International Journal of Production Research
Pages: 3001-3017
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1909169
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1909169
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:10:p:3001-3017



Template-Type: ReDIF-Article 1.0
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme Luz
Author-X-Name-Last: Tortorella
Author-Name: Flavio Sanson Fogliatto
Author-X-Name-First: Flavio Sanson
Author-X-Name-Last: Fogliatto
Author-Name: Vijaya Sunder M
Author-X-Name-First: Vijaya
Author-X-Name-Last: Sunder M
Author-Name: Alejandro Mac Cawley Vergara
Author-X-Name-First: Alejandro Mac
Author-X-Name-Last: Cawley Vergara
Author-Name: Roberto Vassolo
Author-X-Name-First: Roberto
Author-X-Name-Last: Vassolo
Title: Assessment and prioritisation of Healthcare 4.0 implementation in hospitals using Quality Function Deployment
Abstract: 
 This study proposes a problem-oriented methodology, using the algebraic operations proposed in the Quality Function Deployment's house-of-quality, to prioritise the integration of Industry 4.0 (I4.0) technologies in hospitals, allowing us to account for both the importance of healthcare value chain problems and the current level of adoption of I4.0 technologies. The proposed method combines different techniques that aimed at assessing the maturity of organisations regarding specific issues and indicating improvement opportunities. Our propositions are illustrated through two case studies carried out in a large Brazilian public hospital and in a private hospital in India, allowing a comparative analysis in which we identify similarities and divergences in improvement priorities in each institution. Findings indicate that the proposed method supports the systemic integration of I4.0 technologies into healthcare organisations regardless hospital ownership, as digital applications are ranked according to their potential to solve the problems prioritised by managers from both case studies. Digital integration in healthcare organisations has been restricted to specific sectors, departments, treatment or processes. Due to high complexity of hospitals, most of these initiatives have fallen short on results, frustrating managers’ efforts. Thus, our method provides hospitals’ managers, authorities, and governments guidelines to prioritise the digitisation of healthcare organisations.
Journal: International Journal of Production Research
Pages: 3147-3169
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1912429
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1912429
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Template-Type: ReDIF-Article 1.0
Author-Name: Hamed Jalali
Author-X-Name-First: Hamed
Author-X-Name-Last: Jalali
Author-Name: Amir Ansaripoor
Author-X-Name-First: Amir
Author-X-Name-Last: Ansaripoor
Author-Name: Vinay Ramani
Author-X-Name-First: Vinay
Author-X-Name-Last: Ramani
Author-Name: Pietro De Giovanni
Author-X-Name-First: Pietro
Author-X-Name-Last: De Giovanni
Title: Closed-loop supply chain models with coopetition options
Abstract: 
 This paper proposes a Closed-loop Supply Chain game-theoretic model that mimics the DellReconnect Supply Chain. Within this framework, we characterise a game between an Original Equipment Manufacturer (OEM) and a social collector, who work together to recover electronics. The market comprises three segments: consumers purchasing only new goods, consumers purchasing only used goods, and indifferent consumers. The social collector decides whether the returns will be used to serve the used-market segment or the indifferent market segment first, thereby establishing the market structure and deciding whether to opt for competition or coopetition. We find that, whereas the social collector is indifferent when it comes to a choice between coopetition and competition, the OEM strictly prefers coopetition.
Journal: International Journal of Production Research
Pages: 3078-3106
Issue: 10
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1910871
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1910871
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:10:p:3078-3106

Template-Type: ReDIF-Article 1.0
Author-Name: Pedro Piñeyro
Author-X-Name-First: Pedro
Author-X-Name-Last: Piñeyro
Author-Name: Omar Viera
Author-X-Name-First: Omar
Author-X-Name-Last: Viera
Title: The economic lot-sizing problem with remanufacturing and heterogeneous returns: formulations, analysis and algorithms
Abstract: 
 We address an extension of the economic lot-sizing problem with remanufacturing, in which the returns are assumed of heterogeneous quality. Costs for remanufacturing and holding inventory depend on the quality of the returns. For the problem with general cost functions, we provide a network flows formulation and a dynamic programming algorithm of pseudopolynomial time. Then, we consider the problem under stationary costs and different set-up schemes for manufacturing and remanufacturing. For the case of a joint set-up scheme, we derive certain properties related to the form of the optimal solutions. Based on these theoretical results, a polynomial-time algorithm is presented for the particular case of a large quantity of low-cost returns. For the case of separate set-up scheme, we show that the problem is NP-hard and present several lot-sizing rules specially designed for the problem. An extensive numerical experimentation was conducted to evaluate the suggested rules under different combinations of inventory and set-up costs. From the results obtained, we can extract several managerial insights, such as in general it is profitable to remanufacture all the available returns of the same quality in certain periods, but not necessarily those of the highest quality.
Journal: International Journal of Production Research
Pages: 3521-3533
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1925771
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1925771
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Template-Type: ReDIF-Article 1.0
Author-Name: Mingzhu Yu
Author-X-Name-First: Mingzhu
Author-X-Name-Last: Yu
Author-Name: Yan Chen
Author-X-Name-First: Yan
Author-X-Name-Last: Chen
Author-Name: Zelong Yi
Author-X-Name-First: Zelong
Author-X-Name-Last: Yi
Author-Name: Qi Wang
Author-X-Name-First: Qi
Author-X-Name-Last: Wang
Author-Name: Zizhen Zhang
Author-X-Name-First: Zizhen
Author-X-Name-Last: Zhang
Title: Benefits of market information and professional advice in a vertical agricultural supply chain: the role of government provision
Abstract: 
 We study a vertical agricultural supply chain with a farmer cooperative who decides his agricultural product selling price and a social enterprise who makes her order quantity decision and resells products to the end market. The effect of market information and agricultural advice provided by the government on the system's outcomes is investigated. A two-stage game model is proposed to characterise this vertical relationship. The equilibrium decisions of the two players under different government supporting cases are derived. We contrast the system outcomes under different cases and conduct comparative analysis. It is found that (1) the farmer cooperative's profit increases if the government provides market information to him and the social enterprise at the same time; (2) the agricultural advice provided by the government can increase the benefits to each participant in the supply chain; (3) to maximise the total supply chain profit as well as its sustainability, the government may choose to provide market information to the social enterprise only; (4) when the wholesale price is intervened by the government or exogenously provided, the social enterprise's social responsibility concern can increase both the farmer cooperative's profit and the social enterprise's social payoff.
Journal: International Journal of Production Research
Pages: 3461-3475
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1924409
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1924409
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Template-Type: ReDIF-Article 1.0
Author-Name: T. D. Hedberg
Author-X-Name-First: T. D.
Author-X-Name-Last: Hedberg
Author-Name: M. E. Sharp
Author-X-Name-First: M. E.
Author-X-Name-Last: Sharp
Author-Name: T. M. M. Maw
Author-X-Name-First: T. M. M.
Author-X-Name-Last: Maw
Author-Name: M. M. Helu
Author-X-Name-First: M. M.
Author-X-Name-Last: Helu
Author-Name: M. M. Rahman
Author-X-Name-First: M. M.
Author-X-Name-Last: Rahman
Author-Name: S. Jadhav
Author-X-Name-First: S.
Author-X-Name-Last: Jadhav
Author-Name: J. J. Whicker
Author-X-Name-First: J. J.
Author-X-Name-Last: Whicker
Author-Name: A. Barnard Feeney
Author-X-Name-First: A.
Author-X-Name-Last: Barnard Feeney
Title: Defining requirements for integrating information between design, manufacturing, and inspection
Abstract: 
 Industry desires a digital thread of information that aligns as-designed, as-planned, as-executed, and as-inspected viewpoints. An experiment was conducted to test selected open data standards' ability to integrate the lifecycle stages of engineering design, manufacturing, and quality assurance through a thorough implementation of a small-scale model-based enterprise. The research team set out to answer: from design, through production, and final inspections, what are the hurdles that a manufacturer would face during the development of a fully linked and integrated information chain? The research team was not able to fully link all the required information, but value for the industry was still identified. This paper presents the results of the experiment, provides guidance on how to overcome or mitigate identified challenges, and discusses the benefits or incentives to be gained from tracing or linking information through multiple stages a product lifecycle.
Journal: International Journal of Production Research
Pages: 3339-3359
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1920057
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1920057
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Template-Type: ReDIF-Article 1.0
Author-Name: Mengyu He
Author-X-Name-First: Mengyu
Author-X-Name-Last: He
Author-Name: Kai Kang
Author-X-Name-First: Kai
Author-X-Name-Last: Kang
Author-Name: Xiuqing Mu
Author-X-Name-First: Xiuqing
Author-X-Name-Last: Mu
Title: Impact of tax difference and asset structure on a capital-constrained vertical equity holding transnational supply chain
Abstract: 
 Capital and taxes play vital roles in transnational supply chain financing and operations. We use the Stackelberg game method to explore the financing strategy selection and contract clauses setting for a capital-constrained transnational supply chain with vertical equity holding. The results prove that asset structure, tax difference, and shareholding ratio are essential in selecting the financing strategy and additional clause. First, a higher supplier's asset structure can increase the profits of supply chain members. Second, a threshold for contract choice connected to tax difference is discovered. Early payment with a discount clause is optimal when tax difference is significant. When the tax difference is slight, buyer financing without additional clauses is optimal. Further, there exists an optimal shareholding ratio related to tax, which can avoid double marginalisation under buyer financing and reduce supply chain losses under bank financing. Tax subsidies due to deficit make supply chain performance outstrip centralised decision-making when the shareholding ratio is more excellent than a threshold. Last, the choice of strategy under buyer financing is related to the ex-ante or ex-post signing of the purchase contract and the limited deduction of interest payment within the tax law. Our findings guide transnational supply chain financing and operations.
Journal: International Journal of Production Research
Pages: 3606-3629
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1926571
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1926571
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Template-Type: ReDIF-Article 1.0
Author-Name: Haijuan Cui
Author-X-Name-First: Haijuan
Author-X-Name-Last: Cui
Author-Name: Xiaochuan Luo
Author-X-Name-First: Xiaochuan
Author-X-Name-Last: Luo
Author-Name: Yuan Wang
Author-X-Name-First: Yuan
Author-X-Name-Last: Wang
Title: Scheduling of steelmaking-continuous casting process with different processing routes using effective surrogate Lagrangian relaxation approach and improved concave–convex procedure
Abstract: 
 This paper studies a steelmaking-continuous casting scheduling problem with different processing routes. We model this problem as a mixed-integer nonlinear programming problem. Next, Lagrangian relaxation approach is introduced to solve this problem by relaxing the coupling constraints. Due to the nonseparability in Lagrangian functions, we design an improved concave–convex procedure to decompose the Lagrangian relaxation problem into three tractable subproblems and analyse the convergence of the improved concave–convex procedure under some assumptions. Furthermore, we present an effective surrogate subgradient algorithm with global convergence to solve the Lagrangian dual problem. Lastly, computational experiments on the practical production data show the effectiveness of the proposed surrogate subgradient method for solving this steelmaking-continuous casting scheduling problem.
Journal: International Journal of Production Research
Pages: 3435-3460
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1924408
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1924408
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Template-Type: ReDIF-Article 1.0
Author-Name: Albert Corominas
Author-X-Name-First: Albert
Author-X-Name-Last: Corominas
Title: A model for designing a procurement-inventory system as a defence against a recurring epidemic
Abstract: 
 The COVID-19 pandemic has caused a general shortage of personal protection products and therapeutic devices, which has highlighted the need for each country to have its own production resources and not depend solely on imports. Given the time that elapses between the onset of an epidemic and its detection, as well as the time required to activate production and the lead time of purchasing operations, it is necessary to have a permanent reserve, which we call shield stock, in order to immediately meet the demand for equipment at the beginning and throughout the course of the epidemic. This situation is analysed in order to identify the most relevant decisions in the scenario described, formulate a cost optimisation model and develop procedures to find the most economical combination of shield stock, domestic production capacity and imports to guarantee the immediate satisfaction of demand and the restoration of the shield stock after the epidemic, as a preventative measure. The procedure is illustrated with a specific pattern of the spread of the epidemic and some numerical examples.
Journal: International Journal of Production Research
Pages: 3305-3318
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1919779
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1919779
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Template-Type: ReDIF-Article 1.0
Author-Name: Tom Servranckx
Author-X-Name-First: Tom
Author-X-Name-Last: Servranckx
Author-Name: José Coelho
Author-X-Name-First: José
Author-X-Name-Last: Coelho
Author-Name: Mario Vanhoucke
Author-X-Name-First: Mario
Author-X-Name-Last: Vanhoucke
Title: Various extensions in resource-constrained project scheduling with alternative subgraphs
Abstract: 
 In this research, we present several extensions for the resource-constrained project scheduling problem with alternative subgraphs (RCPSP-AS). First of all, we investigate more complex variants of the alternative project structure. More precisely, we consider nested alterative subgraphs, linked alternative branches, multiple selection, caused and closed choices, and split choices. Secondly, we introduce non-renewable resources in the RCPSP-AS in order to implicitly avoid certain combinations of alternatives given a limited availability of this resource over the complete project horizon. We formulate both the basic RCPSP-AS and its extensions as an ILP model and solve it using Gurobi. The computational experiments are conducted on a large set of artificial project instances as well as three case studies. The results show the impact of the different extensions on the project makespan and the computational complexity. We observe that combinations of the proposed extensions might imply complex alternative project structures, resulting in an increasing computational complexity or even infeasible solutions. The analysis of the three case studies shows that it is hard to find feasible solutions with a small time limit or optimal solutions with a larger time limit for projects with a realistic size in terms of the number of activities or alternatives.
Journal: International Journal of Production Research
Pages: 3501-3520
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1924411
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1924411
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Template-Type: ReDIF-Article 1.0
Author-Name: Danial Khorasanian
Author-X-Name-First: Danial
Author-X-Name-Last: Khorasanian
Author-Name: Franklin Dexter
Author-X-Name-First: Franklin
Author-X-Name-Last: Dexter
Author-Name: Erik Demeulemeester
Author-X-Name-First: Erik
Author-X-Name-Last: Demeulemeester
Author-Name: Ghasem Moslehi
Author-X-Name-First: Ghasem
Author-X-Name-Last: Moslehi
Title: Minimising the number of cancellations at the time of a severe lack of postanesthesia care unit beds or nurses
Abstract: 
 A deficiency of the postanesthesia care unit (PACU) beds or nurses may cause delays in the operating rooms (ORs) and increase the number of cancellations. Some disruptions like the COVID-19 pandemic may cause this deficiency. This paper investigates two integrated OR and PACU scheduling problems; one with few PACU beds, and the other with few PACU nurses. For each problem, a mathematical model and a matheuristic are proposed for minimising the number of cancellations. To the best of our knowledge, it is the first study that investigates the implications of a severe lack of the PACU beds or nurses on the number of cancellations. The matheuristics hybridise the decomposition of each instance into some small-sized sub-instances with a variable neighbourhood search algorithm. The main advantages of these methods are their flexibility to incorporate many problem details (such as a step-wise demand for the PACU nurses) and to solve any large-scale problem. Numerical results for a data set with 22 ORs show that with an increasingly severe lack of PACU capacity there is progressively greater benefit of the matheuristics than their initial solutions. Moreover, these results show the influence of the overtime and the recovery in ORs on improving the situation.
Journal: International Journal of Production Research
Pages: 3383-3396
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1921874
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1921874
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Template-Type: ReDIF-Article 1.0
Author-Name: Adrien Rimélé
Author-X-Name-First: Adrien
Author-X-Name-Last: Rimélé
Author-Name: Michel Gamache
Author-X-Name-First: Michel
Author-X-Name-Last: Gamache
Author-Name: Michel Gendreau
Author-X-Name-First: Michel
Author-X-Name-Last: Gendreau
Author-Name: Philippe Grangier
Author-X-Name-First: Philippe
Author-X-Name-Last: Grangier
Author-Name: Louis-Martin Rousseau
Author-X-Name-First: Louis-Martin
Author-X-Name-Last: Rousseau
Title: Robotic mobile fulfillment systems: a mathematical modelling framework for e-commerce applications
Abstract: 
 Robotic Mobile Fulfillment Systems (RMFSs) are a recent type of automated warehouse deployed in e-commerce. In this parts-to-picker system, a fleet of small robots is tasked with retrieving and storing shelves of items in the warehouse. Due to the nature of the e-commerce market, and the high flexibility of RMFSs, there are many opportunities to improve the productivity of the warehouse by optimising operational decisions. Online retailers promise extremely fast deliveries, which requires that new orders be included in the set of requests to fulfil as soon as they are revealed. For this reason, and because of the very dynamic nature of the robots' cycles, decision-making needs to be done in real time, in an uncertain environment. Because such a problem often lacks a formal description, we propose a mathematical framework that models the operational decisions taking place in an RMFS as a stochastic dynamic program. Our objective is to formalise optimisation opportunities, to allow researchers to develop more advanced methods in a well-defined environment. Embedded in a discrete event simulator, this model is illustrated by simulations to compare against standard storage decision rules.
Journal: International Journal of Production Research
Pages: 3589-3605
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1926570
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1926570
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Template-Type: ReDIF-Article 1.0
Author-Name: Jacques Carlier
Author-X-Name-First: Jacques
Author-X-Name-Last: Carlier
Author-Name: Abderrahim Sahli
Author-X-Name-First: Abderrahim
Author-X-Name-Last: Sahli
Author-Name: Antoine Jouglet
Author-X-Name-First: Antoine
Author-X-Name-Last: Jouglet
Author-Name: Eric Pinson
Author-X-Name-First: Eric
Author-X-Name-Last: Pinson
Title: A faster checker of the energetic reasoning for the cumulative scheduling problem
Abstract: 
 This paper constitutes a step forward in resource-constrained scheduling theory. We introduce an 
 $O(n \times \alpha (n) \times \log n) $O(n×α(n)×log⁡n) checker for energetic reasoning (ER), where 
 $\alpha (n) $α(n) is Ackermann's inverse function. Until now, after more than 20 years of research, the best technique, recently obtained by Ouellet and Quimper, was in 
 $O(n\log ^2 n) $O(nlog2⁡n). We identify mathematical properties that allow the number of useful intervals to be reduced. We also discuss the interest of integrating this checker into industrial solvers developed for addressing optimisation problems.
Journal: International Journal of Production Research
Pages: 3419-3434
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1923853
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1923853
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Template-Type: ReDIF-Article 1.0
Author-Name: Chao Li
Author-X-Name-First: Chao
Author-X-Name-Last: Li
Author-Name: Fajun Yang
Author-X-Name-First: Fajun
Author-X-Name-Last: Yang
Author-Name: Lu Zhen
Author-X-Name-First: Lu
Author-X-Name-Last: Zhen
Title: Efficient scheduling approaches to time-constrained single-armed cluster tools with condition-based chamber cleaning operations
Abstract: 
 In semiconductor manufacturing, an extremely stringent quality control is enforced for wafer fabrication processes. Consequently, cleaning operations that clear residual chemical gases and heat in the chambers are frequently performed. As one kind of cleaning operations, a purge operation which executes a cleaning operation each time a wafer is removed from a chamber is widely adopted in leading semiconductor fabrication plants. Such an operation can definitely improve the quality of wafer. However, it results in lower productivity. To make a tradeoff between quality and productivity, a condition-based chamber cleaning operation that performs a cleaning operation with the consideration of the actual state of a chamber is introduced in practice. Aiming to address the scheduling problem of time-constrained single-armed cluster tools with condition-based chamber cleaning operations, efficient scheduling approaches are proposed in this work for the first time and, algorithms for searching for a feasible schedule are also derived. Two illustrative examples are given to show the power of the approach.
Journal: International Journal of Production Research
Pages: 3555-3568
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1926568
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1926568
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Template-Type: ReDIF-Article 1.0
Author-Name: Ke Yan
Author-X-Name-First: Ke
Author-X-Name-Last: Yan
Author-Name: Guowei Hua
Author-X-Name-First: Guowei
Author-X-Name-Last: Hua
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Author-Name: Shouyang Wang
Author-X-Name-First: Shouyang
Author-X-Name-Last: Wang
Author-Name: Jing-Xin Dong
Author-X-Name-First: Jing-Xin
Author-X-Name-Last: Dong
Title: Joint promotion of cross-market retailers: models and analysis
Abstract: 
 To seek more business opportunities, cross-market retailers pursue horizontal joint promotion (HJP) to promote their products together. It is important to determine the factors that make cross-market retailers pursue HJP and how HJP affects the retailers' optimal decisions. We address such issues in the context of a shopping mall in which two cross-market retailers pursue HJP with the possible involvement of the shopping mall. We develop game-theoretic models to study whether the shopping mall should provide consumers with coupons that they can obtain from the retailer in the source market and consume at the retailer in the target market. We find that when coupons are offered to consumers, the retailer in the source market has a higher price and will pay more for HJP, but has a smaller demand and a lower profit than the retailer in the target market. Furthermore, when the effect of the coupon is relatively large, both retailers prefer the coupon as they can have higher prices, demands, and profits, and their promotional strategies change with the denomination and effect of the coupon. Conversely, both retailers would reduce investments in HJP because the coupon may bring them lower profits.
Journal: International Journal of Production Research
Pages: 3397-3418
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1922946
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1922946
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Template-Type: ReDIF-Article 1.0
Author-Name: Zengqiang Jiang
Author-X-Name-First: Zengqiang
Author-X-Name-Last: Jiang
Author-Name: Shuai Yuan
Author-X-Name-First: Shuai
Author-X-Name-Last: Yuan
Author-Name: Jing Ma
Author-X-Name-First: Jing
Author-X-Name-Last: Ma
Author-Name: Qiang Wang
Author-X-Name-First: Qiang
Author-X-Name-Last: Wang
Title: The evolution of production scheduling from Industry 3.0 through Industry 4.0
Abstract: 
 Since the Third Industrial Revolution, technology and the global economy have developed rapidly. Driven by market demand and the development of science and technology, the organisational model of the production system has evolved, which has in turn caused changes in the methods of production scheduling. In the context of the newest industrial revolution (Industry 4.0), this review aims to examine the evolution of production scheduling in terms of economics and technology. First, literature on production scheduling is summarised and analysed from the perspectives of centralised/decentralised scheduling, distributed scheduling, and cloud manufacturing scheduling. Second, future challenges and trends in the development of production scheduling are discussed in view of the globalisation of manufacturing and changes in production modes enabled by new technologies. Finally, based on the findings of this review, we make a prediction for the future expansions of the customer-centric value chain as well as changes in product design and production methods brought by product personalisation.
Journal: International Journal of Production Research
Pages: 3534-3554
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1925772
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1925772
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Template-Type: ReDIF-Article 1.0
Author-Name: Apostolos P. Elekidis
Author-X-Name-First: Apostolos P.
Author-X-Name-Last: Elekidis
Author-Name: Michael C. Georgiadis
Author-X-Name-First: Michael C.
Author-X-Name-Last: Georgiadis
Title: Production scheduling of flexible continuous make-and-pack processes with byproducts recycling
Abstract: 
 This work considers the scheduling problem of continuous make-and-pack industries, including flexible intermediate storage vessels, aiming to provide better synchronisation of the production stages. A novel continuous-time, precedence-based, MILP model is developed for the problem under consideration. Mass balance constraints are cleverly satisfied using a continuous-time representation. Extending previously proposed precedence-based frameworks, flexible vessels are used for storing multiple intermediates of the same recipe. Furthermore, new efficient resource-constraints, related to generation and recycling of byproduct waste are introduced to consider additional benefits by their utilisation in the plant. A two-stage MILP-based solution strategy is proposed for the solution of real-life, large-scale industrial problem instances. Several case studies, inspired by consumer goods industries, are used to illustrate the applicability of the proposed framework. Results illustrate that the utilisation of intermediate buffers leads to a better synchronisation of the production stages and increased productivity, as unnecessary idle times, total waste and total plant costs are reduced.
Journal: International Journal of Production Research
Pages: 3360-3382
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1920058
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1920058
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Template-Type: ReDIF-Article 1.0
Author-Name: Liangqing Zhang
Author-X-Name-First: Liangqing
Author-X-Name-Last: Zhang
Author-Name: Hefu Liu
Author-X-Name-First: Hefu
Author-X-Name-Last: Liu
Author-Name: Zhao Cai
Author-X-Name-First: Zhao
Author-X-Name-Last: Cai
Title: Addressing the consensus on information sharing in CPFR information systems: Insights from manufacturer – retailer dyads
Abstract: 
 This study investigated the mechanism of improving consensus between one dominant manufacturer and retailers in evaluating retailers’ information sharing in a Collaborative Planning, Forecasting, and Replenishment (CPFR) system. IT capability, goodwill trust, and competence trust were proposed as antecedents of this consensus based on organizational information processing theory (OIPT). A matched questionnaire survey was conducted, generating 253 manufacturer-retailer dyads for analysis. Consensus on information sharing was operationalized by the degree-symmetric model (DSM). The empirical results showed that retailers’ IT capability, goodwill trust, and competence trust in the dominant manufacturer were positively related to the consensus on information sharing. Furthermore, the interaction between retailers’ IT capability and goodwill trust was negatively related to this consensus, whereas the interaction effect of retailers’ IT capability and competence trust was positive.
Journal: International Journal of Production Research
Pages: 3569-3588
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1926569
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1926569
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianyu Long
Author-X-Name-First: Jianyu
Author-X-Name-Last: Long
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Author-Name: Chuan Li
Author-X-Name-First: Chuan
Author-X-Name-Last: Li
Title: Level-based multi-objective particle swarm optimizer for integrated production scheduling and vehicle routing decision with inventory holding, delivery, and tardiness costs
Abstract: 
 Integrated optimisation of production scheduling and distribution decision is necessary for reducing the whole cost of the supply chain in the make-to-order business environment. This paper studies a new integrated production scheduling and vehicle routing problem (IPSVRP) with inventory holding, delivery, and tardiness costs. The considered IPSVRP is modelled as a triple-objective optimisation problem, where the first objective aims to obtain the minimal total holding cost in the inventory, the second one attempts to achieve the minimal total travelling cost, and the third one tries to acquire the minimal total tardiness cost. To obtain a set of diverse non-dominated solutions in the Pareto-optimal front of the problem, we first derive several key structural properties used to provide necessary conditions for any solution to be Pareto-optimal through theoretical investigation. Based on the derived structural properties, a level-based multi-objective particle swarm optimizer (LMPSO) is subsequently designed. The performance of LMPSO is analysed by conducting a set of experiments, and its superiority is verified through comparing with other optimisation algorithms. Moreover, the convergence behaviour of LMPSO is also investigated, and the experimental results prove that it has the ability to achieve a set of non-dominated solutions proximity to the true Pareto front.
Journal: International Journal of Production Research
Pages: 3319-3338
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1919780
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1919780
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Template-Type: ReDIF-Article 1.0
Author-Name: Amina Chelly
Author-X-Name-First: Amina
Author-X-Name-Last: Chelly
Author-Name: Imen Nouira
Author-X-Name-First: Imen
Author-X-Name-Last: Nouira
Author-Name: Atidel B. Hadj-Alouane
Author-X-Name-First: Atidel B.
Author-X-Name-Last: Hadj-Alouane
Author-Name: Yannick Frein
Author-X-Name-First: Yannick
Author-X-Name-Last: Frein
Title: A comparative study of progressive carbon taxation strategies: impact on firms’ economic and environmental performances
Abstract: 
 Governments all over the world adopted different forms of progressive carbon taxation strategies (for example concave, convex and linear for respectively Swedish, French, and Canadian government). These progressive strategies provide companies with different degrees of flexibility to adapt their decisions to the new environmental regulations and reduce their carbon emissions without compromising their profit. However, no existing work has compared the impact of each progressive legislation on the optimal decisions of the supply chain, its profit, and its environmental performances. In this paper, we contribute to the literature by developing four multi-period technology selection models under different forms of progressive carbon taxes. We analytically determine the optimal strategic investment timing decision under each taxation strategy. We then develop a carbon tax assessment method using multi-criteria analysis techniques to compare the efficiency of each carbon taxation form in reducing carbon emission and maximising the Supply Chain (SC) profit. We prove that the earliest green investment decision and the decision of not investing in green depend on the target carbon tax rather than the taxation form. We show that government decision about the suitable taxation form should be based on the performance of the available green technologies.
Journal: International Journal of Production Research
Pages: 3476-3500
Issue: 11
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1924410
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1924410
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Template-Type: ReDIF-Article 1.0
Author-Name: Min Ji
Author-X-Name-First: Min
Author-X-Name-Last: Ji
Author-Name: Shengkai Hu
Author-X-Name-First: Shengkai
Author-X-Name-Last: Hu
Author-Name: Yuan Zhang
Author-X-Name-First: Yuan
Author-X-Name-Last: Zhang
Author-Name: T. C. E. Cheng
Author-X-Name-First: T. C. E.
Author-X-Name-Last: Cheng
Author-Name: Yiwei Jiang
Author-X-Name-First: Yiwei
Author-X-Name-Last: Jiang
Title: Parallel-machine scheduling with identical machine resource capacity limits and DeJong’s learning effect
Abstract: 
 We consider parallel-machine scheduling with identical machine resource capacity limits and DeJong’s learning effect. Each job has a resource consumption requirement and a normal processing time. The actual processing time of a job is a function of its normal processing time, subject to DeJong’s learning effect, while the resource consumption of a job is a function of its actual processing time. Each machine has the same resource capacity limit. The objective is to maximise the minimum machine load. Considering three resource consumption functions, namely, linear, concave, and convex, we show that all three scheduling models are NP-hard and propose two approximation algorithms for the models and analyse their worst-case ratios.
Journal: International Journal of Production Research
Pages: 2753-2765
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1902011
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1902011
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhaohui Geng
Author-X-Name-First: Zhaohui
Author-X-Name-Last: Geng
Author-Name: Bopaya Bidanda
Author-X-Name-First: Bopaya
Author-X-Name-Last: Bidanda
Title: Tolerance estimation and metrology for reverse engineering based remanufacturing systems
Abstract: 
 Tolerances are critical to the product’s design, manufacturing, and quality. However, tolerances are often overlooked in a reverse engineering (RE) process for industrial applications, especially in legacy parts or spare parts remanufacturing. Ignoring tolerances could either unnecessarily call for high precision remanufacturing processes or make the reproduced parts unqualified. Additive manufacturing (AM) techniques are used in remanufacturing applications because of their ability to manufacturing intricated parts. Due to its layer-by-layer fabrication nature, the metrology for AM-created parts is drastically different when compared to traditional feature-generation processes. In this study, we first propose a novel way to classify manufacturing processes based on whether they directly identify or generate features, which could profoundly affect their metrology tools. Next, a systematic geometric inspection and tolerance estimation methodology for the RE system is proposed. A set of tools is developed to extract various geometric dimensional values from the point clouds based on their tolerancing types. Moreover, based on the domain knowledge in production process design and planning, methods are developed to estimate empirical tolerances from a small batch of legacy parts. Comparisons of empirical tolerances of real machined parts to their designed tolerances are presented to evaluate the performance of the proposed framework.
Journal: International Journal of Production Research
Pages: 2802-2815
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1904158
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1904158
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Template-Type: ReDIF-Article 1.0
Author-Name: Shan Lu
Author-X-Name-First: Shan
Author-X-Name-Last: Lu
Author-Name: Weifeng Hou
Author-X-Name-First: Weifeng
Author-X-Name-Last: Hou
Author-Name: Zhe Li
Author-X-Name-First: Zhe
Author-X-Name-Last: Li
Author-Name: Junying Xia
Author-X-Name-First: Junying
Author-X-Name-Last: Xia
Author-Name: Lei Xie
Author-X-Name-First: Lei
Author-X-Name-Last: Xie
Author-Name: Hongye Su
Author-X-Name-First: Hongye
Author-X-Name-Last: Su
Title: Design and optimisation of a green manufacturing-recycling network considering heavy metal pollutants – an electronic assembly case
Abstract: 
 This paper presents a green manufacturing-recycling network design approach for multi-echelon electronic assembly process under a complex product mix scenario which incorporates trade-off between economic cost and heavy metal pollutants. The approach is developed by formulating the green manufacturing-recycling network into a closed-loop logistics bi-objective optimisation model, in order to alleviate negative environmental influence by applying proper cleaner production technologies. The environmental influence is quantified by pollution equivalent numbers which are integrated in the model. Moreover, the volume of the heavy metal pollutants is optimised by selecting the cleaner production level and thus is jointly coordinated with the operation cost. To solve the bi-objective optimisation model, an enhanced global criterion approach is presented to improve the effectiveness on dealing with non-convexity of the Pareto-optimal frontier with computational efficient solutions. The proposed model is implemented on a case study to verify its flexibility to handle the closed-loop manufacturing-recycling network design of different sizes, as well as to obtain trade-off between operation cost and environmental influence by the heavy metal pollutants under various scenarios.
Journal: International Journal of Production Research
Pages: 2830-2849
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1904160
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1904160
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Template-Type: ReDIF-Article 1.0
Author-Name: Juan David Cortes
Author-X-Name-First: Juan David
Author-X-Name-Last: Cortes
Author-Name: Yoshinori Suzuki
Author-X-Name-First: Yoshinori
Author-X-Name-Last: Suzuki
Title: Last-mile delivery efficiency: en route transloading in the parcel delivery industry
Abstract: 
 In the last few years, many consumers have shifted their shopping locations from traditional brick-and-mortar stores to online shopping sites to take advantage of larger product selections and convenient delivery services. This has forced parcel delivery service providers, such as UPS and FedEx, to handle large amounts of shipments with complex delivery needs in a time-efficient manner. Given this challenge, parcel delivery companies are looking for faster, more cost-efficient ways to distribute parcels. Based on expert opinions, obtained through a series of interviews with practitioners, this study presents a decision tool to improve the operational efficiency of last-mile delivery for parcel delivery companies. This decision tool extends previous works on Vehicle Routing Problem with Split Deliveries by allowing shipment transloading to take place between vehicles at select points (other than the depot) in the logistics network, within pre-specified time windows.
Journal: International Journal of Production Research
Pages: 2983-3000
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1907628
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1907628
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Template-Type: ReDIF-Article 1.0
Author-Name: Jianxin Chen
Author-X-Name-First: Jianxin
Author-X-Name-Last: Chen
Author-Name: Tonghua Zhang
Author-X-Name-First: Tonghua
Author-X-Name-Last: Zhang
Author-Name: Yong-wu Zhou
Author-X-Name-First: Yong-wu
Author-X-Name-Last: Zhou
Author-Name: Rui Hou
Author-X-Name-First: Rui
Author-X-Name-Last: Hou
Title: Complex dynamic analysis of risk-averse newsvendor models with buyback guarantee financing
Abstract: 
 In the framework of the newsvendor model, both single- and multi-period models are proposed to investigate the ordering strategy of a risk-averse retailer under buyback guarantee financing (BGF) and stochastic demand. In the single-period model, the classical newsvendor is extended by introducing risk aversion and capital constraints simultaneously. It is found that the optimal ordering quantity is a monotonic function in some parameters, such as increasing in the retailer's risk aversion and salvage value, while decreasing in the initial capital and wholesale price. The multi-period model is a dynamical model described by the bounded rationality decision adjustment rules. We then investigate the complex dynamics they admit, such as period-doubling bifurcation and chaotic phenomena, and have found that the dynamical models experience more complex behaviour than their static counterpart. Furthermore, in the dynamical case, we could see periodic, bifurcating or chaotic changes in ordering quantity. We also investigate the influence of BGF on ordering quantity, which may lead to a risk-averse retailer to order aggressively. Finally, some numerical simulations are given to illustrate the theoretical results and some suggestions are also provided.
Journal: International Journal of Production Research
Pages: 2865-2883
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1905901
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1905901
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Template-Type: ReDIF-Article 1.0
Author-Name: Miguel Vieira
Author-X-Name-First: Miguel
Author-X-Name-Last: Vieira
Author-Name: Samuel Moniz
Author-X-Name-First: Samuel
Author-X-Name-Last: Moniz
Author-Name: Bruno S. Gonçalves
Author-X-Name-First: Bruno S.
Author-X-Name-Last: Gonçalves
Author-Name: Tânia Pinto-Varela
Author-X-Name-First: Tânia
Author-X-Name-Last: Pinto-Varela
Author-Name: Ana Paula Barbosa-Póvoa
Author-X-Name-First: Ana Paula
Author-X-Name-Last: Barbosa-Póvoa
Author-Name: Pedro Neto
Author-X-Name-First: Pedro
Author-X-Name-Last: Neto
Title: A two-level optimisation-simulation method for production planning and scheduling: the industrial case of a human–robot collaborative assembly line
Abstract: 
 In this work, a novel optimisation-simulation based on the Recursive Optimisation-Simulation Approach (ROSA) methodology is developed to provide effective decision-support for integrated production planning and scheduling. The proposed iterative approach optimises production plans while satisfying complex scheduling constraints, such as robots' allocation in collaborative tasks. The plans are determined through a two-level MILP model and are iteratively evaluated by a detailed discrete-event simulation model to guarantee capacity-feasible solutions at the scheduling level. Through an industrial case study of a multistage assembly line design collaboratively operated by humans and mobile shared robots, near-optimal solutions comprise lot-sizing decisions, the release schedule of production orders, the allocation of tasks to humans or robots, and the number of robots per period. Moreover, by addressing a set of propositions to assess the methodology, the results highlight the advantages of the hybrid approach to converge into optimised operational decisions and analyse the process dynamics.
Journal: International Journal of Production Research
Pages: 2942-2962
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1906461
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1906461
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Template-Type: ReDIF-Article 1.0
Author-Name: Ruimeng Li
Author-X-Name-First: Ruimeng
Author-X-Name-Last: Li
Author-Name: Hao Yi
Author-X-Name-First: Hao
Author-X-Name-Last: Yi
Author-Name: Huajun Cao
Author-X-Name-First: Huajun
Author-X-Name-Last: Cao
Title: Towards understanding dynamic design change propagation in complex product development via complex network approach
Abstract: 
 Design change propagation is a primary source of risk and innovation in complex product (CP) development. Soundly predicting and managing the design change propagation have become critical issues. Dynamicity is the non-negligible nature of design change propagation. However, existing specific case studies and static predicting methods are inadequate to analyze the dynamicity quantitatively. Here, a general model based on complex network is developed to depict the dynamic design change propagation. Numerical simulations are conducted to explore the general law of the propagation and investigate the influences of design change tolerance capacity distribution (
 $\alpha ,\beta $α,β), attack strategies, and recovery capacity (
 $\gamma $γ). The results show that the model can well portray the real design change propagations. The dynamic design change propagation can be controlled by adjusting the parameter 
 $\alpha $α, 
 $\beta $β, and 
 $\gamma $γ. A new indicator 
 ${\alpha ^\ast } $α∗ is proposed to represent the robustness of the CP network, which is negatively related to β and positively related to γ. The influences of attack strategies and recovery capacity decrease with the increase of β. The cost-effective trade-off criteria to conclude the design change propagation within limited time are provided. This paper provides a basic framework to understand the dynamic design change propagation in CP development.
Journal: International Journal of Production Research
Pages: 2733-2752
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1901155
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1901155
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Template-Type: ReDIF-Article 1.0
Author-Name: Ahmad Ghasemkhani
Author-X-Name-First: Ahmad
Author-X-Name-Last: Ghasemkhani
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Author-Name: Yaser Rahimi
Author-X-Name-First: Yaser
Author-X-Name-Last: Rahimi
Author-Name: Sina Shahnejat-Bushehri
Author-X-Name-First: Sina
Author-X-Name-Last: Shahnejat-Bushehri
Author-Name: Haed Tavakkoli-Moghaddam
Author-X-Name-First: Haed
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: Integrated production-inventory-routing problem for multi-perishable products under uncertainty by meta-heuristic algorithms
Abstract: 
 The present study aims to introduce an integrated production-inventory-routing problem (PIRP) with a mixed-integer linear programming model, remarking a multi-perishable product, multi-period, and heterogeneous fleets with time windows in a distribution network. The objective of the proposed model is to maximise the total profit, which equals the selling revenue subtract the aggregation of the holding, production, transportation, and utility preference costs. At the production level, a multi-period production system with production capacity constraints is considered, in which the inventory at each stage of production is intended to compute the related holding costs and schedule more appropriate planning. The vehicle routing problem is tackled at the distribution level regarding vehicles with various capacities in a multi-period condition. Consequently, a fuzzy chance-constrained programming model is used to deal with fuzzy parameters. Furthermore, two evolutionary algorithms, namely a hybrid imperialist competitive algorithm (HICA) and self-adaptive differential evolution (SADE), are proposed to solve the given problem. Subsequently, several numerical examples with managerial insights are solved to evaluate the performances of the proposed algorithms and show their effectiveness and efficiency. Computational results demonstrate the superiority of the proposed algorithms for this problem. Finally, the applicability of the proposed algorithms is investigated by a real-case study.
Journal: International Journal of Production Research
Pages: 2766-2786
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1902013
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1902013
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Template-Type: ReDIF-Article 1.0
Author-Name: Yi Zhang
Author-X-Name-First: Yi
Author-X-Name-Last: Zhang
Author-Name: Xiang Li
Author-X-Name-First: Xiang
Author-X-Name-Last: Li
Author-Name: Liang Wang
Author-X-Name-First: Liang
Author-X-Name-Last: Wang
Author-Name: Xiande Zhao
Author-X-Name-First: Xiande
Author-X-Name-Last: Zhao
Author-Name: Jinwu Gao
Author-X-Name-First: Jinwu
Author-X-Name-Last: Gao
Title: Financing capital-constrained third party logistic firms: fourth party logistic driven financing mode vs. private lending driven financing mode
Abstract: 
 The accounts payable payment period for transportation costs is usually less than the accounts receivable cycle for transportation fees for a third-party logistic (3PL) firm in China; hence, a capital-constrained 3PL firm has a strong demand to seek credit loans from some competitive lenders (e.g., fourth-party logistic [4PL] firm or private lending [PL] organization). To investigate the attractiveness and effectiveness of different financing modes, two practical financing modes (4PL-driven and PL-driven) and an improved 4PL-driven financing mode are formulated in this work. We present a game-theoretical approach to investigate the equilibria based on the profile functions among 4PL firm (or PL), 3PL firm, supplier and retailer under different financing modes. We find that (1) the practical 4PL-driven financing mode will be the Pareto-dominant financing mode for 3PL firms, suppliers and retailers when the initial budget of the 3PL firm falls below a certain level. (2) The 4PL firm's profit is always higher when using the improved 4PL-driven financing mode. (3) The 4PL firm should use the practical 4PL-driven financing mode for start-up 3PL firms to support their growth; but when they grow to a certain scale, the 4PL firm should use the improved 4PL-driven financing mode to enhance its profit.
Journal: International Journal of Production Research
Pages: 2963-2982
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1907472
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1907472
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiuxian Wang
Author-X-Name-First: Xiuxian
Author-X-Name-Last: Wang
Author-Name: Na Geng
Author-X-Name-First: Na
Author-X-Name-Last: Geng
Author-Name: Shan Jiang
Author-X-Name-First: Shan
Author-X-Name-Last: Jiang
Author-Name: Liping Zhou
Author-X-Name-First: Liping
Author-X-Name-Last: Zhou
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Optimal design of healthcare services after the separation of prescribing and dispensing
Abstract: 
 Healthcare services are customer-intensive services and usually accompanied by other treatment-related consumptions, e.g. medications. Traditionally in China, prescribing and dispensing are both made by hospitals, which causes high drug expenses. To solve this problem, the Chinese government has begun exploring the separation of prescribing and dispensing. Against this background, this paper analyses the optimal designs for healthcare services considering separated medications. We consider a service system with one monopolistic healthcare service provider, which could be a revenue-maximiser or social-welfare maximiser, and assume patients are bounded-rational with demands affected by price and quality of both service and medications. We analyse the optimal service price and service rate for cases involving either single or multiple medications. Revenue-maximiser usually prefers cost-effective medications, and when its service quality is low, more irrational patients are preferred. Its revenue increases with the number of medication types. For the social-welfare-maximiser, as the number of medication types or improved quality of certain medications does not ensure greater social welfare, its benefits depend on the prices and quality of the entire medications. For a social planner, it is effective to institute price caps to achieve socially optimal results. This paper lays theoretical foundations for price regulations of public healthcare systems.
Journal: International Journal of Production Research
Pages: 2918-2941
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1906459
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1906459
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Template-Type: ReDIF-Article 1.0
Author-Name: Fusheng Liang
Author-X-Name-First: Fusheng
Author-X-Name-Last: Liang
Author-Name: Chengwei Kang
Author-X-Name-First: Chengwei
Author-X-Name-Last: Kang
Author-Name: Fengzhou Fang
Author-X-Name-First: Fengzhou
Author-X-Name-Last: Fang
Title: Tool path planning on triangular mesh surfaces based on the shortest boundary path graph
Abstract: 
 In this paper, a new method is developed for tool path planning on triangular mesh surfaces with consideration of the scallop height restriction and the path smoothness. This method first maps the triangular mesh surface into a unit disk region by using a harmonic map algorithm, and then the shortest boundary path graph (SBPG) is constructed on the unit disk region to describe the shortest geodesic distance from each mesh vertex to the surface boundary. The tool path is then obtained by inversely mapping the contours of SBPG from the harmonic mapped region to the physical space of mesh surface. During this process, a subdivision method is used to boost the computing efficiency and a smoothing treatment is conducted on the SBPG to improve the path smoothness. The tool path planning is performed starting from the surface boundary in an iteration process. Taking the level difference of SBPG contours as the initial path interval and being supplemented by a correction process, the maximal step distance between any two paths, which meets the requirement of scallop height restriction, can be determined efficiently. Typical simulation cases and experiments are carried out to illustrate the effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 2683-2702
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1887535
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1887535
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Template-Type: ReDIF-Article 1.0
Author-Name: Tulika Chakraborty
Author-X-Name-First: Tulika
Author-X-Name-Last: Chakraborty
Author-Name: Satyaveer S. Chauhan
Author-X-Name-First: Satyaveer S.
Author-X-Name-Last: Chauhan
Author-Name: Xiao Huang
Author-X-Name-First: Xiao
Author-X-Name-Last: Huang
Title: Quality competition between national and store brands
Abstract: 
 The private label literature assumes that store brands (SBs) are of lower quality than competing national brands (NBs). To contest this notion, this paper examines the quality competition between a NB manufacturer and a SB retailer. The NB manufacturer sells its products through the retailer, and hence the manufacturer and the retailer are in competition. Once both parties decide the right quality level of their respective products, the retailer decides the retail prices for both brands. Using a general quality-dependent cost structure, we explicitly characterise both the price- and quality-level equilibriums under various channel power structures. We find that the SB might have a higher quality level than the NB even with no cost disparity, but will have a lower retail price than the NB, whether its quality is superior or not. Further, price and quality competitions have opposite implications for equilibrium solutions as well as profitability levels. Interestingly, the manufacturer may benefit from a more costly production or quality investment scenario, although both the retailer and the supply chain may suffer from it. The paper highlights the importance of accountability for quality decisions in the study of private label products.
Journal: International Journal of Production Research
Pages: 2703-2732
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1901154
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1901154
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Template-Type: ReDIF-Article 1.0
Author-Name: Yong Jin Suh
Author-X-Name-First: Yong Jin
Author-X-Name-Last: Suh
Author-Name: Jin Young Choi
Author-X-Name-First: Jin Young
Author-X-Name-Last: Choi
Title: Efficient Fab facility layout with spine structure using genetic algorithm under various material-handling considerations
Abstract: 
 The Fabrication (Fab) layout design is a strategic issue and has a significant impact on the operational efficiency of semiconductor manufacturing. This research work was motivated by the actual problem to analyse and disperse the congested material flows of central corridor caused by an automated material-handling system (AMHS) in the spine-structure Fab of S Electronics in Korea, which is currently in mass production. In this paper, we suggest an efficient Fab facility layout determination method using genetic algorithm, while considering the interrelationship between manufacturing processors and AMHS. Specifically, we devise a special fitness function employing traffic congestion penalty for reverse and cross-material flows in addition to the usual material-handling distance. By using numerical experiments, we show the superiority of the suggested approach for reducing the overall distance of congested material handling by decreasing the reverse and cross-flows, which cause traffic congestions in the central corridor and entire Fab as well. We expect that this method is expected to be helpful in solving the Fab process layout problems at the Fab planning stage in the actual industrial field.
Journal: International Journal of Production Research
Pages: 2816-2829
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1904159
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1904159
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Template-Type: ReDIF-Article 1.0
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme
Author-X-Name-Last: Luz Tortorella
Author-Name: Paulo A. Cauchick-Miguel
Author-X-Name-First: Paulo A.
Author-X-Name-Last: Cauchick-Miguel
Author-Name: Wen Li
Author-X-Name-First: Wen
Author-X-Name-Last: Li
Author-Name: Jo Staines
Author-X-Name-First: Jo
Author-X-Name-Last: Staines
Author-Name: Duncan McFarlane
Author-X-Name-First: Duncan
Author-X-Name-Last: McFarlane
Title: What does operational excellence mean in the Fourth Industrial Revolution era?
Abstract: 
 Although the term Operational Excellence (OE) has been widely applied over the past few decades, its meaning is still ill-defined. This issue may be especially aggravated after the advent of the Industry 4.0 (I4.0), which introduces disruptive digital technologies that may help to overcome traditional barriers in operations management. This paper examines the concept of OE in the Fourth Industrial Revolution. For that, we conducted semi-structured interviews with experts from both academia and manufacturing companies, focusing on the shifts in OE's concepts implied by the I4.0 with regards to four key aspects (people, partnerships, processes, and products and services). Experts’ responses had their content analysed through the lens of General Systems Theory, which allowed the formulation of propositions towards the conceptualization of OE in the digital transformation era. Our findings indicated that, although some attributes may remain the same, the emphasis of OE in the Fourth Industrial Revolution is likely to change. The extensive integration of digital technologies into manufacturing companies tends to entail different expectations in terms of excellence in people, partnerships, processes, and products and services. As interconnectivity and cyber-physical systems gain prominence, a more integrative and systemic perspective of OE is facilitated, expanding its meaning and understanding.
Journal: International Journal of Production Research
Pages: 2901-2917
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1905903
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1905903
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:9:p:2901-2917



Template-Type: ReDIF-Article 1.0
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Zhaojie Wang
Author-X-Name-First: Zhaojie
Author-X-Name-Last: Wang
Author-Name: E. Zhang
Author-X-Name-First: E.
Author-X-Name-Last: Zhang
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Title: K-adaptability in robust container vessel sequencing problem with week-dependent demands of a service route
Abstract: 
 This work investigates a robust container vessel sequencing (RCVS) problem in a service route. As weekly demands vary dramatically and cannot be forecasted accurately, shipping companies need to develop a robust sequence of vessels with different capacities to maximally meet demands. As export heavily depends on economy, demands may share the same pattern in adjacent years, which motivates us to study the problem in a cyclic fashion. To refine the literature, we adopt a robust optimisation model to minimise the worst-case total cost, including container tardy and outsourcing cost, due to reliability guarantee. To accommodate human decision-making, we focus on an associated K-adaptability problem, which pre-selects a number of candidate vessel sequences and implements the best one when the uncertain demands have been observed. A branch-and-bound solution approach is explored. Numerical experiments demonstrate the performance of our approach.
Journal: International Journal of Production Research
Pages: 2787-2801
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1902014
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1902014
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:9:p:2787-2801



Template-Type: ReDIF-Article 1.0
Author-Name: Jun Guo
Author-X-Name-First: Jun
Author-X-Name-Last: Guo
Author-Name: Zhipeng Pu
Author-X-Name-First: Zhipeng
Author-X-Name-Last: Pu
Author-Name: Baigang Du
Author-X-Name-First: Baigang
Author-X-Name-Last: Du
Author-Name: Yibing Li
Author-X-Name-First: Yibing
Author-X-Name-Last: Li
Title: Multi-objective optimisation of stochastic hybrid production line balancing including assembly and disassembly tasks
Abstract: 
 Assembly and disassembly are important activities in the manufacturing/remanufacturing process. Although the line balancing problems of them have been extensively discussed in the existing literature, they are rarely integrated into one system. In this paper, a hybrid production line balancing problem is adopted while considering the similarity between the assembly and disassembly tasks. First, to better reflect the uncertainty existing in the actual production environment, a mathematical model of the multi-objective stochastic hybrid production line balancing problem is presented, in which task disassembly times are assumed to be random variables with known normal probability distributions. Then, a hybrid VNS-NSGA II algorithm combining variable neighbourhood search (VNS) and non-dominated sorting genetic algorithm II (NSGA II) is proposed to solve the problem. VNS is embedded into NSGA II as a local search to improve the quality of the solutions found by the NSGA II at each generation. Finally, the effectiveness of the proposed method is verified by a case study, and the superiority of hybrid production line is reflected by comparing the solutions of the independent production line with the hybrid production line. Computational comparisons demonstrate the potential benefits of the hybrid production line and the proposed method.
Journal: International Journal of Production Research
Pages: 2884-2900
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1905902
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1905902
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:9:p:2884-2900



Template-Type: ReDIF-Article 1.0
Author-Name: I. Majdouline
Author-X-Name-First: I.
Author-X-Name-Last: Majdouline
Author-Name: S. Dellagi
Author-X-Name-First: S.
Author-X-Name-Last: Dellagi
Author-Name: L. Mifdal
Author-X-Name-First: L.
Author-X-Name-Last: Mifdal
Author-Name: E. M. Kibbou
Author-X-Name-First: E. M.
Author-X-Name-Last: Kibbou
Author-Name: A. Moufki
Author-X-Name-First: A.
Author-X-Name-Last: Moufki
Title: Integrated production-maintenance strategy considering quality constraints in dry machining
Abstract: 
 The selection of the suitable production parameters for dry machining remains a challenging task which impacts the productivity, the system degradation and the quality of the output product. This study proposes an integrated production-maintenance policy allowing the simultaneous consideration of the production parameters, mainly the cutting speed, the production time and cost, the preventive maintenance period and the quality levels and the selling prices of the output product. A special feature of this strategy, defined on a finite time span, is to allow a change of the cutting speed at a certain instant to be determined in an optimal way concurrently with the preventive maintenance period, such as to maximise the total expected profit per time unit. A mathematical model is developed to express the average profit per time unit as a function of the decision variables. A solving procedure is also proposed. A numerical example and a sensitivity analysis are presented in order to show the impact of some major input parameters on the optimal policy.
Journal: International Journal of Production Research
Pages: 2850-2864
Issue: 9
Volume: 60
Year: 2022
Month: 05
X-DOI: 10.1080/00207543.2021.1905193
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1905193
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:9:p:2850-2864

Template-Type: ReDIF-Article 1.0
Author-Name: Bongsug (Kevin) Chae
Author-X-Name-First: Bongsug (Kevin)
Author-X-Name-Last: Chae
Author-Name: David Olson
Author-X-Name-First: David
Author-X-Name-Last: Olson
Title: Technologies and applications of Industry 4.0: insights from network analytics
Abstract: 
 This paper examines the interactions between Industry 4.0 (I4.0) technology, to include artificial intelligence and the Internet of Things, and industry sectors such as manufacturing, healthcare, delivery of consumer goods, and finance. The landscape of I4.0 technologies is reviewed. Interactions are studied through complex network analysis. Industry data from CrunchBase is used to study the application of I4.0 technology in different industries. The network of 543 industry categories as nodes had 1141 relationships. There were 26 key I4.0 nodes that emerged as network hubs. The relative use of I4.0 technology of companies was identified and interconnections between them were measured by network nodes and edges. Temporal analysis was obtained by dividing companies by date of formation. Some of the I4.0 technologies began to appear around 2000. Younger firms were found to have integrated significantly more I4.0 technologies, as expected. The research provides a review of I4.0 technologies by industry that can be used by management to see what competition is doing, and to generate ideas for maintaining or gaining competitive advantage.
Journal: International Journal of Production Research
Pages: 3682-3704
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1931524
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1931524
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3682-3704



Template-Type: ReDIF-Article 1.0
Author-Name: Ge Guo
Author-X-Name-First: Ge
Author-X-Name-Last: Guo
Author-Name: Sarah M. Ryan
Author-X-Name-First: Sarah M.
Author-X-Name-Last: Ryan
Title: Sequencing mixed-model assembly lines with risk-averse stochastic mixed-integer programming
Abstract: 
 Sequencing decisions in mixed-model assembly lines are complicated by various uncertainty factors. This paper addresses a real-life uncertainty factor identified in a manufacturer of large vehicles, by modelling unreliable part delivery and quality. Stochastic optimisation is applied to find sequencing policies that improve the on-time performance of its mixed-model assembly lines. As schedulers have different levels of risk aversion, a risk-averse programme is further presented to protect against the decision maker’s chosen fraction of worst scenarios. Computational studies with Progressive Hedging as the solution method, and its lower bounding approach, demonstrate the high quality of resulting sequencing decisions and the time efficiency of the solution method.
Journal: International Journal of Production Research
Pages: 3774-3791
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1931978
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1931978
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3774-3791



Template-Type: ReDIF-Article 1.0
Author-Name: Minghui Xu
Author-X-Name-First: Minghui
Author-X-Name-Last: Xu
Author-Name: Xin Li
Author-X-Name-First: Xin
Author-X-Name-Last: Li
Title: The interplay between e-tailer information sharing and supplier cause marketing
Abstract: 
 Inspired by the increasing cause marketing (CM) practices of business firms, this paper investigates an e-tailer's incentives to share demand information with its supplier who may implement a CM campaign. Two different selling modes, agency selling and reselling, are examined. Although most previous studies suggest that a retailer should withhold its private demand observations to maintain an information advantage over the supplier, we find that CM may be a driving factor which motivates the e-tailer to share demand information with its supplier under certain conditions. Specifically, when the CM implementation cost is small or large, the e-tailer would like to share demand information under agency selling mode while keeping information private under reselling mode. When the CM implementation cost is intermediate, the consumer's prosociality level is high and information uncertainty is small, the e-tailer misleads (incentives) the supplier to implement CM by withholding (sharing) information under the agency selling (reselling) mode; otherwise, the e-tailer prefers to share (withhold) information under the agency selling (reselling) mode.
Journal: International Journal of Production Research
Pages: 3863-3878
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1933643
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1933643
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3863-3878



Template-Type: ReDIF-Article 1.0
Author-Name: Wenchong Chen
Author-X-Name-First: Wenchong
Author-X-Name-Last: Chen
Author-Name: Xuejian Gong
Author-X-Name-First: Xuejian
Author-X-Name-Last: Gong
Author-Name: Fangyu Liu
Author-X-Name-First: Fangyu
Author-X-Name-Last: Liu
Author-Name: Hongwei Liu
Author-X-Name-First: Hongwei
Author-X-Name-Last: Liu
Author-Name: Roger J. Jiao
Author-X-Name-First: Roger J.
Author-X-Name-Last: Jiao
Title: Bilevel interactive optimisation for rebatching scheduling problem with selectivity banks in high variety flow line production
Abstract: 
 Mass customization enables the integration of traditional flow line production with product platforms to accommodate abundant product-process varieties. These platform-based flow lines explore common process routes while highlighting rebatching scheduling with selectivity banks (RBS) to handle large process varieties across production stages at minimum setup cost. Given the inherent coupling between decision making in job diverging and retrieval quality, an interactive optimization approach is necessary for the RBS problem. This study proposes a bilevel interactive optimization (BIO) model for RBS to accommodate high variety flow line production. The model addresses the conflicting goals of lane occupancy cost, process setup cost, and job divergence and retrieval efficiency. Regarding job divergence at the leader-level, a vehicle routeing problem with precedence constraints is formulated and solved by a constructed genetic algorithm (GA). Concerning job retrieval at the follower-level and the ongoing characteristic of selectivity banks, a dispatching problem with various batch size preference and dynamic time window is established and dealt with a restricted dynamic programming (RDP) algorithm after balancing search efficiency and accuracy. Thus, to solve the BIO, a hybrid GA-RDP is developed and implemented. A practical application to an automotive painting shop illustrates the operational benefits of the BIO model for the RBS problem.
Journal: International Journal of Production Research
Pages: 3879-3900
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1933644
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1933644
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3879-3900



Template-Type: ReDIF-Article 1.0
Author-Name: Priya Ambilkar
Author-X-Name-First: Priya
Author-X-Name-Last: Ambilkar
Author-Name: Vishwas Dohale
Author-X-Name-First: Vishwas
Author-X-Name-Last: Dohale
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Vijay Bilolikar
Author-X-Name-First: Vijay
Author-X-Name-Last: Bilolikar
Title: Product returns management: a comprehensive review and future research agenda
Abstract: 
 Product return is a critical issue due to the uncertainty associated with the price, demand, and quality of the product. Thus, businesses must improve their information transparency to administer the product return behaviour of the end-user. Different studies so far have contributed to developing solutions to manage product return issues. This paper provides a comprehensive review of the literature on the product returns management domain to provide the scientific landscape map of existing studies for exploring the state of the current body of knowledge. A systematic literature review of existing literature, quantitative bibliometric analysis, and in-depth content analysis are conducted to accomplish the purpose. A total of 518 published articles from January 1986 to November 2020 are selected, reviewed, classified, and analysed in this study. We classified papers into six identified PRM categories, namely product recovery, forecasting product returns, consumer behaviour, return policy, uncertainty, and technology. Finally, we blended the state-of-the-art research and outlined the future research agenda concerning various themes, methodologies used, and aspects like lean, agility, and disruption in PRM based on research gap analysis.
Journal: International Journal of Production Research
Pages: 3920-3944
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1933645
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1933645
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Template-Type: ReDIF-Article 1.0
Author-Name: Yanhong Si
Author-X-Name-First: Yanhong
Author-X-Name-Last: Si
Author-Name: Junfeng Tian
Author-X-Name-First: Junfeng
Author-X-Name-Last: Tian
Author-Name: Li Wang
Author-X-Name-First: Li
Author-X-Name-Last: Wang
Author-Name: Xixiu Sun
Author-X-Name-First: Xixiu
Author-X-Name-Last: Sun
Title: Should banks offer concessions? Lending rates for manufacturers’ green products
Abstract: 
 Green loans are not only a new business opportunity but also an important financial tool to promote green consumption. We study the optimal pricing decision of the manufacturer and the lending rate decision of the bank considering the heterogeneous environmental preferences of consumers. It is demonstrated that whether to offer green loan concessions depends on cut-offs with respect to the cost of nongreen products and the green preferences of environmental consumers. Our results indicate that green loan concessions that meet particular conditions can be more profitable for both banks and manufacturers. Consumer surplus and total social welfare can also be improved simultaneously. This finding explains why green loans can be advocated and implemented. Compared to scenarios involving strong green preferences, green loans are more applicable in scenarios with weak green preferences. From the opposite perspective, we can conclude that withdrawal conditions exist for interest rate concessions. Managerial insights are presented, and theoretical viewpoints are confirmed by taking China’s new energy vehicle subsidy declining policy as an example.
Journal: International Journal of Production Research
Pages: 3901-3919
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1934591
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1934591
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Template-Type: ReDIF-Article 1.0
Author-Name: Nickolas Freeman
Author-X-Name-First: Nickolas
Author-X-Name-Last: Freeman
Author-Name: Arunachalam Narayanan
Author-X-Name-First: Arunachalam
Author-X-Name-Last: Narayanan
Title: The impact of multiple products and limited capacity on routine sourcing decisions
Abstract: 
 We study the influence of limited capacity and multiple products on the optimal sourcing decisions for a manufacturer subject to supply and demand uncertainty. The manufacturer produces two products. The component of one product is sourced from two suppliers, one perfectly reliable and the other cheaper but unreliable, failing to deliver the order with some probability. We develop a mathematical model for a single-period setting and study the associated optimality conditions. Our results show that the supplier diversification strategy is significantly different when the buyer has limited capacity. Specifically, we find that single sourcing from an expensive and reliable supplier may be an optimal procurement strategy even when a cheaper option exists. In addition, when producing multiple products, the optimal sourcing strategy may hold inventory of one component to reduce the amount of capacity idling when the supply of a different component is disrupted. We use stochastic programming to validate our single-period findings in a multi-period setting. Although carrying inventory of finished products provides another tactic to mitigate supply uncertainty in a multi-period environment, we observe the key findings from single period, like single-sourcing from an expensive but reliable supplier, remain valid.
Journal: International Journal of Production Research
Pages: 3728-3750
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1931726
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1931726
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3728-3750



Template-Type: ReDIF-Article 1.0
Author-Name: Jinpeng Xu
Author-X-Name-First: Jinpeng
Author-X-Name-Last: Xu
Author-Name: Yufei Huang
Author-X-Name-First: Yufei
Author-X-Name-Last: Huang
Author-Name: Emmanouil Avgerinos
Author-X-Name-First: Emmanouil
Author-X-Name-Last: Avgerinos
Author-Name: Gengzhong Feng
Author-X-Name-First: Gengzhong
Author-X-Name-Last: Feng
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Title: Dual-channel competition: the role of quality improvement and price-matching
Abstract: 
 Quality improvement and price-matching are two commonly used competing strategies by the retailers. However, it is still unclear how the retailers should deliberate over the two strategies when selling in both online and offline markets. In this paper, we consider two dual-channel retailers selling a substitutable product to consumers in both online and offline markets. Especially, the retailers compete in the online market, and their offline markets are exclusive to themselves. We establish a game-theoretical model to investigate the trade-off between quality improvement and price-matching in competition, and the impact on retailers' profits and consumer surplus in the dual-channel market structure. The analysis shows that, first, a retailer should choose to improve its quality to avoid price competition when the online market is small; second, when retailers engage in price competition, the retailer with larger offline market is more willing to adopt price-matching, while the retailer with a small share of offline market can be hurt; third, quality improvement can always increase the consumer surplus, while price-matching always hurts consumer surplus due to price collusion.
Journal: International Journal of Production Research
Pages: 3705-3727
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1931725
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1931725
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3705-3727



Template-Type: ReDIF-Article 1.0
Author-Name: Shijuan Yang
Author-X-Name-First: Shijuan
Author-X-Name-Last: Yang
Author-Name: Jianjun Wang
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wang
Author-Name: Yiliu Tu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Tu
Title: Bayesian robust parameter design for ordered response
Abstract: 
 Due to the nature of the quality characteristics, or there is no instrument available to measure the characteristics of interest, ordered data, e.g. 1 (poor), 2 (satisfactory), 3 (good), and 4 (excellent), often appears in industrial processes. Methods commonly used for continuous or categorical quality characteristics are not appropriate for modelling and optimising such quality characteristics. This motivated us to develop a more useful approach to address the variable selection, model construction, and process optimisation for the ordered response. Specifically, Bayesian Lasso is incorporated into the framework of the response surface model to simultaneously perform variable selection and model estimation. The relationship between the probability of the response falls into a specific category and significant factor effects are established by introducing a latent variable. The desirability function, which is commonly used for multi-objective optimisation for quantitative responses, is extended to process optimisation for the ordered response. A numerical example and an industrial case are used to validate the effectiveness of the proposed method. The performance studies of the proposed method show that our method is more competitive than existing methods.
Journal: International Journal of Production Research
Pages: 3630-3650
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1930235
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1930235
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3630-3650



Template-Type: ReDIF-Article 1.0
Author-Name: Zhifeng Liu
Author-X-Name-First: Zhifeng
Author-X-Name-Last: Liu
Author-Name: Jun Yan
Author-X-Name-First: Jun
Author-X-Name-Last: Yan
Author-Name: Qiang Cheng
Author-X-Name-First: Qiang
Author-X-Name-Last: Cheng
Author-Name: Hongyan Chu
Author-X-Name-First: Hongyan
Author-X-Name-Last: Chu
Author-Name: Jigui Zheng
Author-X-Name-First: Jigui
Author-X-Name-Last: Zheng
Author-Name: Caixia Zhang
Author-X-Name-First: Caixia
Author-X-Name-Last: Zhang
Title: Adaptive selection multi-objective optimization method for hybrid flow shop green scheduling under finite variable parameter constraints: case study
Abstract: 
 The energy consumption loss is high particularly in manufacturing processes involving heating furnaces. Moreover, the mandatory constraints in continuous heating stage bring difficult challenges to production scheduling. To improve the production efficiency and reduce the energy consumption in a hybrid flow shop with continuous and discrete processing stages, this study developed an adaptive selection multi-objective optimization algorithm with preference (ASMOAP). The mandatory constraints of continuous processing stage are transformed into one of the optimization objectives, which is defined as maximum excess value of adjustment time in this paper. A multi-objective optimization scheduling model with the makespan, energy consumption, and maximum excess of adjustment time is established. The optimization preference is designed in the proposed multi-objective optimization algorithm. The maximum excess of adjustment time is set as the multi-objective optimization preference. Three adaptive selection strategies are designed for the algorithm based on the proportions of outstanding and preference individuals to eliminate constraint conflicts. Presented results prove that the proposed algorithm could effectively solve hybrid flow shop scheduling problem considering discrete and continuous processing stages with limited time. It can be applied to obtain a better feasible solution while improving the efficiency and reducing the energy consumed in practical production processes.
Journal: International Journal of Production Research
Pages: 3844-3862
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1933239
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1933239
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3844-3862



Template-Type: ReDIF-Article 1.0
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Author-Name: Qianyang Zhao
Author-X-Name-First: Qianyang
Author-X-Name-Last: Zhao
Title: Probabilistic tabu search algorithm for container liner shipping problem with speed optimisation
Abstract: 
 This paper considers a container liner shipping problem with speed optimisation (CLSP-SO) to minimise the total costs of the fleet, which includes operating costs, capital costs and voyage costs. A mixed-integer nonlinear programming model is first formulated to illustrate the problem, in which the oil consumption of ships is treated as a cubic function of speeds. Then, the computational complexity of the problem is analysed and a lower bound is given based on the theoretical optimised speed of ships. To solve the problem, a probabilistic tabu search (PTS)-based algorithm is developed considering the NP-hardness of the problem. Extensive computational experiments on randomly generated data and a real-world case are conducted and the performance of the proposed method is compared with the lower bound and that of the basic tabu search (TS) algorithm. The results show that the proposed PTS-based algorithm obtains satisfactory solutions with respect to lower bounds in reasonable computation time and it outperforms the basic TS-based algorithm.
Journal: International Journal of Production Research
Pages: 3651-3668
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1930236
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1930236
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3651-3668



Template-Type: ReDIF-Article 1.0
Author-Name: Zaher Al Chami
Author-X-Name-First: Zaher
Author-X-Name-Last: Al Chami
Author-Name: Bechara Bechara
Author-X-Name-First: Bechara
Author-X-Name-Last: Bechara
Author-Name: Hervé Manier
Author-X-Name-First: Hervé
Author-X-Name-Last: Manier
Author-Name: Marie-Ange Manier
Author-X-Name-First: Marie-Ange
Author-X-Name-Last: Manier
Author-Name: Mohamad Sleiman
Author-X-Name-First: Mohamad
Author-X-Name-Last: Sleiman
Title: A GRASP-ALNS combination for robust pickup and delivery problem
Abstract: 
 One of the well-studied routing issues is the Pickup and Delivery Problem (PDP). It aims to route a fleet of vehicles based on a depot to satisfy a set of transport requests subject to numerous constraints. In real-life cases, the satisfaction of those requests over a given time slot (1 day for example) may become impossible while respecting all problem constraints. Therefore, the studied variant is characterised by the selective aspect which consists of choosing a subset of demands to be honoured. In addition, travel times between sites may be uncertain and may vary according to several scenarios. The robustness consists then at finding a solution which remains feasible over all scenarios. Therefore, the goal of this study is to introduce lexicographic and metaheuristic approaches to solve the Robust Selective PDP (RSPDP). Numerous tests have been done on new instances for the considered variant, in order to show the efficiency of proposed approaches.
Journal: International Journal of Production Research
Pages: 3809-3828
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1933236
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1933236
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Handle: RePEc:taf:tprsxx:v:60:y:2022:i:12:p:3809-3828



Template-Type: ReDIF-Article 1.0
Author-Name: Yuwei Lu
Author-X-Name-First: Yuwei
Author-X-Name-Last: Lu
Author-Name: Kangzhou Wang
Author-X-Name-First: Kangzhou
Author-X-Name-Last: Wang
Author-Name: Biao Yuan
Author-X-Name-First: Biao
Author-X-Name-Last: Yuan
Title: The vehicle relocation problem with operation teams in one-way carsharing systems
Abstract: 
 The imbalance of available vehicles at different stations is an outstanding challenge in one-way carsharing systems. Dedicated to this issue, the operation teams in one company in Shanghai, China, each of which contains several workers, take operation vehicles to rebalance sharing vehicles among stations. A pertinent optimization problem, called the vehicle relocation problem with operation teams, is encountered in practice to find the relocation pairs of stations and the visiting routes of operation vehicles. In this paper, a mathematical programming model for minimizing the sum of relocation distance of sharing vehicles and travel distance of operation vehicles is constructed. An adaptive large neighbourhood search algorithm with several problem-specific algorithmic components is developed to efficiently solve the problem. Computational results validate the competitive performance of the proposed approach by comparing it with the commercial optimization software and a sequential approach.
Journal: International Journal of Production Research
Pages: 3829-3843
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1933238
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1933238
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Template-Type: ReDIF-Article 1.0
Author-Name: Dan Luo
Author-X-Name-First: Dan
Author-X-Name-Last: Luo
Author-Name: Zailin Guan
Author-X-Name-First: Zailin
Author-X-Name-Last: Guan
Author-Name: Cong He
Author-X-Name-First: Cong
Author-X-Name-Last: He
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Lei Yue
Author-X-Name-First: Lei
Author-X-Name-Last: Yue
Title: Data-driven cloud simulation architecture for automated flexible production lines: application in real smart factories
Abstract: 
 In recent years, more manufacturing enterprises are building automated flexible production lines (AFPLs) to satisfy the dynamic and diversified demand. Currently, static planning methods can hardly meet the requirements of the dynamic resource allocation for AFPLs. The technologies of the digital twin can help solve dynamic problems. Therefore, we propose a data-driven cloud simulation architecture for AFPLs in smart factories. First, we design a cloud simulation platform as the architecture foundation. Second, we use the data-driven modelling and simulation method to achieve automated modelling. Third, we implement the system on the cloud using Java, MySQL, and the Anylogic platform, and verify the efficiency of the proposed method by experiments in the real workshop of a 3C (Computer, Communication, Consumer electronics) company. The experimental results show the proposed architecture can support the real-time resource allocation decisions to maximise the throughput in AFPLs. This paper makes contributions by proposing an architecture realising automatic modelling and data-driven simulation first in the cloud simulation environment, and filling the gap of dynamic resource allocation in the research of AFPLs.
Journal: International Journal of Production Research
Pages: 3751-3773
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1931977
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1931977
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Template-Type: ReDIF-Article 1.0
Author-Name: Alexander Seitz
Author-X-Name-First: Alexander
Author-X-Name-Last: Seitz
Author-Name: Renzo Akkerman
Author-X-Name-First: Renzo
Author-X-Name-Last: Akkerman
Author-Name: Martin Grunow
Author-X-Name-First: Martin
Author-X-Name-Last: Grunow
Title: A contract portfolio perspective on the role of customer order lead times in demand fulfilment processes with supply shortage
Abstract: 
 When demands exceed capacities, suppliers allocate available supply to customers based on customer importance and advance demand information. The accuracy of advance demand information interacts with the length of customer order lead times and influences overall customer service levels. In this paper, we analyse industrial contract portfolios with customer-specific terms in order to derive insights for contract portfolio management and the design of demand fulfilment processes. For this purpose, we develop a framework for analysis of contract portfolios capturing the dynamics of industrial planning processes. The framework is applied to portfolios from the semiconductor sector. Our numerical analysis shows that, in order to improve service levels, demand fulfilment processes and contract portfolio management must especially take into account the length of order lead times and the accuracy of advance demand information. Even though suppliers often prefer long order lead times, our analysis shows that demand fulfilment performance is not primarily determined by the absolute length of the order lead times but by the presence of a negative correlation with the accuracy of advance demand information in the entire contract portfolio. Consequently, these factors require increased attention in the management of contract portfolios and in the negotiation of individual contracts.
Journal: International Journal of Production Research
Pages: 3792-3808
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1931979
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1931979
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Template-Type: ReDIF-Article 1.0
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Title: Order release, dispatching and resource assignment in multiple resource-constrained job shops: an assessment by simulation
Abstract: 
 In manufacturing shops in practice, machine capacity is often constrained by more than one type of resource. Yet research mainly focusses on the effects of only one type of resource that constrains machine capacity, e.g. labour, tooling or auxiliary constraints. In response, we use simulation to assess the impact of order release, dispatching and resource assignment rules in make-to-order job shops with multiple resource constraints. The capacity wasted while a machine stands idle waiting for other resources increases with the number of constraints, and all three production planning and control functions have little impact on this waiting time. Effective production planning and control can however improve operational performance in terms of time and tardiness-related measures. In general, combining order release control with a dispatching rule that prioritises jobs for which all resources are available at dispatching and a longest queue resource assignment rule leads to the best performance. Most importantly, and rather counterintuitively, prioritising orders with the fewest missing resources worsens the performance of both the dispatching and resource assignment rule since it reduces resource utilisation during periods of high load. Results from dual resource-constrained shops are consequently not directly transferable to more complex resource-constrained shops.
Journal: International Journal of Production Research
Pages: 3669-3681
Issue: 12
Volume: 60
Year: 2022
Month: 06
X-DOI: 10.1080/00207543.2021.1930240
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1930240
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Template-Type: ReDIF-Article 1.0
Author-Name: Renke Liu
Author-X-Name-First: Renke
Author-X-Name-Last: Liu
Author-Name: Rajesh Piplani
Author-X-Name-First: Rajesh
Author-X-Name-Last: Piplani
Author-Name: Carlos Toro
Author-X-Name-First: Carlos
Author-X-Name-Last: Toro
Title: Deep reinforcement learning for dynamic scheduling of a flexible job shop
Abstract: 
 The ability to handle unpredictable dynamic events is becoming more important in pursuing agile and flexible production scheduling. At the same time, the cyber-physical convergence in production system creates massive amounts of industrial data that needs to be mined and analysed in real-time. To facilitate such real-time control, this research proposes a hierarchical and distributed architecture to solve the dynamic flexible job shop scheduling problem. Double Deep Q-Network algorithm is used to train the scheduling agents, to capture the relationship between production information and scheduling objectives, and make real-time scheduling decisions for a flexible job shop with constant job arrivals. Specialised state and action representations are proposed to handle the variable specification of the problem in dynamic scheduling. Additionally, a surrogate reward-shaping technique to improve learning efficiency and scheduling effectiveness is developed. A simulation study is carried out to validate the performance of the proposed approach under different scenarios. Numerical results show that not only does the proposed approach deliver superior performance as compared to existing scheduling strategies, its advantages persist even if the manufacturing system configuration changes.
Journal: International Journal of Production Research
Pages: 4049-4069
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2022.2058432
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2058432
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Template-Type: ReDIF-Article 1.0
Author-Name: Mir Ehsan Hesam Sadati
Author-X-Name-First: Mir Ehsan Hesam
Author-X-Name-Last: Sadati
Author-Name: Vahid Akbari
Author-X-Name-First: Vahid
Author-X-Name-Last: Akbari
Author-Name: Bülent Çatay
Author-X-Name-First: Bülent
Author-X-Name-Last: Çatay
Title: Electric vehicle routing problem with flexible deliveries
Abstract: 
 Growing concerns about the climate change have forced governments to initiate tighter environmental regulations and tougher emission reduction targets, increasing the interest on electromobility. Logistics operators started employing electric vehicles (EVs) and must face new operational planning challenges. Moreover, with an ever-growing interest in e-commerce, parcel delivery is taking new shapes by offering flexible delivery options to the customers. To mitigate these issues, we introduce the Electric Vehicle Routing Problem with Flexible Deliveries (EVRP-FD), where the customers are served using a fleet of EVs that can recharge their batteries along their routes. In this problem, a customer may specify different delivery locations for different time windows. Our objective is to serve the customers while minimising the total travelled distance using minimum number of vehicles. We first give the mathematical model and then develop a hybrid Variable Neighbourhood Search coupled with Tabu Search by proposing new mechanisms to solve the problem effectively. Then, we verify the performance of our algorithm on instances from the literature. We also introduce new instances for the EVRP-FD and perform an extensive computational study to investigate the trade-offs associated with different operational factors. Finally, we present a case study in Nottingham, UK to provide further insights.
Journal: International Journal of Production Research
Pages: 4268-4294
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2022.2032451
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2032451
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Template-Type: ReDIF-Article 1.0
Author-Name: Sungbum Jun
Author-X-Name-First: Sungbum
Author-X-Name-Last: Jun
Author-Name: Chul Hun Choi
Author-X-Name-First: Chul Hun
Author-X-Name-Last: Choi
Author-Name: Seokcheon Lee
Author-X-Name-First: Seokcheon
Author-X-Name-Last: Lee
Title: Scheduling of autonomous mobile robots with conflict-free routes utilising contextual-bandit-based local search
Abstract: 
 As autonomous robot and sensor technologies have advanced, utilisation of autonomous mobile robots (AMRs) in material handling has grown quickly, owing especially to their scalability and versatility compared with automated guided vehicles (AGVs). In order to take full advantage of AMRs, in this paper, we address an AMR scheduling and routing problem by dividing the entire problem into three sub-problems: path finding, vehicle routing, and conflict resolution. We first discuss the previous literature on characteristics of each sub-problem. We then present a comprehensive framework for minimising total tardiness of transportation requests with consideration of conflicts between routes. First, the shortest paths between all locations are calculated with A*. Based on the shortest paths, for vehicle routing, we propose a new local search algorithm called COntextual-Bandit-based Adaptive Local search with Tree-based regression (COBALT), which utilises the contextual bandit to select the best operator in consideration of contexts. After routing of AMRs, an agent-based model with states and protocols resolves collisions and deadlocks in a decentralised way. The results indicate that the proposed framework can improve the performance of AMR scheduling for conflict-free routes and that, especially for vehicle routing, COBALT outperforms the other algorithms in terms of average total tardiness.
Journal: International Journal of Production Research
Pages: 4090-4116
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2022.2063085
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2063085
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Template-Type: ReDIF-Article 1.0
Author-Name: Yinfeng Du
Author-X-Name-First: Yinfeng
Author-X-Name-Last: Du
Author-Name: Dun Liu
Author-X-Name-First: Dun
Author-X-Name-Last: Liu
Author-Name: Hengxin Duan
Author-X-Name-First: Hengxin
Author-X-Name-Last: Duan
Title: A textual data-driven method to identify and prioritise user preferences based on regret/rejoicing perception for smart and connected products
Abstract: 
 The rapid development of information technologies yields a promising market for information densely products, i.e. smart, connected products (SCPs) and also alters the way of user-designer interaction in the product design and development. Online review has become a convenient and efficient way to express customers' opinions and preferences on products they have bought. In order to identify and prioritise customer needs in the smartness connected era, this study proposes a novel textual data-driven and regret/rejoicing perception-based user preferences identification and priority framework for SCPs. We first dig customer needs and evaluations from online customer reviews, then design a new directional distance index-based approach to acquire user weights. Combining absolute and relative weights, we introduce an integrated approach to prioritise all customer preferences. Specially, absolute weights are obtained by an improved Borda method based on frequency and position information, while relative weights are determined through probabilistic linguistic-based regret/rejoicing decision-making method. Finally, an application of 12 kinds of smart speakers is constructed and discussed to illustrate the feasibility and usefulness of the proposed approach, and these corresponding results are helpful for smart design, development and improvement of SCPs.
Journal: International Journal of Production Research
Pages: 4176-4196
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2023776
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2023776
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Template-Type: ReDIF-Article 1.0
Author-Name: Salama Shady
Author-X-Name-First: Salama
Author-X-Name-Last: Shady
Author-Name: Toshiya Kaihara
Author-X-Name-First: Toshiya
Author-X-Name-Last: Kaihara
Author-Name: Nobutada Fujii
Author-X-Name-First: Nobutada
Author-X-Name-Last: Fujii
Author-Name: Daisuke Kokuryo
Author-X-Name-First: Daisuke
Author-X-Name-Last: Kokuryo
Title: A novel feature selection for evolving compact dispatching rules using genetic programming for dynamic job shop scheduling
Abstract: 
 Because of advances in computational power and machine learning algorithms, the automated design of scheduling rules using Genetic Programming (GP) is successfully applied to solve dynamic job shop scheduling problems. Although GP-evolved rules usually outperform dispatching rules reported in the literature, intensive computational costs and rule interpretability persist as important limitations. Furthermore, the importance of features in the terminal set varies greatly among scenarios. The inclusion of irrelevant features broadens the search space. Therefore, proper selection of features is necessary to increase the convergence speed and to improve rule understandability using fewer features. In this paper, we propose a new representation of the GP rules that abstracts the importance of each terminal. Moreover, an adaptive feature selection mechanism is developed to estimate terminals’ weights from earlier generations in restricting the search space of the current generation. The proposed approach is compared with three GP algorithms from the literature and 30 human-made rules from the literature under different job shop configurations and scheduling objectives, including total weighted tardiness, mean tardiness, and mean flow time. Experimentally obtained results demonstrate that the proposed approach outperforms methods from the literature in generating more interpretable rules in a shorter computational time without sacrificing solution quality.
Journal: International Journal of Production Research
Pages: 4025-4048
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2022.2053603
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2053603
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Template-Type: ReDIF-Article 1.0
Author-Name: Kai Zhang
Author-X-Name-First: Kai
Author-X-Name-Last: Zhang
Author-Name: Ting Qu
Author-X-Name-First: Ting
Author-X-Name-Last: Qu
Author-Name: Yongheng Zhang
Author-X-Name-First: Yongheng
Author-X-Name-Last: Zhang
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Author-Name: George Huang
Author-X-Name-First: George
Author-X-Name-Last: Huang
Title: Big data-enabled intelligent synchronisation for the complex production logistics system under the opti-state control strategy
Abstract: 
 Diversified customer needs make the production system more susceptible to high-frequency fluctuations of uncertain factors (UFs), which puts forward higher requirements for the real-time and systematic decision-making of the system. The opti-state control strategy enables the system to maintain the adaptive optimal state after being disturbed. The core intelligent synchronisation of the opti-state control strategy needs to perceive the state of the affected system and its degree of change. Aiming at the challenge of difficulty in evaluating the uncertain factors impact degree (UFID) of the complex production logistics system, this work proposes a big data-enabled intelligent synchronisation under the opti-state control strategy. Based on the simulation data of system operation, big data is used to mine the relationship between the UFID and the system states, then use wrapper GA-DNN (Deep Neural Network) feature selection and classification method evaluates the UFID, which will be applied to the synchronisation decision. The results show that the method can accurately evaluate the UFID and avoid the waste of resources and the increase in operating costs caused by excessive evaluation of the UFID, thereby also improves the effectiveness and efficiency of the opti-state control strategy.
Journal: International Journal of Production Research
Pages: 4159-4175
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2000657
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2000657
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Template-Type: ReDIF-Article 1.0
Author-Name: Nan Chen
Author-X-Name-First: Nan
Author-X-Name-Last: Chen
Author-Name: Wenxuan Kang
Author-X-Name-First: Wenxuan
Author-X-Name-Last: Kang
Author-Name: Ningxuan Kang
Author-X-Name-First: Ningxuan
Author-X-Name-Last: Kang
Author-Name: Yongzhi Qi
Author-X-Name-First: Yongzhi
Author-X-Name-Last: Qi
Author-Name: Hao Hu
Author-X-Name-First: Hao
Author-X-Name-Last: Hu
Title: Order processing task allocation and scheduling for E-order fulfilment
Abstract: 
 This paper mainly studies a task allocation and scheduling problem in the multi-thread fulfilment process of electronic order, which seeks to minimise the makespan under thread constraints and order precedence constraints. The problem is formulated as a Mixed Integer Programming (MIP) model and a novel depth-first heuristic is proposed to solve it. The depth-first heuristic shows high effectiveness and efficiency, compared with the current policy and the genetic algorithm in both small/medium-scale and large-scale cases from the real transaction data. In addition, two extensions on precedence constraint reduction and resource allocation are discussed to further improve and manage the e-order fulfilment process.
Journal: International Journal of Production Research
Pages: 4253-4267
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2018140
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2018140
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Template-Type: ReDIF-Article 1.0
Author-Name: Jun Kim
Author-X-Name-First: Jun
Author-X-Name-Last: Kim
Author-Name: Hyun-Jung Kim
Author-X-Name-First: Hyun-Jung
Author-X-Name-Last: Kim
Title: An exact algorithm for an identical parallel additive machine scheduling problem with multiple processing alternatives
Abstract: 
 This paper develops an exact algorithm for the identical parallel additive machine scheduling problem by considering multiple processing alternatives to minimise the makespan. This research is motivated from an idea of elevating flexibility of a manufacturing system by using additive machines, such as 3D printers. It becomes possible to produce a job in a different form; a job can be printed in a complete form or in separate parts. This problem is defined as a bi-level optimisation model in which its upper level problem is to determine a proper processing alternative for each product, and its lower level problem is to assign the parts that should be produced to the additive machines. An exact algorithm, which consists of the linear programming relaxation of a one-dimensional cutting stock problem, a branch-and-price algorithm, and a rescheduling algorithm, is proposed to find an optimal solution of the problem. The experimental results show that the computational time of the algorithm outperforms a commercial solver (CPLEX). By examining how the parts are comprised when the processing alternatives are optimally selected, some useful insights are derived for designing processing alternatives of products.
Journal: International Journal of Production Research
Pages: 4070-4089
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2007426
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2007426
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingshan Li
Author-X-Name-First: Jingshan
Author-X-Name-Last: Li
Author-Name: Chao-Bo Yan
Author-X-Name-First: Chao-Bo
Author-X-Name-Last: Yan
Author-Name: Hyun-Jung Kim
Author-X-Name-First: Hyun-Jung
Author-X-Name-Last: Kim
Author-Name: Xiaolei Xie
Author-X-Name-First: Xiaolei
Author-X-Name-Last: Xie
Author-Name: Hyo-Kyung Lee
Author-X-Name-First: Hyo-Kyung
Author-X-Name-Last: Lee
Title: Special Issue on Analysis, Design, and Optimization in Smart and Connected Production and Service Systems
Journal: International Journal of Production Research
Pages: 3945-3947
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2022.2078036
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2078036
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Template-Type: ReDIF-Article 1.0
Author-Name: Oliver Antons
Author-X-Name-First: Oliver
Author-X-Name-Last: Antons
Author-Name: Julia C. Arlinghaus
Author-X-Name-First: Julia C.
Author-X-Name-Last: Arlinghaus
Title: Distributing decision-making authority in manufacturing – review and roadmap for the factory of the future
Abstract: 
 The question of the benefits of autonomous control is more important than ever: production managers, governments and society hope that the vision of smart and digital production systems with high flexibility and low costs may save the value adding and therefore welfare in the high wage, industrialised countries. At the same time, the discussion on the social implications of autonomous objects and decentralised control approaches is growing. Looking back on the history of production research and practice, we find that there has been a constant ply among scholars and production managers between the advantages of the two concepts of centralised and decentralised control approaches. In this article, we study the concept of autonomy in production planning and control, enabled by cyber-physical systems and the distribution of decision-making authority. Based on a profound structured literature review, we analyse the perception of autonomy, the technological requirements and the increasing complexities of modern smart manufacturing. Moreover, we find that recently several research streams suggest the advantages and benefits of autonomous control concepts compared to traditional centralised approaches based on qualitative analysis and identify a distinct lack of quantitative results.
Journal: International Journal of Production Research
Pages: 4342-4360
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2022.2057255
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2057255
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Template-Type: ReDIF-Article 1.0
Author-Name: Marcel Panzer
Author-X-Name-First: Marcel
Author-X-Name-Last: Panzer
Author-Name: Benedict Bender
Author-X-Name-First: Benedict
Author-X-Name-Last: Bender
Title: Deep reinforcement learning in production systems: a systematic literature review
Abstract: 
 Shortening product development cycles and fully customisable products pose major challenges for production systems. These not only have to cope with an increased product diversity but also enable high throughputs and provide a high adaptability and robustness to process variations and unforeseen incidents. To overcome these challenges, deep Reinforcement Learning (RL) has been increasingly applied for the optimisation of production systems. Unlike other machine learning methods, deep RL operates on recently collected sensor-data in direct interaction with its environment and enables real-time responses to system changes. Although deep RL is already being deployed in production systems, a systematic review of the results has not yet been established. The main contribution of this paper is to provide researchers and practitioners an overview of applications and to motivate further implementations and research of deep RL supported production systems. Findings reveal that deep RL is applied in a variety of production domains, contributing to data-driven and flexible processes. In most applications, conventional methods were outperformed and implementation efforts or dependence on human experience were reduced. Nevertheless, future research must focus more on transferring the findings to real-world systems to analyse safety aspects and demonstrate reliability under prevailing conditions.
Journal: International Journal of Production Research
Pages: 4316-4341
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1973138
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1973138
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Template-Type: ReDIF-Article 1.0
Author-Name: Carolin Kellenbrink
Author-X-Name-First: Carolin
Author-X-Name-Last: Kellenbrink
Author-Name: Nicolas Nübel
Author-X-Name-First: Nicolas
Author-X-Name-Last: Nübel
Author-Name: André Schnabel
Author-X-Name-First: André
Author-X-Name-Last: Schnabel
Author-Name: Philipp Gilge
Author-X-Name-First: Philipp
Author-X-Name-Last: Gilge
Author-Name: Joerg R. Seume
Author-X-Name-First: Joerg R.
Author-X-Name-Last: Seume
Author-Name: Berend Denkena
Author-X-Name-First: Berend
Author-X-Name-Last: Denkena
Author-Name: Stefan Helber
Author-X-Name-First: Stefan
Author-X-Name-Last: Helber
Title: A regeneration process chain with an integrated decision support system for individual regeneration processes based on a virtual twin
Abstract: 
 Regeneration processes of complex capital goods such as components of aircraft engines are highly complex and require a multi-disciplinary perspective, bringing together expertise from different fields such as production engineering, image-based measuring technology, turbomachinery, and operations management. Sustainability requirements and digitalisation opportunities both demand and suggest systematic, flexible, and economically efficient design and operation of the regeneration process chains. This multi-disciplinary case study documents the design and operation of a cyber-physical system demonstrator for individual, flexible and economically optimised maintenance, repair, and overhaul (MRO) actions on extremely valuable components of aircraft engines: high-pressure turbine blades. This system demonstrator hence brings together research results from different disciplines considered jointly in the German Collaborative Research Centre 871 ‘Product-Regeneration’. To cope with the substantial variability in used-good damage patterns and the resulting MRO actions, the system demonstrator operates with a virtual layer and uses a virtual twin of the object to be regenerated. In addition to a functional simulation, a central component of that virtual layer is a project-scheduling-based decision support system used to both select the MRO actions and control the shop floor. This paper hence describes how recent research results can be combined to achieve innovative, efficient, and sustainable regeneration processes.
Journal: International Journal of Production Research
Pages: 4137-4158
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2022.2051089
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2051089
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Template-Type: ReDIF-Article 1.0
Author-Name: Zixiang Wang
Author-X-Name-First: Zixiang
Author-X-Name-Last: Wang
Author-Name: Ran Liu
Author-X-Name-First: Ran
Author-X-Name-Last: Liu
Title: Managing appointments of outpatients considering the presence of emergency patients: the combination of the analytical and data-driven approach
Abstract: 
 Patient appointments are an effective method to reduce patient waiting time. However, not all patients can make an appointment before receiving medical services. In this paper, we focus on the patient appointment scheduling problem in the presence of emergency patients. We formulate the problem as a stochastic programming (SP) model to reduce the patient waiting time and increase server utilisation. Considering the service system as a time-varying queuing system with dual-class patients, we propose two methods to evaluate the patients waiting times and the server utilisation for a given patient appointment schedule. The uniformisation method can ‘exactly’ evaluate the performance metrics with a high computation cost, while the trained machine learning models can approximate the metrics with high computing speed. Based on the proposed evaluation methods, we design a simulated annealing algorithm to solve the SP model. Numerical experiments show that the schedule computed by our heuristic algorithm can effectively improve the real-life patient appointment schedule.
Journal: International Journal of Production Research
Pages: 4214-4228
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2007425
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2007425
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Template-Type: ReDIF-Article 1.0
Author-Name: Jingchuan Chen
Author-X-Name-First: Jingchuan
Author-X-Name-Last: Chen
Author-Name: Zhiyang Jia
Author-X-Name-First: Zhiyang
Author-X-Name-Last: Jia
Author-Name: Xiaohan Wang
Author-X-Name-First: Xiaohan
Author-X-Name-Last: Wang
Title: Dynamic performance prediction in flexible production lines with two geometric machines
Abstract: 
 Due to the intelligent manufacturing strategies deployed and being implemented in recent years, flexible production is widely used on the factory floor at present. While most of the existing investigations are concerned with the steady-state of systems, very few results have been published on systems' dynamic behaviour. However, since flexible production is sometimes carried out according to customised orders, most of which are in relatively medium or even small sizes, part or all the production of such systems are in the dynamic process. As a result, the dynamic characteristics of production systems are of significant importance. Meanwhile, dynamic performance is regarded as an important direction in the research of manufacturing systems. In this work, for serial flexible production lines with two geometric machines and one finite buffer, we study the problems of dynamic performance evaluation, system behavioural properties, and energy-efficient operation control. Specifically, the model of production lines under consideration is formulated. Then, an analytical method to assess the dynamic performance of such flexible production lines is proposed. Moreover, the behavioural properties of the systems are also investigated. Finally, we study the problem of control parameters selection for the system under operation control.
Journal: International Journal of Production Research
Pages: 4006-4024
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2009587
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2009587
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Template-Type: ReDIF-Article 1.0
Author-Name: Jiachen Tu
Author-X-Name-First: Jiachen
Author-X-Name-Last: Tu
Author-Name: Liang Zhang
Author-X-Name-First: Liang
Author-X-Name-Last: Zhang
Title: Performance analysis and optimisation of Bernoulli serial production lines with dynamic real-time bottleneck identification and mitigation
Abstract: 
 With the rapid advances of Industry 4.0 technologies, developing rigorous, model-based algorithms for production system performance metrics calculation, control, and optimization has become a critical task to inject intelligence into the smart manufacturing practice, thus facilitating automated decision-making on the factory floor. This paper is intended to contribute to this area. Specifically, we consider serial production lines with finite buffers and machines following the Bernoulli reliability model. In addition, we assume that one can dynamically control the allocation of a shared workforce via real-time production bottleneck identification and mitigation. We first derive formulas to calculate the performance metrics of two-machine systems. Then, we extend the results to multi-machine cases by developing an aggregation-based analytical algorithm, whose accuracy is verified using numerical experiments. Based on this performance evaluation method, we study the optimization of the control policy. In particular, a space reduction technique is applied that decomposes the system into several sub three-machine lines and search algorithms are proposed to identify a good-quality control policy in the reduced policy space. Numerical experiments are used to demonstrate the efficacy of the optimized policy. An illustrative example is given to provide insights into the structure and operation of an effective control policy.
Journal: International Journal of Production Research
Pages: 3989-4005
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2019343
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2019343
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Template-Type: ReDIF-Article 1.0
Author-Name: Weihua Liu
Author-X-Name-First: Weihua
Author-X-Name-Last: Liu
Author-Name: Shangsong Long
Author-X-Name-First: Shangsong
Author-X-Name-Last: Long
Author-Name: Shuang Wei
Author-X-Name-First: Shuang
Author-X-Name-Last: Wei
Author-Name: Dong Xie
Author-X-Name-First: Dong
Author-X-Name-Last: Xie
Author-Name: Jingkun Wang
Author-X-Name-First: Jingkun
Author-X-Name-Last: Wang
Author-Name: Xinyun Liu
Author-X-Name-First: Xinyun
Author-X-Name-Last: Liu
Title: Smart logistics ecological cooperation with data sharing and platform empowerment: an examination with evolutionary game model
Abstract: 
 With the application of advanced technology, smart logistics ecological cooperation is in development, characterised by data sharing and platform empowerment. In order to explore the trend of ecological cooperation between the logistics platform and the supplier from the perspective of business ecosystem, this study uses evolutionary game theory to describe the multi-period game between the two parties, and obtains the equilibrium where the two parties both choose ecological cooperation and its preconditions. Through sensitivity analysis, we obtain the specific paths to convert other evolutionary stable strategies (ESSs) into the ideal ESS by adjusting certain parameters, and provide suggestions for the platform to induce its supplier to choose ecological cooperation. The platform should charge a reasonable agency fee to reach the ecological cooperation. The relationship between the agency fee, empowerment cost, and service price elasticity coefficient determines the platform's ultimate evolutionary stable strategy. This study finds the butterfly effect of ecological cooperation. There are different combinations of the initial probabilities between the two parties making them both choose ecological cooperation or both not choose under the same condition.
Journal: International Journal of Production Research
Pages: 4295-4315
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1925173
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1925173
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoxiao Shen
Author-X-Name-First: Xiaoxiao
Author-X-Name-Last: Shen
Author-Name: Na Li
Author-X-Name-First: Na
Author-X-Name-Last: Li
Title: Scheduling policies analysis for matching operations in Bernoulli selective assembly lines
Abstract: 
 In a selective assembly system, mismatched products can pass inspections due to the flexibility of product quality grades. However, they will be sold at discounted prices leading to a revenue decline. Hence, it is critical to design an appropriate scheduling policy for better matching to maximise the system quality-related revenue. In this paper, we propose a Waiting for Closest Quality Matching Policy (WCQMP), which allows postponing the assembly process within the waiting threshold. And once the postpone is finished, the closest quality parts will be selected to match. The other two policies, Random Matching Policy (RMP) and Closest Quality Matching Policy (CQMP), are also proposed as comparisons. We construct Markov chain models for small systems and develop approximation methodologies for larger systems to analyze the performance under the policies. Comparisons of different scheduling policies and the performance analysis of WCQMP are carried out in numerical studies. Our findings indicate that nearly in all the systems, WCQMP, CQMP performs better than RMP. And when system and policy parameters are properly designed, WCQMP is more superior by improving assembly quality without overly sacrificing system throughput, thereby increasing quality-related revenue. Managerial insights are also provided for industrial practitioners to apply WCQMP more appropriately.
Journal: International Journal of Production Research
Pages: 3965-3988
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1939903
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1939903
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Template-Type: ReDIF-Article 1.0
Author-Name: Xingrui Cheng
Author-X-Name-First: Xingrui
Author-X-Name-Last: Cheng
Author-Name: Chao-Bo Yan
Author-X-Name-First: Chao-Bo
Author-X-Name-Last: Yan
Author-Name: Feng Gao
Author-X-Name-First: Feng
Author-X-Name-Last: Gao
Title: Energy cost optimisation in two-machine Bernoulli serial lines under time-of-use pricing
Abstract: 
 Energy cost optimisation in manufacturing systems has gained more and more attention. Although there are many papers about energy consumption optimisation in serial production lines, energy cost optimisation in serial production lines has rarely been focused. In this paper, we formulate an energy cost optimisation problem in two-machine Bernoulli serial line under time-of-use pricing. We analyse the structural characteristics of the problem and transform the problem into optimally allocating the production rate among the time periods of different electricity rates. A definition of the extreme allocation is proposed and completed, and the optimal allocation is proved to be one of the extreme allocations. Using the property, an efficient method to solve the optimal allocation is proposed. With the help of the method, the multi-electricity-rate problem is transformed into several single-electricity-rate problems, which has been solved in the literature.
Journal: International Journal of Production Research
Pages: 3948-3964
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1936265
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1936265
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Template-Type: ReDIF-Article 1.0
Author-Name: Zhenghao Fan
Author-X-Name-First: Zhenghao
Author-X-Name-Last: Fan
Author-Name: Xiaolei Xie
Author-X-Name-First: Xiaolei
Author-X-Name-Last: Xie
Title: A distributionally robust optimisation for COVID-19 testing facility territory design and capacity planning
Abstract: 
 COVID-19 has been a severe crisis for global health, which caused significant loss of life and property. One of the most effective ways to prevent the spread of the virus during an epidemic is to provide nucleic-acid tests for the population. Management of testing resources is both critical and challenging because outbreaks are irregular and resources are scarce. In this study, we develop a decision support tool for city governments by districting testing facilities and determining their capacities. Considering the stochastic testing demand during a disease outbreak, a set-partitioning model embedded with a two-stage distributionally robust optimisation is formulated. Tractable reformulations are derived to solve the problems efficiently and a conservative approximation method is introduced to achieve acceptable accuracy while reducing the computational burden. Compared with different benchmark models, the numerical analyses demonstrate the effectiveness of the proposed territory design, which realises a robust testing infrastructure network and saves the cost while pursuing capability.
Journal: International Journal of Production Research
Pages: 4229-4252
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2022233
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2022233
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Template-Type: ReDIF-Article 1.0
Author-Name: Hao Wang
Author-X-Name-First: Hao
Author-X-Name-Last: Wang
Author-Name: Jiaqi Tao
Author-X-Name-First: Jiaqi
Author-X-Name-Last: Tao
Author-Name: Tao Peng
Author-X-Name-First: Tao
Author-X-Name-Last: Peng
Author-Name: Alexandra Brintrup
Author-X-Name-First: Alexandra
Author-X-Name-Last: Brintrup
Author-Name: Edward Elson Kosasih
Author-X-Name-First: Edward Elson
Author-X-Name-Last: Kosasih
Author-Name: Yuqian Lu
Author-X-Name-First: Yuqian
Author-X-Name-Last: Lu
Author-Name: Renzhong Tang
Author-X-Name-First: Renzhong
Author-X-Name-Last: Tang
Author-Name: Luoke Hu
Author-X-Name-First: Luoke
Author-X-Name-Last: Hu
Title: Dynamic inventory replenishment strategy for aerospace manufacturing supply chain: combining reinforcement learning and multi-agent simulation
Abstract: 
 The (I, R, S) policy is a well-known inventory replenishment strategy, where inventory is raised to an order-up-to-level S at the end of each review interval I, if it falls below a reorder-point R. Determining the optimal values for these parameters by mathematical analysis methods are difficult, especially in sectors with complex and uncertain purchasing, manufacturing and delivering processes. The (I, R, S) policy has been shown to result in low supply chain performance (SCP) composed of sales revenue, tardiness fine, manufacturing cost, inventory holding cost, raw material cost, etc. in industries that involve highly-customised orders, such as aerospace industry. In this paper, we develop a multi-agent simulation model combined with a reinforcement learning-based dynamic inventory replenishment strategy to maximise the SCP. The approach has been applied in an aerospace manufacturing case study. It empirically demonstrates that the dynamic strategy yields considerable improvements, and has an additional benefit of adaptivity to changes, such as demand and supply uncertainties.
Journal: International Journal of Production Research
Pages: 4117-4136
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2020927
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2020927
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Template-Type: ReDIF-Article 1.0
Author-Name: Xiang Zhong
Author-X-Name-First: Xiang
Author-X-Name-Last: Zhong
Author-Name: Farnaz Babaie Sarijaloo
Author-X-Name-First: Farnaz
Author-X-Name-Last: Babaie Sarijaloo
Author-Name: Aditya Prakash
Author-X-Name-First: Aditya
Author-X-Name-Last: Prakash
Author-Name: Jaeyoung Park
Author-X-Name-First: Jaeyoung
Author-X-Name-Last: Park
Author-Name: Chanyan Huang
Author-X-Name-First: Chanyan
Author-X-Name-Last: Huang
Author-Name: Amelia Barwise
Author-X-Name-First: Amelia
Author-X-Name-Last: Barwise
Author-Name: Vitaly Herasevich
Author-X-Name-First: Vitaly
Author-X-Name-Last: Herasevich
Author-Name: Ognjen Gajic
Author-X-Name-First: Ognjen
Author-X-Name-Last: Gajic
Author-Name: Brian Pickering
Author-X-Name-First: Brian
Author-X-Name-Last: Pickering
Author-Name: Yue Dong
Author-X-Name-First: Yue
Author-X-Name-Last: Dong
Title: A multidisciplinary approach to the development of digital twin models of critical care delivery in intensive care units
Abstract: 
 To investigate critical care delivery in intensive care units (ICUs), we propose a qualitative and quantitative coupling approach to developing an ICU digital twin model. The Systems Engineering Initiative for Patient Safety (SEIPS) 2.0 model was adapted to conceptualise the current ICU system. A hybrid simulation model was developed to characterise major care delivery processes as discrete-time events, feature patients, clinicians, and other artifacts as autonomous agents, and integrate them in the same simulation environment to capture their interactions under a variety of ICU production conditions. Electronic health record (EHR) data from a medical ICU of Mayo Clinic Rochester, Minnesota, were used to calibrate model parameters. Upon iterative refinement and validation, the model has the potential to be integrated with the hospital information system to simulate real-life events as a full-fledged digital twin of the system. It can be used as an in-silico testbed to investigate the real-time allocation of ICU resources such as medical equipment, flexible staffing, workflow change, and support decisions of patient admission, discharge, and transfer, for healthcare delivery innovation. The interdisciplinary nature of this framework demonstrates and promotes the partnership between healthcare and engineering communities to building a better delivery system.
Journal: International Journal of Production Research
Pages: 4197-4213
Issue: 13
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2022235
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2022235
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Template-Type: ReDIF-Article 1.0
# input file: catalog-resolver425669556732838229.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Manoj Dora
Author-X-Name-First: Manoj
Author-X-Name-Last: Dora
Author-Name: Ashwani Kumar
Author-X-Name-First: Ashwani
Author-X-Name-Last: Kumar
Author-Name: Sachin Kumar Mangla
Author-X-Name-First: Sachin Kumar
Author-X-Name-Last: Mangla
Author-Name: Abhay Pant
Author-X-Name-First: Abhay
Author-X-Name-Last: Pant
Author-Name: Muhammad Mustafa Kamal
Author-X-Name-First: Muhammad Mustafa
Author-X-Name-Last: Kamal
Title: Critical success factors influencing artificial intelligence adoption in food supply chains
Abstract: 
 The adoption of Artificial Intelligence (AI) in the food supply chains (FSC) can address unique challenges of food safety, quality and wastage by improving transparency and traceability. However, the technology adoption literature in FSC is still the in infancy stage, meaning little is known about the critical success factors (CSFs) that could affect the adoption of AI in FSC. Therefore, this study makes a pioneering attempt by examining the CSFs influencing the adoption of AI in the Food Supply Chain (FSC). A conceptual framework based on TOEH (Technology–Organisation–Environment–Human) theory is used to determine the CSFs influencing AI adoption in the context of Indian FSC. The rough-SWARA technique was used to rank and prioritise the CSFs for AI adoption using the relative importance weights. The results of the study indicate that technology readiness, security, privacy, customer satisfaction, perceived benefits, demand volatility, regulatory compliance, competitor pressure and information sharing among partners are the most significant CSFs for adopting AI in FSC. The findings of the study would be useful for AI technology providers, supply chain specialists and government agencies in framing appropriate policies to foster the adoption of AI in FSC the sector.
Journal: International Journal of Production Research
Pages: 4621-4640
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1959665
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1959665
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Template-Type: ReDIF-Article 1.0
# input file: catalog-resolver537833132695290306.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Juan Pablo Usuga-Cadavid
Author-X-Name-First: Juan Pablo
Author-X-Name-Last: Usuga-Cadavid
Author-Name: Samir Lamouri
Author-X-Name-First: Samir
Author-X-Name-Last: Lamouri
Author-Name: Bernard Grabot
Author-X-Name-First: Bernard
Author-X-Name-Last: Grabot
Author-Name: Arnaud Fortin
Author-X-Name-First: Arnaud
Author-X-Name-Last: Fortin
Title: Using deep learning to value free-form text data for predictive maintenance
Abstract: 
 Past maintenance logs may encapsulate meaningful data for predicting the duration of machine breakdowns, the potential causes of a problem, or the necessity to stop production to perform repair activities. These insights may be accessed using machine learning (ML). However, maintenance logs tend to have imbalanced distributions and rely on noisy unstructured text data provided by operators. Additionally, the limited interpretability of ML models results in human reluctance when accepting model predictions. Hence, this study explored the use of two recent deep learning models (CamemBERT and FlauBERT) for natural language processing (NLP) to harness unstructured data from maintenance logs. The class imbalance effect was mitigated using data-level and algorithm-level approaches. To improve interpretability, a technique called LIME was employed to interpret single predictions and to propose a method for insight extraction from several maintenance reports. Results suggest three key points: CamemBERT and FlauBERT can achieve excellent results with minimum text pre-processing and hyperparameter tuning. Second, random oversampling (ROS) generally mitigates the effect of class imbalance. However, ROS was observed to be unnecessary when performing pertinent data pre-processing. Finally, at the maintenance level, the proposed insight extraction method can provide valuable information from a set of poorly structured maintenance reports.
Journal: International Journal of Production Research
Pages: 4548-4575
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1951868
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1951868
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Template-Type: ReDIF-Article 1.0
# input file: catalog-resolver7937028058610343040.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Thanos Papadopoulos
Author-X-Name-First: Thanos
Author-X-Name-Last: Papadopoulos
Author-Name: Uthayasankar Sivarajah
Author-X-Name-First: Uthayasankar
Author-X-Name-Last: Sivarajah
Author-Name: Konstantina Spanaki
Author-X-Name-First: Konstantina
Author-X-Name-Last: Spanaki
Author-Name: Stella Despoudi
Author-X-Name-First: Stella
Author-X-Name-Last: Despoudi
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Title: Editorial: Artificial Intelligence (AI) and data sharing in manufacturing, production and operations management research
Journal: International Journal of Production Research
Pages: 4361-4364
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2010979
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2010979
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Template-Type: ReDIF-Article 1.0
# input file: catalog-resolver6794940880765785138.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Femi Olan
Author-X-Name-First: Femi
Author-X-Name-Last: Olan
Author-Name: Shaofeng Liu
Author-X-Name-First: Shaofeng
Author-X-Name-Last: Liu
Author-Name: Jana Suklan
Author-X-Name-First: Jana
Author-X-Name-Last: Suklan
Author-Name: Uchitha Jayawickrama
Author-X-Name-First: Uchitha
Author-X-Name-Last: Jayawickrama
Author-Name: Emmanuel Ogiemwonyi Arakpogun
Author-X-Name-First: Emmanuel Ogiemwonyi
Author-X-Name-Last: Arakpogun
Title: The role of Artificial Intelligence networks in sustainable supply chain finance for food and drink industry
Abstract: 
 In the last decade, food and drink supply chain management has become an important part of global operations strategy. The global food and drink industries (FDIs) is establishing supply chain operations across countries as a result of increasing demand, this expansion has created challenges in coordinating operations that connect multi-suppliers, one as such is the financial enabler for the multi-layered supply chain network. However, literature on artificial intelligence (AI) in FDIs is limited, this study explores AI theory in supply chain networks and alternative supply chain financing for the FDIs. This study proposes a new conceptual framework based on theoretical contributions identified through literature, a conceptual framework is established and further developed to a meta-framework. This study explored the set-theoretic comparative approach for data analysis, the outcomes of this research suggest that the probable contributions of supply chain networks driven by AI technologies provide a sustainable financing stream for the food and drink supply chain.
Journal: International Journal of Production Research
Pages: 4418-4433
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1915510
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1915510
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Template-Type: ReDIF-Article 1.0
# input file: catalog-resolver-2862429470949337193.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Hamed Nayernia
Author-X-Name-First: Hamed
Author-X-Name-Last: Nayernia
Author-Name: Hanna Bahemia
Author-X-Name-First: Hanna
Author-X-Name-Last: Bahemia
Author-Name: Savvas Papagiannidis
Author-X-Name-First: Savvas
Author-X-Name-Last: Papagiannidis
Title: A systematic review of the implementation of industry 4.0 from the organisational perspective
Abstract: 
 Industry 4.0 (I4.0) is a fast-evolving area of research, bringing together knowledge from multiple academic fields into creative solutions for manufacturing innovation. Despite the growing amount of published work covering a wide range of I4.0 areas, there has been relatively little research devoted to the organisational side of implementing I4.0. To address this gap, this systematic review paper used quantitative analysis by text-mining 97 articles from 2015 to 2021. The analysis identified eleven research streams, which were grouped into five levels, namely industry and firm, smart factory, data, human resources and supply chain. The research streams were then comprehensively reviewed and presented. For each stream, the paper presents a number of sub-themes and highlights important findings and areas that may require further development. We discuss three important research avenues in the organisational management literature: (1) the impact of the pandemic on the implementation of I4.0, (2) the tension between value creation and value protection during the implementation of 4.0 and (3) the relevance of a contingency approach during the implementation of I4.0.
Journal: International Journal of Production Research
Pages: 4365-4396
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2002964
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002964
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Template-Type: ReDIF-Article 1.0
# input file: catalog-resolver-7506264610655689212.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Jorge Andrés Palombarini
Author-X-Name-First: Jorge Andrés
Author-X-Name-Last: Palombarini
Author-Name: Ernesto Carlos Martínez
Author-X-Name-First: Ernesto Carlos
Author-X-Name-Last: Martínez
Title: End-to-end on-line rescheduling from Gantt chart images using deep reinforcement learning
Abstract: 
 With the advent of the socio-technical manufacturing paradigm, the way in which rescheduling decisions are taken at the shop floor has radically changed in order to guarantee highly efficient production under increasingly dynamic conditions. To cope with uncertain production environments, a drastic increase in the type and degree of automation used at the shop floor for handling unforeseen events and unplanned disturbances is required. In this work, the on-line rescheduling task is modelled as a closed-loop control problem in which an artificial autonomous agent implements a control policy generated off-line using a schedule simulator to learn schedule repair policies directly from high-dimensional sensory inputs. The rescheduling control policy is stored in a deep neural network, which is used to select repair actions in order to achieve a small set of repaired goal states. The rescheduling agent is trained using Proximal Policy Optimisation based on a wide variety of simulated transitions between schedule states using colour-rich Gantt chart images and negligible prior knowledge as inputs. An industrial example is discussed to highlight that the proposed approach enables end-to-end deep learning of successful rescheduling policies to encode task-specific control knowledge that can be understood by human experts.
Journal: International Journal of Production Research
Pages: 4434-4463
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.2002963
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002963
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# input file: catalog-resolver1643812565585705635.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Elango Murugappan
Author-X-Name-First: Elango
Author-X-Name-Last: Murugappan
Author-Name: Nachiappan Subramanian
Author-X-Name-First: Nachiappan
Author-X-Name-Last: Subramanian
Author-Name: Shams Rahman
Author-X-Name-First: Shams
Author-X-Name-Last: Rahman
Author-Name: Mark Goh
Author-X-Name-First: Mark
Author-X-Name-Last: Goh
Author-Name: Hing Kai Chan
Author-X-Name-First: Hing Kai
Author-X-Name-Last: Chan
Title: Performance analysis of clustering methods for balanced multi-robot task allocations
Abstract: 
 This paper models the Multi-Robot Task Allocation (MRTA) problem with a balance constraint to improve the utilisation (completion time) of the robots. Our balancing constraint attempts to minimise the travel distance difference among the robots as well as allocates an equal set of tasks to these robots. The clustering-based approach is employed to solve the Balanced Multi-Robot Task Allocation (BMRTA) problem for two principal reasons. That is, this approach clusters given tasks into groups using various clustering techniques for each robot and sequences the route for each robot using the travelling salesman problem (TSP) conhull algorithm. This work analyses the suitability and performance of the clustering techniques with respect to the balancing criteria using a benchmark dataset. Our findings suggest that K-means clustering is the most suitable for the solving BMRTA problem with complex topologies and it is scalable to deal with any number of tasks and robots compared with Gaussian Mixtures Models (GMM) and hierarchical clustering methods.
Journal: International Journal of Production Research
Pages: 4576-4591
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1955994
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1955994
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# input file: catalog-resolver-1559016112758779337.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Naoum Tsolakis
Author-X-Name-First: Naoum
Author-X-Name-Last: Tsolakis
Author-Name: Dimitris Zissis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Zissis
Author-Name: Spiros Papaefthimiou
Author-X-Name-First: Spiros
Author-X-Name-Last: Papaefthimiou
Author-Name: Nikolaos Korfiatis
Author-X-Name-First: Nikolaos
Author-X-Name-Last: Korfiatis
Title: Towards AI driven environmental sustainability: an application of automated logistics in container port terminals
Abstract: 
 Artificial intelligence and data analytics capabilities have enabled the introduction of automation, such as robotics and Automated Guided Vehicles (AGVs), across different sectors of the production spectrum which successively has profound implications for operational efficiency and productivity. However, the environmental sustainability implications of such innovations have not been yet extensively addressed in the extant literature. This study evaluates the use of AGVs in container terminals by investigating the environmental sustainability gains that arise from the adoption of artificial intelligence and automation for shoreside operations at freight ports. Through a comprehensive literature review, we reveal this research gap across the use of artificial intelligence and decision support systems, as well as optimisation models. A real-world container terminal is used, as a case study in a simulation environment, on Europe’s fastest-growing container port (Piraeus), to quantify the environmental benefits related to routing scenarios via different types of AGVs. Our study contributes to the cross-section of operations management and artificial intelligence literature by articulating design principles to inform effective digital technology interventions at non-automated port terminals, both at operational and management levels.
Journal: International Journal of Production Research
Pages: 4508-4528
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1914355
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1914355
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# input file: catalog-resolver5360765073493917654.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Abdulrahman Al-Surmi
Author-X-Name-First: Abdulrahman
Author-X-Name-Last: Al-Surmi
Author-Name: Mahdi Bashiri
Author-X-Name-First: Mahdi
Author-X-Name-Last: Bashiri
Author-Name: Ioannis Koliousis
Author-X-Name-First: Ioannis
Author-X-Name-Last: Koliousis
Title: AI based decision making: combining strategies to improve operational performance
Abstract: 
 This study investigates the strategic alignment between marketing and information technology (IT) strategies and provides production and operations decision makers a model for improving operational performance. Based on a comprehensive literature review, the combined strategies were used to develop a novel decision-making framework. The hypothesised relationships of an SEM model are validated with data collected from 242 managers from various industries. An artificial intelligence (AI)–based method is developed using artificial neural networks (ANN) feeding into a decision-making framework which explores the optimality of the combined strategies. The results indicate that (a) IT strategy is positively mediated by marketing strategy on performance and (b) the organisational structure moderates the mediation of marketing strategy on performance. The analysis confirms that the extracted strategies based on the proposed framework have superior performance compared to existing strategies. This paper contributes to the literature by conceptualising and empirically testing the mediation role of marketing strategy on IT strategy, performance and operational decision-making. The use of a novel three-phase decision-making framework which uses AI processes improves operational efficiency, increases insights and enhances the decision accuracy of complex problems at the strategic level in industries such as manufacturing. It could help operations executives to apply effective decisions.
Journal: International Journal of Production Research
Pages: 4464-4486
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1966540
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1966540
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# input file: catalog-resolver-627907881617478315.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Trevor Cadden
Author-X-Name-First: Trevor
Author-X-Name-Last: Cadden
Author-Name: Denis Dennehy
Author-X-Name-First: Denis
Author-X-Name-Last: Dennehy
Author-Name: Matti Mantymaki
Author-X-Name-First: Matti
Author-X-Name-Last: Mantymaki
Author-Name: Raymond Treacy
Author-X-Name-First: Raymond
Author-X-Name-Last: Treacy
Title: Understanding the influential and mediating role of cultural enablers of AI integration to supply chain
Abstract: 
 Artificial Intelligence (AI) has been claimed to offer transformational power across industries and sectors. To date, research has largely focused on the technical characteristics of AI and its influence on organisational capabilities. Despite the hype surrounding AI, there is a scarcity of rigorous research that examines the organisational and behavioural factors that foster AI integration in supply chains is lacking. This quantitative study addresses this gap in knowledge by developing a research hypothesis that examines the relationships between supply chain culture and AI. We extend the generalisability of culture to provide novel insights about AI-driven supply chains that have not been reported in previous studies. The findings demonstrate the influential role that cultural enablers have on the successful integration of AI technologies in supply chains, which has implications for operations and supply chain management.
Journal: International Journal of Production Research
Pages: 4592-4620
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1946614
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1946614
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# input file: catalog-resolver-917249260367881809.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Amine Belhadi
Author-X-Name-First: Amine
Author-X-Name-Last: Belhadi
Author-Name: Sachin Kamble
Author-X-Name-First: Sachin
Author-X-Name-Last: Kamble
Author-Name: Samuel Fosso Wamba
Author-X-Name-First: Samuel
Author-X-Name-Last: Fosso Wamba
Author-Name: Maciel M. Queiroz
Author-X-Name-First: Maciel M.
Author-X-Name-Last: Queiroz
Title: Building supply-chain resilience: an artificial intelligence-based technique and decision-making framework
Abstract: 
 Artificial Intelligence (AI) offers a promising solution for building and promoting more resilient supply chains. However, the literature is highly dispersed regarding the application of AI in supply-chain management. The literature to date lacks a decision-making framework for identifying and applying powerful AI techniques to build supply-chain resilience (SCRes), curbing advances in research and practice on this interesting interface. In this paper, we propose an integrated Multi-criteria decision-making (MCDM) technique powered by AI-based algorithms such as Fuzzy systems, Wavelet Neural Networks (WNN) and Evaluation based on Distance from Average Solution (EDAS) to identify patterns in AI techniques for developing different SCRes strategies. The analysis was informed by data collected from 479 manufacturing companies to determine the most significant AI applications used for SCRes. The findings show that fuzzy logic programming, machine learning big data, and agent-based systems are the most promising techniques used to promote SCRes strategies. The study findings support decision-makers by providing an integrated decision-making framework to guide practitioners in AI deployment for building SCRes.
Journal: International Journal of Production Research
Pages: 4487-4507
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1950935
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1950935
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# input file: catalog-resolver-6708594226265846131.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Dimitrios Bechtsis
Author-X-Name-First: Dimitrios
Author-X-Name-Last: Bechtsis
Author-Name: Naoum Tsolakis
Author-X-Name-First: Naoum
Author-X-Name-Last: Tsolakis
Author-Name: Eleftherios Iakovou
Author-X-Name-First: Eleftherios
Author-X-Name-Last: Iakovou
Author-Name: Dimitrios Vlachos
Author-X-Name-First: Dimitrios
Author-X-Name-Last: Vlachos
Title: Data-driven secure, resilient and sustainable supply chains: gaps, opportunities, and a new generalised data sharing and data monetisation framework
Abstract: 
 The increasing exposure of global supply chains to severe disruptions such as the ones related to the COVID-19 pandemic, clearly demonstrated the need for novel data-driven risk management paradigms that monetise data from internal and external stakeholders to support supply chain security, resilience, and sustainability. We first motivate the challenges that supply chains are facing under the new realities. We then provide a critical taxonomy of the relevant literature and identify gaps which include: (i) the impact of security on supply chain operations; (ii) cost effective resiliency strategies and practices; and (iii) the social and labour dimensions of sustainability. We then propose a new generalised framework that encompasses all the identified challenges, gaps in literature and in practice, and opportunities in supply chain management research. The proposed framework is validated through a real-world case study of the organic food supply chain. This validation further highlights the need for data-driven digital technologies that enable data collection and management, secure storage and effective data processing towards data monetisation for supply chain security, cost-competitive resilience, and sustainability across end-to-end operations.
Journal: International Journal of Production Research
Pages: 4397-4417
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1957506
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1957506
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# input file: catalog-resolver-4367944114666115879.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220713T202513 git hash: 99d3863004
Author-Name: Arunmozhi Manimuthu
Author-X-Name-First: Arunmozhi
Author-X-Name-Last: Manimuthu
Author-Name: V. G. Venkatesh
Author-X-Name-First: V. G.
Author-X-Name-Last: Venkatesh
Author-Name: V. Raja Sreedharan
Author-X-Name-First: V.
Author-X-Name-Last: Raja Sreedharan
Author-Name: Venkatesh Mani
Author-X-Name-First: Venkatesh
Author-X-Name-Last: Mani
Title: Modelling and analysis of artificial intelligence for commercial vehicle assembly process in VUCA world: a case study
Abstract: 
 Real-time monitoring, is  now the integral component in smart manufacturing with the rapid application of Artificial Intelligence (AI) in manufacturing. Machine Learning (ML) algorithms and  Internet of things (IoT) make the volatility, uncertainty, complexity, and ambiguity world (VUCA) more reliable and resilient with the stable industrial environment. In this study, two machine learning algorithms such as K-mean clustering and support vector, are used in combination with IoT-enabled embedded devices to design, deploy and test the effectiveness of the vehicle assembly process in the VUCA context. To accomplish this, the design includes both real-time data and training vector data, which were collected from IoT-enabled devices and evaluated using ML algorithms leading to the novel element called Smart Safe Factor (SSF), a critical threshold indicator that helps in limiting different units in assembly line-ups from excess wastages and energy losses in real-time. Test results highlight the impact of AI in enhancing the productivity and efficiency. Using SSF, 21.84% of energy is saved during the entire assembly process and 8% of excess stocks in storage have been curtailed for monetary benefits. This study deliberates the applications of AI and ML algorithms in a Vehicle Assembly (VA) model, connecting critical parameters such as cost, performance, energy, and productivity.
Journal: International Journal of Production Research
Pages: 4529-4547
Issue: 14
Volume: 60
Year: 2022
Month: 07
X-DOI: 10.1080/00207543.2021.1910361
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1910361
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# input file: TPRS_A_1936262_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Mei Li
Author-X-Name-First: Mei
Author-X-Name-Last: Li
Author-Name: Zixian Liu
Author-X-Name-First: Zixian
Author-X-Name-Last: Liu
Author-Name: Yiliu Liu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Liu
Author-Name: Xiaopeng Li
Author-X-Name-First: Xiaopeng
Author-X-Name-Last: Li
Author-Name: Ling Lv
Author-X-Name-First: Ling
Author-X-Name-Last: Lv
Title: Optimal follow-up policies for monitoring chronic diseases based on virtual age
Abstract: 
 Follow-up policies following treatment are indispensable and effective in reducing the number of complications of chronic diseases, and hence the cost of treating complications, but bring additional follow-up cost inevitably. This paper introduces the virtual age method to measure the effect of follow-up on the patient’s risk of developing a complication, and further proposes a mixed integer nonlinear programming model to develop the optimal periodic follow-up policies from a cost perspective. By means of the proposed model, the optimal timing and type of follow-up checkups for heterogeneous patients can be derived, achieving a tradeoff between costs of treating complications and follow-up. A case study of pediatric type 1 diabetes mellitus patients is presented to illustrate the applicability of the proposed method and analyse the impacts of significant input parameters on the optimal model solutions. The findings form the basis to design flexible and effective follow-up policies for monitoring patients with chronic diseases.
Journal: International Journal of Production Research
Pages: 4712-4726
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1936262
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1936262
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# input file: TPRS_A_1934745_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Young Woong Park
Author-X-Name-First: Young Woong
Author-X-Name-Last: Park
Author-Name: Jennifer Blackhurst
Author-X-Name-First: Jennifer
Author-X-Name-Last: Blackhurst
Author-Name: Chinju Paul
Author-X-Name-First: Chinju
Author-X-Name-Last: Paul
Author-Name: Kevin P. Scheibe
Author-X-Name-First: Kevin P.
Author-X-Name-Last: Scheibe
Title: An analysis of the ripple effect for disruptions occurring in circular flows of a supply chain network*
Abstract: 
 This paper examines the ripple effect in supply chains due to circular flows embedded in supply chain design. Although supply chains are complex and nonlinear, circular flows exist in real-world supply chains but are often unknown or hidden to supply chain managers. These circular flows exist when a Tier 2 supplier is also a Tier 3 (or higher) supplier in the supply chain network. Additionally, a circular network can occur when a supplier is also a customer in the same network. In the presence of these types of supply chain network structures, supply chains may experience a ripple effect (or disruption propagation) in which disruptions impact supply chain performance. Using a real-world supply chain structure, we examine the effect of circular flows on the ripple effect and identify how this influences the supply chain’s resilience to disruptions. We offer managers and researchers insights that improve the understanding of how circular flows exacerbate the ripple effect.
Journal: International Journal of Production Research
Pages: 4693-4711
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1934745
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1934745
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# input file: TPRS_A_1936264_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Peng Yang
Author-X-Name-First: Peng
Author-X-Name-Last: Yang
Author-Name: Guang Jin
Author-X-Name-First: Guang
Author-X-Name-Last: Jin
Author-Name: Guofang Duan
Author-X-Name-First: Guofang
Author-X-Name-Last: Duan
Title: Modelling and analysis for multi-deep compact robotic mobile fulfilment system
Abstract: 
 With high efficiency and good scalability, Robotic Mobile Fulfilment Systems (RMFS) are increasingly applied in various warehouses, especially the e-commerce warehouses with rigid order completion time. RMFS requires less workers and provide more punctual service for customers. The existing literature on RMFS is based on single-deep non-compact layout. As land supply is limited and expensive in urban area, it’s essential to consider compact storage in RMFS. This paper is the first to model and evaluate the multi-deep compact RMFS. We develop a semi-open queueing network (SOQN) model to characterise the multi-deep compact RMFS and solve it by Approximate Mean Value Analysis (AMVA). The obtained approximate analytic solutions of system throughput, robot utilisation, and queue length were verified and assessed through simulations. The numerical experiments investigated the effects of different configuration of the lane depth, number of picking aisles, arrangement of picking stations and the number of robots on performance. Our research can provide useful guidelines for warehouse planners and managers for designing and operating multi-deep compact RMFS.
Journal: International Journal of Production Research
Pages: 4727-4742
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1936264
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1936264
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# input file: TPRS_A_1937747_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: D. E. Sparrow
Author-X-Name-First: D. E.
Author-X-Name-Last: Sparrow
Author-Name: K. Kruger
Author-X-Name-First: K.
Author-X-Name-Last: Kruger
Author-Name: A. H. Basson
Author-X-Name-First: A. H.
Author-X-Name-Last: Basson
Title: An architecture to facilitate the integration of human workers in Industry 4.0 environments
Abstract: 
 While Industry 4.0 research has predominantly focussed on the connection of machines and digital systems and solutions, it is important to consider the role of human workers within the envisaged Industry 4.0 environments. This paper presents the concept of a digital administration shell to support the integration of humans in Industry 4.0 environments and an architecture for the development of such an administration shell. The Biography-Attributes-Schedule-Execution (BASE) architecture builds on holonic systems principles and is guided by the requirements and responsibilities of the Resource Holon, as developed in the Holonic Manufacturing Systems paradigm. The functionality and value of the BASE architecture administration shell is demonstrated by means of a case study implementation.
Journal: International Journal of Production Research
Pages: 4778-4796
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1937747
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1937747
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# input file: TPRS_A_1937748_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Wenbo Wu
Author-X-Name-First: Wenbo
Author-X-Name-Last: Wu
Author-Name: Zhengdong Huang
Author-X-Name-First: Zhengdong
Author-X-Name-Last: Huang
Author-Name: Jiani Zeng
Author-X-Name-First: Jiani
Author-X-Name-Last: Zeng
Author-Name: Kuan Fan
Author-X-Name-First: Kuan
Author-X-Name-Last: Fan
Title: A decision-making method for assembly sequence planning with dynamic resources
Abstract: 
 With the advent of mass customisation, solving the assembly sequence planning (ASP) problem not only involves a non-convex optimisation problem that is hard to solve but also requires a high-speed response to the changes of assembly resources. This paper proposes a deep reinforcement learning (DRL) approach for the ASP problem, aiming at promoting the response speed by exploiting the reusability and expandability of past decision-making experiences. First, the connector-based ASP problem is described in a matrix manner, and its objective function is set to minimise assembly cost under the precedence constraints. Secondly, an instance generation algorithm is developed for policy training, and a mask algorithm is adopted to screen out impracticable assembly operations in each decision-making step. Then, the Monte Carlo sampling method is used to evaluate the ASP policy. The policy is learned from an actor–criticbased DRL algorithm, which contains two networks, policy network and evaluation network. Next, the network structures are introduced and they are trained by a mini-batch algorithm. Finally, four cases are studied to validate this method, and the results are discussed. It is demonstrated that the proposed method can solve the ASP problem accurately and efficiently in the environment with dynamic resource changes.
Journal: International Journal of Production Research
Pages: 4797-4816
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1937748
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1937748
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# input file: TPRS_A_1912427_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Yuqi Li
Author-X-Name-First: Yuqi
Author-X-Name-Last: Li
Author-Name: Desheng Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Wu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Optimal trade credit coordination policy in dual-channel supply chain with consumer transfer
Abstract: 
 The boom in online sales has inspired the enthusiasm of manufacturers to include their own online sale channel with the retailer’s offline channel. This paper investigates the impact of consumer transfer in a capital-constraint dual-channel supply chain and examines the optimal operational decision by considering a Stackelberg game. We capture the trade credit coordination mechanism of the supply chain facing with stochastic demand. The results show that trade credit contract would alleviate financial pressure of the capital-constraint retailer and achieve coordination in the dual-channel supply chain. Besides, the adoption of trade credit stimulates the ordering behaviour of retailers. However, by using trade credit, the default risk increases for the capital-constraint retailer compared to the retailer with sufficient capital. The manufacturer shares the risk with the retailer by trade credit in dual-channel supply chain. Furthermore, the effects of consumer transfer rates on the setting of the trade credit parameters are also presented in this paper.
Journal: International Journal of Production Research
Pages: 4641-4653
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1912427
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1912427
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# input file: TPRS_A_1939454_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: M. S. Shalique
Author-X-Name-First: M. S.
Author-X-Name-Last: Shalique
Author-Name: Sidhartha S. Padhi
Author-X-Name-First: Sidhartha S.
Author-X-Name-Last: Padhi
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Author-Name: Rupesh K. Pati
Author-X-Name-First: Rupesh K.
Author-X-Name-Last: Pati
Title: Adoption of symbolic versus substantive sustainability practices by lower-tier suppliers: a behavioural view
Abstract: 
 Buying firms adopt various governance mechanisms to ensure sustainability compliance among upstream suppliers. While, certification is the most popular governance mechanism used worldwide, mounting evidence indicates that there is an incongruity in sustainability efforts between what is declared by supplier firms and their actual practices. Our empirical analysis of sustainable cocoa suppliers in Kerala (a state in South India) indicate that behavioural characteristics of suppliers, specifically their attitude towards risk and ambiguity can be used to assess suppliers’ tendency to adopt symbolic versus substantive sustainability postures. Risk aversion and ambiguity aversion were found to predict the sustainability posture of substantive (over symbolic) sustainability practices. Also, firm size and collaboration intensity played a significant role in supplier sustainability behaviour. The findings have important implications for academic research on sustainability, and policy implications for agencies charged with compliance with sustainability standards and guidelines. Finally, our study is beneficial for practicing managers who find it difficult to monitor sustainability compliance with respect to their supply base.
Journal: International Journal of Production Research
Pages: 4817-4844
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1939454
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1939454
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# input file: TPRS_A_1939455_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Stephen Mahar
Author-X-Name-First: Stephen
Author-X-Name-Last: Mahar
Author-Name: Sachin Modi
Author-X-Name-First: Sachin
Author-X-Name-Last: Modi
Author-Name: Peter A. Salzarulo
Author-X-Name-First: Peter A.
Author-X-Name-Last: Salzarulo
Title: Appreciating how your bread is buttered: improving online order allocation for cross-channel retailers
Abstract: 
 Existing research has considered how pure online retailers can optimise the allocation of fulfilment responsibilities for online sales. However, the fulfilment policies used by pure online retailers may be suboptimal for their dual-channel counterparts. This paper considers online order allocation policies for cross-channel retail/e-tail organisations which utilise buy online, ship from store (BOSS) fulfilment. Specifically, we develop and evaluate a policy for allocating fulfilment responsibilities for a set of multiproduct online orders across a retailer’s store locations when the retailer also faces in-store demand for the same products. Further, our model incorporates carrier rate schedules into the allocation decision and adjusts allocations based on current and forecasted inventory positions at the stores. As such, the model determines fulfilment responsibilities by balancing quantity discounted carrier shipment costs, fixed costs of handling/packing orders, and expected inventory positions. Computational results highlight the extent to which our policy outperforms single-channel policies without in-store inventory considerations. We find that undertaking BOSS without tailoring online order allocation to the cross-channel setting accommodates online fulfilment at the expense of in-store performance. Conversely, consideration of in-store inventories in the order allocation decision enables a cross-channel retailer utilising BOSS to simultaneously improve service levels and reduce inventory.
Journal: International Journal of Production Research
Pages: 4845-4867
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1939455
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1939455
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# input file: TPRS_A_1937745_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: David Müller
Author-X-Name-First: David
Author-X-Name-Last: Müller
Author-Name: Dominik Kress
Author-X-Name-First: Dominik
Author-X-Name-Last: Kress
Title: Filter-and-fan approaches for scheduling flexible job shops under workforce constraints
Abstract: 
 This paper addresses a flexible job shop scheduling problem that takes account of workforce constraints and aims to minimise the makespan. The former constraints ensure that eligible workers that operate the machines and may be heterogeneously qualified, are assigned to the machines during the processing of operations. We develop different variants of filter-and-fan (F&F) based heuristic solution approaches that combine a local search procedure with a tree search procedure. The former procedure is used to obtain local optima, while the latter procedure generates compound transitions in order to explore larger neighbourhoods. In order to be able to adapt neighbourhood structures that have formerly shown to perform well when workforce restrictions are not considered, we decompose the problem into two components for decisions on machine allocation and sequencing and decisions on worker assignment, respectively. Based on this idea, we develop multiple definitions of neighbourhoods that are successively locked and unlocked during runtime of the F&F heuristics. In a computational study, we show that our solution approaches are competitive when compared with the use of a standard constraint programming solver and that they outperform state-of-the-art heuristic approaches on average.
Journal: International Journal of Production Research
Pages: 4743-4765
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1937745
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1937745
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# input file: TPRS_A_1934590_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Yuyu Liu
Author-X-Name-First: Yuyu
Author-X-Name-Last: Liu
Author-Name: Hu Yu
Author-X-Name-First: Hu
Author-X-Name-Last: Yu
Title: Optimal two-class-based storage policy in an AS/RS with two depots at opposite ends of the aisle
Abstract: 
 Although automated storage/retrieval systems (AS/RSs) with two depots at opposite ends of each aisle (TD-AS/RSs) have been adopted in I-shaped warehouses (one of the three typical warehouse layouts), class-based storage policy has surprisingly not been investigated in TD-AS/RSs. This paper studies TD-AS/RSs with two storage zones, aiming to determine the optimal first storage zone that minimises the S/R machine’s expected travel time. We first formulate an expected travel time model. The analysis is then performed for two situations: (1) the ratio between the number of storage and total requests (Ratio-ST) is constant and (2) the Ratio-ST changes with time but follows a probability distribution. For the first situation, utilising proposed properties, an efficient optimal search-based algorithm (i.e. Algorithm 1) is developed. The results show that the proposed storage policy can improve system performance by up to about 60% and 40%, respectively, compared with two policies used in practice. Contrary to the literature results, our results indicate that the single command cycle performs better than the dual command cycle in the TD-AS/RS. For the second situation, an algorithm based on Algorithm 1 is developed. A case study using two real-world datasets confirms that our policy outperforms practically used policies in this situation.
Journal: International Journal of Production Research
Pages: 4668-4692
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1934590
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1934590
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# input file: TPRS_A_1937746_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Ming Zhang
Author-X-Name-First: Ming
Author-X-Name-Last: Zhang
Author-Name: Chunquan Li
Author-X-Name-First: Chunquan
Author-X-Name-Last: Li
Author-Name: Yuling Shang
Author-X-Name-First: Yuling
Author-X-Name-Last: Shang
Author-Name: Hongyan Huang
Author-X-Name-First: Hongyan
Author-X-Name-Last: Huang
Author-Name: Wangchun Zhu
Author-X-Name-First: Wangchun
Author-X-Name-Last: Zhu
Author-Name: Yujia Liu
Author-X-Name-First: Yujia
Author-X-Name-Last: Liu
Title: A task scheduling model integrating micro-breaks for optimisation of job-cycle time in human-robot collaborative assembly cells
Abstract: 
 Human-Robot Collaboration, whereby human worker and robot perform tasks jointly, is becoming the new frontier in industry production. Unlike robots, continuous work leads to an accumulation of human fatigue, which is the main cause of decreased efficiency and deterioration of health. Characteristic differences between human and robot bring challenges to collaboration task scheduling. In this paper, we studied the task scheduling of a human-robot collaboration assembly cell to achieve a trade-off between job cycle and human fatigue. A task scheduling model integrated with micro-breaks inside job cycles was proposed to avoid human fatigue accumulation by taking advantage of the human-robot collaboration characteristics. Furthermore, the optimisation of task scheduling by taking the job cycle as the objective function and maximum human fatigue as a constraint was solved. The developed method is studied on a cable assembly inspired by an industry case. The results of the case study are presented to indicate the validity and practicability of the proposed model. It suggests that compared with the model of placing rest breaks between job cycles, the proposed model outperforms in job-cycle performance in most cases. Finally, there are some insights on the HRCAC which are obtained from the results of the case study.
Journal: International Journal of Production Research
Pages: 4766-4777
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1937746
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1937746
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# input file: TPRS_A_1934589_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Rico Walter
Author-X-Name-First: Rico
Author-X-Name-Last: Walter
Author-Name: Philipp Schulze
Author-X-Name-First: Philipp
Author-X-Name-Last: Schulze
Title: On the performance of task-oriented branch-and-bound algorithms for workload smoothing in simple assembly line balancing
Abstract: 
 Smoothing the workloads among the stations of an already installed assembly line is one of the major objectives in assembly line (re-)balancing. In order to find a feasible task-station assignment that distributes the total workload as equal as possible, two exact task-oriented branch-and-bound algorithms have recently been proposed. In this paper, we systematically analyse their effectiveness in solving the workload smoothing problem on simple assembly lines. In our experiments, we also examine the performance of a state-of-the-art mathematical programming solver and a ‘combined’ exact branch-and-bound procedure that integrates components of the two algorithms from the literature. In terms of theory, we show the equivalence of two recently developed local lower bounding arguments and suggest a slight improvement of the bound. We also propose an enhanced feasibility test.
Journal: International Journal of Production Research
Pages: 4654-4667
Issue: 15
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1934589
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1934589
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# input file: TPRS_A_1946613_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Simranjeet S. Chadha
Author-X-Name-First: Simranjeet S.
Author-X-Name-Last: Chadha
Author-Name: M. Ali Ülkü
Author-X-Name-First: M. Ali
Author-X-Name-Last: Ülkü
Author-Name: Uday Venkatadri
Author-X-Name-First: Uday
Author-X-Name-Last: Venkatadri
Title: Freight delivery in a Physical Internet Supply Chain: an applied optimisation model with peddling and shipment consolidation
Abstract: 
 The delivery of goods (freight) accounts for the major cost and emissions in logistics systems worldwide. The effective management of the supply chain requires logistical efficiency and sustainability. Several logistics performance measurements such as distances driven and fuel efficiency are also indicators of sustainability. As an emerging paradigm, the Physical Internet (PI) addresses logistical, societal, and sustainability goals. However, the question remains whether some aspects of logistical efficiency in traditional logistics could be incorporated into the PI paradigm. To this effect, we examine how peddling, a consolidation strategy in traditional logistics, can enhance PI supply chain. Specifically, we formulate optimisation models and study the case of a Mexican automotive supply chain from both the PI and traditional logistics perspectives by comparing three different configurations; namely, Model P built on PI, Model S based on conventional standard peddling, and Model H, a hybrid. The hybrid Model H is optimised in a two-phase solution framework. We show via the case of a Mexican automotive supply chain that Model H outperforms others on average distance travelled and truck utilisation. Thereby, it is concluded that appropriate peddling and shipment consolidation policies may enhance PI supply chain logistics performance.
Journal: International Journal of Production Research
Pages: 4995-5011
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1946613
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1946613
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# input file: TPRS_A_1943035_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Faijun Nahar Mim
Author-X-Name-First: Faijun Nahar
Author-X-Name-Last: Mim
Author-Name: Michael B. C. Khoo
Author-X-Name-First: Michael B. C.
Author-X-Name-Last: Khoo
Author-Name: Sajal Saha
Author-X-Name-First: Sajal
Author-X-Name-Last: Saha
Author-Name: Philippe Castagliola
Author-X-Name-First: Philippe
Author-X-Name-Last: Castagliola
Title: Revised triple sampling control charts for the mean with known and estimated process parameters
Abstract: 
 The primary aim of this research is to propose a revised triple sampling (TS) 
 $\bar{X} $X¯ chart, where the derivations of new formulae for computing the average run length of the triple sampling (TS) 
 $\bar{X} $X¯ chart correctly are provided. The secondary aim is to develop the revised TS 
 $\bar{X} $X¯ chart with estimated process parameters. The revised TS 
 $\bar{X} $X¯ charts are compared with the double sampling (DS) 
 $\bar{X} $X¯, two stage adaptive sample size (AS2) 
 $\bar{X} $X¯ and three stage adaptive sample size (AS3) 
 $\bar{X} $X¯ charts when process parameters are known and estimated using the average run length (ARL), average number of observations to signal (ANOS), average of the average run lengths (AARL), standard deviation of the average run lengths (SDARL), average of the average number of observations to signal (AANOS) and standard deviation of the average number of observations to signal (SDANOS) criteria, where the revised TS 
 $\bar{X} $X¯ charts are found to be superior. Additionally, a table giving the minimum number of Phase-I samples for estimating the process mean so that the revised TS 
 $\bar{X} $X¯ chart with estimated process parameters has the desired in-control AARL and AANOS performances is provided.
Journal: International Journal of Production Research
Pages: 4911-4935
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1943035
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1943035
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# input file: TPRS_A_1948136_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Milad Baghersad
Author-X-Name-First: Milad
Author-X-Name-Last: Baghersad
Author-Name: Christopher W. Zobel
Author-X-Name-First: Christopher W.
Author-X-Name-Last: Zobel
Author-Name: Paul Benjamin Lowry
Author-X-Name-First: Paul Benjamin
Author-X-Name-Last: Lowry
Author-Name: Sutirtha Chatterjee
Author-X-Name-First: Sutirtha
Author-X-Name-Last: Chatterjee
Title: The roles of prior experience and the location on the severity of supply chain disruptions
Abstract: 
 This study examines relationships between the location of supply chain disruptions (SCDs) within the supply chain, a firm’s experience with SCDs, and the disruption severity. Using organisational learning theory, we propose that an organisation’s prior experience with SCDs will reduce the negative influence of future disruptions. However, the location of disruption occurrence (internal to the firm vs. external to the firm) also plays a vital role in the severity of future disruptions. We consider two measures of SCD severity to quantify the extent of negative influence on firms: (1) the initial loss of return on assets (ROA) and (2) the total loss of ROA over time. We empirically evaluate the performance of 262 publicly traded U.S. firms that experienced an SCD. Our study shows that the influence of internal and external SCDs on firms can be different when firms do and do not have experience with similar events. More specifically, the results show that when firms have not experienced a similar event in the past, internal SCDs are associated with a higher disruption severity than are external SCDs. The results also show that prior experience significantly decreases the disruption severity suffered by firms after internal SCDs.
Journal: International Journal of Production Research
Pages: 5051-5070
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1948136
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1948136
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# input file: TPRS_A_1948135_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Md Shahriar Jahan Hossain
Author-X-Name-First: Md Shahriar Jahan
Author-X-Name-Last: Hossain
Author-Name: Bhaba R. Sarker
Author-X-Name-First: Bhaba R.
Author-X-Name-Last: Sarker
Title: Inventory policy and magazine reloading schedule optimisation for cutting tools in pipe manufacturing
Abstract: 
 In a steel pipe manufacturing industry, several machining centres are used for different purposes, where tool magazines speed up the tool exchange and machine setup. Early tool replacement incurs unutilised tool lives, leading to additional tool purchase. On the other hand, delays in tool replacement may result in sudden tool failure and machine breakdown. A multiple tool holding facility in a tool magazine provides a good opportunity to reduce the number of magazine reloading. However, an increased magazine size eventually leads to an increase in the inventory and operating cost for the tool magazine. To trade-off between the stated conflicting objectives, a non-linear mixed-integer programming problem is formulated to minimise the total cost for cutting tools. The problem is solved both optimally and heuristically to find an appropriate combination of tool ordering size, magazine size and reload timing. The throughput rate is observed to improve when an optimal size of tool magazine is installed. The sensitivity analyses are done to investigate the influence of different parameter(s) on the optimum solution.
Journal: International Journal of Production Research
Pages: 5029-5050
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1948135
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1948135
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# input file: TPRS_A_1946193_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: M. Mahmoodjanloo
Author-X-Name-First: M.
Author-X-Name-Last: Mahmoodjanloo
Author-Name: R. Tavakkoli-Moghaddama
Author-X-Name-First: R.
Author-X-Name-Last: Tavakkoli-Moghaddama
Author-Name: A. Baboli
Author-X-Name-First: A.
Author-X-Name-Last: Baboli
Author-Name: A. Bozorgi-Amiri
Author-X-Name-First: A.
Author-X-Name-Last: Bozorgi-Amiri
Title: Distributed job-shop rescheduling problem considering reconfigurability of machines: a self-adaptive hybrid equilibrium optimiser
Abstract: 
 The recent trend of globalisation of the economy has been accelerated thanks to emerging new communication technologies. This forces some companies to be adapted to rapidly changing market requirements utilising a multi-factory production network. Job scheduling in such a distributed manufacturing system, is significantly complicated especially in the presence of dynamic events. Furthermore, production systems need to be flexible to timely react to the imposed changes. Hence, reconfigurable machine tools (RMTs) can be used as a resource for flexibility in manufacturing systems. This paper deals with a distributed job-shop rescheduling problem, in which the facilities benefit from reconfigurable machines. Firstly, the problem is mathematically formulated to minimise total weighted lateness in a static state. Then, the dynamic version is extent based on a designed conceptual framework of rescheduling module to update the current schedule. Since the problem is NP-hard, a self-adaptive hybrid equilibrium optimiser algorithm is proposed. The experiments show that the proposed EO algorithm is extremely efficient. Finally, a simulation-optimisation model is developed to evaluate the performance of the manufacturing system facing stochastic arriving jobs. The obtained results show that the production system can be very flexible relying on its distributed facilities and reconfigurable machines.
Journal: International Journal of Production Research
Pages: 4973-4994
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1946193
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1946193
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# input file: TPRS_A_1950934_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Dong Li
Author-X-Name-First: Dong
Author-X-Name-Last: Li
Author-Name: Nishant Mishra
Author-X-Name-First: Nishant
Author-X-Name-Last: Mishra
Title: The impact of parts obsolescence on contracts for durable goods with after-sales service
Abstract: 
 High-quality product support is vital for production, because utility can only be generated by working equipment and system downtime can cause serious consequences. Thus, the suppliers are often required to provide efficient product maintenance and repair services for customers. Component obsolescence is a challenging factor for spare parts management which affects the overall system performance. In this paper, we build a game-theoretic model to study joint contracting on product order quantity and after-sales service in a B2B supply chain, where spare part availability is affected by obsolescence risk, and the after-sales service is operated under the warranty and transaction-based contracts (W&T) and the performance-based contracts (PBC). Our model provides advice for practitioners on how to choose a service contract type: Given a low (high) cost of lifetime-buy of parts, W&T can lead to a higher (lower) supply chain profit than PBC when the warranty period is sufficiently long. Furthermore, we find that PBC can result in higher product availability; however, this may be achieved by overinvestment in spare parts when the supplier is penalised on the buyer's lost revenue, and in such a setting the buyer may order fewer products, which leads to lower profits for the supplier.
Journal: International Journal of Production Research
Pages: 5087-5107
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1950934
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1950934
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# input file: TPRS_A_1944688_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Mohammad Belgasem Elaradi
Author-X-Name-First: Mohammad Belgasem
Author-X-Name-Last: Elaradi
Author-Name: Masoumeh Kazemi Zanjani
Author-X-Name-First: Masoumeh Kazemi
Author-X-Name-Last: Zanjani
Author-Name: Mustapha Nourelfath
Author-X-Name-First: Mustapha
Author-X-Name-Last: Nourelfath
Title: Integrated forest biorefinery network design under demand uncertainty: a case study on canadian pulp & paper industry
Abstract: 
 Transforming Pulp and Paper (P&P) mills into Integrated Forest Biorefineries (IFBR) is a prominent solution to save Canadian P&P industry that has been facing decline of conventional paper demand. We propose a comprehensive decision model for the design of IFBR value chains by taking the uncertain demand of bioproducts into consideration. In particular, we propose a multi-stage stochastic programming model to obtain the optimal investment plan over a long-term planning horizon in the presence of various market trends. We also develop a Monte-Carlo simulation platform to validate the proposed model and to compare its performance with alternative decision models. The model is applied to a realistic case study inspired from P&P companies in Canada, where the value of incorporating the dynamic nature of uncertain demand has been estimated. Further, we elaborate on the value of considering flexibility in terms of adjusting the investment plan in response to changes in the demand. Our results indicate that the demand for bioproducts has a substantial impact on the profitability of the IFBR. We also demonstrated the significant value of explicitly incorporating the uncertainty in IFBR network design as well as adapting the investment plan to the changes in the demand.
Journal: International Journal of Production Research
Pages: 4954-4972
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1944688
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1944688
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1942285_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Andrea Chiarini
Author-X-Name-First: Andrea
Author-X-Name-Last: Chiarini
Author-Name: Maneesh Kumar
Author-X-Name-First: Maneesh
Author-X-Name-Last: Kumar
Title: What is Quality 4.0? An exploratory sequential mixed methods study of Italian manufacturing companies
Abstract: 
 The purpose of this paper is to contribute to the scientific debate on Quality 4.0 by exploring the main theoretical themes underpinning the Quality 4.0 model and how the model may be developed. An exploratory sequential mixed methods design was employed to study two different samples of Italian manufacturing companies over two phases. For each sample, a different questionnaire was distributed to the companies’ quality managers. As a result, eleven themes were elicited and tested. These themes are related to model development, top management, process mapping, data collection and integration with the enterprise resource planning system, use of artificial intelligence software, machine-to-machine data communication, product identification and traceability, document control and digital skills for quality control staff. A theoretical model for Q4.0 is proposed that encapsulates eleven themes of Q4.0 across three categories- people, process, and technology. Results could be particularly helpful for practitioners who may use them as a guideline for implementing and developing Quality 4.0 in a typical Industry 4.0 environment.
Journal: International Journal of Production Research
Pages: 4890-4910
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1942285
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1942285
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# input file: TPRS_A_1948134_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Huaxing Zhong
Author-X-Name-First: Huaxing
Author-X-Name-Last: Zhong
Author-Name: Min Liu
Author-X-Name-First: Min
Author-X-Name-Last: Liu
Author-Name: La Bao
Author-X-Name-First: La
Author-X-Name-Last: Bao
Title: A job-priority based soft scheduling approach for uncertain work area scheduling in Semiconductor Manufacturing
Abstract: 
 This paper studies the uncertain scheduling problem of the oxidation/deposition/diffusion work area in semiconductor manufacturing, where fluctuations in arrival times and processing times are considered. To overcome the shortcomings of the conventional schedule, which has a fixed processing machine and starting time for each operation, we design a new form of schedule called the job-priority based soft schedule. Its basic idea is to assign global priority to each job in advance, and to make remaining decisions (including batch formation, machine assignment and real-time dispatching) in the process of implementing the initial soft schedule. Then we develop a job-priority based soft scheduling approach that involves two layers: (1) in the offline optimisation layer, an initial soft schedule is obtained by a proposed hybrid harmony search algorithm; (2) in the online dispatching layer, the remaining decisions are made in real time by a designed online heuristic rule. The comparative experimental results demonstrate that the two-layer soft scheduling mechanism can effectively adapt to an uncertain production environment due to its integration of the global optimisation perspective and local flexibility.
Journal: International Journal of Production Research
Pages: 5012-5028
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1948134
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1948134
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# input file: TPRS_A_1949642_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Anh Tuan Bui
Author-X-Name-First: Anh Tuan
Author-X-Name-Last: Bui
Author-Name: Daniel W. Apley
Author-X-Name-First: Daniel W.
Author-X-Name-Last: Apley
Title: Robust monitoring of stochastic textured surfaces
Abstract: 
 Stochastic textured surfaces (STSs) do not have well-defined features, and their quality characteristics are reflected through the stochastic nature of their surface textures. Monitoring general global changes in the stochastic nature of STSs is a relatively new, yet important problem. The limited literature for solving this problem has not considered the common situation in which the normal, in-control STS data are subject to structured surface-to-surface variation in their stochastic nature, due to the challenging nature of this problem. In this paper, we propose a dissimilarity-based multivariate control charting approach for monitoring general global changes in STSs in the presence of such structured in-control variation. Our approach is novel in that it quantifies the level of abnormality from multiple ‘spanning points’, instead of a single reference as in prior work. The spanning points are selected via dissimilarity-based manifold learning and space filling sampling methods. We test our approach with simulated and real textile examples and demonstrate its superior robustness to the structured in-control variation. Our approach has potential to provide a general control charting framework for any applications involving complex data structures other than STS data.
Journal: International Journal of Production Research
Pages: 5071-5086
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1949642
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1949642
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# input file: TPRS_A_1941374_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Weiyue Zhang
Author-X-Name-First: Weiyue
Author-X-Name-Last: Zhang
Author-Name: ChenGuang Liu
Author-X-Name-First: ChenGuang
Author-X-Name-Last: Liu
Author-Name: Lin Li
Author-X-Name-First: Lin
Author-X-Name-Last: Li
Title: Economic and environmental implications of the interfirm waste utilisation
Abstract: 
 Considering the mismatch in the supply of and demand for the industrial process wastes, we investigate when the interfirm waste utilisation can be both economically and environmentally superior to the no waste utilisation. The Nash bargaining approach is employed to resolve the incentive misalignment problem. Our analysis suggests that the conversion strategy changes from over-conversion, to full conversion, and then to partial conversion with increasing waste trading price. Furthermore, an increase in the waste disposal fee contributes to the diversion of wastes from the landfill but may result in worse environmental consequences especially for wastes with a slight reduction in the production impact compared to raw materials. This implies that policy makers should charge the waste disposal fee based on waste types and focus on increasing that for wastes with higher disposal and lower production impacts. Finally, at the lower waste trading price, the interfirm waste utilisation is always a win-win strategy. While at the higher waste trading price, it is a win-win strategy for products with a substantial reduction in the production impact when producing with wastes. Otherwise, it is a win-win strategy for products with a lower production impact relative to the raw material usage and waste disposal impacts.
Journal: International Journal of Production Research
Pages: 4868-4889
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1941374
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1941374
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# input file: TPRS_A_1950936_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Jacob Lohmer
Author-X-Name-First: Jacob
Author-X-Name-Last: Lohmer
Author-Name: Franz Kossmann
Author-X-Name-First: Franz
Author-X-Name-Last: Kossmann
Author-Name: Rainer Lasch
Author-X-Name-First: Rainer
Author-X-Name-Last: Lasch
Title: Manufacturing strategy in multi-plant networks – a multi-case study on decision-making authority, network capabilities and competitive advantages
Abstract: 
 Modern manufacturing firms are globalised organisations that regularly operate multi-plant networks. Network configuration elements, e.g. plant roles or the multi-plant strategy, were intensively examined by scholars. Another complex and less studied task is coordinating the manufacturing strategy of the plants in the network. Efficient distribution of competences and decision-making authorities is crucial for decision-makers. An appropriate level of autonomy has to be found that determines which decisions are centralised and which are delegated to the decentralised plants. The interaction of network coordination and configuration with network capabilities and competitive advantages is examined in this article using an empirical multi-case study. We focus on how manufacturing strategy decisions are made in the intra-firm network and how the distribution of decision-making authorities affects the network capabilities. Results indicate that both network coordination and configuration affect network capabilities, which in turn affect competitive advantages. Network thriftiness reduces costs, while mobility and flexibility promote delivery capabilities and learning effects improve quality and costs. A conceptual research model is developed as a starting point for future studies in this emerging research area. Besides, managers are provided with guidance on the efficient design of distributed manufacturing networks to achieve the desired competitive advantages.
Journal: International Journal of Production Research
Pages: 5108-5129
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1950936
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1950936
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# input file: TPRS_A_1943037_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220804T044749 git hash: 24b08f8188
Author-Name: Shengluo Yang
Author-X-Name-First: Shengluo
Author-X-Name-Last: Yang
Author-Name: Zhigang Xu
Author-X-Name-First: Zhigang
Author-X-Name-Last: Xu
Title: Intelligent scheduling and reconfiguration via deep reinforcement learning in smart manufacturing
Abstract: 
 To realise the intelligent decision-making of dynamic scheduling and reconfiguration, we studied the intelligent scheduling and reconfiguration with dynamic job arrival for a reconfigurable flow line (RFL) using deep reinforcement learning (DRL), for the first time. The system architecture of intelligent scheduling and reconfiguration in smart manufacturing is proposed, and the mathematical model is established to minimise total tardiness cost. In addition, a DRL system of scheduling and reconfiguration is proposed by designing state features, actions, and rewards for scheduling and reconfiguration agents. Moreover, the advantage actor-critic (A2C) is adapted to solve the studied problem. The training curve shows the A2C-based agents have effectively learned to generate better solutions for unseen instances. The test results show that the A2C-based approach outperforms two traditional meta-heuristics, iterated greedy (IG) and genetic algorithm (GA), in solution quality and CPU times by a large margin. Specifically, the A2C-based approach outperforms IG and GA by 57.43% and 88.30%, using only 0.46‱ and 2.20‱ CPU times of IG and GA. The trained model can generate a scheduling or reconfiguration decision within 1.47 ms, which is almost instantaneous and can satisfy real-time optimisation. Our work shows a promising prospect of using DRL for intelligent scheduling and reconfiguration.
Journal: International Journal of Production Research
Pages: 4936-4953
Issue: 16
Volume: 60
Year: 2022
Month: 08
X-DOI: 10.1080/00207543.2021.1943037
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1943037
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# input file: TPRS_A_1955310_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Qian Gao
Author-X-Name-First: Qian
Author-X-Name-Last: Gao
Author-Name: Xiaolong Guo
Author-X-Name-First: Xiaolong
Author-X-Name-Last: Guo
Author-Name: Feng Yang
Author-X-Name-First: Feng
Author-X-Name-Last: Yang
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Title: Commitment or not? Creator's quality strategies with uncertain market in reward-based crowdfunding
Abstract: 
 This paper studies a creator's quality commitment strategies with uncertain demand when the creator lacks setup funding and chooses crowdfunding to finance. Facing uncertain demand, the creator may or may not choose to make a quality commitment. Conventional wisdom indicates that the strategy of committing to a certain quality outperforms the no-commitment strategy by eliminating the consumers' strategic behavior of delaying purchases. We build a two-period model consisting of crowdfunding and spot sales periods, a creator lacking setup funding, and consumers with heterogeneous valuations for the product. When considering the creator's setup cost and market uncertainty, we find, counterintuitively, that making no quality commitment to consumers can be more profitable for the creator because of the advantage of flexibility. Moreover, our analysis shows that when the creator's setup cost is high enough, the profit-maximising creator will make a quality commitment to consumers and offer a higher-quality product than when making no commitment. Also, we show that the product quality increases with the market uncertainty under certain conditions. In addition, we find that the creator should finance through crowdfunding only when the setup cost is less than a threshold, and the threshold increases with market uncertainty.
Journal: International Journal of Production Research
Pages: 5307-5331
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1955310
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1955310
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# input file: TPRS_A_1953180_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Seyedmohsen Hosseini
Author-X-Name-First: Seyedmohsen
Author-X-Name-Last: Hosseini
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: A multi-layer Bayesian network method for supply chain disruption modelling in the wake of the COVID-19 pandemic
Abstract: 
 While the majority of companies anticipated the negative and severe impacts of the COVID-19 pandemic on the supply chains (SC), most of them lacked guidance on how to model disruptions and their performance impacts under pandemic conditions. Lack of such guidance resulted in delayed reactions, incomplete understanding of pandemic impacts, and late deployment of recovery actions. In this study, we offer a method of modelling and quantifying the SC disruption impacts in the wake of a pandemic. We develop a multi-layer Bayesian network (BN) model that can be used to identify SC disruption triggers and risk events amid the COVID-19 pandemic and quantify the consequences of pandemic disruptions. The unique features of BN, such as forward and backward propagation analysis, are utilised to simulate and measure the impact of different triggers on SC financial performance and business continuity. In this way, we combine resilience and viability SC perspectives and explicitly account for the pandemic settings. The outcomes of this research open a novel theoretical lens on application of BNs to SC disruption modelling in the pandemic setting. Our results can be used as a decision-support tool to predict and better understand the pandemic impacts on SC performance.
Journal: International Journal of Production Research
Pages: 5258-5276
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1953180
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1953180
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# input file: TPRS_A_1957508_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Yue Wang
Author-X-Name-First: Yue
Author-X-Name-Last: Wang
Author-Name: Xiang Li
Author-X-Name-First: Xiang
Author-X-Name-Last: Li
Author-Name: Linda L. Zhang
Author-X-Name-First: Linda L.
Author-X-Name-Last: Zhang
Author-Name: Daniel Mo
Author-X-Name-First: Daniel
Author-X-Name-Last: Mo
Title: Configuring products with natural language: a simple yet effective approach based on text embeddings and multilayer perceptron
Abstract: 
 Product configurators are recognised as critical toolkits enabling customers to co-create products with companies. Most available product configurators require customers to select suitable product attributes from predefined options. However, customers usually find the selection processes frustrating due to their lack of product knowledge. In view of the fact that customers often express their needs in imprecise and vague natural language, we define a new needs-based configuration mechanism and propose an implementation approach based on text embeddings and multilayer perceptron. Specifically, we leverage the massive amount of product reviews by encoding them into text embeddings. A multilayer perceptron is trained to map text embeddings to product attribute options. Experiment results indicate that the mapping has good generalisation capability to map customer needs into product configurations. The performance of our approach is comparable to that of deep learning-based approaches but with much higher efficiency in terms of computational complexity. Our needs-based configuration thus provides a quick and effective means of facilitating product customisation. It also demonstrates an innovative way of utilising customer resources in unstructured text to co-create products with companies.
Journal: International Journal of Production Research
Pages: 5394-5406
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1957508
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1957508
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# input file: TPRS_A_1956697_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Edward Elson Kosasih
Author-X-Name-First: Edward Elson
Author-X-Name-Last: Kosasih
Author-Name: Alexandra Brintrup
Author-X-Name-First: Alexandra
Author-X-Name-Last: Brintrup
Title: A machine learning approach for predicting hidden links in supply chain with graph neural networks
Abstract: 
 Supply chain business interruption has been identified as a key risk factor in recent years, with high-impact disruptions due to disease outbreaks, logistic issues such as the recent Suez Canal blockage showing examples of how disruptions could propagate across complex emergent networks. Researchers have highlighted the importance of gaining visibility into procurement interdependencies between suppliers to develop more informed business contingency plans. However, extant methods such as supplier surveys rely on the willingness or ability of suppliers to share data and are not easily verifiable. In this article, we pose the supply chain visibility problem as a link prediction problem from the field of Machine Learning (ML) and propose the use of an automated method to detect potential links that are unknown to the buyer with Graph Neural Networks (GNN). Using a real automotive network as a test case, we show that our method performs better than existing algorithms. Additionally, we use Integrated Gradient to improve the explainability of our approach by highlighting input features that influence GNN’s decisions. We also discuss the advantages and limitations of using GNN for link prediction, outlining future research directions.
Journal: International Journal of Production Research
Pages: 5380-5393
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1956697
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1956697
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# input file: TPRS_A_1951867_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Martin Hallmann
Author-X-Name-First: Martin
Author-X-Name-Last: Hallmann
Author-Name: Benjamin Schleich
Author-X-Name-First: Benjamin
Author-X-Name-Last: Schleich
Author-Name: Sandro Wartzack
Author-X-Name-First: Sandro
Author-X-Name-Last: Wartzack
Title: Process and machine selection in sampling-based tolerance-cost optimisation for dimensional tolerancing
Abstract: 
 Tolerance-cost optimisation, i.e. using optimisation techniques for tolerance allocation, is frequently used to determine a cost-efficient tolerance design that can meet the stringent requirements on high-quality products. Besides various manufacturing aspects, the selection of available alternative machines and processes hold great potential for an early optimal process planning by identifying their best combination. Although machine/process selection by minimum cost and mixed-integer optimisation is often applied in theory and practice, their proper implementation in tolerance-cost optimisation based on sampling techniques for tolerance analysis, which can statistically consider various individual part tolerance distributions, has not been studied so far. With the aim to overcome this drawback, this article focuses on machine/process selection in sampling-based tolerance-cost optimisation for dimensional tolerances considering the respective machine characteristics of several machine options, e.g. process capabilities and manufacturing distributions. A comparative study proves that machine/process selection by mixed-integer optimisation leads to minimum total manufacturing costs since it covers the whole search space, including all technically feasible machine combinations and thus identifies the global cost minimum.
Journal: International Journal of Production Research
Pages: 5201-5216
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1951867
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1951867
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# input file: TPRS_A_1955995_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Ece Naz Duman
Author-X-Name-First: Ece Naz
Author-X-Name-Last: Duman
Author-Name: Duygu Taş
Author-X-Name-First: Duygu
Author-X-Name-Last: Taş
Author-Name: Bülent Çatay
Author-X-Name-First: Bülent
Author-X-Name-Last: Çatay
Title: Branch-and-price-and-cut methods for the electric vehicle routing problem with time windows
Abstract: 
 In this paper, we address the electric vehicle routing problem with time windows and propose two branch-and-price-and-cut methods based on a column generation algorithm. One is an exact algorithm whereas the other is a heuristic method. The pricing sub-problem of the column generation method is solved using a label correcting algorithm. The algorithms are strengthened with the state-of-the-art acceleration techniques and a set of valid inequalities. The acceleration techniques include: (i) an intermediate column pool to prevent solving the pricing sub-problem at each iteration, (ii) a label correcting method employing the ng-route algorithm adopted to our problem, (iii) a bidirectional search mechanism in which both forward and backward labels are created, (iv) a procedure for dynamically eliminating arcs that connect customers to remote stations from the network during the path generation, (v) a bounding procedure providing early elimination of sub-optimal routes, and (vi) an integer programming model that generates upper bounds. Numerical experiments are conducted using a benchmark data set to compare the performances of the algorithms. The results favour the heuristic algorithm in terms of both the computational time and the number of instances solved. Moreover, the heuristic algorithm is shown to be specifically effective for larger instances. Both algorithms introduce a number of new solutions to the literature.
Journal: International Journal of Production Research
Pages: 5332-5353
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1955995
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1955995
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# input file: TPRS_A_1951447_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Jie Gan
Author-X-Name-First: Jie
Author-X-Name-Last: Gan
Author-Name: Wenyu Zhang
Author-X-Name-First: Wenyu
Author-X-Name-Last: Zhang
Author-Name: Siyu Wang
Author-X-Name-First: Siyu
Author-X-Name-Last: Wang
Author-Name: Xiaohong Zhang
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Zhang
Title: Joint decision of condition-based opportunistic maintenance and scheduling for multi-component production systems
Abstract: 
 In this study, system maintenance and production scheduling are jointly decided to solve the problems of resource idleness and time cost increase due to system maintenance in the processing of production scheduling. For the multi-component system with economic dependence, a joint strategy of condition-based maintenance and production scheduling is formulated, which includes opportunistic maintenance, preventive maintenance, and corrective maintenance. On this basis, a joint decision model is established to minimise the total weighted expected completion time. Subsequently, all possible maintenance requirements and their corresponding probabilities for the multi-component system in the entire production scheduling process are deduced via the deterioration state space partition modelling method. Furthermore, the stationary probability density function of the joint state of the system is derived, and its numerical solution method is provided. Finally, taking the KS5 adjustable multi-axis tapping machine as an example, numerical experiments are conducted to verify the efficacy of the proposed strategy and the established model. Comparisons with previous strategies using different numbers of components and scheduling job scales indicate that the joint decision model yields better results.
Journal: International Journal of Production Research
Pages: 5155-5175
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1951447
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1951447
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# input file: TPRS_A_1953179_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Reza Rahmati
Author-X-Name-First: Reza
Author-X-Name-Last: Rahmati
Author-Name: Mahdi Bashiri
Author-X-Name-First: Mahdi
Author-X-Name-Last: Bashiri
Author-Name: Erfaneh Nikzad
Author-X-Name-First: Erfaneh
Author-X-Name-Last: Nikzad
Author-Name: Ali Siadat
Author-X-Name-First: Ali
Author-X-Name-Last: Siadat
Title: A two-stage robust hub location problem with accelerated Benders decomposition algorithm
Abstract: 
 In this paper, a two-stage robust optimisation is presented for an uncapacitated hub location problem in which demand is uncertain and the level of conservatism is controlled by an uncertainty budget. In the first stage, locations for establishing hub facilities were determined, and allocation decisions were made in the second stage. An accelerated Benders decomposition algorithm was used to solve the problem. Computational experiments showed better results in terms of number of iterations and computation time for Benders decomposition with Pareto-optimal cuts in comparison with the classical Benders decomposition algorithm. According to numerical analysis, it was concluded that increasing the uncertainty budget also increased total costs for more established hubs. To determine the uncertainty budget in an appropriate manner, a new expected aggregate function was introduced. The numerical studies demonstrated the usefulness of the proposed method in defining the appropriate uncertainty budget in the presence of uncertainty.
Journal: International Journal of Production Research
Pages: 5235-5257
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1953179
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1953179
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# input file: TPRS_A_1951446_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Christian Gahm
Author-X-Name-First: Christian
Author-X-Name-Last: Gahm
Author-Name: Stefan Wahl
Author-X-Name-First: Stefan
Author-X-Name-Last: Wahl
Author-Name: Axel Tuma
Author-X-Name-First: Axel
Author-X-Name-Last: Tuma
Title: Scheduling parallel serial-batch processing machines with incompatible job families, sequence-dependent setup times and arbitrary sizes
Abstract: 
 The scheduling of (parallel) serial-batch processing machines is a task arising in many industrial sectors. In the metal-processing industry for instance, cutting operations are necessary to fabricate varying metal pieces out of large base slides. Here, the (cutting) jobs have individual, arbitrary base slide capacity requirements (sizes), individual processing times and due dates, and specific material requirements (i.e. each job belongs to one specific job family, whereby jobs of different families cannot be processed within the same batch and thus are incompatible). In addition, switching of base metal slides and material dependent adjustments of machine parameters cause sequence-dependent setup times. All these conditions need to be considered while minimising total weighted tardiness. For solving the scheduling problem, a mixed-integer program and several tailor-made construction heuristics (enhanced by local search mechanisms) are presented. The experimental results show that problem instances with up to five machines and 60 jobs can be tackled using the optimisation model. The experiments on small and large problem instances (with up to 400 jobs) show that a purposefully used batch capacity limitation improves the solution quality remarkably. Applying the best heuristic to the data of two real-world application cases shows its huge potential to increase delivery reliability.
Journal: International Journal of Production Research
Pages: 5131-5154
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1951446
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1951446
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# input file: TPRS_A_1954712_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Julia Mindlina
Author-X-Name-First: Julia
Author-X-Name-Last: Mindlina
Author-Name: Horst Tempelmeier
Author-X-Name-First: Horst
Author-X-Name-Last: Tempelmeier
Title: Performance analysis and optimisation of stochastic flow lines with limited material supply
Abstract: 
 We consider stochastic flow lines with limited buffer sizes and limited material supply. In these systems, the configuration of the flow line parameters and the configuration of the material supply determine the system output. Shortages of material supply can limit the performance of the production system. We use flexible (mixed-integer) linear programming approaches to evaluate and optimise the performance of long stochastic flow lines with limited material supply in discrete and continuous time. The approaches are used to quantify the impact of material shortages on the system output. Further, they are applied to determine the minimum material levels that are required to prevent material shortages of a given flow line configuration. The results of the numerical study reveal insights on the approximation accuracy of the linear programs as well as on the dependence of optimal material levels on flow line characteristics such as the presence of bottleneck machines and the system variability. The contribution of this paper consists of both, integrated models for stochastic flow lines with limited material supply and new insights on the optimal material supply of stochastic flow lines.
Journal: International Journal of Production Research
Pages: 5293-5306
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1954712
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1954712
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# input file: TPRS_A_1951448_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Siamak Khayyati
Author-X-Name-First: Siamak
Author-X-Name-Last: Khayyati
Author-Name: Barış Tan
Author-X-Name-First: Barış
Author-X-Name-Last: Tan
Title: Supervised-learning-based approximation method for multi-server queueing networks under different service disciplines with correlated interarrival and service times
Abstract: 
 Developing efficient performance evaluation methods is important to design and control complex production systems effectively. We present an approximation method (SLQNA) to predict the performance measures of queueing networks composed of multi-server stations operating under different service disciplines with correlated interarrival and service times with merge, split, and batching blocks separated with infinite capacity buffers. SLQNA yields the mean, coefficient of variation, and first-lag autocorrelation of the inter-departure times and the distribution of the time spent in the block, referred as the cycle time at each block. The method generates the training data by simulating different blocks for different parameters and uses Gaussian Process Regression to predict the inter-departure time and the cycle time distribution characteristics of each block in isolation. The predictions obtained for one block are fed into the next block in the network. The cycle time distributions of the blocks are used to approximate the distribution of the total time spent in the network (total cycle time). This approach eliminates the need to generate new data and train new models for each given network. We present SLQNA as a versatile, accurate, and efficient method to evaluate the cycle time distribution and other performance measures in queueing networks.
Journal: International Journal of Production Research
Pages: 5176-5200
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1951448
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1951448
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# input file: TPRS_A_1951869_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Jingjing Li
Author-X-Name-First: Jingjing
Author-X-Name-Last: Li
Author-Name: Guanghui Zhou
Author-X-Name-First: Guanghui
Author-X-Name-Last: Zhou
Author-Name: Chao Zhang
Author-X-Name-First: Chao
Author-X-Name-Last: Zhang
Title: A twin data and knowledge-driven intelligent process planning framework of aviation parts
Abstract: 
 As the core link of intelligent manufacturing, the process planning of aviation parts still faces the challenges such as relying on manual experiences for process decision-making and lack of linkage between process design and manufacturing for process optimisation. Process knowledge could support scientific decision-making on process issues, while twin data, namely high-fidelity simulation data and feedback information of manufacturing site, could further verify the process plans and optimise process parameters, so as to continuously improve the quality of process plans. Consequently, this paper proposes a general framework for twin data and knowledge-driven intelligent process planning (TDKIPP) of aviation parts, and analyses four standard procedures that support the above-mentioned reference framework, namely mechanism-data fusion process digital twin model, dynamic process knowledge base, process decision-making and evaluation, machining quality prediction and process feedback optimisation. A thus constructed test bed of TDKIPP and its four application examples about the process planning of a micro turbojet engine integral impeller demonstrate the feasibility and effectiveness of the proposed approach.
Journal: International Journal of Production Research
Pages: 5217-5234
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1951869
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1951869
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# input file: TPRS_A_1956695_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Duy Tan Nguyen
Author-X-Name-First: Duy Tan
Author-X-Name-Last: Nguyen
Author-Name: Yossiri Adulyasak
Author-X-Name-First: Yossiri
Author-X-Name-Last: Adulyasak
Author-Name: Jean-François Cordeau
Author-X-Name-First: Jean-François
Author-X-Name-Last: Cordeau
Author-Name: Silvia I. Ponce
Author-X-Name-First: Silvia I.
Author-X-Name-Last: Ponce
Title: Data-driven operations and supply chain management: established research clusters from 2000 to early 2020
Abstract: 
 Despite the long-recognised importance of data-driven operations and supply chain management (OSCM) scholarship and practice, and the impressive development of big data analytics (BDA), research finds that firms struggle with BDA adoption, which suggests the existence of gaps in the literature. Therefore, we conduct this systematic literature review of journal articles on data-driven OSCM from 2000 to early 2020 to ascertain established research clusters and literature lacunae. Using co-citation analysis software and double-checking the results with factor analysis and multidimensional-scaling-based k-means clustering, we find six clusters of studies on data-driven OSCM, whose primary topics are identified by keyword co-occurrence analysis. Five of these clusters relate directly to manufacturing, which, in line with the existing literature, indicates the crucial role of production in OSCM. We highlight the evolution of these research clusters and propose how the literature on data-driven OSCM can support BDA in OSCM. We synthesise what has been studied in the literature as points of reference for practitioners and researchers and identify what necessitates further exploration. In addition to the insights contributed to the literature, our study is amongst the first efforts to deploy multiple clustering techniques to undertake a rigorous data-driven systematic literature review (SLR) of data-driven OSCM.
Journal: International Journal of Production Research
Pages: 5407-5431
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1956695
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1956695
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1953715_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Tong Qin
Author-X-Name-First: Tong
Author-X-Name-Last: Qin
Author-Name: Ruxu Du
Author-X-Name-First: Ruxu
Author-X-Name-Last: Du
Author-Name: Andrew Kusiak
Author-X-Name-First: Andrew
Author-X-Name-Last: Kusiak
Author-Name: Hui Tao
Author-X-Name-First: Hui
Author-X-Name-Last: Tao
Author-Name: Yong Zhong
Author-X-Name-First: Yong
Author-X-Name-Last: Zhong
Title: Designing a resilient production system with reconfigurable machines and movable buffers
Abstract: 
 The resilience of a production system is determined by its capability to respond to internal breakdowns and/or external disruptions and recover. In conventional production systems, internal disruptions such as machine breakdown are handled by parallel stations and storage buffers, which come at a cost. In this paper, we propose to use reconfigurable machines (RMs) and movable buffers (MBs) to increase the resilience of a production system. The production system is modelled using a modified Markov chain model. To reduce the computational effort, an iterative method is adopted for the production lines that have many RMs and MBs. The resilience of the production system is evaluated by a combination of production loss, steady production rate with threshold, work-in-process in Idle-area of MBs, process time of work-in-process in Idle-area of MB with threshold, and investment return. Two production systems are analysed, one with 3 operations and the other with 10 operations. The computer simulation results indicate that the resilience of a production system can be improved by more than 9% by RMs and MBs. Finally, a set of guidelines for design production systems with RMs and MBs are also given.
Journal: International Journal of Production Research
Pages: 5277-5292
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1953715
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1953715
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# input file: TPRS_A_1956694_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220823T191300 git hash: 39867e6e2f
Author-Name: Zihao Jiao
Author-X-Name-First: Zihao
Author-X-Name-Last: Jiao
Author-Name: Ying Yin
Author-X-Name-First: Ying
Author-X-Name-Last: Yin
Author-Name: Lun Ran
Author-X-Name-First: Lun
Author-X-Name-Last: Ran
Author-Name: Zhen Gao
Author-X-Name-First: Zhen
Author-X-Name-Last: Gao
Title: Integrating vehicle-to-grid contract design with power dispatching optimisation: managerial insights, and carbon footprints mitigation
Abstract: 
 Towards booms on massive electric vehicle adoptions, vehicle-to-grid service creates significantly social-environmental benefits on acting as a flexible power resource alternative for stabilising the violent fluctuations and overload in the power grid. However, the customer's acceptance and unstable external environment degrade these positive influences on embracing V2G operations. Motivated by these practical challenges, we attempt to design a V2G power dispatching plan integrated with a revenue-sharing contract to coordinate the multi-parties interests in the power supply chain and further improve V2G service adoption. Specifically, we focus on an urban microgrid system, in which the aggregator integrates the supply chain coordination conditions of a revenue sharing contract into a V2G power dispatching plan. The nonlinear terms generated by the supply chain coordination conditions are approximated into a tractable convex form. Furthermore, by solving instances generated from real-world and synthetic data from CAR2GO in Amsterdam, the Netherlands, we demonstrate several implications: (1) the proposed contract integrated policy is proved cost-saving for the aggregator operation, revenue-improving for the EV user, and carbon footprint mitigation for the society; (2) our proposed policy facilitates the aggregator to balance the trade-off between revenue sharing ratio and operation cost; (3) based on our contract integrated policy, we also explore the influences of service rate.
Journal: International Journal of Production Research
Pages: 5354-5379
Issue: 17
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1956694
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1956694
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# input file: TPRS_A_1966541_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Zhong-Zhong Jiang
Author-X-Name-First: Zhong-Zhong
Author-X-Name-Last: Jiang
Author-Name: Na He
Author-X-Name-First: Na
Author-X-Name-Last: He
Author-Name: Song Huang
Author-X-Name-First: Song
Author-X-Name-Last: Huang
Title: Contracting with asymmetric information under government subsidy programmes in a bioenergy supply chain
Abstract: 
 This paper investigates the government subsidy programmes for a bioenergy supply chain composed of a power plant and farmers who privately know their quality information of bioenergy. The government offers two types of subsidy programmes to increase the supply of bioenergy: Agriculture Quantity Coverage (AQC) programme that pays the farmers subsidies based on the quantity of bioenergy, and Price Loss Coverage (PLC) programme that is triggered when the market price of bioenergy falls below a reference price. With AQC programme, when the quantity of bioenergy is large, farmers may get more subsidies but the wholesale price of bioenergy would decrease, thus hurting the farmers' payoffs. By contrast, with PLC programme, the farmers can get more subsidies with a lower wholesale price, which also undermines the farmers' profitability. In equilibrium, the government prefers the AQC programme when the cost of the non-bioenergy is high, or the cost of the non-bioenergy is low and the government's subsidy payment coefficient in the PLC programme is high. Moreover, social welfare is higher with the PLC programme than that with the AQC programme when the cost of the non-bioenergy is high and the subsidy payment coefficient is low, and is lower otherwise.
Journal: International Journal of Production Research
Pages: 5571-5594
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1966541
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1966541
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# input file: TPRS_A_1959664_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Zhen He
Author-X-Name-First: Zhen
Author-X-Name-Last: He
Author-Name: Yuan Gao
Author-X-Name-First: Yuan
Author-X-Name-Last: Gao
Author-Name: Liang Qu
Author-X-Name-First: Liang
Author-X-Name-Last: Qu
Author-Name: Zhiqiong Wang
Author-X-Name-First: Zhiqiong
Author-X-Name-Last: Wang
Title: A nonparametric CUSUM scheme for monitoring multivariate time-between-events-and-amplitude data with application to automobile painting
Abstract: 
 Monitoring time-between-events-and-amplitude (TBEA) data, including the time interval between two successive nonconforming events and the amplitude of an event, is significant in many applications, especially manufacturing and service operations. Almost all TBEA control charts consider only one quality characteristic of the event, and most of the related research is restricted to cases where data are assumed to follow specific distributions. However, an event is usually described by multiple quality characteristics of which underlying distributions are unknown. In this article, we integrate the TBEA data into a specified form and then design a nonparametric multivariate TBEA (NMTBEA) control chart based on log-linear modelling. This chart is used to monitor the location shifts of the time interval and the amplitudes in an event. Next, we investigate the performance of some improved nonparametric control charts in monitoring multivariate TBEA data. The numerical simulation results show that the NMTBEA control chart performs best in most shifts that occur in six representative distributions. A real example of the colour difference monitoring of the car body in the automotive industry is provided to illustrate the implementation of the proposed chart.
Journal: International Journal of Production Research
Pages: 5432-5449
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1959664
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1959664
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# input file: TPRS_A_1967500_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Hani Pourvaziri
Author-X-Name-First: Hani
Author-X-Name-Last: Pourvaziri
Author-Name: Saeideh Salimpour
Author-X-Name-First: Saeideh
Author-X-Name-Last: Salimpour
Author-Name: Seyed Taghi Akhavan Niaki
Author-X-Name-First: Seyed Taghi
Author-X-Name-Last: Akhavan Niaki
Author-Name: Ahmed Azab
Author-X-Name-First: Ahmed
Author-X-Name-Last: Azab
Title: Robust facility layout design for flexible manufacturing: a doe-based heuristic
Abstract: 
 Flexible manufacturing systems (FMS) should be able to respond to changing manufacturing requirements and environments. From the layout point of view, FMS need to be rearranged to fit the new requirements. However, rearranging the layout is often undesirable due to its unpredicted high costs and production disruption. This paper proposes a practical approach to mitigate the effects and repercussions of changing environments and avoid rearranging the layout. A robust layout approach is presented, where changes in product demand and mix are absorbed by altering product routes and not rearranging the layout. In this approach, the problem is decomposed into two sub-problems: sub-problem 1 (SP1) where a robust layout is constructed, and sub-problem 2 (SP2) to obtain the best routes of products. To solve SP1, design of experiments is used to find a critical period, which is the period most affected under demand changes. Then, the layout for the critical period is determined using a hybridized genetic-tabu search algorithm. Then SP2 is solved by a branch and cut algorithm to obtain the optimal routes of the products in each period. The performance of the proposed methodology is illustrated using a case study and is benchmarked against rival ones from the literature.
Journal: International Journal of Production Research
Pages: 5633-5654
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1967500
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1967500
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# input file: TPRS_A_1968061_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Jianbo Yu
Author-X-Name-First: Jianbo
Author-X-Name-Last: Yu
Author-Name: Xing Liu
Author-X-Name-First: Xing
Author-X-Name-Last: Liu
Title: One-dimensional residual convolutional auto-encoder for fault detection in complex industrial processes
Abstract: 
 Fault detection and diagnosis have always been the key techniques for safe and reliable operation of industrial processes. However, the high dimension and noise of process variables have brought great challenges to the fault detection model. In recent years, due to the powerful feature extraction ability, deep learning has been widely applied in process fault detection and diagnosis. However, these deep neural networks (DNNs) often need a large amount of label data for supervised training, or show poor performance in learning features under unsupervised-learning condition. This paper proposes a new DNN model, a one-dimension residual convolutional auto-encoder (1DRCAE), where unsupervised learning is used to extract representative features from complex industrial processes. 1DRCAE effectively integrates the one-dimensional convolutional kernel with an auto-encoder and is embedded residual learning block for effective feature extraction from one-dimensional data. The two statistics and squared prediction error are generated in the feature space and residual space of 1DRCAE, respectively. Finally, the feasibility and superiority of 1DRCAE are verified on a simulation process, Tennessee Eastman process, Fed-batch fermentation penicillin process, and a real-life case. The convolutional auto-encoder technique provides a new way for feature learning and fault detection on complex industrial processes.
Journal: International Journal of Production Research
Pages: 5655-5674
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1968061
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1968061
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1967499_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ada Che
Author-X-Name-First: Ada
Author-X-Name-Last: Che
Author-Name: Jieyu Lei
Author-X-Name-First: Jieyu
Author-X-Name-Last: Lei
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Optimised redesign of reverse logistics network with multi-level capacity choices for household appliances
Abstract: 
 Reverse logistics networks reintroduce end-of-life products to remanufacturing, which is significant for sustainable development and environmental protection. In this paper, we investigate the current reverse logistics network of household appliances in China and redesign a new network that introduces necessary facilities: disassembly centres and three types of remanufacturing plants to improve recycling rates. A mixed-integer linear programming model with multi-level capacity choices is proposed to determine the locations and capacities for disassembly centres and remanufacturing plants. An efficient decomposition-and-expansion heuristic is developed to solve the model. The redesigned network is evaluated using a real case. The results indicate that the recycling rate is largely improved by the new network in which almost all useful materials can be recycled, whereas, in the traditional network, only metals are efficiently recycled. A sensitivity analysis of model parameters is conducted using the Taguchi method to identify their effects on recycling decisions. The proposed algorithm is further evaluated using a set of randomly generated instances. The results show that the algorithm can yield high-quality solutions within a short time. The best configuration of the algorithm is suggested via sensitivity analysis of parameters using the generated instances.
Journal: International Journal of Production Research
Pages: 5615-5632
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1967499
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1967499
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# input file: TPRS_A_1961037_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Husam Dauod
Author-X-Name-First: Husam
Author-X-Name-Last: Dauod
Author-Name: Daehan Won
Author-X-Name-First: Daehan
Author-X-Name-Last: Won
Title: Real-time order picking planning framework for warehouses and distribution centres
Abstract: 
 This paper proposes a dynamic-order picking (DOP) framework where batches and picker routes are continuously modified in response to urgent orders arrival and disruption events. In the proposed framework, we consider conflicts between pickers in narrow aisles to ensure a smooth replanning function. For this purpose, we first formulate a static joint-order batching and sequencing model (J-OBS) that takes into account congestion time. Then, we propose a replanning model (D-J-OBS) that utilises real-time input from multiple information systems. As a solution approach and due to the NP-hardness of the problem, we use a tabu search algorithm to solve practical sizes of the static and the dynamic problems. The results indicate that the DOP framework generates significant tardiness savings compared to online-order picking, especially for systems with high degree of dynamism.
Journal: International Journal of Production Research
Pages: 5468-5487
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1961037
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1961037
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1962017_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Jeffrey Schaller
Author-X-Name-First: Jeffrey
Author-X-Name-Last: Schaller
Author-Name: Jorge M. S. Valente
Author-X-Name-First: Jorge M. S.
Author-X-Name-Last: Valente
Title: Scheduling in a no-wait flow shop to minimise total earliness and tardiness with additional idle time allowed
Abstract: 
 Scheduling jobs in a no-wait flow shop with the objective of minimising total earliness and tardiness is the problem addressed in this paper. Idle time may be needed on the first machine due to the no-wait restriction. A model is developed that shows additional idle can be inserted on the first machine to help reduce earliness. Several dispatching heuristics previously used in other environments were modified and tested. A two-phased procedure was also developed, estimating additional idle in the first phase, and applying dispatching heuristics in the second phase. Several versions of an insertion improvement procedure were also developed. The procedures are tested on instances of various sizes and due date tightness and range. The results show the two-phase heuristics are more effective than the simple rules, and the insertion search improvement procedure can provide considerable improvements.
Journal: International Journal of Production Research
Pages: 5488-5504
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1962017
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1962017
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1966117_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xiao-qiu Shi
Author-X-Name-First: Xiao-qiu
Author-X-Name-Last: Shi
Author-Name: Xue-jiao Yuan
Author-X-Name-First: Xue-jiao
Author-X-Name-Last: Yuan
Author-Name: Ding-shan Deng
Author-X-Name-First: Ding-shan
Author-X-Name-Last: Deng
Title: Research on supply network resilience considering the ripple effect with collaboration
Abstract: 
 Local disruptions can be propagated from one firm to another in a supply network (SN) and eventually influence the whole SN. Therefore, numerous studies on SN resilience considering the ripple effect have been reported recently. However, previous studies paid less attention to this phenomenon from a network structure perspective: if a firm is facing the risk of failure, then its partners may help it to mitigate the risk of failure by collaboration during the process of disruption propagation. Specifically, how SN structures (e.g. characterised by different scaling exponents) and other parameters (e.g. redundancy) influence the effectiveness of collaboration on improving SN resilience considering the ripple effect is not clear. Accordingly, we propose a ripple effect with collaboration (REC) model to consider the aforementioned phenomenon. We also present three new SN resilience metrics to evaluate SN resilience. Then, using both generated (by a novel SN generating model) and real-life SNs, we simulate the SN resilience considering REC under random and targeted disruptions. Our results demonstrate that the effectiveness of collaboration can be affected by SN structures and other parameters, and collaboration can even negatively affect SN resilience in some cases. We also summarise managerial implications and give future research directions.
Journal: International Journal of Production Research
Pages: 5553-5570
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1966117
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1966117
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# input file: TPRS_A_1963876_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Przemysław Ignaciuk
Author-X-Name-First: Przemysław
Author-X-Name-Last: Ignaciuk
Title: Linear-quadratic optimal control of multi-modal distribution systems with imperfect channels*
Abstract: 
 The paper examines the perspectives of linear-quadratic (LQ) optimal control in steering the process of goods distribution in logistic systems with multiple transportation options. In the considered class, the distribution centre governs the stock replenishment process of subordinate depots, from which un uncertain market demand is served. The centre is linked with the depots via shared supply channels with different characteristics regarding delay, reliability, and capacity, e.g. train vs truck delivery. The design objective is a rule of dynamical channel allocation – how many goods to send in a period using a given mode – so that balanced, cost-efficient system performance and high customer service rate are achieved. The received goods are inspected for quality defects and rejected when faulty. Thus, one needs to cope with two major sources of uncertainty: unpredictable demand variations and channel imperfections. A multi-variable LQ optimal controller is designed and presented in closed form for detailed analytical and numerical treatment. It is formally shown that despite perturbations, the controller always establishes a non-negative and upper-bounded replenishment signal, and the stock level does not cross the reference value. Conditions for warehouse space selection and obtaining full demand satisfaction at the depots are specified and formally proved.
Journal: International Journal of Production Research
Pages: 5523-5538
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1963876
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1963876
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# input file: TPRS_A_1959954_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Roberto Cigolini
Author-X-Name-First: Roberto
Author-X-Name-Last: Cigolini
Author-Name: Simone Franceschetto
Author-X-Name-First: Simone
Author-X-Name-Last: Franceschetto
Author-Name: Andrea Sianesi
Author-X-Name-First: Andrea
Author-X-Name-Last: Sianesi
Title: Shop floor control in the VLSI circuit manufacturing: a simulation approach and a case study
Abstract: 
 This paper introduces a new approach to design and model shop floor control techniques for wafer fabs in the very large-scale integrated circuit manufacturing industry. The new model suggests the scheduling system should be selected by considering the type of work centres – whether they are sequential or batch – and the relevance of set-up times and capacity utilisation rate. The proposed scheduling model has been tested via a simulation model of the existing system, and by using data coming from the field, which leads to consider real-life performance to be close to the output of the simulation campaign. The main results point out that the performance of batch work centres – even though they represent a reduced portion of the whole set of work centres – can remarkably affect the performance of the whole fab. In addition, relevant improvements in term of throughput rate and capital productivity can be obtained also at the shop floor level via slack-based dispatching procedures. Results are particularly appealing because they can be implemented in a very short period and without significant infrastructural investments.
Journal: International Journal of Production Research
Pages: 5450-5467
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1959954
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1959954
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# input file: TPRS_A_1963875_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Aura Maria Jalal
Author-X-Name-First: Aura Maria
Author-X-Name-Last: Jalal
Author-Name: Eli Angela Vitor Toso
Author-X-Name-First: Eli Angela Vitor
Author-X-Name-Last: Toso
Author-Name: Reinaldo Morabito
Author-X-Name-First: Reinaldo
Author-X-Name-Last: Morabito
Title: Integrated approaches for logistics network planning: a systematic literature review
Abstract: 
 Researchers and practitioners often separate logistics network planning into strategic, tactical, and operational decisions. Due to the interdependence among these levels of decisions, their integration can bring important cost reductions and better network responsiveness in scenarios where there is business change. However, integrated problems entail challenges, such as decision timing, and they are more difficult to model and solve. This article presents a literature review of integrated problems in logistics network planning. The objective is to identify the main integrated decisions, their scopes, integration approaches, and the solution methods used. Although this review addresses research with decisions at different hierarchical planning levels, we observed that integration of strategic and tactical decisions is more common and some of the integration approaches are single-level mono-period models, single-level multi-period models, multi-time scale models, and multi-level models. There is a predominance of aggregated data in these studies. Regarding the solution methods, there is a predominance of heuristic approaches over exact ones, including methods based on decomposition or sequential procedures. Based on the findings of this systematic review, we draw a conceptual framework presenting the main modelling assumptions, integration strategies, and solution methods to the integrated problems, and we also discuss some promising research opportunities.
Journal: International Journal of Production Research
Pages: 5697-5725
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1963875
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1963875
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# input file: TPRS_A_1966706_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yuqing Zhang
Author-X-Name-First: Yuqing
Author-X-Name-Last: Zhang
Author-Name: Min Xie
Author-X-Name-First: Min
Author-X-Name-Last: Xie
Author-Name: Yihai He
Author-X-Name-First: Yihai
Author-X-Name-Last: He
Author-Name: Wei Dai
Author-X-Name-First: Wei
Author-X-Name-Last: Dai
Title: Product quality monitoring approach considering non-geometric dimensioning data with rapid production process simulation
Abstract: 
 Workpiece is composed of its profile and material. The non-geometric dimensioning interior features of products, such as residual stress, may determine the workpiece material properties and the product performance, which should be included into manufacture quality control. The influence of process parameter uncertainty and fluctuation on state of interior property could not be neglected. In this paper, a novel framework of monitoring workpiece quality considering interior features is presented. In this framework, product quality of interior property is considered. In this framework, a rapid simulation method is proposed to acquire the state of product interior features. According to actual process parameter measured by sensors, this simulation method could calculate simulation results of the workpiece’s non-geometric dimensioning interior features. By extracting data from off-line database and creating an on-line simulation model, the proposed method can finish the simulation of workpiece interior features rapidly. This simulation algorithm is proposed and discussed mathematically based on the multi-subdomain coupling method, and the simulation error is estimated. With the simulation method, this framework could supplement production quality assessment and control criteria. A case study of a rolling production process shows that this method is effective and could be used to monitor workpiece quality in-process.
Journal: International Journal of Production Research
Pages: 5595-5614
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1966706
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1966706
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# input file: TPRS_A_1968526_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Weibo Ren
Author-X-Name-First: Weibo
Author-X-Name-Last: Ren
Author-Name: Yan Yan
Author-X-Name-First: Yan
Author-X-Name-Last: Yan
Author-Name: Yaoguang Hu
Author-X-Name-First: Yaoguang
Author-X-Name-Last: Hu
Author-Name: Yu Guan
Author-X-Name-First: Yu
Author-X-Name-Last: Guan
Title: Joint optimisation for dynamic flexible job-shop scheduling problem with transportation time and resource constraints
Abstract: 
 Dynamic flexible job-shop scheduling is traditionally a challenge in real-world manufacturing systems, especially considering the constraints of transportation resources and transportation time. To address the dynamic optimisation problem in flexible manufacturing systems, this paper proposes a novel proactive-reactive methodology to adapt to the dynamic changes in working environments and addresses the joint scheduling problem for machine tools and transportation resources. The joint optimisation model is first formulated as a mixed-integer programming model considering production efficiency and transportation constraints. The flowchart of the dynamic scheduling system is then designed for dynamic decision-making, and a novel particle swarm optimisation algorithm integrated with genetic operators is developed to respond to dynamic events and generate the reschedule plan in time. Finally, several numerical experiments and case studies in reality are applied to verify the efficiency of the developed methodology. Common dispatching rules and heuristic methods are also applied to test and evaluate the efficiency of the developed algorithm. Computational results demonstrate that the developed methods and decision models are efficient for dynamic job-shop scheduling problems in flexible manufacturing systems, which can acquire rather a good effect in practical production.
Journal: International Journal of Production Research
Pages: 5675-5696
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1968526
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1968526
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# input file: TPRS_A_1964705_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Frank Wiengarten
Author-X-Name-First: Frank
Author-X-Name-Last: Wiengarten
Author-Name: George Onofrei
Author-X-Name-First: George
Author-X-Name-Last: Onofrei
Author-Name: Brian Fynes
Author-X-Name-First: Brian
Author-X-Name-Last: Fynes
Author-Name: Paul Humphreys
Author-X-Name-First: Paul
Author-X-Name-Last: Humphreys
Title: Exploring the quality performance implications of temporary workers: the importance of process capabilities
Abstract: 
 The current pandemic with its associated economic downturn has intensified the pressures on companies to produce quality offerings with an increased pressure on cost controls. Across industries companies have reduced their costs by enhancing their ability to operate flexibly, through increasing the use of temporary workers. However, such a reliance on temporary workers is generally associated with deteriorating quality. In order to untangle the relationship between quality and temporary workers we address the following research questions: (1) What are the quality performance implications of employing temporary workers? and (2) Can process capabilities eliminate the potential quality performance deterioration that are due to temporary workers? Process capabilities are conceptualised through the plant’s level of of-the-art manufacturing processes technology. To address our research questions, we utilise survey data collected through the Global Manufacturing Research Group. The results suggest that an increased usage of temporary workers significantly increases reject rates and customer returns. Furthermore, we identified that managers cannot rely on their processes to safeguard them from quality performance deterioration, when employing temporary workers.
Journal: International Journal of Production Research
Pages: 5539-5552
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1964705
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1964705
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# input file: TPRS_A_1963496_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ganquan Shi
Author-X-Name-First: Ganquan
Author-X-Name-Last: Shi
Author-Name: Zhouwang Yang
Author-X-Name-First: Zhouwang
Author-X-Name-Last: Yang
Author-Name: Yang Xu
Author-X-Name-First: Yang
Author-X-Name-Last: Xu
Author-Name: Yuchen Quan
Author-X-Name-First: Yuchen
Author-X-Name-Last: Quan
Title: Solving the integrated process planning and scheduling problem using an enhanced constraint programming-based approach
Abstract: 
 Due to various factors of flexibility introduced into manufacturing systems, researchers have gradually shifted their focus to the integrated process planning and scheduling (IPPS) problem to improve productivity. The previous literature rarely associates IPPS with constraint programming, even though constraint programming has achieved success in the scheduling field. Furthermore, existing approaches are usually customized to certain types of IPPS problems and cannot handle the general problem. In this paper, with a view to obtaining the optimal AND/OR graph automatically, a depth first search generating algorithm is designed to convert the type-1 IPPS problem into our approach's standard input format. Moreover, we propose an approach based on enhanced constraint programming to cope with the general problem, employing advanced schemes to enhance the constraint propagation and improve the search efficiency. Our approach is implemented on ORTOOLS, and its superiority is verified by testing on 15 benchmarks with 50 instances. Experimental results indicate that 41 instances are solved optimally, among which the optimality of the solutions for 20 instances is newly confirmed, and the solutions of six instances are improved. Our approach is the first method to reach the overall optimum in the most influential benchmark with 24 instances.
Journal: International Journal of Production Research
Pages: 5505-5522
Issue: 18
Volume: 60
Year: 2022
Month: 09
X-DOI: 10.1080/00207543.2021.1963496
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1963496
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# input file: TPRS_A_1976859_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Felipe Alexandre de Lima
Author-X-Name-First: Felipe Alexandre
Author-X-Name-Last: de Lima
Author-Name: Stefan Seuring
Author-X-Name-First: Stefan
Author-X-Name-Last: Seuring
Author-Name: Philipp C. Sauer
Author-X-Name-First: Philipp C.
Author-X-Name-Last: Sauer
Title: A systematic literature review exploring uncertainty management and sustainability outcomes in circular supply chains
Abstract: 
 The circular economy (CE) has inspired the emergence of circular supply chains (CSCs) to reduce the environmental impacts of linear production systems. However, the transition to CSCs faces numerous challenges and uncertainties, which in turn impact the sustainability performance of CSCs. Following a systematic review process, this paper aims to identify the uncertainties that CSCs entail and the uncertainty management strategies which can be used to mitigate them to enhance their sustainability performance. A conceptual framework is proposed under which the current literature on CSCs, including 106 peer-reviewed English journal articles, is analysed and discussed based on CE practices, uncertainty management, and sustainability performance indicators. This framework offers guidance to CE and CSC scholars and supports practitioners and policymakers in being aware of the uncertainties related to the operationalisation and implementation of the CE in order to offer CE-inspired solutions. This paper also proposes a research agenda to investigate the integration of CE practices with supply chain management; the ways in which organisations manage different uncertainties simultaneously; and the effect of multiple uncertainty management strategies on firms’ sustainability performance.
Journal: International Journal of Production Research
Pages: 6013-6046
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1976859
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1976859
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# input file: TPRS_A_1969048_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Antoine Perraudat
Author-X-Name-First: Antoine
Author-X-Name-Last: Perraudat
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Scott Jennings Mason
Author-X-Name-First: Scott Jennings
Author-X-Name-Last: Mason
Title: Stochastic programming approaches for an energy-aware lot-sizing and sequencing problem with incentive
Abstract: 
 Motivated by real challenges on energy management faced by industrial firms, we propose a novel way to reduce production costs by including the pricing of electricity in a multi-product lot-sizing problem. In incentive-based programs, when electric utilities face power consumption peaks, they request electricity-consuming firms to curtail their electric load, rewarding the industrial firms with incentives if they comply with the curtailment requests. Otherwise, industrial firms must pay financial penalties for an excessive electricity consumption. A two-stage stochastic formulation is presented to cover the case where a manufacturer wants to satisfy any curtailment request. A chance-constrained formulation is also proposed, and its relevance in practice is discussed. Finally, computational studies are conducted to compare mathematical models and highlight critical parameters and show potential savings when subscribing incentive-based programs. We show that the setup cost ratio, the capacity utilisation rate, the number of products and the timing of curtailment requests are critical parameters for manufacturers.
Journal: International Journal of Production Research
Pages: 5746-5768
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1969048
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1969048
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# input file: TPRS_A_1974115_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Neven Hadžić
Author-X-Name-First: Neven
Author-X-Name-Last: Hadžić
Author-Name: Viktor Ložar
Author-X-Name-First: Viktor
Author-X-Name-Last: Ložar
Author-Name: Tihomir Opetuk
Author-X-Name-First: Tihomir
Author-X-Name-Last: Opetuk
Author-Name: Jerolim Andrić
Author-X-Name-First: Jerolim
Author-X-Name-Last: Andrić
Title: The Bernoulli splitting line: analytical and semi-analytical evaluation of the steady-state performance
Abstract: 
 Many industrial facilities involve splitting production systems of different complexities and arrangements. The accurate and efficient evaluation of the associated performance measures is, therefore, of great importance. This challenging task can be accomplished by applying mathematical models of production system engineering at different intricacies. This paper presents the development and application of the analytical approach to splitting production systems modelling. The same problem is also addressed using the finite state method as a semi-analytical model. Several theoretical examples were considered to validate the finite state method that proved to be quite efficient and accurate. Finally, the developed modelling approach was applied in the case of a wood-processing facility. The obtained results were validated successfully against the acquired factory-floor data.
Journal: International Journal of Production Research
Pages: 5912-5936
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1974115
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1974115
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# input file: TPRS_A_1970846_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Kasin Ransikarbum
Author-X-Name-First: Kasin
Author-X-Name-Last: Ransikarbum
Author-Name: Scott J. Mason
Author-X-Name-First: Scott J.
Author-X-Name-Last: Mason
Title: A bi-objective optimisation of post-disaster relief distribution and short-term network restoration using hybrid NSGA-II algorithm
Abstract: 
 Humanitarian logistics research has recently received tremendous interest from researchers and practitioners due to its importance in assisting relief operations. While there is an increasing trend for mathematical models related to preparedness and response phases for disaster operations management, recovery-phase models are not as emphasised as other phases due to scarce data and model complication from NP-hard nature of the models. One particular approach that can provide a sufficiently good solution for the NP-hard problems is the metaheuristic approach. In this research, we explore the bi-criteria integrated response and recovery model for making strategic post-disaster decisions in the relief distribution and short-term network restoration. Next, with a focus on considering conflicting objectives between fairness and cost of this problem, we propose a hybrid approach with its evolutionary component based on the non-dominated sorting genetic algorithm-II (NSGA-II) called HNSGA-II. The proposed HNSGA-II is compared against the exact method using the approximate Pareto-front analysis. The proposed algorithm is verified using a case study from a risk assessment tool called Hazus to illustrate how to cope with the aftermath of an earthquake. Finally, results are evaluated using a Hypervolume-based technique and computation time to illustrate the efficiency of the proposed algorithm.
Journal: International Journal of Production Research
Pages: 5769-5793
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1970846
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1970846
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# input file: TPRS_A_1968527_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Serena Finco
Author-X-Name-First: Serena
Author-X-Name-Last: Finco
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Alessandro Persona
Author-X-Name-First: Alessandro
Author-X-Name-Last: Persona
Title: A Joint Assembly Line Balancing and Feeding Problem (JALBFP) considering direct and indirect supply strategies
Abstract: 
 In an assembly system, balancing the line and designing the part feeding setting play a fundamental role in guaranteeing efficiency and effectiveness. Although these two aspects are interrelated, they are usually performed subsequent to each other, with the part feeding decisions only being made once the line has already been balanced. However, the simultaneous solving of the assembly line balancing and part feeding problems can lead to interesting benefits. In this paper, an innovative approach for solving the Joint Assembly Line Balancing and Feeding Problem (JALBFP) is proposed, to achieve an integrated balancing of assembly tasks and parts picking/kitting and a fully synchronised assembly-feeding system. The aim is to minimise the operational system cost, including workforce, space and transportation costs. The Mixed Integer Linear Programming (MILP) model is applied to several instances and two case studies and compared to a hierarchical approach. The proposed model leads to a significant improvement in reducing the number of assembly stations required and the inventory level at the line, where space is notoriously scarce, also avoiding workforce oversizing in the feeding system. The strength of the model relies on its formulation and on its versatility, which makes it applicable to different assembly sectors.
Journal: International Journal of Production Research
Pages: 5727-5745
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1968527
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1968527
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# input file: TPRS_A_1973136_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Régis Chenavaz
Author-X-Name-First: Régis
Author-X-Name-Last: Chenavaz
Author-Name: Walid Klibi
Author-X-Name-First: Walid
Author-X-Name-Last: Klibi
Author-Name: Rainer Schlosser
Author-X-Name-First: Rainer
Author-X-Name-Last: Schlosser
Title: Dynamic pricing with reference price effects in integrated online and offline retailing
Abstract: 
 Omnichannel retailing is of growing importance. Yet, retailers lack knowledge about how to set prices overtime in their different channels, that is, in-store and online, which gives rise to a dual-channel pricing problem. The retailing issue is even more salient when consumers are prone to a psychological element, that is, when a reference price exerts influence. This article fills the gap by offering an analytical model of intertemporal price setting for dual channel pricing problem. We present an optimal control framework of dynamic pricing when (1) consumer behaviour is prone to a reference price and (2) the online channel is subject to the last-mile delivery cost. Analytical results, which hold for a general (nonlinear) reference-dependent demand formulation, inform about the relationships between the store and online prices over time and also about the market power of the retailer in each channel. Numerical results describe the features of three different phases of the planning horizon. The managerial recommendations show how a retailer sets differentiated dynamic pricing policies when offline and online channels are integrated. Such recommendations pave the way to more profitable omnichannel management.
Journal: International Journal of Production Research
Pages: 5854-5875
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1973136
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1973136
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# input file: TPRS_A_1972179_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Andreas Kuhnle
Author-X-Name-First: Andreas
Author-X-Name-Last: Kuhnle
Author-Name: Marvin Carl May
Author-X-Name-First: Marvin Carl
Author-X-Name-Last: May
Author-Name: Louis Schäfer
Author-X-Name-First: Louis
Author-X-Name-Last: Schäfer
Author-Name: Gisela Lanza
Author-X-Name-First: Gisela
Author-X-Name-Last: Lanza
Title: Explainable reinforcement learning in production control of job shop manufacturing system
Abstract: 
 Manufacturing in the age of Industry 4.0 can be characterised by a high product variety and complex material flows. The increasing individualisation of products requires adaptive production planning and control systems. Research in the area of Machine Learning demonstrates the applicability and potential of Reinforcement Learning (RL) systems for the control of complex manufacturing. However, a major disadvantage of RL-methods is that they are usually considered as ‘black box’ models. For this reason, this paper investigates methods of explainable reinforcement learning in production control. Based on a comprehensive literature review an approach to increase the plausibility of RL-based control strategies is presented. The approach combines the advantages of high prediction accuracy (e.g. neural networks) and high explainability (e.g. decision trees). In doing so, understandable control strategies such as heuristics can be generated, and an advanced RL-system can be designed including specific domain expertise. The results are demonstrated based on a real-world system, taken from semiconductor manufacturing, which is investigated in a simulated approach.
Journal: International Journal of Production Research
Pages: 5812-5834
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1972179
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1972179
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# input file: TPRS_A_1973684_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ufuk Bahçeci
Author-X-Name-First: Ufuk
Author-X-Name-Last: Bahçeci
Author-Name: Temel Öncan
Author-X-Name-First: Temel
Author-X-Name-Last: Öncan
Title: An evaluation of several combinations of routing and storage location assignment policies for the order batching problem
Abstract: 
 In this work, we address the Order Batching Problem (OBP) and we devise tailor-made Mixed Integer Linear Programming (MILP) formulations of the OBP considering composite, largest gap and optimum routing policies, for the first time. We also introduce a novel picker routing policy named as mixed policy which combines the properties of both midpoint and return routing policies. Then, we perform extensive computational experiments with MILP formulations of the OBP considering several combinations of routing and storage policies under different operating conditions on randomly generated test instances. Finally, we present several managerial insights based on the computational results.
Journal: International Journal of Production Research
Pages: 5892-5911
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1973684
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1973684
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# input file: TPRS_A_1977408_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Moritz von Stietencron
Author-X-Name-First: Moritz
Author-X-Name-Last: von Stietencron
Author-Name: Karl Hribernik
Author-X-Name-First: Karl
Author-X-Name-Last: Hribernik
Author-Name: Katerina Lepenioti
Author-X-Name-First: Katerina
Author-X-Name-Last: Lepenioti
Author-Name: Alexandros Bousdekis
Author-X-Name-First: Alexandros
Author-X-Name-Last: Bousdekis
Author-Name: Marco Lewandowski
Author-X-Name-First: Marco
Author-X-Name-Last: Lewandowski
Author-Name: Dimitris Apostolou
Author-X-Name-First: Dimitris
Author-X-Name-Last: Apostolou
Author-Name: Gregoris Mentzas
Author-X-Name-First: Gregoris
Author-X-Name-Last: Mentzas
Title: Towards logistics 4.0: an edge-cloud software framework for big data analytics in logistics processes
Abstract: 
 Logistics 4.0 aims at enabling the sustainable satisfaction of customer demands with optimised costs of services with the use of emerging technologies, such as Internet of Things, streaming analytics, and optimised decision making. The availability of massive sensor data streams over time opens new perspectives for extracting meaningful and timely insights from data-in-motion through streaming analytics. Logistics 4.0 is a relatively new field of research which demands the development of scalable and efficient software solutions and their deployment to successful real-life case studies. In this paper, we propose a software framework for streaming analytics in an edge-cloud computational environment aiming at covering the whole data analytics lifecycle in logistics processes and thus, advancing the evolution and realisation of the Logistics 4.0 concept. The proposed framework takes advantage of edge computing technologies, streaming analytics and proactive decision making in order to monitor, analyse and support decision making in the frame of Logistics 4.0. It is applied and evaluated in a maintenance service logistics use case from the aerospace industry.
Journal: International Journal of Production Research
Pages: 5994-6012
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1977408
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1977408
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# input file: TPRS_A_1973135_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ashutosh Mishra
Author-X-Name-First: Ashutosh
Author-X-Name-Last: Mishra
Author-Name: Priyanka Verma
Author-X-Name-First: Priyanka
Author-X-Name-Last: Verma
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: A circularity-based quality assessment tool to classify the core for recovery businesses
Abstract: 
 To realise circularity in the management of used materials and associated recovery practices for value creation, a circularity-based quality assessment tool (CQAT) is proposed in this study. The issue is addressed with core classification based on quality factors assessing circularity at the product level. A circularity-based quality indicator (QI) is developed that classifies the core into reusable, remanufacturable, and recyclable (3R) at the acquisition phases of the core retrieval system. For the validation of CQAT, four real cases of small-medium-sized dismantling firms dealing with engines, motor gearboxes, motor pumps, and refrigerators involved in remanufacturing activities are analysed. The study employs an integrative coefficient correlation maximisation approach (CCMA) and whitenization weight functions (WWF) clustering model that estimates the priorities of regenerative and restorative actions. The result reveals that the severe damage with high disassembly processing time due to destructive disassembly in the post-acquisition phase is highly critical to the circularity of the retrieval system. It exhibits that damage, processing time, value retention classify core into lowest grade at acquisition phases. Since possibilities of value recovery are lost, firms are least concerned with social and environmental considerations. Additionally, the design and functionality dimensions in the inspection majorly classify cores into remanufacturable.
Journal: International Journal of Production Research
Pages: 5835-5853
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1973135
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1973135
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# input file: TPRS_A_1975058_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ece Sanci
Author-X-Name-First: Ece
Author-X-Name-Last: Sanci
Author-Name: Mark S. Daskin
Author-X-Name-First: Mark S.
Author-X-Name-Last: Daskin
Author-Name: Young-Chae Hong
Author-X-Name-First: Young-Chae
Author-X-Name-Last: Hong
Author-Name: Steve Roesch
Author-X-Name-First: Steve
Author-X-Name-Last: Roesch
Author-Name: Don Zhang
Author-X-Name-First: Don
Author-X-Name-Last: Zhang
Title: Mitigation strategies against supply disruption risk: a case study at the Ford Motor Company
Abstract: 
 Supply chains are exposed to different risks, which can be mitigated by various strategies based on the characteristics and needs of companies. In collaboration with Ford, we develop a decision support framework to choose the best mitigation strategy against supply disruption risk, especially for companies operating with a small supplier base and low inventory levels. Our framework is based on a multistage stochastic programming model which incorporates a variety of plausible strategies, including reserving backup capacity from the primary supplier, reserving capacity from a secondary supplier, and holding backup inventory. We reflect disruption risk into the framework through decision makers’ input on the time to recover and the disruption probability. Our results demonstrate that relying on the strategy which is optimal when there is no disruption risk can increase the expected total cost substantially in the presence of disruption risk. However, this increase can be reduced significantly by investing in the mitigation strategy recommended by our framework. Our results also show that this framework removes the burden of estimating the time to recover and the disruption probability precisely since there is often a small loss associated with using another strategy that is optimal in the neighbourhood of the estimated values.
Journal: International Journal of Production Research
Pages: 5956-5976
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1975058
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1975058
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# input file: TPRS_A_1977407_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yuwei Lu
Author-X-Name-First: Yuwei
Author-X-Name-Last: Lu
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Author-Name: Na Geng
Author-X-Name-First: Na
Author-X-Name-Last: Geng
Author-Name: Shan Jiang
Author-X-Name-First: Shan
Author-X-Name-Last: Jiang
Author-Name: Xiaolan Xie
Author-X-Name-First: Xiaolan
Author-X-Name-Last: Xie
Title: Appointment window scheduling with wait-dependent abandonment for elective inpatient admission
Abstract: 
 In this study, we propose a new appointment window scheduling (AWS) approach of informing customers of an admission window (AW) rather than the traditional appointment time. We provide a formal description of this AWS problem for only one kind of customer and propose a dedicated chance-constrained policy to assign AWs dynamically under the condition with fixed service capacity, different scales as well as status in different waiting stages, and wait-dependent abandonment. Numerical experiments show that customer satisfaction can be significantly improved (by reducing over 60% of wait-but-abandon events and by reducing 90% of departures caused by waiting beyond the AW), and server utilisation is slightly improved. And the improvements are more significant when systems are overloaded, and customers are more sensitive to online waiting than offline waiting. The AWS scenario can also be applied to other queueing systems as long as it is possible and profitable to let customers wait outside of the waiting area.
Journal: International Journal of Production Research
Pages: 5977-5993
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1977407
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1977407
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# input file: TPRS_A_1975057_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Peng Cheng Luo
Author-X-Name-First: Peng Cheng
Author-X-Name-Last: Luo
Author-Name: Huan Qian Xiong
Author-X-Name-First: Huan Qian
Author-X-Name-Last: Xiong
Author-Name: Bo Wen Zhang
Author-X-Name-First: Bo Wen
Author-X-Name-Last: Zhang
Author-Name: Jie Yang Peng
Author-X-Name-First: Jie Yang
Author-X-Name-Last: Peng
Author-Name: Zhao Feng Xiong
Author-X-Name-First: Zhao Feng
Author-X-Name-Last: Xiong
Title: Multi-resource constrained dynamic workshop scheduling based on proximal policy optimisation
Abstract: 
 Multi-resource constrained dynamic workshop scheduling is a complex and challenging task in discrete manufacturing. In this paper, to obtain a high-performance scheduling in limited time, this problem is modelled into a Markov decision process, and solved by proximal policy optimisation algorithm, which can learn from the simulated workshop environment directly. A multi-modal hybrid neural network is used in the model to make good use of numerical state features representing workshop environment information and graphical state features representing constraint information during the learning process. Multi-label technique is used in this paper to decouple the output acts of jobs, machines, tools, and workers. Action mask technique coding the constraints is also used to prune invalid exploration. The experimental results show that compared with heuristic rules such as weighted shortest processing time, weighted modified due date, weighted cost over time, apparent tardiness cost and other reinforcement learning methods such as DeepRM and DeepRM2, the performance of the proposed method is at least 
 $ 1.138\% $ 1.138% better in scheduling penalty.
Journal: International Journal of Production Research
Pages: 5937-5955
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1975057
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1975057
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# input file: TPRS_A_1973137_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Gongshu Wang
Author-X-Name-First: Gongshu
Author-X-Name-Last: Wang
Author-Name: Qingxin Guo
Author-X-Name-First: Qingxin
Author-X-Name-Last: Guo
Author-Name: Wenjie Xu
Author-X-Name-First: Wenjie
Author-X-Name-Last: Xu
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Title: A graph partitioning based cooperative coevolution for the batching problem in steelmaking production
Abstract: 
 This paper studies a common planning problem encountered in steelmaking production. The problem is to group different customer orders into a set of batches to accommodate the mass production mode of steelmaking furnaces. We formulate the problem as a novel mixed-integer programming model by considering the practical technological requirements. To solve the problem, we propose a cooperative coevolution framework in which an effective decomposition scheme based on graph partitioning is developed. The decomposition scheme first explores the problem structure by considering the production process rules and then exploits the batch information of the best-so-far solution to identify the potentially better decompositions. To solve each decomposed subcomponent, we propose a new differential evolution algorithm which incorporates a subpopulation-based classification mechanism and local search with an external archive strategy to balance the abilities of exploration and exploitation. Computational tests on a set of real production data as well as on a more diverse set of randomly generated problem instances show that our method is effective and efficient in practical application and outperforms other benchmark algorithms.
Journal: International Journal of Production Research
Pages: 5876-5891
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1973137
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1973137
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# input file: TPRS_A_2117224_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: The Editors
Title: Correction
Journal: International Journal of Production Research
Pages: 6047-6047
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2022.2117224
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2117224
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# input file: TPRS_A_1970847_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ardavan Asef-Vaziri
Author-X-Name-First: Ardavan
Author-X-Name-Last: Asef-Vaziri
Author-Name: Morteza Kazemi
Author-X-Name-First: Morteza
Author-X-Name-Last: Kazemi
Author-Name: Maryam Radman
Author-X-Name-First: Maryam
Author-X-Name-Last: Radman
Title: The facility layout instances of the generalised travelling salesman problem
Abstract: 
 In this paper, we provide new insight into the problem of designing loop flow-patterns and input-output (I/O) stations in a facility layout to minimise the summation of loaded and empty trip distances. The loop covering at least one contourline of each workcenter in a manufacturing facility layout is an instance of the generalised travelling salesman problem (GTSP). The shortest length solution to this GTSP provides a promising heuristic scheme to minimise the total loaded and empty flow in vehicle-based material handling. The sequence of the I/O stations alongside the loop also plays a significant role in determining the volume of the loaded and empty flow. The larger the set of candidate locations for I/O stations, the higher the flexibility in sequencing the stations. On this foundation, we define a new objective function of maximal-node-covering for our instance of the GTSP. By combining the characteristics of the shortest and the maximal-node-covering loops, a set of complementary heuristics are developed to design a loop and locate the I/O stations to minimise the total loaded and empty flow.
Journal: International Journal of Production Research
Pages: 5794-5811
Issue: 19
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1970847
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1970847
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# input file: TPRS_A_1991022_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Azin Setayesh
Author-X-Name-First: Azin
Author-X-Name-Last: Setayesh
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Title: Determining the source of human-system errors in manual order picking with respect to human factors
Abstract: 
 Order picking (OP) is a time- and labour-intensive operation in which human-system errors can lead to deficiencies in quality. This study aimed to identify human factors-related failure modes that cause human-system errors and quality deficits in OP. We conducted a systematic literature review and qualitative interviews with 38 order pickers employed by 14 different companies in four countries. The literature review found 46 papers that identified eight different failure modes related to OP system design: physical workload, physical fatigue, mental fatigue, complexity, memory demand, vision, hearing, and motivation. The interview results confirmed many of the same factors noted in the literature review but also identified communication and supervision failure modes that had not been addressed before. The results illustrate human factors-related failure modes linked to OP system design, operation, and management that ultimately increase quality deficits and pick errors. Further research on human factors and OP system design interaction is warranted, as no assessment tool has been found to support engineers and managers seeking to improve system designs to reduce pick errors.
Journal: International Journal of Production Research
Pages: 6350-6372
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1991022
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1991022
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# input file: TPRS_A_1987549_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Fatima Ezzahra Achamrah
Author-X-Name-First: Fatima Ezzahra
Author-X-Name-Last: Achamrah
Author-Name: Fouad Riane
Author-X-Name-First: Fouad
Author-X-Name-Last: Riane
Author-Name: Sabine Limbourg
Author-X-Name-First: Sabine
Author-X-Name-Last: Limbourg
Title: Solving inventory routing with transshipment and substitution under dynamic and stochastic demands using genetic algorithm and deep reinforcement learning
Abstract: 
 In this paper, we investigate a two-level supply chain consisting of a company which manufactures a set of products and distributes them via its central warehouse to a set of customers. The problem is modelled as a dynamic and stochastic inventory routing problem (DSIRP) that considers two flexible instruments of transshipment and substitution to mitigate shortages at the customer level. A new resolution approach, based on the hybridisation of mathematical modelling, Genetic Algorithm and Deep Reinforcement Learning is proposed to handle the combinatorial complexity of the problem at hand. Tested on the 150 most commonly used benchmark instances for single-vehicle-product DSIRP, results show that the proposed algorithm outperforms the current best results in the literature for medium and large instances. Moreover, 450 additional instances for multi-products DSIRP are generated. Different demand distributions are examined in these experiments, namely, Normal distribution, Poisson distribution for demand occurrence, combined with demands of constant size; Stuttering Poisson distribution and Negative Binomial distribution. In terms of managerial insights, results show the advantages of promoting inventory sharing and substitutions on the overall supply chain performance.
Journal: International Journal of Production Research
Pages: 6187-6204
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1987549
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1987549
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# input file: TPRS_A_1985736_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Pedram Farghadani-Chaharsooghi
Author-X-Name-First: Pedram
Author-X-Name-Last: Farghadani-Chaharsooghi
Author-Name: Pooria Kamranfar
Author-X-Name-First: Pooria
Author-X-Name-Last: Kamranfar
Author-Name: Mohammad Seyed Mirzapour Al-e-Hashem
Author-X-Name-First: Mohammad Seyed
Author-X-Name-Last: Mirzapour Al-e-Hashem
Author-Name: Yacine Rekik
Author-X-Name-First: Yacine
Author-X-Name-Last: Rekik
Title: A joint production-workforce-delivery stochastic planning problem for perishable items
Abstract: 
 Despite the existence of a rich literature on Production Routing Problem (PRP), the lack of investigations on the workforce planning, and its impact on costs and productivity of the organisation caught our attention. This paper aims to fill this gap by designing a novel framework to integrate inventory, production, distribution, routing, and workforce planning decisions simultaneously. Because of the potential long distances between the main plant and the retailers spread throughout the country and also the perishability nature of the products, considering travelling time uncertainty for delivering products is necessary to have feasible decisions. The application of the proposed approach is investigated by being inspired from a supply chain structure from a knowledge-based company. We derive managerial insights on the benefit of an integrated decision. Besides, given the size and complexity of the proposed problem, we were challenged by exactly solving it in a reasonable time. We succeeded to reach this target by designing an innovative hybrid algorithm. Computational experiments on several numerical examples applied on both the studied real case and on PRP literature instances reveal the effectiveness and efficiency of our new hybrid method and permits to derive interesting managerial insights on the joint decisions.
Journal: International Journal of Production Research
Pages: 6148-6172
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1985736
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1985736
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1979680_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Puwadol Oak Dusadeerungsikul
Author-X-Name-First: Puwadol Oak
Author-X-Name-Last: Dusadeerungsikul
Author-Name: Xiang He
Author-X-Name-First: Xiang
Author-X-Name-Last: He
Author-Name: Maitreya Sreeram
Author-X-Name-First: Maitreya
Author-X-Name-Last: Sreeram
Author-Name: Shimon Y. Nof
Author-X-Name-First: Shimon Y.
Author-X-Name-Last: Nof
Title: Multi-agent system optimisation in factories of the future: cyber collaborative warehouse study
Abstract: 
 The rapid advancement of technologies leading to automation 5.0 has challenged manufacturers preparing for factories of the future, including warehouses, which are considered a key element in supply chains. Because of technologies such as warehouse robots, Internet of Things, Internet of Services, and cyber-augmented collaboration, the traditional warehouse system structure has been changed, improving its performances significantly. The challenges, however, are how to design a system with multi-agents and technologies to reach maximum potential. In this study, a new collaborative workflow protocol for cyber collaborative warehouse, called Collaboration Requirement Planning protocol for HUB-CI (CRP-H), is developed for optimising the collaborative workflow of a warehouse multi-agent system. The two phases of CRP-H are designed to answer questions: (1) Which robot(s) should execute which task? and (2) When should this task be executed? Results show (with statistical significance) that under CRP-H, total operational cost reduces by 11.84%, and total weighted completion time reduces by 37.11%. When the system has unplanned requests, CRP-H can still reduce total operational cost by 5.70% and total weighted completion time by 10.11%. Lastly, CRP-H, which enables a human input integrated into the design, can also reduce the total operational cost even when critical information is missing.
Journal: International Journal of Production Research
Pages: 6072-6086
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1979680
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1979680
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# input file: TPRS_A_1989076_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Dengyu Li
Author-X-Name-First: Dengyu
Author-X-Name-Last: Li
Author-Name: Kaibo Wang
Author-X-Name-First: Kaibo
Author-X-Name-Last: Wang
Title: A multisource domain adaptation method for quality prediction in small-batch production systems
Abstract: 
 Quality prediction for small-batch production processes is a complex problem due to limitations in available training samples. In this study, a multisource domain adaptation joint-Y partial least square (PLS) method is proposed to learn the similarities between domains and use them to construct a quality prediction model. Without constraints on the number of source and target domains, the proposed method can transfer more historical information for the in-operation process than traditional methods. Numerical experiments and a real-world case study of quality prediction in computer wafer production are performed to verify the effectiveness of the proposed method. The results show that the prediction accuracy of the proposed method is high in cases with few training samples in the target domain compared to the accuracies of the joint-Y PLS model and the traditional PLS model.
Journal: International Journal of Production Research
Pages: 6268-6281
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1989076
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# input file: TPRS_A_1991021_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Feng Li
Author-X-Name-First: Feng
Author-X-Name-Last: Li
Author-Name: Xin Guo
Author-X-Name-First: Xin
Author-X-Name-Last: Guo
Author-Name: Li Zhou
Author-X-Name-First: Li
Author-X-Name-Last: Zhou
Author-Name: Jianjun Wu
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wu
Author-Name: Tongfei Li
Author-X-Name-First: Tongfei
Author-X-Name-Last: Li
Title: A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation
Abstract: 
 Working from home becomes the norm; this trend has put added pressure on urban logistics, as large volumes of goods and services are required for domestic use. Meanwhile, public transport operators face a big challenge and trade-off due to higher labour and frequent cleaning costs, with lower passenger revenue over a longer period. Considering the collaborative urban public transport services achieve a seamless movement for both passengers and goods, and could reduce the adverse effects of the existing urban public transport systems. Therefore, a mixed-integer linear programming model introducing the concept of capacity matching is proposed to assist this collaborative urban freight service network in minimising total freight transport time at station hubs and not affecting passenger transportation in this paper. Moreover, an efficient improved optimisation algorithm based on the Artificial Bee Colony Algorithm (ABC) is designed, and the numerical examples and real cases are illustrated to demonstrate the feasibility and effectiveness of the proposed model and algorithm. The performance evaluations suggest that the coordinated operating strategy of the collaborative freight transportation system supports increasing mobility demands for freight, resulting in declining congestion levels and reducing transport emissions, while no influence in passenger transport, notably in urban areas.
Journal: International Journal of Production Research
Pages: 6303-6328
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1991021
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1987550_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Mohammad Rohaninejad
Author-X-Name-First: Mohammad
Author-X-Name-Last: Rohaninejad
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Author-Name: Behdin Vahedi-Nouri
Author-X-Name-First: Behdin
Author-X-Name-Last: Vahedi-Nouri
Author-Name: Zdeněk Hanzálek
Author-X-Name-First: Zdeněk
Author-X-Name-Last: Hanzálek
Author-Name: Shadi Shirazian
Author-X-Name-First: Shadi
Author-X-Name-Last: Shirazian
Title: A hybrid learning-based meta-heuristic algorithm for scheduling of an additive manufacturing system consisting of parallel SLM machines
Abstract: 
 Additive manufacturing (AM) has been recognised as a promising technology under the context of Industry 4.0, which is reshaping manufacturing paradigms. A prominent type of AM machine is the selective laser melting (SLM) machine, in which several parts may form a job and be produced concurrently. This paper aims to investigate a scheduling problem in an AM system with non-identical parallel SLM machines. Since, in this system, there might be differences in the material types of parts, the required setup time between two consecutive jobs on the relevant machine is dependent on their material types. Accordingly, a bi-objective mathematical model is extended for the problem, considering the makespan and the total tardiness penalty as two objective functions. Due to the high complexity of the problem, an efficient hybrid meta-heuristic algorithm is developed by combining the non-dominated sorting genetic algorithm (NSGA-II) with a novel learning-based local search founded on the k-means clustering algorithm and a regression neural network. The local search enhances the exploitation ability of the NSGA-II while intelligently being taught during the solving procedure. Finally, the superiority of the proposed hybrid algorithm is demonstrated through a computational experiment.
Journal: International Journal of Production Research
Pages: 6205-6225
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1987550
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# input file: TPRS_A_1985182_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Farnoosh Naderkhani
Author-X-Name-First: Farnoosh
Author-X-Name-Last: Naderkhani
Title: Time to signal distribution of multivariate bayesian control chart with dual sampling scheme
Abstract: 
 The ability of a control chart to detect a shift in the process can be determined by the average run length (ARL), a widely used performance indicator for single sampling interval (SSI) control charts. When it comes to variable sampling interval (VSI) schemes, average time to signal (ATS) is utilized instead of ARL. Although analysis of ARL has been extensively studied for SSI schemes, calculation of the ATS for VSI control charts is still in its infancy due to several theoretical challenges. In this context, the paper derives closed-form expressions for time to signal distribution and the ATS for a spatial design of VSI multivariate Bayesian control chart referred to as the dual sampling scheme (DSS). In a DSS strategy, the process is being monitored initially with a longer sampling interval, which is changed to the shorter sampling interval at a designed switching point. Unlike previous approximate developments where the switching point is ignored, the paper derives exact expressions for computation of time to signal distribution and ATS within such a Bayesian framework. Derivations of the ATS are based on an intuitively pleasing definition of an artificial absorbing state and coded values of the posterior probability using Markov chain theory.
Journal: International Journal of Production Research
Pages: 6124-6147
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1985182
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2044537_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Imen Khettabi
Author-X-Name-First: Imen
Author-X-Name-Last: Khettabi
Author-Name: Lyes Benyoucef
Author-X-Name-First: Lyes
Author-X-Name-Last: Benyoucef
Author-Name: Mohamed Amine Boutiche
Author-X-Name-First: Mohamed
Author-X-Name-Last: Amine Boutiche
Title: Sustainable multi-objective process planning in reconfigurable manufacturing environment: adapted new dynamic NSGA-II vs New NSGA-III
Abstract: 
 The highly competitive and volatile market puts companies in a tough position. While cost and time efficiency are important to stay competitive, environmental awareness is more and more critical. The reconfigurable manufacturing system (RMS) paradigm is suggested to cope with these new challenges. In addition to its six fundamental characteristics, it is seen as an enabler for Industry 4.0. This article investigates the multi-objective process planning problem in an environmentally conscious manner in a reconfigurable manufacturing environment. Four criteria are minimised: total production cost, total production time, total amount of greenhouse gas produced by machines, and total quantity of hazardous liquid wastes. To address the problem, modified versions of the non-dominated sorting genetic algorithm (NSGA) method, namely new dynamic NSGA-II (NewD-NSGA-II) and New NSGA-III, are developed and evaluated. Rich experimental results are presented and analysed using three metrics to demonstrate the efficacy of the proposed approaches: inverted generational distance (IGD), diversity measure (DM), and cardinality of the mixed Pareto fronts (CMPF). The effects of the similarity coefficient on the convergence of the NewD-NSGA-II and New NSGA-III are investigated, and the TOPSIS technique is used to assist the decision-maker in evaluating and selecting the best process plans.
Journal: International Journal of Production Research
Pages: 6329-6349
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2022.2044537
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2044537
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# input file: TPRS_A_1978576_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Christoph G. Schmidt
Author-X-Name-First: Christoph G.
Author-X-Name-Last: Schmidt
Author-Name: Tingting Yan
Author-X-Name-First: Tingting
Author-X-Name-Last: Yan
Author-Name: Stephan M. Wagner
Author-X-Name-First: Stephan M.
Author-X-Name-Last: Wagner
Author-Name: Lorenzo Lucianetti
Author-X-Name-First: Lorenzo
Author-X-Name-Last: Lucianetti
Title: Performance implications of knowledge inputs in inter-organisational new product development projects: the moderating roles of technology interdependence
Abstract: 
 Successful inter-organisational new product development (NPD) is a key source of competitive advantage, yet many NPD projects are still failing. To generate new insights on the phenomenon, we examine the performance implications of knowledge inputs among collaborating organisations, both in terms of external input ratio and input concentration. We test a set of hypotheses using multi-industry primary and secondary data on 210 inter-organisational NPD projects. Results support our hypotheses about the negative effect of input concentration on design quality, which in turn is positively associated with product market performance. Although we surprisingly find a negative linear effect of external input ratio on design quality, our post-hoc analysis confirms the relationship to be an inverse U-shaped relationship. We also find support for the roles of technology interdependence in moderating the performance implications of external input ratio and input concentration. By clarifying how knowledge inputs affect project outcomes under different levels of technology interdependence, the study provides managerial implications regarding how to select innovation partners in order to create a knowledge portfolio that best improves NPD project performance.
Journal: International Journal of Production Research
Pages: 6048-6071
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1978576
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# input file: TPRS_A_1991020_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ebru Gökalp
Author-X-Name-First: Ebru
Author-X-Name-Last: Gökalp
Author-Name: Veronica Martinez
Author-X-Name-First: Veronica
Author-X-Name-Last: Martinez
Title: Digital transformation maturity assessment: development of the digital transformation capability maturity model
Abstract: 
 The use of on-premises technology in the business environment to create a competitive advantage is ushering in a new era known as digital transformation. Although companies are aware of its potential benefits, they face challenges creating a clear roadmap to reform their existing processes in line with these technologies. Maturity models are developed to assist organisations by providing extensive guidance and a roadmap for improvement. However, as a result of the systematic literature review and its analysis, it was observed that none of the 18 existing maturity models in the digital transformation domain fully satisfies all the criteria of suitability, completeness, clearness, and objectivity. To close this research gap, this study aims to develop a holistic maturity model in the digital transformation domain, entitled DX-CMM, by applying a theoretically grounded development approach, which has so far been neglected despite its remarkable relevance. The purpose of DX-CMM is to assist organisations by providing current capability and maturity determination, deriving a gap analysis, and creating a comprehensive roadmap for improvement in a standardised way. An exploratory case study is also conducted to check the applicability of the model in this study.
Journal: International Journal of Production Research
Pages: 6282-6302
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1991020
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1991020
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# input file: TPRS_A_1987547_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Merve Er
Author-X-Name-First: Merve
Author-X-Name-Last: Er
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Atanu Chaudhuri
Author-X-Name-First: Atanu
Author-X-Name-Last: Chaudhuri
Title: Visualisation of ripple effect in supply chains under long-term, simultaneous disruptions: a system dynamics approach
Abstract: 
 Supply chains (SCs) are exposed to multiple risks and vulnerable to disruption propagation (i.e. the ripple effect). Despite established literature, quantitative analysis of the ripple effect in SCs considering simultaneous, long-term disruptions (i.e. induced by the COVID-19 pandemic) remains limited. This study defines, applies and demonstrates the capability of system dynamics modelling to recognise and visualise the ripple effect subject to supply, demand, and logistics disruptions as well as a combined, simultaneous disruption of supply, demand and logistics. Simulation results for these four risk scenarios indicate that disruption propagation and its impacts vary based on risk type, combination of risks and the impacting node. The bi-directional, increasing effect is significant for disruptions of longer duration. Retailers and manufacturers are most fragile to multiple disruptions due to broader risk exposure points. In generalised terms, systems theory-based study provides insights into the complex behaviour of simultaneous risks and associated disruptions occurring at a node and across the SC. The outcomes derived can help practitioners visualise and recognise the dynamic nature of the ripple effect cascading across the SC network. In addition, some novel insights on the systemic nature and delayed impact of disruption propagations are uncovered and discussed.
Journal: International Journal of Production Research
Pages: 6173-6186
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1987547
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1987547
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# input file: TPRS_A_1988748_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Zhenyong Wu
Author-X-Name-First: Zhenyong
Author-X-Name-Last: Wu
Author-Name: Lina He
Author-X-Name-First: Lina
Author-X-Name-Last: He
Author-Name: Xinguo Ming
Author-X-Name-First: Xinguo
Author-X-Name-Last: Ming
Author-Name: Mark Goh
Author-X-Name-First: Mark
Author-X-Name-Last: Goh
Title: Service-oriented knowledge recommender system and performance evaluation in industrial product development
Abstract: 
 Manufacturing firms today co-exist in a complex collaboration network with their partners, who often seek help from external knowledge services to co-develop more competitive products. Thus, knowing how to accurately and rapidly acquire such knowledge to sustainably improve the quality of knowledge services are critical to maintaining the competitiveness of such firms. There is a need to develop reliable frameworks and tools to support the knowledge services of these firms. This paper proposes a service-oriented knowledge recommender framework focusing on the mechanism of knowledge service transfer and the knowledge recommendation model, which comprises the knowledge service demanders, knowledge service providers, and platform operators. The matching processes and algorithm of the knowledge service demanders and knowledge service providers are designed based on the product development tasks. A fuzzy synthetic evaluation method is proposed, using multi-factor, fuzzy decision making techniques, to improve the quality of the knowledge service. To validate the approach, a case study on gantry crane development is provided to show how to apply the proposed framework and system. An experimental evaluation is designed to demonstrate the benefit and performance of the framework.
Journal: International Journal of Production Research
Pages: 6226-6247
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1988748
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1988748
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# input file: TPRS_A_1988751_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Tian Liu
Author-X-Name-First: Tian
Author-X-Name-Last: Liu
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Bipan Zou
Author-X-Name-First: Bipan
Author-X-Name-Last: Zou
Title: Analysis of pickup/deposit stations and dwell point locations in bi-directional flow-rack AS/RSs
Abstract: 
 A traditional flow-rack automated storage and retrieval system stores unit-loads in storage lanes with the same slope. This paper considers a new bi-directional flow-rack automated storage and retrieval system, in which adjacent storage lanes slope to opposite directions. While such a system can conduct a dual-command cycle, it is critical to operate the system in an efficient way. We focus on both the pickup/deposit (P/D) station policy and the dwell point location policy, considering two scenarios for each policy. We first build a single-command and a dual-command travel time models for each examined P/D station policy and dwell point location policy. Then, we validate the accuracy of the analytical models by simulation, and theoretically compare the examined P/D point policies and dwell point location policies, in terms of both single-command and dual-command cycle times. We find that locating both the P/D station and the dwell point location at the midpoint of the rack is the best policy. We prove the advantage of the BFR AS/RSs over the traditional flow-rack AS/RSs in terms of single-command cycle time, and that of the dual-command cycle over the single-command cycle. Two case studies are also conducted to examine the effectiveness of the examined policies.
Journal: International Journal of Production Research
Pages: 6248-6267
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1988751
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1988751
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# input file: TPRS_A_1983222_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Joep van den Bogaert
Author-X-Name-First: Joep
Author-X-Name-Last: van den Bogaert
Author-Name: Willem van Jaarsveld
Author-X-Name-First: Willem
Author-X-Name-Last: van Jaarsveld
Title: Vendor-managed inventory in practice: understanding and mitigating the impact of supplier heterogeneity
Abstract: 
 Vendor managed inventory (VMI) agreements are a supply chain collaboration principle in which the supplier is responsible for keeping the inventory at the buyer between given lower and upper inventory limits. VMI gives the supplier a lot of autonomy while making replenishments, allowing the supplier to efficiently ensure availability at the buyer. But different suppliers may apply different approaches for staying between the limits under VMI. Relatedly, the objectives of a supplier are not completely aligned with those of the buyer. We develop a methodology for setting appropriate lower and upper inventory limits, taking into account the heterogeneity in the supplier base. To this end, by distinguishing between various possible strategic supplier objectives and various approaches for staying within the inventory limits, we arrive at four possible supplier types. We develop a methodology for classifying suppliers into one of these four types based on historic inventory trajectories and argue how to set inventory limits tailored to each supplier type. A case study of the approach at a large high-tech manufacturer reveals that the approach accurately identifies the type of each of the 47 VMI suppliers of the manufacturer. Moreover, a simulation with company data shows that tailoring inventory limits to the suppliers' types may lead to a cost reduction of 4–6
 $ \% $ % without reducing the service level, as compared to a benchmark method that does not take into account supplier types.
Journal: International Journal of Production Research
Pages: 6087-6103
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1983222
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1983222
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1983224_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yantong Li
Author-X-Name-First: Yantong
Author-X-Name-Last: Li
Author-Name: Jean-François Côté
Author-X-Name-First: Jean-François
Author-X-Name-Last: Côté
Author-Name: Leandro C. Coelho
Author-X-Name-First: Leandro C.
Author-X-Name-Last: Coelho
Author-Name: Peng Wu
Author-X-Name-First: Peng
Author-X-Name-Last: Wu
Title: Novel efficient formulation and matheuristic for large-sized unrelated parallel machine scheduling with release dates
Abstract: 
 This study investigates the unrelated parallel machine scheduling problem with release dates to minimise the makespan. The solution to this problem finds wide applications in manufacturing and logistics systems. Due to the strong NP-hardness of the problem, most researchers develop heuristics, and the largest instances they consider are limited to 400 jobs. To tackle this problem, we develop a novel mixed-integer linear program (MILP) with significantly fewer integer variables than the state-of-the-art ones. The proposed MILP does not rely on a binary sequence variable usually used in the existing models. To deal with large-sized instances, a new three-stage matheuristic algorithm (TSMA) is proposed to obtain scheduling decisions. It uses a dispatching rule to sequentially schedule jobs on machines. Then a reassignment procedure is performed to reduce the makespan. Finally, it employs a re-optimisation procedure based on the proposed MILP to perform job moves and exchanges between two selected machines. We conduct numerical experiments on 1440 instances with up to 3000 jobs and 20 machines. Our results first clearly indicate that the proposed model significantly outperforms existing ones. Moreover, the results on large-sized instances show that the proposed TSMA can obtain high-quality near-optimal solutions in a short computation time.
Journal: International Journal of Production Research
Pages: 6104-6123
Issue: 20
Volume: 60
Year: 2022
Month: 10
X-DOI: 10.1080/00207543.2021.1983224
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1983224
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110473_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: The Editors
Title: Obituary Emeritus Professor Roy Sury CEng PhD (1924-1999) Principal Editor of IJPR (1980-1998)
Journal: International Journal of Production Research
Pages: 1199-1200
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191201
File-URL: http://hdl.handle.net/10.1080/002075499191201
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110474_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: C. N. Hasan
Author-X-Name-First: C. N.
Author-X-Name-Last: Hasan
Author-Name: M. L. Spearman
Author-X-Name-First: M. L.
Author-X-Name-Last: Spearman
Title: Optimal material release times in stochastic production environments
Abstract: 
 The problem of determining the 'optimal' material release times is an important and complex problem for most manufacturing firms. In this age of global competition, firms need to have low inventories, short cycle times and the ability to meet customer orders on time. In this paper, we consider a firm operating in a Make-To-Order environment and formulate this problem as an unconstrained cost minimization problem for a fixed sequence of work. We propose a solution methodology using stochastic approximation and infinitesimal perturbation analysis of a transient state simulation of the system. We discuss the implementation of this algorithm and present some preliminary results. We also present an algorithm to obtain a lower bound on the optimal objective function value under certain conditions.
Journal: International Journal of Production Research
Pages: 1201-1216
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191210
File-URL: http://hdl.handle.net/10.1080/002075499191210
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110475_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: O. Oyeleye
Author-X-Name-First: O.
Author-X-Name-Last: Oyeleye
Title: Automatic visual inspection of surface mount solder joint defects
Abstract: 
 The ever increasing use of surface mount technology in printed circuit board assembly has considerably increased the importance of automated solder joint inspection. This paper documents our experience with the development of an experimental automated solder joint inspection system. Dominant solder joint defect classes are identified. Three-dimensional geometric models of these defects are created and used to test a non-parametric classification algorithm and optimal feature selection scheme. The classification algorithm and optimal feature selection scheme are then implemented on an experimental system using a laser line and vision system for solder joint data acquisition. The capability and limitations of this system are assessed through experimentation with actual solder joint defects.
Journal: International Journal of Production Research
Pages: 1217-1242
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191229
File-URL: http://hdl.handle.net/10.1080/002075499191229
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110476_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: M. J. Khouja
Author-X-Name-First: M. J.
Author-X-Name-Last: Khouja
Title: An options view of robot performance parameters in a dynamic environment
Abstract: 
 A potential robot user is faced with a large number of robots to select from. The selection decision is complex because robot performance is specified by a large number of time-varying parameters. Product design parameters are changing over time, robot technology is improving, and demand is uncertain. Existing selection models do not take into account trends in product design such as the tightening of product tolerances, and trends in robot technology such as improvements in repeatability. We propose using an options model for robot selection, which in turn gives the decision-maker the option of replacing the selected robot with a better one during the life of products with uncertain demand. This replacement option is important when the pace of technological improvement is fast. The model takes into account the tightening of product tolerances and the interaction of these tolerances with robot specifications to determine product quality. The model is illustrated using an actual set of robots and the options model is shown to result in a different selection from the traditional net present value criteria advocated in previous work.
Journal: International Journal of Production Research
Pages: 1243-1257
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191238
File-URL: http://hdl.handle.net/10.1080/002075499191238
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110477_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: B. S. Prabhu
Author-X-Name-First: B. S.
Author-X-Name-Last: Prabhu
Title: Automatic extraction of manufacturable features from CADD models using syntactic pattern recognition techniques
Abstract: 
 This paper reports a system for automatic extraction of manufacturable features from 'engineering drawings' created in CADD format. It employs the techniques of string based pattern recognition and natural language processing. Drawing entities are processed to derive feature string patterns, which are syntactically analyzed to detect the feature topology and geometry. The information of the features so detected is augmented by non-geometric data like dimensions, position, tolerances and the relevant drawing callouts. The system is capable of detecting generic classes of features like holes, pockets, steps, slots, bosses, etc. The derived information can be easily linked to the downline CAD/CAM activities in the product cycle. The system, thus, demonstrates the feasibility of design automation from CADD models.
Journal: International Journal of Production Research
Pages: 1259-1281
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191247
File-URL: http://hdl.handle.net/10.1080/002075499191247
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Handle: RePEc:taf:tprsxx:v:37:y:1999:i:6:p:1259-1281



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110478_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Q. A. Sayeed
Author-X-Name-First: Q. A.
Author-X-Name-Last: Sayeed
Title: Compliance based MIP model and heuristic for support layout optimization
Abstract: 
 Machining-fixture supports are used to increase workpiece rigidity. A critical problem of machining fixture design is where to place a fixed number of supports in order to minimize the affect of workpiece deformation on machined feature geometric error during machining. In a previous effort, a linear Mixed Integer Programming (MIP) model was developed to solve this problem. This model is based upon a statically reduced FEA model of the workpiece, and is capable of solving the more general problem of locator button-support layout. A major disadvantage of this model is that its size is sensitive to the square of the number of machining response points considered. Since the difficulty of solving an MIP model increases with model size, this presents a severe limitation to the use of the MIP model in applications in which a large number of machining response points must be considered. This paper illustrates a technique that can be used to make the MIP model size strictly proportional to the number of machining response points. In addition, it presents a heuristic based on the MIP model, that can be used to solve support layout problems of any size.
Journal: International Journal of Production Research
Pages: 1283-1301
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191256
File-URL: http://hdl.handle.net/10.1080/002075499191256
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110479_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: F. Guerrero
Author-X-Name-First: F.
Author-X-Name-Last: Guerrero
Author-Name: S. Lozano
Author-X-Name-First: S.
Author-X-Name-Last: Lozano
Author-Name: T. Koltai
Author-X-Name-First: T.
Author-X-Name-Last: Koltai
Author-Name: J. Larrañeta
Author-X-Name-First: J.
Author-X-Name-Last: Larrañeta
Title: Machine loading and part type selection in flexible manufacturing systems
Abstract: 
 This paper presents a new approach to the loading problem in flexible manufacturing systems. It focuses on the existence of alternatives routes for each part type. Also, the optimal number of copies of each tool type to be loaded into each tool magazine is directly determined. Thus, the decision variables are the routing mix and the tool allocation. The loading objective is to balance machine workloads. Constraints on the number of available tools and on tool magazine capacities can be imposed. The problem is modelled as a mixed-integer linear program. Also, an extension of the model is formulated that includes part type selection.
Journal: International Journal of Production Research
Pages: 1303-1317
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191265
File-URL: http://hdl.handle.net/10.1080/002075499191265
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110480_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: A.-P. Hameri
Author-X-Name-First: A.-P.
Author-X-Name-Last: Hameri
Title: Document viewpoint on one-of-a-kind delivery process
Abstract: 
 This paper presents the results of an analysis on document interdependencies in a major production system delivery process. In total 28 chief engineers from various design groups were interviewed by identifying the main document classes produced and the required input information. The results of the interviews were summarised into a Design Structure Matrix (DSM) representation. Analyses were made based on design groups, document classes and on the exchange of documents. The group-level analysis highlights the central role of inter-organisational information transfer between the manufacturer and customer as well as between manufacturer and consultant behind the system configuration. The analysis on document classes indicates that the total number of different documents required as an input from the project partners remains small, when compared to the overall document mass. More specifically, the analysis highlights the fundamental role of the requirements specification produced in the course of bid preparation. Concerning the physical document exchange, the study shows that for in-house transfers the electronic medium is widely used. However, paper-print is still the predominant media for transferring information across organisational boundaries. At the same time around 90% of the end-system cost comes from machinery, external design work and parts and components supplied by external vendors. The results indicate, that by focusing on the key documents (10% of the overall document mass), which are needed by practically all collaborating parties and design groups (90% of the contributors), and their efficient dissemination and control, the project could be carried out with fewer mistakes and uncertainty. It is also concluded that Internet and WWW based solutions are rapidly becoming mature enough to tackle the challenge of inter-organisational document sharing.
Journal: International Journal of Production Research
Pages: 1319-1336
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191274
File-URL: http://hdl.handle.net/10.1080/002075499191274
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110481_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: I. Nelson Joseph
Author-X-Name-First: I. Nelson
Author-X-Name-Last: Joseph
Title: Organizational factors and total quality management an empirical study
Abstract: 
 The level of awareness of Total Quality Management (TQM) has increased considerably over the last few years. Different sets of organizational requirements are prescribed by quality management gurus and practitioners for the effective practice of TQM. These requirements do not seem to have been formulated on the basis of systematic empirical research. Many researchers point out that tacit factors, e.g. employee empowerment, open culture and executive commitment, and not TQM tools and techniques alone, could drive TQM success, and that organizations would need to acquire these factors to stay successful. Many TQM advocates have also suggested that a conducive organizational environment would be essential for an effective practice of TQM. However, they did not offer any empirical evidence. There appears to be no empirical study reported in the literature that could establish a relation between TQM and organizational factors. The objective of this paper is to describe an empirical research on TQM conducted in Indian business units carried out recently by considering some organizational factors, e.g. quality of work life, organizational climate and communication. The methodology and findings are discussed in detail.
Journal: International Journal of Production Research
Pages: 1337-1352
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191283
File-URL: http://hdl.handle.net/10.1080/002075499191283
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Handle: RePEc:taf:tprsxx:v:37:y:1999:i:6:p:1337-1352



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110482_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: S. H. Cheraghi
Author-X-Name-First: S. H.
Author-X-Name-Last: Cheraghi
Title: A closed-loop process analysis and control system for machining parts
Abstract: 
 In the production of parts involving multiple interrelated machining operations a process plan is developed and then checked for feasibility using the tolerance charting technique. Owing to inherent variations in manufacturing processes a feasible process plan does not guarantee an acceptable product. Because of the discrete nature of the machining operations and the interrelationship between different dimensions, information on a produced dimension may be used to control the subsequent operations and thus ensure that a part meets specifications. A closed-loop process analysis and control system (PACS) has been developed for this purpose. The closed-loop PACS has several components. The core of the closed-loop PACS is the process adjustment routine (PAR). In the implementation of PAR the actual dimensional information is gathered online and is fed back to PAR, which then advises the machine operator to make adjustments to subsequent operations so that the part is produced with a higher degree of quality. This paper provides an overview of the closed-loop PACS and presents the techniques and procedures for the development and implementation of PAR.
Journal: International Journal of Production Research
Pages: 1353-1368
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191292
File-URL: http://hdl.handle.net/10.1080/002075499191292
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110483_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: F. S. C. Lam
Author-X-Name-First: F. S. C.
Author-X-Name-Last: Lam
Title: Scheduling to minimize product design time using a genetic algorithm
Abstract: 
 We consider a scheduling problem encountered in a semiconductor manufacturing company where the time for designing products (or makespan) needs to be minimized. The problem can be stated as follows: there are sets of tasks (or jobs) to be performed in a design project by a set of engineers. Since engineers are qualified to perform a certain set of jobs, so they are considered to be nonidentical. However, a job can be worked on by more than one engineer while an engineer can work on one job at a time. Moreover, there is a precedence relation among the jobs. The problem is to schedule jobs to engineers so that the makespan is minimized. We develop a Genetic Algorithm (GA) for this problem, which is one of combinatorial optimization subjects to many practical constraints. The GA is found to be very effective for solving this intractable problem. This research attempts to study this scheduling problem in a scientific manner and to propose ways in which the task can be automated with the help of an algorithm embedded in a computer program.
Journal: International Journal of Production Research
Pages: 1369-1386
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191300
File-URL: http://hdl.handle.net/10.1080/002075499191300
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Handle: RePEc:taf:tprsxx:v:37:y:1999:i:6:p:1369-1386



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110484_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: C.-L. Huang
Author-X-Name-First: C.-L.
Author-X-Name-Last: Huang
Title: The construction of production performance prediction system for semiconductor manufacturing with artificial neural networks
Abstract: 
 The major performance measurements for wafer fabrication system comprise WIP level, throughput and cycle time. These measurements are influenced by various factors, including machine breakdown, operator absence, poor dispatching rules, emergency order and material shortage. Generally, production managers use the WIP level profile of each stage to identify an abnormal situation, and then make corrective actions. However, such a measurement is reactive, not proactive. Proactive actions must effectively predict the future performance, analyze the abnormal situation, and then generate corrective actions to prevent performance from degrading. This work systematically constructs artificial neural network models to predict production performances for a semiconductor manufacturing factory. An application for a local DRAM wafer fabrication has demonstrated the accuracy of neural network models in predicting production performances.
Journal: International Journal of Production Research
Pages: 1387-1402
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191319
File-URL: http://hdl.handle.net/10.1080/002075499191319
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Handle: RePEc:taf:tprsxx:v:37:y:1999:i:6:p:1387-1402



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110485_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: R. Handfield
Author-X-Name-First: R.
Author-X-Name-Last: Handfield
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Author-Name: S. Ghosh
Author-X-Name-First: S.
Author-X-Name-Last: Ghosh
Title: An empirical examination of quality tool deployment patterns and their impact on performance
Abstract: 
 Although research suggests that quality management initiatives often fail to meet managers' expectations, few studies consider that an inappropriate choice of quality tools may adversely affect the results. This paper analyses the pattern of quality tool deployment and its impact on performance using a sample of 313 North American and European firms. The analysis reveals that four primary types of quality tool applications occur: Human Resource (HR) tools, Design tools, Discipline tools and Measurement tools. Several significant relationships between these dimensions and quality performance were found, suggesting that successful tool deployment often depends on competitive conditions and internal strategies.
Journal: International Journal of Production Research
Pages: 1403-1426
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191328
File-URL: http://hdl.handle.net/10.1080/002075499191328
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110486_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: J. N. D. Gupta
Author-X-Name-First: J. N. D.
Author-X-Name-Last: Gupta
Title: Part dispatching and machine loading in flexible manufacturing systems using central queues
Abstract: 
 This paper describes a dispatching approach for FMSs where all parts are stored in a central buffer. When a machine becomes available, a part from the buffer, which can be processed by that machine, will be dispatched. If there is more than one candidate part, one part will be selected according to pre-determined loading rules. Results of the simulation experiments, used to compare the performance of the proposed dispatching algorithm with the traditional approach where parts were sent directly to the local machine buffers, which have been pre-selected during the process planning stage, show that the proposed dispatching approach outperforms the traditional one with respect to makespans, average flow time, and average tardiness. Makespans are improved by 22% while average flow time and tardiness are improved by 15% and 30% respectively. Machine failures and loading rules have also been shown to have less impact on the proposed dispatching algorithm than the traditional one
Journal: International Journal of Production Research
Pages: 1427-1435
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191337
File-URL: http://hdl.handle.net/10.1080/002075499191337
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# input file: TPRS_A_10110487_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: The Editors
Title: Book reviews
Journal: International Journal of Production Research
Pages: 1437-1438
Issue: 6
Volume: 37
Year: 1999
Month: 4
X-DOI: 10.1080/002075499191346
File-URL: http://hdl.handle.net/10.1080/002075499191346
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Handle: RePEc:taf:tprsxx:v:37:y:1999:i:6:p:1437-1438

Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_125142_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: J. Vits
Author-X-Name-First: J.
Author-X-Name-Last: Vits
Author-Name: L. Gelders
Author-X-Name-First: L.
Author-X-Name-Last: Gelders
Author-Name: L. Pintelon
Author-X-Name-First: L.
Author-X-Name-Last: Pintelon
Title: Manufacturing process changes: myopic and long-term planning
Abstract: 
 The introduction of process changes is frequently used by management to improve manufacturing competencies. However, the implementation of process changes disturbs learning driven by manufacturing activities. This work introduces a model to explore myopic and long-term process change strategies that maximize the total discounted profits of operating a production system. In accordance with the existing literature, the key benefit sought from process change implementation is an increase in effective capacity. Due to the learning curve effect, the unit production costs decrease with the level of experience generated by operating the production system. On the other hand, changing the production process makes a part of the accumulated experience obsolete. It is found that a myopic planner should increase investment in process change if the level of experience increases. The economic law of diminishing marginal returns from investments in effective capacity induces the myopic producer to limit investment in process change if the effective capacity level of a production system is already high. The structure of the optimal long-term process change policy echoes the optimal myopic process change policy, although the level of process change efforts can differ. Especially for very low and very high effective capacity levels, optimal long-term planning differs from optimal myopic planning.
Journal: International Journal of Production Research
Pages: 1-27
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540500251596
File-URL: http://hdl.handle.net/10.1080/00207540500251596
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_138086_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: A. Das
Author-X-Name-First: A.
Author-X-Name-Last: Das
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Title: Socio-technical perspective on manufacturing system synergies
Abstract: 
 A micro-level perspective using socio-technical theory is used to examine synergies in advanced manufacturing systems (AMS) and their impact on manufacturing performance. It is proposed that the system-level interactions predicated by socio-technical theory extend to the subsystem-level. AMS are classified into three constituent subsystems – technological, manufacturing methods and high-involvement work practices – and hypothesize various ‘microsystems’ formed by combinations of the components of these subsystems. Each ‘microsystem’ is hypothesized to have an impact on particular dimensions of performance. The hypothesis is tested by employing regression analysis. The findings isolate synergistic influences among the components of AMSs on performance. The implications of these findings are discussed in the light of theory and practice.
Journal: International Journal of Production Research
Pages: 169-205
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540500381039
File-URL: http://hdl.handle.net/10.1080/00207540500381039
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_144222_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Chih-Hsuan Wang
Author-X-Name-First: Chih-Hsuan
Author-X-Name-Last: Wang
Author-Name: Way Kuo
Author-X-Name-First: Way
Author-X-Name-Last: Kuo
Author-Name: Hairong Qi
Author-X-Name-First: Hairong
Author-X-Name-Last: Qi
Title: An integrated approach for process monitoring using wavelet analysis and competitive neural network
Abstract: 
 A novel framework involving both a detection module and a classification module is proposed for the recognition of the six main types of process signals. In particular, a multi-scale wavelet filter is used for denoising and its performance is compared with that of single-scale linear filters. Moreover, two kinds of competitive neural networks, based on learning vector quantization (LVQ) and adaptive resonance theory (ART), are adopted for the task of pattern classification and benchmarking. Our results show that denoising through a wavelet filter is best for pattern classification, and the classification accuracy with respect to six predefined categories using a LVQ-X network is a little better than using an ART network. However, when an unexpected novel pattern occurs within the process, LVQ will force the novel pattern to be classified into one of those predefined categories that is most similar to the novel pattern. On the contrary, ART will automatically construct a new class when the similarity measured between the novel pattern and the most similar category is too small to be incorporated. Therefore, under the consideration of the stability–plasticity dilemma, our simplified ART network based on multi-scale wavelet denoising provides a more promising way to adapt unexpected novel patterns.
Journal: International Journal of Production Research
Pages: 227-244
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540500442393
File-URL: http://hdl.handle.net/10.1080/00207540500442393
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_150726_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: D. Y. Sha
Author-X-Name-First: D. Y.
Author-X-Name-Last: Sha
Author-Name: R. L. Storch
Author-X-Name-First: R. L.
Author-X-Name-Last: Storch
Author-Name: C.-H. Liu
Author-X-Name-First: C.-H.
Author-X-Name-Last: Liu
Title: Development of a regression-based method with case-based tuning to solve the due date assignment problem
Abstract: 
 Many regression-based methods to date have been proposed for solving the due date assignment (DDA) problem. The advantages of regression-based DDA methods are that they are easy to both put into practice and comprehend. However, relatively little scheduling research has focused on improving the performances of regression-based DDA methods. The performance of a regression-based DDA method could be improved if its values of regression coefficients could provide a more accurate and precise flowtime estimation for each individual job. The difficulty in doing this stems from the dynamic and stochastic nature of production environment that precludes accurate estimation. Therefore, the aim of this study is to suggest a particular methodology for setting the regression coefficients to improve the performance of regression-based DDA method. In particular, the regression-based DDA method achieved by our suggested methodology is able to adjust the values of coefficients dynamically to best predict the job due date based on the condition of the shop at the instant of job entry. To evaluate the robustness of the methodology, an experimental design was used with four regression coefficient determining procedures, two shop models, and three dispatching rules. The results of this investigation clearly indicate that significant improvements in the performance of regression-based DDA method can occur when the suggested methodology is used.
Journal: International Journal of Production Research
Pages: 65-82
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540500507435
File-URL: http://hdl.handle.net/10.1080/00207540500507435
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_159995_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: W. L. Pearn
Author-X-Name-First: W. L.
Author-X-Name-Last: Pearn
Author-Name: YA Ching Cheng
Author-X-Name-First: YA Ching
Author-X-Name-Last: Cheng
Title: Estimating process yield based on Spk for multiple samples
Abstract: 
 Boyles (1994) proposed a process measurement called Spk, which provides an exact measure on the process yield for normal processes. Lee et al. (2002) considered an asymptotic distribution for the natural estimator of Spk under a single sample. In this paper, we extend the results for the case of multiple samples. We first compare the yield index Spk with the most commonly used index, Cpk, and review some results of Spk under a single sample. Next, we derive the sampling distribution for the estimator <?TeX \hat S^{\,\prime}_{pk} ?> of Spk under multiple samples and find that for the same Spk, the variance of <?TeX \hat S^{\,\prime}_{pk} ?> would be largest when the process mean is on the centre of specification limits. We calculate the lower bounds for various commonly used quality requirements under the situation with the largest variance of <?TeX \hat S^{\,\prime}_{pk} ?> for assurance purposes. To assess the normally approximated distribution of <?TeX \hat S^{\,\prime}_{pk} ?>, we simulate with 10 000 replications to generate 10 000 estimates of <?TeX \hat S^{\,\prime}_{pk} ?>, calculate their lower bounds, compare with the real (preset) Spk and check the actual type I error. We also compute how many sample sizes are required for the normal approximation to converge to Spk within a designated accuracy. Then, we present a real-world application of the one-cell rechargeable Li-ion battery packs, to illustrate how we apply the lower bounds to actual data collected from factories.
Journal: International Journal of Production Research
Pages: 49-64
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540600600122
File-URL: http://hdl.handle.net/10.1080/00207540600600122
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:45:y:2007:i:1:p:49-64



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_160379_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Anthony Ross
Author-X-Name-First: Anthony
Author-X-Name-Last: Ross
Author-Name: Vaidyanathan Jayaraman
Author-X-Name-First: Vaidyanathan
Author-X-Name-Last: Jayaraman
Author-Name: Powell Robinson
Author-X-Name-First: Powell
Author-X-Name-Last: Robinson
Title: Optimizing 3PL service delivery using a cost-to-serve and action research framework
Abstract: 
 Full spectrum visibility and real-time management of increasingly complex, high-velocity operations will be the landmark practices of supply chain management in the twenty-first century. Integrating various business processes across functions is at the heart of supply chain management. As we survey the landscape, we can identify two sets of converging forces and newly emerging capabilities that will shape the way supply chains will develop in the near future. The first issue deals with the rapid rise of global third party logistics (3PL) companies that manage entire supply chains. The second issue has to do with how supply chain organizations plan and budget for a process of change, while simultaneously maintaining focus on full supply chain costs using a method known as the cost-to-serve (CSM) method. It is precisely these two issues that we address in this paper. Our first objective is to document the research conducted by the authors in the offshore oil and gas exploration and production industry. Our second objective is to use the CSM method to identify relevant cost drivers of 3PL services by nesting within an action research approach that pinpoints relevant operational constraints. The third objective is to use the action research framework and CSM to model various cost elements that could be incorporated into the objective function of a mathematical programming model. We compared the current design to the optimal design that we obtained from the model, and performed cost-benefit analysis to show the superiority of our procedure.
Journal: International Journal of Production Research
Pages: 83-101
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540600603969
File-URL: http://hdl.handle.net/10.1080/00207540600603969
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Handle: RePEc:taf:tprsxx:v:45:y:2007:i:1:p:83-101



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_160698_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: K. A. Chatha
Author-X-Name-First: K. A.
Author-X-Name-Last: Chatha
Author-Name: J. O. Ajaefobi
Author-X-Name-First: J. O.
Author-X-Name-Last: Ajaefobi
Author-Name: R. H. Weston
Author-X-Name-First: R. H.
Author-X-Name-Last: Weston
Title: Enriched multi-process modelling in support of the life cycle engineering of Business Processes
Abstract: 
 A new approach to enterprise modelling is described that facilitates the reuse of multi-perspective models of Business Process networks. The approach has been designed to advance current best practice when engineering change to interdependent Business Processes of types commonly deployed within Manufacturing Enterprises. The approach is unique in the way it maintains coherence between (1) conventional enterprise models, used primarily to represent graphically (at multiple levels of abstraction) relatively enduring properties of Business Process networks; and (2) dynamic models of selected segments of a parent Business Process network, which can be computer-executed via conventional simulation modelling and workflow modelling technology. Thereby, context-dependent dynamic models can be used to replicate and analyse historical patterns of enterprise behaviour, and predict and analyse possible future patterns of enterprise behaviour, should selected elements and parameters of the modelled Business Process network be changed. The paper also considers ‘needed decision support capabilities’ during Business Process Reengineering and Business Process improvement projects. In so doing, it collates those decision support requirements identified into a generalized description of the life phases of such projects. This generalized description was used to help structure the design of the new enterprise modelling approach. Furthermore, it is used to help illustrate an example application of the new modelling approach.
Journal: International Journal of Production Research
Pages: 103-141
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540600607150
File-URL: http://hdl.handle.net/10.1080/00207540600607150
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Handle: RePEc:taf:tprsxx:v:45:y:2007:i:1:p:103-141



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_163198_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Q. Su
Author-X-Name-First: Q.
Author-X-Name-Last: Su
Title: Applying case-based reasoning in assembly sequence planning
Abstract: 
 Assembly sequence planning (ASP) is the foundation of the assembly process planning which plays a key role in the whole product life cycle. In this paper, a unique ASP reasoning method supported by the artificial intelligent technique of case-based reasoning (CBR) is proposed and developed. First, based on the previous ASP literatures review and the CBR characteristics analysis, the systematic architecture of the CBR based ASP is presented. Then, some key techniques including assembly case modelling, similar case retrieving, case based reasoning, and case base maintenance, etc., are explored thoroughly. To enhance the efficiency and quality of the reasoning process, genetic algorithm (GA) is designed and applied to automatically inferring of the reference assembly sequence. Finally, the corresponding software system with an engineering example is given to demonstrate the effectiveness of the CBR based ASP.
Journal: International Journal of Production Research
Pages: 29-47
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540600632182
File-URL: http://hdl.handle.net/10.1080/00207540600632182
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Handle: RePEc:taf:tprsxx:v:45:y:2007:i:1:p:29-47



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_164895_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Seong Beom Lee
Author-X-Name-First: Seong Beom
Author-X-Name-Last: Lee
Author-Name: Chanseok Park
Author-X-Name-First: Chanseok
Author-X-Name-Last: Park
Author-Name: Byung-Rae Cho
Author-X-Name-First: Byung-Rae
Author-X-Name-Last: Cho
Title: Development of a highly efficient and resistant robust design
Abstract: 
 Robust design uses the ordinary least squares method to obtain adequate response functions for the process mean and variance by assuming that experimental data are normally distributed and that there is no major contamination in the data set. Under these assumptions, the sample mean and variance are often used to estimate the process mean and variance. In practice, the above assumptions are not always satisfied. When these assumptions are violated, one can alternatively use the sample median and median absolute deviation to estimate the process mean and variance. However, the median and median absolute deviation both suffer from a lack of efficiency under the normal distribution, although they are fairly outlier-resistant. To remedy this problem, we propose new robust design methods based on a highly efficient and outlier-resistant estimator. Numerical studies substantiate the new methods developed and compare the performance of the proposed methods with the ordinary dual-response robust design.
Journal: International Journal of Production Research
Pages: 157-167
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540600649202
File-URL: http://hdl.handle.net/10.1080/00207540600649202
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Handle: RePEc:taf:tprsxx:v:45:y:2007:i:1:p:157-167



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_167863_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xiao-Yuan Huang
Author-X-Name-First: Xiao-Yuan
Author-X-Name-Last: Huang
Author-Name: Ni-Na Yan
Author-X-Name-First: Ni-Na
Author-X-Name-Last: Yan
Author-Name: Hai-Feng Guo
Author-X-Name-First: Hai-Feng
Author-X-Name-Last: Guo
Title: An H∞ control method of the bullwhip effect for a class of supply chain system
Abstract: 
 In this paper, we develop models of a class of supply chain systems, including a multi-echelon supply chain system, a time-lag dynamic supply chain system, and a dual-channel supply chain with a B2B e-market, and analyse each of the bullwhip effects respectively. Furthermore, we address a new method for dynamic quantification and calculations of the bullwhip effect based on classical control theories and methods, and discuss the H∞ control strategies of these systems under the worst fluctuation of demand. Finally, combined with the empirical practices of the most representative state-owned companies in China, we carry out three simulation experiments, and from the results we find that the bullwhip-effect coefficients of these three systems are all controlled and dampened with the H∞ control method.
Journal: International Journal of Production Research
Pages: 207-226
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540600678912
File-URL: http://hdl.handle.net/10.1080/00207540600678912
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Handle: RePEc:taf:tprsxx:v:45:y:2007:i:1:p:207-226



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_169271_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: S. C. Ren
Author-X-Name-First: S. C.
Author-X-Name-Last: Ren
Author-Name: D. Xu
Author-X-Name-First: D.
Author-X-Name-Last: Xu
Author-Name: F. Wang
Author-X-Name-First: F.
Author-X-Name-Last: Wang
Author-Name: M. Tan
Author-X-Name-First: M.
Author-X-Name-Last: Tan
Title: Timed event graph-based cyclic reconfigurable flow shop modelling and optimization
Abstract: 
 The manufacturing process of a part involves sequential steps and each step could be viewed as the part being manufactured by a process module with some specific function. The module must be placed on a machine and connected to the machine via standard interfaces. The machine considered here is a carrier or general platform that can hold one or several different modules simultaneously. Based on the idea that modules are independent of machines and different combinations of modules and machines result in different configurations, the cyclic reconfigurable flow shop is proposed for the new manufacturing paradigm—Reconfigurable Manufacturing System (RMS). The cyclic reconfigurable flow shop can be modelled as a timed event graph. Different cases of cyclic reconfigurable flow shops are discussed and the optimal configuration can be obtained by solving the corresponding mixed-integer program derived from the timed event graph model.
Journal: International Journal of Production Research
Pages: 143-156
Issue: 1
Volume: 45
Year: 2007
Month: 1
X-DOI: 10.1080/00207540600693036
File-URL: http://hdl.handle.net/10.1080/00207540600693036
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Handle: RePEc:taf:tprsxx:v:45:y:2007:i:1:p:143-156

Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_169320_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: P.-T. Chang
Author-X-Name-First: P.-T.
Author-X-Name-Last: Chang
Author-Name: K.-P. Lin
Author-X-Name-First: K.-P.
Author-X-Name-Last: Lin
Author-Name: P.-F. Pai
Author-X-Name-First: P.-F.
Author-X-Name-Last: Pai
Author-Name: C.-Z. Zhong
Author-X-Name-First: C.-Z.
Author-X-Name-Last: Zhong
Author-Name: C.-H. Lin
Author-X-Name-First: C.-H.
Author-X-Name-Last: Lin
Author-Name: L.-T. Hung
Author-X-Name-First: L.-T.
Author-X-Name-Last: Hung
Title: Ant colony optimization system for a multi-quantitative and qualitative objective job-shop parallel-machine-scheduling problem
Abstract: 
 This paper addresses a multi-stage job-shop parallel-machine-scheduling problem with an ant colony optimization system developed. The problem is practically important and yet more complex, especially when customer order splitting in multiple lots for the reduction of operation times in each workstation is allowed. It also includes the decisions of the numbers of parallel machines in workstations dynamically scheduled. In addition, this paper also addresses the multiple-objectives scheduling. For the practical concern, in addition to the production (or quantitative) objectives, the marketing (strategic or qualitative) criteria are also considered. A soft constraint thus may be realized from a thus-called qualitatively evaluated order sequence. The soft constraint with the ant colony optimization solution constructs a penalty function for the multiple qualitative objectives and the results of scheduling obtained by ant colony optimization. For this problem, the ant colony optimization components (including the network representation, tabu lists, transition probabilities, and pheromone trail updating) are also developed and adapted for the multiple objectives. The experiment results of parameter design and different problem sizes are provided. The results of a genetic algorithm also developed for the present problem under the developed system concept are also provided, since in the literature the genetic algorithm has also not been explored for the present problem with multiple objectives and order splitting. The results of both solution techniques show the potential usefulness of the system and are comparable, but the ant colony optimization provides a more computationally efficient better result.
Journal: International Journal of Production Research
Pages: 5719-5759
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540600693523
File-URL: http://hdl.handle.net/10.1080/00207540600693523
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_218148_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Arthur B. Yeh
Author-X-Name-First: Arthur B.
Author-X-Name-Last: Yeh
Author-Name: Richard N. Mcgrath
Author-X-Name-First: Richard N.
Author-X-Name-Last: Mcgrath
Author-Name: Mark A. Sembower
Author-X-Name-First: Mark A.
Author-X-Name-Last: Sembower
Author-Name: Qi Shen
Author-X-Name-First: Qi
Author-X-Name-Last: Shen
Title: EWMA control charts for monitoring high-yield processes based on non-transformed observations
Abstract: 
 We propose and study exponentially weighted moving average (EWMA) control charts for monitoring high-yield processes. The EWMA control charts are developed based on non-transformed geometric, binomial and Bernoulli counts. The proposed charts are evaluated based on the average number of items sampled before the first out-of-control signal is detected. By selecting small smoothing constants, the proposed EWMA control charts outperform in numerous cases the recently developed CUSUM control charts [Chang, T.C. and Gan, F.F., Cumulative sum charts for high yield processes. Statist. Sin., 2001, 11, 791–805], which are considered the most efficient control charting mechanisms in the existing literature for monitoring fraction non-conforming as small as 0.0001. Numerous simulations are included for performance comparisons. An example is also given to demonstrate the applicability of the proposed EWMA control charts.
Journal: International Journal of Production Research
Pages: 5679-5699
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540601182252
File-URL: http://hdl.handle.net/10.1080/00207540601182252
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:46:y:2008:i:20:p:5679-5699



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_218149_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: S. Panagiotidou
Author-X-Name-First: S.
Author-X-Name-Last: Panagiotidou
Author-Name: G. Tagaras
Author-X-Name-First: G.
Author-X-Name-Last: Tagaras
Title: Evaluation of maintenance policies for equipment subject to quality shifts and failures
Abstract: 
 We develop an economic model for the optimization of maintenance procedures in a production process with two quality states. In addition to deteriorating with age, the equipment may experience a jump to an out-of-control state (quality shift), which is characterized by lower production revenues and higher tendency to failure. The times to quality shift and failure are allowed to be generally distributed random variables. We consider two types of maintenance: minimal maintenance (MM) that upgrades the quality state of the equipment without affecting its age and perfect preventive maintenance (PM) that fully upgrades the equipment to the as-good-as-new condition. We derive the expression for the expected profit per time unit and we investigate, through a large number of numerical examples, the type of the optimal solution. It is concluded that in practically every case the optimal maintenance policy is an extreme one: it either calls for immediate MM as soon as a quality shift occurs (active policy) or it allows operation in the out-of-control state until the time of a scheduled PM action (passive policy).
Journal: International Journal of Production Research
Pages: 5761-5779
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540601182260
File-URL: http://hdl.handle.net/10.1080/00207540601182260
File-Format: text/html
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Handle: RePEc:taf:tprsxx:v:46:y:2008:i:20:p:5761-5779



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_224099_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: B. J. Alvarez
Author-X-Name-First: B. J.
Author-X-Name-Last: Alvarez
Author-Name: P. Fernandez
Author-X-Name-First: P.
Author-X-Name-Last: Fernandez
Author-Name: J. C. Rico
Author-X-Name-First: J. C.
Author-X-Name-Last: Rico
Author-Name: S. Mateos
Author-X-Name-First: S.
Author-X-Name-Last: Mateos
Author-Name: C. M. Suarez
Author-X-Name-First: C. M.
Author-X-Name-Last: Suarez
Title: Accessibility analysis for automatic inspection in CMMs by using bounding volume hierarchies
Abstract: 
 Accessibility analysis represents one of the most critical tasks in inspection planning. This analysis determines those probe orientations that can touch an inspection point without collision. This paper presents a methodology based on part discretization and the application of space partitioning techniques (kd-tree) in order to reduce the number of intersection tests between probe and part. A STL model has been used for discretizing the inspection part in a set of triangles, which permits the application of the developed system to any type of part, regardless of its shape and its complexity. Likewise, a recursive ray traversal algorithm has been used in order to speed up the traversal of the kd-tree hierarchical structure and to calculate exclusively the intersection of each probe orientation with those part triangles that can potentially interfere with it. In a further step of the analysis, the real geometry of the probe has been considered. Hence, a simplified model has been developed for each probe component (column, head, touch probe, stylus and tip) using different basic geometrical shapes. Finally, collision-free probe orientations are clustered for minimizing the orientation changes during the inspection process. Furthermore, the applied algorithm allows for determining different valid combinations of clusters. The developed system was applied to two example parts in order to prove that this methodology is adequate for the solution of real cases.
Journal: International Journal of Production Research
Pages: 5797-5826
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701241867
File-URL: http://hdl.handle.net/10.1080/00207540701241867
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_224101_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: H. B. Hwarng
Author-X-Name-First: H. B.
Author-X-Name-Last: Hwarng
Title: Toward identifying the source of mean shifts in multivariate SPC: a neural network approach
Abstract: 
 To identify the source(s) of process shifts under a multivariate setting is a challenging problem. Though some statistical techniques have been proposed, they are limited or restricted in their level of success and ease of use. In this paper, we propose a neural-network based identifier (NNI) to detect process mean shifts as well as indicate the variable(s) responsible for the shifts in a process where variables are correlated. Various network configurations and training strategies were investigated to develop an effective network. This research demonstrates how the NNI with a simple network structure, i.e. without any hidden layers, can perform superiorly to the Hotelling T 2 chart and comparably to the MEWMA chart in detecting small to moderate shifts for bivariate processes. The run length analysis also indicates that the NNI performs much more stably than the Hotelling T 2 chart and the MEWMA chart. One of the great advantages of this approach is that the proposed identifier, aided with the NNI output chart, can indicate the source(s) of the shift(s), i.e. the variable(s) responsible for the shift(s). The NNI output chart allows this monitoring scheme to easily interpret the underlying structures of the process variables.
Journal: International Journal of Production Research
Pages: 5531-5559
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701241883
File-URL: http://hdl.handle.net/10.1080/00207540701241883
File-Format: text/html
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_227606_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: A. S. Gogate
Author-X-Name-First: A. S.
Author-X-Name-Last: Gogate
Author-Name: S. S. Pande
Author-X-Name-First: S. S.
Author-X-Name-Last: Pande
Title: Intelligent layout planning for rapid prototyping
Abstract: 
 Significant savings in cost and time can be achieved in rapid prototyping (RP) by manufacturing multiple parts in a single setup to achieve efficient machine volume utilization. This paper reports the design and implementation of a system for the optimal layout planning of 3D parts for a RP process. A genetic algorithm (GA) based search strategy has been used to arrive at a good packing layout for a chosen set of parts and RP process. A two stage approach has been proposed to initially short-list acceptable orientations for each part followed by the search for a layout plan which optimizes in terms of final product quality and build time. The GA uses a hybrid objective function comprising of the weighted measures like part build height, staircase effect, volume and area-of-contact of support structures. In essence it captures the key metrics of efficiency and goodness of packing for RP. The final layout plan is produced in the form of a composite part CAD model which can be directly exported to a RP machine for manufacturing. Design methodology of the system has been presented with some representative case studies.
Journal: International Journal of Production Research
Pages: 5607-5631
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701277002
File-URL: http://hdl.handle.net/10.1080/00207540701277002
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_228714_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: R. Siva Sankar
Author-X-Name-First: R.
Author-X-Name-Last: Siva Sankar
Author-Name: P. Asokan
Author-X-Name-First: P.
Author-X-Name-Last: Asokan
Author-Name: G. Prabhaharan
Author-X-Name-First: G.
Author-X-Name-Last: Prabhaharan
Author-Name: A. V. Phani
Author-X-Name-First: A. V.
Author-X-Name-Last: Phani
Title: A CAPP framework with optimized process parameters for rotational components
Abstract: 
 Process planning, as a critical stage integrating the design and manufacturing phase in a manufacturing environment, has been automated to meet the needs for higher productivity and lower production cost. Being an input to various systems such as scheduling and routing, process planning results are of great importance in the manufacturing stage. Though feature extraction and sequence optimization have been given much attention, the process parameters are rarely dealt with. This paper focuses on the development of a new generative computer aided process planning (CAPP) framework for rotational components. The developed framework includes modules for feature extraction based on CAD application programming interfaces, determination of the optimum sequence and generation of optimum process parameters. The optimization of the machining operations is achieved using the evolutionary technique. The approach resulted in the reduction and prediction of machining time and cost. The framework is demonstrated with a case study.
Journal: International Journal of Production Research
Pages: 5561-5587
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701288108
File-URL: http://hdl.handle.net/10.1080/00207540701288108
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_229367_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: K. Dhouib
Author-X-Name-First: K.
Author-X-Name-Last: Dhouib
Author-Name: A. Gharbi
Author-X-Name-First: A.
Author-X-Name-Last: Gharbi
Author-Name: S. Ayed
Author-X-Name-First: S.
Author-X-Name-Last: Ayed
Title: Availability and throughput of unreliable, unbuffered production lines with non-homogeneous deterministic processing times
Abstract: 
 This paper studies production lines composed of several serial machines which are subject to random operation-dependent failures. The production lines have no intermediate buffers between adjacent machines. Machines have different deterministic processing times. The purpose of this paper is to propose analytical models to assess steady-state availability and throughput of such lines. Thousands of production line configurations have been experimented to compare the performance of the proposed approach to approximate existing techniques. A general simulation model was developed and statistical tests carried out to prove that the proposed approach is exact and robust to model unreliable, unbuffered, and non-homogeneous production lines.
Journal: International Journal of Production Research
Pages: 5651-5677
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701294635
File-URL: http://hdl.handle.net/10.1080/00207540701294635
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# input file: TPRS_A_234770_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: X. Liu
Author-X-Name-First: X.
Author-X-Name-Last: Liu
Author-Name: Y. L. Tu
Author-X-Name-First: Y. L.
Author-X-Name-Last: Tu
Title: Capacitated production planning with outsourcing in an OKP company
Abstract: 
 This paper addresses a dynamic capacitated production planning (CPP) problem in small to medium-sized enterprises (SMEs). These companies practise their businesses based on a manufacturing paradigm called one-of-a-kind production (OKP). Typically, they employ outsourcing in their CPP practice. Therefore, the CPP problem in this paper includes outsourcing, which is called the outsourcing CPP problem. The outsourcing strategy considered in this paper has the following features: (1) outsourcing takes place when the demand exceeds the capacity; (2) all excessive demands are outsourced without backlogging; and (3) production, inventory, and outsourcing levels all have a limit. One important difference of the problem considered in this paper from other problems is that the cost functions are considered arbitrarily time-varying. The outsourcing CPP problem is formulated into an optimization problem which captures the mentioned features. The objective of the problem is to minimize the total cost. It is very likely that there is no solution in our model so we propose a necessary and sufficient condition for feasible solutions. Dynamic programming techniques are employed in searching for a global optimal solution with a pseudo-polynomial time. This paper also presents a case study for a real-life problem in an OKP company to illustrate our approach and to show its effectiveness. The case study has shown that our approach is very effective.
Journal: International Journal of Production Research
Pages: 5781-5795
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701348779
File-URL: http://hdl.handle.net/10.1080/00207540701348779
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# input file: TPRS_A_235413_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ekrem Duman
Author-X-Name-First: Ekrem
Author-X-Name-Last: Duman
Author-Name: Mehmet Bayram Yildirim
Author-X-Name-First: Mehmet Bayram
Author-X-Name-Last: Yildirim
Author-Name: Ali Fuat Alkaya
Author-X-Name-First: Ali Fuat
Author-X-Name-Last: Alkaya
Title: Scheduling continuous aluminium casting lines
Abstract: 
 This study considers the problem of scheduling casting lines of an aluminium casting and processing plant. In aluminium processing plants, continuous casting lines are the bottleneck resources, i.e. factory throughput is limited by the amount of aluminium that can be cast. The throughput of a casting line might be increased by minimizing total setup time between jobs. The objective is to minimize setup time on production lines for a given time period while balancing workload between production lines to accommodate potential new orders. A mathematical formulation for scheduling jobs to minimize the total setup time while achieving workload balance between the production lines is presented. Since the casting scheduling problem is an NP-hard problem, even with only one casting line, a four-step algorithm to find good solutions in a reasonable amount of time is proposed. In this process, a set of asymmetric travelling salesman problems is followed by a pairwise exchange heuristic. The proposed procedure is applied to a case study using real casting data.
Journal: International Journal of Production Research
Pages: 5701-5718
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701355212
File-URL: http://hdl.handle.net/10.1080/00207540701355212
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# input file: TPRS_A_236813_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: B. Lee
Author-X-Name-First: B.
Author-X-Name-Last: Lee
Author-Name: Y. H. Lee
Author-X-Name-First: Y. H.
Author-X-Name-Last: Lee
Author-Name: T. Yang
Author-X-Name-First: T.
Author-X-Name-Last: Yang
Author-Name: J. Ignisio
Author-X-Name-First: J.
Author-X-Name-Last: Ignisio
Title: A due-date based production control policy using WIP balance for implementation in semiconductor fabrications
Abstract: 
 Production control policies are critical in the re-entrant processes of semiconductor fabrication. Manufacturing control policies such as input dispatching rules, CONWIP, and optimization-based rules have been implemented according to the managerial objectives of the wafer fabrication line. When few semiconductor wafer fabrication facilities were available, and the semiconductor industry was a seller's market, fabrications were operated to achieve both a high rate of production and high utilization of equipment. With the availability of more fabrications and the gradual shift to a buyer's market, customer satisfaction became a major measure of performance in semiconductor manufacturing. In this paper, due-date based production control policies for semiconductor fabrications are suggested, and their performances evaluated. Target balance (TB) optimization models using production target, due-dates, and WIP (work-in-process) are presented. The evaluation result shows that the TB models perform better than the ones cited in the literature.
Journal: International Journal of Production Research
Pages: 5515-5529
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701369213
File-URL: http://hdl.handle.net/10.1080/00207540701369213
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# input file: TPRS_A_238018_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: F.-Y. Ding
Author-X-Name-First: F.-Y.
Author-X-Name-Last: Ding
Author-Name: J. He
Author-X-Name-First: J.
Author-X-Name-Last: He
Title: A heuristic procedure for the automobile assembly-line sequencing problem considering multiple product options
Abstract: 
 Mixed-model assembly nowadays is a common practice in the automobile industry. In an automobile assembly plant, many car options often need to be considered in sequencing an assembly line, for example, the multiple sequencing objectives that consider a pattern, blocking, spacing, and smoothing of options. A general heuristic procedure is developed in this paper for sequencing automobile assembly lines considering multiple options. The procedure obtains an initial sequence by an enhanced constructive procedure, swaps orders for the most deteriorating category of objectives, and performs re-sequencing attempting to improve the swapped sequence. The heuristic procedure was shown to frequently improve the initial sequences by swapping and re-sequencing when swapping opportunities exist. A further improvement step is also proposed to perform a limited search based on the swapped solution. The limited-search improvement step was shown to be effective in further improving solutions from the heuristic procedure in the computational experimentation. Solutions from the heuristic procedure in conjunction with the limited-search improvement step were compared to those from the simulated annealing procedure for large-size problems and showed relatively positive results.
Journal: International Journal of Production Research
Pages: 5827-5847
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701381291
File-URL: http://hdl.handle.net/10.1080/00207540701381291
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# input file: TPRS_A_239203_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Lawrence M. Corbett
Author-X-Name-First: Lawrence M.
Author-X-Name-Last: Corbett
Title: Manufacturing strategy, the business environment, and operations performance in small low-tech firms
Abstract: 
 This paper reports on a ten-year study of ten manufacturing companies in New Zealand. Over the period the firms endured a turbulent environment where they were subject to large changes in exchange rate, and some faced forced changes in products, and markets as a result of changes in ownership and government policy. The paper examines the stability of manufacturing strategies in such an environment, the emphasis placed on improvement initiatives and what impact these decisions had on manufacturing performance. The study uses a multi-case, longitudinal approach. It found the strategy configurations were not stable and many firms moved towards a price-based configuration, contrary to other literature. The more successful firms put greater investments into infrastructural categories of their operations strategy in accordance with the resource-based view. Operations performance indicators showed some improvement on manufacturing costs but other indicators showed no real pattern.
Journal: International Journal of Production Research
Pages: 5491-5513
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701393163
File-URL: http://hdl.handle.net/10.1080/00207540701393163
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_241276_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: J. Mula
Author-X-Name-First: J.
Author-X-Name-Last: Mula
Author-Name: R. Poler
Author-X-Name-First: R.
Author-X-Name-Last: Poler
Author-Name: J. P. Garcia-Sabater
Author-X-Name-First: J. P.
Author-X-Name-Last: Garcia-Sabater
Title: Capacity and material requirement planning modelling by comparing deterministic and fuzzy models
Abstract: 
 A model for the capacity and material requirement planning problem with uncertainty in a multi-product, multi-level and multi-period manufacturing environment is proposed. An optimization model is formulated which takes into account the uncertainty that exists in both the market demand and capacity data, and the uncertain costs for backlog. This work uses the concept of possibilistic programming by comparing trapezoidal fuzzy numbers. Such an approach makes it possible to model the ambiguity in market demand, capacity data, cost information, etc. that could be present in production planning systems. The main goal is to determine the master production schedule, stock levels, backlog, and capacity usage levels over a given planning horizon in such a way as to hedge against the uncertainty. Finally, the fuzzy model and the deterministic model adopted as the basis of this work are compared using real data from an automobile seat manufacturer. The paper concludes that fuzzy numbers could improve the solution of production planning problems.
Journal: International Journal of Production Research
Pages: 5589-5606
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701413912
File-URL: http://hdl.handle.net/10.1080/00207540701413912
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_242878_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Author-Name: S. Vickery
Author-X-Name-First: S.
Author-X-Name-Last: Vickery
Author-Name: C. Droge
Author-X-Name-First: C.
Author-X-Name-Last: Droge
Title: Relationship building, lean strategy and firm performance: an exploratory study in the automotive supplier industry
Abstract: 
 In contrast to previous literature, we propose that commitment to lean strategy should be preceded by building close relationships with key supply chain partners (suppliers and customers). Two aspects of lean strategy, lean manufacturing and lean design are studied in this paper. We hypothesize that relationship building positively affects both aspects of lean strategy, which in turn positively influences firm performance. To test these relationships, we use data from the top 150 auto suppliers to the ‘Big Three’ original equipment manufacturers (OEMs). The results show positive relationships between (1) relationship building and lean design, (2) relationship building and lean manufacturing, and (3) lean design and firm performance. This suggests that relationship building is more valuable for enhancing the ‘product’ aspects of lean strategy as opposed to the ‘process’ aspects of lean strategy. Process aspects of lean strategy appear to be largely a function of internal efforts.
Journal: International Journal of Production Research
Pages: 5633-5649
Issue: 20
Volume: 46
Year: 2008
Month: 1
X-DOI: 10.1080/00207540701429942
File-URL: http://hdl.handle.net/10.1080/00207540701429942
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1991024_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yuxiang Cheng
Author-X-Name-First: Yuxiang
Author-X-Name-Last: Cheng
Author-Name: David L. Olson
Author-X-Name-First: David L.
Author-X-Name-Last: Olson
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Financing with preferential credit to coordinate the capital-constraint supply chain
Abstract: 
 This paper investigates the impacts of preferential credit policy, faced by capital constraint retailers, on coordinating the supply chain. Apart from different bank’s and manufacturer’s risk preferences, preferential credit is also affected by the retailers’ exogenous collateral. We establish the preferential credit coordinating model (PCCM) to examine the optimal decisions and coordinate the supply chain with different financing channels, such as the preferential bank loan, preferential trade credit and portfolio credit. In this paper, we conclude some critical findings. Firstly, we find that the retailer’s optimal would improve its optimal order quantity in the coordinated supply chain when he finances from a risk-pursuing bank or the manufacturer. Secondly, the retailer’s financial cost would be shared with the manufacturer whether the retailer utilises preferential trade credit or bank financing channel. Thirdly, the capital constraint retailer would prefer preferential trade credit to the other financing methods for the purpose that the preferential trade credit could improve the coordinated supply chain’s efficiency. Finally, we capture different impacts of collateral and risk preference on the supply chain. This article supplements the existing literature on supply chain finance with a preferential credit insight into the condition of the coordinated supply chain.
Journal: International Journal of Production Research
Pages: 6391-6412
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1991024
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1991024
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# input file: TPRS_A_1995792_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: François Larroche
Author-X-Name-First: François
Author-X-Name-Last: Larroche
Author-Name: Odile Bellenguez
Author-X-Name-First: Odile
Author-X-Name-Last: Bellenguez
Author-Name: Guillaume Massonnet
Author-X-Name-First: Guillaume
Author-X-Name-Last: Massonnet
Title: Clustering-based solution approach for a capacitated lot-sizing problem on parallel machines with sequence-dependent setups*
Abstract: 
 This paper studies an industrial lot-sizing and scheduling problem coming from the food-industry that extends the multi-item capacitated lot-sizing and includes lost sales, overtimes, safety stock and non-uniform sequence-dependent setups on parallel machines. We introduce two different formulations and adapt the well-known Relax-and-Fix and Fix-and-Optimise heuristics in order to quickly obtain feasible solutions on large industrial instances. The complexity of our problem prevents the procedure to obtain good solutions within the time allocated by practitioners on real-life cases, hence we propose to use a clustering approach to approximate the sequence-dependent setup times. The resulting problem is significantly smaller to solve and experimental results suggest that this transformation effectively improves the solutions found on industrial instances. In particular, the combination of this clustering method and Relax-and-Fix and Fix-and-Optimise procedure turns out to be a promising approach to obtain good solutions in the given time-limit.
Journal: International Journal of Production Research
Pages: 6573-6596
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1995792
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1995792
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1994166_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Author-Name: Bartosz Sawik
Author-X-Name-First: Bartosz
Author-X-Name-Last: Sawik
Title: A rough cut cybersecurity investment using portfolio of security controls with maximum cybersecurity value
Abstract: 
 This paper deals with optimisation of cybersecurity investment in supply chains using stochastic programming approach. A classical exponential function of breach probability and the intuitive idea of ‘the expected net benefits’, originally presented in 2002 by Gordon and Loeb, were applied to introduce the concept of cybersecurity value. The cybersecurity value of security control is defined as the value gained by implementing a single control to secure a subset of components. The cybersecurity value of a control can be seen as a measure of its efficiency in reducing vulnerability of a secured system or component. A mixed binary optimisation problem, next transformed into an unconstrained binary program is developed to maximise total cybersecurity value of control portfolio. The optimal solution to the binary program provides a simple formula to immediately obtain the portfolio of security controls with maximum total cybersecurity value and determine a rough cut cybersecurity investment. This study also shows that portfolio of security controls with maximum total cybersecurity value reduces the losses from security breaches and mitigate the impact of cyber risk.
Journal: International Journal of Production Research
Pages: 6556-6572
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1994166
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1994166
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1991023_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Maaz Saleem Kapadia
Author-X-Name-First: Maaz Saleem
Author-X-Name-Last: Kapadia
Author-Name: Reha Uzsoy
Author-X-Name-First: Reha
Author-X-Name-Last: Uzsoy
Author-Name: Binil Starly
Author-X-Name-First: Binil
Author-X-Name-Last: Starly
Author-Name: Donald P. Warsing
Author-X-Name-First: Donald P.
Author-X-Name-Last: Warsing
Title: A genetic algorithm for order acceptance and scheduling in additive manufacturing
Abstract: 
 We consider the problem of order acceptance and scheduling faced by an additive manufacturing facility consisting of multiple build chambers and postprocessing operations for support removal and surface finishing. We model each build chamber as a batch processing machine with processing times determined by the nesting and orientation of parts within the chamber. Due to the difficulty of developing an explicit functional relation between part batching, batch processing time, and postprocessing requirements we develop random-keys based genetic algorithms to select orders for complete or partial acceptance and produce a high-quality schedule satisfying all technological constraints, including part orientation and rotation within the build chamber. Extensive computational experiments show that the proposed approaches yield significant improvements in profit over the situation where all orders must be accepted, and produce solutions that compare favourably to statistically estimated bounds.
Journal: International Journal of Production Research
Pages: 6373-6390
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1991023
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1991023
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1994164_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Kamar Zekhnini
Author-X-Name-First: Kamar
Author-X-Name-Last: Zekhnini
Author-Name: Anass Cherrafi
Author-X-Name-First: Anass
Author-X-Name-Last: Cherrafi
Author-Name: Imane Bouhaddou
Author-X-Name-First: Imane
Author-X-Name-Last: Bouhaddou
Author-Name: Abla Chaouni Benabdellah
Author-X-Name-First: Abla
Author-X-Name-Last: Chaouni Benabdellah
Author-Name: Surajit Bag
Author-X-Name-First: Surajit
Author-X-Name-Last: Bag
Title: A model integrating lean and green practices for viable, sustainable, and digital supply chain performance
Abstract: 
 In disrupted environments, the concept of digitalisation, viability, and sustainability have attracted considerable attention for the last decade. Digital, lean, and green capabilities have stimulated enormous advances in the development of industries. This paper discusses the current state of the art literature regarding sustainable and digital supply chain management performance. It reviews the relationship between digital technologies, lean, green, sustainability, and supply chain performance. A literature review approach, combined with a bibliometric analysis was adopted for robust field analysis. A set of 86 papers has been analysed and synthesised. The analysis of these papers has enabled the identification of the impact of Industry 4.0 technologies on the supply chain performance; the relationship of lean, green, and sustainability capabilities and digital supply chain; and the implications of the digital transformation of those capabilities. It presents a roadmap model integrating lean and green for viable, sustainable, and digital supply chain performance. The study is useful for academics and practitioners as it provides a roadmap framework and a solid background for integrating lean and green in the digital supply chain to achieve sustainable and viable performance as it outlines the necessity for incorporating the sustainability and viability performances in the digital supply chains.
Journal: International Journal of Production Research
Pages: 6529-6555
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1994164
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1994164
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1992031_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Matteo Rossini
Author-X-Name-First: Matteo
Author-X-Name-Last: Rossini
Author-Name: Federica Costa
Author-X-Name-First: Federica
Author-X-Name-Last: Costa
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme Luz
Author-X-Name-Last: Tortorella
Author-Name: Alessia Valvo
Author-X-Name-First: Alessia
Author-X-Name-Last: Valvo
Author-Name: Alberto Portioli-Staudacher
Author-X-Name-First: Alberto
Author-X-Name-Last: Portioli-Staudacher
Title: Lean Production and Industry 4.0 integration: how Lean Automation is emerging in manufacturing industry
Abstract: 
 Despite its potentialities, Lean Automation (LA) has not attracted attention for over two decades. However, due to the new opportunities offered by Industry 4.0 technologies, LA revives expectations and enthusiasm. This paper aims to test empirically the association of LA, in the form of integration of Lean practices and Industry 4.0 technologies, and operational performance. The paper used a rigorous, multi-stage empirical method and data from a set of more than 200 manufacturing firms; one representative from each of the studied companies filled in a survey on Lean practices and Industry 4.0 technology bundles, with productivity, delivery, inventory, quality as performance indicators. The extensive survey results helped in identifying underlying components of LA: one focuses on operational stability and includes practices and technologies supporting efficiency along the supply chain; the other focuses on streamlining the flow, on fastening the process to reach the customer. Moreover, it demonstrates the positive correlation between LA and operational performance. Besides its contribution to the body of knowledge on LA, this research paves the base of improving academics and practitioners understanding of the integration of new technologies with Lean Production systems.
Journal: International Journal of Production Research
Pages: 6430-6450
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1992031
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1992031
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# input file: TPRS_A_1992681_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yunrong Zhang
Author-X-Name-First: Yunrong
Author-X-Name-Last: Zhang
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: Zhixiang Chen
Author-X-Name-First: Zhixiang
Author-X-Name-Last: Chen
Title: Estimating the participation value of electricity demand-response programmes for a two-stage production system
Abstract: 
 Electricity demand-response programmes, such as the incentive-based and price-based programmes, have been used by utilities to induce customers to reduce their electricity consumption during peak periods. This study investigates the production decisions of a two-stage production system under these programmes in a situation where peak periods arrive randomly in the manufacturing cycle. Analytical results show that under demand-response programmes, the manufacturer, who aims at minimising the total operational cost, usually selects a lower production rate during peak periods and a higher one during non-peak periods. Notably, the uncertainty of the peak periods also has a significant influence on the manufacturer's production plans under these programmes. This paper further investigates the efficiency of different demand-response programmes in reducing the inventory holding cost and electricity cost. The results indicate that participating in the demand-response programmes does not always result in a higher inventory holding cost, which goes against the manufacturer's intuition about these programmes. In addition, this paper evaluates the manufacturers' preference for these demand-response programmes by comparing the operational cost savings generated from participating in the two programmes. It turns out that both the demand-response signals and the inventory holding cost substantially influence the manufacturer's willingness to participate in the programmes.
Journal: International Journal of Production Research
Pages: 6508-6528
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1992681
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1992681
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1991598_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: To-Cheng Wang
Author-X-Name-First: To-Cheng
Author-X-Name-Last: Wang
Author-Name: Bi-Min Hsu
Author-X-Name-First: Bi-Min
Author-X-Name-Last: Hsu
Author-Name: Ming-Hung Shu
Author-X-Name-First: Ming-Hung
Author-X-Name-Last: Shu
Title: An integrated quick-switch sampling system based on a process capability index for constructing a solid supplier-buyer relationship
Abstract: 
 The quick-switch sampling (QSS) systems based on process capability index (PCI) have been proved to be useful for inspecting processes streaming at a low level of defects because of their small sizes required and dynamic responsiveness to problems. However, most of the recent studies have aimed at deriving the mathematical model and comparing performances for the acceptance criteria-type QSS system, and only a few of them have an interest in the development of the required sample-size-type QSS system; their studies have limited simultaneous discussions on both systems’ advantages and disadvantages, not to mention the lack of investigations on the impact of the joint application of the two QSS system types. In this paper, an integrated QSS (IQSS) system based on the most popular PCI was proposed; the system can accommodate two existing types of PCI-based QSS systems and further boost the sampling performance and discriminatory power. Moreover, by operating suitable types of PCI-based QSS systems in different stages of the supplier-buyer partnership, a progressive lot-disposition strategy was introduced to construct a solid supplier-buyer relationship. We also developed a web-based tool to accurately and efficiently execute all types’ PCI-based QSS systems. Finally, the industrial applicability was demonstrated in a case study.
Journal: International Journal of Production Research
Pages: 6413-6429
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1991598
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1991598
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1992032_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Seongtae Kim
Author-X-Name-First: Seongtae
Author-X-Name-Last: Kim
Author-Name: Kai Foerstl
Author-X-Name-First: Kai
Author-X-Name-Last: Foerstl
Author-Name: Christoph G. Schmidt
Author-X-Name-First: Christoph G.
Author-X-Name-Last: Schmidt
Author-Name: Stephan M. Wagner
Author-X-Name-First: Stephan M.
Author-X-Name-Last: Wagner
Title: Adoption of green supply chain management practices in multi-tier supply chains: examining the differences between higher and lower tier firms
Abstract: 
 Customer pressure has been widely discussed as the primary driver of green supply chain management (GSCM) practices. However, relatively little is known about supplier capabilities as a key mediator for GSCM practice adoption. Drawing from the resource dependence theory (RDT), we investigate how the interplay between customer pressure and supplier capabilities affects GSCM practice adoption along multi-tier supply chains. We test our hypotheses using multiple regression analysis based on a sample of 284 manufacturing firms operating at different tiers of a supply chain. Our results indicate that the supplier capabilities mediate the direct effect of customer pressure on the adoption of GSCM practices for focal firms. Specifically, we find a full mediation effect of supplier capabilities for higher-tier (i.e. OEM and system supplier) firms and a partial mediation effect for lower-tier (i.e. component and raw material) firms. Our findings provide support for the RDT perspective regarding GSCM. The focal firm’s adoption of GSCM practices as a response to customer pressure is dependent on the level of green resources and capabilities available from their suppliers. The level of such resource dependence varies between focal firms at higher- and lower-tier positions in a multi-tier supply chain.
Journal: International Journal of Production Research
Pages: 6451-6468
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1992032
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1992032
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# input file: TPRS_A_1998699_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Asma Rakiz
Author-X-Name-First: Asma
Author-X-Name-Last: Rakiz
Author-Name: Nabil Absi
Author-X-Name-First: Nabil
Author-X-Name-Last: Absi
Author-Name: Pierre Fenies
Author-X-Name-First: Pierre
Author-X-Name-Last: Fenies
Title: An integrated production and direct shipment problem in a mining industry
Abstract: 
 This research aims to solve an integrated production, storage and distribution planning problem in a multi-level multi-product logistics system. The work was conducted in collaboration with a leading mining industry. The present research presents a mixed-integer linear program inspired by the classical Multi-Level Lot-Sizing model to solve the problem. It combines several aspects related to (1) multi-level and multi-product production units, (2) multi-level and multi-product storage units and (3) train transportation with time windows. Besides the standard features of lot-sizing problems, this work encompasses further aspects related to mining activity precisely and, more generally, to the structural specifications of continuous production processes. The objective is to hierarchically satisfy deterministic demand, minimise the total number of switch-offs of production units, and minimise total operational costs. On a sizeable real data-set obtained from our industrial partner, we demonstrate the benefit of integrating decisions in terms of improving demand satisfaction rates, increasing resource efficiency, and minimising total operational costs. In addition, we study the cost structure and provide a detailed cost sensitivity analysis. Finally, this work evaluates the upstream and downstream propagation of decisions in the logistics system and underlines the benefits in terms of flexibility offered by the global approach.
Journal: International Journal of Production Research
Pages: 6659-6681
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1998699
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1998699
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# input file: TPRS_A_1998694_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Adalberto Sato Michels
Author-X-Name-First: Adalberto Sato
Author-X-Name-Last: Michels
Author-Name: Alysson M. Costa
Author-X-Name-First: Alysson M.
Author-X-Name-Last: Costa
Title: Conserving workforce while temporarily rebalancing assembly lines under demand disruption
Abstract: 
 In stable circumstances, assembly lines have workers with different capabilities assigned to stations. They perform a set of specialised tasks multiple times daily. Under a situation of high demand disruption (e.g. the COVID-19 pandemic), the overproduction rate would lead inventory levels to soar. An approach to cope with these demand drops and ongoing workforce costs is to dismiss employees and rebalance the line. Nevertheless, this implies social and economic costs related to rehiring and training. Alternatively, agreements can be made to reduce workload with a proportional wage deduction. These decisions are particularly challenging in heterogeneous workforces. We propose a Mixed-Integer Linear Programming (MILP) model to address the Assembly Line Worker Assignment and Rebalancing Problem (ALWARP). Our model aims at preserving jobs while minimising labour costs. We consider scenarios with falling demands and impose regularity metrics on workload reductions. Computational tests on benchmark datasets show that our strategy can distribute social costs among workers, with only slightly higher cumulative labour hours, while avoiding inconveniences associated with future renovations. A real-world case study of a truck cabin assembly line is investigated: the model can easily incorporate many realistic features and decide which workers should have their workload reduced and at which rate.
Journal: International Journal of Production Research
Pages: 6616-6636
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1998694
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1998694
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1996652_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Liping Zhang
Author-X-Name-First: Liping
Author-X-Name-Last: Zhang
Author-Name: Zhenwei Zhu
Author-X-Name-First: Zhenwei
Author-X-Name-Last: Zhu
Author-Name: Xionghui Zhou
Author-X-Name-First: Xionghui
Author-X-Name-Last: Zhou
Title: A node sequence-based ant colony optimisation algorithm for die scheduling problem with twin-crane transportation
Abstract: 
 With the increasing demand for multi-variety and small-batch products, it’s necessary to frequently dispatch and replace the progressive press dies on the stamping production lines to ensure the diversity of processed automobile covering parts. This paper formulates a die scheduling problem with twin-crane transportation (DSP-TCT) encountered in the stamping production line, which concentrates on the scheduling of transporting dies between the production line and warehouse by twin cranes with satisfying crane distance constraint, die position constraint, and precedence constraint. To solve DSP-TCT, this paper proposes a node sequence-based ant colony optimisation algorithm (NS-ACO). In this algorithm, each node represents a single die transportation task with action and time information executed by the twin cranes. The combination of adjacent nodes with a high time utilisation rate can be accumulated as heuristic priority knowledge for guiding optimisation. To demonstrate the effectiveness of the NS-ACO algorithm, numerical experiments with three different die stacking strategies are executed.
Journal: International Journal of Production Research
Pages: 6597-6615
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1996652
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1996652
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1992529_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Jinting Wang
Author-X-Name-First: Jinting
Author-X-Name-Last: Wang
Author-Name: Zhongbin Wang
Author-X-Name-First: Zhongbin
Author-X-Name-Last: Wang
Author-Name: Zhe George Zhang
Author-X-Name-First: Zhe George
Author-X-Name-Last: Zhang
Author-Name: Fang Wang
Author-X-Name-First: Fang
Author-X-Name-Last: Wang
Title: Efficiency-quality trade-off in allocating resource to public healthcare systems
Abstract: 
 In practice, both comprehensive hospital (e.g. AAA hospital) and primary hospital (e.g. community hospital) can exist in healthcare system, where the comprehensive hospital can provide a guaranteed service, but the waiting time of patients is relatively long. By contrast, the primary hospital is less congested, but the patients cannot be treated if the illness is found to be severe. Then the trade-off between efficiency (primary hospital) and quality (comprehensive hospital) should be considered. In this paper, we consider a resource allocation problem in a public service system with multi-type service providers and patients. To capture the interactions between the multi-type hospitals, a queueing-game-theoretical model is established. And we obtain the following results. First, the socially optimal reimbursement policy is obtained, and the sensitivities of parameters are examined, which indicate that, somewhat interestingly, both the optimal budget to primary hospital and the maximal social welfare are non-monotone in the effectiveness parameter or the joining probability of patients. Second, by comparing the socially optimal strategy with individually equilibrium strategy, we find that individual behaviour of patients does not necessarily lead to systems more congested than what is socially desirable. Third, we demonstrate the robustness of our model by extending it to a three-level system and a system with multiple parallel primary hospitals.
Journal: International Journal of Production Research
Pages: 6469-6490
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1992529
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1992529
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1992680_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Eduardo e Oliveira
Author-X-Name-First: Eduardo
Author-X-Name-Last: e Oliveira
Author-Name: Vera L. Miguéis
Author-X-Name-First: Vera L.
Author-X-Name-Last: Miguéis
Author-Name: José L. Borges
Author-X-Name-First: José L.
Author-X-Name-Last: Borges
Title: On the influence of overlap in automatic root cause analysis in manufacturing
Abstract: 
 To improve manufacturing processes, it is essential to find the root causes of occurring problems, in order to solve them permanently. Automatic Root Cause Analysis (ARCA) solutions aid analysts in finding such root causes, by using automatic data analysis to improve the digital decision. When trying to locate the root cause of a problem in a manufacturing process, a phenomenon can occur that disrupts the application of ARCA solutions. Overlap, as we denominated, is a phenomenon where local synchronicities in the manufacturing process lead to data where it is impossible to discern the influence of each location in the quality of products, which impedes automated diagnosis, especially when using classifiers. This paper identifies and defines overlap, and proposes a two-phase ARCA solution that uses factor-ranking algorithms, instead of classifiers. The proposed solution is evaluated in simulated and real case-study data. Results proved the presence of overlap in the datasets, and its negative impact on classifiers. The proposed solution has a positive performance detecting root causes even in the presence of overlap.
Journal: International Journal of Production Research
Pages: 6491-6507
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1992680
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1992680
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1998697_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Frank Bodendorf
Author-X-Name-First: Frank
Author-X-Name-Last: Bodendorf
Author-Name: Philipp Merkl
Author-X-Name-First: Philipp
Author-X-Name-Last: Merkl
Author-Name: Jörg Franke
Author-X-Name-First: Jörg
Author-X-Name-Last: Franke
Title: Artificial neural networks for intelligent cost estimation – a contribution to strategic cost management in the manufacturing supply chain
Abstract: 
 In today’s complex supply networks sharing information between buyers and suppliers is critical for sustainable competitive advantage. In particular, for both business partners, cost information is highly relevant in purchasing situations. According to empirical studies in literature, artificial neural networks (ANNs) are expected to have a great potential to reveal cost structures by machine learning (ML). In digitally enabled supply chains this information can contribute to cost reduction and operational excellence and lead to win-win situations in supplier relationship management. Nevertheless, authors do not thoroughly investigate how ANNs may support cost estimation for purchasing decisions. Based on a case study from the automotive industry, we evaluate ANNs regarding their capability to gain cost structure data. In an additional comparative study, we benchmark ANNs for cost estimation in purchasing against other promising ML algorithms. Thereby, we apply the cross-industry standard process model for data mining projects. The findings of the studies show that some ML algorithms outperform ANNs regarding accuracy. The research results give indications for choosing the ML approach that promises the best outcome for cost estimations and cost structure information to support decision-making in buyer–supplier relationships.
Journal: International Journal of Production Research
Pages: 6637-6658
Issue: 21
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1998697
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1998697
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1949641_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Jian Jin
Author-X-Name-First: Jian
Author-X-Name-Last: Jin
Author-Name: Danping Jia
Author-X-Name-First: Danping
Author-X-Name-Last: Jia
Author-Name: Kejia Chen
Author-X-Name-First: Kejia
Author-X-Name-Last: Chen
Title: Mining online reviews with a Kansei-integrated Kano model for innovative product design
Abstract: 
 Optimising affective design based on customer needs help to earn competitive advantages. However, affective design has been studied qualitatively and the value of online opinions providing affective design ideas has not been exploited deeply. To fill this gap, a framework is proposed to reveal customer affective needs from a perspective of the Kansei-integrated Kano model. Firstly, inspired by Kansei Engineering, customer affective emotions are extracted contextually from online reviews. Next, related product features are positioned based on syntactic relations and a clustering algorithm. Enlightened by the Kano model, product features are prioritised based on affective emotions to show their importance on customer satisfaction. Finally, experiments with practical data are illustrated to evaluate the effectiveness in innovative product design. Take smartphone for example and camera, material, aesthetic design, safety, service, physical interface, and price are found to be attractive features in this study. Additionally, product reviews are transferred into a structured format by analysing affective emotions and corresponding features. It provides a straightforward perspective on affective needs, which facilitate new product design by including innovative design ideas and the proposed KE-integrated Kano model helps to capture customer affective needs and give inspirable insights for affective design from the viewpoint of companies.
Journal: International Journal of Production Research
Pages: 6708-6727
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1949641
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1949641
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1950937_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Angie Nguyen
Author-X-Name-First: Angie
Author-X-Name-Last: Nguyen
Author-Name: Samir Lamouri
Author-X-Name-First: Samir
Author-X-Name-Last: Lamouri
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Author-Name: Simon Tamayo
Author-X-Name-First: Simon
Author-X-Name-Last: Tamayo
Author-Name: Béranger Lekens
Author-X-Name-First: Béranger
Author-X-Name-Last: Lekens
Title: Data analytics in pharmaceutical supply chains: state of the art, opportunities, and challenges
Abstract: 
 In recent years, data analytics in pharmaceutical supply chains has aroused much interest as it has the potential of enabling better supply and management of healthcare products by leveraging data generated by modern systems. This article presents the current state, opportunities, and challenges of data analytics in pharmaceutical supply chains through a systematic literature review surveying the Scopus, ScienceDirect, and Springerlink databases. 85 publications from 2012 to 2021 were reviewed and classified based on the research approach, objective addressed, and data used. The contributions of this paper are threefold: (i) it proposes a framework focused on challenges and data resources to assess the current state of data analytics in pharmaceutical supply chains; (ii) it provides examples of techniques exemplified that will serve as inspiring references; and (iii) it gathers and maps existing literature to identify gaps and research perspectives. Findings outlined that despite promising results from machine learning algorithms to address drug shortages and inventories optimisation, the various data resources have not yet been fully harnessed. Unstructured data have barely been used and combined with other types of information. New challenges related to green practices adoption and medicines supply during crises call for further applications of advanced analytics techniques.
Journal: International Journal of Production Research
Pages: 6888-6907
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1950937
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1950937
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1923854_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Danyu Bai
Author-X-Name-First: Danyu
Author-X-Name-Last: Bai
Author-Name: Ali Diabat
Author-X-Name-First: Ali
Author-X-Name-Last: Diabat
Author-Name: Xinyue Wang
Author-X-Name-First: Xinyue
Author-X-Name-Last: Wang
Author-Name: Dandan Yang
Author-X-Name-First: Dandan
Author-X-Name-Last: Yang
Author-Name: Yao Fu
Author-X-Name-First: Yao
Author-X-Name-Last: Fu
Author-Name: Zhi-Hai Zhang
Author-X-Name-First: Zhi-Hai
Author-X-Name-Last: Zhang
Author-Name: Chin-Chia Wu
Author-X-Name-First: Chin-Chia
Author-X-Name-Last: Wu
Title: Competitive bi-agent flowshop scheduling to minimise the weighted combination of makespans
Abstract: 
 Customer satisfaction is a prevalent issue amongst manufacturing enterprises. Multi-agent scheduling models aim to optimise the given criteria for improving customer satisfaction by fulfilling the customisation requirements. An investigation is executed on a bi-agent flowshop scheduling model, where a mass of tasks maintained by two competitive agents share a group of successive processors over time. The objective is to determine a feasible schedule that minimises the weighted combination of makespans belonging to two different agents. Asymptotic and worst-case analyses are conducted on a class of dominant-agent-based heuristics proposed to find approximate solutions for large-scale instances. An effective branch and bound algorithm is presented to achieve optimal solutions for small-scale instances, where the release-date-based branching rules and the preemption-based lower bounds significantly speed up the convergence of the proposed algorithm. A discrete artificial bee colony algorithm is introduced to find high-quality solutions for medium-scale instances. Extensive computational experiments are conducted to reveal the effectiveness of the proposed algorithms.
Journal: International Journal of Production Research
Pages: 6750-6771
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1923854
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1923854
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2130589_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yunqiang Yin
Author-X-Name-First: Yunqiang
Author-X-Name-Last: Yin
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Author-Name: M.C. Zhou
Author-X-Name-First: M.C.
Author-X-Name-Last: Zhou
Title: Big data analytics in production and distribution management
Abstract: 
 Production and distribution are two key constituents of a supply chain. In view of the growing availability of data and advances in big data analytics techniques, there have been more and more applications of data analytics to deal with the problems in production and distribution management. With this in mind, we proposed a special issue on ‘Big Data Analytics in Production and Distribution Management' to report the latest development in this field. In this editorial, we first introduce the background and examine the existing review works on the applications of data analytics to operations management. We then introduce the papers accepted in the issue, and discuss how different types of big data analytics techniques are applied to production and distribution management, including demand forecasting, production scheduling, distribution management, manufacturing management, and supply chain management. Finally, we conclude the paper with a discussion of future research.
Journal: International Journal of Production Research
Pages: 6682-6690
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2022.2130589
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2130589
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1906971_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: T. C. Edwin Cheng
Author-X-Name-First: T. C.
Author-X-Name-Last: Edwin Cheng
Author-Name: Sachin S. Kamble
Author-X-Name-First: Sachin S.
Author-X-Name-Last: Kamble
Author-Name: Amine Belhadi
Author-X-Name-First: Amine
Author-X-Name-Last: Belhadi
Author-Name: Nelson Oly Ndubisi
Author-X-Name-First: Nelson Oly
Author-X-Name-Last: Ndubisi
Author-Name: Kee-hung Lai
Author-X-Name-First: Kee-hung
Author-X-Name-Last: Lai
Author-Name: Manoj Govind Kharat
Author-X-Name-First: Manoj Govind
Author-X-Name-Last: Kharat
Title: Linkages between big data analytics, circular economy, sustainable supply chain flexibility, and sustainable performance in manufacturing firms
Abstract: 
 The digital supply chains enabled by Big Data Analytics (BDA) capabilities have become a business significance to develop a competitive and sustainable supply chain. The implementation of BDA for sustainable supply chains introduces various organisational challenges for the manufacturing firms demanding complementary capabilities. This study presents an investigation of the linkages between BDA capabilities, circular economy (CE) practices, and sustainable supply chain (SSC) flexibility on the SSC performance. Based on a survey of 320 manufacturing organisations, the study presents very interesting results. It is revealed that the BDA does not have a direct effect on sustainable performance. The CE practices and SSC flexibility are significant mediating variables between the BDA capabilities and SSC performance. The BDA is found to drive the implementation of CE practices. Further, CE practices are found to develop SSC flexibility with the BDA complementing these flexibilities.
Journal: International Journal of Production Research
Pages: 6908-6922
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1906971
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1906971
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2051765_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Jing Liang
Author-X-Name-First: Jing
Author-X-Name-Last: Liang
Author-Name: Shilei Yang
Author-X-Name-First: Shilei
Author-X-Name-Last: Yang
Author-Name: Xiaowen Huang
Author-X-Name-First: Xiaowen
Author-X-Name-Last: Huang
Author-Name: Jing Zhu
Author-X-Name-First: Jing
Author-X-Name-Last: Zhu
Title: Forward or backward: The Impact of Vertical Integration Direction on the bullwhip effect
Abstract: 
 The bullwhip effect represents a major source of supply chain inefficiency. Traditional OM analytical approaches and theories view vertical integration as a countermeasure to the bullwhip effect. Despite its intuitive appeal, this relationship has yet to be rigorously examined. To be specific, a firm may choose backward integration to tighten its grip on the supply and production side, or forward integration to control over the demand and distribution side. The effect of different integration could be diverse depending on the firm’s supply chain position, but research on this link is limited. Driven by a large dataset containing 292,080 detailed business information of listed firms in China, we empirically examine the impact of forward and backward vertical integration on the bullwhip effect, as well as the moderating role of the firms’ supply chain positions. We find that: (1) forward vertical integration does reduce the bullwhip effect, and this mitigation effect is more pronounced for firms located further downstream; (2) the magnitude and direction of backward vertical integration effects are diverse. It has a strong mitigation effect on the bullwhip effect for upstream firms, and when firms are located further downstream, backward vertical integration will surprisingly increase the bullwhip effect.
Journal: International Journal of Production Research
Pages: 6923-6944
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2022.2051765
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2051765
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# input file: TPRS_A_1962558_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Peng-Hao Cui
Author-X-Name-First: Peng-Hao
Author-X-Name-Last: Cui
Author-Name: Jun-Qiang Wang
Author-X-Name-First: Jun-Qiang
Author-X-Name-Last: Wang
Author-Name: Yang Li
Author-X-Name-First: Yang
Author-X-Name-Last: Li
Title: Data-driven modelling, analysis and improvement of multistage production systems with predictive maintenance and product quality
Abstract: 
 Predictive maintenance (PM) and quality management help to improve the business bottom line by alleviating the system performance degradation caused by unscheduled machine breakdown and product quality problems. In modern production systems, the wide application of new IT technology results in data-rich environments. However, it is not clear how to take advantage of the data to facilitate maintenance decision-making and production performance improvement. Aiming at multistage production systems with batching machines and finite buffers, this research studies data-driven modelling, analysis and improvement of production systems with predictive maintenance and product quality. First, a data-driven quantitative method is proposed to analyze the impact of machine breakdowns, predictive maintenance and product quality failure on system performance. Then, based on the obtained system production loss, a PM decision model is established to minimise the maintenance and production costs, and the optimal maintenance policy is exploited based on an approximate dynamic programming algorithm. In addition, downtime bottleneck (DT-BN) is defined, and a data-driven bottleneck indicator is derived. A continuous improvement method is established through the identification and mitigation of the bottlenecks. Finally, numerical case studies are performed to validate the effectiveness of the proposed PM decision model and continuous improvement method.
Journal: International Journal of Production Research
Pages: 6848-6865
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1962558
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1962558
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# input file: TPRS_A_1919333_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Saumyaranjan Sahoo
Author-X-Name-First: Saumyaranjan
Author-X-Name-Last: Sahoo
Title: Big data analytics in manufacturing: a bibliometric analysis of research in the field of business management
Abstract: 
 Big data is of great importance in manufacturing, since knowing the diverse origin of underlying causes of problems is completely necessary for managing continuous improvement. As manufacturers are shifting towards digital transformation driven by big data, business analytics is becoming a dominant methodology for strategic decision-making in business management research. In response to this emerging phenomenon, the purpose of the current study is to provide a thorough literature review of the applicability of big data in manufacturing, with a perspective to exploring various research trends in this field and identifying the scope of potential investigations in the future. This study uses bibliometric and visual analysis approaches to systematically identify and analyse research articles from leading business journals in the Scopus database. The study sample included 89 research articles published in ABDC A*/A category journals to map thematic evolution and conceptual clusters related to keywords of ‘big data’, ‘business analytics’ and ‘manufacturing’. Using factorial analysis in Biblioshiny software, the study presents three research clusters in which researchers shall be encouraged to expand the big data/business analytics research in the context of manufacturing.
Journal: International Journal of Production Research
Pages: 6793-6821
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1919333
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1919333
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# input file: TPRS_A_1887536_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Barış Tan
Author-X-Name-First: Barış
Author-X-Name-Last: Tan
Author-Name: Siamak Khayyati
Author-X-Name-First: Siamak
Author-X-Name-Last: Khayyati
Title: Supervised learning-based approximation method for single-server open queueing networks with correlated interarrival and service times
Abstract: 
 Efficient performance evaluation methods are needed to design and control production systems. We propose a method to analyse single-server open queueing network models of manufacturing systems composed of delay, batching, merge and split blocks with correlated interarrival and service times. Our method (SLQNA) is based on using a supervised learning approach to determine the mean, the coefficient of variation, and the first-lag autocorrelation of the inter-departure time process as functions of the mean, coefficient of variation and first-lag autocorrelations of the interarrival and service times for each block, and then using the predicted inter-departure time process as the input to the next block in the network. The training data for the supervised learning algorithm is obtained by simulating the systems for a wide range of parameters. Gaussian Process Regression is used as a supervised learning algorithm. The algorithm is trained once for each block. SLQNA does not require generating additional training data for each unique network. The results are compared with simulation and also with the approximations that are based on Markov Arrival Process modelling, robust queueing, and G/G/1 approximations. Our results show that SLQNA is flexible, computationally efficient, and significantly more accurate and faster compared to the other methods.
Journal: International Journal of Production Research
Pages: 6822-6847
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1887536
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1887536
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# input file: TPRS_A_1887534_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xiaofeng Xu
Author-X-Name-First: Xiaofeng
Author-X-Name-Last: Xu
Author-Name: Ziru Lin
Author-X-Name-First: Ziru
Author-X-Name-Last: Lin
Author-Name: Xiang Li
Author-X-Name-First: Xiang
Author-X-Name-Last: Li
Author-Name: Changjing Shang
Author-X-Name-First: Changjing
Author-X-Name-Last: Shang
Author-Name: Qiang Shen
Author-X-Name-First: Qiang
Author-X-Name-Last: Shen
Title: Multi-objective robust optimisation model for MDVRPLS in refined oil distribution
Abstract: 
 At depots with refined oil shortage, arranging a reasonable distribution scheme with limited supply affects operation costs, demand satisfaction rate of gasoline stations (hereafter, ‘station satisfaction’), and overtime penalty. This study considers the refined oil distribution problem with shortages using a multi-objective optimisation approach from the perspective of decision makers of oil marketing companies. The modelling and solving process involves (i) formulation of a crisp multi-depot vehicle routing model with limited supply (MDVRPLS) which considers station priority and soft time windows, (ii) development of a robust optimisation model (ROM) to manage uncertainty in demand, and (iii) the proposal of a multi-objective particle swarm optimisation (MOPSO)algorithm. Results of numerical experiments show that (i) the crisp model can better balance operation costs, station satisfaction, and overtime penalty, which produces 3.33% and 4.60% increase in station satisfaction at an increased unit cost and overtime penalty respectively; (ii) ROM successfully addresses uncertainty in demand compared to the crisp model, which requires an additional 8.81% in cost and 12.85% in penalty; and (iii) the MOPSO manages these MDVRPLS models more effectively than other heuristic algorithms. Therefore, applying ROM of refined oil supply shortage to the management significantly improves the efficiency and resists the disturbance caused by external uncertainties, providing scope for efficient distribution of scarce resources.
Journal: International Journal of Production Research
Pages: 6772-6792
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1887534
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1887534
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# input file: TPRS_A_1946192_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Rossella Pozzi
Author-X-Name-First: Rossella
Author-X-Name-Last: Pozzi
Author-Name: Violetta Giada Cannas
Author-X-Name-First: Violetta Giada
Author-X-Name-Last: Cannas
Author-Name: Maria Pia Ciano
Author-X-Name-First: Maria Pia
Author-X-Name-Last: Ciano
Title: Linking data science to lean production: a model to support lean practices
Abstract: 
 The literature discusses data science (DS) as a very promising set of techniques and tools to support lean production (LP) practices. DS could aid manufacturing companies in transforming massive real-time data into meaningful knowledge, increasing process transparency and product quality information and supporting improvement activities through data-driven decision-making. However, no attempt has been made in the literature to formalise the links between DS and LP practices. Thus, this study aims to overcome this gap by clarifying the DS techniques and tools that can support LP practices and how to apply them. This study employs a quantitative bibliometric method – specifically, a keyword co-occurrence network analysis – on a set of papers extracted from Scopus. The results obtained allowed the researchers to identify a set of DS techniques and tools that can support LP practices and to develop a model to guide their implementation based on the typical improvement implementation stages of the plan-do-check-act cycle. The model shows how to use DS techniques and tools in LP for: identifying areas for improvement and subsequent implementation (plan); enabling a better knowledge and process management (do); identifying/predicting potential problems and employing statistical process control (check); providing remedial actions and effectively applying process improvement (act).
Journal: International Journal of Production Research
Pages: 6866-6887
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1946192
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1946192
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# input file: TPRS_A_1900617_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xiang T.R. Kong
Author-X-Name-First: Xiang T.R.
Author-X-Name-Last: Kong
Author-Name: Miaohui Zhu
Author-X-Name-First: Miaohui
Author-X-Name-Last: Zhu
Author-Name: Kaida Qin
Author-X-Name-First: Kaida
Author-X-Name-Last: Qin
Author-Name: Pengyu Yan
Author-X-Name-First: Pengyu
Author-X-Name-Last: Yan
Title: Demand-predictive storage assignment mechanism for flower auction centers
Abstract: 
 As the number of daily transactions continues to increase, congestion frequently occurs in flower auction centers. Put system is widely applied in intralogistics operations, which includes distribution and redistribution areas. The uncertain arrivals of demands pose significant challenges for the efficient intralogistics operations in flower auction center. In order to improve performance of the put system, this study newly designs a demand-predictive storage assignment (DSA) mechanism in which uncertain demands are forecasted by constructing 
 $A/F $A/F ratio time series of each customer. Based on the demand forecasts, the customer locations within the distribution area and the number of locations within the redistribution area are easily determined. Furthermore, a paired redistribution strategy is proposed that enables two customers to share a staging block. A simulation experiment bed is constructed based on a real-life case. The experimental results indicate that the 
 $A/F $A/F forecasting method outperforms other demand forecast methods in literature with lower forecasting error, and the proposed DSA mechanism reduces the total travel distance compared with the closest open location.
Journal: International Journal of Production Research
Pages: 6691-6707
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2021.1900617
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1900617
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# input file: TPRS_A_2053602_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yuanbo Li
Author-X-Name-First: Yuanbo
Author-X-Name-Last: Li
Author-Name: Yong-Hong Kuo
Author-X-Name-First: Yong-Hong
Author-X-Name-Last: Kuo
Author-Name: Runjie Li
Author-X-Name-First: Runjie
Author-X-Name-Last: Li
Author-Name: Houcai Shen
Author-X-Name-First: Houcai
Author-X-Name-Last: Shen
Author-Name: Lianmin Zhang
Author-X-Name-First: Lianmin
Author-X-Name-Last: Zhang
Title: A target-based distributionally robust model for the parallel machine scheduling problem
Abstract: 
 We develop a distributionally robust optimisation (DRO) model based on a risk measure for the parallel machine scheduling problem (PMSP) with random job processing times. We propose an underperformance risk index (URI) to control the extent of the total weighted completion time (TWCT) that exceeds target level T. With partially characterised uncertainty set information, we transform the model with URI to its equivalent mixed-integer linear programming (MILP) counterparts. Due to the NP-hardness of PMSP with different job weights, we design a hybrid algorithm with a heuristic assignment and exact subproblem for large-scale problems. The proposed hybrid algorithm reduces the computation time significantly at the expense of solution quality. We also introduce a reformulation approach under the setting of equally weighted and identical machines. Numerical results show that our model performs better than the distributionally β-robust optimisation models. Our proposed URI accounts for both the frequency and magnitude of violation from the target. The uncertainty set we used preserves a linear structure under partially characterised distributional information. Our computational results and sensitivity analysis show the effectiveness and efficiency of our proposed DRO model under various settings, including different problem sizes, different processing time variations, and information misalignment.
Journal: International Journal of Production Research
Pages: 6728-6749
Issue: 22
Volume: 60
Year: 2022
Month: 11
X-DOI: 10.1080/00207543.2022.2053602
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2053602
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# input file: TPRS_A_1999523_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Malek Abbassi
Author-X-Name-First: Malek
Author-X-Name-Last: Abbassi
Author-Name: Abir Chaabani
Author-X-Name-First: Abir
Author-X-Name-Last: Chaabani
Author-Name: Nabil Absi
Author-X-Name-First: Nabil
Author-X-Name-Last: Absi
Author-Name: Lamjed Ben Said
Author-X-Name-First: Lamjed
Author-X-Name-Last: Ben Said
Title: An elitist cooperative evolutionary bi-level multi-objective decomposition-based algorithm for sustainable supply chain
Abstract: 
 Many real-life applications are modelled using hierarchical decision-making in which: an upper-level optimisation task is constrained by a lower-level one. Such class of optimisation problems is referred in the literature as Bi-Level Optimisation Problems (BLOPs). Most of the proposed methods tackled the single-objective continuous case adhering to some regularity assumptions. This is at odds with real-world problems which involve mainly discrete variables and expensive objective function evaluations. Besides, the optimisation process becomes exorbitantly time-consuming, especially when optimising several objectives at each level. For this reason, the Multi-objective variant (MBLOP) remains relatively less explored and the number of methods tackling the combinatorial case is much reduced. Motivated by these observations, we propose in this work an elitist decomposition-based evolutionary algorithm to solve MBLOPs, called ECODBEMA. The basic idea of our proposal is to handle, decomposition, elitism and multithreading mechanisms to cope with the MBLOP's high complexity. ECODBEMA is applied to the production–distribution problem and to a sustainable end-of-life products disassembly case-study based on real-data of Aix-en-Provence French city. We compared the optimal solutions of an exact method using CPLEX solver with near-optimal solutions obtained by ECODBEMA. The statistical results show the significant outperformance of ECODBEMA against other multi-objective bi-level optimisation algorithms.
Journal: International Journal of Production Research
Pages: 7013-7032
Issue: 23
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.1999523
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1999523
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# input file: TPRS_A_1999521_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Maximilian Gebhardt
Author-X-Name-First: Maximilian
Author-X-Name-Last: Gebhardt
Author-Name: Matthias Kopyto
Author-X-Name-First: Matthias
Author-X-Name-Last: Kopyto
Author-Name: Hendrik Birkel
Author-X-Name-First: Hendrik
Author-X-Name-Last: Birkel
Author-Name: Evi Hartmann
Author-X-Name-First: Evi
Author-X-Name-Last: Hartmann
Title: Industry 4.0 technologies as enablers of collaboration in circular supply chains: a systematic literature review
Abstract: 
 Close and novel forms of collaboration among supply chain stakeholders within and beyond industry boundaries are essential for implementing a circular economy. Industry 4.0 technologies, as recognised enablers for circular systems, can support such collaboration. This study explores the intersection of the circular economy, supply chain collaboration, and Industry 4.0. First, we derive an analytical framework that contextualises circular supply chain collaboration. Second, based on this framework, we conduct a systematic literature review that explores how Industry 4.0 technologies can enable collaboration mechanisms. The review shows that information sharing and joint planning and decision-making are the most common collaboration mechanisms studied. Simultaneously, the Internet of Things, Blockchain, and Cloud Systems are the most discussed technologies to enable those mechanisms. The most prominent review sample patterns are synthesised into three archetypes for Industry 4.0-enabled circular supply chain collaboration. Furthermore, the study derives nine promising questions for future research along six main dimensions: Digital Twins and Artificial Intelligence, joint knowledge creation and innovation, collaboration in product design and planning, systemic collaboration across industry boundaries, contextualisation with barriers for implementing circular supply chains, and transferability of applications across industries.
Journal: International Journal of Production Research
Pages: 6967-6995
Issue: 23
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.1999521
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1999521
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# input file: TPRS_A_2002960_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Zhongzheng Liu
Author-X-Name-First: Zhongzheng
Author-X-Name-Last: Liu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Rongfan Liu
Author-X-Name-First: Rongfan
Author-X-Name-Last: Liu
Author-Name: Feifeng Zheng
Author-X-Name-First: Feifeng
Author-X-Name-Last: Zheng
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Risk-averse assembly line worker assignment and balancing problem with limited temporary workers and moving workers
Abstract: 
 Assembly line worker assignment and balancing problem (ALWABP) is an important research topic originated from sheltered work centres for disabled, in which workforce is assumed to be heterogeneous due to their disabilities. Since the employment of disabled workers may sustain higher absenteeism rates due to their health, especially under COVID-19, employing temporary workers to fill labour shortage is a crucial issue. In addition, in practice, the movement of workers between stations on assemble lines can increase the flexibility of worker assignment. In this study, we investigate a new risk-averse ALWABP with uncertain disabled worker availability, limited temporary workers and moving workers. The objective is to minimise the risk-averse weighted sum of the cycle time and the number of employed temporary workers. For the problem, a risk-averse two-stage stochastic programming model is formulated. The first stage assigns specific tasks (called fixed tasks) to stations, while the second stage assigns workers and remaining tasks (called flexible tasks) to stations. A genetic algorithm combining K-means clustering approach and variable neighbourhood search (GAKV) is designed. Experiment results show the superiority of the GAKV in terms of solution quality and computation time compared with sample average approximation (SAA). In addition, managerial insights are drawn.
Journal: International Journal of Production Research
Pages: 7074-7092
Issue: 23
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2002960
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002960
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# input file: TPRS_A_2000655_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Hyun-Jung Kim
Author-X-Name-First: Hyun-Jung
Author-X-Name-Last: Kim
Author-Name: Eun-Seok Kim
Author-X-Name-First: Eun-Seok
Author-X-Name-Last: Kim
Author-Name: Jun-Ho Lee
Author-X-Name-First: Jun-Ho
Author-X-Name-Last: Lee
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Author-Name: Yang Yang
Author-X-Name-First: Yang
Author-X-Name-Last: Yang
Title: Single-machine scheduling with energy generation and storage systems
Abstract: 
 This paper considers a single-machine scheduling problem with sequence-dependent setup times and energy-generation and storage systems. Each job requires a sequence-dependent setup to be processed on the machine, and both setup and processing of the job require job-dependent amounts of energy. The energy consumed by the machine can be bought from an Electric Power Company (EPC) or generated by own Distributed Energy Resource (DER), such as solar photovoltaic or wind, and the energy can be stored in an Energy Storage System (ESS). The objective is to minimise the total cost, the sum of production cost depending on makespan and energy cost by considering energy usage from the EPC, DER and ESS. For the problem, a mathematical programming model is first derived by using period-based indexes. Then, a hybrid genetic algorithm, which adds appropriate idle times between jobs and determines an efficient energy schedule by storing some energy during less expensive periods into the ESS for later use in high-price periods, is developed. Finally, computational experiments show that the proposed algorithm provides effective solutions, and which component of the total cost affects the performance the most, how effective adding idle times between jobs is, and how much cost can be saved by having a DER and ESS.
Journal: International Journal of Production Research
Pages: 7033-7052
Issue: 23
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2000655
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2000655
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# input file: TPRS_A_2002965_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Rony Arsène Djeunang Mezafack
Author-X-Name-First: Rony Arsène
Author-X-Name-Last: Djeunang Mezafack
Author-Name: Maria Di Mascolo
Author-X-Name-First: Maria
Author-X-Name-Last: Di Mascolo
Author-Name: Zineb Simeu-Abazi
Author-X-Name-First: Zineb
Author-X-Name-Last: Simeu-Abazi
Title: Systematic literature review of repair shops: focus on sustainability
Abstract: 
 Maintenance activities are crucial for all manufacturing industries. To ensure availability and lifetime of production equipment, operations management and logistics support for maintenance need to evolve year after year. Besides, Centralised Maintenance Workshops are one of the most interesting approaches to reduce the cost and time required to repair faulty equipment. Generally known in the research community as ‘repair shops’, they aim to pool all the resources needed to repair defective equipment provided by different production sites. This paper aims to provide a comprehensive overview of repair shops and to present opportunities for future research with a focus on the circular economy context. The most relevant papers have been rigorously selected and analyzed, providing interesting reference materials on the subject. Repair shops are a set of workstations, operators, and spare parts inventories required to restore a group of failed production equipment. After detecting the origin of the failures, there are two options: either repair the equipment by restoring its defective components or replace the defective components with others in good working order. In the case of non-repairable components/equipment, circular strategies allow identification of components/equipment that could be restored and used to supply the spare parts warehouse.
Journal: International Journal of Production Research
Pages: 7093-7112
Issue: 23
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2002965
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002965
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# input file: TPRS_A_2000656_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Junegak Joung
Author-X-Name-First: Junegak
Author-X-Name-Last: Joung
Author-Name: Harrison M. Kim
Author-X-Name-First: Harrison M.
Author-X-Name-Last: Kim
Title: Explainable neural network-based approach to Kano categorisation of product features from online reviews
Abstract: 
 The Kano model is an extensively used technique for understanding different types of customer preferences. It classifies product features based on the effects of their performance on the overall customer satisfaction. Compared to surveys, numerous online reviews can be easily collected at a lower cost. This paper proposes an explainable neural network-based approach for the Kano categorisation of product features from online reviews. First, product feature words are identified by clustering nouns based on word embedding. Subsequently, the sentiments of the product feature words are determined by conducting the Vader sentiment analysis. Finally, the effects of the sentiments of each product feature on the star rating are estimated using explainable neural networks. Based on their effects, the product features are classified into the Kano categories. A case study of three Fitbit models is performed to validate the proposed approach. The Kano categorisation by the proposed approach is compared with the results of a previous product feature word clustering and ensemble neural network-based method. The results exhibit that the former presents a more reliable performance than the latter. The proposed approach is automated after providing several hyperparameters and can assist companies in conducting the Kano analysis with increased speed and efficiency.
Journal: International Journal of Production Research
Pages: 7053-7073
Issue: 23
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2000656
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2000656
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# input file: TPRS_A_1999522_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Elham Sharifi
Author-X-Name-First: Elham
Author-X-Name-Last: Sharifi
Author-Name: Atanu Chaudhuri
Author-X-Name-First: Atanu
Author-X-Name-Last: Chaudhuri
Author-Name: Brian Vejrum Waehrens
Author-X-Name-First: Brian
Author-X-Name-Last: Vejrum Waehrens
Author-Name: Lasse Guldborg Staal
Author-X-Name-First: Lasse
Author-X-Name-Last: Guldborg Staal
Author-Name: Christian-Friedrich Lindemann
Author-X-Name-First: Christian-Friedrich
Author-X-Name-Last: Lindemann
Author-Name: Saeed Davoudabadi Farahani
Author-X-Name-First: Saeed
Author-X-Name-Last: Davoudabadi Farahani
Title: Part selection for Freeform Injection Moulding: comparison of alternate approaches using a novel comprehensive methodology
Abstract: 
 The purpose of this study is to provide an overview of a methodology, which will enable the industrial end-users to identify the potential parts to be manufactured by freeform injection moulding (FIM). Our proposed approach can be used ‘with’ or ‘without’ FIM reference parts. In the reference part-based screening method, the process of part selection starts by identifying the most similar parts (from the end-user part libraries) to some reference parts, which can be produced by FIM, followed by part size classification and cluster analysis based on the importance factors. A multi-criteria decision-making approach is then used to rank the clusters and the parts within each cluster using a user-defined criteria. The identification process without using FIM reference part does not include comparison with the reference parts. In both methods, once the first set of potential parts have been identified, the cost of using FIM is calculated using the developed FIM cost model and compared with the production cost using a conventional manufacturing. The novelty of this research lies in using a comprehensive methodology to compare the suitability of a reference part-based approach with the non-reference part-based approach. The results show that using a reference part-based approach is more suitable for the parts with bigger size.
Journal: International Journal of Production Research
Pages: 6996-7012
Issue: 23
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.1999522
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1999522
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# input file: TPRS_A_1998698_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Frank Bodendorf
Author-X-Name-First: Frank
Author-X-Name-Last: Bodendorf
Author-Name: Stefan Merbele
Author-X-Name-First: Stefan
Author-X-Name-Last: Merbele
Author-Name: Jörg Franke
Author-X-Name-First: Jörg
Author-X-Name-Last: Franke
Title: Deep learning based cost estimation of circuit boards: a case study in the automotive industry
Abstract: 
 Early cost estimation is a decisive value driver in the product development process in manufacturing industries. Machine learning offers new intelligent methods to support traditional cost calculation processes. While traditional research on intelligent cost estimation focuses on machine learning regression or classification models, we propose a new approach based on interlocking deep learning methods. In this paper we investigate the applicability of deep learning techniques, focusing on image recognition and deep learning regression as well as autoencoding to estimate product costs of circuit boards to be purchased. We create and evaluate deep learning models using real-world data from an original equipment manufacturer (OEM). Our findings suggest that deep learning models can streamline cost calculation and estimation processes while deep learning object recognition-based cost estimation outperforms autoencoding techniques. This research is designed to be transferable to other cost estimation projects.
Journal: International Journal of Production Research
Pages: 6945-6966
Issue: 23
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.1998698
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1998698
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# input file: TPRS_A_2004465_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yue Li
Author-X-Name-First: Yue
Author-X-Name-Last: Li
Author-Name: Xiaobo Zhao
Author-X-Name-First: Xiaobo
Author-X-Name-Last: Zhao
Author-Name: Jinxing Xie
Author-X-Name-First: Jinxing
Author-X-Name-Last: Xie
Author-Name: Wanshan Zhu
Author-X-Name-First: Wanshan
Author-X-Name-Last: Zhu
Title: Inequality aversion in cooperative advertising in supply chain: an experimental study
Abstract: 
 In this study, we experimentally investigate the decisions of a manufacturer and a retailer in cooperative advertising. Specifically, in the first stage, the manufacturer proposes the percentage he will reimburse on the advertising expenditure, and then the retailer decides the advertising expenditure in the second stage. In the controlled laboratory experiments, we find that the manufacturer's and the retailer's decisions systematically deviate from the equilibrium prediction and exhibit inequality aversion on both cost and profit. The manufacturer tends to share half of the advertising cost and also decreases the participation rate when his profit is less than the retailer, whereas the retailer decreases the advertising expenditure to reduce the gap on cost and profit between the two parties. We further develop behavioural models and show that the manufacturer's inequality aversion on cost can be a positive force, because it increases the supply chain profit when the profit margin ratio is relatively low between the manufacturer and the retailer.
Journal: International Journal of Production Research
Pages: 7113-7135
Issue: 23
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2004465
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2004465
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# input file: TPRS_A_2075811_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Mohit Goswami
Author-X-Name-First: Mohit
Author-X-Name-Last: Goswami
Author-Name: Yash Daultani
Author-X-Name-First: Yash
Author-X-Name-Last: Daultani
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: Saurabh Pratap
Author-X-Name-First: Saurabh
Author-X-Name-Last: Pratap
Title: Assessing the impact of supplier benchmarking in manufacturing value chains: an Intelligent decision support system for original equipment manufacturers
Abstract: 
 This research aims to aid original equipment manufacturers (OEMs) to model, analyze, evaluate, and benchmark potential design and manufacturing suppliers based on respective product engineering teams’ efficiencies. The product engineering efficiency in this study is modeled in terms of product engineering-related attributes such as commercial lead time, number of parts, number of green features, number of end products developed, and so forth. Essentially, these parameters capture more complex interactions than simple traditional supplier selection criteria such as cost, quality, delivery, and flexibility. Due to the presence of information uncertainty in terms of bounds related to the suppliers’ related parameters, a number of data envelopment analysis (DEA) efficiency measurement models have been deployed. The proposed decision support system is novel because it models both the self-assessment type and cross-efficiency type using DEA such that maximum discrimination can be achieved amongst suppliers in the presence of interval data. The study is demonstrated for ten different sheet-metal cabin suppliers. Comparison with some well-known, relevant methods is also carried out to illustrate the validity of the proposed method. The research can specifically help supply chain managers to align the evaluation of potential suppliers with their firm's commercial considerations in the presence of information uncertainty.
Journal: International Journal of Production Research
Pages: 7411-7435
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2075811
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2075811
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# input file: TPRS_A_2034192_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Dhirendra Prajapati
Author-X-Name-First: Dhirendra
Author-X-Name-Last: Prajapati
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Author-Name: Yash Daultani
Author-X-Name-First: Yash
Author-X-Name-Last: Daultani
Author-Name: Saurabh Pratap
Author-X-Name-First: Saurabh
Author-X-Name-Last: Pratap
Title: Sustainable vehicle routing of agro-food grains in the e-commerce industry
Abstract: 
 As a result of rapid industrialisation, rising food demand globally, and, increasing concerns associated with food safety and quality, the implementation of sustainable supply chain concepts is becoming critically important to the agro-food sector. This paper introduces an integrated first-mile pickup and last-mile delivery logistics problem, where agro-food grains are available at multiple farmer’s locations and are in demand by businesses like e-retailers, supermarkets, grocery shops, restaurants, hotels, etc. In addition, this work addresses a sustainable framework for agro-food grains supply chain (AFGSC) in urban and rural areas for e-commerce in developing countries. The proposed optimisation model considers costs related to first-mile pickup, transportation with last-mile delivery, carbon emission tax, inventory holding, vehicle and food damage due to accidents, and penalties on late pickup and delivery. This model also takes environmental and social (due to accidents) sustainability aspects into consideration, along with the economic aspects of sustainability. To solve the large complex practical scenarios by using four nature-inspired algorithms. The obtained results of this study are used to recommend significant managerial insights for implementing AFGSC in the e-commerce industry in considering practical conditions. Moreover, policy implications in terms of economic, social, and environmental aspects of sustainability are also discussed.
Journal: International Journal of Production Research
Pages: 7319-7344
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2034192
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2034192
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# input file: TPRS_A_2078248_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Hoda ElMaraghy
Author-X-Name-First: Hoda
Author-X-Name-Last: ElMaraghy
Author-Name: Waguih ElMaraghy
Author-X-Name-First: Waguih
Author-X-Name-Last: ElMaraghy
Title: Adaptive Cognitive Manufacturing System (ACMS) – a new paradigm
Abstract: 
 Innovation and transformative changes in products, manufacturing technologies, business strategies, and manufacturing paradigms have profoundly changed the manufacturing systems. In addition to being environmentally, economically socially sustainable, manufacturing systems are increasingly using intelligent technologies to be even more resilient, responsive, and adaptable. A new Adaptive Cognitive Manufacturing Systems (ACMS) paradigm, its drivers, enablers, and characteristics, including cognitive adaptation, is presented. Classification and definitions of four types of adaptability in manufacturing systems are included. Human-centric collaboration of workers and intelligent machines and applications, and the future of work in cognitive adaptive manufacturing systems are outlined. Cognitive Digital Twins (CDT), their features, evolution, and their use to support humans in intelligent, collaborative manufacturing settings are discussed. Industrial applications and case studies are used to illustrate the presented concepts and paradigms. Challenges and future research directions to achieve the ACMS paradigm and implement more intelligent, more adaptive, and sustainable manufacturing systems are presented. The presented novel concepts and technologies make significant contributions to the fast-evolving field of manufacturing systems. This pioneering research sheds light on many important future research topics and provides a road map and motivation for researchers in this field.
Journal: International Journal of Production Research
Pages: 7436-7449
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2078248
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2078248
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# input file: TPRS_A_2013565_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xi Gu
Author-X-Name-First: Xi
Author-X-Name-Last: Gu
Author-Name: Yoram Koren
Author-X-Name-First: Yoram
Author-X-Name-Last: Koren
Title: Mass-Individualisation – the twenty first century manufacturing paradigm
Abstract: 
 The forthcoming paradigm of Mass-Individualisation will combine the low-cost advantage of the Mass-Production paradigm with the buyer’s individual need of a specific product. The buyers will initiate the product and its features that fit their explicit taste and individual needs, and the manufacturer will build it at low cost in a local factory, which enables a rapid communication of the factory with the buyer. The realisation of the mass-individualisation paradigm requires innovations in (a) product development, (b) manufacturing system and network design, (c) system operations, and (d) business strategies. New factories will have to be in proximity to the customers who participate in the design of their product, which will have an enormous economic impact on local economies. We elaborate on the research challenges and directions for the realisation of the emerging mass-individualisation paradigm.
Journal: International Journal of Production Research
Pages: 7572-7587
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2013565
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2013565
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# input file: TPRS_A_2121870_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Shaojian Qu
Author-X-Name-First: Shaojian
Author-X-Name-Last: Qu
Author-Name: Lei Xu
Author-X-Name-First: Lei
Author-X-Name-Last: Xu
Author-Name: Sachin Kumar Mangla
Author-X-Name-First: Sachin Kumar
Author-X-Name-Last: Mangla
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Author-Name: Jianli Zhu
Author-X-Name-First: Jianli
Author-X-Name-Last: Zhu
Author-Name: Sobhan Arisian
Author-X-Name-First: Sobhan
Author-X-Name-Last: Arisian
Title: Matchmaking in reward-based crowdfunding platforms: a hybrid machine learning approach
Abstract: 
 Traditional clustering methods fail to accurately cluster the feature vectors of backers and macth the potential backers to compatible crowdfunding projects, mainly due to their sensitivity to the setting of the initial value. In this paper, we use the Apriori algorithm in conjunction with other machine learning tools to cluster the potential backers  and provide more accurate recommendations for crowdfunding projects. Focusing on potential projects listed in a major reward-based crowdfunding platform, we first train the data obtained from the available list of backers. Using the Apriori algorithm, the degree of association between different project backers is then obtained, and weight calculation of the backers is carried out according to the association degree of the backers. The degree of association is used as a key index to cluster similar backers. Finally, we test the model and determine whether clustering can correctly classify the data in the test set based on the Apriori algorithm. Our experimental results show that there is 90% accuracy, precision and recall of the model. The proposed solution outperforms the other five benchmark methods and offers an imporved matchmaking by connecting the listed crowdfunding projects to the right backers.
Journal: International Journal of Production Research
Pages: 7551-7571
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2121870
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2121870
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# input file: TPRS_A_2077672_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Agus Wicaksana
Author-X-Name-First: Agus
Author-X-Name-Last: Wicaksana
Author-Name: William Ho
Author-X-Name-First: William
Author-X-Name-Last: Ho
Author-Name: Srinivas Talluri
Author-X-Name-First: Srinivas
Author-X-Name-Last: Talluri
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: A decade of progress in supply chain risk management: risk typology, emerging topics, and research collaborators
Abstract: 
 Contemporary supply chains are facing myriad types of risks caused by unprecedented risk factors. This condition motivates us to develop a contemporary supply chain risk typology to help identify and monitor newly surfaced risks and reveal emerging topics and research collaborators to help foster impactful research in supply chain risk management (SCRM). In this paper, we applied the scholarly network analysis approach to critically analyse an extensive list of 345 SCRM journal articles published from 2011 to 2020. We address two research questions: What is the contemporary supply chain risk typology? How can SCRM research be mapped comprehensively in terms of its emerging topics and research collaborators? First, we propose a novel and holistic classification of supply chain risks based on three interconnected perspectives, namely the characteristics, the location, and the impact of risks. Second, we identify five emerging SCRM topics. In each of these emerging topics, we identify the prominent collaborators and the core author, the main research themes, commonly used approaches and theories, and potential research agendas for bridging the identified research gaps. This paper contributes to the field of SCRM by aiding scholars and practitioners in managing contemporary supply chains resiliently and sustainably.
Journal: International Journal of Production Research
Pages: 7155-7177
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2077672
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2077672
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# input file: TPRS_A_2028922_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Author-Name: Sherwat Ibrahim
Author-X-Name-First: Sherwat
Author-X-Name-Last: Ibrahim
Title: Building knowledge beyond our experience: integrating sustainable development goals into IJPR’s research future
Abstract: 
 The United Nations’ sustainable development goals (SDGs) are now entering their decade of action. We are supporting this decade by further encouraging the International Journal of Production Research (IJPR) and its scholarly community to lead on contributing to global SDGs through research, knowledge development, and dissemination. There are islands of excellence that are evident from the past 60 years of IJPR research – especially in ecologically sustainable production-related SDG. There are also serious SDG gaps – for example, general environmental, gender, and inclusiveness research – that can provide additional insights that can greatly advance the IJPR disciplines. This thematic analysis ends with a number of recommendations that seek to expand our experiences and knowledge.
Journal: International Journal of Production Research
Pages: 7301-7318
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2028922
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2028922
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# input file: TPRS_A_2023911_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Mostafa Moussa
Author-X-Name-First: Mostafa
Author-X-Name-Last: Moussa
Author-Name: Hoda ElMaraghy
Author-X-Name-First: Hoda
Author-X-Name-Last: ElMaraghy
Title: Multi-period additive/subtractive product platform design and inventory management
Abstract: 
 Forming product platforms is an effective strategy to offer products variety economically. The short products life span and new variants pose a challenge to designing platforms, which satisfy the changing customer demands. There is a need to design platforms that can adapt to changes. In addition, it is important to account for the partially completed platforms inventory held in each production period which could be utilised in subsequent production periods. An important contribution of this work is the use of combined additive and subtractive manufacturing in customising the product platform by adding and/or removing features to suit the changing product features and demands for different product variants. In this paper, a holistic non-linear model is presented for designing optimal multi-period additive/subtractive product platforms and managing their inventory. The model provides the optimal product platform design for each production period, macro process plans for customisation, the number of each platform stored as inventory, and the product variant platform assignment. The initial model is subsequently linearised to reduce computation time. A gear shaft family of products is used as a demonstration example. The model redesigns the product platform as needed to meet the changing demand of each product variant while minimising the costs.
Journal: International Journal of Production Research
Pages: 7262-7280
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2023911
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2023911
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# input file: TPRS_A_2036853_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Fayez F. Boctor
Author-X-Name-First: Fayez F.
Author-X-Name-Last: Boctor
Title: Single-machine capacitated lot-sizing and scheduling with delivery dates and quantities
Abstract: 
 This paper deals with the more realistic version of the lot sizing and scheduling problem where we have a single machine that process a number of different products and for each product we have a set of delivery dates and the quantities to deliver at each of these dates. The objective is to minimise the sum of setup costs and inventory holding costs including the holding cost of products from the finish time of each production lot to the next delivery date. In addition, a setup can be carried over from a production run to the immediately succeeding one if the same product is processed during these two runs. A mathematical formulation of this problem is given as well as two specially designed solution heuristics. As the literature does not provide any other method to solve this problem, only the results obtained by these two heuristics are compared.
Journal: International Journal of Production Research
Pages: 7345-7359
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2036853
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2036853
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# input file: TPRS_A_2118889_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: The shortage economy and its implications for supply chain and operations management
Abstract: 
 Supply chain (SC) and operations management has been developed for decades under the fundamental assumption of continuous availability (with some temporary fluctuations and disruptions) of resources to satisfy demand. Under extreme shocks and long-lasting disruptions, SCs and operations face long-term shortages of components, energy, capital, and labour, as well as rapidly rising prices. These long-term resource shortages and risks of hyper-inflation pose novel and unexpected challenges potentially leading to global ripple effects. In this conceptual paper, we first analyse and categorise the available literature on SC and operations management with resource shortages. We then systemise some managerial implications of resource shortages and rising inflation, conceptualising some potential research directions which appeared or may appear in the settings of shortage economy. We conclude that the shortage economy provides a distinct and specific context which goes beyond the conventional problems under constrained or disrupted resources – i.e. the long-term resource shortages with simultaneous disruptions in labour, material, energy, and capital availability. This paper could be useful for researchers and practitioners alike to systemise potential impacts of a shortage economy on SCs and operations, and to navigate adaptation and recovery processes in a structured way to help society cope with deep uncertainties.
Journal: International Journal of Production Research
Pages: 7141-7154
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2118889
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2118889
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# input file: TPRS_A_2031332_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Robert W. Grubbström
Author-X-Name-First: Robert W.
Author-X-Name-Last: Grubbström
Title: Incorporating non-empty initial states into MRP Theory
Abstract: 
 MRP theory is a theoretical body treating production-inventory systems, in which produced items are made up of sets of produced or purchased sub-items, required to be available a lead-time before each product is completed. The hierarchical dependence between items is captured using input matrices from input-output-analysis, the necessary advanced timing by employing Laplace transform methodology, and the economic consequences by applying the net present value. Little attention has hitherto been given to aspects of a non-empty initial state, e.g. an initial inventory position. Since such states are common in industry, there is a strong need for this theory to include such aspects, in order to gain further practical acceptance. In this paper, theoretical consequences from having a non-empty initial state are investigated. A method for finding the Lot-for-Lot solution is developed using the concept of a truncated monotonically non-decreasing time function, generalising the approach of the generalised Leontief inverse and instrumental for designing plans meeting the necessary inner-corner requirement for optimality. Also the definition of inventory-related costs needs a modification for this concept to be consistent with NPV. These findings are applied in an extensive numerical example. Immediate future research concerns investigating principles for the optimal removal of initial backlogs.
Journal: International Journal of Production Research
Pages: 7281-7300
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2031332
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2031332
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# input file: TPRS_A_2072786_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Siddhartha Kushwaha
Author-X-Name-First: Siddhartha
Author-X-Name-Last: Kushwaha
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Author-Name: Kaustov Chakraborty
Author-X-Name-First: Kaustov
Author-X-Name-Last: Chakraborty
Author-Name: Saurabh Pratap
Author-X-Name-First: Saurabh
Author-X-Name-Last: Pratap
Title: Collection and remanufacturing channels selection under a product take-back regulation with remanufacturing target
Abstract: 
 Consider a product take-back regulation with remanufacturing target imposed on a manufacturer. The manufacturer is responsible for regulation compliance by remanufacturing the product collected from multiple geographic regions. The channel alternatives for the manufacturer are 1) regional third-party collection firms, 2) regional third-party collection-remanufacturing firms, 3) a third-party firm for remanufacturing, 4) in-house collection, and 5) in-house remanufacturing. The paper proposes a mixed-integer linear programming problem (MILP) formulation for the manufacturer to select a combination of these channels to maximise the profit over a finite planning horizon. The decision model has the number of used products, remanufacturing approach, heterogeneity in the quality of returned products, and the remanufacturing target as constraints. We conduct numerical analysis using field study data for 200 litres of mild-steel drums in India to draw managerial insights. The vital suggestions and insights are as follows. 1) Regulators to impose incremental targets considering the current optimum level of remanufacturing. 2) A comprehensive remanufacturing target covering multi-region/market to discourage manufacturers from evading behaviour. 3) Managers to assist regional firms in increasing the recovery rate of products that can collect and remanufacture. 5) Manufacturers to remanufacture products during the decline stage of product life cycle (PLC) for higher profits.
Journal: International Journal of Production Research
Pages: 7384-7410
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2072786
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2072786
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# input file: TPRS_A_2029611_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Rohit Sharma
Author-X-Name-First: Rohit
Author-X-Name-Last: Sharma
Author-Name: Anjali Shishodia
Author-X-Name-First: Anjali
Author-X-Name-Last: Shishodia
Author-Name: Angappa Gunasekaran
Author-X-Name-First: Angappa
Author-X-Name-Last: Gunasekaran
Author-Name: Hokey Min
Author-X-Name-First: Hokey
Author-X-Name-Last: Min
Author-Name: Ziaul Haque Munim
Author-X-Name-First: Ziaul Haque
Author-X-Name-Last: Munim
Title: The role of artificial intelligence in supply chain management: mapping the territory
Abstract: 
 The study aims to identify the current trends, gaps, and research opportunities in research pertaining to the disruptive field of artificial intelligence (AI) applications in supply chain management (SCM). Since SCM represents managerial innovation due to its new way of integrated system thinking, SCM has emerged as one of the most fruitful business disciplines for AI applications. The study utilises bibliometric review in tracing the evolution of AI research in SCM and further synthesises decades of past AI research efforts to develop viable solutions for various supply chain problems and then proposes promising future research themes that would enrich supply chain decision-aid tools. The study identified five main research clusters through scholarly network and content analysis. The identified themes were: (a) supply chain network design (SCND), (b) supplier selection, (c) inventory planning, (d) demand planning, and (e) green supply chain management. As the role of AI in SCM continues to grow, there is a growing need for exploiting AI as a way to add value to supply chain process. The study proposes a research framework which will help academicians and practitioners in identifying current research patterns of AI in SCM.
Journal: International Journal of Production Research
Pages: 7527-7550
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2029611
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2029611
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# input file: TPRS_A_2028031_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xufeng Yao
Author-X-Name-First: Xufeng
Author-X-Name-Last: Yao
Author-Name: Nourah Almatooq
Author-X-Name-First: Nourah
Author-X-Name-Last: Almatooq
Author-Name: Ronald G. Askin
Author-X-Name-First: Ronald G.
Author-X-Name-Last: Askin
Author-Name: Greg Gruber
Author-X-Name-First: Greg
Author-X-Name-Last: Gruber
Title: Capacity planning and production scheduling integration: improving operational efficiency via detailed modelling
Abstract: 
 Successful capacity planning and production scheduling is built on the understanding of market opportunities and the costs of capacity, production, sourcing, inventory, and distribution over the planning horizon. Increasingly, companies attempt to integrate capacity planning and production scheduling to improve upon the commonly used sequential decision process, but most related research works fail to capture the granularity of actual operational decisions and therefore may overlook potential cost-saving opportunities. The contributions of this study include: (1) a detailed integrated capacity and production scheduling model with multiple discrete and continuous options for varying short and medium-term capacity, (2) a heuristic algorithm that exploits the problem structure to solve the nonlinear mixed integer problem, (3) an evaluation of the value of the integrated model relative to traditional practice and its sensitivity to parameters, (4) a review of past contributions to integrated planning, particularly focused on IJPR, and (5) a case study originated from a world-class automobile manufacturer illustrating how the model can be applied and confirming its value relative to hierarchical and less detailed modelling approaches.
Journal: International Journal of Production Research
Pages: 7239-7261
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2028031
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2028031
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2110014_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Burcu Balcik
Author-X-Name-First: Burcu
Author-X-Name-Last: Balcik
Author-Name: Ecem Yucesoy
Author-X-Name-First: Ecem
Author-X-Name-Last: Yucesoy
Author-Name: Berna Akca
Author-X-Name-First: Berna
Author-X-Name-Last: Akca
Author-Name: Sirma Karakaya
Author-X-Name-First: Sirma
Author-X-Name-Last: Karakaya
Author-Name: Asena A. Gevsek
Author-X-Name-First: Asena A.
Author-X-Name-Last: Gevsek
Author-Name: Hossein Baharmand
Author-X-Name-First: Hossein
Author-X-Name-Last: Baharmand
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Title: A mathematical model for equitable in-country COVID-19 vaccine allocation
Abstract: 
 Given the scarcity of COVID-19 vaccines, equitable (fair) allocation of limited vaccines across the main administrative units of a country (e.g. municipalities) has been an important concern for public health authorities worldwide. In this study, we address the equitable allocation of the COVID-19 vaccines inside countries by developing a novel, evidence-based mathematical model that accounts for multiple priority groups (e.g. elderly, healthcare workers), multiple vaccine types, and regional characteristics (e.g. storage capacities, infection risk levels). Our research contributes to the literature by developing and validating a model that proposes equitable vaccine allocation alternatives in a very short time by (a) minimising deviations from the so-called ‘fair coverage’ levels that are computed based on weighted pro-rata rations, and (b) imposing minimum coverage thresholds to control the allocation of vaccines to higher priority groups and regions. To describe the merits of our model, we provide several equity and effectiveness metrics, and present insights on different allocation policies. We compare our methodology with similar models in the literature and show its better performance in achieving equity. To illustrate the performance of our model in practice, we perform a comprehensive numerical study based on actual data corresponding to the early vaccination period in Turkey.
Journal: International Journal of Production Research
Pages: 7502-7526
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2110014
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2110014
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# input file: TPRS_A_2098075_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Hanbo Yang
Author-X-Name-First: Hanbo
Author-X-Name-Last: Yang
Author-Name: S. K. Ong
Author-X-Name-First: S. K.
Author-X-Name-Last: Ong
Author-Name: A. Y. C. Nee
Author-X-Name-First: A. Y. C.
Author-X-Name-Last: Nee
Author-Name: Gedong Jiang
Author-X-Name-First: Gedong
Author-X-Name-Last: Jiang
Author-Name: Xuesong Mei
Author-X-Name-First: Xuesong
Author-X-Name-Last: Mei
Title: Microservices-based cloud-edge collaborative condition monitoring platform for smart manufacturing systems
Abstract: 
 In the context of the Industrial Internet of things (IIoT), large-scale IIoT data is generated, which can be effectively mined to provide valuable information for condition monitoring (CM). However, traditional CM methods cannot meet unprecedented challenges concerning large-scale IIoT data transmission, storage and analysis. Therefore, manufacturers have begun to shift from the traditional manufacturing paradigm to smart manufacturing, which integrates the encapsulated manufacturing services and the enabling cloud-edge computing technology to handle large-scale IIoT data. To enhance the agility, scalability and portability of traditional manufacturing services, a microservices-based cloud-edge collaborative CM platform for smart manufacturing systems is proposed. First, leveraging the microservices management system, the lightweight edge and cloud services are constructed from the microservices level, which enables flexible deployment and upgrade of services. Next, the proposed platform architecture effectively integrates the computing and storage capabilities of the cloud layer and the real-time nature of the edge layer, where the cloud-edge collaborative mechanism is introduced to achieve real-time diagnosis and enhance prognosis accuracy. Finally, based on the proposed system, the diagnosis and prognosis tasks are implemented on a manufacturing line, and the results show that the diagnostic accuracy is 90% and the prediction error is 50%.
Journal: International Journal of Production Research
Pages: 7492-7501
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2098075
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2098075
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# input file: TPRS_A_1971318_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yuanfu Li
Author-X-Name-First: Yuanfu
Author-X-Name-Last: Li
Author-Name: Jinwei Chen
Author-X-Name-First: Jinwei
Author-X-Name-Last: Chen
Author-Name: Zhenchao Hu
Author-X-Name-First: Zhenchao
Author-X-Name-Last: Hu
Author-Name: Huisheng Zhang
Author-X-Name-First: Huisheng
Author-X-Name-Last: Zhang
Author-Name: Jinzhi Lu
Author-X-Name-First: Jinzhi
Author-X-Name-Last: Lu
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: Co-simulation of complex engineered systems enabled by a cognitive twin architecture
Abstract: 
 Since the complex engineered system involves multi-disciplinary, co-simulation is the key technique to the performance analysis. However, the co-simulation is hindered by heterogeneous sub-systems and ununified environments. In this paper, a Cognitive Twin (CT) to support the co-simulation of the complex engineered system is introduced. It is a generic approach that can be applied in many complex engineered systems such as the aerospace field, automotive system, the Internet of Things, manufacturing systems, etc. CT adopts an ontology model to develop cognition capability based on CT architecture. Then, a unified ontology modelling approach based on GOPPRR (graph, object, point, property, role, relationship) is presented to support an accurate semantic description of the topology between digital entities that use FMI 2.0 as the interconnection standard. Besides, four types of information are included in the ontology model to form the knowledge in co-simulation. Finally, the co-simulation is automatically executed using the cognition capability. Furthermore, a master-slave algorithm is deployed to establish a unified co-simulation environment. The flexibility of CT is evaluated using a gas turbine case. The results demonstrate that the complication in the co-simulation of complex engineered systems is solved by the unified ontology modelling approach and the architecture of CT.
Journal: International Journal of Production Research
Pages: 7588-7609
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.1971318
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1971318
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2023912_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Jelena Petronijevic
Author-X-Name-First: Jelena
Author-X-Name-Last: Petronijevic
Author-Name: Alain Etienne
Author-X-Name-First: Alain
Author-X-Name-Last: Etienne
Author-Name: Ali Siadat
Author-X-Name-First: Ali
Author-X-Name-Last: Siadat
Title: Global risk assessment for development processes: from framework to simulation
Abstract: 
 The dynamic and complex nature of development processes calls for improvements in risk management methods. To deal with the risks, the authors advocate for a paradigm shift. The focus is moving from individual risk to risk interactions. Standards suggest integrating methods to address the limitations imposed by existing approaches. As a result, new strategies are needed to express and assess risk connections. The paper proposes a global framework and its simulator for: (a) representing individual risk events and including them in a product development, (b) expressing risk interactions, (c) integrating risks hierarchically and (d) evaluating risks. The solution is based on distinction between individual risk events and global process and its risk behaviour. Risk behaviour is characterised on task level. Process behaviour enables the integration of task risk into the development process. Risk management is viewed as a part of the development process, with final risk assessed bottom-up from individual risk to process risk. Consequently, the main contribution is not only in taking risk interactions into account but also in contextualising risk assessment in relation to development processes. Simulation is conducted for hair dryer design. However, the solution is global and can be used for other manufacturing and development processes.
Journal: International Journal of Production Research
Pages: 7214-7238
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2023912
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2023912
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# input file: TPRS_A_2018519_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Kosmas Alexopoulos
Author-X-Name-First: Kosmas
Author-X-Name-Last: Alexopoulos
Author-Name: Ioannis Anagiannis
Author-X-Name-First: Ioannis
Author-X-Name-Last: Anagiannis
Author-Name: Nikolaos Nikolakis
Author-X-Name-First: Nikolaos
Author-X-Name-Last: Nikolakis
Author-Name: George Chryssolouris
Author-X-Name-First: George
Author-X-Name-Last: Chryssolouris
Title: A quantitative approach to resilience in manufacturing systems
Abstract: 
 Resilience is one of the key characteristics that manufacturing systems should have as it offers the ability to withstand difficult situations and be able to accommodate disruptions without the incurrence of significant additional costs. The main contribution of this study is the presentation of a method for quantifying resilience in manufacturing systems based on calculating the penalty of possible changes. The method is applied to an industrially-relevant scenario to estimate the resilience of two production systems when COVID-19 disrupts their production. The first system uses additive manufacturing (3D printing), and the second uses injection moulding. Several scenarios, related to the systems’ operational environment, are presented on the basis of pandemic-related possible events. The validation of the proposed resilience measure demonstrates the method’s suitability and reliability to be considered in industrial practice, in support of decision-making. The resilience measure can be used by managers to assess, compare and improve their production systems, and decide on strategic investment costs to improve systems’ resilience. It can be applied for several disruption scenarios or variations of the same disruption scenario with different disruption characteristics, such as duration, recovery time and impact on the production system.
Journal: International Journal of Production Research
Pages: 7178-7193
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2018519
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2018519
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# input file: TPRS_A_2065549_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Chaorui Huang
Author-X-Name-First: Chaorui
Author-X-Name-Last: Huang
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Author-Name: S. H. Chung
Author-X-Name-First: S. H.
Author-X-Name-Last: Chung
Title: The impact of payment term extensions on the working capital management of an automotive supply chain
Abstract: 
 Substantial evidence has shown that payment delays generate negative effects on suppliers’ working capital level and thus can further affect the entire supply chain’s working capital efficiency and even result in bankruptcy for capital-constrained suppliers. The adoption of emerging solutions such as supply chain finance (SCF) is considered an innovative approach to deal with this issue. However, the current literature seldom considers the impact of payment term extensions on the supply chain’s working capital management (WCM) through the development of applicable SCF methods. Thus, motivated by how SCF can improve a supply chain’s WCM in the presence of payment delay, we establish a multi-cycle model and identify the conditions under which extended payments will impact on the supply chain’s collaborative cash to cash (CC2C) cycle and the shareholder-value added (SVA). Finally, the numerical analysis not only confirms the major findings of this paper but also provides some additional insights that can assist practitioners in mitigating the adverse effects caused by payment delays.
Journal: International Journal of Production Research
Pages: 7360-7383
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2065549
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2065549
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# input file: TPRS_A_2085634_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Abdelrahman E. E. Eltoukhy
Author-X-Name-First: Abdelrahman E. E.
Author-X-Name-Last: Eltoukhy
Author-Name: Z. X. Wang
Author-X-Name-First: Z. X.
Author-X-Name-Last: Wang
Author-Name: I. A. Shaban
Author-X-Name-First: I. A.
Author-X-Name-Last: Shaban
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Title: Coordinating aircraft maintenance routing and integrated maintenance staffing and rostering: a Stackelberg game theoretical model
Abstract: 
 There is an interdependence between operational-based flight delay aircraft maintenance routing problem (AMRPD) and maintenance staffing problem (MSP). Furthermore, MSP and maintenance rostering problem (MRP) are interdependent. In the literature, most of the studies only consider a single interdependence and neglect the other one. This results in difficulties in implementing the optimal plan constructed by each problem, leading finally to an increase in the operational cost of airlines and maintenance providers. Therefore, the main objective of this study is to investigate these interdependences simultaneously. This is accomplished by developing a Stackelberg game model (LFSGM), in which leader and follower are the airlines and maintenance providers, respectively. This LFSGM is modelled as a bi-level mixed integer linear programming (MILP) model. The upper-level is represented by the AMRPD, while the integrated maintenance staffing and rostering (IMSR) functions as the lower-level. The solution of the LFSGM is obtained from an iterative algorithm. The viability and superiority of the LFSGM are demonstrated by presenting a case study of a leading airline in the Middle East serviced by four maintenance providers. The results reveal a significant cost saving for airline and maintenance providers.
Journal: International Journal of Production Research
Pages: 7450-7474
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2085634
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2085634
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2086083_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Zhaohui Geng
Author-X-Name-First: Zhaohui
Author-X-Name-Last: Geng
Author-Name: Arman Sabbaghi
Author-X-Name-First: Arman
Author-X-Name-Last: Sabbaghi
Author-Name: Bopaya Bidanda
Author-X-Name-First: Bopaya
Author-X-Name-Last: Bidanda
Title: A framework of tolerance specification for freeform point clouds and capability analysis for reverse engineering processes
Abstract: 
 The combination of reverse engineering (RE) with additive manufacturing (AM) is widely used for solid freeform fabrication and overcomes limitations with the current capabilities of designers and CAD packages that are restricted to classical model shapes. The shape flexibility offered by RE typically leads to the generated CAD models being represented in point cloud formats or stereolithography files. One resulting challenge is the difficulty with tolerance specification for the RE-generated models, especially for freeform shapes. Geometric metrology for the AM-produced parts to determine their geometric conformation can also be involved. Furthermore, conventional process analyses cannot be performed directly after RE because of the complex geometric data structure. We propose to address all these issues with a new tolerance specification and process analysis framework based on volumetric data analysis. The tolerance zone constructed under our framework, and the corresponding geometric measurements, are consistent with the profile tolerance in geometric dimensioning and tolerancing standards. Reverse engineering's process capability is assessed under our methodology via a parametric bootstrap procedure in the size-and-shape space. The performance and utility of the proposed framework are validated via a process capability study on RE-generated CAD models of multiple, additively manufactured freeform objects.
Journal: International Journal of Production Research
Pages: 7475-7491
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2086083
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2086083
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2014591_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xiaochen Zheng
Author-X-Name-First: Xiaochen
Author-X-Name-Last: Zheng
Author-Name: Jinzhi Lu
Author-X-Name-First: Jinzhi
Author-X-Name-Last: Lu
Author-Name: Dimitris Kiritsis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Kiritsis
Title: The emergence of cognitive digital twin: vision, challenges and opportunities
Abstract: 
 As a key enabling technology of Industry 4.0, Digital Twin (DT) has been widely applied to various industrial domains covering different lifecycle phases of products and systems. To fully realize the Industry 4.0 vision, it is necessary to integrate multiple relevant DTs of a system according to a specific mission. This requires integrating all available data, information and knowledge related to the system across its entire lifecycle. It is a challenging task due to the high complexity of modern industrial systems. Semantic technologies such as ontology and knowledge graphs provide potential solutions by empowering DTs with augmented cognitive capabilities. The Cognitive Digital Twin (CDT) concept has been recently proposed which reveals a promising evolution of the current DT concept towards a more intelligent, comprehensive, and full lifecycle representation of complex systems. This paper reviews existing studies relevant to the CDT concept, and further explores its definitions and key features. To facilitate CDT development, a reference architecture is proposed based on the RAMI4.0 and some other existing architectures. Moreover, some key enabling technologies and several application scenarios of CDT are introduced. The challenges and opportunities are discussed in the end to boost future studies.
Journal: International Journal of Production Research
Pages: 7610-7632
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2021.2014591
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2014591
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# input file: TPRS_A_2027038_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Saurabh Ambulkar
Author-X-Name-First: Saurabh
Author-X-Name-Last: Ambulkar
Author-Name: Sridhar Ramaswami
Author-X-Name-First: Sridhar
Author-X-Name-Last: Ramaswami
Author-Name: Jennifer Blackhurst
Author-X-Name-First: Jennifer
Author-X-Name-Last: Blackhurst
Author-Name: M. Johnny Rungtusanatham
Author-X-Name-First: M.
Author-X-Name-Last: Johnny Rungtusanatham
Title: Supply chain disruption risk: an unintended consequence of product innovation
Abstract: 
 Growth is one of the more important strategic priorities for top managers today and product innovation is a necessary strategy for achieving that goal. While product innovation is beneficial and necessary, it also introduces greater complexity and uncertainty in a firm’s operations. We focus in this study on an untested negative consequence of product innovation-induced complexity and uncertainty – namely, increased supply chain disruption risk. Using data from multiple sources that combines product innovation-related data from firm websites, patent services websites and key informant interview data for 164 firms, we empirically show that greater product innovation activity is associated with greater supplier dependence and increased product variety which, in turn, increase the supply chain disruption risk faced by firms. We also examine if a firm’s central position in the supply network mitigates the disruption risk it faces because of greater supplier dependence. Similarly, we examine if external knowledge utilisation mitigates the disruption risk faced by the firm because of greater product variety.
Journal: International Journal of Production Research
Pages: 7194-7213
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2027038
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2027038
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# input file: TPRS_A_2147744_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Editorial Board contributions celebrating the 60th Anniversary of IJPR: Part 3
Journal: International Journal of Production Research
Pages: 7136-7140
Issue: 24
Volume: 60
Year: 2022
Month: 12
X-DOI: 10.1080/00207543.2022.2147744
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2147744
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# input file: TPRS_A_2131930_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ruibin Bai
Author-X-Name-First: Ruibin
Author-X-Name-Last: Bai
Author-Name: Zhi-Long Chen
Author-X-Name-First: Zhi-Long
Author-X-Name-Last: Chen
Author-Name: Graham Kendall
Author-X-Name-First: Graham
Author-X-Name-Last: Kendall
Title: Analytics and machine learning in scheduling and routing research
Journal: International Journal of Production Research
Pages: 1-3
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2022.2131930
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2131930
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# input file: TPRS_A_1998696_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Bruno E. Demantova
Author-X-Name-First: Bruno E.
Author-X-Name-Last: Demantova
Author-Name: Cassius T. Scarpin
Author-X-Name-First: Cassius T.
Author-X-Name-Last: Scarpin
Author-Name: Leandro C. Coelho
Author-X-Name-First: Leandro C.
Author-X-Name-Last: Coelho
Author-Name: Maryam Darvish
Author-X-Name-First: Maryam
Author-X-Name-Last: Darvish
Title: An improved model and exact algorithm using local branching for the inventory-routing problem with time windows
Abstract: 
 The Inventory-Routing Problem (IRP) deals with the joint optimisation of inventory and the associated routing decisions. The IRP with time windows (IRPTW) considers time windows for the deliveries to the customers. Due to its importance and several real-world applications, in this paper, we develop an intricate solution algorithm for this problem. A combination of tools ranging from established groups of valid inequalities, pre-processing techniques, local search procedures, and a local branching algorithm is utilised to solve the IRPTW efficiently. We compare the performance of our algorithm on a benchmark set of instances and show how our solution algorithm provides promising results against a competing algorithm from the literature. Moreover, the results of our study provide an overview of the performance of several already proposed techniques and their integration in the literature.
Journal: International Journal of Production Research
Pages: 49-64
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1998696
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1998696
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# input file: TPRS_A_1788737_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Hongbo Li
Author-X-Name-First: Hongbo
Author-X-Name-Last: Li
Author-Name: Xianchao Zhang
Author-X-Name-First: Xianchao
Author-X-Name-Last: Zhang
Author-Name: Jinshuai Sun
Author-X-Name-First: Jinshuai
Author-X-Name-Last: Sun
Author-Name: Xuebing Dong
Author-X-Name-First: Xuebing
Author-X-Name-Last: Dong
Title: Dynamic resource levelling in projects under uncertainty
Abstract: 
 In the resource levelling problem (RLP) under uncertainty, existing studies focus on obtaining an open-loop activity list that is not updated during project execution. In project management practice, it is also necessary to address more situations, such as activity overlaps and resource breakdowns. In this paper, we extend the uncertain RLP by proposing a resource levelling problem with multiple uncertainties (RLP-MU) that simultaneously considers uncertainties in activity durations, activity overlaps and resource availabilities. We formulate the RLP-MU as a Markov decision process model. Aimed at levelling resource usage by dynamically scheduling activities at each decision point based on the observed information, we develop a hybrid open–closed-loop approximate dynamic programming algorithm (HOC-ADP). In the HOC-ADP, we devise a closed-loop rollout policy to approximate the cost-to-go function and use the concept of the average project to avoid time-consuming simulation. A greedy-decoding-based estimation of distributed algorithm is also devised to construct an open-loop policy that is embedded in the HOC-ADP to further improve it. We additionally develop a simulation algorithm to evaluate the resource levelling performance of the HOC-ADP. Computational experiments on a benchmark dataset consisting of 540 problem instances are conducted to analyze the performance of the HOC-ADP, and the impact of various factors on resource levelling are investigated. The comparison experimental results indicate that our HOC-ADP outperforms the state-of-the-art meta-heuristics.
Journal: International Journal of Production Research
Pages: 198-218
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2020.1788737
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1788737
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# input file: TPRS_A_2013566_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ruibin Bai
Author-X-Name-First: Ruibin
Author-X-Name-Last: Bai
Author-Name: Xinan Chen
Author-X-Name-First: Xinan
Author-X-Name-Last: Chen
Author-Name: Zhi-Long Chen
Author-X-Name-First: Zhi-Long
Author-X-Name-Last: Chen
Author-Name: Tianxiang Cui
Author-X-Name-First: Tianxiang
Author-X-Name-Last: Cui
Author-Name: Shuhui Gong
Author-X-Name-First: Shuhui
Author-X-Name-Last: Gong
Author-Name: Wentao He
Author-X-Name-First: Wentao
Author-X-Name-Last: He
Author-Name: Xiaoping Jiang
Author-X-Name-First: Xiaoping
Author-X-Name-Last: Jiang
Author-Name: Huan Jin
Author-X-Name-First: Huan
Author-X-Name-Last: Jin
Author-Name: Jiahuan Jin
Author-X-Name-First: Jiahuan
Author-X-Name-Last: Jin
Author-Name: Graham Kendall
Author-X-Name-First: Graham
Author-X-Name-Last: Kendall
Author-Name: Jiawei Li
Author-X-Name-First: Jiawei
Author-X-Name-Last: Li
Author-Name: Zheng Lu
Author-X-Name-First: Zheng
Author-X-Name-Last: Lu
Author-Name: Jianfeng Ren
Author-X-Name-First: Jianfeng
Author-X-Name-Last: Ren
Author-Name: Paul Weng
Author-X-Name-First: Paul
Author-X-Name-Last: Weng
Author-Name: Ning Xue
Author-X-Name-First: Ning
Author-X-Name-Last: Xue
Author-Name: Huayan Zhang
Author-X-Name-First: Huayan
Author-X-Name-Last: Zhang
Title: Analytics and machine learning in vehicle routing research
Abstract: 
 The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms have been proposed. To tackle the complexities, uncertainties and dynamics involved in real-world VRP applications, Machine Learning (ML) methods have been used in combination with analytical approaches to enhance problem formulations and algorithmic performance across different problem solving scenarios. However, the relevant papers are scattered in several traditional research fields with very different, sometimes confusing, terminologies. This paper presents a first, comprehensive review of hybrid methods that combine analytical techniques with ML tools in addressing VRP problems. Specifically, we review the emerging research streams on ML-assisted VRP modelling and ML-assisted VRP optimisation. We conclude that ML can be beneficial in enhancing VRP modelling, and improving the performance of algorithms for both online and offline VRP optimisations. Finally, challenges and future opportunities of VRP research are discussed.
Journal: International Journal of Production Research
Pages: 4-30
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2013566
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2013566
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1957505_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Elad Shufan
Author-X-Name-First: Elad
Author-X-Name-Last: Shufan
Author-Name: Tal Grinshpoun
Author-X-Name-First: Tal
Author-X-Name-Last: Grinshpoun
Author-Name: Ehud Ikar
Author-X-Name-First: Ehud
Author-X-Name-Last: Ikar
Author-Name: Hagai Ilani
Author-X-Name-First: Hagai
Author-X-Name-Last: Ilani
Title: Reentrant flow shop with identical jobs and makespan criterion
Abstract: 
 The article focuses on the problem of a reentrant flow shop with identical jobs and makespan minimisation objective. After presenting an optimal integer programming formulation for the problem, we consider the case of unit processing times. We correct two results published a few decades ago regarding two greedy heuristic algorithms. In some cases, these algorithms lead to an optimal solution, but they are generally not optimal. We point out the advantages of each of the two heuristic algorithms and, by machine learning analysis, discuss features that differentiate between them.
Journal: International Journal of Production Research
Pages: 183-197
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1957505
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1957505
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# input file: TPRS_A_1948133_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Hamza Heni
Author-X-Name-First: Hamza
Author-X-Name-Last: Heni
Author-Name: S. Arona Diop
Author-X-Name-First: S.
Author-X-Name-Last: Arona Diop
Author-Name: Jacques Renaud
Author-X-Name-First: Jacques
Author-X-Name-Last: Renaud
Author-Name: Leandro C. Coelho
Author-X-Name-First: Leandro C.
Author-X-Name-Last: Coelho
Title: Measuring fuel consumption in vehicle routing: new estimation models using supervised learning
Abstract: 
 In this paper, we propose and assess the accuracy of new fuel consumption estimation models for vehicle routing. Based on real-world data consisting of instantaneous fuel consumption, time-varying speeds observations, and high-frequency traffic, we propose effective methods to estimate fuel consumption. By carrying out nonlinear regression analysis using supervised learning methods, namely Neural Networks, Support Vector Machines, Conditional Inference Trees, and Gradient Boosting Machines, we develop new models that provide better prediction accuracy than classical models. We correctly estimate consumption for time-dependent point-to-point routing under realistic conditions. Our methods provide a more precise alternative to classical regression methods used in the literature, as they are developed for a specific situation. Extensive computational experiments under realistic conditions show the effectiveness of the proposed machine learning consumption models, clearly outperforming macroscopic and microscopic consumption models such as the Comprehensive Modal Emissions Model (CMEM) and the Methodology for Estimating air pollutant Emissions from Transport (MEET). Based on sensitivity analyses we show that MEET underestimates real-world consumption by 24.94% and CMEM leads to an overestimation of consumption by 7.57% with optimised parameters. Our best machine learning model (Gradient Boosting Machines) exhibited superior estimation accuracy with a gap of only 1.70%.
Journal: International Journal of Production Research
Pages: 114-130
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1948133
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1948133
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1998695_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Hongtao Hu
Author-X-Name-First: Hongtao
Author-X-Name-Last: Hu
Author-Name: Xurui Yang
Author-X-Name-First: Xurui
Author-X-Name-Last: Yang
Author-Name: Shichang Xiao
Author-X-Name-First: Shichang
Author-X-Name-Last: Xiao
Author-Name: Feiyang Wang
Author-X-Name-First: Feiyang
Author-X-Name-Last: Wang
Title: Anti-conflict AGV path planning in automated container terminals based on multi-agent reinforcement learning
Abstract: 
 AGV conflict prevention path planning is a key factor to improve transportation cost and operation efficiency of the container terminal. This paper studies the anti-conflict path planning problem of Automated Guided Vehicle (AGV) in the horizontal transportation area of the Automated Container Terminals (ACTs). According to the characteristics of magnetic nail guided AGVs, a node network is constructed. Through the analysis of two conflict situations, namely the opposite conflict situation and same point occupation conflict situation, an integer programming model is established to obtain the shortest path. The Multi-Agent Deep Deterministic Policy Gradient (MADDPG) method is proposed to solve the problem, and the Gumbel-Softmax strategy is applied to discretize the scenario created by the node network. A series of numerical experiments are conducted to verify the effectiveness and the efficiency of the model and the algorithm.
Journal: International Journal of Production Research
Pages: 65-80
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1998695
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1998695
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1942284_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xueqin Lu
Author-X-Name-First: Xueqin
Author-X-Name-Last: Lu
Author-Name: Chenxin Wu
Author-X-Name-First: Chenxin
Author-X-Name-Last: Wu
Author-Name: Xuhua Yang
Author-X-Name-First: Xuhua
Author-X-Name-Last: Yang
Author-Name: Minxia Zhang
Author-X-Name-First: Minxia
Author-X-Name-Last: Zhang
Author-Name: Yujun Zheng
Author-X-Name-First: Yujun
Author-X-Name-Last: Zheng
Title: Adapted water wave optimization for integrated bank customer service representative scheduling
Abstract: 
 In modern banks, establishing efficient and quality customer services plays a crucial role to achieve the business success. There are a large number of customers to be served daily; however, required service resources (in particular, customer service representatives) can be rather limited. Therefore, customer service representative scheduling is a challenging problem for bank managers. In the present paper, we focus on a customer service representative scheduling problem considering the stochastic customer arrival time and service duration to minimise the total cost including two parts: (i) the loss concerning the customer waiting and (ii) cost of providing service representatives. We formulate this scheduling problem as an integer programming problem and employ an adapted water wave optimization (WWO) algorithm to solve this problem efficiently. We adapt the propagation and refraction operators of WWO according to the solution space of this problem. The results of the conducted computational experiments demonstrate that the adapted WWO algorithm outperforms the considered state-of-the-art evolutionary algorithms in solving a set of test instances.
Journal: International Journal of Production Research
Pages: 320-335
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1942284
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1942284
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# input file: TPRS_A_2005267_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Mahmoud Efatmaneshnik
Author-X-Name-First: Mahmoud
Author-X-Name-Last: Efatmaneshnik
Author-Name: Shraga Shoval
Author-X-Name-First: Shraga
Author-X-Name-Last: Shoval
Title: Stochastic modelling of process scheduling for reduced rework cost and scrap
Abstract: 
 Uncertainties in manufacturing can have a significant effect on the outcomes of a process and pose difficulties for the management of the processes. Although many models that consider uncertainties in the manufacturing process focus on differences in the processing time and availability of resources, this article reflects on a new aspect of the Stochastic Job Shop Scheduling Problem, evaluating the probability of success (or failure) of a manufacturing job and the effect of a job failure on the other jobs in the process, in particular the rework costs. The article presents a Markovian approach to model a set of manufacturing jobs based on the cost and the probabilistic distribution for success. A failure causes either rework of the failed job, or repetition of some or all previous jobs. The article presents a brief analysis for optimal tolerance assignment using the proposed model and includes a discussion on how this approach can be augmented with machine-learning tools. The article also presents an artificial intelligence–assisted methodology through online scheduling of production processes coupled with online and adaptive tolerance redesign for better management of machining assets.
Journal: International Journal of Production Research
Pages: 219-237
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2005267
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2005267
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1978577_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Liang Tang
Author-X-Name-First: Liang
Author-X-Name-Last: Tang
Author-Name: Huanying Han
Author-X-Name-First: Huanying
Author-X-Name-Last: Han
Author-Name: Zhen Tan
Author-X-Name-First: Zhen
Author-X-Name-Last: Tan
Author-Name: Ke Jing
Author-X-Name-First: Ke
Author-X-Name-Last: Jing
Title: Centralized collaborative production scheduling with evaluation of a practical order-merging strategy
Abstract: 
 We study a collaborative scheduling problem where the dominant manufacturer (DM) outsources several processes to collaborative manufacturers (CMs). We consider multiple types of products defined by different collaborative production networks which may share some common CMs. The DM assigns the orders to the CMs and coordinates the production scheduling among the CMs. We analyse a practical order-merging strategy which combines a subset of same-type orders throughout the production aming at the cost benefit by continuous processing. Such a strategy is easy to implement but may increase the scheduling cost because of increased deviation between the completion time and the required delivery window of some orders. To this end, a heuristic algorithm based on a learning mechanism and ant colony optimisation is proposed for solving the collaborative scheduling problem under the order-merging plans. Simulation case study was carried out to compare the costs under different merging options. We conclude that merging more orders could lead to a better cost in a few cases, and the overall system performance is more sensitive to the merging schemes when the network capacity is tighter due to disruption. Our study provides an effective solution approach and managerial insights for collaborative scheduling problems with practical order-merging strategies.
Journal: International Journal of Production Research
Pages: 282-301
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1978577
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1978577
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# input file: TPRS_A_1842938_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Kuo-Ching Ying
Author-X-Name-First: Kuo-Ching
Author-X-Name-Last: Ying
Author-Name: Pourya Pourhejazy
Author-X-Name-First: Pourya
Author-X-Name-Last: Pourhejazy
Author-Name: Chen-Yang Cheng
Author-X-Name-First: Chen-Yang
Author-X-Name-Last: Cheng
Author-Name: Ren-Siou Syu
Author-X-Name-First: Ren-Siou
Author-X-Name-Last: Syu
Title: Supply chain-oriented permutation flowshop scheduling considering flexible assembly and setup times
Abstract: 
 Given the significant proportion of the outsourced parts, components, and the complex assembly structure of the automobiles, agriculture machinery and heavy industry equipment, distributed production and flexible assembly are much-needed production scheduling settings to optimise their global supply chains. This research extends the distributed assembly permutation flowshop scheduling problem to account for flexible assembly and sequence-independent setup times (DPFSP_FAST) in a supply chain-like setting. For this purpose, an original mixed-integer linear programming (MILP) formulation to the DPFSP_FAST problem is first investigated. Considering makespan as the optimisation criterion, constructive heuristic and customised metaheuristic algorithms are then proposed to solve this emerging scheduling extension. Through extensive computational experiments, it is shown that the proposed algorithms outperform the existing best-performing algorithms to solve the DPFSP_FAST problem, yielding the best-found solutions in nearly all of the benchmark instances. Narrowing the gap between theory and practice, this study helps integrate the production planning scheduling across the supply chain.
Journal: International Journal of Production Research
Pages: 258-281
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2020.1842938
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1842938
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1901153_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Md Shajalal
Author-X-Name-First: Md
Author-X-Name-Last: Shajalal
Author-Name: Petr Hajek
Author-X-Name-First: Petr
Author-X-Name-Last: Hajek
Author-Name: Mohammad Zoynul Abedin
Author-X-Name-First: Mohammad Zoynul
Author-X-Name-Last: Abedin
Title: Product backorder prediction using deep neural network on imbalanced data
Abstract: 
 Taking backorders on products is a common scenario in inventory and supply chain management systems. The ability to predict the likelihood of backorders can surely minimise a company's losses. Because the number of backorders is much lower than the number of orders that ship on time, applying a predictive model for this domain is a challenging task. This paper proposes a model that uses a deep neural network to predict backorders; it handles the data imbalance between backorders and filled orders with efficient techniques. To make the dataset balanced, we employ different techniques that include minority class weight boosting, randomised oversampling, SMOTE oversampling, and a combination of oversampling and undersampling. The balanced training data are used in our proposed, fully connected deep neural networks model to train the predictive model. The predictive model learns the likelihood of product backorders by using the training samples. We conduct experiments on a large benchmark dataset to test the performance of our proposed deep neural network–based model. The experimental results achieve a new state-of-the-art performance and outperform some prominent classification models in terms of standard evaluation metrics and expected profit measure.
Journal: International Journal of Production Research
Pages: 302-319
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1901153
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1901153
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2113928_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Erfaneh Nikzad
Author-X-Name-First: Erfaneh
Author-X-Name-Last: Nikzad
Author-Name: Mahdi Bashiri
Author-X-Name-First: Mahdi
Author-X-Name-Last: Bashiri
Title: A two-stage stochastic programming model for collaborative asset protection routing problem enhanced with machine learning: a learning-based matheuristic algorithm
Abstract: 
 In this paper, a two-stage stochastic mathematical model is developed for an asset protection routing problem under a wildfire. The main aim of this study is to reduce the negative impact of a wildfire. Some parameters, such as travel and service times, obtaining profit by protecting an asset, and upper bounds of time windows, are considered as stochastic parameters. Generating proper scenarios for uncertain parameters has a large impact on the accuracy of the obtained solutions. Therefore, artificial neural networks are employed to extract possible scenarios according to previous actual wildfire events. The problem cannot be solved by exact solvers for large instances, so two matheuristic algorithms are proposed in this study to solve the problem in a reasonable time. In the first algorithm, a set of feasible routes is generated based on a heuristic approach, then a route-based mathematical model is used to obtain the final solution. Also, another matheuristic algorithm based on adaptive large neighbourhood search (ALNS) is proposed. In this algorithm, routing decisions are determined using the ALNS algorithm while other decisions are achieved by solving an intermediate mathematical model. The numerical analysis confirms the efficiency of both proposed algorithms; however, the first algorithm performs more efficiently.
Journal: International Journal of Production Research
Pages: 81-113
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2022.2113928
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2113928
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# input file: TPRS_A_1942283_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Namyong Kim
Author-X-Name-First: Namyong
Author-X-Name-Last: Kim
Author-Name: Stephane Barde
Author-X-Name-First: Stephane
Author-X-Name-Last: Barde
Author-Name: Kiwook Bae
Author-X-Name-First: Kiwook
Author-X-Name-Last: Bae
Author-Name: Hayong Shin
Author-X-Name-First: Hayong
Author-X-Name-Last: Shin
Title: Learning per-machine linear dispatching rule for heterogeneous multi-machines control
Abstract: 
 This paper proposes a per-machine linear dispatching rule learning approach to improve the scheduling of re-entrant flow shop such as semiconductor fab. Finding an optimal schedule of a complex manufacturing system is intractable; hence, a dispatching rule as a heuristic approach is widely used in actual practice. Also, to develop a good dispatching rule, an automated methodology for developing heuristics, also known as a hyper-heuristic, has been studied extensively. However, most of the literature has focused on finding a single-sophisticated dispatching rule, in which every machine uses the same rule. Such an approach often shows suboptimal performance when the optimal dispatching rule is different on each machine. To solve this problem, we introduce a simple and effective per-machine dispatching rule learning approach, in which each machine has one linear dispatching rule that is optimised by the Gradient-based Evolutionary Strategy (GES). This method is sample-efficient and can be applied to non-differentiable objective functions such as average Cycle Time. The proposed approach was mainly compared to two popular methods based on Genetic Programming (GP) and the Genetic Algorithm (GA) on a four-station and eight-machine re-entrant flow shop. Numerical results show that the proposed approach outperforms widely used methods.
Journal: International Journal of Production Research
Pages: 162-182
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1942283
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1942283
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# input file: TPRS_A_1943762_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Jens Heger
Author-X-Name-First: Jens
Author-X-Name-Last: Heger
Author-Name: Thomas Voss
Author-X-Name-First: Thomas
Author-X-Name-Last: Voss
Title: Dynamically adjusting the k-values of the ATCS rule in a flexible flow shop scenario with reinforcement learning
Abstract: 
 Given the fact that finding the optimal sequence in a flexible flow shop is usually an NP-hard problem, priority-based sequencing rules are applied in many real-world scenarios. In this contribution, an innovative reinforcement learning approach is used as a hyper-heuristic to dynamically adjust the k-values of the ATCS sequencing rule in a complex manufacturing scenario. For different product mixes as well as different utilisation levels, the reinforcement learning approach is trained and compared to the k-values found with an extensive simulation study. This contribution presents a human comprehensible hyper-heuristic, which is able to adjust the k-values to internal and external stimuli and can reduce the mean tardiness up to 5%.
Journal: International Journal of Production Research
Pages: 147-161
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1943762
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1943762
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# input file: TPRS_A_1820095_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Guo-Qiang Fan
Author-X-Name-First: Guo-Qiang
Author-X-Name-Last: Fan
Author-Name: Jun-Qiang Wang
Author-X-Name-First: Jun-Qiang
Author-X-Name-Last: Wang
Author-Name: Zhixin Liu
Author-X-Name-First: Zhixin
Author-X-Name-Last: Liu
Title: Two-agent scheduling on mixed batch machines to minimise the total weighted makespan
Abstract: 
 This paper studies a two-agent scheduling problem on mixed batch machines in parallel. A mixed batch machine can process several jobs simultaneously as a batch, as long as the number of jobs in the batch does not exceed the machine capacity. The processing time of a mixed batch is the weighted sum of the maximum processing time and the total processing time of jobs in the batch. The objective is to minimise the weighted sum of two agents' makespans. We present four approximation algorithms based on two strategies: the machine-centric strategy and the agent-centric strategy. For each strategy, a full batch longest processing time (FBLPT) rule and a longest processing time greedy (LPTG) rule are used. We conduct theoretical analyses based on the worst-case performance ratio to provide the provable guarantees on the performances of the algorithms, and simulation analyses based on randomly generated instances to evaluate the average performances of the algorithms. Furthermore, we verify the consistency between the theoretical and simulation results. The algorithms using agent-centric strategy perform better than ones using machine-centric strategy. Finally, we provide managerial insights for the problem by analysing the technological parameters of batches, importance of agents, and demand seasonality.
Journal: International Journal of Production Research
Pages: 238-257
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2020.1820095
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1820095
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# input file: TPRS_A_2002962_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Dian Huang
Author-X-Name-First: Dian
Author-X-Name-Last: Huang
Author-Name: Zhaofang Mao
Author-X-Name-First: Zhaofang
Author-X-Name-Last: Mao
Author-Name: Kan Fang
Author-X-Name-First: Kan
Author-X-Name-Last: Fang
Author-Name: Lin Chen
Author-X-Name-First: Lin
Author-X-Name-Last: Chen
Title: Solving the shortest path interdiction problem via reinforcement learning
Abstract: 
 This paper addresses the shortest path interdiction problem, in which the leader aims to maximise the length of the shortest path that the follower can traverse subject to a limited interdiction budget. To solve this problem, we propose a reinforcement learning framework and use the pointer network to handle the situation of variable output sizes. To evaluate the performance of our proposed reinforcement learning model, we conduct extensive computational experiments on a set of instances that are generated from two different network topologies, i.e. the grid networks and the random graphs. To train the pointer network, we consider three different baselines, i.e. the exponential, critical, and rollout baselines, among which the rollout baseline policy achieves the best computational results, and thus is used as the default baseline during our computational experiments. Moreover, when the size of instances increases, we find that solving the equivalent single-level mixed integer program of the problem could be quite time-consuming, while our proposed reinforcement learning approach can still obtain solutions with good performance effectively for both the grid networks and the random graphs.
Journal: International Journal of Production Research
Pages: 31-48
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2002962
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002962
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# input file: TPRS_A_1766716_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Bing Chen
Author-X-Name-First: Bing
Author-X-Name-Last: Chen
Author-Name: Ruibin Bai
Author-X-Name-First: Ruibin
Author-X-Name-Last: Bai
Author-Name: Jiawei Li
Author-X-Name-First: Jiawei
Author-X-Name-Last: Li
Author-Name: Yueni Liu
Author-X-Name-First: Yueni
Author-X-Name-Last: Liu
Author-Name: Ning Xue
Author-X-Name-First: Ning
Author-X-Name-Last: Xue
Author-Name: Jianfeng Ren
Author-X-Name-First: Jianfeng
Author-X-Name-Last: Ren
Title: A multiobjective single bus corridor scheduling using machine learning-based predictive models
Abstract: 
 Many real-life optimisation problems, including those in production and logistics, have uncertainties that pose considerable challenges for practitioners. In spite of considerable efforts, the current methods are still not satisfactory. This is primarily caused by a lack of effective methods to deal with various uncertainties. Existing literature comes from two isolated research communities, namely the operations research community and the machine learning community. In the operations research community, uncertainties are often modelled and solved through techniques like stochastic programming or robust optimisation, which are often criticised for their over conservativeness. In the machine learning community, the problem is formulated as a dynamic control problem and solved through techniques like supervised learning and/or reinforcement learning, which could suffer from being myopic and unstable. In this paper, we aim to fill this research gap and develop a novel framework that takes advantages of both short-term accuracy from mathematical models and high-quality future forecasts from machine learning modules. We demonstrate the practicality and feasibility of our approach for a real-life bus scheduling problem and two controlled bus scheduling instances that are generated artificially. To our knowledge, the proposed framework represents the first multi-objective bus-headway-optimisation method for non-timetabled bus schedule with major practical constraints being considered. The advantages of our proposed methods are also discussed, along with factors that need to be carefully considered for practical applications.
Journal: International Journal of Production Research
Pages: 131-145
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2020.1766716
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1766716
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# input file: TPRS_A_1916118_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Ming Chen
Author-X-Name-First: Ming
Author-X-Name-Last: Chen
Author-Name: Xuan Huang
Author-X-Name-First: Xuan
Author-X-Name-Last: Huang
Author-Name: Hongyu Chen
Author-X-Name-First: Hongyu
Author-X-Name-Last: Chen
Author-Name: Xuemei Su
Author-X-Name-First: Xuemei
Author-X-Name-Last: Su
Author-Name: Jasmine Yur-Austin
Author-X-Name-First: Jasmine
Author-X-Name-Last: Yur-Austin
Title: Data driven course scheduling to ensure timely graduation
Abstract: 
 With progressively decreasing state funding in the last two decades, timely graduation has become an imperative yet challenging problem for many public universities. Our research empirically studies students' enrolment and performance data during an 8-year period in a large college at the California State University Long Beach. Through data analytics, we identify four fundamental issues that lead to delayed graduation. We propose innovative solutions that directly tackle each of the four identified issues while systematically matching capacity and demand. Specifically, we propose major-specific degree roadmaps tailored to increase the chance students can successfully complete all required courses within the timely graduation window. Given major migration behaviours, we design robust roadmaps that proactively prepare students for possible major change later without delaying graduation. The well-crafted degree roadmap provides students with a clear path to degree attainment, as well as guidance on the timing of course enrolments. Further, to maximise students' access to courses as well as capacity utilisation, we develop an optimisation model to determine the class schedule in which all students are guaranteed a seat within their preferred time window in all required classes. The proposed approach is widely applicable to many institutions facing the timely graduation challenge.
Journal: International Journal of Production Research
Pages: 336-361
Issue: 1
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.1916118
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1916118
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# input file: TPRS_A_2011982_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Damien Lovato
Author-X-Name-First: Damien
Author-X-Name-Last: Lovato
Author-Name: Romain Guillaume
Author-X-Name-First: Romain
Author-X-Name-Last: Guillaume
Author-Name: Caroline Thierry
Author-X-Name-First: Caroline
Author-X-Name-Last: Thierry
Author-Name: Olga Battaia
Author-X-Name-First: Olga
Author-X-Name-Last: Battaia
Title: Managing disruptions in aircraft assembly lines with staircase criteria
Abstract: 
 We study a rescheduling problem in paced aircraft assembly lines with specific resource and precedence constraints. We develop an efficient model based on constraint programming to provide rapidly rescheduling solutions to managers. We propose original optimisation criteria and show that their use outperforms the classic criteria in terms of solution time and quality. We validate our approach through experiments run on industrial problem instances of large scale and derive useful managerial insights from this experimental study.
Journal: International Journal of Production Research
Pages: 632-648
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2011982
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2011982
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# input file: TPRS_A_2010143_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Selmen Boubaker
Author-X-Name-First: Selmen
Author-X-Name-Last: Boubaker
Author-Name: Zied Jemai
Author-X-Name-First: Zied
Author-X-Name-Last: Jemai
Author-Name: Evren Sahin
Author-X-Name-First: Evren
Author-X-Name-Last: Sahin
Author-Name: Yves Dallery
Author-X-Name-First: Yves
Author-X-Name-Last: Dallery
Title: A supply chain flow model to assess agility in supply chains
Abstract: 
 This paper addresses the relevant topic of supply chain agility. Our work proposes a quantitative approach to evaluate and improve agility, in the context of a serial end-to-end supply chain. We define a metric to assess the agility of a supply chain. Then, we develop a supply chain flow model that integrates various parameters related to physical and information/decision flows such as production and logistics/transportation capacities and lead times, frozen planning horizons, target stocks … This flow model is then used to simulate the supply chain information and physical flows in the nominal mode and when a situation needing agility happens. The model enables to calculate the agility metric when no action is done as well as in situations where the use of some agility levers is considered. A numerical study is presented allowing to illustrate the model developed in this work. We also discuss some interesting insights we have obtained from real-life applications of our model.
Journal: International Journal of Production Research
Pages: 485-502
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2010143
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2010143
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# input file: TPRS_A_2012614_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Li Hu
Author-X-Name-First: Li
Author-X-Name-Last: Hu
Author-Name: Shaofu Du
Author-X-Name-First: Shaofu
Author-X-Name-Last: Du
Author-Name: Lei Wang
Author-X-Name-First: Lei
Author-X-Name-Last: Wang
Author-Name: Wenzhi Tang
Author-X-Name-First: Wenzhi
Author-X-Name-Last: Tang
Title: Differentiated premium membership mechanism in platform competition
Abstract: 
 The rapid rise of premium memberships on e-commerce platforms has made it a core strategy for platform competition, attracting widespread attention from the industry and academia. This paper studies two kinds of differentiated membership mechanisms, i.e. the General Pattern (GP) available to all consumers and the Top-tier Pattern (TP) offered only to high-value consumers. We have a detailed description of the consumer's consumption behaviour in line with the real platform competition scenario. We first conducted a separate analysis of the two membership mechanisms and found that the actual implementation effect of TP and GP membership mechanisms are equivalent when there is no membership competition. Then we focussed on the scenario of differentiated member competition. We discuss the interaction between the two membership mechanisms and do a sensitivity analysis of the optimal decisions. The impact of the membership mechanism competition on the member group segmentation and consumption transfer is depicted well and analysed. At last, we use numerical examples to show the relationship between platform profits and some important exogenous variables under differentiated membership competition, and we also find that the differentiated membership mechanisms competition can let the two platforms achieve a win-win result.
Journal: International Journal of Production Research
Pages: 649-667
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2012614
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2012614
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# input file: TPRS_A_2010144_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Zhongyang Li
Author-X-Name-First: Zhongyang
Author-X-Name-Last: Li
Author-Name: Zhaohui Deng
Author-X-Name-First: Zhaohui
Author-X-Name-Last: Deng
Author-Name: Zhiguang Ge
Author-X-Name-First: Zhiguang
Author-X-Name-Last: Ge
Author-Name: Lishu Lv
Author-X-Name-First: Lishu
Author-X-Name-Last: Lv
Author-Name: Jimin Ge
Author-X-Name-First: Jimin
Author-X-Name-Last: Ge
Title: A hybrid approach of case-based reasoning and process reasoning to typical parts grinding process intelligent decision
Abstract: 
 After grinding, the machine tool spindle with high surface integrity has a significant impact on its subsequent service life. Therefore, it is necessary to create a reasonable process plan for the grinding process of the machine tool spindle. A hybrid method based on case-based reasoning (CBR) and process reasoning (PR) was proposed in this paper. The subjective and objective weights of feature attributes are determined in the CBR by the AHP method and the CRITIC method, respectively, and the similarities between the latest case and the retrieved case are calculated on the basis of the nearest neighbour algorithm. The most suitable process solution can be selected from the case database by means of CBR. PR is applied to solve the problem that the case cannot be retrieved through CBR or is unsatisfactory. In the case of the grinding machine spindle, the applicability of this technology was demonstrated. Consequently, the results revealed that the surface consistency of the spindle after grinding was substantially increased. A decision-making system based on the proposed approach was developed by using Qt 4.8.7 and SQLite 3. The results demonstrate the viability and efficacy of the hybrid CBR-PR method to rapidly generate process planning for specific parts.
Journal: International Journal of Production Research
Pages: 503-519
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2010144
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2010144
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# input file: TPRS_A_2008041_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xu Xin
Author-X-Name-First: Xu
Author-X-Name-Last: Xin
Author-Name: Qiangqiang Jiang
Author-X-Name-First: Qiangqiang
Author-X-Name-Last: Jiang
Author-Name: Cui Li
Author-X-Name-First: Cui
Author-X-Name-Last: Li
Author-Name: Sihang Li
Author-X-Name-First: Sihang
Author-X-Name-Last: Li
Author-Name: Kang Chen
Author-X-Name-First: Kang
Author-X-Name-Last: Chen
Title: Permutation flow shop energy-efficient scheduling with a position-based learning effect
Abstract: 
 Severe environmental problems have made green scheduling an emerging research hotspot. In this paper, a permutation flow shop energy-efficient scheduling problem that considers multiple criteria is investigated. The aim is to find the optimal job processing sequence and conveyor speed that minimise both the makespan and total energy consumption. In addition to two types of common criteria, namely, machine-based criterion (i.e. sequence-dependent setup time) and energy-based criteria (including both the transportation time control strategy and machine shutdown strategy), a human-based criterion (i.e. a position-based learning effect) is introduced. A bi-objective programming model is developed, and a multi-objective iterated greedy (MOIG) is designed to reach the Pareto front of the model. Considering that there are two types of decisions in the model (i.e. job sequence and conveyor speed), two algorithm alternatives are designed based on the job sequence and conveyor speed, respectively. Meanwhile, an acceptance criterion with advantages in terms of the convergence speed and solution diversity is proposed. Existing algorithms, including NSGA-II and MOEA/D, are introduced to evaluate the performance of the MOIG. The results emphasise the efficiency of the MOIG. Overall, the model and MOIG effectively improve the green efficiency of enterprises and can reasonably control operating costs.
Journal: International Journal of Production Research
Pages: 382-409
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2008041
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2008041
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# input file: TPRS_A_2009141_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Haim Shore
Author-X-Name-First: Haim
Author-X-Name-Last: Shore
Title: Estimating operating room utilisation rate for differently distributed surgery times
Abstract: 
 A method is developed to determine the required sample size to estimate utilisation rate (UR) of a facility, where blocks of work processes/jobs with i.i.d execution times are consecutively executed, and different blocks possibly pursuing different distributions. It is assumed that within-block processes may be repetitive (constant work-content; execution time normally distributed), semi-repetitive (work-content somewhat varies between cycles) or memoryless (no characteristic work-content; exponentially distributed). Surgeries are known to comprise all three types of work processes. In this article, we use operating theatres as prototype facility to estimate UR, assuming that surgeries are allocated in blocks, in conformance with the specified scenario. A recently developed model for surgery duration, bridging the gap between duration models for repetitive and memoryless processes, is used to estimate UR. A database of ten thousand surgeries serve to compare sample sizes, calculated under normality (the traditional method) or lognormality, with the correct model-based values. The latter deviate appreciably from the former, corroborating the need for the new methodology.Abbreviations: OF: objective function; OR: operating room; SD: Surgery duration; SDD: Surgery duration distribution; UR: utilisation rate
Journal: International Journal of Production Research
Pages: 447-461
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2009141
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2009141
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2011464_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Junhao Chen
Author-X-Name-First: Junhao
Author-X-Name-Last: Chen
Author-Name: Xiaoliang Jia
Author-X-Name-First: Xiaoliang
Author-X-Name-Last: Jia
Author-Name: Qixuan He
Author-X-Name-First: Qixuan
Author-X-Name-Last: He
Title: A novel bi-level multi-objective genetic algorithm for integrated assembly line balancing and part feeding problem
Abstract: 
 The manufacturing industry has been pursuing an efficient and economical assembly system. By considering assembly line balancing (ALB) and part feeding (PF) as an integrated problem and programming them simultaneously opens additional opportunities to improve the performance of the entire assembly system. However, the integrated ALB and PF problem is a non-deterministic polynomial (NP) hard problem. This implies that exact solutions cannot be obtained in a reasonable computation time and its near-optimal solutions can only be realised by meta-heuristics. In this study, we propose a novel bi-level multi-objective genetic algorithm (NBMGA) to solve the integrated ALB and PF problem. First, a bi-level mathematical model is established to simultaneously minimise the number of stations and workload smoothness of ALB in the upper level as well as the number of supermarkets of PF in the lower level. Second, the NBMGA with two modified strategies, including extending fitness evaluation and adaptive termination condition, is designed for problem solving. Finally, a series of computational experiments are conducted to demonstrate the efficacy of the proposed algorithm. The computational results indicate that the proposed algorithm outperforms the bi-level nondominated sorting genetic algorithm (NSGA) II in terms of the approximation to the true frontier without sacrificing computational efficiency.
Journal: International Journal of Production Research
Pages: 580-603
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2011464
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2011464
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# input file: TPRS_A_2009138_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Shuai Liu
Author-X-Name-First: Shuai
Author-X-Name-Last: Liu
Author-Name: Guowei Hua
Author-X-Name-First: Guowei
Author-X-Name-Last: Hua
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Jing-Xin Dong
Author-X-Name-First: Jing-Xin
Author-X-Name-Last: Dong
Title: Pricing strategies for logistics robot sharing platforms
Abstract: 
 Sharing platforms play a key role in the development of the sharing economy. This paper considers a logistics robot sharing platform comprising logistics robot providers and customers that need to rent robots. We develop an analytical model to investigate pricing strategies of a sharing platform, incorporating service response speed and additional services. Afterward, we examine the impact and value of the logistics robot sharing platform. We interestingly find that a high service response speed does not necessarily bring benefits to the platform. In addition, when customers are sensitive to the additional services, despite the increased cost of providing additional services, the platform can still profit from them. Finally, we generate additional insights by exploring two extended models, namely (i) the model with endogenous additional services, and (ii) the case considering the service response speed.
Journal: International Journal of Production Research
Pages: 410-426
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2009138
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2009138
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# input file: TPRS_A_2011465_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Jingru Wang
Author-X-Name-First: Jingru
Author-X-Name-Last: Wang
Author-Name: Kuanyun Zhu
Author-X-Name-First: Kuanyun
Author-X-Name-Last: Zhu
Author-Name: Jiawu Peng
Author-X-Name-First: Jiawu
Author-X-Name-Last: Peng
Author-Name: Wenyan Zhuo
Author-X-Name-First: Wenyan
Author-X-Name-Last: Zhuo
Title: Strategic demand information sharing under partial cross ownership
Abstract: 
 We consider a two-echelon supply chain with partial cross ownership (PCO) comprising a supplier and a retailer. The retailer is endowed with superior information about uncertain market potential. The supplier must produce the product before the market potential is realized. We explore the retailer’s strategy to share his private demand information with the supplier via cheap talk. We demonstrate that when the proportion of partial cross holding shares is moderate, the retailer can disclose private demand information truthfully. Without PCO, this informative equilibrium cannot be achieved regardless of the acquired signal. With PCO, the retailer wants to obtain a sufficient production quantity if the realized demand is high and fears the cost of unsold products if the realized demand is low. These two countervailing incentives can cause the retailer to share his information truthfully. We find that this truthful information sharing benefits both the retailer and the supplier. In addition, we discuss the case of endogenous wholesale price and indicate the conditions in which truthful information sharing can be achieved. Moreover, we find that when the market potential follows a general continuous distribution, the perfect informative equilibrium does not exist.
Journal: International Journal of Production Research
Pages: 604-631
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2011465
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2011465
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# input file: TPRS_A_2013559_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Duo Wang
Author-X-Name-First: Duo
Author-X-Name-Last: Wang
Author-Name: Kai Yang
Author-X-Name-First: Kai
Author-X-Name-Last: Yang
Author-Name: Lixing Yang
Author-X-Name-First: Lixing
Author-X-Name-Last: Yang
Title: Risk-averse two-stage distributionally robust optimisation for logistics planning in disaster relief management
Abstract: 
 Relief logistics is vital to disaster relief management. Herein, a risk-averse two-stage distributionally robust programming model is proposed to provide decision support for planning disaster relief logistics. It is distinct from the conventional disaster relief logistics planning problem in that (i) the facility location-inventory model and the multi-commodity network flow formulation are integrated; (ii) the probability distribution information of the supply, demand, and road link capacity is partially known, and (iii) the two-stage distributionally robust optimisation (DRO) method based on the worst-case mean-conditional value-at-risk criterion is developed. For tractability, we reformulate the proposed DRO model as equivalent mixed-integer linear programs for box and polyhedral ambiguity sets, which can be directly solved to optimality using the CPLEX software. To evaluate the validity of the proposed DRO model, we conduct numerical experiments based on a real-world case study addressing hurricane threats in the Gulf of Mexico region of the United States. Furthermore, we compare the performance of the proposed DRO model with that of the conventional two-stage stochastic programming model. Finally, we report the managerial implications and insights of using the risk-averse two-stage DRO approach for disaster relief management.
Journal: International Journal of Production Research
Pages: 668-691
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2013559
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2013559
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# input file: TPRS_A_2007310_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Zhongyuan Liang
Author-X-Name-First: Zhongyuan
Author-X-Name-Last: Liang
Author-Name: Mei Liu
Author-X-Name-First: Mei
Author-X-Name-Last: Liu
Author-Name: Peisi Zhong
Author-X-Name-First: Peisi
Author-X-Name-Last: Zhong
Author-Name: Chao Zhang
Author-X-Name-First: Chao
Author-X-Name-Last: Zhang
Title: Application research of a new neighbourhood structure with adaptive genetic algorithm for job shop scheduling problem
Abstract: 
 The job shop scheduling problem (JSSP) is to find the optimal jobs sequence to optimise one or more performance indicators and makespan is the most common optimisation target. In solving NP-hard problems such as JSSPs by genetic algorithm (GA), trapping in local extremum, low search efficiency and instability are often encountered, especially unable to find the optimisation direction. To restrain this condition, a new neighbourhood structure with adaptive GA was put forward. The crossover probability (Pc) and mutation probability (Pm) can be adjusted in nonlinear and adaptive based on the dispersion of the fitness of population in the evolution. The idle time before critical operations can be made full use of through the multi-operations combination and adjustment. To research the performance of the proposed method in solving JSSPs, a detailed application scheme was given out for the process of it. In the solving scheme, the chromosome active decoding algorithm with the objective function of maximum makespan was proposed. From the results of testing of 28 JSSP benchmark instances in 3 adaptive strategies and 3 neighbourhood strategies, the new neighbourhood structure with adaptive GA has been significant improvement in solution accuracy and convergence efficiency.
Journal: International Journal of Production Research
Pages: 362-381
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2007310
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2007310
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# input file: TPRS_A_2010825_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Mejdal A. Alqahtani
Author-X-Name-First: Mejdal A.
Author-X-Name-Last: Alqahtani
Author-Name: Myong K. Jeong
Author-X-Name-First: Myong K.
Author-X-Name-Last: Jeong
Author-Name: Elsayed A. Elsayed
Author-X-Name-First: Elsayed A.
Author-X-Name-Last: Elsayed
Title: Generalised spatially weighted autocorrelation approach for monitoring and diagnosing faults in 3D topographic surfaces
Abstract: 
 Digital transformation driven by artificial intelligence (AI) allows Industry 4.0 and the internet of things (IIoT) to make significant advancements in automating, controlling, and improving the quality of numerous manufacturing processes. Three-dimensional (3D) surface topography of manufactured products holds important information about the quality of manufacturing processes. Surface topography consists of unique properties, which makes the current monitoring approaches ineffective in identifying local and spatial surface faults. In this paper, we develop a generalised spatially weighted autocorrelation approach based on AI for monitoring changes in products based on their 3D topographic surfaces. We propose two effective algorithms to identify and assign spatial weights to the topographic regions with suspicious characteristics. The normal surface hard thresholding algorithm initially enhances the representation of surface characteristics through binarization, followed by the normal surface connected-component labelling algorithm, which utilises the obtained binary results to identify and assign spatial weights to the suspicious regions. We then introduce a generalised spatially weighted Moran index, which exploits the assigned weights to locally characterise and monitor changes in the spatial autocorrelation structure of identified regions. After an anomaly surface is detected, we extract different fault diagnostic information. The proposed approach proves its robustness and efficiency in characterising, monitoring, and diagnosing different patterns of faults in 3D topographic surfaces.
Journal: International Journal of Production Research
Pages: 541-558
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2010825
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2010825
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# input file: TPRS_A_2009586_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Z.A.M.S. Juman
Author-X-Name-First: Z.A.M.S.
Author-X-Name-Last: Juman
Author-Name: Rym M’Hallah
Author-X-Name-First: Rym
Author-X-Name-Last: M’Hallah
Author-Name: Ruchira Lokuhetti
Author-X-Name-First: Ruchira
Author-X-Name-Last: Lokuhetti
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Title: A multi-vendor multi-buyer integrated production-inventory model with synchronised unequal-sized batch delivery
Abstract: 
 Integrating vendors’ and buyers’ production-inventory systems can significantly reduce the total costs incurred by both parties. In this paper, we study the synchronised multi-vendor multiple-buyer integrated production-inventory system with a production flow where the lot sizes follow a geometric sequence. We model this new problem with the objective to minimise the total cost incurred by the vendors and the buyers and determine the optimal production shipment policy. The computational experiments realised on real case study show the efficiency of the developed model for optimising production shipment and synchronisation of vendor-buyer inventories.
Journal: International Journal of Production Research
Pages: 462-484
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2009586
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2009586
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# input file: TPRS_A_2010824_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Xiaoning Cao
Author-X-Name-First: Xiaoning
Author-X-Name-Last: Cao
Author-Name: Hongguang Bo
Author-X-Name-First: Hongguang
Author-X-Name-Last: Bo
Author-Name: Yongkui Liu
Author-X-Name-First: Yongkui
Author-X-Name-Last: Liu
Author-Name: Xiaobing Liu
Author-X-Name-First: Xiaobing
Author-X-Name-Last: Liu
Title: Effects of different resource-sharing strategies in cloud manufacturing: a Stackelberg game-based approach
Abstract: 
 Cloud manufacturing (CMfg) aims to realise the sharing of manufacturing resources amongst different stakeholders. Resource-sharing strategies of suppliers are essential in achieving this aim. However, current studies on this topic rarely focus on the sharing of management rights over manufacturing resources. To fill this research gap, this study investigates three resource-sharing strategies: independently, as an alliance and by cooperating with a cloud platform operator. This study explores the effects of these different strategies on meeting client requirements in CMfg. The interactions between the operator and suppliers are modelled as a two-stage Stackelberg game that contains a simultaneous subgame. The equilibrium results indicate that players achieve a lower system profit when suppliers share as an alliance rather than independently, which is why the cloud platform operator strongly opposes it. The extended analysis indicates that considering multiple suppliers complicates the allocation of tasks and profits. Low-cost suppliers have significant advantages in terms of tasks and profits when considering different marginal costs. These findings provide insights for suppliers to select appropriate resource-sharing strategies in CMfg.
Journal: International Journal of Production Research
Pages: 520-540
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2010824
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2010824
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# input file: TPRS_A_2010828_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Félicien Barhebwa-Mushamuka
Author-X-Name-First: Félicien
Author-X-Name-Last: Barhebwa-Mushamuka
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Claude Yugma
Author-X-Name-First: Claude
Author-X-Name-Last: Yugma
Title: A global scheduling approach for cycle time control in complex manufacturing systems
Abstract: 
 This paper proposes a novel global scheduling approach for cycle time control strategy in large complex manufacturing systems with multiple workcentres, such as semiconductor manufacturing systems. The interaction between workcentres is taken into account by using global information such as release quantities, the Work-In-Process (WIP), cycle time targets and machine capacities. Local scheduling decisions in workcentres are steered by production targets, i.e. quantities of products to complete in each operation and each period on a scheduling horizon. These global production targets are determined by a mathematical model (global scheduling model), which optimises the satisfaction of cycle time targets. One of the major innovations of the proposed model is that it relies on the temporal trace of the WIP. The mathematical model is coupled with a generic multi-method simulation model for evaluation purpose. Computational experiments conducted on industrial data show that our global scheduling approach efficiently controls the cycle times of products.
Journal: International Journal of Production Research
Pages: 559-579
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2010828
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2010828
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# input file: TPRS_A_2009140_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20220907T060133 git hash: 85d61bd949
Author-Name: Yesim Koca
Author-X-Name-First: Yesim
Author-X-Name-Last: Koca
Author-Name: Tugce Martagan
Author-X-Name-First: Tugce
Author-X-Name-Last: Martagan
Author-Name: Ivo Adan
Author-X-Name-First: Ivo
Author-X-Name-Last: Adan
Title: Optimising the fermentation throughput in biomanufacturing with bleed–feed
Abstract: 
 Bleed–feed is a novel technology that allows biomanufacturers to skip bioreactor setups. However, the time at which bleed–feed is performed is important for its successful implementation. In addition, bleed–feed operations involve unique trade-offs that affect the system's throughput. For example, the biomass replenishment amount during bleed–feed affects the expected yield of the system. In this study, we formalise these operational trade-offs and formulate a stochastic optimisation model using renewal reward theory. Our analytical model captures both the biological dynamics and operational trade-offs of bleed–feed decisions to maximise throughput. We present an industry case study to demonstrate the use of our model. Through several practically relevant scenarios, we assess the potential impact of implementing bleed–feed on current practice and develop insights for practitioners. Although our work is primarily motivated by the biomanufacturing industry, our analytical model and insights are applicable to other industries that involve fermentation. Our results show that bleed–feed brings the most benefit for fast-growing cells or high-risk cultures. Although counter-intuitive, our numerical analysis shows that it is optimal not to adopt bleed–feed when biomass accumulation is too slow.
Journal: International Journal of Production Research
Pages: 427-446
Issue: 2
Volume: 61
Year: 2023
Month: 01
X-DOI: 10.1080/00207543.2021.2009140
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2009140
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# input file: TPRS_A_2015081_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mohammed-Amine Abdous
Author-X-Name-First: Mohammed-Amine
Author-X-Name-Last: Abdous
Author-Name: Xavier Delorme
Author-X-Name-First: Xavier
Author-X-Name-Last: Delorme
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Sandrine Berger-Douce
Author-X-Name-First: Sandrine
Author-X-Name-Last: Berger-Douce
Title: Assembly line balancing problem with ergonomics: a new fatigue and recovery model
Abstract: 
 Assembly lines are production lines used to manufacture products, ranging from mass-production products to mass-customisation with low unit products. Assembly lines consume the largest parts of investment funds and involve the largest proportion of companies' labour force. However, workers in assembly lines are exposed to work-related musculoskeletal disorders (MSDs) and ergonomics problems. Poor distribution of workloads reduces the performance of assembly lines and causes workers MSDs and injuries, largely affecting the economics of production systems and resulting in high workers' compensation and absenteeism costs. Furthermore, ergonomics problems and MSDs impact product quality and decrease productivity. We propose a methodology for taking physical ergonomics into account as early as in the design phase of assembly lines. This methodology is based on Integer Linear Programming for the assembly line balancing problem with consideration of ergonomics with a quantitative fatigue and recovery criterion. As solving approach, we develop a dedicated exact algorithm, denoted Iterative Dichotomic Search, to solve low and medium-size instances of the problem. We validate our approach by proposing numerical experiments and analysis on instances from the literature.
Journal: International Journal of Production Research
Pages: 693-706
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2015081
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2015081
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# input file: TPRS_A_2017052_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Brandon W. Lee
Author-X-Name-First: Brandon W.
Author-X-Name-Last: Lee
Author-Name: Lakshminarayana Nittala
Author-X-Name-First: Lakshminarayana
Author-X-Name-Last: Nittala
Author-Name: Mark A. Jacobs
Author-X-Name-First: Mark A.
Author-X-Name-Last: Jacobs
Author-Name: Wantao Yu
Author-X-Name-First: Wantao
Author-X-Name-Last: Yu
Title: Impact of psychological safety on supply chain operational performance
Abstract: 
 This study examines the relationship between psychological safety and operational performance in the context of supply chain partners, i.e. an inter-organisational setting. While collaboration among supply chain partners enables effective problem solving and generates innovation, such collaborations may result in superior performance improvements when a psychologically safe business environment is created along the supply chain. The analysis of this study is based on data collected from 241 manufacturing companies in China using a survey questionnaire. A confirmatory factor analysis (CFA) was conducted to assess the validity of the measures, and an ordinary least squares (OLS) regression was used to test the hypotheses. Study results indicate that there is a significant positive association between psychological safety and operational performance in the context of supply chain partners. The results further show the relationship to be moderated by the learning orientation and inter-functional coordination. While the effect of psychological safety on performance has been studied in intra-organisational settings, studies on the psychological safety – performance relationship in an inter-organisational setting are scant. This study contributes to the literature in psychological safety and supply chain management as it extends the relationship to the context of supply chain partners.
Journal: International Journal of Production Research
Pages: 754-773
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2017052
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2017052
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# input file: TPRS_A_2020928_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ruixiao Dong
Author-X-Name-First: Ruixiao
Author-X-Name-Last: Dong
Author-Name: Xu Guan
Author-X-Name-First: Xu
Author-X-Name-Last: Guan
Author-Name: Baoshan Liu
Author-X-Name-First: Baoshan
Author-X-Name-Last: Liu
Author-Name: Sihua Chen
Author-X-Name-First: Sihua
Author-X-Name-Last: Chen
Title: Coopetition strategy in an imbalanced competitive environment
Abstract: 
 This study examines a firm's strategic choices of self-development or cooperation with (wholesaling from) its stronger rival. Both choices can improve the efficiency and competitive strength. We develop a benchmark of a full competition model, coopetition strategy, self-development strategy and hybrid strategy to investigate the effect of coopetition and self-development on firms who sell substitutive products in the end market. We show that both coopetition and self-development can benefit the high-cost firm. While the low-cost firm prefers the coopetition strategy. And in the hybrid strategy, the high-cost firm just utilises the self-development ability as a threat to enjoy a lower wholesale price. Interestingly, our research indicates that the mixed cooperation and competition relationship varies low-cost firm's attitudes towards product differentiation. On the one hand, the low-cost firm wants to produce homogeneous products to compete with rivals. On the other hand, he also wants to provide heterogenous products to alleviate competition in the coopetition strategy. The result provides company managers with a certain meaning in the complicated cooperative and competitive market environment.
Journal: International Journal of Production Research
Pages: 910-938
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2020928
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2020928
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# input file: TPRS_A_2018138_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yannick Kergosien
Author-X-Name-First: Yannick
Author-X-Name-Last: Kergosien
Author-Name: Valérie Bélanger
Author-X-Name-First: Valérie
Author-X-Name-Last: Bélanger
Author-Name: Angel Ruiz
Author-X-Name-First: Angel
Author-X-Name-Last: Ruiz
Title: A capacity sharing approach to manage jointly transportation and emergency fleets at EMS organisations
Abstract: 
 Emergency Medical Services (EMS) first mission is to reach people requiring urgent medical attention and transport them to hospitals or care facilities. In many cases, EMS also provide a second mission, which concerns the non-emergency transportation of patients. These services have different characteristics and goals from a managerial standpoint and in practice, most EMS organisations split their fleet into two sub-fleets that are managed independently. However, both missions are in most of the cases carried out by the same types of ambulances and crews, suggesting that managing both fleets together might bring potential advantages. This study explores the potential advantages of a new management strategy that allows sharing resources between two separated ambulance fleets. In particular, the proposed strategy allows for dynamically modifying the size of each fleet considering that a subset of ambulances can change their mission during the day to better adapt to the system's state. This strategy offers an incomplete integration of the fleets, but has the worthy advantages of improving the overall system performance and being simple to implement by an EMS organisation. Numerical experiments on realistic instances demonstrate, using a discrete event simulation tool, the feasibility and benefits of the proposed strategy.
Journal: International Journal of Production Research
Pages: 880-897
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2018138
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2018138
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# input file: TPRS_A_2018139_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Amel Ben Mabrouk
Author-X-Name-First: Amel
Author-X-Name-Last: Ben Mabrouk
Author-Name: Anis Chelbi
Author-X-Name-First: Anis
Author-X-Name-Last: Chelbi
Title: Optimal maintenance policy for equipment leased with base and extended warranty
Abstract: 
 In this paper, we consider an equipment leased with a warranty contract with the possibility to extend the warranty at a given price that depends on its duration. During the warranty period, the lessor (who possesses the equipment) performs and pays for repairs at failure and for preventive maintenance (PM) actions whenever the equipment reliability reaches a specific limit. After the warranty ends, repairs and PM actions are still performed by the lessor, but they are billed to the lessee (who rents the equipment). Furthermore, in case the total average equipment downtime due to repair and PM actions during the lease period surpasses a certain pre-specified limit agreed on in the lease contract, a penalty is supported by the lessor. A mathematical model and numerical procedure are proposed to determine the PM intervals durations that maximise the lessor’s expected total profit during the lease period. The optimal solution is obtained by determining the combination between the optimal equipment reliability threshold that triggers a PM action and the optimal extended warranty period. A numerical example is given to illustrate the use of the proposed model and a sensitivity analysis is performed.
Journal: International Journal of Production Research
Pages: 898-909
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2018139
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2018139
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Handle: RePEc:taf:tprsxx:v:61:y:2023:i:3:p:898-909



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# input file: TPRS_A_2015807_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Elvan Gökalp
Author-X-Name-First: Elvan
Author-X-Name-Last: Gökalp
Author-Name: Ece Sanci
Author-X-Name-First: Ece
Author-X-Name-Last: Sanci
Title: Robust capacity planning for sterilisation department of a hospital
Abstract: 
 Sterile services departments are special units designed to perform sterilisation operations in an efficient way within a hospital. The delays in sterilisation services cause significant disruptions on surgery schedules and bed management. To prevent the delays, an upper time limit can be imposed on the time spent in the sterilisation services. In this paper, we propose a mathematical modelling approach for the optimum capacity planning of a sterilisation service unit considering the uncertainties in the sterilisation process. The model aims to find the optimum capacity on four tandem steps of the sterilisation whilst at the same time minimising the total cost and keeping the maximum time in the system below a limit. Assuming general distributions for service and interarrival times, an approximation structure based on robust optimisation is used to formulate the maximum time spent in the system. We analysed the structural property of the resulting model and found that the relaxed version of the model is convex. The real data from a large sterilisation services unit is used for computational experiments. The results indicated that the approximation fits well against the simulated maximum time in the system. Other experiments revealed that an upper limit of 7 hours for the sterilisation services balances the cost vs. robustness trade-off.
Journal: International Journal of Production Research
Pages: 726-740
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2015807
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2015807
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Handle: RePEc:taf:tprsxx:v:61:y:2023:i:3:p:726-740



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# input file: TPRS_A_2017056_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Binghai Zhou
Author-X-Name-First: Binghai
Author-X-Name-Last: Zhou
Author-Name: Zhaoxu He
Author-X-Name-First: Zhaoxu
Author-X-Name-Last: He
Title: A novel hybrid-load AGV for JIT-based sustainable material handling scheduling with time window in mixed-model assembly line
Abstract: 
 Since global warming and the needs for sustainable production models, this paper focuses on a Just-in-Time (JIT)-based sustainable material handling scheduling problem (JSMHSP) with time window and capacity constraints for mixed-model assembly lines in the automobile industry. A novel Hybrid-load Automated Guided Vehicle (H-AGV) is proposed to fulfil material handling tasks between supermarkets and assembly lines. The motivation is to minimise the total line-side inventory and the total energy consumption, which corresponds to JIT and environmental objectives. Due to the NP-hard nature of the proposed scheduling problem, a Deep Q network and Non-dominated sorting-based Hyper-Heuristic (DN-HH) algorithm is presented to solve the bi-objective scheduling problem, which benefits from the synergy of the Deep Q Network (DQN) and Hyper-Heuristic (HH). In the DQN, the states and rewards are designed according to the characteristics of the scheduling problem. To improve the performance of DQN, the experience pool (EP) and the target network are presented to improve the convergence speed. Computational results reveal that the proposed DN-HH algorithm outperforms the other two compared algorithms in both solution quality and convergence speed and the performance of the H-AGV is better than that of the other two types of AGVs.
Journal: International Journal of Production Research
Pages: 796-817
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2017056
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2017056
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# input file: TPRS_A_2017057_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Golshan Madraki
Author-X-Name-First: Golshan
Author-X-Name-Last: Madraki
Author-Name: Seyedamirabbas Mousavian
Author-X-Name-First: Seyedamirabbas
Author-X-Name-Last: Mousavian
Author-Name: Yasamin Salmani
Author-X-Name-First: Yasamin
Author-X-Name-Last: Salmani
Title: A theoretical framework to accelerate scheduling improvement heuristics using a new longest path algorithm in perturbed DAGs
Abstract: 
 Job-shop scheduling problems are complex and still well-studied manufacturing problems. Improvement heuristic algorithms have been proposed to solve the scheduling problems using makespan as their performance measure. All these heuristics iteratively perturb trial schedules by selecting a new schedule from a set of nearby schedules (neighbourhood); then, recalculate and compare the makespan until a sufficient schedule is determined. Unlike previous studies, we did not generate a new heuristic or a novel neighbourhood calculation. Instead, we proposed a theoretical framework, Algorithm to Visit Affected Node (AVAN), which can be incorporated in qualified heuristics while using their current neighbourhood structure to accelerate the recalculation of the makespan in each iteration. We modelled the system by Directed Acyclic Graph (DAG) where the length of the longest path equals the makespan. The scheduling perturbations are represented by adding and deleting edges. AVAN investigates the configuration of scheduling perturbations (added/deleted edges) to find an appropriate starting point to traverse the graph. AVAN is mathematically more efficient than previous longest path algorithms for perturbed DAG. Its time complexity is 
 $ \textrm{O}({\Delta + \vert {\Delta } \vert \log ({\vert \Delta \vert } )} ) $ O(Δ+|Δ|log⁡(|Δ|)), where 
 $ \vert {\Delta } \vert $ |Δ| is the number of affected nodes and 
 $ \Delta $ Δ is the number of incoming and outgoing edges of the affected nodes.
Journal: International Journal of Production Research
Pages: 818-838
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2017057
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2017057
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# input file: TPRS_A_2018137_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Moustafa Gadalla
Author-X-Name-First: Moustafa
Author-X-Name-Last: Gadalla
Author-Name: Deyi Xue
Author-X-Name-First: Deyi
Author-X-Name-Last: Xue
Title: An efficient optimisation method based on weighted AND-OR trees for concurrent reconfigurable product design and reconfiguration process planning
Abstract: 
 A reconfigurable product can be used to replace multiple products through change of its configurations. Since multiple design candidates are usually considered based on design requirements, and multiple reconfiguration process candidates are usually considered to change between two product configurations, a method was developed in our previous research to identify both the optimal reconfigurable product design and its optimal reconfiguration process plan. This method was not effective when the numbers of design candidates and reconfiguration process candidates are large. To solve this problem, an efficient optimisation method is developed in this research based on weighted AND-OR trees for concurrent reconfigurable product design and reconfiguration process planning. First, the nodes in the product design and reconfiguration process AND-OR trees for modelling design and process candidates are associated with weights representing evaluation heuristics. Then a modified beam search method is developed to improve optimisation efficiency by pruning of the nodes in the AND-OR trees that are unlikely to achieve the optimal results. The created solutions modelled by design and reconfiguration process candidates are further ranked by heuristics. The top-ranked solutions are finally evaluated by numerical engineering functions to identify the optimal solution.
Journal: International Journal of Production Research
Pages: 859-879
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2018137
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2018137
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# input file: TPRS_A_2015806_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Karlijn Fransen
Author-X-Name-First: Karlijn
Author-X-Name-Last: Fransen
Author-Name: Joost van Eekelen
Author-X-Name-First: Joost
Author-X-Name-Last: van Eekelen
Title: Efficient path planning for automated guided vehicles using A* (Astar) algorithm incorporating turning costs in search heuristic
Abstract: 
 The path planned for an automated guided vehicle in, for example, a production facility is often the lowest-cost path in a (weighted) geometric graph. The weights in the graph may represent a distance or travel time. Sometimes turning costs are taken into account; turns (and decelerations before and accelerations after turning) take time, so it is desirable to minimise turns in the path. Several well-known algorithms can be used to find the lowest-cost path in a geometric graph. In this paper, we focus on the A
 $ ^* $ ∗ algorithm, which uses an (internal) search heuristic to find the lowest-cost path. In the current literature, generally, either turning costs are not taken into account in the heuristic or the heuristic can only be used for specific graph structures. We propose an improved heuristic for the A
 $ ^* $ ∗ algorithm that can be used to find the lowest-cost path in a geometric graph with turning costs. Our heuristic is proven to be monotone and admissible. Moreover, our heuristic provides a higher lower bound estimate for the actual costs compared to other heuristics found in the literature, causing the lowest-cost path to be found faster (i.e. with less iterations). We validate this through an extensive comparative study.
Journal: International Journal of Production Research
Pages: 707-725
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2015806
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2015806
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# input file: TPRS_A_2017054_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ece Yağmur
Author-X-Name-First: Ece
Author-X-Name-Last: Yağmur
Author-Name: Saadettin Erhan Kesen
Author-X-Name-First: Saadettin Erhan
Author-X-Name-Last: Kesen
Title: Bi-objective coordinated production and transportation scheduling problem with sustainability: formulation and solution approaches
Abstract: 
 This paper studies a new variant of integrated production scheduling and vehicle routing problem where production of customer orders are performed under job-shop environment and order deliveries are made by a heterogeneous fleet of vehicles, each of which is allowed to take multiple trips. Two conflicting objectives are considered, namely minimisation of the total amount of CO2 emitted by the vehicles and minimisation of maximum tardiness resulting from late deliveries. To this end, we present a bi-objective mixed-integer programming formulation. Augmented ε-Constraint (Augmecon) method is implemented to find Pareto optimal solutions. Due to problem complexity, Augmecon cannot provide solutions even with small-sized problems. Thus, we adopt Pareto Local Search (PLS) and non-dominated sorting genetic algorithm-II (NSGA-II) for practical sized instances. For small-sized instances involving 5, 6, and 7 customers, experimental results indicate that CPU time of Augmecon are 11, 84, and 524 sec, respectively with an average number of Pareto efficient solution of 3.5. In terms of hypervolume index, Augmecon shows the best performance, followed by NSGA-II with 11.32% and PLS with 20.75% degradation for small-sized instances. For medium and large-sized instances, PLS shows worse performance than NSGA-II by 16.87% and 40.48%.
Journal: International Journal of Production Research
Pages: 774-795
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2017054
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2017054
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# input file: TPRS_A_2015808_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Guillaume Dessevre
Author-X-Name-First: Guillaume
Author-X-Name-Last: Dessevre
Author-Name: Pierre Baptiste
Author-X-Name-First: Pierre
Author-X-Name-Last: Baptiste
Author-Name: Jacques Lamothe
Author-X-Name-First: Jacques
Author-X-Name-Last: Lamothe
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Title: Visual charts produced by simulation to correlate service rate, resource utilization and DDMRP parameters
Abstract: 
 Demand Driven Material Requirements Planning (DDMRP) is a recent method mixing push and pull flow management. Although it claims to be the solution to traditional methods’ limitations, the DDMRP method works at infinite capacity: manufacturing or supply orders are launched according to a logic of replenishment of stocks defined as buffers. This article proposes an evaluation of capacity management using visual charts developed by simulation. These charts correlate the bottleneck resource's loading rate to a service rate by considering one of the DDMRP method parameters, the Decoupled Lead Time (DLT). The charts are a decision support tool. They allow identifying to which loading rate the DLTs are representative of the flow times of manufacturing orders and which capacity level to use. We study different workshops, including a real industrial case. Our results show that it is better to control the flow times by adjusting capacity rather than adjust the DLT parameter.
Journal: International Journal of Production Research
Pages: 741-753
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2015808
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2015808
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2093680_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Biao Zhang
Author-X-Name-First: Biao
Author-X-Name-Last: Zhang
Author-Name: Quan-ke Pan
Author-X-Name-First: Quan-ke
Author-X-Name-Last: Pan
Author-Name: Lei-lei Meng
Author-X-Name-First: Lei-lei
Author-X-Name-Last: Meng
Author-Name: Xin-li Zhang
Author-X-Name-First: Xin-li
Author-X-Name-Last: Zhang
Author-Name: Xu-chu Jiang
Author-X-Name-First: Xu-chu
Author-X-Name-Last: Jiang
Title: A decomposition-based multi-objective evolutionary algorithm for hybrid flowshop rescheduling problem with consistent sublots
Abstract: 
 Lot streaming is the most widely used technique to facilitate the overlap of successive operations. Considering the consistent sublots and machine breakdown, this study investigates the multi-objective hybrid flowshop rescheduling problem with consistent sublots (MOHFRP_CS), which aims at optimising the total completion time, starting time deviations of operations, and average adjustment of sublot sizes simultaneously. By introducing the decomposition strategy and effective migrating birds optimisation framework, this paper develops a multi-objective migrating birds optimisation algorithm based on decomposition (MMBO/D). In MMBO/D, the problem is decomposed into a series of sub-problems, and its solutions are initialised by the Glover operator and further optimised by the variable neighbourhood descent strategy. The weights assigned to the sub-problems are adapted dynamically according to a variable weight strategy, and a global update strategy is employed to update the solutions. A novel sharing and benefiting mechanism is proposed to implement coevolution among different sub-problems. Competitive mechanisms are modified by considering similar sub-problems to improve population quality. A criterion is designed to check whether a subproblem is stuck in the local optima. The comprehensive computational results demonstrate that MMBO/D outperforms other state-of-the-art multi-objective evolutionary algorithms (MOEAs) for the addressed problem.
Journal: International Journal of Production Research
Pages: 1013-1038
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2093680
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2093680
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# input file: TPRS_A_2022801_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mojtaba Ebrahimi
Author-X-Name-First: Mojtaba
Author-X-Name-Last: Ebrahimi
Author-Name: Mehdi Mahmoodjanloo
Author-X-Name-First: Mehdi
Author-X-Name-Last: Mahmoodjanloo
Author-Name: Behnam Einabadi
Author-X-Name-First: Behnam
Author-X-Name-Last: Einabadi
Author-Name: Armand Baboli
Author-X-Name-First: Armand
Author-X-Name-Last: Baboli
Author-Name: Eva Rother
Author-X-Name-First: Eva
Author-X-Name-Last: Rother
Title: A mixed-model assembly line sequencing problem with parallel stations and walking workers: a case study in the automotive industry
Abstract: 
 A newly emerging mass-individualisation concept has attracted increasing attention in recent years. However, this concept increases the complexity of manufacturing systems within organisations. In such systems, one of the main challenges is the sequencing problem, especially in dynamic environments where unpredictable events demand new constraints. In this context, the ability to use real-time data to make efficient, quick decisions has become one of the main priorities of managers. In this paper, based on a real-world case from Fiat Powertrain Technologies, we define a dynamic mixed-model assembly line sequencing problem with walking workers. In this context, each worker is assigned to a product for all assembly operations and moves from one station to another. A mathematical model is proposed to minimise production time. Since the problem is NP-hard, a hyper-heuristic is also developed to solve the problem. Moreover, a simulation-optimisation model is developed using FlexSim software to solve a real-world problem in a dynamic environment. Comparison of the results illustrates the effectiveness of using the simulation approach to dynamically solve such problems, especially in real-world cases. Finally, a thorough description of managerial insights is provided to indicate the applicability of the proposed approach.
Journal: International Journal of Production Research
Pages: 993-1012
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2022801
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2022801
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# input file: TPRS_A_2022800_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xixi Li
Author-X-Name-First: Xixi
Author-X-Name-Last: Li
Author-Name: Fotios Petropoulos
Author-X-Name-First: Fotios
Author-X-Name-Last: Petropoulos
Author-Name: Yanfei Kang
Author-X-Name-First: Yanfei
Author-X-Name-Last: Kang
Title: Improving forecasting by subsampling seasonal time series
Abstract: 
 Time series forecasting plays an increasingly important role in modern business decisions. In today's data-rich environment, people often aim to choose the optimal forecasting model for their data. However, identifying the optimal model requires professional knowledge and experience, making accurate forecasting a challenging task. To mitigate the importance of model selection, we propose a simple and reliable algorithm to improve the forecasting performance. Specifically, we construct multiple time series with different sub-seasons from the original time series. These derived series highlight different sub-seasonal patterns of the original series, making it possible for the forecasting methods to capture diverse patterns and components of the data. Subsequently, we produce forecasts for these multiple series separately with classical statistical models (ETS or ARIMA). Finally, the forecasts are combined. We evaluate our approach on widely used forecasting competition data sets (M1, M3, and M4) in terms of both point forecasts and prediction intervals. We observe performance improvements compared with the benchmarks. Our approach is particularly suitable and robust for the data with higher frequency. To demonstrate the practical value of our proposition, we showcase the performance improvements from our approach on hourly load data that exhibit multiple seasonal patterns.
Journal: International Journal of Production Research
Pages: 976-992
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2022800
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2022800
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2021456_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Myungho Lee
Author-X-Name-First: Myungho
Author-X-Name-Last: Lee
Author-Name: Juntaek Hong
Author-X-Name-First: Juntaek
Author-X-Name-Last: Hong
Author-Name: Hyunjoon Kim
Author-X-Name-First: Hyunjoon
Author-X-Name-Last: Kim
Author-Name: Inhye Bang
Author-X-Name-First: Inhye
Author-X-Name-Last: Bang
Author-Name: Kangbok Lee
Author-X-Name-First: Kangbok
Author-X-Name-Last: Lee
Author-Name: Byung-In Kim
Author-X-Name-First: Byung-In
Author-X-Name-Last: Kim
Author-Name: Jungkyu Kim
Author-X-Name-First: Jungkyu
Author-X-Name-Last: Kim
Title: An integrated batching problem for steel plate manufacturing with bi-strand casting
Abstract: 
 We consider an integrated batching problem for steel-making and continuous casting process of steel plate manufacturing. For steel-making, slab batching problem is defined to make charges from slabs, and for continuous casting, charge batching problem is defined to make casts from charges. Our batching problem is regarded as a combination of slab batching and charge batching problems. Since steel-making and continuous casting are processes that must be synchronised, two batching problems must be integratedly handled. However, because of their difficulties, most papers solved each batching problem sequentially. We deal with a batching problem under bi-strand casting environment where slabs are cast with two strands. We also consider practical aspects that were barely considered before such as slab length difference constraints between strands and casts having few charges. We propose two mixed integer programming models. The first one is to create frames to define the overall structure of the solution and the second one is to fill the created frames with slabs to concretise the solution. The proposed matheuristic algorithm solves the problem in an integrated manner and finds a near-optimal solution in a reasonable time. It outperforms the company's current practice, as shown in experiments with real and randomly generated data.
Journal: International Journal of Production Research
Pages: 955-975
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2021456
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2021456
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# input file: TPRS_A_2017504_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ann-Louise Andersen
Author-X-Name-First: Ann-Louise
Author-X-Name-Last: Andersen
Author-Name: Thomas D. Brunoe
Author-X-Name-First: Thomas D.
Author-X-Name-Last: Brunoe
Author-Name: Markus Thomas Bockholt
Author-X-Name-First: Markus Thomas
Author-X-Name-Last: Bockholt
Author-Name: Alessia Napoleone
Author-X-Name-First: Alessia
Author-X-Name-Last: Napoleone
Author-Name: Jesper Hemdrup Kristensen
Author-X-Name-First: Jesper
Author-X-Name-Last: Hemdrup Kristensen
Author-Name: Michele Colli
Author-X-Name-First: Michele
Author-X-Name-Last: Colli
Author-Name: Brian Vejrum Wæhrens
Author-X-Name-First: Brian
Author-X-Name-Last: Vejrum Wæhrens
Author-Name: Kjeld Nielsen
Author-X-Name-First: Kjeld
Author-X-Name-Last: Nielsen
Title: Changeable closed-loop manufacturing systems: challenges in product take-back and evaluation of reconfigurable solutions
Abstract: 
 Due to continuous focus on sustainability and circular economy, product take-back programs are becoming increasingly relevant and attractive. Thus, closed-loop manufacturing systems have to be designed and developed for disassembly, reprocessing of materials, re-assembly, and remanufacturing in a cost-efficient way. Compared to traditional manufacturing, this involves a higher need for changeability due to higher uncertainty, e.g. in terms of timing and quantity that the system needs to handle, uncertainty in quality and materials of received items, and in particular significant variety in returned items, the system should be designed to process. Therefore, the objective of this paper is to investigate how reconfigurability, as the enabler of changeability at manufacturing system level, can be utilised to aid challenges in closed-loop manufacturing systems for product take-back. Initially, insights from an industrial case are presented regarding challenges in establishing and operating closed-loop manufacturing systems for product take-back programs. Secondly, different closed-loop manufacturing concepts applying the principles of reconfigurability are proposed and evaluated in terms of cost and robustness towards the inherent uncertainties in supplied end-of-use items. The results show significant potential of utilising a modular and platform-based approach towards meeting supply uncertainties through reconfiguration, which allows for a more efficient setup for product take-back.
Journal: International Journal of Production Research
Pages: 839-858
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2017504
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2017504
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# input file: TPRS_A_2020929_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Richard F. Hartl
Author-X-Name-First: Richard F.
Author-X-Name-Last: Hartl
Author-Name: Peter M. Kort
Author-X-Name-First: Peter M.
Author-X-Name-Last: Kort
Author-Name: Stefan Wrzaczek
Author-X-Name-First: Stefan
Author-X-Name-Last: Wrzaczek
Title: Reputation or warranty, what is more effective against planned obsolescence?
Abstract: 
 In determining the durability of its product a firm faces a trade off. Performing a policy of planned obsolescence by making their products less durable implies that the consumer needs to replace them earlier, which thus enhances demand. However, a lower quality of the product will result in a lower reputation, which in turn will affect demand negatively. In many cases, the government protects the consumer by implementing a warranty period. Our paper studies how a firm should optimally deal with this trade off and react to government policy. We obtain the following results. First, we find that the length of the warranty period has an inverted U-shaped effect on the product life time. Second, if more consumers are aware of the existence of a warranty period and ask for a free product replacement, this will increase the product life time. Third, increasing uncertainty about the breakdown of the product also has an inverted U-shaped effect on the product lifetime.
Journal: International Journal of Production Research
Pages: 939-954
Issue: 3
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2021.2020929
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2020929
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# input file: TPRS_A_2036850_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Martin Løkkegaard
Author-X-Name-First: Martin
Author-X-Name-Last: Løkkegaard
Author-Name: Christian Alexander Bertram
Author-X-Name-First: Christian Alexander
Author-X-Name-Last: Bertram
Author-Name: Niels Henrik Mortensen
Author-X-Name-First: Niels Henrik
Author-X-Name-Last: Mortensen
Author-Name: Lars Hvam
Author-X-Name-First: Lars
Author-X-Name-Last: Hvam
Author-Name: Anders Haug
Author-X-Name-First: Anders
Author-X-Name-Last: Haug
Title: Identifying profitable reference architectures in an engineer-to-order context
Abstract: 
 Companies operating with an engineer-to-order (ETO) strategy are often challenged with generating the desired profit as a consequence of product volumes and high levels of product customisation. Profit margins are seen to vary greatly from project to project, which may partly be explained by a lack of references to guide design decisions. Specifically, new product offerings are often based on reuse of design knowledge, which is often not efficiently utilised, as the knowledge transfer and reuse across projects are unstructured, incomplete, or not providing a suitable reference for design specification. To address this issue, this paper presents a method for identifying reference architectures under the consideration of profitability. The method was developed by combining and extending known methods within the fields of product architecture and complexity cost estimation to cover part of the ETO domain. The method was tested in two companies, one producing industrial spray drying plants and the other providing solutions for the production of confectionary products. The findings suggest that a limited understanding of ‘preferred solutions' existed in the two case companies, and applying the suggested method to identifying reference architectures could potentially support a more profitable project execution.
Journal: International Journal of Production Research
Pages: 1358-1372
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2036850
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2036850
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# input file: TPRS_A_2028921_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mohammad Givehchi
Author-X-Name-First: Mohammad
Author-X-Name-Last: Givehchi
Author-Name: Yongkui Liu
Author-X-Name-First: Yongkui
Author-X-Name-Last: Liu
Author-Name: Xi Vincent Wang
Author-X-Name-First: Xi Vincent
Author-X-Name-Last: Wang
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Title: Function block-enabled operation planning and machine control in Cloud-DPP
Abstract: 
 Today, due to shop-floor uncertainties and widespread cross-enterprise collaborations, manufacturing systems of enterprises are increasingly demanded to be agile, adaptive, flexible and interoperable. Process planning systems are mission-critical constituent components of manufacturing systems in machining job shops of small and medium-sized enterprises in the machining and metal cutting sector. Cloud-based adaptive distributed process planning, which includes global supervisory planning in the cloud and local operation planning based on function block and cloud technologies, provides an effective approach for enhancing agility, adaptability, flexibility and interoperability of manufacturing systems.
Journal: International Journal of Production Research
Pages: 1168-1184
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2028921
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2028921
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# input file: TPRS_A_2035008_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ashish Dwivedi
Author-X-Name-First: Ashish
Author-X-Name-Last: Dwivedi
Author-Name: Jitender Madaan
Author-X-Name-First: Jitender
Author-X-Name-Last: Madaan
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Author-Name: Mohit Dalal
Author-X-Name-First: Mohit
Author-X-Name-Last: Dalal
Title: A comparative study of GA and PSO approach for cost optimisation in product recovery systems
Abstract: 
 A product recovery system is proposed to reduce the bulk of waste sent to landfills by retrieving materials and parts of obsolete products for using them in remanufacturing and recycling. Product recovery is a significant strategy for enhancing customer satisfaction with regard to environmental concerns. Considering the fact that some products are returned, it becomes challenging to analyse whether to manufacture a new product or to rework the returned product at every step of the product recovery chain. Our approach uses a mixed integer linear programming model with the genetic algorithm and particle swarm optimisation, where two meta-heuristic algorithms are introduced for solving the MILP problem. Here, a recovery scenario is modelled, subject to the time and type of product to be processed. The study is intended to enhance the overall productivity of the product recovery chain. To demonstrate the approach, a case study is presented in the fast-moving consumer goods industry in which the proposed model demonstrates a reduction in the overall cost in the product recovery chain.
Journal: International Journal of Production Research
Pages: 1283-1297
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2035008
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2035008
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# input file: TPRS_A_2028199_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mohand-Lounes Bentaha
Author-X-Name-First: Mohand-Lounes
Author-X-Name-Last: Bentaha
Author-Name: Pascale Marangé
Author-X-Name-First: Pascale
Author-X-Name-Last: Marangé
Author-Name: Alexandre Voisin
Author-X-Name-First: Alexandre
Author-X-Name-Last: Voisin
Author-Name: Néjib Moalla
Author-X-Name-First: Néjib
Author-X-Name-Last: Moalla
Title: End-of-Life product quality management for efficient design of disassembly lines under uncertainty
Abstract: 
 The design of a disassembly line is a long-term investment. Therefore, it is important to optimise its performance and demonstrate its financial viability. The design process must consider the unique End-of-Life product characteristics and disassembly operation particularities. These peculiarities are mainly expressed by uncertainty in post-consumer products quality, variability of task processing times and presence of hazardous material. To achieve efficient disassembly line design, efficient decision-making tools are needed. The purpose of this work is to propose such a tool. The objective is to efficiently design a disassembly line, as a disassembly system, that provides optimal income and takes into account Enf-of-Life (EoL) product quality uncertainty and task processing times variability. The proposed tool allows the decision-maker to select the optimal disassembly process and depth while assigning retained tasks to the line workstations. Hazardous material of EoL products is handled and the designed line guarantees a certain level of service set by the decision-maker. The product part revenue depends formally on its EoL state or quality. Several product examples from remanufacturing sectors in industry are utilised to demonstrate interest and relevance of the proposed decision-aiding tool in an industrial context.
Journal: International Journal of Production Research
Pages: 1146-1167
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2028199
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2028199
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# input file: TPRS_A_2033336_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Giampaolo Campana
Author-X-Name-First: Giampaolo
Author-X-Name-Last: Campana
Author-Name: Enrico Malaguti
Author-X-Name-First: Enrico
Author-X-Name-Last: Malaguti
Author-Name: Mattia Mele
Author-X-Name-First: Mattia
Author-X-Name-Last: Mele
Author-Name: Paolo Paronuzzi
Author-X-Name-First: Paolo
Author-X-Name-Last: Paronuzzi
Title: Scheduling of semi-automatic carousels with fixed production sequences
Abstract: 
 Rotary transfer machines are widely used in different industrial sectors. A rich literature concerning their design and optimisation is available, but mainly dedicated to integrated machining systems. This machine architecture is also implemented in the aluminium gravity die casting technology where the specificity of the casting process needs an appropriate design. In particular, the constraints related to processing times and the rigidity of the production sequence impose a specific approach to schedule the production for achieving an optimal cycle time. We approach this problem with an optimisation perspective: first we propose a mixed-integer linear programming formulation for defining the sequencing and scheduling of the machine in order to obtain a specified production with minimum makespan, and discuss strategies for enumerating the variables of the formulation. Second, we describe a heuristic algorithm as an alternative to the solution of the formulation through a general-purpose solver. Eventually, we present extensive computational experiments on a set of instances generated from real data, comparing these alternative approaches.
Journal: International Journal of Production Research
Pages: 1252-1267
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2033336
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2033336
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# input file: TPRS_A_2030066_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lisha Song
Author-X-Name-First: Lisha
Author-X-Name-Last: Song
Author-Name: Shuguang He
Author-X-Name-First: Shuguang
Author-X-Name-Last: He
Author-Name: Ting Li
Author-X-Name-First: Ting
Author-X-Name-Last: Li
Author-Name: Yanfen Shang
Author-X-Name-First: Yanfen
Author-X-Name-Last: Shang
Title: Semiparametric control schemes for dynamically monitoring profiles with count data and arbitrary design
Abstract: 
 Many existing studies on profile monitoring focus on parametric profiles or normally distributed responses, and usually assume that the design points within different profiles are deterministic. In practice, however, profiles with count responses are common, and different profiles often have different within-profile sample sizes and design points. Furthermore, it is difficult to fit models to complex profiles with multiple explanatory variables either parametrically or nonparametrically. This article aims to monitor small-sample size profiles with count response and arbitrary design using a semiparametric model. Two novel control schemes with dynamic control limits are proposed based on the weighted likelihood ratio test and the weighted F test, respectively. Numerical simulations are conducted to investigate the performance of the proposed control charts. The performance between the control chart with constant and dynamic control limits is also compared, and the effect of model misspecification is explored. Finally, a real-data example of automobile warranty claims is presented to illustrate the implementation of the proposed control charts.
Journal: International Journal of Production Research
Pages: 1185-1201
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2030066
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2030066
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# input file: TPRS_A_2035010_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Maedeh Chaleshigar Kordasiabi
Author-X-Name-First: Maedeh
Author-X-Name-Last: Chaleshigar Kordasiabi
Author-Name: Hadi Gholizadeh
Author-X-Name-First: Hadi
Author-X-Name-Last: Gholizadeh
Author-Name: Marzieh Khakifirooz
Author-X-Name-First: Marzieh
Author-X-Name-Last: Khakifirooz
Author-Name: Mahdi Fathi
Author-X-Name-First: Mahdi
Author-X-Name-Last: Fathi
Title: Robust-heuristic-based optimisation for an engine oil sustainable supply chain network under uncertainty
Abstract: 
 This study configures various carbon regulation mechanisms to control carbon emissions following clean technology strategies in engine oil production. Considering clean technology strategies for designing a sustainable supply chain (SSC) in the engine oil industry, two carbon reduction policies, namely, carbon capacity and carbon emissions tax, are discussed to study the effects of environmental factors. A mixed-integer linear programming model that examines demand, technology, budget, carbon policies, and capacity constraints under several uncertainties is proposed for engine oil production from petrochemical resources, refinery plant production, and distribution system capacities. This study controls and mitigates risk and timing decisions for output decisions from a hybrid robust-heuristic-based method, wherein a modified scenario-based GA is used to eliminate the effect of uncertainties. The results indicate high-quality convergence of solutions for different strategic scenarios. We successfully apply the introduced model to address a real-world supply chain (SC) of the engine oil industry. The proposed model improves the state-of-the-art models for the engine oil SC. Finally, the study finding shows that managers can improve technologies with the lowest possible cost, maximum product profitability, and minimum possible losses in the production process and product quality through the carbon tax policy to reduce the environmental effects.
Journal: International Journal of Production Research
Pages: 1313-1340
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2035010
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2035010
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# input file: TPRS_A_2027041_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Changqing Liu
Author-X-Name-First: Changqing
Author-X-Name-Last: Liu
Author-Name: Yingguang Li
Author-X-Name-First: Yingguang
Author-X-Name-Last: Li
Author-Name: Chong Huang
Author-X-Name-First: Chong
Author-X-Name-Last: Huang
Author-Name: Yujie Zhao
Author-X-Name-First: Yujie
Author-X-Name-Last: Zhao
Author-Name: Zhiwei Zhao
Author-X-Name-First: Zhiwei
Author-X-Name-Last: Zhao
Title: A meta-reinforcement learning method by incorporating simulation and real data for machining deformation control of finishing process
Abstract: 
 Finishing determines the final dimension and geometric accuracy of parts, and the finishing process directly affects the stiffness and residual stress redistribution of the workpiece, so the optimisation of the finishing process plays a very important role in deformation control. At present, existing data-driven methods for deformation control need a large amount of labelled training data, which is always a challenge in the manufacturing area, especially for machining deformation. To address the above issues, this paper presents a meta-reinforcement learning model incorporated by simulation and real data, which is trained in a simulation environment with a piecewise sampling strategy for data collection, and can be updated in a real machining environment through a very small number of real monitoring data. The finishing process optimisation for deformation control can be realised using the proposed approach. Finally, the effectiveness of the proposed method is verified both in simulation environment and actual machining, and better results are obtained compared with other existing methods.
Journal: International Journal of Production Research
Pages: 1114-1128
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2027041
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2027041
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# input file: TPRS_A_2031330_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yilmaz Uygun
Author-X-Name-First: Yilmaz
Author-X-Name-Last: Uygun
Author-Name: Nikoloz Gotsadze
Author-X-Name-First: Nikoloz
Author-X-Name-Last: Gotsadze
Author-Name: Florian Schupp
Author-X-Name-First: Florian
Author-X-Name-Last: Schupp
Author-Name: Lizi Gzirishvili
Author-X-Name-First: Lizi
Author-X-Name-Last: Gzirishvili
Author-Name: Brigitte Stephanie Tindjou Nana
Author-X-Name-First: Brigitte Stephanie
Author-X-Name-Last: Tindjou Nana
Title: A holistic model for understanding the dynamics of outsourcing
Abstract: 
 Outsourcing is a complex process as many external and internal factors that look convincing in the first place might, however, lead to a failure in the long run. Motivated by this, we wanted to get a holistic understanding of such outsourcing decisions. Thus, we created a comprehensive System Dynamics simulation model including all relevant variables to examine the dynamic nature of outsourcing in a holistic manner and over time that consists of more than 200 interrelated variables. Our results show, amongst others, that higher process specialisation that requires substantial investments by the supplier appears to be favourable for an outsourcing company and shifting a larger quantity to such a supplier achieves better cost savings and thus accounts for a better overall outsourcing result. On an operational level, we identified an innovation trap, a bargaining power shift, a plagiarism trap, and a knowledge trap. Based on that, we give specific managerial recommendations to tackles these aspects. We conclude that, amongst others, it is important for innovative companies with rather complex processes and parts to carefully plan which and how many employees to release so as not to lose the knowledge on those outsourced processes and parts.
Journal: International Journal of Production Research
Pages: 1202-1232
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2031330
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2031330
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# input file: TPRS_A_2027040_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hyojoong Kim
Author-X-Name-First: Hyojoong
Author-X-Name-Last: Kim
Author-Name: Heeyoung Kim
Author-X-Name-First: Heeyoung
Author-X-Name-Last: Kim
Title: Deep embedding kernel mixture networks for conditional anomaly detection in high-dimensional data
Abstract: 
 In various industrial problems, sensor data are often used to detect the abnormal state of manufacturing systems. Sensor data are sometimes influenced by contextual variables that are not related to the system health status and may exhibit different behaviours depending on their values, even if the system is in a normal condition. In this case, a conditional anomaly detection method should be used to consider the effects of contextual variables. In this study, we propose a conditional anomaly detection method, particularly for high-dimensional and complex data, using a deep embedding kernel mixture network. The proposed method comprises embedding and kernel mixture networks. The embedding network learns low-dimensional embeddings from high-dimensional data, and the kernel mixture network models the distribution of the learned embeddings conditional on contextual variables. The two networks enable a flexible estimation of conditional density using the high expressive power of deep neural networks. The two networks are trained simultaneously such that the high-dimensional data are embedded into a low-dimensional space, to assist conditional density estimation. The effectiveness of the proposed model is demonstrated using real data examples from the UCI repository and a case study from a tire company.
Journal: International Journal of Production Research
Pages: 1101-1113
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2027040
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2027040
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# input file: TPRS_A_2025943_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Lipan Feng
Author-X-Name-First: Lipan
Author-X-Name-Last: Feng
Author-Name: Yongjian Li
Author-X-Name-First: Yongjian
Author-X-Name-Last: Li
Title: Ethical fashion supply chain operations: product development and moral hazards
Abstract: 
 Corporate social responsibility (CSR) is critical. As a part of CSR, fashion companies have to decide whether to be ethical or not during the product development process. Motivated by real-world practices, we conduct a gametheoretic modeling analysis and derive the firms’ optimal decisions (including ethical operations (ETO) adoption, pricing, and product greenness level) in fashion product development. We identify a key moderating factor which governs how an increase of basic market demand significantly affects the optimal product greenness level and how an increase of basic production cost influences the optimal retail price. Furthermore, we find that there is a threshold that plays a critical role in determining whether the optimal retail price and product greenness level are higher or lower with the adoption of ETO. We prove that when the fixed payment from the retailer to the manufacturer under the ETO case is set to be sufficiently small, the retailer prefers to adopt ETO and requests the manufacturer to follow. We propose three practical measures (including the use of technologies) to help encourage the supply chain members to invest in ETO willingly. We finally consider the probable occurrence of moral hazard problems and explore the managerial implications.
Journal: International Journal of Production Research
Pages: 1058-1075
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2025943
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2025943
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# input file: TPRS_A_2025945_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Chong Wu
Author-X-Name-First: Chong
Author-X-Name-Last: Wu
Author-Name: Jing Gao
Author-X-Name-First: Jing
Author-X-Name-Last: Gao
Author-Name: David Barnes
Author-X-Name-First: David
Author-X-Name-Last: Barnes
Title: Sustainable partner selection and order allocation for strategic items: an integrated multi-stage decision-making model
Abstract: 
 Current environmental issues and government requirements, together with pressure from the market and other stakeholders, emphasise the importance of partner selection in constructing and operating sustainable supply chains. Strategic items, which carry both high supply risk and high importance of purchase, are particularly important in sustainable supply chains. This paper presents an integrated decision-making model, which aims to solve the partner selection and order allocation problem for strategic items in sustainable supply chains. In the proposed model, weightings of different decision-makers are first calculated using Trapezoidal Fuzzy Numbers. Then, Taguchi loss function is used to evaluate the relative importance of potential partners, with the weighting results of criteria by Best-Worst Method. Finally, considering the weights of different potential partners, Particle Swarm Optimisation (PSO) is used to solve the multi-objective programming problem, and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) is applied to identify the most appropriate Pareto solution for sustainable partner selection and order allocation of strategic items. An illustrative application of the proposed model is undertaken in a leading Chinese LED lighting manufacturer to show its effectiveness and applicability.
Journal: International Journal of Production Research
Pages: 1076-1100
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2025945
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2025945
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# input file: TPRS_A_2034193_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Nuno O. Fernandes
Author-X-Name-First: Nuno O.
Author-X-Name-Last: Fernandes
Author-Name: Stefan Haeussler
Author-X-Name-First: Stefan
Author-X-Name-Last: Haeussler
Author-Name: Mark Stevenson
Author-X-Name-First: Mark
Author-X-Name-Last: Stevenson
Title: Dynamic planned lead times in production planning and control systems: does the lead time syndrome matter?
Abstract: 
 Many companies in practice want to dynamically adjust planned lead times in their production planning and control systems in response to demand fluctuations. But for decades it has been recognised that this can lead to escalating planned lead times and realised throughput times. Authors have highlighted the negative impact of this ‘lead time syndrome’, especially in the context of Material Requirements Planning systems, prompting the development of alternative concepts intended to overcome its vicious cycle, such as Workload Control. Yet some authors have shown that increasing planned lead times has advantages – it can improve end-item service levels. To resolve this paradox, we conjecture that the effects of the lead time syndrome are limited when demand is independent of internally planned lead times, such as in make-to-order companies, and subsequently use simulation to prove this conjecture. We show that although dynamic planned lead times have a detrimental effect on performance in make-to-order systems, it is not an increase in planned lead times that leads to a performance loss. Rather, it is the decrease of lead times in low load periods that increases workloads in upcoming periods of high load. This questions the use of upper bounds (WIP-cap) in these contexts.
Journal: International Journal of Production Research
Pages: 1268-1282
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2034193
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2034193
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# input file: TPRS_A_2036382_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Paul Stief
Author-X-Name-First: Paul
Author-X-Name-Last: Stief
Author-Name: Alain Etienne
Author-X-Name-First: Alain
Author-X-Name-Last: Etienne
Author-Name: Jean-Yves Dantan
Author-X-Name-First: Jean-Yves
Author-X-Name-Last: Dantan
Author-Name: Ali Siadat
Author-X-Name-First: Ali
Author-X-Name-Last: Siadat
Title: A methodology for production system design driven by product modelling and analysis – application in the automotive industry
Abstract: 
 This article synthesises the return of experience of performing a product variety analysis for a (supplier in the automotive sector) that haven’t had yet a product variety management strategy. This paper is part of a multi-year research project on the design of reconfigurable production systems. The contribution is (i) to present at a glance the developed strategy of product similarity assessment and (ii) to underline the industrial benefits of this similarity assessment obtained as a result of the industrial case studies. First, the article reminds, in the context of product variety, a developed methodology to assess product similarities by four indices. These consider the functions, product structures and the way to assemble them. Second, the focus is put on the benefits of their application through three industrial use cases: during the design of a new product identifying its impact on the manufacturing system, identifying the fittest production line for a new product to assemble and generating a new adapted production line by gathering products belonging to the same product family. All benefits are illustrated through the results of the industrial case studies. These are anonymised due to confidentiality issues.
Journal: International Journal of Production Research
Pages: 1341-1357
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2036382
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2036382
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# input file: TPRS_A_2031331_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jingcao Cai
Author-X-Name-First: Jingcao
Author-X-Name-Last: Cai
Author-Name: Deming Lei
Author-X-Name-First: Deming
Author-X-Name-Last: Lei
Author-Name: Jing Wang
Author-X-Name-First: Jing
Author-X-Name-Last: Wang
Author-Name: Lei Wang
Author-X-Name-First: Lei
Author-X-Name-Last: Wang
Title: A novel shuffled frog-leaping algorithm with reinforcement learning for distributed assembly hybrid flow shop scheduling
Abstract: 
 Distributed hybrid flow shop scheduling (DHFS) problem has attracted much attention in recent years; however, DHFS with actual processing constraints like assembly is seldom considered and reinforcement learning is hardly embedded into meta-heuristic for DHFS. In this study, a distributed assembly hybrid flow shop scheduling (DAHFS) problem with fabrication, transportation and assembly is considered and a mathematic model is constructed. A new shuffled frog-learning algorithm with Q-learning (QSFLA) is proposed to minimise makespan. A three-string representation is used. A newly defined Q-learning process is embedded into QSFLA to select a search strategy dynamically for memeplex search. It is composed of four actions based on the combination of global search, neighbourhood search and solution acceptance rule, six states depicted by population evaluation on elite solution and diversity, and a newly defined reward function. A number of experiments are conducted. The computational results demonstrate that QSFLA can provide promising results on the considered DAHFS.
Journal: International Journal of Production Research
Pages: 1233-1251
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2031331
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2031331
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# input file: TPRS_A_2027539_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jaeseung Baek
Author-X-Name-First: Jaeseung
Author-X-Name-Last: Baek
Author-Name: Myong K. Jeong
Author-X-Name-First: Myong K.
Author-X-Name-Last: Jeong
Author-Name: Elsayed A. Elsayed
Author-X-Name-First: Elsayed A.
Author-X-Name-Last: Elsayed
Title: Monitoring variations in multimode surface topography
Abstract: 
 The recent development of optical measuring instruments has increased the use of surface topographic data for monitoring the quality of the engineered surface. Due to the complexities of modern industrial processes, however, surfaces of final products under the normal manufacturing process may have multiple modes, such that the surface consists of different topographic features from one in-control mode to another. In this case, existing monitoring approaches based on the single mode surface cannot characterise normal surfaces with multiple modes, and result in poor detection performance. In this article, a new approach for monitoring variations in multimode surface topography is presented. We propose a multimode surface prediction model, which characterises the generic behaviour of normal surfaces with multiple in-control modes. Moreover, we present a mode-specific surface monitoring approach that identifies topographic variations on the surfaces based on the similarity between probability density function (PDF) of residuals from observed and normal surfaces obtained through the prediction model. A novel probabilistic distance measure is introduced to effectively measure the similarity between a single residual PDF and a set of residual PDFs under the same mode. The effectiveness of the proposed approach is demonstrated through numerical simulation and real-life application of paper surface monitoring.
Journal: International Journal of Production Research
Pages: 1129-1145
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2027539
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2027539
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# input file: TPRS_A_2025554_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Changcheng Wan
Author-X-Name-First: Changcheng
Author-X-Name-Last: Wan
Author-Name: Hualin Zheng
Author-X-Name-First: Hualin
Author-X-Name-Last: Zheng
Author-Name: Liang Guo
Author-X-Name-First: Liang
Author-X-Name-Last: Guo
Author-Name: Yongkui Liu
Author-X-Name-First: Yongkui
Author-X-Name-Last: Liu
Title: Hierarchical scheduling for multi-composite tasks in cloud manufacturing
Abstract: 
 Cloud manufacturing (CMfg) is a new manufacturing mode formed by the integration of information technology and communication technology with manufacturing. As a core role in CMfg, the CMfg platform is responsible for decomposing a large number of tasks from demander and allocating them to available services. The scheduling requires comprehensive consideration of the relevance, complexity and dynamics of task and service. When the decomposable task is multi-composite, how to allocate the optimum services to multi-composite tasks is a tricky and important problem. To solve the issue, a hierarchical scheduling model for multi-composite tasks is proposed, which is divided into user-level scheduling and sublevel scheduling to reduce the scale and difficulty of scheduling. User-level scheduling achieves two-way matching between demander and provider based on various attributes. For the sublevel scheduling, an improved firefly genetic algorithm is created for multi-objective optimisation. A detailed analysis of the hierarchical scheduling strategy is performed by testing several different instances. Experimental results indicate that this strategy reduces the complexity than collective scheduling; and has a better comprehensive balance effect on multiple optimisation goals than sequential scheduling.
Journal: International Journal of Production Research
Pages: 1039-1057
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2025554
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2025554
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# input file: TPRS_A_2035009_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Qiunan Meng
Author-X-Name-First: Qiunan
Author-X-Name-Last: Meng
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Title: Factor selection of product quotation with incomplete covering rough set
Abstract: 
 Factor selection is crucial for any enterprise to make a quick and accurate quotation decision. For the objects of quotation with missing values, traditional rough sets construct their relations (e.g. tolerance, cover) either with objects having known values, or only with those that also include the missing values of the attribute domains. Such classifications may not work well for reduction in many real-world problems. In this paper, by measuring the similarity of objects, an incomplete covering rough set is proposed to derive a cover for attribute reduction. Firstly, a similarity relation is defined by an approximation degree that tunes the relation in line with the semantics of objects, and then a cover is induced. Secondly, a reduct is derived by the relations of objects with respect to covers; the properties of reduction are proven. Finally, an approach is developed by discernibility matrix. The experimental results of the UCI (University of California Irvine) Repository and real-life quotation data sets show the incomplete covering rough set outperforms the compared rough set in the accuracy of factor selection within the comparable computation time. It is also demonstrated that the proposed quotation model is effective in quote prediction with various proportions of missing data.
Journal: International Journal of Production Research
Pages: 1298-1312
Issue: 4
Volume: 61
Year: 2023
Month: 02
X-DOI: 10.1080/00207543.2022.2035009
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2035009
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# input file: TPRS_A_1897175_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xiaoping Xu
Author-X-Name-First: Xiaoping
Author-X-Name-Last: Xu
Author-Name: Yujing Chen
Author-X-Name-First: Yujing
Author-X-Name-Last: Chen
Author-Name: Ping He
Author-X-Name-First: Ping
Author-X-Name-Last: He
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Gongbing Bi
Author-X-Name-First: Gongbing
Author-X-Name-Last: Bi
Title: The selection of marketplace mode and reselling mode with demand disruptions under cap-and-trade regulation
Abstract: 
 This paper studies a cooperating mode selection problem of a manufacturer who sells its products through an offline channel and an online platform under cap-and-trade regulation. The platform can operate with marketplace or reselling mode. We investigate the manufacturer's optimal operational decisions and selection of the platform's modes considering demand disruptions. First, when the carbon cap decreases in the application process, this regulation is firstly easy and then hard to be implemented if the cross-channel effect is small. Even though the platform increases its commission rate, greater cross-channel effect can still bring more production. Second, the increase of demand disruptions brings more profits for the manufacturer and the platform. Specifically, considering demand disruptions, the total profit with reselling mode in decentralised case is larger than that in centralised case under some situations. Third, without demand disruptions, the manufacturer prefers marketplace mode (reselling mode) if the commission rate is low (high). However, demand disruptions make the manufacturer's mode selection a little complicated. Lastly, without demand disruptions, the two firms can be coordinated with reselling mode but cannot be coordinated with marketplace mode. With demand disruptions, the two firms can be coordinated with the two modes in some situations.
Journal: International Journal of Production Research
Pages: 2738-2757
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1897175
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1897175
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# input file: TPRS_A_2009588_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Anni-Kaisa Kähkönen
Author-X-Name-First: Anni-Kaisa
Author-X-Name-Last: Kähkönen
Author-Name: Pietro Evangelista
Author-X-Name-First: Pietro
Author-X-Name-Last: Evangelista
Author-Name: Jukka Hallikas
Author-X-Name-First: Jukka
Author-X-Name-Last: Hallikas
Author-Name: Mika Immonen
Author-X-Name-First: Mika
Author-X-Name-Last: Immonen
Author-Name: Katrina Lintukangas
Author-X-Name-First: Katrina
Author-X-Name-Last: Lintukangas
Title: COVID-19 as a trigger for dynamic capability development and supply chain resilience improvement
Abstract: 
 A firm’s ability to manage risk and resilience in supply chains has turned out to be an invaluable capability during the COVID-19 pandemic. Fast responsiveness, quick decision-making, and the ability to reconfigure the resource base have helped firms during the pandemic, which caused rapid disruptive effects for which they were unprepared. This research applies the dynamic capability view as a theoretical framework to study the impact of the COVID-19 pandemic on firms’ dynamic capabilities and, the influence of dynamic capabilities on supply chain resilience. These capabilities are highly needed to survive during the pandemic. Using the survey data, we found that the impacts that COVID-19 had on a firm’s upstream supply chain influence firms’ capabilities to seize opportunities or neutralise threats. Furthermore, we found that reconfiguring ability has a strong influence on supply chain resilience. Thus, the impacts of COVID-19 on the downstream supply chain pushed firms to realign resources to respond better to demand. Upstream disruptions pushed companies to react to threats and opportunities in the supply market, while downstream disruptions leveraged reconfiguring capabilities.
Journal: International Journal of Production Research
Pages: 2696-2715
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.2009588
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2009588
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# input file: TPRS_A_1884310_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: ManMohan S. Sodhi
Author-X-Name-First: ManMohan S.
Author-X-Name-Last: Sodhi
Author-Name: Christopher S. Tang
Author-X-Name-First: Christopher S.
Author-X-Name-Last: Tang
Author-Name: Evan T. Willenson
Author-X-Name-First: Evan T.
Author-X-Name-Last: Willenson
Title: Research opportunities in preparing supply chains of essential goods for future pandemics
Abstract: 
 The COVID-19 pandemic severely tested the resilience and robustness of supply chains for medically critical items and various common household goods. Severe and prolonged shortages of personal protective equipment (PPE) and ventilators in the United States have revealed vulnerabilities in the supply chains of such essential products in a time of need. Consequently, corporations have felt public pressure to rethink their supply chains. We begin this paper by examining the underlying causes of the prolonged shortages of critical products in the US as well as government’s and some companies’ initial response. Drawing from the lessons learned from the COVID pandemic, we propose a research agenda and opportunities to develop responsive supply chains to fight future pandemics. These opportunities revolve around measures that are intended to improve the supply chain responsiveness of essential products to combat future pandemics and other major public health emergencies.
Journal: International Journal of Production Research
Pages: 2416-2431
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1884310
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884310
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# input file: TPRS_A_2177049_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Jennifer V. Blackhurst
Author-X-Name-First: Jennifer V.
Author-X-Name-Last: Blackhurst
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Title: Toward supply chain viability theory: from lessons learned through COVID-19 pandemic to viable ecosystems
Abstract: 
 The COVID-19 pandemic has triggered new research areas in supply chain resilience. One of these new areas is viability. Viability extends the resilience understanding from performance-based assessment of firm’s responses to disruptions towards survivability of both supply chains and associated ecosystems not only during some short-term disruptions but also under conditions of long-term crises. To explore the state-of-the-art knowledge on methods, models, capabilities, and technologies of supply chain viability, we edited this important IJPR special issue. To introduce the special issue, we review the existing literature on supply chain viability, conceptualise seven major pillars of supply chain viability theory (i.e. viable supply chain design, viability in process planning and control, ripple effect, intertwined and reconfigurable supply networks, ecosystems, digital supply chain, and Industry 5.0), and establish some associated future research directions. The findings of this editorial paper, as well as the articles in the special issue, can be used by researchers and practitioners alike to consolidate recent advances and practices of viability in supply chain networks and lay the solid foundation for further developments in this area.
Journal: International Journal of Production Research
Pages: 2402-2415
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2023.2177049
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2177049
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# input file: TPRS_A_1977865_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Javad Feizabadi
Author-X-Name-First: Javad
Author-X-Name-Last: Feizabadi
Author-Name: David M. Gligor
Author-X-Name-First: David M.
Author-X-Name-Last: Gligor
Author-Name: Thomas Y. Choi
Author-X-Name-First: Thomas Y.
Author-X-Name-Last: Choi
Title: Examining the resiliency of intertwined supply networks: a jury-rigging perspective
Abstract: 
 The COVID-19 pandemic has highlighted the salience of different supply networks merging together to provide critical products in short supply. The automotive supply network and the medical device supply network, for instance, became intertwined to meet rising demands for ventilators. As such, coming to the fore is a search mechanism, based on recombination of multiple components, conceptualized as jury-rigging behavior. Designing and changing the interdependencies across firms/supply chains become relevant. Drawing on complex adaptive systems and Ashby's law of requisite variety, we use a computational model to examine these mechanisms’ isolated and combined effect on supply chain network resiliency. Our results show statistically significant difference in the adaptiveness and mortality rate between a jury-rigged supply chain network and a non-jury-rigged one. In particular, the effect of jury-rigging is diminished by the level of coupling among the supply chains.
Journal: International Journal of Production Research
Pages: 2432-2451
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1977865
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1977865
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# input file: TPRS_A_2126021_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xavier Brusset
Author-X-Name-First: Xavier
Author-X-Name-Last: Brusset
Author-Name: Morteza Davari
Author-X-Name-First: Morteza
Author-X-Name-Last: Davari
Author-Name: Aseem Kinra
Author-X-Name-First: Aseem
Author-X-Name-Last: Kinra
Author-Name: Davide La Torre
Author-X-Name-First: Davide
Author-X-Name-Last: La Torre
Title: Modelling ripple effect propagation and global supply chain workforce productivity impacts in pandemic disruptions
Abstract: 
 An increasing number of disruptions in ports, plants and warehouses have generated ripple effects over supply networks impacting economic activity. We demonstrate how the spread of the pandemic geographically expands the ripple effect by reducing the workers' participation in production, so undermining the ability of firms and, as a result, the entire cross-border sup- ply chain network to satisfy customers' demands. Our model of the spatio-temporal dynamics of the propagation of Covid-19 infection for supply networks contributes toward ripple effect visualisation and quantification by combining the flow of goods and materials through a typical global supply chain with an epidemiological model. The model enables prospective analyses to be performed in what-if scenarios to simulate the impact on the workforce in each node. The outcome should be helpful tools for managers and scholars. Results from this research will help mitigate the impact and spread of a pandemic in a particular region and the ability of a supply network to overcome the ripple effect. A stylised case study of a cross-border supply chain illustrates the ripple effect by showing how waves with crests at varying dates impact the ability to serve demand showing how a supply chain manager can obtain a forward-looking picture.
Journal: International Journal of Production Research
Pages: 2493-2512
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2126021
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2126021
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# input file: TPRS_A_1976431_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Sanjoy Kumar Paul
Author-X-Name-First: Sanjoy Kumar
Author-X-Name-Last: Paul
Author-Name: Md. Abdul Moktadir
Author-X-Name-First: Md. Abdul
Author-X-Name-Last: Moktadir
Author-Name: Karam Sallam
Author-X-Name-First: Karam
Author-X-Name-Last: Sallam
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Ripon Kumar Chakrabortty
Author-X-Name-First: Ripon Kumar
Author-X-Name-Last: Chakrabortty
Title: A recovery planning model for online business operations under the COVID-19 outbreak
Abstract: 
 This study analytically develops a new recovery planning optimisation model for managing the impacts of the recent COVID-19 outbreak for online business operations. Firstly, a mathematical model for the ideal plan is designed and then extended to generate a recovery plan in a finite planning horizon that maximises total profit. Recovery plans are generated considering two scenarios, namely the dynamic and uncertain situations. For the dynamic situation, a realistic system with time-dependent and dynamic demand, supply, and warehouse capacity for investigating the impacts of the COVID-19 outbreak is developed using several measures, such as collaborating with emergency suppliers, increasing warehouse capacity, and considering back-orders and lost sales to form recovery strategies. For the uncertain situation, demand, supply, and warehouse capacities are considered as uncertain variables. Further, an innovative solution approach using an adapted differential evolution technique, which is capable of (i) generating long-term recovery plans and (ii) solving both small- and large-scale problems, is developed. The results are illustrated using numerical analyses and simulation experiments. A sensitivity analysis is also conducted. In practice, the proposed optimisation model will assist the decision-makers of online business operations facing the COVID-19 outbreak to decide the optimal recovery plans.
Journal: International Journal of Production Research
Pages: 2613-2635
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1976431
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1976431
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# input file: TPRS_A_2172964_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Title: A stochastic optimisation approach to maintain supply chain viability under the ripple effect
Abstract: 
 This paper presents a novel quantitative approach and stochastic quadratic optimisation model to maintain supply chain viability under the ripple effect. Instead of viability kernel commonly used in the viability theory, this paper establishes the boundaries on acceptable production states for which the production can be continued under the ripple effect, with no severe losses. For a given implementable portfolio of controls, the boundaries on acceptable production trajectories associated with the two conflicting objectives, cost and customer service level are determined. The decision maker selects a viable production trajectory in-between the two boundary trajectories: the cost-optimal and the service-optimal. The selection depends on the decision maker preference, represented by a chosen weight factor in the optimised quadratic objective function that minimises weighted deviations from the cost-optimal and from the service-optimal production schedules under the ripple effect. The findings indicate that for the extreme values of the weight factor, the viable production trajectory is inclined toward the corresponding boundary trajectory and remains in-between the two boundaries, when both objectives are equally important. Keeping production trajectory in-between the two boundaries makes the supply chain more resilient to disruption risks, while the supply chain resilience diminishes as the production trajectory approaches a boundary trajectory. Then a more severe disruption may push the production outside the viability region and cause greater losses.
Journal: International Journal of Production Research
Pages: 2452-2469
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2023.2172964
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2172964
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# input file: TPRS_A_2098073_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Rohit Sindhwani
Author-X-Name-First: Rohit
Author-X-Name-Last: Sindhwani
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Author-Name: Venkataramanaiah Saddikuti
Author-X-Name-First: Venkataramanaiah
Author-X-Name-Last: Saddikuti
Title: Ripple effect mitigation capabilities of a hub and spoke distribution network: an empirical analysis of pharmaceutical supply chains in India
Abstract: 
 In this study, we focus on ripple effect mitigation capability of the Indian pharmaceutical distribution network during disruptions like COVID-19 pandemic. To study the mitigation capabilities, we conduct a multi-layer analysis (network, process, and control levels) using Bayesian network, mathematical optimisation, and discrete event simulation methodologies. This analysis revealed an associative relationship between ripple effect mitigation capabilities and network design characteristics of upstream supply chain entities. Using stochastic optimisation and Lagrangian relaxation, we then find ideal candidates for regional distribution centres at the downstream level. We then integrate these downstream locations with other supply chain entities for building the network optimisation and simulation model to analyse overall performance of the system. We demonstrate utility of our proposed methodology using a case study involving distribution of N95 masks to ‘Jan Aushadhi’ (peoples’ medicines) stores in India during COVID-19 pandemic. We find that supply chain reconfiguration improves service level to 95.7% and reduces order backlogs by 10.7%. We also find that regional distribution centres and backup supply sources provide overall flexibility and improve occupational health and safety. We further investigate alternate mitigation capabilities through fortification of suppliers’ workforce by vaccination. We offer recommendations for policymakers and managers and implications for academic research.
Journal: International Journal of Production Research
Pages: 2795-2827
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2098073
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2098073
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# input file: TPRS_A_2029610_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Christopher Münch
Author-X-Name-First: Christopher
Author-X-Name-Last: Münch
Author-Name: Evi Hartmann
Author-X-Name-First: Evi
Author-X-Name-Last: Hartmann
Title: Transforming resilience in the context of a pandemic: results from a cross-industry case study exploring supply chain viability
Abstract: 
 Lately, there has been increased interest among researchers in studying the resilience of manufacturing supply chains. However, the Covid-19 pandemic has caused severe disruptions in global supply chains, which have led to calls for greater resilience in these supply chains. This study provides insights into the impact of the Covid-19 pandemic on supply chain resilience by conducting a multiple case study in three intertwined industries based on the dynamic capability view and the relational capability view as a theoretical underpinning. Data were collected during the pandemic in a two-stage interview process with 18 supply chain and production experts directly involved in crisis management. Internal and external documents supplemented the interviews. The results revealed seven higher-level capability groups for building resilience in intertwined supply chains during a pandemic outbreak: agility, collaboration, digital preparedness, flexible redundancy, human resource management, contingency planning, and transparency and visibility. Each capability group is supported by associated capabilities extracted from the data analysis. The findings obtained based on the results of the multiple case study are discussed, and implications for management and future research directions are presented.
Journal: International Journal of Production Research
Pages: 2544-2562
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2029610
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2029610
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# input file: TPRS_A_2027039_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xiongping Yue
Author-X-Name-First: Xiongping
Author-X-Name-Last: Yue
Author-Name: Dong Mu
Author-X-Name-First: Dong
Author-X-Name-Last: Mu
Author-Name: Chao Wang
Author-X-Name-First: Chao
Author-X-Name-Last: Wang
Author-Name: Huanyu Ren
Author-X-Name-First: Huanyu
Author-X-Name-Last: Ren
Author-Name: Pezhman Ghadimi
Author-X-Name-First: Pezhman
Author-X-Name-Last: Ghadimi
Title: Topological structure and COVID-19 related risk propagation in TFT-LCD supply networks
Abstract: 
 Thin-film-transistor liquid-crystal displays (TFT-LCDs) have gained popularity due to their widespread use in the production of televisions, laptops, and iPads. TFT-LCD firms’ activities that build relationships with suppliers and customers contribute to the emergence of supply networks. A firm’s ability to identify risks, however, is complicated, as TFT-LCD supply networks are becoming increasingly global, complex, and interconnected. The extant research on the topological structure of TFT-LCD supply networks is limited, and the risks identified rely on untested assumptions about the topological structure of such networks. To fill these gaps, this study examines the topological structure and COVID-19 related risk propagation in TFT-LCD supply networks from a dynamic perspective. First, the evolution of the topological structure of TFT-LCD supply networks from 2015 to 2020 is explored by constructing a weighted and undirected supply network. Second, the hidden risky sources in TFT-LCD supply networks are revealed by the proposed risk propagation model. The results show that TFT-LCD supply networks are characterised by a ‘hub and spoke’ feature and an explicit shift from geographical to global cooperation. Additionally, a ‘robust-yet-fragile’ configuration in these supply networks is uncovered, and the hidden risky sources in the main TFT-LCD manufacturers and suppliers and in interfirm cooperations are revealed. These findings will help managers reduce the vulnerability of TFT-LCD supply networks to disruptions and construct more robust and resilient networks.
Journal: International Journal of Production Research
Pages: 2758-2778
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2027039
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2027039
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# input file: TPRS_A_1946726_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mohamed R. Salama
Author-X-Name-First: Mohamed R.
Author-X-Name-Last: Salama
Author-Name: Ronald G. McGarvey
Author-X-Name-First: Ronald G.
Author-X-Name-Last: McGarvey
Title: Resilient supply chain to a global pandemic
Abstract: 
 The design and management of a supply chain (SC) in a global pandemic require a different approach than those used for more spatially restricted risks, such as earthquakes. A successful SC design and management plan should consider pandemic spatiotemporal characteristics as well as its effects on production and logistical operations, and on the SC workforce at risk. In this paper, a stochastic mixed integer linear programming model is developed to maximise the conditional value at risk (CVaR) of SC profit given a set of pandemic scenarios. An exemplar SC network from the literature is utilised, along with randomly generated pessimistic and optimistic pandemic scenarios. The proposed model is demonstrated by obtaining SC designs for different cases pertaining to pandemic influence and strategic policies. The resultant SC designs are used to contrast the performance of management plans across different pandemic scenarios and for different levels of workforce at risk. Supply chains for socially critical products, such as ventilators, are studied separately to examine the impact of SC network expansion on maximizing satisfied demand. Finally, we investigate the effects of diversifying network node locations across different administrative regions on SC performance. Several managerial insights are presented for SC planners to aid in creating viable designs and management plans.
Journal: International Journal of Production Research
Pages: 2563-2593
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1946726
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1946726
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# input file: TPRS_A_1970848_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ahmed Mohammed
Author-X-Name-First: Ahmed
Author-X-Name-Last: Mohammed
Author-Name: Ana Beatriz Lopes de Sousa Jabbour
Author-X-Name-First: Ana Beatriz Lopes de Sousa
Author-X-Name-Last: Jabbour
Author-Name: Ali Diabat
Author-X-Name-First: Ali
Author-X-Name-Last: Diabat
Title: COVID-19 pandemic disruption: a matter of building companies’ internal and external resilience
Abstract: 
 This paper develops an integrated methodology aimed at diagnosing supply chain resilience in terms of (1) internal dynamic capabilities of an enterprise, and (2) resilience of its suppliers. In addition, unlike other research, it integrates the suppliers’ resilience evaluation into the order size allocation plan. Multi-attribute decision making (MADM) algorithms were employed to quantify the relative importance to evaluate the internal and external resilience of an enterprise. Furthermore, the MADM output was combined with a multi-objective programming model formulated to solve the order size problem considering economic and resilience objectives. The applicability of the developed methodology is demonstrated via a dairy manufacturing enterprise that suffered from disruptions attributed to COVID-19. The results translate the enterprise’s non-viable manufacturing due to its poor external and internal resilience profiles. It is emphasized that if an enterprise fails to develop internal capabilities such as readiness and sensing, the enterprise could also fail in managing external resilience. A resilient supply chain requires a blend of internal and external resilience. This work represents the first quantitative attempt to provide a unified methodology for identifying and measuring internal and external resilience.
Journal: International Journal of Production Research
Pages: 2716-2737
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1970848
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1970848
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# input file: TPRS_A_1944390_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Muhammad Shujaat Mubarik
Author-X-Name-First: Muhammad Shujaat
Author-X-Name-Last: Mubarik
Author-Name: Simonov Kusi-Sarpong
Author-X-Name-First: Simonov
Author-X-Name-Last: Kusi-Sarpong
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Sharfuddin Ahmed Khan
Author-X-Name-First: Sharfuddin Ahmed
Author-X-Name-Last: Khan
Author-Name: Adegboyega Oyedijo
Author-X-Name-First: Adegboyega
Author-X-Name-Last: Oyedijo
Title: Supply chain mapping: a proposed construct
Abstract: 
 During COVID-19, supply chain (SC) mapping has appeared as one of the critical supply chain capabilities that could make a striking difference in organisations’ supply chain performance. Despite its crucial role in responding to SC disruptions, there is a void in the literature on this topic. In this context, the prime objective of the current study is to introduce a comprehensive measure of SC mapping accounting for its various dimensions. A review of the literature is conducted to identify the relevant dimensions and sub-dimensions of SC mapping. Next, two rounds of focused group discussions are conducted in order to refine the identified dimensions and to add any relevant dimensions of SC mapping. Third, we employ exploratory factor analysis to develop the construct of SC mapping. The findings reveal that SC mapping has three major dimensions, namely upstream mapping, downstream mapping, and midstream mapping, with a total 25 items. The developed construct can be used to operationalise the SC mapping and to examine its antecedents and precedents.
Journal: International Journal of Production Research
Pages: 2653-2669
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1944390
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1944390
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# input file: TPRS_A_1930237_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mozhu Wang
Author-X-Name-First: Mozhu
Author-X-Name-Last: Wang
Author-Name: Jianming Yao
Author-X-Name-First: Jianming
Author-X-Name-Last: Yao
Title: Intertwined supply network design under facility and transportation disruption from the viability perspective
Abstract: 
 To ensure viability, it is necessary for an intertwined supply network (ISN) system to optimise network structure to provide flexible redundancy in response to changing environment. Considering resilience methods are usually designed as reactions to single discrete disruptions rather than situational reactions to real-time changes, this study proposes a novel redundancy optimisation approach dynamically providing each demand market with a pair of supply routes to optimise the flexible redundancy of ISN, thereby ensuring the survivability of supply chains and demand markets under continuous changes. Based on this, we propose the ISN design (ISND) model to capture the trade-off between total cost and viability performance under facility and transportation disruption. The Lagrangian relaxation algorithm, combined with the sub-gradient method and the improved cellular genetic algorithm, are utilised for solving problems of different scales. To test the performance of the model and corresponding algorithms, we also conduct a numerical analysis of the data from medical equipment ISN in southern China. The results indicate that the ISND model can effectively optimise ISN structures, which makes it possible to dynamically provide flexible redundancy; the two algorithms also show good calculation efficiency. The relationship between ISN structure and viability performance is thus observed and explained.
Journal: International Journal of Production Research
Pages: 2513-2543
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1930237
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1930237
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# input file: TPRS_A_2147235_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Maximilian Klöckner
Author-X-Name-First: Maximilian
Author-X-Name-Last: Klöckner
Author-Name: Christoph G. Schmidt
Author-X-Name-First: Christoph G.
Author-X-Name-Last: Schmidt
Author-Name: Stephan M. Wagner
Author-X-Name-First: Stephan M.
Author-X-Name-Last: Wagner
Title: The COVID-19 pandemic and shareholder value: impact and mitigation
Abstract: 
 The financial implications of the worldwide COVID-19 pandemic and the effective mitigation of the negative effects are the subject of an ongoing debate. We aim to empirically substantiate this debate. Based on a sample of 4,032 publicly traded U.S. and Chinese firms, we conduct an event study and find that the COVID-19 pandemic is associated with a substantial decrease in shareholder value, significantly varying between U.S. and Chinese firms and across industries. We further identify structure- and supply chain-related firm factors that mitigate the negative impact. Specifically, we find that smaller firms experience a less negative impact on shareholder value, challenging established findings. Our results also suggest that a lower dependence on physical assets, a shorter trade cycle, and a higher degree of vertical integration attenuate the negative impact on shareholder value. Our findings provide important insights for managers and policymakers. We recommend managers to reduce the dependency on business models that strongly rely on physical assets, to streamline trade cycles, and to reduce supply chain complexity. From a policy perspective, we emphasise the importance of more industry-specific granularity of public support measures.
Journal: International Journal of Production Research
Pages: 2470-2492
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2147235
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2147235
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# input file: TPRS_A_1962559_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Salomée Ruel
Author-X-Name-First: Salomée
Author-X-Name-Last: Ruel
Author-Name: Jamal El Baz
Author-X-Name-First: Jamal
Author-X-Name-Last: El Baz
Title: Disaster readiness’ influence on the impact of supply chain resilience and robustness on firms’ financial performance: a COVID-19 empirical investigation
Abstract: 
 This study investigates the impact of supply chain (SC) disaster readiness on SC resilience and robustness and the subsequent impact on firms’ financial performance in the context of the COVID-19 outbreak. Drawing on the dynamic capabilities view and organisational readiness for change theory, we provide a theoretical model and assess data gathered of 398 French firms using structural equation modelling. The findings corroborate the role of SC disaster readiness in setting the stage for resilience and robustness. In addition, the results indicate the positive influence of SC resilience on financial performance; however, the effects of SC robustness on performance are not demonstrated. Based on these results, we offer theoretical and practical implications for the extant literature and provide further avenues for research.
Journal: International Journal of Production Research
Pages: 2594-2612
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1962559
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1962559
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# input file: TPRS_A_1943036_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bin Shen
Author-X-Name-First: Bin
Author-X-Name-Last: Shen
Author-Name: Yang Liu
Author-X-Name-First: Yang
Author-X-Name-Last: Liu
Author-Name: Vincent Quan
Author-X-Name-First: Vincent
Author-X-Name-Last: Quan
Author-Name: Xin Wen
Author-X-Name-First: Xin
Author-X-Name-Last: Wen
Title: Supplying masks to combat respiratory diseases: safety index, welfare and government involvement
Abstract: 
 Coronavirus (COVID-19) is a highly infectious respiratory disease which spread can be effectively curbed by wearing facial masks, especially N95 and surgical masks. In this paper, we develop a stylised game-theoretical model to evaluate the impacts of producing and selling masks on supply chain profits, safety index and consumer and social welfare. Firstly, we find that as the infection probability without protection (IPWP) increases, both the retail price and demand for these masks will increase. When the IPWP is sufficiently low, those consumers who want to purchase masks are more likely to purchase N95 masks, but when the IPWP increases, surgical masks are more popular amongst consumers. Secondly, we develop a safety index that indicates the effectiveness of using masks in preventing respiratory disease infection. This index is especially crucial in cases where the IPWP is moderate; in other words, recommending to wear masks is particularly important when the IPWP is moderate. We also examine the impacts of government involvement in handling the outbreak of respiratory diseases. Providing consumer subsidies and promoting the social mask enterprise can effectively combat respiratory diseases under different conditions. Our results can be used for combating COVID-19 and preparing for future health crisess.
Journal: International Journal of Production Research
Pages: 2636-2652
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1943036
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1943036
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# input file: TPRS_A_1982152_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Pradeep K. Jha
Author-X-Name-First: Pradeep K.
Author-X-Name-Last: Jha
Author-Name: Suvadip Ghorai
Author-X-Name-First: Suvadip
Author-X-Name-Last: Ghorai
Author-Name: Rakhi Jha
Author-X-Name-First: Rakhi
Author-X-Name-Last: Jha
Author-Name: Rajul Datt
Author-X-Name-First: Rajul
Author-X-Name-Last: Datt
Author-Name: Gowrishankar Sulapu
Author-X-Name-First: Gowrishankar
Author-X-Name-Last: Sulapu
Author-Name: Surya Prakash Singh
Author-X-Name-First: Surya Prakash
Author-X-Name-Last: Singh
Title: Forecasting the impact of epidemic outbreaks on the supply chain: modelling asymptomatic cases of the COVID-19 pandemic
Abstract: 
 An epidemic outbreak largely disrupts supply chains (SCs) worldwide through plummeting business confidence, especially when it becomes a pandemic; its unpredictable re-emergence and spreadability may lead to inappropriate decision-making, in turn causing severe economic shocks. In March 2020, the coronavirus disease 2019 (COVID-19) outbreak attained a pandemic level, and many millions of cases were confirmed globally. Many countries reported an increasing number of active cases and formulated long-term lockdown guidelines, which resulted in an unexpected disruption of SCs. A key challenge in this scenario is that the rising number of confirmed COVID-19 cases does not necessarily reflect the already infected or asymptomatic cases. It is thus critical to understand the impact of asymptomatic carriers on the SC, as they may be the key driver of the novel virus spread, disrupting long-term SCs. This paper generalised the susceptible-exposed-infected-recovered (S-E-I-R) approach to create a mathematical model for which the impact of a proposed asymptomatic situation on the SC is evaluated through the basic reproduction number (R0), considered the main driver of SC disruption and the equilibrium status of infection over time. This paper presents an action plan for reducing disruption in the SC based on the R0 of the model. Overall, the current study as validated through a case study suggests that the asymptomatic-situation-based model is more convenient for critically understanding as well as forecasting the outbreak’s impact on SCs. This study also highlights different perspectives of SCs for managing such types of pandemics using modelling approaches.
Journal: International Journal of Production Research
Pages: 2670-2695
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2021.1982152
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1982152
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# input file: TPRS_A_2053604_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yiji Cai
Author-X-Name-First: Yiji
Author-X-Name-Last: Cai
Author-Name: Shuyi Wang
Author-X-Name-First: Shuyi
Author-X-Name-Last: Wang
Author-Name: Zhiyuan Ouyang
Author-X-Name-First: Zhiyuan
Author-X-Name-Last: Ouyang
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Impacts of social distancing measures on global supply chain configuration
Abstract: 
 World Health Organisation has advised governments to prevent the spread of COVID-19 by introducing stringent social distancing measures (SDMs) in five levels, ranging from pandemic surveillance, stay-at-home recommendations, workplace closures, to national and international travel restrictions. These measures inevitably disrupt global business environment and supply chain configuration. Existing literature does not comprehensively analyze the five-level SDMs’ impacts on firms and supply chains. Thus, we established a mixed-integer programming model to integrate environment changes in lead time and cost for transportation and processing, market size, and the number of countries (NoC) imposing the SDMs. Sensitivity analysis is conducted to evaluate propagation impacts on global supply chains when the SDMs are imposed on firms in different echelons of supply chains. Results show that (i) supply chain losses and disruptions primarily depend on the NoC, followed by restricted transportation, market size, and processing limitations. (ii) When the SDMs, especially restrictions on transportation, are implemented in downstream echelons, the propagation impacts on supply chains and firms become more significant. (iii) Compared with elastic-demand supply chains, the fixed-demand one, e.g. food supply chain, suffers more significantly with the stringent SDMs and high holding costs. Finally, managerial implications are discussed from supply chains, firms, and policymakers.
Journal: International Journal of Production Research
Pages: 2779-2794
Issue: 8
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2053604
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2053604
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# input file: TPRS_A_2070882_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mateus Martin
Author-X-Name-First: Mateus
Author-X-Name-Last: Martin
Author-Name: Horacio Hideki Yanasse
Author-X-Name-First: Horacio
Author-X-Name-Last: Hideki Yanasse
Author-Name: Maristela O. Santos
Author-X-Name-First: Maristela O.
Author-X-Name-Last: Santos
Author-Name: Reinaldo Morabito
Author-X-Name-First: Reinaldo
Author-X-Name-Last: Morabito
Title: Models for two- and three-stage two-dimensional cutting stock problems with a limited number of open stacks
Abstract: 
 We address three variants of the two-dimensional cutting stock problem in which the guillotine cutting of large objects produces a set of demanded items. The characteristics of the variants are the rectangular shape of the objects and items; the number of two or three orthogonal guillotine stages; and a sequencing constraint that limits the number of open stacks to a scalar associated with the number of automatic compartments or available space near the cutting machine. These problems arise in manufacturing environments that seek minimum waste solutions with limited levels of work-in-process. Despite their practical relevance, we are not aware of mathematical models for them. In this paper, we propose an integer linear programming (ILP) formulation for each of these variants based on modelling strategies for the two-dimensional guillotine cutting stock problem and the minimisation of the open stacks problem. The first two variants deal with exact and non-exact 2-stage patterns, and the third with a specific type of 3-stage patterns. Using a general-purpose ILP solver, we performed computational experiments to evaluate these approaches with benchmark instances. The results show that several equivalent solutions of the cutting problem allow obtaining satisfactory solutions with a reduced number of open stacks.
Journal: International Journal of Production Research
Pages: 2894-2915
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2070882
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2070882
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# input file: TPRS_A_2077673_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Eduardo Álvarez-Miranda
Author-X-Name-First: Eduardo
Author-X-Name-Last: Álvarez-Miranda
Author-Name: Jordi Pereira
Author-X-Name-First: Jordi
Author-X-Name-Last: Pereira
Author-Name: Camila Vargas
Author-X-Name-First: Camila
Author-X-Name-Last: Vargas
Author-Name: Mariona Vilà
Author-X-Name-First: Mariona
Author-X-Name-Last: Vilà
Title: Variable-depth local search heuristic for assembly line balancing problems
Abstract: 
 Assembly lines are production flow systems wherein activities are organised around a line consisting of various workstations through which the product flows. At each station, the product is assembled through a subset of operations. The assembly line balancing problem (ALBP) consists of allocating operations between stations to maximise the system efficiency. In this study, a variable-depth local search algorithm is proposed for solving simple assembly line balancing problems (SALBPs), which are the most widely studied versions of the ALBP. Although the state-of-the-art techniques for solving the SALBP consist of exact enumeration-based methods or heuristics, this paper proposes a local search-based heuristic using variable-length sequences that allow the solution space to be efficiently explored. The proposed algorithm improves the best solution known for multiple instances reported in the literature, indicating that its efficiency is comparable to those of the state-of-the-art method for solving the SALBP. Moreover, the characteristics of the instances for which the proposed procedure provides a better solution than previously reported construction procedures are investigated.
Journal: International Journal of Production Research
Pages: 3102-3120
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2077673
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2077673
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# input file: TPRS_A_2070786_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Fuqing Zhao
Author-X-Name-First: Fuqing
Author-X-Name-Last: Zhao
Author-Name: Xiaotong Hu
Author-X-Name-First: Xiaotong
Author-X-Name-Last: Hu
Author-Name: Ling Wang
Author-X-Name-First: Ling
Author-X-Name-Last: Wang
Author-Name: Tianpeng Xu
Author-X-Name-First: Tianpeng
Author-X-Name-Last: Xu
Author-Name: Ningning Zhu
Author-X-Name-First: Ningning
Author-X-Name-Last: Zhu
Author-Name:  Jonrinaldi
Author-X-Name-First: 
Author-X-Name-Last: Jonrinaldi
Title: A reinforcement learning-driven brain storm optimisation algorithm for multi-objective energy-efficient distributed assembly no-wait flow shop scheduling problem
Abstract: 
 A reinforcement learning-driven brain storm optimisation idea (RLBSO) is proposed in this paper to solve multi-objective energy-efficient distributed assembly no-wait flow shop scheduling problem. The objectives of the problem include minimising the maximum assembly completion time (
 $ {C_{\textrm{max}}} $ Cmax), minimising the total energy consumption (TEC) and achieving resource allocation balanced . Four operations, which are critical factory insert, critical factory swap, critical factory insert to other factories, critical factory swap with other factories, are designed to optimise the objective of maximum assembly completion time. Q-learning mechanism is utilised to guide the selection of operations to avoid blind search in the iteration process. The learning mechanism based on clustering mechanism in brain storm optimisation algorithm is utilised to assign products to factories in the objective space according to the processing time of products to balance the resources allocation. The speed of operations on non-critical path is slowed down to reduce TEC regarded with the characteristics of no-wait flow shop scheduling problem. The experimental results under 810 large-scale instances by RLBSO show that the RLBSO outperforms the comparison algorithm for addressing the problem.
Journal: International Journal of Production Research
Pages: 2853-2871
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2070786
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2070786
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# input file: TPRS_A_2075292_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jun Dong
Author-X-Name-First: Jun
Author-X-Name-Last: Dong
Author-Name: Chunming Ye
Author-X-Name-First: Chunming
Author-X-Name-Last: Ye
Title: Joint optimisation of uncertain distributed manufacturing and preventive maintenance for semiconductor wafers considering multi-energy complementary
Abstract: 
 Aiming at the joint optimisation problem of uncertain distributed manufacturing and preventive maintenance (PM) for semiconductor wafers considering multi-energy complementary (UDMPM-MEC), a bi-level integrated scheduling model is constructed with interval makespan, total interval carbon emissions and total interval cost as the optimisation objectives. The upper model is used to obtain the joint optimisation scheduling scheme of distributed manufacturing and PM, and the lower model determines the energy allocation scheme on this basis. Given the problem characteristics, we propose an improved multi-objective whale swarm algorithm (IMOWSA). By designing jobs-to-factories allocation strategy, synchronous scheduling maintenance strategy, multi-energy complementary energy allocation decoding strategy, individual distance calculation strategy, multi-neighbourhood search strategy and deduplication strategy, the local and global search are effectively balanced, and the convergence precision is improved. A large number of simulation experiments and comparative analyses show that the IMOWSA algorithm is feasible and effective to solve this problem.
Journal: International Journal of Production Research
Pages: 3029-3050
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2075292
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2075292
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# input file: TPRS_A_2075291_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Riccardo Aldrighetti
Author-X-Name-First: Riccardo
Author-X-Name-Last: Aldrighetti
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Ajay Das
Author-X-Name-First: Ajay
Author-X-Name-Last: Das
Author-Name: Marco Simonetto
Author-X-Name-First: Marco
Author-X-Name-Last: Simonetto
Title: The performance impact of Industry 4.0 technologies on closed-loop supply chains: insights from an Italy based survey
Abstract: 
 Closed-Loop Supply Chain (CLSC) and Industry 4.0 (I4.0) are two significant initiatives that have engaged European and global business over the past few years. While direct effects of these initiatives on performance have been found, the nature and performance effects of interactions among these two initiatives remain largely unexamined. This exploratory study theorises and investigates how I4.0 technologies can facilitate CLSC initiatives. Data are collected and analysed from enterprises located in the northeast of Italy. Partial least squares structural equation modelling (PLS-SEM) is deployed to analyse the data. The data suggest a significant and beneficial moderator of I4.0 technologies on the relationship between CLSC practices and firm environmental and social performance. The data fails to find a significant relationship between CLSC practices and financial performance. Data-driven I4.0 technologies are seen to be of greater significance in such moderator roles, comparative to process-driven I4.0 technologies. Our analysis suggests that companies may be advised to adopt a targeted, systems approach for using data-driven I4.0 applications in conjunction with CLSC practices in order to realise performance gains. The findings represent important building blocks in developing theory in this formative area of study. Further implications are discussed from theoretical and practical perspectives.Abbreviations: CE: Circular Economy; CLSC: Closed-Loop Supply Chain; CLSC_ADO: Closed-Loop Supply Chain activities adoption; I4.0: Industry 4.0; I4.0_ADO: Industry 4.0 technologies adoption; PERF: Company Performance; PLS-SEM: Partial least squares structural equation modelling; TBL: Triple Bottom Line (Financial, Environmental, Social)
Journal: International Journal of Production Research
Pages: 3003-3028
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2075291
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2075291
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# input file: TPRS_A_2077151_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jianbin Li
Author-X-Name-First: Jianbin
Author-X-Name-Last: Li
Author-Name: Fangying Hu
Author-X-Name-First: Fangying
Author-X-Name-Last: Hu
Author-Name: Tingting Yan
Author-X-Name-First: Tingting
Author-X-Name-Last: Yan
Author-Name: Xueyuan Cai
Author-X-Name-First: Xueyuan
Author-X-Name-Last: Cai
Author-Name: Xiangrong Song
Author-X-Name-First: Xiangrong
Author-X-Name-Last: Song
Title: How to charge doctors and price medicines in a two-sided online healthcare platform with network externalities?
Abstract: 
 Platform business models are upending the value proposition of the companies in traditional industries, such as healthcare, through competitively pricing value-added services and products. In this study, we consider a unique, but important, on-demand two-sided service platform: a monopolistic online healthcare platform, which not only provides medical services to patients by connecting them with doctors, but also sells medical products to patients. A crucial operational decision for the platform is to set up a pricing scheme to encourage enough doctors and patients to participate on the platform. We consider two common pricing schemes in this study: fixed and linear pricing, in an empirically-grounded optimisation model that considers medicine pricing decisions together with network externalities. Our results show that the fixed pricing scheme almost always dominates the linear pricing scheme by providing the platform with higher expected profit. Our results also reveal the strong interdependence between the optimal doctor service pricing decision and optimal medicine pricing decision. However, these decisions are often made independently by different functional units of a firm, which could cause suboptimal platform financial performance. These results indicate the importance of pricing products and services in an integrated manner for maximising the profit of a product/service platform.
Journal: International Journal of Production Research
Pages: 3051-3069
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2077151
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2077151
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# input file: TPRS_A_2073480_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Eric K.H. Leung
Author-X-Name-First: Eric K.H.
Author-X-Name-Last: Leung
Author-Name: Zhiyuan Ouyang
Author-X-Name-First: Zhiyuan
Author-X-Name-Last: Ouyang
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Community logistics: a dynamic strategy for facilitating immediate parcel delivery to smart lockers
Abstract: 
 The COVID Pandemic since early 2019 has imposed significant effects on our life. In the retail and logistics sector, the large-scale national lockdown has drastically driven e-commerce sales because the e-marketplace has become the only sales channel. Whilst the pandemic has accelerated the shift towards a more digital world and led to an irreversible dependence on e-commerce retailing, the pressure is on retailers and logistics service providers to respond to the growing demand for immediate delivery in the e-commerce era. Given the integration of smart lockers into developing a more favourable environment which potentially makes immediate delivery more feasible, this paper introduces a novel, dynamic delivery strategy, namely Community Logistics Strategy (CLS), for formulating and updating the new delivery plan in real time as new delivery requests to smart lockers arrive. To shed light on the effect of dynamic order arrival towards delivery planning, the CLS attempts to update the delivery plan by taking new requests into account in real time. Simulation results reveal the superiority of the proposed strategy in managing e-commerce delivery requests, especially within megacities where consumers are highly dense in a compact geographical area.
Journal: International Journal of Production Research
Pages: 2936-2961
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2073480
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2073480
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# input file: TPRS_A_2077670_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ryan O'Neil
Author-X-Name-First: Ryan
Author-X-Name-Last: O'Neil
Author-Name: Claver Diallo
Author-X-Name-First: Claver
Author-X-Name-Last: Diallo
Author-Name: Abdelhakim Khatab
Author-X-Name-First: Abdelhakim
Author-X-Name-Last: Khatab
Author-Name: El-Houssain Aghezzaf
Author-X-Name-First: El-Houssain
Author-X-Name-Last: Aghezzaf
Title: A hybrid column-generation and genetic algorithm approach for solving large-scale multimission selective maintenance problems in serial K-out-of-n:G systems
Abstract: 
 This paper introduces a solution method for the multimission selective maintenance problem (SMP) that combines column-generation (CG) and genetic algorithms (GAs). The multimission SMP is an optimisation problem that arises when a system performs a sequence of missions separated by breaks of finite duration. During these finite breaks, only a subset of possible maintenance actions can be performed due to resource limitations. The problem is in deciding what actions to perform during each break duration such that the system meets or exceeds a minimum target reliability for all missions. The resulting optimisation problems are usually modelled as mixed integer nonlinear mathematical programmes, which are hard to solve. They are usually solved using metaheuristics. We propose a solution method based on CG framework in which the subproblems are solved using a GA. By integrating the GA within the classical CG framework, high-quality solutions can be obtained very quickly. The proposed solution method is capable of solving systems composed of both parallel and k-out-of-n:G subsystems. This hybrid CG algorithm is shown to obtain near optimal solutions and outperform other metaheuristic solution methods; it is also shown to be capable of solving large-scale systems composed of many subsystems and hundreds of components in a reasonable amount of time.
Journal: International Journal of Production Research
Pages: 3070-3086
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2077670
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2077670
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# input file: TPRS_A_2077671_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Kaiping Luo
Author-X-Name-First: Kaiping
Author-X-Name-Last: Luo
Author-Name: Jianfei Sun
Author-X-Name-First: Jianfei
Author-X-Name-Last: Sun
Author-Name: Liuwei Guo
Author-X-Name-First: Liuwei
Author-X-Name-Last: Guo
Title: Network-based integer programming models for flexible process planning
Abstract: 
 Flexible process planning (FPP) involves selecting and sequencing the requisite operations according to technological requirements, and meanwhile allocating a right machine, a right tool and a right access direction to each selected operation by a given criterion. In this article, the FPP problem is exactly and concisely formulated as linear integer programming models based on the topology of the AND/OR-network under two criteria: production cost minimisation and completion time minimisation. Distinctively, more flexible manufacturing elements and process plan evaluation criteria are considered; more complicated tool and access direction changeover identifications are linearly expressed without the big-M parameter. Compared with the latest mathematical programming models for process planning, the proposed models have lower complexity and better performance. The results from numerous comparative experiments indicate that (i) the number of decision variables of the proposed models reduces approximately by 68% and the number of constraints of the proposed models dramatically reduces by 99%; (ii) within the same running time, the proposed models can exactly solve more benchmark cases than the latest models; and (iii) the solutions obtained by the proposed models are also better than the best ones founded by some state-of-the-art meta-heuristic algorithms.
Journal: International Journal of Production Research
Pages: 3087-3101
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2077671
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2077671
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# input file: TPRS_A_2070881_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jianguang Feng
Author-X-Name-First: Jianguang
Author-X-Name-Last: Feng
Author-Name: Ada Che
Author-X-Name-First: Ada
Author-X-Name-Last: Che
Title: A note on integrated disassembly line balancing and routing problem
Abstract: 
 This note comments on the study of [Diri Kenger, Zülal, Çağrı Koç, and Eren Özceylan. 2020. “Integrated Disassembly Line Balancing and Routing Problem.” International Journal of Production Research 58 (23): 7250–7268.] which studies an integrated disassembly line balancing and routing problem and develops two mixed integer linear programming (MILP) models and three mixed integer nonlinear programming (MINLP) models to handle five different scenarios, respectively. The purpose is twofold. First, we demonstrate that the two MILP models can be separated into two parallel subproblems whose optimal solutions can be combined to obtain the optimal solution of the original models. Second, we show that the three MINLP models can be linearised and propose two different linearisation techniques to reformulate them as equivalent MILP models. Computational results indicate that the linearised model outperforms the original nonlinear model in most cases.
Journal: International Journal of Production Research
Pages: 3144-3150
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2070881
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2070881
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# input file: TPRS_A_2070880_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hamidreza Arbabi
Author-X-Name-First: Hamidreza
Author-X-Name-Last: Arbabi
Author-Name: Ali Bozorgi-Amiri
Author-X-Name-First: Ali
Author-X-Name-Last: Bozorgi-Amiri
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: Integrated configuration design and capacity planning in a dynamic cloud manufacturing system
Abstract: 
 A cloud manufacturing (CMfg) system is presented as a novel service- and customer-oriented manufacturing paradigm that integrates the distributed manufacturing enterprises to share their manufacturing capabilities or resources and collaborate as an interconnected system in a dynamic environment. Since the high performance of this system depends on the formation of a suitable group of manufacturing service providers, this paper develops an integrated c onfiguration design and capacity planning problem for the CMfg system by considering the dynamic environment of this system. In this regard, dynamic service providers and dynamic demand are considered as two aspects of the dynamic nature of this system. A multi-period multi-objective mathematical model is proposed by maximising the utilities of all three stakeholders of the system. Moreover, three extensions of a discrete multi-objective grey wolf optimiser (DMOGWO) algorithm are devised to solve the medium- and large-scale instances. A comprehensive computational experiment is conducted to assess the performance of the developed meta-heuristic algorithms. Furthermore, by carrying out a sensitivity analysis, some managerial insight is suggested for the managers.
Journal: International Journal of Production Research
Pages: 2872-2893
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2070880
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2070880
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# input file: TPRS_A_2074323_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Alessia Napoleone
Author-X-Name-First: Alessia
Author-X-Name-Last: Napoleone
Author-Name: Elisa Negri
Author-X-Name-First: Elisa
Author-X-Name-Last: Negri
Author-Name: Marco Macchi
Author-X-Name-First: Marco
Author-X-Name-Last: Macchi
Author-Name: Alessandro Pozzetti
Author-X-Name-First: Alessandro
Author-X-Name-Last: Pozzetti
Title: How the technologies underlying cyber-physical systems support the reconfigurability capability in manufacturing: a literature review
Abstract: 
 Nowadays, manufacturing firms need the reconfigurability capability to be responsive in the current context characterised by unpredictable and frequent market changes and the reduction of product life cycle. Despite the relevance of the subject, a challenge for practitioners is the development of a strategy aimed to increase the level of reconfigurability with long-term goals of customisation and responsiveness. Moreover, traditional manufacturing paradigms are disrupted by the transformation of manufacturing systems in cyber-physical systems (CPS), thus introducing innovative means also to increase the level of reconfigurability in manufacturing systems. This study investigates how the technologies underlying CPS support the reconfigurability capability along system life cycle. Thus the technologies underlying CPS are classified into seven categories and it is shown how they enable the sequence of utilisation of the reconfigurability characteristics (modularity, integrability, diagnosability, scalability, convertibility and customisation) along the system life cycle. The results of the study can guide practitioners in developing reconfigurability as a strategic capability. Moreover, different directions for future research can be considered, as discussed in the conclusion.
Journal: International Journal of Production Research
Pages: 3121-3143
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2074323
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2074323
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# input file: TPRS_A_2070044_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Angie Nguyen
Author-X-Name-First: Angie
Author-X-Name-Last: Nguyen
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Author-Name: Samir Lamouri
Author-X-Name-First: Samir
Author-X-Name-Last: Lamouri
Author-Name: Béranger Lekens
Author-X-Name-First: Béranger
Author-X-Name-Last: Lekens
Title: Managing demand volatility of pharmaceutical products in times of disruption through news sentiment analysis
Abstract: 
 Unplanned events such as epidemic outbreaks, natural disasters, or major scandals are usually accompanied by supply chain disruption and highly volatile demand. Besides, authors have recently outlined the need for new applications of artificial intelligence to provide decision support in times of crisis. In particular, natural language processing allows for deriving an understanding from unstructured data in human languages, such as online news content, which can provide valuable information during disruptive events. This article contributes to this research strand as it aims to leverage textual data from news through sentiment analysis and predict demand volatility of pharmaceutical products in times of crisis. As a result, (1) a deep-learning-based sentiment analysis model was developed to extract and structure information from medicines-related news; (2) a framework allowing for combining extracted information from unstructured data with structured data of medicines demand was defined; and (3) an approach combining efficient artificial intelligence techniques with existing forecasting models was proposed to enhance demand forecasting in times of disruption. Additionally, the framework was applied to two examples of disruptive events in France: a pharmaceutical scandal and the COVID-19 pandemic. Findings outlined that using sentiment analysis allowed for enhancing demand forecasting accuracy.
Journal: International Journal of Production Research
Pages: 2828-2839
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2070044
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2070044
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# input file: TPRS_A_2074322_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: M. Ghasemi
Author-X-Name-First: M.
Author-X-Name-Last: Ghasemi
Author-Name: S. M. Mousavi
Author-X-Name-First: S. M.
Author-X-Name-Last: Mousavi
Author-Name: S. Aramesh
Author-X-Name-First: S.
Author-X-Name-Last: Aramesh
Author-Name: R. Shahabi-Shahmiri
Author-X-Name-First: R.
Author-X-Name-Last: Shahabi-Shahmiri
Author-Name: E. K. Zavadskas
Author-X-Name-First: E. K.
Author-X-Name-Last: Zavadskas
Author-Name: J. Antucheviciene
Author-X-Name-First: J.
Author-X-Name-Last: Antucheviciene
Title: A new approach for production project scheduling with time-cost-quality trade-off considering multi-mode resource-constraints under interval uncertainty
Abstract: 
 Due to today’s competitive environment and information boom, companies are concerned about production planning in uncertain conditions. This paper integrates decision-making method with production scheduling model by considering limited resources. In this paper, a new mathematical model is extended for production project scheduling with multiple execution modes. The main aim of the formulation is to plan and schedule real production projects in uncertain environments. A new mixed-integer linear formulation is presented by considering trade-off of cost, time, as well as quality. Cost–time-quality trade-off is extended with the interval information. In the presented model, activity quality could be enhanced by reworking. The interval forms of some parameters, including duration, quality of activities, cost, and total available resources, are obtained by determining weights of experts and aggregating them. The presented group decision-making method is based on a bi-directional projection measure to deal with interval information. Since the mathematical model is multi-objective and some data are interval, a new modified solution method is developed for solving the model. The presented method for both decision-making and mathematical models is investigated by a real-world production project and two datasets to ascertain the accuracy of the model. Finally, an appropriate sensitivity analysis is proposed.
Journal: International Journal of Production Research
Pages: 2962-2984
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2074322
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2074322
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# input file: TPRS_A_2074907_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hao Zhang
Author-X-Name-First: Hao
Author-X-Name-Last: Zhang
Author-Name: Shaowen Yao
Author-X-Name-First: Shaowen
Author-X-Name-Last: Yao
Author-Name: Qiang Liu
Author-X-Name-First: Qiang
Author-X-Name-Last: Liu
Author-Name: Lijun Wei
Author-X-Name-First: Lijun
Author-X-Name-Last: Wei
Author-Name: Libin Lin
Author-X-Name-First: Libin
Author-X-Name-Last: Lin
Author-Name: Jiewu Leng
Author-X-Name-First: Jiewu
Author-X-Name-Last: Leng
Title: An exact approach for the constrained two-dimensional guillotine cutting problem with defects
Abstract: 
 This paper studies the constrained two-dimensional guillotine cutting problem with defects, whose objective is to cut a subset of given items from a defective sheet such that the profit of selected items is maximised. The guillotine cut constraint, which requires each cut must go through one side of the sheet to the opposite side, is considered. We solve this problem via a recursive dynamic programming approach. A set of upper bounds is proposed to keep the promising nodes. The normal points and raster points are extended to reduce the number of vertical and horizontal cuts by considering the effect of the defect. The experiment results show that our approach can solve most of the instances in the literature and outperforms existing approaches.
Journal: International Journal of Production Research
Pages: 2985-3002
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2074907
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2074907
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# input file: TPRS_A_2073287_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Zhi Pei
Author-X-Name-First: Zhi
Author-X-Name-Last: Pei
Author-Name: Peiqi Yang
Author-X-Name-First: Peiqi
Author-X-Name-Last: Yang
Author-Name: Yujuan Wang
Author-X-Name-First: Yujuan
Author-X-Name-Last: Wang
Author-Name: Chao-Bo Yan
Author-X-Name-First: Chao-Bo
Author-X-Name-Last: Yan
Title: Energy consumption control in the two-machine Bernoulli serial production line with setup and idleness
Abstract: 
 In recent years, the topic of sustainable manufacturing system design with energy saving features has received increasing attention. For a typical production line setting, the machines are subject to random breakdown and restart besides blockage and starvation, and they are usually connected via buffer areas with finite capacity. In the present study, the energy consumption of the serial production line with two Bernoulli machines is considered, with an aim to minimise the total energy consumption under a desired production rate. The energy consumption of the two-machine system is composed of the energy needed to setup, to remain idle, and for actual manufacturing. In order to minimise the total energy expenditure, a nonlinear fractional polynomial optimisation model is constructed, which is first converted to a nonlinear polynomial optimisation problem. Then the property of the total energy cost is analysed via the sum of squares (SOS) method. To speed up the solving process, a new heuristic approach named energy consumption saving (ECS) algorithm is proposed considering the monotonicity and local optimality of the energy cost function. Finally, by presenting optimal configurations of the production line with different throughputs, buffer capacities, and energy parameters, a simulation-based study is performed to validate the SOS and ECS algorithms.
Journal: International Journal of Production Research
Pages: 2916-2935
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2073287
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2073287
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# input file: TPRS_A_2070045_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yadong Xu
Author-X-Name-First: Yadong
Author-X-Name-Last: Xu
Author-Name: Guowei Hua
Author-X-Name-First: Guowei
Author-X-Name-Last: Hua
Author-Name: T. C. E. Cheng
Author-X-Name-First: T. C. E.
Author-X-Name-Last: Cheng
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Yisong Li
Author-X-Name-First: Yisong
Author-X-Name-Last: Li
Author-Name: Shuai Liu
Author-X-Name-First: Shuai
Author-X-Name-Last: Liu
Title: Retailing and ordering strategies for online apparel retailers facing bracketing purchase behaviour
Abstract: 
 Consumer behaviour is changing in the e-commerce age for apparel products. More and more consumers tend to bracket, which means they purchase multiple versions of the same product to try at home and return those that do not meet their requirements. This bracketing behaviour can increase the likelihood that consumers buy the good-fit products. However, the tsunami of returns from bracketing has become challenging for online retailers. In this paper, we analytically address this issue by developing profit-maximising models for retailers facing bracketing customers. Our contribution is to explore whether and under what conditions should retailers encourage or discourage the bracketing purchase behaviour. Whether or not bracketing is profitable for retailers depends on the bracketer proportion and retailer’s reverse logistics cost. Further, we also find that while the profit is eroded because of the large number of returns, retailers should order more product to meet bracketers’ demand. In addition, we generate managerial insights from the findings that help online apparel retailers convert the seemingly harmful consumer returns from bracketing into an advantage.
Journal: International Journal of Production Research
Pages: 2840-2852
Issue: 9
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2070045
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2070045
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# input file: TPRS_A_2044531_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Kuen-Suan Chen
Author-X-Name-First: Kuen-Suan
Author-X-Name-Last: Chen
Author-Name: Yuan-Lung Lai
Author-X-Name-First: Yuan-Lung
Author-X-Name-Last: Lai
Author-Name: Ming-Chieh Huang
Author-X-Name-First: Ming-Chieh
Author-X-Name-Last: Huang
Author-Name: Tsang-Chuan Chang
Author-X-Name-First: Tsang-Chuan
Author-X-Name-Last: Chang
Title: Fuzzy judgement model for assessment of improvement effectiveness to performance of processing characteristics
Abstract: 
 Maintaining high levels of process quality is crucial to the competitiveness of manufacturing firms in today's increasingly global marketplace. To ensure the quality of manufactured products meets customer needs, process capability indices (PCIs) are widely used to analyze the process performance of various processing characteristics. Products characterise by processing characteristics of both unilateral and bilateral specifications are common in the current sales market. Manufacturing firms must often adopt multiple PCIs to analyze the process performance of a single product, which is inefficient in practical applications and management. Yield-based index 
 $ {C_{pk}} $ Cpk is not subject to this limitation. For this reason, we employed 
 $ {C_{pk}} $ Cpk to evaluate process performance and the effectiveness of improvement measures. In practice, 
 $ {C_{pk}} $ Cpk is estimated from samples, which means that misjudgment may occur in the assessment of process performance and improvement effectiveness due to sampling errors. We therefore derived the 
 $ 100({1 - \alpha } )\% $ 100(1−α)% confidence interval of 
 $ {C_{pk}} $ Cpk and, based on the producer's perspective, used the upper confidence limit to evaluate improvement effectiveness. To lower the risk of misjudgment and increase the reliability of improvement effectiveness in the case of data uncertainty, this paper further proposes fuzzy estimation using the right-sided confidence interval of 
 $ {C_{pk}} $ Cpk and develops the fuzzy judgement model.
Journal: International Journal of Production Research
Pages: 1591-1605
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2044531
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2044531
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# input file: TPRS_A_2037778_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Wei Guo
Author-X-Name-First: Wei
Author-X-Name-Last: Guo
Author-Name: Pingyu Jiang
Author-X-Name-First: Pingyu
Author-X-Name-Last: Jiang
Author-Name: Maolin Yang
Author-X-Name-First: Maolin
Author-X-Name-Last: Yang
Title: Unequal area facility layout problem-solving: a real case study on an air-conditioner production shop floor
Abstract: 
 Solving facility layout problems aims at identifying the optimal plan for placing a number of facilities or departments on a shop floor considering multiple optimisation criteria and constraints. Recently, the unequal area facility layout problem (UA-FLP) has drawn more attention as it is closer to real industrial scenarios. To address this problem, the typical UA-FLP in an air-conditioner production shop floor is analysed, and then a modified non-dominated sorting genetic algorithm (NSGA-II) is developed to identify the optimal layout plan considering the material handling cost (MHC) and the closeness rating score (CRS). NSGA-II is a stable algorithm for engineering applications and has an encoding structure of chromosomes that can express facility layout expediently. Besides that, the two objectives (MHC and CRS) that are conflicting might be another reason for adopting NSGA-II. During the process, the crossover and mutation operators of NSGA-II are modified based on the non-overlapping method, which reduces the time cost for eliminating unsuitable layout plans. The modified NSGA-II is compared with two related algorithms, and the results show that it has better performance on the UA-FLP with a large number of departments.
Journal: International Journal of Production Research
Pages: 1479-1496
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2037778
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2037778
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# input file: TPRS_A_2037777_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: D. G. Mogale
Author-X-Name-First: D. G.
Author-X-Name-Last: Mogale
Author-Name: Arijit De
Author-X-Name-First: Arijit
Author-X-Name-Last: De
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Designing a sustainable freight transportation network with cross-docks
Abstract: 
 This study aims to develop a sustainable freight transportation network considering capacitated cross-docks for minimising the overall supply chain costs, including carbon emission cost. The problem is inspired by a major retail company based in India, which would like to expand its product portfolio in the new region. A mathematical model is developed to minimise total costs encompassing transportation cost, pipeline and retailers inventory cost, fixed cost of cross-dock and carbon emission costs. The deterministic time dependant demand, multiple products and multiple sourcing and distribution are some of the challenges faced by the retail industry. A two-level self-adaptive variable neighbourhood search algorithm is applied to solve a computationally complex problem. The results based on a two-level self-adaptive variable neighbourhood search algorithm are compared with the variable neighbourhood search algorithm to test the robustness of the developed model. Results reveal that an increase in retailers over suppliers significantly influences the number of open cross-docks. A multiple-case scenario approach captures the implications of varying capacity on the number of open cross-docks; thus, supporting the freight distribution managers in making sustainability-driven decisions.
Journal: International Journal of Production Research
Pages: 1455-1478
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2037777
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2037777
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2023777_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lei Cai
Author-X-Name-First: Lei
Author-X-Name-Last: Cai
Author-Name: Wenfeng Li
Author-X-Name-First: Wenfeng
Author-X-Name-Last: Li
Author-Name: Yun Luo
Author-X-Name-First: Yun
Author-X-Name-Last: Luo
Author-Name: Lijun He
Author-X-Name-First: Lijun
Author-X-Name-Last: He
Title: Real-time scheduling simulation optimisation of job shop in a production-logistics collaborative environment
Abstract: 
 In a complex and dynamic job shop containing logistics factor, schedule needs to be generated rapidly, so the real-time scheduling method is more suitable for such scenario. Such method takes advantage of local information within a short time due to the rapid changes of information under uncertain environment. Therefore, how to make use of the future information by prediction while ensuring the robustness of schedule is a valuable problem. To solve it, firstly, a new real-time scheduling model and algorithm is proposed. There is a new kind of release moment of task information which can give AGVs the longest time to prepare for the task than existing research. Secondly, a real-time information update mechanism is designed to increase schedule’s robustness. Finally, a large-scale and dynamic job shop simulation experimental platform is developed. Dynamic factors include the random insertion of orders and failures of equipment. Results show that the method proposed outperforms existing research in terms of customer satisfaction, equipment utilisation and energy consumption. The robustness of schedule can also be acceptable. This paper also finds a rule that in job shop with the large proportion of logistics transportation time, the above method can achieve more competitive results.
Journal: International Journal of Production Research
Pages: 1373-1393
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2021.2023777
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2023777
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# input file: TPRS_A_2036852_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Arturo J. Fernández
Author-X-Name-First: Arturo J.
Author-X-Name-Last: Fernández
Title: Optimum lot inspection based on lognormal reliability tests
Abstract: 
 Improved lognormal reliability test plans are proposed for lot sentencing. A mixed integer nonlinear programming problem is stated and solved in order to find the duration of the reliability test based on lognormal failure count data that minimises the inspection effort. The maximum number of failures tolerated by the decision maker and the necessary number of devices to be tested are also determined. The producer and consumer risks are limited in advanced, whereas the cost function is essentially a linear combination of the required sample size and test time. The minimum-cost test for device reliability demonstration provides the best criterion to decide the acceptability of manufacturing processes and submitted lots. A quick and effective iterative algorithm is suggested to obtain the optimal reliability demonstration test plan. The developed methodology is applied to the production of microelectronic chips, semiconductor lasers and ball bearings for illustrative purposes.
Journal: International Journal of Production Research
Pages: 1424-1435
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2036852
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2036852
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2118892_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: The Industry 5.0 framework: viability-based integration of the resilience, sustainability, and human-centricity perspectives
Abstract: 
 Industry 5.0 is a combination of organisational principles and technologies to design and manage operations and supply chains as resilient, sustainable, and human-centric systems. While the general notion of Industry 5.0 has been elaborated, its implications for future operations and supply chains remain underexplored. This paper contributes to the conceptualisation of Industry 5.0 from the perspective of viability. We contextualise a framework of Industry 5.0 through the lens of the viable supply chain model, the reconfigurable supply chain, and human-centric ecosystems. Our study uncovers the major dimensions that characterise Industry 5.0 as a technological-organisational framework. First, the major technological principles of Industry 5.0 are collaboration, coordination, communication, automation, data analytics processing, and identification. Second, Industry 5.0 covers four areas: organisation, management, technology, and performance assessment. Third, Industry 5.0 spans three levels: society level, network level, and plant level. Last but not least, Industry 5.0 frames a new triple bottom line: resilient value creation, human well-being, and sustainable society. We provide a definition of Industry 5.0 and discuss its implications by elaborating on the understanding of value in Industry 5.0, which spans the dimensions of profit, people, and society. We also discuss open research areas.
Journal: International Journal of Production Research
Pages: 1683-1695
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2118892
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2118892
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# input file: TPRS_A_2044532_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Qiao Zhang
Author-X-Name-First: Qiao
Author-X-Name-Last: Zhang
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Author-Name: Jun Lin
Author-X-Name-First: Jun
Author-X-Name-Last: Lin
Title: Interaction between innovation choice and market-entry timing in a competitive fashion supply chain
Abstract: 
 We consider a duopoly in which a premium firm (Firm 1) competes with a regular firm (Firm 2). They launch a new fashion product, adopting one of two types of innovation, qualitative or non-qualitative, which offer different levels of market acceptance and uncertainty. We consider two groups of fashion consumers, snobs and conformists (defined by preference for exclusivity or conformity). We first examine the case in which the premium firm commits to entering the market first and chooses its type of innovation, and then the regular firm decides on market-entry timing and innovation type. The price game and the strategy interaction between the two firms are examined. We show that consumers' exclusivity and conformity positively impact the optimal decisions of the two firms when the initial market share of snobs is large. When the market-share loss due to late entry is sufficiently high, Firm 1 may prefer a non-qualitative innovation under certain identified conditions; otherwise, it always prefers a qualitative innovation. Firm 2 always benefits from Firm 1's choice of qualitative rather than non-qualitative innovation. We further discuss the strategy interaction when the premium firm commits to entering the market late.
Journal: International Journal of Production Research
Pages: 1606-1623
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2044532
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2044532
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# input file: TPRS_A_2039413_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Tarun Kumar Agrawal
Author-X-Name-First: Tarun Kumar
Author-X-Name-Last: Agrawal
Author-Name: Jannis Angelis
Author-X-Name-First: Jannis
Author-X-Name-Last: Angelis
Author-Name: Wajid Ali Khilji
Author-X-Name-First: Wajid Ali
Author-X-Name-Last: Khilji
Author-Name: Ravi Kalaiarasan
Author-X-Name-First: Ravi
Author-X-Name-Last: Kalaiarasan
Author-Name: Magnus Wiktorsson
Author-X-Name-First: Magnus
Author-X-Name-Last: Wiktorsson
Title: Demonstration of a blockchain-based framework using smart contracts for supply chain collaboration
Abstract: 
 Blockchain technologies can support traceability, transparency and trust among participants. This has primarily been explored in established supply chains and not in the growing use of business networks or ecosystems, which is a notable limitation since supply chains typically are organised with a dominant actor that ensures common information systems and standards that negate blockchain benefits. Hence, this study explores the design of a blockchain-based collaborative framework for resource sharing using smart contracts. These are particularly well-suited for supporting operations in broader networks or ecosystems beyond supply chains with established collaborations and hierarchies. Based on a systematic literature review, a demonstrator framework was developed for stakeholder interactions through a procurement and distribution unit backed with blockchain technology. The framework consists of (a) network architecture to demonstrate partner interactions; (b) rules for network working principles based on supply collaboration requirements; (c) UML diagram to define smart contract interaction sequence; and (d) algorithm for smart contract network verification and validation. Applicability of these smart contracts was verified by deployment on an Ethereum blockchain. The demonstrator framework ensures quality and data authenticity in supply networks, so it is useful for effective resource utilisation in networks where outsourcing and production surpluses are major issues.
Journal: International Journal of Production Research
Pages: 1497-1516
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2039413
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2039413
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# input file: TPRS_A_2023832_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bo Zhang
Author-X-Name-First: Bo
Author-X-Name-Last: Zhang
Author-Name: Meng Zhao
Author-X-Name-First: Meng
Author-X-Name-Last: Zhao
Author-Name: Xiangpei Hu
Author-X-Name-First: Xiangpei
Author-X-Name-Last: Hu
Title: Location planning of electric vehicle charging station with users’ preferences and waiting time: multi-objective bi-level programming model and HNSGA-II algorithm
Abstract: 
 Interactive users’ preferences and waiting time together have great impact on charging station network design of electric vehicles (EVs), but only waiting time was considered in previous studies. To fill this research gap, this paper addresses a location planning problem for EV charging stations, which considers users’ preferences and waiting time simultaneously. The problem is formulated as a multi-objective bi-level programming model, the upper level model determines locations and capacity options of charging stations with the objectives of minimising total cost and minimising total service tardiness, and the lower level model determines the allocation of users to stations with the objective of minimising total travel time. A hybrid non-dominated sorting genetic algorithm II (HNSGA-II) with embedded level determination algorithm (LDA) and a partial enumeration algorithm (PEA) are proposed, respectively, to solve the model. Furthermore, managerial analysis is implemented to verify the advantages of considering users’ preferences in reducing charging service tardiness and saving cost compared with the mode of no considering users’ preferences. And sensitivity analysis is also performed to provide managerial insights for EV charging station location practice. Finally, a real-world case study is conducted to verify the applicability of the proposed approach in solving practical location planning problems.
Journal: International Journal of Production Research
Pages: 1394-1423
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2021.2023832
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2023832
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# input file: TPRS_A_2037025_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Chen Zheng
Author-X-Name-First: Chen
Author-X-Name-Last: Zheng
Author-Name: Yushu An
Author-X-Name-First: Yushu
Author-X-Name-Last: An
Author-Name: Zhanxi Wang
Author-X-Name-First: Zhanxi
Author-X-Name-Last: Wang
Author-Name: Xiansheng Qin
Author-X-Name-First: Xiansheng
Author-X-Name-Last: Qin
Author-Name: Benoît Eynard
Author-X-Name-First: Benoît
Author-X-Name-Last: Eynard
Author-Name: Matthieu Bricogne
Author-X-Name-First: Matthieu
Author-X-Name-Last: Bricogne
Author-Name: Julien Le Duigou
Author-X-Name-First: Julien
Author-X-Name-Last: Le Duigou
Author-Name: Yicha Zhang
Author-X-Name-First: Yicha
Author-X-Name-Last: Zhang
Title: Knowledge-based engineering approach for defining robotic manufacturing system architectures
Abstract: 
 Robotic manufacturing systems have proven to be an effective solution for modern manufacturing enterprises to deal with increasing in customer demands and market competition. However, these systems may be unable to completely satisfy user requirements because of the difference between user and design perspectives. Thus, designing robotic manufacturing systems requires iterative processes that significantly increase development costs and lead time.A user-customised design approach is needed that enables users to customise robotic manufacturing systems as well as alleviate the burden on designers of eliciting user requirements. However, most users may not be able to customise their systems because of a lack of engineering knowledge. The authors propose a knowledge-based engineering approach to aid users in customising the architectures of robotic manufacturing systems. Two models — an ontological knowledge model and a multi-attribute decision-making model — are defined and integrated in the proposed KBE architecture definition method. A rule-based reasoning process is proposed in the ontological knowledge model based on explicit semantic descriptions of users’ unstructured or semi-structured requirements and the components of robotic manufacturing systems, which infers the possible architecture of the required system. The MADM model is adopted to evaluate the architecture alternatives to determine the optimal solution.
Journal: International Journal of Production Research
Pages: 1436-1454
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2037025
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2037025
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# input file: TPRS_A_2043566_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Shengnan Zhao
Author-X-Name-First: Shengnan
Author-X-Name-Last: Zhao
Author-Name: Ying Meng
Author-X-Name-First: Ying
Author-X-Name-Last: Meng
Author-Name: Lijie Su
Author-X-Name-First: Lijie
Author-X-Name-Last: Su
Author-Name: Jiyin Liu
Author-X-Name-First: Jiyin
Author-X-Name-Last: Liu
Author-Name: Lixin Tang
Author-X-Name-First: Lixin
Author-X-Name-Last: Tang
Title: Optimal plate design problem in steel production
Abstract: 
 In this paper, we address a new optimal plate design problem in steel production, in which slab selection is jointly considered. On the basis of the underlying features, the problem is formulated as a mixed integer nonlinear programming (MINLP) model with generalized disjunctive programming (GDP) constraints. A logic-based outer approximation (L-OA) algorithm is proposed to solve the problem. Specifically, a two-stage heuristic method is designed to initialise the L-OA algorithm. Numerical results are presented to demonstrate that the proposed L-OA algorithm and the heuristic method are effective and computationally efficient.
Journal: International Journal of Production Research
Pages: 1575-1590
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2043566
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2043566
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# input file: TPRS_A_2042415_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ziyan Feng
Author-X-Name-First: Ziyan
Author-X-Name-Last: Feng
Author-Name: Chengxuan Cao
Author-X-Name-First: Chengxuan
Author-X-Name-Last: Cao
Author-Name: Alireza Mostafizi
Author-X-Name-First: Alireza
Author-X-Name-Last: Mostafizi
Author-Name: Haizhong Wang
Author-X-Name-First: Haizhong
Author-X-Name-Last: Wang
Author-Name: Ximing Chang
Author-X-Name-First: Ximing
Author-X-Name-Last: Chang
Title: Uncertain demand based integrated optimisation for train timetabling and coupling on the high-speed rail network
Abstract: 
 Transportation is an important component in the logistics and production processes. To accurately match rapidly growing demand and limited transport capacity, the goal of minimising costs while ensuring high service quality under existing infrastructure has received significant attention. This paper presents an integrated optimisation approach for the short-term operational management under daily fluctuating demand, with a focus on two key strategic decisions: train timetabling and coupling. In particular, an integrated two-stage stochastic model and a combined heuristic local search algorithm with the branch-and-bound method are developed to (1) obtain the optimal demand assignment to the rail network, (2) investigate trains’ coupling plans to avoid waste of resources when demand is low, and (3) add candidate trains to generate new feasible timetables when demand surges. To verify the solving method, a lower bound algorithm is introduced. Using a hypothetical small-scale and a real-world China high-speed rail network as numerical experiments, different demand scales and critical parameters are tested to obtain optimised timetables. The results show that good solutions are achieved in several seconds, making it possible to adjust trains’ schedules efficiently and effectively according to the variable demand in short-term operational management.
Journal: International Journal of Production Research
Pages: 1532-1555
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2042415
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2042415
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# input file: TPRS_A_2044535_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xavier Brusset
Author-X-Name-First: Xavier
Author-X-Name-Last: Brusset
Author-Name: Aida Jebali
Author-X-Name-First: Aida
Author-X-Name-Last: Jebali
Author-Name: Davide La Torre
Author-X-Name-First: Davide
Author-X-Name-Last: La Torre
Title: Production optimisation in a pandemic context
Abstract: 
 A pandemic can wreak havoc in supply chains, as witnessed in the COVID-19 context. As workers get infected, production level drops and demand from customers goes unfulfilled. Combining in a novel way an epidemic model with optimal control theory, our model provides a plant manager with the optimal level of prophylactic effort she needs to deploy over a planning horizon to protect the workforce from a pandemic in its early stage and so maintain production levels. Given the production planning problem, the effort in terms of prophylactic measures can be optimally determined in closed form, balancing worker protection against production requirements in a single step. The manager must initially implement the strictest measures before relaxing them in time. Three extensions are presented:, (1) determine the optimal period of time over which the prophylactic measures should be maintained; (2) determine the optimal effort in terms of prophylactic measures in the case of an endemic disease; and (3) assess the effect of a stochastic exogenous shock on the total number of infected. This research provides a production planning model that allows a decision-maker to mitigate the impact of worker absenteeism at the onset of a pandemic, thus improving supply chain resilience.
Journal: International Journal of Production Research
Pages: 1642-1663
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2044535
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2044535
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# input file: TPRS_A_2042611_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yosuke Otsubo
Author-X-Name-First: Yosuke
Author-X-Name-Last: Otsubo
Author-Name: Naoya Otani
Author-X-Name-First: Naoya
Author-X-Name-Last: Otani
Author-Name: Megumi Chikasue
Author-X-Name-First: Megumi
Author-X-Name-Last: Chikasue
Author-Name: Mineyuki Nishino
Author-X-Name-First: Mineyuki
Author-X-Name-Last: Nishino
Author-Name: Masashi Sugiyama
Author-X-Name-First: Masashi
Author-X-Name-Last: Sugiyama
Title: Root cause estimation of faults in production processes: a novel approach inspired by approximate Bayesian computation
Abstract: 
 This paper presents a methodology for estimating root causes of faults in multistage mass production processes that have three properties: (1) only the final inspection data can be acquired, (2) hundreds of products are manufactured in a lot-wise manner, and (3) the acquired dataset does not always follow a Gaussian distribution. The proposed method consists of two components: (i) derive the distribution of part variables from the inspection dataset by fusing the approximate Bayesian computation (ABC) and the process model, and (ii) derive the root cause scores from the normal and abnormal datasets, which quantify how much each part contributes to the abnormal condition. The proposed method can estimate candidates of the fault causes, and numerical experiments are performed to explore the effectiveness and limitations of the method. Furthermore, the application to actual data of an internal camera module yields consistent results with design information given as domain knowledge.
Journal: International Journal of Production Research
Pages: 1556-1574
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2042611
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2042611
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# input file: TPRS_A_2039795_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Anthony Quenehen
Author-X-Name-First: Anthony
Author-X-Name-Last: Quenehen
Author-Name: Nathalie Klement
Author-X-Name-First: Nathalie
Author-X-Name-Last: Klement
Author-Name: Amine Mohamed Abdeljaouad
Author-X-Name-First: Amine Mohamed
Author-X-Name-Last: Abdeljaouad
Author-Name: Lionel Roucoules
Author-X-Name-First: Lionel
Author-X-Name-Last: Roucoules
Author-Name: Olivier Gibaru
Author-X-Name-First: Olivier
Author-X-Name-Last: Gibaru
Title: Economic and ergonomic performance enhancement in assembly process through multiple collaboration modes between human and robot
Abstract: 
 Collaborative robots have open new ways of designing assembly processes, thanks to their ability to share work space with operators. not only may they support the economical performance, but they can also improve the overall ergonomics. Building on existing work on task allocation problems, the authors study further the collaboration opportunities between operator and robot, namely cooperation phases (type of collaboration where both operator and robot act on the same work piece). This work proposes a new formulation of the related problem, and solutions are sought through heuristics methods, to investigate whether concurrent usage of different collaboration modes delivers better performance. The results indicate that cooperation mode enables higher process performances while controlling ergonomic risks. With a concern for real-life application, it has been applied on a real case study to verify its applicability.
Journal: International Journal of Production Research
Pages: 1517-1531
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2039795
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2039795
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# input file: TPRS_A_2044534_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jun Zheng
Author-X-Name-First: Jun
Author-X-Name-Last: Zheng
Author-Name: Jinkang Yao
Author-X-Name-First: Jinkang
Author-X-Name-Last: Yao
Author-Name: Yicheng Ren
Author-X-Name-First: Yicheng
Author-X-Name-Last: Ren
Author-Name: Junjie Shi
Author-X-Name-First: Junjie
Author-X-Name-Last: Shi
Author-Name: Feng Lin
Author-X-Name-First: Feng
Author-X-Name-Last: Lin
Author-Name: Wei Ling
Author-X-Name-First: Wei
Author-X-Name-Last: Ling
Author-Name: Tao Peng
Author-X-Name-First: Tao
Author-X-Name-Last: Peng
Author-Name: Wei Wang
Author-X-Name-First: Wei
Author-X-Name-Last: Wang
Title: An influence modelling and analysis method of reducing carbon emissions for mould forming processes in patternless sand casting
Abstract: 
 The foundry industry has gradually become an important concern for carbon emissions. The composite patternless casting, which combines sand mould 3D printing and sand mould milling technologies, is an effective way to explore the potential of energy saving and emission reduction in the foundry industry. However, the technical advantages of composite patternless casting in terms of energy saving and emission reduction have not been fully studied. To address this issue, this paper combines the composite patternless casting with the modular division method, and proposes a influence modelling and analysis method for carbon emissions and carbon efficiency ratio based on the process characteristics stage. The model and method are applied to the patternless casting process of a cylinder block. And the modular division schemes of the mould were proposed. The results show that through different modular division schemes, carbon emissions can be effectively reduced by 8.39%, the carbon efficiency ratio can be increased by up to 30%. This method is helpful to describe the carbon emission influence of the patternless casting forming process, and analyse the energy saving and emission reduction potential and carbon efficiency of the process.
Journal: International Journal of Production Research
Pages: 1624-1641
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2044534
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2044534
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# input file: TPRS_A_2044085_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Rasmus Andersen
Author-X-Name-First: Rasmus
Author-X-Name-Last: Andersen
Author-Name: Thomas Ditlev Brunoe
Author-X-Name-First: Thomas Ditlev
Author-X-Name-Last: Brunoe
Author-Name: Kjeld Nielsen
Author-X-Name-First: Kjeld
Author-X-Name-Last: Nielsen
Title: Platform-based product development in the process industry: a systematic literature review
Abstract: 
 Platform-based product development has been applied extensively in discrete manufacturing industry to accommodate changing market demands. Nevertheless, while process industry manufacturers face similar market demands, the topic is only sparsely covered in literature. Through a systematic review of the literature, this study uncovers the definitions used, drivers behind, approaches and methods applied, and industry examples of platform-based product development in the process industry. Based on these analyses, a research agenda is then proposed to further the knowledge of this topic. The study identified existing definitions of key platform-related terms used in several studies and furthermore discovered new definitions for some terms. The most prominent drivers behind pursuing platform-based product development was found to be cost reduction and productivity of product development, with development lead time reduction playing a less significant role. Literature related to platform-based product development focuses primarily on product design and development issues, with less attention given to market, manufacturing, and supply chain issues. Only few industrial cases were identified within the process industry while multiple anecdotal descriptions were discovered. For future research, further insight into key platform concepts, applicability of existing methods, broader value chain focus and detailed industrial cases are considered relevant.
Journal: International Journal of Production Research
Pages: 1696-1719
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2044085
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2044085
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# input file: TPRS_A_2044536_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Liyuan Sun
Author-X-Name-First: Liyuan
Author-X-Name-Last: Sun
Author-Name: Bintong Chen
Author-X-Name-First: Bintong
Author-X-Name-Last: Chen
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Author-Name: Hui Yang
Author-X-Name-First: Hui
Author-X-Name-Last: Yang
Title: When should a retailer with competing manufacturers reveal product fit information?
Abstract: 
 We investigate whether and when a retailer who sells two quality differentiated products supplied by two manufacturers should reveal product fit information to help consumers find a product that better fits their needs. We show that the retailer’s optimal information strategy depends on the consumer’s unit misfit cost and production efficiencies of both manufacturers. The retailer should reveal product fit information when the ratio of the efficiencies of the two manufacturers is sufficiently low, or the consumer’s unit misfit cost is sufficiently high. The retailer is less likely to benefit from revealing product fit information when the consumer’s unit misfit cost is either low or very high. Two mechanisms, margin-enhancing (driving the efficient manufacturer to reduce the wholesale price) and market-targeting (setting higher retail prices for both products), that the retailer can benefit from revealing product fit information are discussed, and the associated conditions are identified. Our findings suggest that the inefficient manufacturer is always better off when the retailer reveals fit information, but the efficient manufacturer may suffer. A win-win-win for all supply chain members can be achieved under certain conditions.
Journal: International Journal of Production Research
Pages: 1664-1682
Issue: 5
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2044536
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2044536
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# input file: TPRS_A_2049909_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hajar Hilali
Author-X-Name-First: Hajar
Author-X-Name-Last: Hilali
Author-Name: Vincent Hovelaque
Author-X-Name-First: Vincent
Author-X-Name-Last: Hovelaque
Author-Name: Vincent Giard
Author-X-Name-First: Vincent
Author-X-Name-Last: Giard
Title: Integrated scheduling of a multi-site mining supply chain with blending, alternative routings and co-production
Abstract: 
 This paper proposes a multi-site global optimisation model of blending operations, alternative routings and order scheduling with a co-production flow. It is performed in a phosphoric supply chain owning three open-pit mines of different geological structures and chemical compositions, each having a dry blending plant. One main challenge of the phosphate industries is to produce merchantable ores (MO) that verify a quality charter (chemical composition) with chemical heterogeneous source ores (SO). Thus, a process of SO blending followed by a treatment is mostly necessary to obtain the required MO. Six alternative routings exist to produce an MO; one of them involving a calcination plant generates a co-product. The model objective is to determine the least costly production programme of a set of MO orders to be delivered within precise time windows, in given quantities and compliance with a specific quality charter, by assigning for each MO its blending plant, routing, blend of SOs and production schedule; it also defines the feeding of the blending plants. A real case study illustrates the proposed model.
Journal: International Journal of Production Research
Pages: 1829-1848
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2049909
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2049909
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# input file: TPRS_A_2045377_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Sohrab Faramarzi-Oghani
Author-X-Name-First: Sohrab
Author-X-Name-Last: Faramarzi-Oghani
Author-Name: Parisa Dolati Neghabadi
Author-X-Name-First: Parisa
Author-X-Name-Last: Dolati Neghabadi
Author-Name: El-Ghazali Talbi
Author-X-Name-First: El-Ghazali
Author-X-Name-Last: Talbi
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: Meta-heuristics for sustainable supply chain management: a review
Abstract: 
 Due to the complexity and the magnitude of optimisation models that appeared in sustainable supply chain management (SSCM), the use of meta-heuristic algorithms as competent solution approaches is being increased in recent years. Although a massive number of publications exist around SSCM, no extant paper explicitly investigates the role of meta-heuristics in the sustainable (forward) supply chain. To fill this gap, a literature review is provided on meta-heuristic algorithms applied in SSCM by analyzing 160 rigorously selected papers published by the end of 2020. Our statistical analysis ascertains a considerable growth in the number of papers in recent years and reveals the contribution of 50 journals in forming the extant literature. The results also show that in the current literature the use of hybrid meta-heuristics is overtaking pure meta-heuristics, the genetic algorithm (GA) and the non-dominated sorting GA (NSGA-II) are the most-used single- and multi-objective algorithms, the aspects of sustainability are mostly addressed in connection with product distribution and routing of vehicles as pivotal operations in supply chain management, and last but not least, the economic-environmental category of sustainability has been further noticed by the scholars. Finally, a detailed discussion of findings and recommendations for future research are provided.
Journal: International Journal of Production Research
Pages: 1979-2009
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2045377
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2045377
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# input file: TPRS_A_2050827_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Shan Wang
Author-X-Name-First: Shan
Author-X-Name-Last: Wang
Author-Name: Huiqiao Su
Author-X-Name-First: Huiqiao
Author-X-Name-Last: Su
Author-Name: Guohua Wan
Author-X-Name-First: Guohua
Author-X-Name-Last: Wan
Author-Name: Liwei Zhong
Author-X-Name-First: Liwei
Author-X-Name-Last: Zhong
Title: Surgery scheduling in the presence of operating room eligibility and dedicated surgeon: an adaptive composite dispatching method
Abstract: 
 Motivated by a real problem in a big hospital in China, we study a daily surgery scheduling problem with operating room eligibility and dedicated surgeon. We model the problem as a parallel machine scheduling problem with machine and resource constraints to minimise the makespan, and innovatively propose an adaptive composite dispatching method to deal with such a strongly NP-hard problem. The dispatching rule is a combination of three popular rules LPT, LFJ and LRW, each of which can deal with some special features of the scheduling problems, and the scaling parameters are estimated through a statistical model learned from historical data. The adaptive composite dispatching method is easy-to-implement, fast, adaptable, robust and flexible. To examine the performance of the proposed solution approach, we first carry out a series of computational experiments showing that the adaptive composite dispatching method works very well compared to the optimal solution. Using a real data set, we further conduct a case study showing that our solution approach can improve the current practice by significantly shortening the makespan and reducing the overnight work.
Journal: International Journal of Production Research
Pages: 1866-1881
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2050827
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2050827
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# input file: TPRS_A_2047239_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bo Li
Author-X-Name-First: Bo
Author-X-Name-Last: Li
Author-Name: Antonio Arreola-Risa
Author-X-Name-First: Antonio
Author-X-Name-Last: Arreola-Risa
Title: Managing a bone marrow transplant centre to maximise patients' health benefits
Abstract: 
 We study a Bone Marrow Transplant (BMT) Centre whose objective is to maximise the expected health benefits of the admitted patients. The arrival of patients is a renewal process with generally distributed inter-arrival times, and the length of stay in a transplant room is a generally distributed random variable. Arriving patients are immediately admitted into a transplant room if available; otherwise, they would be added to a finite waiting list called patient reserve. When a transplant room becomes available, a member of the patient reserve is selected for admission. Patients who arrive when all transplant rooms are occupied and the patient reserve is full are referred to other BMT Centres. Because the patient reserve members' health will continue to deteriorate while waiting for a transplant room, our research results illustrate the optimal trade-offs among the number of transplant rooms, the number of spots in the patient reserve, and the expected health benefits of the admitted patients. Our experience with a leading BMT Centre supports the notion that an understanding of these optimal trade-offs is crucial for managers of BMT Centres.
Journal: International Journal of Production Research
Pages: 1771-1795
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2047239
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2047239
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# input file: TPRS_A_2056540_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lotte van Hezewijk
Author-X-Name-First: Lotte
Author-X-Name-Last: van Hezewijk
Author-Name: Nico Dellaert
Author-X-Name-First: Nico
Author-X-Name-Last: Dellaert
Author-Name: Tom Van Woensel
Author-X-Name-First: Tom
Author-X-Name-Last: Van Woensel
Author-Name: Noud Gademann
Author-X-Name-First: Noud
Author-X-Name-Last: Gademann
Title: Using the proximal policy optimisation algorithm for solving the stochastic capacitated lot sizing problem
Abstract: 
 This paper studies the multi-item stochastic capacitated lot-sizing problem with stationary demand to minimise set-up, holding, and backorder costs. This is a common problem in the industry, concerning both inventory management and production planning. We study the applicability of the Proximal Policy Optimisation (PPO) algorithm in this problem, which is a type of Deep Reinforcement Learning (DRL). The problem is modelled as a Markov Decision Process (MDP), which can be solved to optimality in small problem instances by using Dynamic Programming. In these settings, we show that the performance of PPO approaches the optimal solution. For larger problem instances with an increasing number of products, solving to optimality is intractable, and we demonstrate that the PPO solution outperforms the benchmark solution. Several adjustments to the standard PPO algorithm are implemented to make it more scalable to larger problem instances. We show the linear growth in computation time for the algorithm, and present a method for explaining the outcomes of the algorithm. We suggest future research directions that could improve the scalability and explainability of the PPO algorithm.
Journal: International Journal of Production Research
Pages: 1955-1978
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2056540
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2056540
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# input file: TPRS_A_2049910_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Fanbing Meng
Author-X-Name-First: Fanbing
Author-X-Name-Last: Meng
Author-Name: Jun Yang
Author-X-Name-First: Jun
Author-X-Name-Last: Yang
Author-Name: Qi Li
Author-X-Name-First: Qi
Author-X-Name-Last: Li
Title: Process quality recheck for Gamma quality characteristic from supplier products: a case study on radio-frequency power
Abstract: 
 Quality fraud seriously damages the right-to-known of customers. Therefore, it is necessary for customers to recheck the process quality level declared by suppliers, which is often measured by process capability indices (PCIs). However, there exist two practical problems when rechecking PCIs based on a quality characteristic (QC). First, QC data often do not follow normal distributions. Second, to enhance the market competitiveness, the supplier usually conducts a full inspection and eliminates the non-conforming items before selling them, which causes the QC data to be truncated. To overcome these problems, motivated by the radio-frequency (RF) power output data, this paper proposes a two-phase process capability recheck method, including data-filling and generalised p-value (GE-P) test. The novel data-filling method integrates the quantile-filling (QA) and bias-correction closed-form (BC) estimator for Gamma distributions, and simulation results show it performs better than the traditional methods on unbiasedness and consistency. Based on the filling pseudo-complete data, GE-P is adopted to complete the recheck by testing whether the process capability reaches the supplier declared level. Numerical analysis indicates it performs well on two types of errors. Finally, a real case study on the motivating example is presented to verify the effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 1849-1865
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2049910
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2049910
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# input file: TPRS_A_2048114_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Maximiliano Udenio
Author-X-Name-First: Maximiliano
Author-X-Name-Last: Udenio
Author-Name: Eleni Vatamidou
Author-X-Name-First: Eleni
Author-X-Name-Last: Vatamidou
Author-Name: Jan C. Fransoo
Author-X-Name-First: Jan C.
Author-X-Name-Last: Fransoo
Title: Exponential smoothing forecasts: taming the bullwhip effect when demand is seasonal
Abstract: 
 In this paper, we study the influence of seasonal demands and forecasts on the performance of an Automatic Pipeline, Variable Inventory, Order-Based, Production Control System (APVIOBPCS) using linear control theory. In particular, we consider a system that uses a seasonal forecast based on a no-trend, additive-seasonality exponential-smoothing model, and compare its performance to an equivalent system using simple exponential smoothing. We find that the system with seasonal forecasting significantly outperforms the system with simple exponential smoothing under certain demand assumptions. With optimal parameter settings, the forecast error of the seasonal model can be up to 40% lower. However, we also find that the forecast superiority does not necessarily translate to the performance of the system measured through the bullwhip metrics. In addition, the seasonal forecasting model is very sensitive to the demand frequency and smoothing parameters, while the simple exponential smoothing model is very robust. This implies that the real life benefits of implementing a seasonal forecasting model are not obvious and depend on the particular situation; under a large number of settings (e.g. low seasonality, high-smoothing), the good performance of simple exponential smoothing certainly justifies its popularity in the industry and research worlds alike.
Journal: International Journal of Production Research
Pages: 1796-1813
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2048114
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2048114
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# input file: TPRS_A_2049911_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jun Pei
Author-X-Name-First: Jun
Author-X-Name-Last: Pei
Author-Name: Ya Zhou
Author-X-Name-First: Ya
Author-X-Name-Last: Zhou
Author-Name: Ping Yan
Author-X-Name-First: Ping
Author-X-Name-Last: Yan
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Title: A concise guide to scheduling with learning and deteriorating effects
Abstract: 
 In practical manufacturing systems, the job processing time usually varies with the performance change of manufacturing resources, among which the learning and deteriorating effects are typical characteristics. Due to the interests from both academic exploration and industrial innovation, the research on scheduling problems with these effects is abundant and diverse. However, some studied problems need to be strengthened in combination with realistic production scenarios. This paper provides a concise guide to scheduling problems with these effects, giving a comprehensive review and critical hints for future research. A novel classification scheme is designed based on four levels of different domains, i.e. effects, processing ways, processing time functions, and manufacturing environments. Based on this scheme, the scheduling problems are first distinguished into three categories: learning effects, deteriorating effects, and combined effects. In each category, models are then refined along three lines: general processing way, batch scheduling, and group scheduling. Combined with the attributes of actual processing time functions and manufacturing environments, the evolvement of related scheduling models and a critical analysis on the proposed algorithms are well analysed. Afterwards, the research gaps are revealed and the research directions are indicated from the perspectives of practical applications, time functions, and designed algorithms.
Journal: International Journal of Production Research
Pages: 2010-2031
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2049911
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2049911
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# input file: TPRS_A_2053223_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Sarah Vanheusden
Author-X-Name-First: Sarah
Author-X-Name-Last: Vanheusden
Author-Name: Teun van Gils
Author-X-Name-First: Teun
Author-X-Name-Last: van Gils
Author-Name: Katrien Ramaekers
Author-X-Name-First: Katrien
Author-X-Name-Last: Ramaekers
Author-Name: Trijntje Cornelissens
Author-X-Name-First: Trijntje
Author-X-Name-Last: Cornelissens
Author-Name: An Caris
Author-X-Name-First: An
Author-X-Name-Last: Caris
Title: Practical factors in order picking planning: state-of-the-art classification and review
Abstract: 
 Market trends such as globalisation, increasing customer expectations, expensive industrial land and high labour costs cause a need for efficient order picking systems in practice. However, managers often do not implement findings from academic research on order picking planning into practice because researchers hardly account for practical factors (e.g. high-level storage, human factors, pick vehicle properties) or make unrealistic assumptions in their solution algorithms. A state-of-the-art review of the scientific literature on order picking planning (1) identifies and classifies highly influential practical factors, (2) shows the impact of these practical factors on order picking performance, and (3) illustrates how existing order picking planning models should be elaborated to account for practical factors. This study contributes to close the gap between research and practice by guiding future researchers to further increase the practical applicability of their research results.
Journal: International Journal of Production Research
Pages: 2032-2056
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2053223
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2053223
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# input file: TPRS_A_2045378_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Nanyan Shen
Author-X-Name-First: Nanyan
Author-X-Name-Last: Shen
Author-Name: Yang Wu
Author-X-Name-First: Yang
Author-X-Name-Last: Wu
Author-Name: Jing Li
Author-X-Name-First: Jing
Author-X-Name-Last: Li
Author-Name: Tianqiang He
Author-X-Name-First: Tianqiang
Author-X-Name-Last: He
Author-Name: Yushun Lu
Author-X-Name-First: Yushun
Author-X-Name-Last: Lu
Author-Name: Yingjie Xu
Author-X-Name-First: Yingjie
Author-X-Name-Last: Xu
Title: Research on procedure optimisation for composite grinding based on Digital Twin technology
Abstract: 
 The complexity of composite grinding movement, the variety of machining features and available grinding wheels, and the changing working conditions pose a challenge to the rapid programming of safe and efficient composite grinding procedure. The procedure optimisation plays an important role in solving this difficult problem. Therefore, a procedure optimisation method is proposed for composite grinding based on a Digital Twin (DT) system, which takes procedure time as optimisation objective to achieve high efficiency and ensures process rationality and safety by constructing corresponding constraint conditions. Moreover, the actual working conditions mapped into the DT system, such as workpiece parameters, machining requirements, grinding wheel parameters and status, machine tool motion position, and so on, are obtained to update the parameters involved in the optimisation model. And thus, the proposed method has the ability to timely find the optimal procedure under changing working conditions. In addition, a combination algorithm based on genetic algorithm (GA) and dynamic programming is proposed, which greatly reduces the search space of GA and realises the two-class co-optimisation of grinding wheel selection and procedure. Finally, the case study verifies the effectiveness of the proposed method to reduce procedure time and the dynamic response ability to changing working conditions.
Journal: International Journal of Production Research
Pages: 1736-1754
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2045378
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2045378
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# input file: TPRS_A_2045376_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Shuzhen Chen
Author-X-Name-First: Shuzhen
Author-X-Name-Last: Chen
Author-Name: Yuchen Pan
Author-X-Name-First: Yuchen
Author-X-Name-Last: Pan
Author-Name: Desheng Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Wu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: In-house versus outsourcing collection in a closed-loop supply chain with remanufacturing technology development
Abstract: 
 This paper develops a game model of a closed-loop supply chain consisting of one manufacturer, one remanufacturer and one retailer and investigates the long-term collection strategies of the manufacturer who needs to cooperate with the remanufacturer to develop the remanufacturing technology. The game model is developed from a fully dynamic perspective on the remanufacturing technology development and analyzed using the system dynamics method. We identify the trade-off in the choice of collection strategies: the early entry in the remanufacturing industry versus the complete control in the later stage. The simulation results show that when the entry barrier to the remanufacturing industry is low, the manufacturer can develop the remanufacturing technology in a short time and the direct reverse channel outperforms the indirect reverse channel; when the entry barrier is high, the manufacturer can achieve more profits under the indirect reverse channel by acquiring the remanufacturing technology directly from the remanufacturer. Moreover, the indirect reverse channel is more likely to be superior for low-barrier remanufacturing industry when the cost advantage is high as the early entry in the remanufacturing industry becomes more important than the complete control in the later stage.
Journal: International Journal of Production Research
Pages: 1720-1735
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2045376
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2045376
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# input file: TPRS_A_2054744_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Zhe Zhang
Author-X-Name-First: Zhe
Author-X-Name-Last: Zhang
Author-Name: Xiaoling Song
Author-X-Name-First: Xiaoling
Author-X-Name-Last: Song
Author-Name: Xue Gong
Author-X-Name-First: Xue
Author-X-Name-Last: Gong
Author-Name: Yong Yin
Author-X-Name-First: Yong
Author-X-Name-Last: Yin
Author-Name: Benjamin Lev
Author-X-Name-First: Benjamin
Author-X-Name-Last: Lev
Author-Name: Xiaoyang Zhou
Author-X-Name-First: Xiaoyang
Author-X-Name-Last: Zhou
Title: An effective heuristic based on 3-opt strategy for seru scheduling problems with learning effect
Abstract: 
 This paper is concerned with the scheduling problem in a new-type seru production system by consideration of DeJong's learning effect to minimise the total weighted completion time, so as to achieve efficiency, flexibility, and fast responsiveness to cope with the current volatile market. A combinatorial optimisation model is constructed and then reformulated to a binary quadratic assignment program. Accordingly, after presenting the necessary and sufficient condition for the locally optimal solution, a tabu search with strategic oscillation based on 3-opt as a diversification strategy is designed as the solution approach. A set of test problems are generated, and computational experiments with large-scale cases are made finally. The results indicate that the proposed heuristic algorithm is promising in solving seru scheduling problems and has a good performance in term of solution quality, efficiency, and scalability.
Journal: International Journal of Production Research
Pages: 1938-1954
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2054744
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2054744
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# input file: TPRS_A_2051090_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Kerstin Maier
Author-X-Name-First: Kerstin
Author-X-Name-Last: Maier
Author-Name: Veronika Taferner
Author-X-Name-First: Veronika
Author-X-Name-Last: Taferner
Title: Solving the constrained Single-Row Facility Layout Problem with Integer Linear Programming
Abstract: 
 The Single-Row Facility Layout Problem (SRFLP) is one of the most studied facility layout problems in the literature. It asks for an optimal arrangement of departments with given lengths on a row such that the weighted sum of all centre-to-centre distances between department pairs is minimised. Real-world facility layouts may require taking different restrictions on the placement of departments into account, such as arrangement on a fixed position, pairwise placement, or precedence considerations. Therefore, we consider the constrained Single-Row Facility Layout Problem (cSRFLP) that additionally considers positioning, ordering, and relation constraints on single-row facility layouts. In this work, we suggest a new Integer Linear Programming (ILP) formulation for the cSRFLP, which outperforms the best available exact approach in literature. In an extensive computational study, we apply our ILP approach as well as an LP-based cutting plane algorithm on SRFLP and cSRFLP instances from the literature. We provide optimal cSRFLP layouts as well as strong lower bounds for instances with up to 42 departments. Further, we present new results for SRFLP instances from the literature. Additionally, we demonstrate the individual impact of the constraint sets on the run times of cSRFLP instances to emphasise further research on this rarely studied practice-oriented Facility Layout Problem.
Journal: International Journal of Production Research
Pages: 1882-1897
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2051090
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2051090
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# input file: TPRS_A_2051091_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bin Shen
Author-X-Name-First: Bin
Author-X-Name-Last: Shen
Author-Name: Yuan Xin
Author-X-Name-First: Yuan
Author-X-Name-Last: Xin
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Kejing Zhang
Author-X-Name-First: Kejing
Author-X-Name-Last: Zhang
Title: Integration strategies of luxury rental operations: is it wise to operate with the manufacturer or co-operate with the competitor?
Abstract: 
 Luxury rental operations are increasingly popular nowadays. In this study, we develop game-theoretical models to examine the optimal renter’s integration strategies (RISs) in a luxury supply chain with conspicuous consumers. The luxury supply chain consists of one manufacturer, one seller and one renter. Based on observed industrial practices, we compare three RISs, namely non-integration (the renter works on his own), vertical integration (the renter operates with the manufacturer) and horizontal integration (the renter co-operates with the seller). The main findings are as follows. First, integration is not always a wise strategy for the renter. When the proportion of conspicuous consumers (PCC) is sufficiently high, the renter should work on his own. When the PCC is lower than a threshold, the optimal RIS depends on the trade-off between the double-marginalisation and retail competition effects. Second, we evaluate the environmental impacts of RISs and uncover that the environmental effects depend on the product types’ environmental impact. We further identify the conditions how a dominating situation with respect to profitability and environmental impact can be achieved (called ‘PE dominating’). Third, we investigate the effects of consumer segmentation on the optimal RIS. Managerial implications are discussed.
Journal: International Journal of Production Research
Pages: 1898-1912
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2051091
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2051091
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# input file: TPRS_A_2048115_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme Luz
Author-X-Name-Last: Tortorella
Author-Name: Flavio Sanson Fogliatto
Author-X-Name-First: Flavio Sanson
Author-X-Name-Last: Fogliatto
Author-Name: Diego Tlapa Mendoza
Author-X-Name-First: Diego
Author-X-Name-Last: Tlapa Mendoza
Author-Name: Matthew Pepper
Author-X-Name-First: Matthew
Author-X-Name-Last: Pepper
Author-Name: Daniel Capurro
Author-X-Name-First: Daniel
Author-X-Name-Last: Capurro
Title: Digital transformation of health services: a value stream-oriented approach
Abstract: 
 Health organisations have adopted technologies since the 1960s, but only after the Industry 4.0 were such technologies systematized and organised under the H4.0 acronym. The pace at which digital information and communication applications have been developed in recent years challenge healthcare managers to choose assertively those with the largest potential impacts on their operations. In this paper, we propose using value stream mapping, a technique from the lean healthcare (LH) toolbox, to guide the choice of H4.0 digital applications that are more likely to support the improvement of value flows in healthcare organisations. We propose a three-step method, starting with mapping current and future value streams of the process under analysis, gathering data from team members on the indicated kaizen bursts and H4.0 digital applications, and finally assessing and ranking H4.0 digital applications that best support improvements and comply with attributes that characterise successful technological innovations. Our propositions are illustrated through a case study conducted in the sterilisation unit of a large public university hospital. Our findings indicate that three H4.0 digital applications should be prioritised to support the improvement of the value stream under analysis. Our method combines the simplicity of LH with more sophisticated solutions brought by H4.0.
Journal: International Journal of Production Research
Pages: 1814-1828
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2048115
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2048115
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# input file: TPRS_A_2053224_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Roberto Rosario Corsini
Author-X-Name-First: Roberto Rosario
Author-X-Name-Last: Corsini
Author-Name: Antonio Costa
Author-X-Name-First: Antonio
Author-X-Name-Last: Costa
Author-Name: Salvatore Cannella
Author-X-Name-First: Salvatore
Author-X-Name-Last: Cannella
Author-Name: Jose M. Framinan
Author-X-Name-First: Jose M.
Author-X-Name-Last: Framinan
Title: Analysing the impact of production control policies on the dynamics of a two-product supply chain with capacity constraints
Abstract: 
 In this paper, we investigate the impact in terms of Fill Rate of production control policies in a two-product, two-echelon supply chain dynamic problem with production capacity. The factory node is subject to two different disruptive occurrences (i.e. failure events and changeovers) that can cause unforeseen problems in the supply chain. To control these adverse events, the factory can adopt different production control policies. We compare the well-known Hedging Corridor Policy with two variants, namely Modified Hedging Corridor Policy and Improved Modified Hedging Corridor Policy, and Demand-Driven Material Requirements Planning policy. Firstly, we use the Response Surface Methodology to calibrate the endogenous factors for each strategy. Then, through an extended full-factorial Design Of Experiments, we evaluate the effectiveness of the production control policies for several operational and market scenarios defined by varying exogenous factors. Interestingly, our study reveals that the Hedging Corridor Policy represents the best rule to increase the Fill Rate. The policies have been compared also in terms of indicators related to the factory inventory level. The results seem to point out that efficient production control policies (measured in terms of operational efficiency) do not necessarily yield the best results when measured in terms of supply chain efficiency.
Journal: International Journal of Production Research
Pages: 1913-1937
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2053224
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2053224
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# input file: TPRS_A_2047238_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ying-Ying Huang
Author-X-Name-First: Ying-Ying
Author-X-Name-Last: Huang
Author-Name: Quan-Ke Pan
Author-X-Name-First: Quan-Ke
Author-X-Name-Last: Pan
Author-Name: Liang Gao
Author-X-Name-First: Liang
Author-X-Name-Last: Gao
Title: An effective memetic algorithm for the distributed flowshop scheduling problem with an assemble machine
Abstract: 
 The distributed flowshop has been a hot topic in research in recent years. This paper considers a distributed permutation flowshop scheduling problem with an assemble machine, so-called the distributed assembly permutation flowshop scheduling problem (DAPFSP), with total tardiness criterion. We propose an effective memetic algorithm (EMA). Firstly, a constructive heuristic combining the well-known earliest due date rule and largest processing time rule is presented for producing a seed sequence. On this basis, an effective initialisation method is used to generate an initial population with a high level of quality and diversity. The EMA uses a new structure of a small iteration nested within a large iteration. Moreover, an improved crossover and mutation expand the solution space in a good direction. According to different operation situations and objects, we design four targeted and flexible local search methods. We evaluate the strategies of the EMA, compare and analyse it with seven efficient algorithms based on the 810 benchmark instances. The experimental results confirm the effectiveness and efficiency of the proposed EMA.
Journal: International Journal of Production Research
Pages: 1755-1770
Issue: 6
Volume: 61
Year: 2023
Month: 03
X-DOI: 10.1080/00207543.2022.2047238
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2047238
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# input file: TPRS_A_2065551_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Alessandro Agnetis
Author-X-Name-First: Alessandro
Author-X-Name-Last: Agnetis
Author-Name: Marco Pranzo
Author-X-Name-First: Marco
Author-X-Name-Last: Pranzo
Title: Sequencing two classes of jobs on a machine with an external no-idle constraint
Abstract: 
 In this paper, we deal with a special type of scheduling problem. There are two classes of jobs to be processed on a single machine. Jobs of class A are directly delivered to the customers and we want to minimise their total flow time. Jobs of class B do not contribute to the objective function but must respect a no-idle constraint (i.e. they are required to keep an external downstream machine busy). This problem arises in some real-world production environments where the downstream process must not be interrupted because of technological constraints, economic viability or because the firm is bound to keep the external process continuously active (e.g. a contract with a downstream firm imposing penalties if the supply is interrupted). We prove that the general problem is NP-Hard. We introduce two mathematical programming-based approaches and some constructive heuristics. The various approaches are compared on the basis of a large computational campaign.
Journal: International Journal of Production Research
Pages: 2178-2189
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2065551
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2065551
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# input file: TPRS_A_2062580_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bilge Torbali
Author-X-Name-First: Bilge
Author-X-Name-Last: Torbali
Author-Name: Gülgün Alpan
Author-X-Name-First: Gülgün
Author-X-Name-Last: Alpan
Title: A literature review on robust and real-time models for cross-docking
Abstract: 
 Cross-docking is a logistics procedure implemented in a warehouse to achieve a competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. Today, one of the challenges related to cross-docking for both practitioners and researchers is handling the uncertainty. Robust cross-docking solutions bring a part of the answer to this challenge. This paper proposes an overview of robust and real-time models for cross-dock problems with a focus on scheduling problems, notably in the road-to-road cross-dock environment. To this end, the conducted systematic literature review addresses the collection, identification, screening, eligibility, and inclusion steps to extract the most relevant literature. The gaps in the literature are identified, and some perspectives to support future studies are proposed.
Journal: International Journal of Production Research
Pages: 2372-2401
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2062580
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2062580
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# input file: TPRS_A_2069059_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Wei Liang
Author-X-Name-First: Wei
Author-X-Name-Last: Liang
Author-Name: Zeqiang Zhang
Author-X-Name-First: Zeqiang
Author-X-Name-Last: Zhang
Author-Name: Yu Zhang
Author-X-Name-First: Yu
Author-X-Name-Last: Zhang
Author-Name: Peiyu Xu
Author-X-Name-First: Peiyu
Author-X-Name-Last: Xu
Author-Name: Tao Yin
Author-X-Name-First: Tao
Author-X-Name-Last: Yin
Title: Improved social spider algorithm for partial disassembly line balancing problem considering the energy consumption involved in tool switching
Abstract: 
 As the waste products have a variety of connection structure characteristics, the energy consumed in tool switching in the disassembly process is considered to better comprehensively optimise the energy consumption index. A mixed-integer non-linear programming (MINLP) model of multi-objective partial disassembly line balancing problem (PDLBP) is constructed to minimise four optimisation objectives which are the number of workstations, workstation load, number of the tools are switched, and energy consumption. Based on the characteristics of PDLBP, we constructed an energy consumption matrix of tool switching and proposed a multi-objective improved social spider algorithm (ISSA). The random movement and mask change operations of ISSA were improved, and the artificial spiders were added to enhance the global optimisation capabilities of ISSA. ISSA was applied to optimise two typical benchmark instances, which have different scales, respectively. And the computational results were compared with several algorithms of existing literature to verify the superiority of ISSA. Finally, ISSA was applied to a partial disassembly instance of a printer, which considered the energy consumed in tool switching. Then, multiple better disassembly schemes were provided for decision-makers.
Journal: International Journal of Production Research
Pages: 2250-2266
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2069059
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2069059
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# input file: TPRS_A_2056723_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ramin Ahmed
Author-X-Name-First: Ramin
Author-X-Name-Last: Ahmed
Author-Name: H. Sebastian Heese
Author-X-Name-First: H. Sebastian
Author-X-Name-Last: Heese
Author-Name: Michael Kay
Author-X-Name-First: Michael
Author-X-Name-Last: Kay
Title: Designing a manufacturing network with additive manufacturing using stochastic optimisation
Abstract: 
 Two of the major problems Traditional Manufacturing (TM) supply chains face are setting requisite reactive strategies to address the uncertainties in demand and the optimal placement of these buffering capacities in order to be both responsive and cost-effective. With Additive Manufacturing (AM) stepping into large-scale production at different firms, we address the aforementioned supply chain dilemmas by considering the potential role of AM in a TM supply chain network where AM facilities can act as a recourse to the TMs and, also, as a dedicated source providing responsive and cost-effective sourcing alternatives. We develop an analytical allocation rule based on cost differentials, which provides optimal sourcing decisions through sequential demand replenishment and facilitates an efficient performance evaluation of possible network configurations. We first model the scenario as a three-stage stochastic optimisation problem. We then solve it using the allocation rule and present an illustration of our analysis and the optimal supply chain network configuration. Furthermore, we derive some insights as to how different problem characteristics affect the value and usage of AM.
Journal: International Journal of Production Research
Pages: 2267-2287
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2056723
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2056723
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# input file: TPRS_A_2060770_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Elham Taghizadeh
Author-X-Name-First: Elham
Author-X-Name-Last: Taghizadeh
Author-Name: Saravanan Venkatachalam
Author-X-Name-First: Saravanan
Author-X-Name-Last: Venkatachalam
Title: Two-stage risk-averse stochastic programming approach for multi-item single source ordering problem: CVaR minimisation with transportation cost
Abstract: 
 Integrating inventory and transportation decisions is vital in supply chain management and can enable decision-makers to achieve competitive advantages. This study considers a multi-item replenishment problem (MIRP) with a piece-wise linear transportation cost under demand uncertainty, which usually occurs both in retail and production environment when several items must be ordered from a single supplier. Conventionally, two-stage stochastic programming formulation is risk-neutral, and it lacks robustness in the presence of high data variability. Hence, we introduce the Conditional Value at Risk (CVaR) approach for MIRP. Additionally, we deploy both single and multi-cut L-shaped and the sample average approximation method to circumvent the computational complexity to solve large-scale instances. The data-driven simulation study is used to benchmark the results from deterministic, risk-neutral, and risk-averse stochastic models. The results indicate that under higher data variations, the risk-averse model provides better perspectives for a decision-maker. The results show a 40–50% reduction in lost sales with marginal growth in total cost while considering CVaR instead of a risk-neutral approach.
Journal: International Journal of Production Research
Pages: 2129-2146
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2060770
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2060770
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# input file: TPRS_A_2067505_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Gabriel Lyon
Author-X-Name-First: Gabriel
Author-X-Name-Last: Lyon
Author-Name: Alejandro Cataldo
Author-X-Name-First: Alejandro
Author-X-Name-Last: Cataldo
Author-Name: Gustavo Angulo
Author-X-Name-First: Gustavo
Author-X-Name-Last: Angulo
Author-Name: Pablo A. Rey
Author-X-Name-First: Pablo A.
Author-X-Name-Last: Rey
Author-Name: Antoine Sauré
Author-X-Name-First: Antoine
Author-X-Name-Last: Sauré
Title: A column generation approach to intraday scheduling of chemotherapy patients
Abstract: 
 Chemotherapy scheduling at cancer treatment centres is a complex problem due to high and growing demand, diversity of treatment protocols, limitations on resources and the need to coordinate treatment session times with laboratory preparation of medication. Over a given planning horizon, treatment centres assign patients first to specific days (interday scheduling) and then to specific times within each day (intraday scheduling), the latter process including the definition of medication preparation time. This paper addresses the intraday scheduling problem using an integer programming model that attempts to schedule all patients assigned to the horizon, and the preparation of the medication to be administered, simultaneously. The linear relaxation of the model formulation, which is based on treatment patterns, is solved using column generation. The proposed approach allows for medication preparation on the day of treatment or a previous day subject to time slot availability. A case study is conducted using actual data from a Chilean cancer centre to compare through simulation the schedules generated by the proposed approach and the centre's manual method. The results show that the proposed approach performs better on makespan, treatment chair occupancy, number of overtime hours and finding solutions at high demand levels.
Journal: International Journal of Production Research
Pages: 2231-2249
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2067505
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2067505
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# input file: TPRS_A_2068163_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Carlos J. Pérez-González
Author-X-Name-First: Carlos J.
Author-X-Name-Last: Pérez-González
Author-Name: Arturo J. Fernández
Author-X-Name-First: Arturo J.
Author-X-Name-Last: Fernández
Author-Name: Vicent Giner-Bosch
Author-X-Name-First: Vicent
Author-X-Name-Last: Giner-Bosch
Author-Name: Andrés Carrión-García
Author-X-Name-First: Andrés
Author-X-Name-Last: Carrión-García
Title: Optimal repetitive reliability inspection of manufactured lots for lifetime models using prior information
Abstract: 
 Repetitive group inspection of production lots is considered to develop the failure censored plan with minimal expected sampling effort using prior information. Optimal reliability test plans are derived for the family of log-location-scale lifetime distributions, whereas a limited beta distribution is assumed to model the proportion nonconforming, p. A highly efficient and quick step-by-step algorithm is proposed to solve the underlying mixed nonlinear programming problem. Conventional repetitive group plans are often very effective in reducing the average sample number with respect to other inspection schemes, but sample sizes may increase under certain conditions such as high censoring. The inclusion of previous knowledge from past empirical results contributes to drastically reduce the amount of sampling required in life testing. Moreover, the use of expected sampling risks significantly improves the assessment of the actual producer and consumer sampling risks. Several tables and figures are presented to analyse the effect of the available prior evidence about p. The results show that the proposed lot inspection scheme clearly outperforms the standard repetitive group plans obtained under the traditional approach based on conventional risks. Finally, an application to the manufacture of integrated circuits is included for illustrative purposes.
Journal: International Journal of Production Research
Pages: 2214-2230
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2068163
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2068163
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# input file: TPRS_A_2057256_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Swapnil Bhalla
Author-X-Name-First: Swapnil
Author-X-Name-Last: Bhalla
Author-Name: Erlend Alfnes
Author-X-Name-First: Erlend
Author-X-Name-Last: Alfnes
Author-Name: Hans-Henrik Hvolby
Author-X-Name-First: Hans-Henrik
Author-X-Name-Last: Hvolby
Title: Tools and practices for tactical delivery date setting in engineer-to-order environments: a systematic literature review
Abstract: 
 The research interest in topics related to production and supply chain planning and control in engineer-to-order (ETO) environments has grown significantly over the last three decades. One of the strategically important and challenging decision areas for planning and control in ETO environments is estimating and quoting feasible delivery dates and assessing the feasibility of customer-imposed delivery dates, collectively referred to as delivery date setting (DDS). While DDS has received substantial attention in literature, research supporting the process in ETO companies is fragmented – lacking clear guidelines for industrial practice and gaps to guide future research on the topic. To address these issues, this study systematically reviews literature supporting DDS in ETO environments, identifying tools and practices proposed in the extant literature, and proposing an agenda for future research. Findings suggest that most of the research has focused on developing planning and decision-support tools for tactical capacity planning to support reliable DDS, however, with a noticeable lack of alignment with industrial decision-support needs of ETO environments. Furthermore, despite previous research emphasising the importance of high levels of coordination and formalisation in the DDS process, there is a lack of research to guide practitioners in achieving high levels of coordination and formalisation.
Journal: International Journal of Production Research
Pages: 2339-2371
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2057256
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2057256
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# input file: TPRS_A_2059413_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Dirk Briskorn
Author-X-Name-First: Dirk
Author-X-Name-Last: Briskorn
Author-Name: Lena Rotfuß
Author-X-Name-First: Lena
Author-X-Name-Last: Rotfuß
Author-Name: Marcel Helmdach
Author-X-Name-First: Marcel
Author-X-Name-Last: Helmdach
Title: Modelling and optimising the capacity and production network planning in plastics processing factories
Abstract: 
 This paper deals with the capacity planning and production network planning in plastics processing factories. We lay emphasis on the opportunity and – potentially – necessity to move machines, tools and material. Furthermore, we consider the option to outsource production to external suppliers. Demand is deterministic and has to be satisfied in the same period. We present a linear mixed integer programming model representing the problem to find a minimum-cost production plan where total cost accounts for variable production cost, setup cost, transportation cost, relocation cost and cost caused by machine purchases. The decisions to be made are the allocation of machines to plants. This includes to decide for investments or relocating machines between plants. In addition, the allocation of products to machines and the determination of the corresponding optimal quantities of production, purchase and transportation within the network of suppliers, plants and customers are decided. We provide a computational study validating the model and conduct a sensitivity analysis of the run time using an off-the-shelf solver. Finally, we present a real-world case of an international automobile supplier. Tackling the instance with an off-the-shelf solver the problem cannot be solved in reasonable time. Thus we apply a simple decomposition scheme to provide decision support for the real-world case.
Journal: International Journal of Production Research
Pages: 2105-2128
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2059413
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2059413
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# input file: TPRS_A_2063086_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mahdi Abolghasemi
Author-X-Name-First: Mahdi
Author-X-Name-Last: Abolghasemi
Author-Name: Bahman Rostami-Tabar
Author-X-Name-First: Bahman
Author-X-Name-Last: Rostami-Tabar
Author-Name: Aris Syntetos
Author-X-Name-First: Aris
Author-X-Name-Last: Syntetos
Title: The value of point of sales information in upstream supply chain forecasting: an empirical investigation
Abstract: 
 Traditionally, manufacturers use past orders (received from some downstream supply chain level) to forecast future ones, before turning such forecasts into appropriate inventory and production optimisation decisions. With recent advances in information sharing technologies, upstream supply chain (SC) companies may have access to downstream point of sales (POS) data. Such data can be used as an alternative source of information for forecasting. There are a few studies that investigate the benefits of using orders versus POS data in upstream SC forecasting; the results are mixed and empirical evidence is lacking, particularly in the context of multi-echelon SCs and in the presence of promotions. We investigate an actual three-echelon SC with 684 series where the manufacturer aims to forecast orders received from distribution centres (DCs) using either aggregated POS data at DCs level or historical orders received from the DCs. Our results show that the order-based methods outperform the POS-based ones by 6–15%. We find that low values of mean, variance, non-linearity and entropy of POS data, and promotion presence negatively impact the performance of the POS-based forecasts. Such findings are useful for determining the appropriate source of data and the impact of series characteristics for order forecasting in SCs.
Journal: International Journal of Production Research
Pages: 2162-2177
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2063086
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2063086
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2057254_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Fuli Xiong
Author-X-Name-First: Fuli
Author-X-Name-Last: Xiong
Author-Name: Siyuan Chen
Author-X-Name-First: Siyuan
Author-X-Name-Last: Chen
Author-Name: Zongfang Ma
Author-X-Name-First: Zongfang
Author-X-Name-Last: Ma
Author-Name: Linlin Li
Author-X-Name-First: Linlin
Author-X-Name-Last: Li
Title: Approximate model and algorithms for precast supply chain scheduling problem with time-dependent transportation times
Abstract: 
 This paper focuses on the precast supply chain scheduling problem with time-dependent transportation time to minimise the total weighted tardiness (PSCSP_TDT |TWT). In the problem, an order sequence and several job sequences are to be determined simultaneously. At first, through in-depth analysis of problem structure and real data from a precast manufacturer, we approximate the problem into a three-stage order scheduling problem by combining the seven production stages into one differentiation stage, and then explore some useful properties of the schedules for the approximate problem. Subsequently, to solve the small instances for the PSCSP_TDT |TWT, we propose an approximate model-based hybrid dynamic programming and heuristic (AMHDPH) and obtain a lower bound as a by-product of the algorithm. For dealing with medium-or large instances, with considering the complexity of the problem, we propose four approximate model-based hybrid iterated greedy (AMHIG) algorithms by integration of constructive heuristics, structural properties of solutions, an iterated greedy, and a correction heuristic. Comprehensive computational results show that the AMHDPH generates tight lower bounds for small instances and solves the most of small instances to optimality within 60 seconds. Whereas the best AMHIG generates feasible solutions with an average optimality gap below 5 percent for around 70 percent instances.
Journal: International Journal of Production Research
Pages: 2057-2085
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2057254
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2057254
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# input file: TPRS_A_2058433_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Serhat Saylam
Author-X-Name-First: Serhat
Author-X-Name-Last: Saylam
Author-Name: Melih Çelik
Author-X-Name-First: Melih
Author-X-Name-Last: Çelik
Author-Name: Haldun Süral
Author-X-Name-First: Haldun
Author-X-Name-Last: Süral
Title: The min–max order picking problem in synchronised dynamic zone-picking systems
Abstract: 
 In both manual and automated warehouses, a combination of efficient zoning and picker routing plays an important role in improving travel time, congestion, and system throughput. This paper considers the order picker routing problem in a dynamic and synchronised zoning environment, where the items corresponding to each customer order are picked simultaneously in multiple zones, and zones may change between different orders. The objective is to minimise the maximum time of completing the picking activities in any zone. Using a min–max type of objective not only minimises the makespan of an order picking wave, but it also helps balance the workload of the order pickers more effectively. We present a mathematical model for the optimal solution of this problem, as well as a dynamic programming approach to find the optimal solution for the case where a zone is a set of adjacent aisles. Computational experiments on randomly generated instances show that the dynamic programming approach is able to find optimal solutions in negligible computational times.
Journal: International Journal of Production Research
Pages: 2086-2104
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2058433
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2058433
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2069525_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: G. Castañé
Author-X-Name-First: G.
Author-X-Name-Last: Castañé
Author-Name: A. Dolgui
Author-X-Name-First: A.
Author-X-Name-Last: Dolgui
Author-Name: N. Kousi
Author-X-Name-First: N.
Author-X-Name-Last: Kousi
Author-Name: B. Meyers
Author-X-Name-First: B.
Author-X-Name-Last: Meyers
Author-Name: S. Thevenin
Author-X-Name-First: S.
Author-X-Name-Last: Thevenin
Author-Name: E. Vyhmeister
Author-X-Name-First: E.
Author-X-Name-Last: Vyhmeister
Author-Name: P-O. Östberg
Author-X-Name-First: P-O.
Author-X-Name-Last: Östberg
Title: The ASSISTANT project: AI for high level decisions in manufacturing
Abstract: 
 This paper outlines the main idea and approach of the H2020 ASSISTANT (LeArning and robuSt deciSIon SupporT systems for agile mANufacTuring environments) project. ASSISTANT is aimed at the investigation of AI-based tools for adaptive manufacturing environments, and focuses on the development of a set of digital twins for integration with, management of, and decision support for production planning and control. The ASSISTANT tools are based on the approach of extending generative design, an established methodology for product design, to a broader set of manufacturing decision making processes; and to make use of machine learning, optimisation, and simulation techniques to produce executable models capable of ethical reasoning and data-driven decision making for manufacturing systems. Combining human control and accountable AI, the ASSISTANT toolsets span a wide range of manufacturing processes and time scales, including process planning, production planning, scheduling, and real-time control. They are designed to be adaptable and applicable in a both general and specific manufacturing environments.
Journal: International Journal of Production Research
Pages: 2288-2306
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2069525
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2069525
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# input file: TPRS_A_2068086_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Sylvain Chabanet
Author-X-Name-First: Sylvain
Author-X-Name-Last: Chabanet
Author-Name: Hind Bril El-Haouzi
Author-X-Name-First: Hind
Author-X-Name-Last: Bril El-Haouzi
Author-Name: Michael Morin
Author-X-Name-First: Michael
Author-X-Name-Last: Morin
Author-Name: Jonathan Gaudreault
Author-X-Name-First: Jonathan
Author-X-Name-Last: Gaudreault
Author-Name: Philippe Thomas
Author-X-Name-First: Philippe
Author-X-Name-Last: Thomas
Title: Toward digital twins for sawmill production planning and control: benefits, opportunities, and challenges
Abstract: 
 Sawmills are key elements of the forest product industry supply chain, and they play important economic, social, and environmental roles. Sawmill production planning and control are, however, challenging owing to several factors, including, but not limited to, the heterogeneity of the raw material. The emerging concept of digital twins introduced in the context of Industry 4.0 has generated high interest and has been studied in a variety of domains, including production planning and control. In this paper, we investigate the benefits digital twins would bring to the sawmill industry via a literature review on the wider subject of sawmill production planning and control. Opportunities facilitating their implementation, as well as ongoing challenges from both academic and industrial perspectives, are also studied.
Journal: International Journal of Production Research
Pages: 2190-2213
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2068086
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2068086
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# input file: TPRS_A_2069524_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hongfei Guo
Author-X-Name-First: Hongfei
Author-X-Name-Last: Guo
Author-Name: Linsheng Zhang
Author-X-Name-First: Linsheng
Author-X-Name-Last: Zhang
Author-Name: Yaping Ren
Author-X-Name-First: Yaping
Author-X-Name-Last: Ren
Author-Name: Yun Li
Author-X-Name-First: Yun
Author-X-Name-Last: Li
Author-Name: Zhongwei Zhou
Author-X-Name-First: Zhongwei
Author-X-Name-Last: Zhou
Author-Name: Jianzhao Wu
Author-X-Name-First: Jianzhao
Author-X-Name-Last: Wu
Title: Optimizing a stochastic disassembly line balancing problem with task failure via a hybrid variable neighborhood descent-artificial bee colony algorithm
Abstract: 
 A disassembly line is an effective disassembly system to recover end-of-life products. In real life, as end-of-life products are subject to varying degrees of wear and tear, task failure may occur in the disassembly process. In this paper, the task failure risks are considered, and an expected profit-based stochastic disassembly line balancing problem is studied. First, a mathematical model is presented to maximise the expected recovering profit with task failures. Then, a hybrid metaheuristic approach is developed to efficiently solve the proposed model, which is integrated with a variable neighbourhood descent method and an artificial bee colony algorithm. Finally, the effectiveness and robustness of the proposed algorithm are verified by three cases, and experiment results show that the solution performance of the proposed approach is superior to the other three existing methods.
Journal: International Journal of Production Research
Pages: 2307-2321
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2069524
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2069524
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# input file: TPRS_A_2062266_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Youssef Lahrichi
Author-X-Name-First: Youssef
Author-X-Name-Last: Lahrichi
Author-Name: David Damand
Author-X-Name-First: David
Author-X-Name-Last: Damand
Author-Name: Laurent Deroussi
Author-X-Name-First: Laurent
Author-X-Name-Last: Deroussi
Author-Name: Nathalie Grangeon
Author-X-Name-First: Nathalie
Author-X-Name-Last: Grangeon
Author-Name: Sylvie Norre
Author-X-Name-First: Sylvie
Author-X-Name-Last: Norre
Title: Investigating two variants of the sequence-dependent robotic assembly line balancing problem by means of a split-based approach
Abstract: 
 The Robotic Assembly Line Balancing Problem (RALBP) is a joint optimisation problem that is concerned with assigning both assembly operations and robots to workstations that are placed within a straight line. RALBP-2 is the particular problem where the cycle time, which is the maximum time spent on a workstation by the product being assembled, is minimised while the number of workstations is fixed. Sequence-dependent setup times are considered which raises the problem of sequencing the operations assigned to each workstation. Both the durations of the operations and the setup times depend on the robot. Two different variants are identified from literature. The first variant assumes that, given a set of types of robots, each type of robot can be assigned to multiple workstations without any limitation. Given a set of robots, the second variant forces each robot to be assigned to at most one workstation. Both assumptions are studied in this paper. The particular case of a given giant sequence of operations is solved thanks to a polynomial optimal algorithm. The latter algorithm, called split, is then embedded in a metaheuristic framework that explores the space of giant sequences. Benchmark data sets from literature are considered in the experimental section. A comparative study with other methods from literature shows the competitiveness of the suggested approach.
Journal: International Journal of Production Research
Pages: 2322-2338
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2062266
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2062266
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# input file: TPRS_A_2060772_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jin Xie
Author-X-Name-First: Jin
Author-X-Name-Last: Xie
Author-Name: Xinyu Li
Author-X-Name-First: Xinyu
Author-X-Name-Last: Li
Author-Name: Liang Gao
Author-X-Name-First: Liang
Author-X-Name-Last: Gao
Author-Name: Lin Gui
Author-X-Name-First: Lin
Author-X-Name-Last: Gui
Title: A new neighbourhood structure for job shop scheduling problems
Abstract: 
 Job shop scheduling problem (JSP) is a widely studied NP-complete combinatorial optimisation problem. Neighbourhood structures play a critical role in solving JSP. At present, there are three state-of-the-art neighbourhood structures, i.e. N5, N6, and N7. Improving the upper bounds of some famous benchmarks is inseparable from the role of these neighbourhood structures. However, these existing neighbourhood structures only consider the movement of critical operations within a critical block. According to our experiments, it is also possible to improve the makespan of a scheduling scheme by moving a critical operation outside its critical block. According to the above finding, this paper proposes a new N8 neighbourhood structure considering the movement of critical operations within a critical block and the movement of critical operations outside the critical block. Besides, a neighbourhood clipping method is designed to avoid invalid movement, discarding non-improving moves. Tabu search (TS) is a commonly used algorithm framework combined with neighbourhood structures. This paper uses this framework to compare the N8 neighbourhood structure with N5, N6, and N7 neighbourhood structures on four famous benchmarks. The experimental results verify that the N8 neighbourhood structure is more effective and efficient in solving JSP than the other state-of-the-art neighbourhood structures.
Journal: International Journal of Production Research
Pages: 2147-2161
Issue: 7
Volume: 61
Year: 2023
Month: 04
X-DOI: 10.1080/00207543.2022.2060772
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2060772
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# input file: TPRS_A_2079015_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yuting Sun
Author-X-Name-First: Yuting
Author-X-Name-Last: Sun
Author-Name: Liang Zhang
Author-X-Name-First: Liang
Author-X-Name-Last: Zhang
Title: Application of a novel approach of production system modelling, analysis and improvement for small and medium-sized manufacturers: a case study
Abstract: 
 With the great opportunities created by the new advances in Industry 4.0, many manufacturers are testing and investing in new equipment and infrastructure to deploy these technologies. However, there are a huge number of small and medium-sized manufacturers (SMMs) that are lagging behind due to the lack of in-house R&D capabilities and workforce shortage and/or financial constraints to afford such investment. Additionally, application of theoretical production research in SMMs often confront challenges such as low data availability and data quality, etc. In this paper, we describe a case study at a local medium-sized manufacturer of electromechanical devices for industrial, consumer, and medical applications, who was struggling to meet ever-growing market demand, and apply a novel approach of production system modelling to overcome the challenge of unavailability of the operation up- and downtime data. Specifically, the parametric model of the production system is identified using several system performance metrics derived based on the parts flow data of the in-process buffer. With the mathematical model constructed, the system bottleneck is analysed and a number of improvement scenarios are explored that can potentially enhance the system throughput. Finally, model sensitivity is analysed by calculating the deviation of the model-predicted performance metrics to those produced by a reference nominal model. This analysis demonstrates that the model constructed using our proposed approach is robust even when the system parameters vary from the baseline ones.
Journal: International Journal of Production Research
Pages: 3279-3299
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2079015
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2079015
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# input file: TPRS_A_2081629_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Songi Kim
Author-X-Name-First: Songi
Author-X-Name-Last: Kim
Author-Name: Keeheon Lee
Author-X-Name-First: Keeheon
Author-X-Name-Last: Lee
Title: The paradigm shift of mass customisation research
Abstract: 
 Industrial manufacturing is a core component of a nation’s economic wealth. It is driven by technology, and its paradigm has shifted from craft production to mass production to lean production to mass customisation (MC). We identify how emerging technologies offer a new way to shift MC research focusing on the scientific communities that have been driving MC research, changes in MC throughout the years, and the technological advances that influence future research trends of MC. We then identify MC paradigms. We analyse 1,947 MC papers from 1992 to 2019 and discover the research attention changes from the perspectives of the communities and themes using topic modelling. Our result indicates that MC was explained in terms of the business and marketing strategy (BMS) and the operations management (OM), in accordance with technological development. In BMS, MC topics moved from demand uncertainty to industry transformation. In OM, topics changed from assembly line for product differentiation to additive manufacturing. We discuss the future research agenda according to the technological advances in computer-aided design, additive manufacturing, machine learning, identification technologies, virtual reality, and human–robot collaboration. Not only researchers but practitioners and policymakers can utilise our approach to analyse and formulate MC strategies considering new technologies.
Journal: International Journal of Production Research
Pages: 3350-3376
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2081629
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2081629
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2085209_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Farzad Fathizadeh
Author-X-Name-First: Farzad
Author-X-Name-Last: Fathizadeh
Author-Name: Jean Savinien
Author-X-Name-First: Jean
Author-X-Name-Last: Savinien
Author-Name: Yacine Rekik
Author-X-Name-First: Yacine
Author-X-Name-Last: Rekik
Title: Fuzzy Gaussian mixture optimisation of the newsvendor problem: mixing fuzzy perception and randomness of customer demand
Abstract: 
 Motivated by the increasing exposition of decision makers to both statistical and judgemental based sources of demand information, we develop in this paper a fuzzy Gaussian Mixture Model (GMM) for the newsvendor permitting to mix probabilistic inputs with a subjective weight modelled as a fuzzy number. The developed framework can model for instance situations where sales are impacted by customers sensitive to online review feedback or expert opinions. It can also model situations where a marketing campaign leads to different stochastic alternatives for the demand with a fuzzy weight. Thanks to a tractable mathematical application of the fuzzy machinery on the newsvendor problem, we derived the optimal ordering strategy taking into account both probabilistic and fuzzy components of the demand. We show that the fuzzy GMM can be rewritten as a classical newsvendor problem with an associated density function involving these stochastic and fuzzy components of the demand. The developed model enables to relax the single modality of the demand distribution usually used in the newsvendor literature and to encode the risk attitude of the decision maker.
Journal: International Journal of Production Research
Pages: 3459-3480
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2085209
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2085209
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Handle: RePEc:taf:tprsxx:v:61:y:2023:i:10:p:3459-3480



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2082896_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Adèle Louis
Author-X-Name-First: Adèle
Author-X-Name-Last: Louis
Author-Name: Gülgün Alpan
Author-X-Name-First: Gülgün
Author-X-Name-Last: Alpan
Author-Name: Bernard Penz
Author-X-Name-First: Bernard
Author-X-Name-Last: Penz
Author-Name: Alain Benichou
Author-X-Name-First: Alain
Author-X-Name-Last: Benichou
Title: Mixed-model sequencing versus car sequencing: comparison of feasible solution spaces
Abstract: 
 In the automotive industry, a great challenge of production scheduling is to sequence cars on assembly lines. Among a wide variety of scheduling approaches, academics and manufacturers pay close attention to two specific models: Mixed-Model Sequencing (MMS) and Car Sequencing (CS). Whereas MMS explicitly considers the assembly line balance, CS operates with sequencing rules to find the best car sequence fulfilling the assembly plant requirements, like minimising work overload for assembly workers. Meanwhile, automakers including Renault Group are increasingly willing to consider other requirements, like end-to-end supply chain matters, in production planning and scheduling. In this context, this study compares MMS- and CS-feasible solution spaces to determine which workload-oriented sequencing model would be the most appropriate to later integrate new optimisation. We introduce two exact methods based on Dynamic Programming to assess the gap between both models. Numerical experiments are carried out on real-life manufacturing features from a Renault Group assembly plant. They show that MMS generates more feasible sequences than CS regardless of the sequencing rule calculation method. Only the sequencing rules used by real-life production schedulers result in a higher number of distinct feasible sequences for CS, highlighting that the plant might select a sequence with work overload situations.
Journal: International Journal of Production Research
Pages: 3415-3434
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2082896
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2082896
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2081630_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: J. B. H. C. Didden
Author-X-Name-First: J. B. H. C.
Author-X-Name-Last: Didden
Author-Name: E. Lefeber
Author-X-Name-First: E.
Author-X-Name-Last: Lefeber
Author-Name: I. J. B. F. Adan
Author-X-Name-First: I. J. B. F.
Author-X-Name-Last: Adan
Author-Name: I. W. F. Panhuijzen
Author-X-Name-First: I. W. F.
Author-X-Name-Last: Panhuijzen
Title: Genetic algorithm and decision support for assembly line balancing in the automotive industry
Abstract: 
 An important and highly complex process in the automotive industry is the balancing of the assembly lines. Optimally distributing jobs among the lines in order to obtain the highest efficiency is mostly done manually, taking a lot of time. This paper aims to automate the process of line balancing for a real-world test case. Automotive assembly lines are highly complex, and multiple factors have to be considered while balancing the lines. All factors relevant in a case study at VDL Nedcar are considered, namely, mixed-model production, sequence-dependent setup times, variable workplaces with multiple operators and multiple assignment constraints. A Genetic Algorithm (GA) is proposed to solve the formulated balancing problem and to act as a decision support system. Results on newly proposed benchmark instances show that the solution is dependent on the relation between the takt time and processing time of jobs, as well as the setup times. In addition, results of a real-life case study show that the proposed GA is effective in balancing a real-world assembly line and that it can both increase the efficiency of the line and decrease the variance in operating time between all model variants when compared to current practice.
Journal: International Journal of Production Research
Pages: 3377-3395
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2081630
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2081630
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# input file: TPRS_A_2079437_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Thomas De Lombaert
Author-X-Name-First: Thomas
Author-X-Name-Last: De Lombaert
Author-Name: Kris Braekers
Author-X-Name-First: Kris
Author-X-Name-Last: Braekers
Author-Name: René De Koster
Author-X-Name-First: René
Author-X-Name-Last: De Koster
Author-Name: Katrien Ramaekers
Author-X-Name-First: Katrien
Author-X-Name-Last: Ramaekers
Title: In pursuit of humanised order picking planning: methodological review, literature classification and input from practice
Abstract: 
 At the core of every high-performing warehouse is an efficient order picking (OP) system. To attain such a system, policy choices should be carefully aligned with subjects responsible for the actual picking within the established system. Despite recent advancements in automating the picking process due to Industry 4.0, human operators will continue to play a crucial role in the future of warehousing. However, unlike robots, human operators have specific skills, conduct, and perceptions, which are only partly accounted for in current planning models. This review adopts a multimethod approach to identify and analyse how these phenomena are currently integrated into OP planning problems. In addition, we assess the relevance and adequacy of human factors modelling in academic literature with practice-based insights gathered via semi-structured interviews. This leads to five major human factors integration constructs and dedicated recommendations on how to refine them. We then take the analysis one step further and make suggestions on how to integrate these constructs with leading research methodologies in the context of Industry 5.0. The results highlight the prevalent need to increasingly account for psychosocial phenomena and their impact on operational performance. Future research opportunities provide a substantiated foundation to assist in human-centric work design.
Journal: International Journal of Production Research
Pages: 3300-3330
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2079437
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2079437
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# input file: TPRS_A_2079438_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Fehmi Burcin Ozsoydan
Author-X-Name-First: Fehmi Burcin
Author-X-Name-Last: Ozsoydan
Author-Name: İlker Gölcük
Author-X-Name-First: İlker
Author-X-Name-Last: Gölcük
Title: A hybridisation of linear programming and genetic algorithm to solve the capacitated facility location problem
Abstract: 
 This paper introduces a cooperative approach of a swarm intelligence algorithm and a linear programming solver to solve the capacitated facility location problem (CFLP). Given a set of potential locations to open facilities, the aim in CFLP is to find the minimum cost, which is the sum of facility opening costs and transportation costs. The developed solution strategy decomposes CFLP into two sub-problems. The former sub-problem has a binary domain. Although most of the swarm intelligence algorithms employ additional procedures such as sigmoid function to deal with binary domains, the proposed algorithm does not require for such methods. An adaptive mutation operator enhances this algorithm. The aim of the latter sub-problem is to generate a policy that optimally assigns customers to the opened facilities. In this regard, the generated binary vectors by the proposed algorithm are passed to a solver to optimise the generated linear model. Commonly used instances available in the literature are solved by the proposed strategy. Comprehensive experimental study includes comparisons with the sate-of-the-art. According to the statistically verified results, the proposed strategy is found as promising in solving CFLP.
Journal: International Journal of Production Research
Pages: 3331-3349
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2079438
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2079438
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2079012_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Daoyuan Liu
Author-X-Name-First: Daoyuan
Author-X-Name-Last: Liu
Author-Name: Yu Guo
Author-X-Name-First: Yu
Author-X-Name-Last: Guo
Author-Name: Shaohua Huang
Author-X-Name-First: Shaohua
Author-X-Name-Last: Huang
Author-Name: Weiguang Fang
Author-X-Name-First: Weiguang
Author-X-Name-Last: Fang
Author-Name: Xu Tian
Author-X-Name-First: Xu
Author-X-Name-Last: Tian
Title: A stacking denoising auto-encoder with sample weight approach for order remaining completion time prediction in complex discrete manufacturing workshop
Abstract: 
 Accurate order remaining completion time (ORCT) prediction provides an essential criterion for dynamically triggering the adjustment of production plans and establishment of dispatching strategies, which helps to improve the plan rationality and production efficiency, thus guaranteeing delivery orders on time. With the extensive deployment of Industrial Internet of Things in the workshop, the data for ORCT prediction is perceived in real-time. However, data quality, knowledge inconsistency, and data distribution variation make ORCT prediction more difficult. Hence, a stacking denoising auto-encoder with sample weight (SW-SDAE) method is proposed to improve the robustness and applicability of ORCT prediction. Firstly, a four-layer SDAEs is constructed to extract high-level and robust features. Secondly, a dynamic updating method of sample weight for regression prediction is designed to guide the training of prediction model parameters and improve the prediction accuracy. Thirdly, model-based transfer learning is employed to adapt to the data distribution change over time and ensure the prediction applicability. Finally, different prediction models are applied to an actual case for comparison. The experimental results show that the proposed prediction method is effective for ORCT prediction and superior to other methods.
Journal: International Journal of Production Research
Pages: 3246-3259
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2079012
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2079012
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# input file: TPRS_A_2078747_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ruben D'Haen
Author-X-Name-First: Ruben
Author-X-Name-Last: D'Haen
Author-Name: Kris Braekers
Author-X-Name-First: Kris
Author-X-Name-Last: Braekers
Author-Name: Katrien Ramaekers
Author-X-Name-First: Katrien
Author-X-Name-Last: Ramaekers
Title: Integrated scheduling of order picking operations under dynamic order arrivals
Abstract: 
 To remain competitive in the current e-commerce environment, warehouses are expected to handle customer orders as efficiently and quickly as possible. Previous research on order picking in a static context has shown that integrating batching, routing and scheduling decisions leads to better results than addressing these planning problems individually. In this study we propose an integrated solution approach that is able to deal with dynamic order arrivals, a problem often encountered in practice. Furthermore, we demonstrate the need to anticipate on future order arrivals to keep customer service levels high. We develop a new large neighbourhood search algorithm to solve the online, integrated batching, routing and scheduling problem. First, the algorithm is shown to outperform the current state-of-the-art static solution algorithm. Next, we develop an experimental design based on real-life data, to test the applicability of the model in different settings. The results of this experimental design are used to obtain insights on the particularity of this online, integrated problem. The effect of several real-life characteristics is demonstrated by using an ANOVA, leading to several managerial insights that may help companies to operate efficiently without jeopardising customer satisfaction.
Journal: International Journal of Production Research
Pages: 3205-3226
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2078747
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2078747
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2079014_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Shijuan Yang
Author-X-Name-First: Shijuan
Author-X-Name-Last: Yang
Author-Name: Jianjun Wang
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wang
Author-Name: Yiliu Tu
Author-X-Name-First: Yiliu
Author-X-Name-Last: Tu
Author-Name: Yunxia Han
Author-X-Name-First: Yunxia
Author-X-Name-Last: Han
Author-Name: Xiaolei Ren
Author-X-Name-First: Xiaolei
Author-X-Name-Last: Ren
Author-Name: Chunfeng Ding
Author-X-Name-First: Chunfeng
Author-X-Name-Last: Ding
Author-Name: Xiaoying Chen
Author-X-Name-First: Xiaoying
Author-X-Name-Last: Chen
Title: Robust multi-response surface optimisation based on Bayesian quantile model
Abstract: 
 In robust parameter design, model parameter uncertainty and quality of experimental data often affect the establishment of response surface models, which in turn affect the acquisition of the optimal operating conditions. This paper proposes a robust multi-response surface modelling and optimisation method based on Bayesian quantile regression, which is a robust regression technique insensitive to outliers, to address the above problems. We first incorporate quantile regression into the Bayesian framework and use Bayes's theorem to obtain posterior inference of model parameters. Then, the Monte Carlo-based expectation maximisation algorithm is used to estimate the model parameters, and the entropy-based overall desirability function is taken as an optimisation objective to obtain the optimal settings. The effectiveness of the proposed method is demonstrated by an additive manufacturing process and a simulation study. Compared with other existing methods, the proposed method can resist the disturbance of outliers, and thus obtain more accurate optimisation results.
Journal: International Journal of Production Research
Pages: 3260-3278
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2079014
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2079014
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2078745_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Author-Name: Armin Darmawan
Author-X-Name-First: Armin
Author-X-Name-Last: Darmawan
Author-Name: Shih-Wen Liu
Author-X-Name-First: Shih-Wen
Author-X-Name-Last: Liu
Title: Stage-independent multiple sampling plan by variables inspection for lot determination based on the process capability index Cpk
Abstract: 
 Multiple sampling plan (MSP) has been proved that the sample units required for inspection at each stage are usually smaller than the conventional single or double sampling. However, it is more complex to administer and difficult to derive the corresponding operating characteristic function since the judgment on the submitted lot under the MSP is not only dependent on the result of current sampling but also on previous sampling results. Thus, this paper attempts to provide a relaxed type of conventional MSP by assuming the sampling inspection at each stage is independent which is called variables stage-independent multiple sampling plan and integrated with the most widely-used process capability index Cpk. For the cost-efficient purpose, the plan parameters are solved under an optimisation model that minimises the average sample number by satisfying the required quality levels and tolerated risks. Finally, the applicability of the proposed plan is illustrated in a case study.
Journal: International Journal of Production Research
Pages: 3171-3183
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2078745
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2078745
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2081631_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Luiz Fernando Puttow Southier
Author-X-Name-First: Luiz Fernando Puttow
Author-X-Name-Last: Southier
Author-Name: Dalcimar Casanova
Author-X-Name-First: Dalcimar
Author-X-Name-Last: Casanova
Author-Name: Luis Barbosa
Author-X-Name-First: Luis
Author-X-Name-Last: Barbosa
Author-Name: Cesar Torrico
Author-X-Name-First: Cesar
Author-X-Name-Last: Torrico
Author-Name: Marco Barbosa
Author-X-Name-First: Marco
Author-X-Name-Last: Barbosa
Author-Name: Marcelo Teixeira
Author-X-Name-First: Marcelo
Author-X-Name-Last: Teixeira
Title: Modelling and control of manufacturing systems subject to context recognition and switching
Abstract: 
 Finite-State Automata (FSA) are foundations for modelling, synthesis, verification, and implementation of controllers for manufacturing systems. However, FSA are limited to represent emerging features in manufacturing, such as the ability to recognise and switch contexts. One option is to enrich FSA with parameters that carry details about the manufacturing, which may favour design and control. A parameter can be embedded either on transitions or states of an FSA, and each approach defines its own modelling framework, so that their comparison and integration are not straightforward, and they may lead to different control solutions, modelled, processed and implemented distinctly. In this paper, we show how to combine advantages from parameters in manufacturing the modelling and control. We initially present a background that allows to understand each parameterisation strategy. Then, we introduce a conversion method that translates a design-friendly model into a synthesis-efficient structure. Finally, we use the converted models is synthesis, highlighting their advantages. Examples are used throughout the paper to illustrate and compare our results and tooling support is also provided.
Journal: International Journal of Production Research
Pages: 3396-3414
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2081631
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2081631
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# input file: TPRS_A_2083997_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Zhuojun Liu
Author-X-Name-First: Zhuojun
Author-X-Name-Last: Liu
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Author-Name: Claver Diallo
Author-X-Name-First: Claver
Author-X-Name-Last: Diallo
Author-Name: Uday Venkatadri
Author-X-Name-First: Uday
Author-X-Name-Last: Venkatadri
Title: Optimal extended warranty pricing and retailing strategies in a closed-loop supply chain
Abstract: 
 Extended warranties are widely adopted and accepted in the marketplace by manufacturers and retailers as it helps to enhance the customers' post-sale satisfaction. In closed-loop supply chains, the extended warranty not only generates profit for the manufacturer, but also provides warranty returns of the new products for remanufacturing. In this paper, a two-period model is developed and optimal pricing strategies for the extended warranties are derived. We compare the optimal pricing and retailing strategies of the extended warranties for remanufactured and new products offered by the manufacturer with and without the retailer's own extended warranty while considering the competition between the manufacturer and the retailer for the extended warranty of new products. We find that the introduction of the retailer's extended warranty does not always hurt the manufacturer's profit. Numerical analyses also show that there exists an optimal extended warranty length for the manufacturer that maximises its profit. Moreover, we show that the retailer cannot extract more profit by increasing the length of its own extended warranty.
Journal: International Journal of Production Research
Pages: 3435-3458
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2083997
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2083997
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# input file: TPRS_A_2078249_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Sara Ceschia
Author-X-Name-First: Sara
Author-X-Name-Last: Ceschia
Author-Name: Margaretha Gansterer
Author-X-Name-First: Margaretha
Author-X-Name-Last: Gansterer
Author-Name: Simona Mancini
Author-X-Name-First: Simona
Author-X-Name-Last: Mancini
Author-Name: Antonella Meneghetti
Author-X-Name-First: Antonella
Author-X-Name-Last: Meneghetti
Title: The on-demand warehousing problem
Abstract: 
 Warehouses are key elements of supply chain networks, and great attention is paid to increase their efficiency. Highly volatile space requirements are enablers of innovative resource sharing concepts, where warehouse capacities are traded on online platforms. In this context, our paper introduces the on-demand warehousing problem from the perspective of platform providers. The objective prioritises demand–supply matching with maximisation of the number of transactions. If there is a tie, the secondary objective maximises the number of suppliers matched with at least one customer and the number of customers that have matches within a specific threshold with respect to the minimum achievable cost. Besides the mathematical integer programming formulation, a myopic list-based heuristic and an efficient matheuristic approach are presented and benchmarked against the performance of a commercial optimisation solver. The impact of several parameters on the platform's objective is analysed. A particularly relevant finding is that the pricing flexibility on the demand side does not necessarily imply higher payments to the supply side. All data instances are made available publicly to encourage more researchers to work on this timely and challenging topic.
Journal: International Journal of Production Research
Pages: 3152-3170
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2078249
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2078249
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# input file: TPRS_A_2078746_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: D. G. Mogale
Author-X-Name-First: D. G.
Author-X-Name-Last: Mogale
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Naoufel Cheikhrouhou
Author-X-Name-First: Naoufel
Author-X-Name-Last: Cheikhrouhou
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Designing a food supply chain for enhanced social sustainability in developing countries
Abstract: 
 The food grain production in India has progressively risen in the past few decades, whereas the storage capacity has remained limited. The policymakers in India are attempting to close this capacity gap while addressing sustainability objectives. However, the quantification and integration of multiple social sustainability factors have remained a challenge. To improve the overall sustainability, the study attempts to develop a mathematical model considering procurement, transportation, inventory, and location-related issues. Several supply chain network factors are integrated and assessed while focussing on the social sustainability dimension. Three cases of India's largest food grain-producing and consuming states are analysed with the help of two Pareto-based algorithms. Multiple relationships between variations in supply, demand, and the capacity of silos with three defined objectives are evaluated. It is observed that, the demand significantly influences the economic and environmental objectives compared with the supply and silo capacity. The capacity of silos has a more significant impact on social objectives than economic and environmental objectives. Results reveal the importance of establishing a sufficient number of modernised silos, which reduces environmental impact and improves social factors such as farmers’ economic condition and welfare, balanced economic development, number of jobs created, and public health level.
Journal: International Journal of Production Research
Pages: 3184-3204
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2078746
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2078746
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# input file: TPRS_A_2078748_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Zhaoguang Xu
Author-X-Name-First: Zhaoguang
Author-X-Name-Last: Xu
Author-Name: Yanzhong Dang
Author-X-Name-First: Yanzhong
Author-X-Name-Last: Dang
Title: Data-driven causal knowledge graph construction for root cause analysis in quality problem solving
Abstract: 
 Root cause analysis (RCA) plays an essential role in quality problem solving (QPS). Due to the difficulty of obtaining causal knowledge of quality problems, companies often rely on expert experience and conventional RCA tools when conducting RCA. Rich QPS data have remained mostly untapped but provide the potential for causal knowledge mining, while the semistructured nature of these data poses enormous challenges to this task. Thus, we propose a data-driven framework to mine large-scale causalities between quality problems and production factors from QPS data and exploit a causal knowledge graph for quality problems (QPCKG) to express these causalities. We first classify QPS data to identify the data containing causality. The causal linguistic patterns are then employed to extract cause slots and effect slots from these data. Subsequently, we apply the BiLSTM-CRF to extract the core content of problems. A vertex fusion method is last proposed to integrate discrete causalities into QPCKG. The approach is validated in a real-world application at a leading automotive company. Three potential applications of the QPCKG are demonstrated for quality diagnosis and prediction. The QPCKG reveals a grand picture of the core interaction mechanism of product quality and production factors and provides decision-making support for RCA.
Journal: International Journal of Production Research
Pages: 3227-3245
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2078748
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2078748
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# input file: TPRS_A_2086084_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Myungeun Eom
Author-X-Name-First: Myungeun
Author-X-Name-Last: Eom
Author-Name: Byung-In Kim
Author-X-Name-First: Byung-In
Author-X-Name-Last: Kim
Title: Combinatorial Benders decomposition for melted material blending systems considering transportation and scheduling
Abstract: 
 We study an integrated optimisation problem with blending, scheduling, and routing components for a melted material blending production system. The problem is formulated as a mixed-integer linear programming model that considers the blending machine environment, due dates, target amounts, required chemical compositions of the products, and ready times of the materials in containers. This model aimed to determine the container pairings, blending plants for container pairs, and schedules for blending operations while minimising the total end time of material usage, total penalty for violating component specifications, and employee workload. Further, we propose a three-stage approach that involves solving a relaxed problem and then resolving the problem with fixed variables. We developed a combinatorial Benders decomposition algorithm with a minimal infeasible subsystem identification algorithm for the blending scheduling problem. The experimental results indicate that the proposed method can find high-quality solutions within a reasonable amount of time.
Journal: International Journal of Production Research
Pages: 3481-3503
Issue: 10
Volume: 61
Year: 2023
Month: 05
X-DOI: 10.1080/00207543.2022.2086084
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2086084
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# input file: TPRS_A_2002968_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hongfeng Wang
Author-X-Name-First: Hongfeng
Author-X-Name-Last: Wang
Author-Name: Qi Yan
Author-X-Name-First: Qi
Author-X-Name-Last: Yan
Author-Name: Junwei Wang
Author-X-Name-First: Junwei
Author-X-Name-Last: Wang
Title: Blockchain-secured multi-factory production with collaborative maintenance using Q learning-based optimisation approach
Abstract: 
 To quickly manufacture multi-variety and low-volume products, manufacturing factories are increasingly sharing resources on collaborative production networks. However, the reliability of communication between factories cannot be fully guaranteed using traditional centralised approaches. Emerging blockchain technology can solve this problem due to its characteristics such as decentralisation and security. In this context, an integrated optimisation problem of multi-factory production and blockchain-secured collaborative maintenance is studied in this paper. Two scenarios are introduced with respective Q learning-based solution frameworks to solve the integrated problem. In the simulation scenario, preventive maintenance (PM) with flexible time windows is integrated with multi-factory production scheduling for reducing the probability of machine failures, and an initial integrated optimisation scheme is obtained. To make it more realistic, inevitable failures are considered in the actual production scenario, and the proposed collaborative maintenance strategy is triggered. Specifically, a corrective maintenance (CM) strategy is carried out immediately on the failed machine in case of a failure, followed by the PM on machines of the same type as the failed machine in other factories and the rescheduling of unprocessed jobs. Through a series of numerical studies, the effectiveness of the proposed optimisation approach and maintenance strategy is validated, and some interesting managerial implications also rise.
Journal: International Journal of Production Research
Pages: 3685-3702
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.2002968
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002968
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# input file: TPRS_A_1987548_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Chang Xu
Author-X-Name-First: Chang
Author-X-Name-Last: Xu
Author-Name: Tijun Fan
Author-X-Name-First: Tijun
Author-X-Name-Last: Fan
Author-Name: Qi Zheng
Author-X-Name-First: Qi
Author-X-Name-Last: Zheng
Author-Name: Yang Song
Author-X-Name-First: Yang
Author-X-Name-Last: Song
Title: Contract selection for fresh produce suppliers cooperating with a platform under a markdown-pricing policy
Abstract: 
 Since some platforms such as Amazon, and JD.com are expanding their business into the fresh produce market, traditional fresh produce suppliers are seeking to cooperate with them. However, markdown-pricing policies caused by the interaction between the time-varying quality of fresh produce and the time-varying price strongly influence the choice of the cooperation mode in current research. A wholesale price contract (WPC) and a consignment revenue-sharing contract (CRSC) are two common modes for cooperation between the fresh produce supplier and the platform. Accordingly, the markdown-pricing policies for fresh produce under these two contracts are analysed. The impacts of the deterioration rate and the price markdown time on profit and the pricing of the supplier and the platform are also discussed. Finally, the contracting strategy of the supplier and the contracting preference of the platform are examined. The results show that a CRSC is always beneficial for the supplier but not for the platform: if the price-sensitivity increase in the second period is small, then the platform is worse off under a CRSC when the price markdown time is moderate or the market size is small. However, the platform prefers a CRSC due to the high deterioration rate of fresh produce.
Journal: International Journal of Production Research
Pages: 3756-3780
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1987548
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1987548
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# input file: TPRS_A_1894497_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xue-Yan Wu
Author-X-Name-First: Xue-Yan
Author-X-Name-Last: Wu
Author-Name: Zhi-Ping Fan
Author-X-Name-First: Zhi-Ping
Author-X-Name-Last: Fan
Author-Name: Bing-Bing Cao
Author-X-Name-First: Bing-Bing
Author-X-Name-Last: Cao
Title: An analysis of strategies for adopting blockchain technology in the fresh product supply chain
Abstract: 
 This paper investigates the strategies for adopting blockchain technology in the fresh product supply chain (FPSC) consisting of a supplier, a third-party logistics service provider (3PL) and an e-tailer. We analyse the optimal strategies of FPSC members under the benchmark scenario where the FPSC does not adopt blockchain technology and those under the three scenarios where the supplier, 3PL and e-tailer lead the construction of the blockchain-based traceability system (BTS), respectively. We find that adopting blockchain technology is not always the optimal decision for the FPSC, which is related to the consumers’ acceptance degree for the product without blockchain technology, the deterioration rate of the fresh product and the allocation proportion of traceability cost of FPSC members when adopting blockchain technology. Regardless of the power and status of each member in the FPSC, it can lead the construction of the BTS. From the perspective of whole FPSC’s profit maximisation, the leader of the FPSC should lead the construction of the BTS under the coordination of a two-part tariff contract. This study provides valuable insights for FPSCs to adopt blockchain technology.
Journal: International Journal of Production Research
Pages: 3717-3734
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1894497
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1894497
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# input file: TPRS_A_1894367_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xiaoping Xu
Author-X-Name-First: Xiaoping
Author-X-Name-Last: Xu
Author-Name: Mengying Zhang
Author-X-Name-First: Mengying
Author-X-Name-Last: Zhang
Author-Name: Guowei Dou
Author-X-Name-First: Guowei
Author-X-Name-Last: Dou
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Title: Coordination of a supply chain with an online platform considering green technology in the blockchain era
Abstract: 
 This paper considers a supply chain consisting of a manufacturer and a retailer. The manufacturer sells its products through the retailer and an online platform and adopts green technology in the blockchain era. The platform can operate with marketplace mode or reselling mode. The network effect is considered to reflect the power of the platform to enlarge the potential market size. In the decentralised supply chain, the online platform encroaches the offline demand despite the same retail price. The increase of the network coefficient improves the abatement level, and benefits the manufacturer and the platform but damages the retailer’s profit. For the supply chain coordination, the abatement level with reselling mode in the centralised supply chain is less than that in the decentralised supply chain if the network coefficient is high. Both marketplace mode and reselling mode can coordinate the supply chain if the network coefficient is low. Blockchain technology helps the products become greener and brings more profits for the manufacturer and the platform. And it induces supply chain coordination. Based on real data of a supply chain, its profit is increased by 3% after coordination.
Journal: International Journal of Production Research
Pages: 3793-3810
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1894367
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1894367
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# input file: TPRS_A_1953182_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xiutian Shi
Author-X-Name-First: Xiutian
Author-X-Name-Last: Shi
Author-Name: Shuning Yao
Author-X-Name-First: Shuning
Author-X-Name-Last: Yao
Author-Name: Suyuan Luo
Author-X-Name-First: Suyuan
Author-X-Name-Last: Luo
Title: Innovative platform operations with the use of technologies in the blockchain era
Abstract: 
 With the development of ecommerce and digital technologies, we have witnessed a boom of platform operations. Amid their strong growth prospects, it is observed that platforms have created controversial issues and challenges, which could be potentially solved by the combination of blockchain features. More and more studies exploring the implementation of blockchain in platform operations have appeared in recent years. In this paper, motivated by the industrial practices of different types of product selling and service platforms, we first conduct a holistic literature review of the most representative papers relevant to platform operations. Examining the value of different blockchain features in operations management field, we further review the related works on platform operations with blockchain technologies. Afterwards, we analyse the innovative applications and challenges in platforms such as physical and virtual product selling platforms, rental/sharing and on-demand service platforms. A future research agenda is established which lays the solid foundation for further studies on platform operations in the blockchain era.
Journal: International Journal of Production Research
Pages: 3651-3669
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1953182
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1953182
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# input file: TPRS_A_1976434_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Qingyun Xu
Author-X-Name-First: Qingyun
Author-X-Name-Last: Xu
Author-Name: Yi He
Author-X-Name-First: Yi
Author-X-Name-Last: He
Title: Optimal information disclosure strategies for a retail platform in the blockchain technology era
Abstract: 
 This paper considers a retail platform selling a product to consumers and voluntarily discloses product quality information by using blockchain technology (BCT). Consumers decide whether to deliberate before making purchase decisions. We develop an analytical model to explore the effects of information disclosure strategies on the retail platform’s pricing and consumers’ deliberation decisions. Some interesting results are obtained. First, regardless of the information disclosure strategy, consumers’ deliberation and purchasing decisions depend on the deliberation cost and product price. Consumers will only deliberate if the price is at the medium level and the deliberation cost is not too high. Second, when the disclosure cost is high, the retail platform either stimulates or prevents consumer deliberation; however, when the disclosure cost is at a medium interval, the retail platform’s pricing decision depends on its information disclosure strategy. Specifically, when disclosing quality information, the retail platform will implement the stimulated deliberation (SD) or prevented deliberation (PD) strategy and will never adopt the sold at a low price (SL) strategy; however, when quality information is withheld, the retail platform will only adopt the PD strategy. Third, we identify the conditions under which the retail platform should disclose quality information when facing different disclosure costs.
Journal: International Journal of Production Research
Pages: 3781-3792
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1976434
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1976434
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# input file: TPRS_A_1961038_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bin Shen
Author-X-Name-First: Bin
Author-X-Name-Last: Shen
Author-Name: Ming Cheng
Author-X-Name-First: Ming
Author-X-Name-Last: Cheng
Author-Name: Ciwei Dong
Author-X-Name-First: Ciwei
Author-X-Name-Last: Dong
Author-Name: Yixuan Xiao
Author-X-Name-First: Yixuan
Author-X-Name-Last: Xiao
Title: Battling counterfeit masks during the COVID-19 outbreak: quality inspection vs. blockchain adoption
Abstract: 
 The coronavirus pandemic (COVID-19) threatens people’s health. During the COVID-19 outbreak, people are encouraged to wear masks to reduce the spread of the virus. With the strong demand for masks, it has come a boom in counterfeit production. Combating counterfeit masks is vital and urgent to reduce the risks for public health. Motivated by the actual practices during the COVID-19, we examine how quality inspection and blockchain adoption help combat counterfeit masks. We find that quality inspection may not be always effective, as the government will tolerate the presence of counterfeit masks if the presence of the counterfeits is not significant. Comparing quality inspection with blockchain adoption, when the spread of COVID-19 is mild, authentic mask sellers may be encouraged to use the blockchain technology, which can increase their profits and reduce the social health risk. Furthermore, we extend our model to investigate the impacts of endogenous quality. Both quality inspection and blockchain adoption can induce low-quality mask sellers to enhance thequality level. When the number of counterfeit masks is increasing, encouraging the high-quality mask sellers to adopt the blockchain technology is effective to reduce social health risk when the spread of the coronavirus is rapid.
Journal: International Journal of Production Research
Pages: 3634-3650
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1961038
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1961038
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# input file: TPRS_A_1972180_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mengqi Liu
Author-X-Name-First: Mengqi
Author-X-Name-Last: Liu
Author-Name: Xuefeng Zhang
Author-X-Name-First: Xuefeng
Author-X-Name-Last: Zhang
Author-Name: Huamin Wu
Author-X-Name-First: Huamin
Author-X-Name-Last: Wu
Title: The impact of platform restriction on manufacturer quality transparency in the blockchain era
Abstract: 
 This study investigates a supply chain comprising of a manufacturer and a retail platform, wherein the former decides the quality information transparency strategy of products and the latter determines whether or not to implement price parity clauses (PPCs). The manufacturer can directly sell the end-of-season product to the end-consumer market and indirectly via the retail platform. Specifically, this study considers two quality information transparency strategies (i.e. ex-ante blockchain-adoption and ex-post voluntary disclosure) that differ on whether the manufacturer’s decision on quality information transparency strategy is made before or after observing the actual product quality. Results show that the manufacturer may prefer the ex-ante blockchain-adoption strategy in specific conditions but maintains the flexibility of information disclosure under ex-post voluntary disclosure strategy. Moreover, the implementation of PPCs significantly reduces the manufacturer’s incentive to disclose a large extent of quality information transparency when the effort cost is high or the service effect coefficient is low. By contrast, the manufacturer is more likely to adopt information transparency strategies under PPCs when the effort cost is low and the service effect coefficient is high. More interestingly, contrary to theories of harm from PPCs, the implementation of PPCs may simultaneously benefit the manufacturer and retail platform, achieving a ‘win-win' situation.
Journal: International Journal of Production Research
Pages: 3582-3598
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1972180
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1972180
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1930239_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jiaguo Liu
Author-X-Name-First: Jiaguo
Author-X-Name-Last: Liu
Author-Name: Huimin Zhang
Author-X-Name-First: Huimin
Author-X-Name-Last: Zhang
Author-Name: Lu Zhen
Author-X-Name-First: Lu
Author-X-Name-Last: Zhen
Title: Blockchain technology in maritime supply chains: applications, architecture and challenges
Abstract: 
 As an essential carrier of cross-border trade, the maritime supply chain has always been plagued by long service cycles, complex structures, and heterogeneous information from multiple sources. In this context, as a distributed database system, the emerging blockchain technology has the characteristics of decentralization, tamper-proofness, and traceability, which can be correctly applied in the maritime industry to promote its transformation and upgrading. However, blockchain application in the maritime supply chain remains notably absent, leaving this critical topic almost unexplored. Thus, we first conduct a comprehensive literature review and an industrial investigation to clarify the current status, problems, and challenges of the blockchain-based maritime supply chain system (BMSCS). We construct a new operation management mode of the maritime supply chain and propose an integrated BMSCS suitable for global economic development. Finally, based on comparison of the current research results, reasonable suggestions for the future operation and development of the BMSCS are put forward to enhance the coordination among members, accelerate the application of blockchain in the maritime industry, and gradually realise the intelligent operation of the maritime supply chain.
Journal: International Journal of Production Research
Pages: 3547-3563
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1930239
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1930239
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# input file: TPRS_A_2050828_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Feng Tao
Author-X-Name-First: Feng
Author-X-Name-Last: Tao
Author-Name: Yao-Yu Wang
Author-X-Name-First: Yao-Yu
Author-X-Name-Last: Wang
Author-Name: Shi-Hu Zhu
Author-X-Name-First: Shi-Hu
Author-X-Name-Last: Zhu
Title: Impact of blockchain technology on the optimal pricing and quality decisions of platform supply chains
Abstract: 
 We investigate how blockchain technology influences optimal pricing and quality decisions under two different supply chain structures. In both cases, the supplier is the leader and plays a Stackelberg game with downstream platform(s). Specifically, the supplier determines the wholesale prices and quality levels of the products, and the platform(s) decides the selling prices. Based on our analysis, we find that when consumer acceptance of blockchain is low, among the two products in the single platform, the products with blockchain technology have not only a high quality but also a low price. However, in the case of the two competitive platforms, although blockchain will also enable the platform that uses this technology to provide products with a high quality and low price, its advantages are not obvious. Nevertheless, in comparing the two cases, when consumer acceptance is high, the two competing platforms tend to provide products with a high quality and low price, regardless of whether or not the products use blockchain technology. Our conclusions reveal that although blockchain will benefit a supplier and consumers, in some cases, the supplier will have an incentive to decrease the quality level of the products with blockchain technology, which will eventually negatively affect consumers.
Journal: International Journal of Production Research
Pages: 3670-3684
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2050828
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2050828
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# input file: TPRS_A_1970849_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Kunpeng Li
Author-X-Name-First: Kunpeng
Author-X-Name-Last: Li
Author-Name: Jun-Yeon Lee
Author-X-Name-First: Jun-Yeon
Author-X-Name-Last: Lee
Author-Name: Amir Gharehgozli
Author-X-Name-First: Amir
Author-X-Name-Last: Gharehgozli
Title: Blockchain in food supply chains: a literature review and synthesis analysis of platforms, benefits and challenges
Abstract: 
 The globalisation of the food industry increases the complexity and the difficulty in enhancing efficiency and solving issues in food supply chains. Blockchain is a promising decentralised information technology that could benefit food supply chains by reducing transaction cost and time, increasing process transparency, security, and efficiency, as well as building trust among participants. In this paper, we introduce the major blockchain platforms currently used in food supply chains and conduct a synthesis analysis to explore the benefits and challenges of blockchain technology in the food industry. We demonstrate that blockchain enables unprecedented visibility at each step of the food supply chain, helps increase transaction transparency, food safety, and quality, and also reduces food fraud and waste. Furthermore, it serves as a digital solution for reducing operational costs and improving efficiency in food supply chains.
Journal: International Journal of Production Research
Pages: 3527-3546
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1970849
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1970849
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# input file: TPRS_A_2072785_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Liu Yang
Author-X-Name-First: Liu
Author-X-Name-Last: Yang
Author-Name: Yaodong Ni
Author-X-Name-First: Yaodong
Author-X-Name-Last: Ni
Author-Name: Chi-To Ng
Author-X-Name-First: Chi-To
Author-X-Name-Last: Ng
Title: Blockchain-enabled traceability and producer’s incentive to outsource delivery
Abstract: 
 Applications of the blockchain technology in supply chains have attracted extensive attention in both academia and industries. However, little research has investigated the effects of the blockchain technology on firms’ operational strategies. In this paper, we investigate the impacts of the traceability enabled by the blockchain technology on a producer’s decision whether to outsource delivery to a third-party logistics firm. We find that without the blockchain technology, the logistics firm has a moral hazard—an incentive to set the delivery quality at the lowest level even though improving the delivery quality is for free. The traceability enabled by the blockchain technology can resolve the logistics firm’s moral hazard and encourage the producer to improve the production quality. Furthermore, when the delivery is cost-efficient for the producer, the traceability enabled by the blockchain technology motivates the producer to outsource the delivery to the logistics firm; otherwise, the producer’s outsourcing decision is not affected. When quality cost is low, the blockchain technology makes the logistics firm improve its delivery quality significantly and encourages the producer to improve the production quality. When the quality cost is moderate, only under certain conditions, the blockchain technology has effects on both parties’ decisions.
Journal: International Journal of Production Research
Pages: 3811-3828
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2072785
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2072785
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# input file: TPRS_A_1994163_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lingpeng Meng
Author-X-Name-First: Lingpeng
Author-X-Name-Last: Meng
Author-Name: Junliang He
Author-X-Name-First: Junliang
Author-X-Name-Last: He
Author-Name: Shaolong Hu
Author-X-Name-First: Shaolong
Author-X-Name-Last: Hu
Author-Name: Chuanfeng Han
Author-X-Name-First: Chuanfeng
Author-X-Name-Last: Han
Title: Strategic reliable supply chain network design: determining tradeoffs between cost and risk
Abstract: 
 The design of a supply chain network (SCN) should address two conflicting objectives, i.e. inexpensive yet reliable operation. This paper presents models to choose supply facilities and determine distribution options while considering the expected risk of not serving customers attributed to supply shortages. The goal is to design a reliable network with a lower cost under traditional cost objectives. We formulate a stochastic mixed-integer biobjective programming model considering the protection of facilities and solve this problem with a progressive hedging algorithm (PHA). We examine the tradeoff curve between the cost and risk through a case study involving Shanghai in China. The results indicate that substantial improvements in reliability can be reached with a limited increase in the total cost.
Journal: International Journal of Production Research
Pages: 3621-3633
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1994163
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1994163
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# input file: TPRS_A_2027037_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jianghua Wu
Author-X-Name-First: Jianghua
Author-X-Name-Last: Wu
Author-Name: Jiahao Yu
Author-X-Name-First: Jiahao
Author-X-Name-Last: Yu
Title: Blockchain’s impact on platform supply chains: transaction cost and information transparency perspectives
Abstract: 
 This study examines the impact of blockchain technology on platform supply chains from the perspectives of information transparency and transaction cost. We build a hybrid-format supply chain in which one supplier adopts an agency selling format and sells a product through the platform by paying a commission fee, while the other supplier adopts a reselling format. A game theory model is adopted to solve the key question: What is the best blockchain strategy for each supply chain member? Our research shows that blockchain technology can be a powerful weapon for platforms to adjust prices and control the market. As for the two suppliers in our supply chain, they will become better off with blockchain technology due to the elimination of information asymmetry and transaction costs. Moreover, the optimal strategies for platforms strongly depend on transaction cost, commission rate, and blockchain’s operation cost. Furthermore, we also provide a side-payment contract to help different players achieve Pareto improvement, thus reaching a win-win-win outcome. Our findings not only provide guidance for the adoption of blockchains in the platform economy but also complement the gap in research on information sharing.
Journal: International Journal of Production Research
Pages: 3703-3716
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2027037
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2027037
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# input file: TPRS_A_2013560_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Kannan Govindan
Author-X-Name-First: Kannan
Author-X-Name-Last: Govindan
Author-Name: Arash Khalili Nasr
Author-X-Name-First: Arash Khalili
Author-X-Name-Last: Nasr
Author-Name: Mohammad Saeed Heidary
Author-X-Name-First: Mohammad
Author-X-Name-Last: Saeed Heidary
Author-Name: Saeede Nosrati-Abarghooee
Author-X-Name-First: Saeede
Author-X-Name-Last: Nosrati-Abarghooee
Author-Name: Hassan Mina
Author-X-Name-First: Hassan
Author-X-Name-Last: Mina
Title: Prioritizing adoption barriers of platforms based on blockchain technology from balanced scorecard perspectives in healthcare industry: a structural approach
Abstract: 
 Since the advent of blockchain technology (BT), extensive research has explored using this technology in non-financial cases. The healthcare industry is one of the non-financial sectors that BT has significantly impacted. In this paper, for the first time, barriers to implement BT-based platforms from a balanced scorecard perspective in the healthcare sector are introduced, and these barriers are prioritized using a structural approach based on the weighted influence non-linear gauge system. Unlike other structural models such as decision-making trial and evaluation laboratory (DEMATEL), in this approach, both strength and influence intensity of components are considered in the ranking process. The proposed approach is applied in networks that have a hierarchical structure and intertwined components. The performance of the proposed approach is evaluated using the ranking of BT-based platform adoption barriers in the healthcare industry in Iran. The results show that financial issues, security issues, lack of expertise and knowledge, and uncertain government policies are the most important barriers to BT adoption in the healthcare industry.
Journal: International Journal of Production Research
Pages: 3512-3526
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.2013560
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2013560
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# input file: TPRS_A_2087567_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Wu Yang
Author-X-Name-First: Wu
Author-X-Name-Last: Yang
Author-Name: Wang Ziyang
Author-X-Name-First: Wang
Author-X-Name-Last: Ziyang
Author-Name: Zhou Xiaohao
Author-X-Name-First: Zhou
Author-X-Name-Last: Xiaohao
Author-Name: Yao Jianming
Author-X-Name-First: Yao
Author-X-Name-Last: Jianming
Title: The optimisation research of Blockchain application in the financial institution-dominated supply chain finance system
Abstract: 
 As an information technology that could significantly improve supply chain visibility and process automation, blockchain has been extensively applied in the field of supply chain finance (SCF). However, tradeoffs among the security, the operation cost, and the efficiency of the blockchain system may cause the SCF system dominated by a financial institution to inevitably fall into the dilemmas of risky or un-economic if the blockchain technology is applied inappropriately. Therefore, the objective of this paper is to optimise the blockchain application in the financial institution-based SCF system. We first analyse the application of blockchain security in SCF, and then the performance tradeoffs of blockchain and its impact on the performance of the supported SCF system. Based on the analysis above, an optimisation approach has been proposed and a corresponding non-linear integer programming (NIP) model has been constructed to select the best blockchain design schemes for the SCF system to achieve overall optimal in terms of security, cost, and efficiency. A designed ant colony algorithm is used to solve the optimisation problem. An application case analysis is used to verify the feasibility and effectiveness of the optimisation model.
Journal: International Journal of Production Research
Pages: 3735-3755
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2087567
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2087567
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# input file: TPRS_A_2036851_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Wei Liu
Author-X-Name-First: Wei
Author-X-Name-Last: Liu
Author-Name: Ruirui Chai
Author-X-Name-First: Ruirui
Author-X-Name-Last: Chai
Author-Name: Xinyan Cao
Author-X-Name-First: Xinyan
Author-X-Name-Last: Cao
Author-Name: Xiang Fang
Author-X-Name-First: Xiang
Author-X-Name-Last: Fang
Author-Name: Yu Yang
Author-X-Name-First: Yu
Author-X-Name-Last: Yang
Title: Promoting product idea contribution of heterogeneous users for product improvement in online innovation communities
Abstract: 
 Collaboration between firms and product users has been widely practiced to enhance the efficiency and quality of product development. We consider a collaborative product improvement setting where a sponsoring firm and product users jointly create or promote product design ideas through firm-sponsored online user innovation communities (FOUICs). Using a differential-game framework, we study a benchmark case in which product users involved in FOUICs are homogeneous in their innovative contribution capacities and propensities. We then incorporate users’ heterogeneity such that product users are distinguished into lead users and common users. Our analytical result shows that the equilibrium effort levels and utilities of both the sponsoring firm and product users may increase or decrease with a change in the output elasticities of product design ideas or in the cost elasticities of the effort levels. Moreover, lead users’ equilibrium effort level and utility are more sensitive to the elasticity parameters of product users’ effort than those of common users, and lead users obtain a higher total incentive reward than that of common users. Last, we compare the benchmark model and the extended model to identify the condition under which one model outperforms the other one for both the sponsoring firm and product users.
Journal: International Journal of Production Research
Pages: 3599-3620
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2036851
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2036851
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# input file: TPRS_A_1884308_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ting Zhang
Author-X-Name-First: Ting
Author-X-Name-Last: Zhang
Author-Name: Peimiao Li
Author-X-Name-First: Peimiao
Author-X-Name-Last: Li
Author-Name: Ningning Wang
Author-X-Name-First: Ningning
Author-X-Name-Last: Wang
Title: Multi-period price competition of blockchain-technology-supported and traditional platforms under network effect
Abstract: 
 We build a multi-period pricing model between a blockchain-technology-supported platform and a traditional platform, where the blockchain-technology-supported platform provides a higher value for customers. Customers are influenced by network effect, that is, they value a platform more if the platform has more users. As either platform can adopt static pricing or dynamic pricing, four scenarios may occur. By deriving the equilibrium of each scenario, we reveal the 'Matthew effect' caused by network effect, that platform advantage (from adopting blockchain technology) or disadvantage (from not adopting blockchain technology) accumulates as time goes by. Thus, platforms are advised to adopt the blockchain technology antecedent to the competitors. Network effect, which amplifies the benefit of initial users, may intensify price competition and harm both platforms. By comparing the four scenarios, we derive the equilibrium pricing strategies: when network effect is weak, one platform adopts static pricing and the other adopts dynamic pricing; when network effect is medium, the blockchain-technology-supported platform adopts static pricing and the traditional platform adopts dynamic pricing; and when network effect is strong, both platforms adopt dynamic pricing. Dynamic pricing is more desirable for the traditional platform relative to the blockchain-technology-supported platform.
Journal: International Journal of Production Research
Pages: 3829-3843
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1884308
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1884308
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# input file: TPRS_A_2001601_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lu Liu
Author-X-Name-First: Lu
Author-X-Name-Last: Liu
Author-Name: Yongjian Li
Author-X-Name-First: Yongjian
Author-X-Name-Last: Li
Author-Name: Tao Jiang
Author-X-Name-First: Tao
Author-X-Name-Last: Jiang
Title: Optimal strategies for financing a three-level supply chain through blockchain platform finance
Abstract: 
 The application of blockchain technology solves the trust problem between core enterprises (CEs), small and medium-sized enterprises (SMEs), and commercial banks, facilitating CEs and commercial banks to provide guarantee for SMEs and finance them, respectively. This study considers a three-level supply chain composed of a manufacturer, a distributor, and a capital-constrained retailer, and explores the operational strategies of blockchain platform finance (BPF), a supply chain finance mode enabled by blockchain technology. First, optimal decision solutions are obtained through decision and parameter sensitivity analyses. Second, by comparing the BPF and SME independent finance (SIF) modes, we obtain the applicable BPF mode conditions; for instance, when the retailer’s initial capital is low and the production cost is high, BPF is the better option for the manufacturer, distributor, and retailer compared to SIF. Third, we find that risk sharing improves the financing efficiency of the BPF mode. This study provides a theoretical basis for decision makers to implement blockchain supply chain finance at three levels: joint financing and operation decision-making, financing mode selection, and financing efficiency improvement.
Journal: International Journal of Production Research
Pages: 3564-3581
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.2001601
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2001601
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# input file: TPRS_A_2185397_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Author-Name: Guo Li
Author-X-Name-First: Guo
Author-X-Name-Last: Li
Author-Name: Xiaohang Yue
Author-X-Name-First: Xiaohang
Author-X-Name-Last: Yue
Title: Platform supply chain innovations in the blockchain era: the ABCDE framework
Abstract: 
 Platforms are giants in today’s operations. Companies like Amazon and eBay are huge enterprises which belong to top enterprises in the world. In this article, we discuss platform supply chain innovations in the blockchain era. We first search the literature and identify the level of popularity of the topic over the past years. Next, we review some closely related studies in the literature and introduce the featured papers in this IJPR special issue. After that, we identify research gaps, present the ABCDE framework and propose a future research agenda.
Journal: International Journal of Production Research
Pages: 3505-3511
Issue: 11
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2023.2185397
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2185397
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# input file: TPRS_A_2081099_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Erik Flores-García
Author-X-Name-First: Erik
Author-X-Name-Last: Flores-García
Author-Name: Yongkuk Jeong
Author-X-Name-First: Yongkuk
Author-X-Name-Last: Jeong
Author-Name: Sichao Liu
Author-X-Name-First: Sichao
Author-X-Name-Last: Liu
Author-Name: Magnus Wiktorsson
Author-X-Name-First: Magnus
Author-X-Name-Last: Wiktorsson
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Title: Enabling industrial internet of things-based digital servitization in smart production logistics
Abstract: 
 Digital servitization (DS) enabled by the Industrial Internet of Things (IIoT) is essential for securing long-term competitiveness in manufacturing. The literature identifies the need for developing data models for multichannel communications across IIoT devices that fulfil the DS vision. This is crucial for avoiding isolated systems based on proprietary solutions and for promoting data sharing and interoperability across existing and future DS applications. Accordingly, this study proposes a data model for multichannel communication that facilitates IIoT-enabled DS for smart production logistics (SPL). We present three findings from a case study focussing on material handling in a manufacturing company. First, this study provides a model with four modelling profiles, including IIoT devices, databases, and services for multichannel communication. Second, it shows how the proposed modelling profiles transfer information across monitoring, control, optimisation, and autonomous decision services. Third, it presents the operational benefits of applying the proposed data models, including improvements in the delivery, makespan, and energy of material handling. These findings are essential for capturing, processing, and transferring information across products, services, and software databases in IIoT-enabled DS for SPL. They are relevant for manufacturing managers and academics and improve our understanding of IIoT-enabled DS's deployment for SPL in manufacturing.
Journal: International Journal of Production Research
Pages: 3884-3909
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2081099
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2081099
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# input file: TPRS_A_1969462_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Chao Liu
Author-X-Name-First: Chao
Author-X-Name-Last: Liu
Author-Name: Pai Zheng
Author-X-Name-First: Pai
Author-X-Name-Last: Zheng
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Title: Digitalisation and servitisation of machine tools in the era of Industry 4.0: a review
Abstract: 
 Machine tools play a pivotal role in the manufacturing world since their performance significantly affects the product quality and production efficiency. In the era of Industry 4.0, machine tools are expected to have a higher level of accessibility, connectivity, intelligence, adaptivity, and autonomy. With the rapid development and application of various Industry 4.0 technologies, digitalisation and servitisation of machine tools have become a new research trend. However, few review articles on the development of machine tools in the context of Industry 4.0 have been reported. To understand the current status of digitalisation and servitisation of machine tools, this paper provides a systematic literature review combining both bibliometric and qualitative analysis. Our review results provide a comprehensive and in-depth understanding of recent advancements of digitalisation and servitisation of machine tools, including the key enabling technologies, methods, standards, architectures, and applications. Furthermore, we propose a novel conceptual framework of Cyber-Physical Machine Tool (CPMT) as a systematic approach to achieving digitalisation and servitisation of next-generation machine tools. Finally, major research issues, challenges, and future research directions are discussed. This work will help researchers and industrial practitioners spark new ideas for developing the next-generation machine tools in the era of Industry 4.0.
Journal: International Journal of Production Research
Pages: 4069-4101
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1969462
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1969462
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# input file: TPRS_A_1959666_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Majid Azadi
Author-X-Name-First: Majid
Author-X-Name-Last: Azadi
Author-Name: Zohreh Moghaddas
Author-X-Name-First: Zohreh
Author-X-Name-Last: Moghaddas
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Author-Name: Reza Farzipoor Saen
Author-X-Name-First: Reza
Author-X-Name-Last: Farzipoor Saen
Title: Assessing the sustainability of cloud computing service providers for Industry 4.0: a state-of-the-art analytical approach
Abstract: 
 While interests in Industry 4.0 technologies such as cloud computing and the Internet of Things (IoT) are growing, an ongoing challenge is to properly evaluate the performance of the providers of such technologies. Methods have been developed and applied to assess the efficiency of cloud service providers (CSPs) for Industry 4.0. However, most existing methods suffer from such shortcomings as subjective weights and computing complexity, rendering it difficult to succinctly differentiate the performance of CSPs in a competitive market. Besides, the literature has not taken into account many different types of data such as ratios, integers, and undesirable factors that can affect the performance of CSPs. Most importantly, most existing studies do not consider the sustainability of CSPs in evaluating their performance. To address the above issues, we present a comprehensive analytical method based on data envelopment analysis (DEA) to gauge the sustainability of CSPs for Industry 4.0. Validating the usefulness of our method using a real-life dataset, we provide not only a viable means with sound academic underpinning but also significant managerial insights for practitioners to assess the sustainability of CSPs for Industry 4.0.
Journal: International Journal of Production Research
Pages: 4196-4213
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1959666
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1959666
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# input file: TPRS_A_2056860_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Changchun Liu
Author-X-Name-First: Changchun
Author-X-Name-Last: Liu
Author-Name: Haihua Zhu
Author-X-Name-First: Haihua
Author-X-Name-Last: Zhu
Author-Name: Dunbing Tang
Author-X-Name-First: Dunbing
Author-X-Name-Last: Tang
Author-Name: Qingwei Nie
Author-X-Name-First: Qingwei
Author-X-Name-Last: Nie
Author-Name: Shipei Li
Author-X-Name-First: Shipei
Author-X-Name-Last: Li
Author-Name: Yi Zhang
Author-X-Name-First: Yi
Author-X-Name-Last: Zhang
Author-Name: Xuan Liu
Author-X-Name-First: Xuan
Author-X-Name-Last: Liu
Title: A transfer learning CNN-LSTM network-based production progress prediction approach in IIoT-enabled manufacturing
Abstract: 
 In make-to-order manufacturing workshops, accurate prediction value of production progress (PP) is a significant reference index for dynamic optimisation of production process and on-time delivery of production orders. The implementation of big data and Industrial Internet of Things (IIoT) in manufacturing workshops makes it possible to obtain large amounts of production data which can affect PP. However, the particularities of massive historical order data are not fully excavated and the amount of target order data is insufficient to support the training of high-precision prediction model, which will result in bad training approximation and generalisation. To overcome these shortcomings, a PP prediction approach consisting of two models with transfer learning (TL) is proposed. TL can avoid the training of PP prediction model from scratch every time. Consequently, computational efficiency can be greatly improved. A convolutional neural network (CNN) model with TL is devised to excavate the comprehensive features from historical and current orders. Additionally, a long short-term memory network (LSTM) model with TL is constructed to ﬁt the nonlinear relation of the features provided by CNN-TL model for PP prediction. In order to validate the performance of the proposed PP prediction approach, comparative experiments of eight algorithms are conducted in an IIoT-enabled manufacturing workshop.
Journal: International Journal of Production Research
Pages: 4045-4068
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2056860
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2056860
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# input file: TPRS_A_1953181_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Zhuming Bi
Author-X-Name-First: Zhuming
Author-X-Name-Last: Bi
Author-Name: Yan Jin
Author-X-Name-First: Yan
Author-X-Name-Last: Jin
Author-Name: Paul Maropoulos
Author-X-Name-First: Paul
Author-X-Name-Last: Maropoulos
Author-Name: Wen-Jun Zhang
Author-X-Name-First: Wen-Jun
Author-X-Name-Last: Zhang
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Title: Internet of things (IoT) and big data analytics (BDA) for digital manufacturing (DM)
Abstract: 
 This paper aims to investigate the impact of enterprise architecture (EA) on system capabilities in dealing with changes and uncertainties in globalised business environments. Enterprise information systems are viewed as information systems to acquire, process, and utilise data in decision-making supports at all levels and domains of businesses, and Internet of things (IoT), big data analytics (BDA), and digital manufacturing (DM) are introduced as representative enabling technologies for data collection, processing, and utilisation in manufacturing applications. The historical development of manufacturing technologies is examined to understand the evolution of system paradigms. The Shannon entropy is adopted to measure the complexity of systems and illustrate the roles of EAs in managing system complexity and achieving system stability in the long term. It is our argument that existing EAs sacrifice system flexibility, resilience, and adaptability for the reduction of system complexity; note that higher adaptability is critical to make a manufacturing system successfully. New EA is proposed to maximise system capabilities for higher flexibility, resilience, and adaptability. The potentials of the proposed EA to modern manufacturing are explored to identify critical research topics with illustrative examples from an application perspective.
Journal: International Journal of Production Research
Pages: 4004-4021
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1953181
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1953181
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2003462_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xinlai Liu
Author-X-Name-First: Xinlai
Author-X-Name-Last: Liu
Author-Name: Yishuo Jiang
Author-X-Name-First: Yishuo
Author-X-Name-Last: Jiang
Author-Name: Zicheng Wang
Author-X-Name-First: Zicheng
Author-X-Name-Last: Wang
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Author-Name: H. H. Cheung
Author-X-Name-First: H. H.
Author-X-Name-Last: Cheung
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: imseStudio: blockchain-enabled secure digital twin platform for service manufacturing
Abstract: 
 The manufacturing industry is experiencing a service-oriented transformation in the digitalisation era. However, many small and middle enterprises (SMEs) still rely on traditional manufacturing patterns in which they can hardly servitise manufacturing resources due to the limited budget and poor digitalisation capability. To servitise manufacturing resources, this paper proposes unified five-layer blockchain-enabled secure digital twin platform architecture, followed by its core enabling components and technologies. Firstly, a service-oriented digital twinning model is developed to transform physical resources into digital services. Secondly, a rule-based off-chain matching mechanism is designed to bridge customers’ orders with manufacturing services. Thirdly, service-oriented architecture (SOA) is adopted as the major methodology to design and develop the whole blockchain platform. Four blockchain frontend services are developed using React.js, whilst the blockchain backend is developed using private Ethereum blockchain and InterPlanetary File System (IPFS). Finally, an experimental case is conducted based on the 3D printing scenario to verify the effectiveness and efficiency of the proposed platform, named imseStudio. The results show that it not only provides an effective solution to digitalise manufacturing resources but also promotes the transformation towards service manufacturing.HighlightsBlockchain-enabled secure digital twin platform is developed to servitise manufacturing resourcesService-oriented digital twinning model is developed to transform physical resources into digital servicesRule-based off-chain matching mechanism is built to bridge customers’ orders with 3D printerFour blockchain explorers are developed to facilitate 3D printing services
Journal: International Journal of Production Research
Pages: 3984-4003
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.2003462
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2003462
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# input file: TPRS_A_2117868_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Baozhuang Niu
Author-X-Name-First: Baozhuang
Author-X-Name-Last: Niu
Author-Name: Jianhua Zhang
Author-X-Name-First: Jianhua
Author-X-Name-Last: Zhang
Author-Name: Zihao Mu
Author-X-Name-First: Zihao
Author-X-Name-Last: Mu
Title: IoT-enabled delivery time guarantee in logistics outsourcing and efficiency improvement
Abstract: 
 Industrial Internet of Things (IoT) technologies have been widely implemented in today’s logistics operations to reduce the handling time and improve service efficiency. This enables a firm to promise a delivery time (PDT) when selling products, which improves customer satisfaction and enhances the firm’s brand image. However, the costly PDT logistics service should be seriously evaluated when the market competition is intensified to aggravate the firm’s cost concern. In a competitive decentralized framework, this paper investigates the value of IoT-enabled PDT quotation in a brand’s logistics outsourcing decisions. We develop three-stage optimization models and show that the brand’s production quantity and equilibrium profit exhibit non-monotonic relationships to the competition intensity degree. Given a moderate competition intensity degree, the brand developing IoT and quoting PDT suffers from imbalanced payoffs between PDT cost-saving and sales volume expansion. This distorts the PDT cost and hence, investing in the IoT-enabled logistics system might not be beneficial. This paper contributes to the existing literature by examining the impact of heterogeneous logistics service incorporating the PDT quotation on traditional quantity competition within a dual-channel supply chain.
Journal: International Journal of Production Research
Pages: 4135-4156
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2117868
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2117868
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2022803_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bin Zhou
Author-X-Name-First: Bin
Author-X-Name-Last: Zhou
Author-Name: Xingwang Shen
Author-X-Name-First: Xingwang
Author-X-Name-Last: Shen
Author-Name: Yuqian Lu
Author-X-Name-First: Yuqian
Author-X-Name-Last: Lu
Author-Name: Xinyu Li
Author-X-Name-First: Xinyu
Author-X-Name-Last: Li
Author-Name: Bao Hua
Author-X-Name-First: Bao
Author-X-Name-Last: Hua
Author-Name: Tianyuan Liu
Author-X-Name-First: Tianyuan
Author-X-Name-Last: Liu
Author-Name: Jinsong Bao
Author-X-Name-First: Jinsong
Author-X-Name-Last: Bao
Title: Semantic-aware event link reasoning over industrial knowledge graph embedding time series data
Abstract: 
 The time series data in the manufacturing process reflects the sequential state of the manufacturing system, and the fusion of temporal features into the industrial knowledge graph will undoubtedly significantly improve the knowledge process efficiency of the manufacturing system. This paper proposes a semantic-aware event link reasoning over an industrial knowledge graph embedding time series data. Its knowledge graph skeleton is constructed through a specific manufacturing process. NLTK is used to transform technical documents into a structured industrial knowledge graph. We employ deep learning (DL)-based models to obtain semantic information related to product quality prediction using time series data collected from IoT devices. Then the prediction information is attached to the specified node in the knowledge graph. Thus, the knowledge graph will describe the dynamic semantic information of manufacturing contexts. Meanwhile, a dynamic event link reasoning model that uses graph embedding to aggregate manufacturing processes information is proposed. The implicit information with industrial temporal knowledge can be further mined and inferred. The case study has shown that the proposed knowledge graph link reasoning reflects dynamic temporal characteristics. Compared to the classical knowledge graph prediction models, our model is superior to the baseline methods.
Journal: International Journal of Production Research
Pages: 4117-4134
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.2022803
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2022803
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2022234_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xiang T. R. Kong
Author-X-Name-First: Xiang T. R.
Author-X-Name-Last: Kong
Author-Name: Miaohui Zhu
Author-X-Name-First: Miaohui
Author-X-Name-Last: Zhu
Author-Name: Yu Liu
Author-X-Name-First: Yu
Author-X-Name-Last: Liu
Author-Name: Kaida Qin
Author-X-Name-First: Kaida
Author-X-Name-Last: Qin
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: An advanced order batching approach for automated sequential auctions with forecasting and postponement
Abstract: 
 In sequential auctions, all the sub-orders from a buyer need to be sorted and consolidated within a short time window for shipping. Buyer demands and sub-order arrival times are uncertain. The current auction order fulfillment is facing several challenges. Based on a re-engineered Industrial Internet-of-Things (IIoT)-enabled automation system, this paper introduces an order batching approach with forecasting and postponement. Such an approach generates batches considering time interval and buyer completion rate to minimise the total processing time of the auction orders and system response time. The buyer completion rate refers to the ratio of current cumulative and predicted purchase quantity. We use the forecasting method proposed by Kong et al. (2021) to estimate the purchasing quantity. Through a series of computational experiments using real-life data, the proposed order batching method achieves a shorter order processing time and system response time. Results show that the number of auction buyers poses no effect on the performance of the proposed approach. Key parameters of order postponement rule influence on performance.
Journal: International Journal of Production Research
Pages: 4180-4195
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.2022234
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2022234
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1955996_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jingwei Guo
Author-X-Name-First: Jingwei
Author-X-Name-Last: Guo
Author-Name: Ying Cheng
Author-X-Name-First: Ying
Author-X-Name-Last: Cheng
Author-Name: Dongxu Wang
Author-X-Name-First: Dongxu
Author-X-Name-Last: Wang
Author-Name: Fei Tao
Author-X-Name-First: Fei
Author-X-Name-Last: Tao
Author-Name: Stefan Pickl
Author-X-Name-First: Stefan
Author-X-Name-Last: Pickl
Title: Industrial Dataspace for smart manufacturing: connotation, key technologies, and framework
Abstract: 
 Smart manufacturing is a popular concept for smarter decision-making and more efficient production. Although distributed methods for data management and processing in smart manufacturing have many advantages such as low cost of adaptation and convenience for local database, some methods are hard to manage variable data sources and discover proper range of data for smart decision-making. Therefore, Dataspace is considered in this article to be a feasible and effective method. From the relation-defined perspective of utilisation of industrial Big Data, the contribution is a novel industrial Dataspace design with static structure and working flow paths for smart manufacturing. In design, the industrial Dataspace platform has been proposed to accommodate smart manufacturing characteristics with the intelligence of pay-as-you-go, like harnessing distributed heterogenous data from industrial enterprises, understanding industrial data by ontology or knowledge, corelating the data with smart applications, and enabling related decisions. A further analytical case in Surface Mounting Technology manufacturing of welding procedure is provided to illustrate the execution of customisation, focused and related decision support, and system evolution within industrial Dataspace.
Journal: International Journal of Production Research
Pages: 3868-3883
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1955996
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1955996
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2013564_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Geng Zhang
Author-X-Name-First: Geng
Author-X-Name-Last: Zhang
Author-Name: Chun-Hsien Chen
Author-X-Name-First: Chun-Hsien
Author-X-Name-Last: Chen
Author-Name: Bufan Liu
Author-X-Name-First: Bufan
Author-X-Name-Last: Liu
Author-Name: Xinyu Li
Author-X-Name-First: Xinyu
Author-X-Name-Last: Li
Author-Name: Zuoxu Wang
Author-X-Name-First: Zuoxu
Author-X-Name-Last: Wang
Title: Hybrid sensing-based approach for the monitoring and maintenance of shared manufacturing resources
Abstract: 
 With the rapid development of information technologies, shared manufacturing is proposed to meet the prevailing tendency of servitization and digitalisation in the industry. As the crucial section for performing shared manufacturing, resource monitoring and maintenance aim to detect production exceptions and ensure normal task execution. Existing research mainly uses a resource-centric strategy to acquire production-related data and make decisions for the management of shared resources. The experience data from the users/customers of the shared resources or its similar resources is rarely acquired actively in a cost-effective manner. However, the user/customer's experience data may contain essential knowledge that can be used for effective production performance identification and maintenance. To fill this gap, a hybrid sensing-based approach is proposed to perform the monitoring and maintenance of the shared manufacturing resources. It leverages both the sensor-sensed production data and user/customer-generated data for value creation in a cost-effective manner. Based on the acquired hybrid data, a service model is constructed to achieve the monitoring of the shared manufacturing resource, and a knowledge-based mechanism is designed to perform efficient maintenance. A case study is further presented to verify the effectiveness of the proposed approach.
Journal: International Journal of Production Research
Pages: 3849-3867
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.2013564
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2013564
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1970850_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Andrea de Giorgio
Author-X-Name-First: Andrea
Author-X-Name-Last: de Giorgio
Author-Name: Malvina Roci
Author-X-Name-First: Malvina
Author-X-Name-Last: Roci
Author-Name: Antonio Maffei
Author-X-Name-First: Antonio
Author-X-Name-Last: Maffei
Author-Name: Milan Jocevski
Author-X-Name-First: Milan
Author-X-Name-Last: Jocevski
Author-Name: Mauro Onori
Author-X-Name-First: Mauro
Author-X-Name-Last: Onori
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Title: Measuring the effect of automatically authored video aid on assembly time for procedural knowledge transfer among operators in adaptive assembly stations
Abstract: 
 Can automatically authored videos of industrial operators help other operators to learn procedural tasks? This question is relevant to the advent of the industrial internet of things (IIoT) and Industry 4.0, where smart machines can help human operators rather than replacing them in order to benefit from the best of humans and machines. This study considers an industrial ecosystem where procedural knowledge (PK) is quickly and effectively transferred from one operator to another. Assembly tasks are procedural in nature and present a certain complexity that still does not allow machines and their sensors to capture all the details of the operations. Especially if the assembly operation is adaptive and not fixed in terms of assembly sequence plan. In order to help the operators, videos of other operators executing the complex procedural tasks can be automatically recorded and authored from machines. This study shows by means of statistical design and analysis of experiments that expert aid can reduce the assembly time of an untrained operator, whereas automatically authored video aids can transfer PK but producing an opposite effect on the assembly time. Therefore, hybrid training methods are still necessary and trade-offs have to be considered. Managerial insights from the results suggest an unneglectable impact of the choice to digitise industrial operations too early. The experimental studies presented can act as guidelines for the correct statistical testing of innovative solutions in industry.
Journal: International Journal of Production Research
Pages: 3910-3925
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1970850
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1970850
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2116499_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Wiebke Reim
Author-X-Name-First: Wiebke
Author-X-Name-Last: Reim
Author-Name: Ebba Andersson
Author-X-Name-First: Ebba
Author-X-Name-Last: Andersson
Author-Name: Kajsa Eckerwall
Author-X-Name-First: Kajsa
Author-X-Name-Last: Eckerwall
Title: Enabling collaboration on digital platforms: a study of digital twins
Abstract: 
 Digital platforms are transforming almost every industry today and are expected to revolutionize future value creation. Digital platforms require collaboration, but this is challenging especially in the manufacturing industry where sensitive data need shared and high investments are required. Therefore, the purpose of this study is to enhance the understanding of how to successfully collaborate on digital platforms in the manufacturing industry by developing a contingency framework. The study is an explorative single case study of a digital platform. More specifically, the study examined the development process of a digital twin platform created by a large high-technological company and its collaborative actors. The results are based on 21 semi-structured interviews and reveals that actors on digital platforms can face five types of challenges that hinder a successful collaboration: disadvantages of dependency, uncertainty regarding data management, varying customer needs, insufficient work methods, and unsuitable payment models. The analysis also reveals four strategies that can be used to address the challenges: transparency strategy, incentive model strategy, servitization strategy, and control strategy. Moreover, these findings are summarized in a contingency framework that explains which types of challenges that can be addressed with which strategies based on the specific prerequisites of each collaboration.
Journal: International Journal of Production Research
Pages: 3926-3942
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2116499
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2116499
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2042416_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lei Ren
Author-X-Name-First: Lei
Author-X-Name-Last: Ren
Author-Name: Yingjie Li
Author-X-Name-First: Yingjie
Author-X-Name-Last: Li
Author-Name: Xiaokang Wang
Author-X-Name-First: Xiaokang
Author-X-Name-Last: Wang
Author-Name: Jin Cui
Author-X-Name-First: Jin
Author-X-Name-Last: Cui
Author-Name: Lin Zhang
Author-X-Name-First: Lin
Author-X-Name-Last: Zhang
Title: An ABGE-aided manufacturing knowledge graph construction approach for heterogeneous IIoT data integration
Abstract: 
 The Industrial Internet of Things (IIoT) provides a foundation for the development of emerging digital servitization paradigm in smart manufacturing. The deep integration of massive heterogeneous IIOT data plays a critical role in realising manufacturing digital servitization. However, there is a knowledge gap between different manufacturing fields, which brings a challenge for efficient integration and leverage of industrial big data. For this purpose, a Framework of Manufacturing Knowledge Graph (FMKG) is proposed, which is used to extracts industry knowledge triples from multi-source heterogeneous data to integrate domain knowledge. Also, an attention-based graph embedding model (ABGE) is proposed to discover and complement the implicit missing relationships in the knowledge graph to obtain a complete industrial knowledge graph. The effectiveness of the ABGE model has been verified on several knowledge graph data sets. And an aerospace enterprise production process was taken as an example to establish a product quality knowledge graph, which proved the feasibility of the proposed method.
Journal: International Journal of Production Research
Pages: 4102-4116
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2042416
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2042416
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_1966118_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ming Li
Author-X-Name-First: Ming
Author-X-Name-Last: Li
Author-Name: Yelin Fu
Author-X-Name-First: Yelin
Author-X-Name-Last: Fu
Author-Name: Qiqi Chen
Author-X-Name-First: Qiqi
Author-X-Name-Last: Chen
Author-Name: Ting Qu
Author-X-Name-First: Ting
Author-X-Name-Last: Qu
Title: Blockchain-enabled digital twin collaboration platform for heterogeneous socialized manufacturing resource management
Abstract: 
 Social manufacturing is conceptualised as a new type of networked manufacturing paradigm that supports the organisation of socialised manufacturing resources (SMRs) to satisfy the growth of personalised demands on crowd intelligence in a timely manner when co-creating open architecture products. The high participation of each stakeholder in this type of product production places a higher requirement on sufficient collaboration among social, cyber and physical spaces. However, under a decentralised social manufacturing network, the management of SMRs has encountered some real-life challenges in terms of their distributed and heterogeneous features. Hence, this paper proposes a blockchain-enabled digital twin collaboration platform (BcDTCP) as an integrated solution to address these challenges. A hybrid domain-driven design method is presented to design and implement business-knowledge driven systems. To address the heterogeneity of SMRs, a ubiquitous object structure is designed to flexibly adjust the functionality of the digital twin. Blockchain is introduced to construct a peer-to-peer network to organise the SMRs in a decentralised manner. Additionally, a timed coloured Petri net-based workflow is adopted to formulise the collaboration logic into a smart contract executed on the blockchain. Finally, a demonstrative case study is conducted to verify and evaluate the proposed BcDTCP under a 3D printing scenario.
Journal: International Journal of Production Research
Pages: 3963-3983
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1966118
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1966118
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# input file: TPRS_A_2002458_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Tongtong Zhou
Author-X-Name-First: Tongtong
Author-X-Name-Last: Zhou
Author-Name: Xinguo Ming
Author-X-Name-First: Xinguo
Author-X-Name-Last: Ming
Author-Name: Zhihua Chen
Author-X-Name-First: Zhihua
Author-X-Name-Last: Chen
Author-Name: Rui Miao
Author-X-Name-First: Rui
Author-X-Name-Last: Miao
Title: Selecting industrial IoT Platform for digital servitisation: a framework integrating platform leverage practices and cloud HBWM-TOPSIS approach
Abstract: 
 Digital servitisation has emerged as an important strategy to enhance industrial companies' competitiveness. Leveraging the IIoT (industrial internet of thing) platform is considered an essential way to facilitate digital servitisation. Selecting an appropriate IIoT platform from numerous alternatives in the market is a difficult task for the firms due to lack of deep understanding of the required IIoT platform capabilities for deploying industrial service. To help firms make wise decision, we propose a feasible multi-criteria decision making framework for IIoT platform selection. Firstly, a practice-oriented technical-managerial-service criteria system is derived from typical platform leverage logics for digital servitisation. Next, an integrative approach combining cloud hierarchical BWM (best-worst method) and cloud TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is proposed for selecting the best IIoT platform. Using this approach, the criteria weights and the ranking of potential platforms can be accurately determined by considering the fuzziness and randomness of linguistic decision information. Finally, a case study of a Chinese crane manufacturer illustrates the feasibility and reliability of the proposed framework. The analysis results can help the managers find the best IIoT platform and provide them with deep insight and direction for leveraging the IIoT platform towards digital servitisation.
Journal: International Journal of Production Research
Pages: 4022-4044
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.2002458
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002458
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# input file: TPRS_A_2202258_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Pai Zheng
Author-X-Name-First: Pai
Author-X-Name-Last: Zheng
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Title: Editorial notes: Industrial Internet-of-Things (IIoT)-enabled digital servitisation
Journal: International Journal of Production Research
Pages: 3844-3848
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2023.2202258
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2202258
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# input file: TPRS_A_2051088_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Litong Zhang
Author-X-Name-First: Litong
Author-X-Name-Last: Zhang
Author-Name: Yu Guo
Author-X-Name-First: Yu
Author-X-Name-Last: Guo
Author-Name: Weiwei Qian
Author-X-Name-First: Weiwei
Author-X-Name-Last: Qian
Author-Name: Weili Wang
Author-X-Name-First: Weili
Author-X-Name-Last: Wang
Author-Name: Daoyuan Liu
Author-X-Name-First: Daoyuan
Author-X-Name-Last: Liu
Author-Name: Sai Liu
Author-X-Name-First: Sai
Author-X-Name-Last: Liu
Title: Modelling and online training method for digital twin workshop
Abstract: 
 Aiming at the difficulties in modelling, simulation and verification in digital twin workshop, a modelling and online training method for digital twin workshop is proposed. This paper describes a multi-level digital twin aggregate modelling method, including the status attributes, the static performance attributes and the fluctuation performance attributes, and designs a digital twin organisation system, namely, digital twin graph. According to the data demand for digital twin aggregates, a spatio-temporal data model is constructed. The digital twin model training method using truncated normal distribution is presented. Furthermore, a verification method based on real-virtual error for a digital twin model is proposed. The effectiveness of real-time status monitoring, online model training and simulation for production is verified by a case.
Journal: International Journal of Production Research
Pages: 3943-3962
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2022.2051088
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2051088
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# input file: TPRS_A_1960447_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lin Li
Author-X-Name-First: Lin
Author-X-Name-Last: Li
Author-Name: Ou Tang
Author-X-Name-First: Ou
Author-X-Name-Last: Tang
Author-Name: Wei Zhou
Author-X-Name-First: Wei
Author-X-Name-Last: Zhou
Author-Name: Tijun Fan
Author-X-Name-First: Tijun
Author-X-Name-Last: Fan
Title: Backroom effect on perishable inventory management with IoT information
Abstract: 
 We introduce an original concept of the backroom effect for perishable products when the deterioration rate in a backroom is lower than that on retail shelves. With IoT-generated real-time information about the perishable products, this phenomenon has a significant impact on joint shelf-space and inventory decisions. We define the deterioration rate gap, formulate the perceived on-shelf product freshness, and describe the freshness-dependent demand distribution, with continuous backroom-shelf replenishment. Assuming that demand depends on both perceived freshness and shelf level, we develop a decision-making model that simultaneously determines the inventory replenishment policy and the shelf space allocation for multiple items. To facilitate the solution process, we propose a hybrid solution approach by combining genetic algorithm (GA) and variable neighbourhood search (VNS). The results provide a prioritised inventory policy for item selection that incorporates the deterioration improvement. The results of the performance analysis show that a policy considering the backroom effect achieves increased profit when the backroom/shelf deterioration gap increases. The optimal solutions for the problems with large backroom/shelf gap also show that the practitioner should increase the ordering quantity, which is contradictory to the outcome of traditional models.
Journal: International Journal of Production Research
Pages: 4157-4179
Issue: 12
Volume: 61
Year: 2023
Month: 06
X-DOI: 10.1080/00207543.2021.1960447
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1960447
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# input file: TPRS_A_2138613_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Zetian Zhao
Author-X-Name-First: Zetian
Author-X-Name-Last: Zhao
Author-Name: Bingtao Hu
Author-X-Name-First: Bingtao
Author-X-Name-Last: Hu
Author-Name: Yixiong Feng
Author-X-Name-First: Yixiong
Author-X-Name-Last: Feng
Author-Name: Bin Zhao
Author-X-Name-First: Bin
Author-X-Name-Last: Zhao
Author-Name: Chen Yang
Author-X-Name-First: Chen
Author-X-Name-Last: Yang
Author-Name: Zhaoxi Hong
Author-X-Name-First: Zhaoxi
Author-X-Name-Last: Hong
Author-Name: Jianrong Tan
Author-X-Name-First: Jianrong
Author-X-Name-Last: Tan
Title: Multi-surface defect detection for universal joint bearings via multimodal feature and deep transfer learning
Abstract: 
 Surface defect detection by machine vision has received increased attention concerning the quality control of universal joint bearings (UJB). The defect distribution and counting information are important for product quality optimisation. However, vision defect detection for UJB remains a challenging task due to the diversity of background textures and defect characters on multiple surfaces. In this study, a multi-surface defect detection (MSDD) method consisting of region segmentation, feature extraction and detection is proposed. First, defect regions are accurately localised by the proposed adaptive defect region segmentation algorithm, which suppresses the inference of background variety. Then, a novel defect feature named multimodal fusion shape descriptor that integrates the global information and local information of defects is constructed to generate the discriminative defect representation. Finally, a defect feature extraction ability transfer strategy based on the transfer learning mechanism is proposed to address the problem of insufficient defect samples. The experimental results show that our method achieves the best accuracy of 94.8% macro-F1 and processes 28 defect images per second. Besides, the application effect in the practical production line indicates that our method meets the accuracy and real-time requirements of MSDD for UJB.
Journal: International Journal of Production Research
Pages: 4402-4418
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2138613
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2138613
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# input file: TPRS_A_2010827_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Chuqiao Xu
Author-X-Name-First: Chuqiao
Author-X-Name-Last: Xu
Author-Name: Junliang Wang
Author-X-Name-First: Junliang
Author-X-Name-Last: Wang
Author-Name: Jing Tao
Author-X-Name-First: Jing
Author-X-Name-Last: Tao
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Author-Name: Ray Y. Zhong
Author-X-Name-First: Ray Y.
Author-X-Name-Last: Zhong
Title: A knowledge augmented image deblurring method with deep learning for in-situ quality detection of yarn production
Abstract: 
 In the in-situ quality detection of yarn production, image deblurring plays a critical role in the vision-based detection systems to restore a sharp image and provide more accurate input for inspection. However, image deblurring is still challenging since the current methods are mainly based on the pre-defined blur degree. In dynamic yarn production, the relationship between the defocus blur degrees and the poses of the yarn body is highly associated, which can be excavated to prior knowledge in image deblurring to achieve more effective restoration. Thus, a knowledge augmented deep learning model is proposed to adaptively deblur yarn images with variable defocus blur degrees. A pose classification module designed by prior knowledge is embedded into the deep neural network, which classifies the yarn poses and feeds them into multi-scale deblurring channels. In each channel, we incorporate the image gradient prior into the specially designed loss function to attract the attention of the deblurring network on the edge details of the yarn. The experimental results from actual spinning processes demonstrate that the proposed method performs a better effect not only in the variable-scale deblurring of the global image but also in the restoration of the edge details.
Journal: International Journal of Production Research
Pages: 4220-4236
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.2010827
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2010827
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# input file: TPRS_A_2093683_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Abhinav Kumar Sharma
Author-X-Name-First: Abhinav Kumar
Author-X-Name-Last: Sharma
Author-Name: Indrajit Mukherjee
Author-X-Name-First: Indrajit
Author-X-Name-Last: Mukherjee
Author-Name: Sasadhar Bera
Author-X-Name-First: Sasadhar
Author-X-Name-Last: Bera
Title: A novel machine learning-based multiobjective robust optimisation strategy for quality improvement of multivariate manufacturing processes
Abstract: 
 The primary objective of this study was to develop a novel data-driven machine learning-based multiobjective robust optimisation strategy to improve the overall quality of multivariate manufacturing processes. The new strategy was conceptualised considering a manufacturing environment with unreplicated non-normal data observations and limited opportunity for off-line sequential design of experiments. At a macro level, the new strategy adopts suitable artificial intelligence-based process models and a fine-tuned non-dominated sorting genetic algorithm-II (NSGA-II) to derive robust efficient process setting conditions. These robust solutions are iteratively derived considering process model predictive uncertainties, process setting sensitivities, and variance-covariance structure of uncontrollable multivariate non-normal inputs (or covariates). These solutions are also ranked based on multicriteria decision-making (MCDM) techniques to facilitate implementation. In this study, the quality of the best-ranked solutions was compared (w.r.t. closeness to specified multiple targets and predicted multivariate output variabilities) with those of the solutions obtained from parametric and commercial software-based approaches using three different real-life manufacturing cases.
Journal: International Journal of Production Research
Pages: 4322-4340
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2093683
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2093683
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# input file: TPRS_A_2131927_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jiliang Han
Author-X-Name-First: Jiliang
Author-X-Name-Last: Han
Author-Name: Lin Li
Author-X-Name-First: Lin
Author-X-Name-Last: Li
Author-Name: Zilai Sun
Author-X-Name-First: Zilai
Author-X-Name-Last: Sun
Author-Name: Xiaochun Feng
Author-X-Name-First: Xiaochun
Author-X-Name-Last: Feng
Author-Name: Na Lin
Author-X-Name-First: Na
Author-X-Name-Last: Lin
Author-Name: Junhu Ruan
Author-X-Name-First: Junhu
Author-X-Name-Last: Ruan
Title: An integrative decision-making model for the Internet of Things-enabled supply chains of fresh agri-product
Abstract: 
 The application of new information technologies such as the Internet of Things (IoT) has caused a deep impact on production and operations management in various fields. In this paper, a mixed-integer programming model is proposed to generate integrative decision-making in the IoT-enabled fresh agri-products supply chains. The designed model integrates three key stages, that is, planting, storage, and distribution, to help growers make the optimal decisions for maximising revenue. Decisions are made after comprehensive consideration of market factors such as price and demand as well as agricultural characteristics such as crop yield and shelf life. Results of numerical experiments show that significant improvement of benefits can be obtained through the overall decision-making of planting, storage, and distribution. Additionally, it may be most beneficial for growers to keep the warehouse’s storage time and storage capacity at a medium level. The IoT-based integrative decision-making method explored in this study can be applied to other fields including manufacturing to achieve more efficient production and operations management.
Journal: International Journal of Production Research
Pages: 4358-4373
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2131927
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2131927
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# input file: TPRS_A_2022802_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ying Cheng
Author-X-Name-First: Ying
Author-X-Name-Last: Cheng
Author-Name: Yanshan Gao
Author-X-Name-First: Yanshan
Author-X-Name-Last: Gao
Author-Name: Lei Wang
Author-X-Name-First: Lei
Author-X-Name-Last: Wang
Author-Name: Fei Tao
Author-X-Name-First: Fei
Author-X-Name-Last: Tao
Author-Name: Qing-Guo Wang
Author-X-Name-First: Qing-Guo
Author-X-Name-Last: Wang
Title: Graph-based operational robustness analysis of industrial Internet of things platform for manufacturing service collaboration
Abstract: 
 As industrial Internet of things (IIoT) for Manufacturing Service Collaboration (MSC) is becoming the current trend to accelerate the upgrade iteration of manufacturing capability, developing the robust IIoT platform operation mechanism for MSC is crucial to promote the continuous and stable service collaboration in the presence of supply and demand uncertainties. This paper studies the operational robustness of the IIoT platform for MSC. Firstly, the operation performances, requirements, and challenges of the IIoT platform towards manufacturing collaboration are analysed in classified platform practices, which can provide a comprehensive cognition about platform operation for manufacturing collaboration. Then, to evaluate the tolerance and persistence capabilities of MSC under supply and demand uncertainties, a graph-based operational robustness analysis method of the IIoT platform for MSC is proposed. The IIoT platform operation network for MSC is modelled as an interdependent network-of-network structure based on graph theory, which helps to characterise MSC performance properties under complexities. By combining manufacturing properties with network statistics, the evaluation metrics of operational robustness are established, which is done to quantise the MSC effectiveness under uncertainty effects. A case about customised manufacturing of automobiles illustrates the application of the proposed methods. Finally, future studies about robust MSC regulation are discussed.
Journal: International Journal of Production Research
Pages: 4237-4264
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.2022802
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2022802
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# input file: TPRS_A_2142314_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jingyuan Lei
Author-X-Name-First: Jingyuan
Author-X-Name-Last: Lei
Author-Name: Jizhuang Hui
Author-X-Name-First: Jizhuang
Author-X-Name-Last: Hui
Author-Name: Fengtian Chang
Author-X-Name-First: Fengtian
Author-X-Name-Last: Chang
Author-Name: Salim Dassari
Author-X-Name-First: Salim
Author-X-Name-Last: Dassari
Author-Name: Kai Ding
Author-X-Name-First: Kai
Author-X-Name-Last: Ding
Title: Reinforcement learning-based dynamic production-logistics-integrated tasks allocation in smart factories
Abstract: 
 In Industry 4.0, the production planning and execution of smart factories (SFs) full of continuously delivered small-batch orders become dynamic and complicated. Traditional centralised manufacture planning is difficult to handle unexpected disturbances. With the aid of new information technologies, resources in SFs become smart and connected to make autonomous decisions. This paper tries to release intelligence of smart connected resources to allocate production tasks and logistics tasks in SFs coordinately and autonomously. The architecture is modelled as an autonomous decision-making manufacturing system with IIoT support, which aims to synchronously allocate manufacturing tasks by the bidding of resources in SFs. Then, a dynamic production-logistics-integrated tasks allocation model is built. The orders makespan and resources utilisation are considered as the objective function, and production resources and logistics resources are integrated to autonomously communicate and interact with each other to bid for dynamic production-logistics integrated operations. To figure out, a reinforcement learning (RL) algorithm is studied, which makes operations decisions for each job step by step based on in-situ data during manufacturing process. Finally, a demonstrative case showed that compared to centralised scheduling system, the RL-based model performs better in handling production-logistics-integrated tasks allocation problem in SFs full of dynamic and small-batch individualised orders.
Journal: International Journal of Production Research
Pages: 4419-4436
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2142314
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2142314
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# input file: TPRS_A_2132312_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yu Zhang
Author-X-Name-First: Yu
Author-X-Name-Last: Zhang
Author-Name: Nan Liu
Author-X-Name-First: Nan
Author-X-Name-Last: Liu
Title: Blockchain adoption in serial logistics service chain: value and challenge
Abstract: 
 Inefficient practices in the logistics industry cause huge losses in social resources. Addressing the quality control issues is challenging in multi-stage transport. Due to the structural characteristics of the serial logistics service chains, the real delivery quality of each Third Party Logistics (3PL) is invisible to the Lead Logistics Provider (LLP), and the defects of a single 3PL’s delivery quality will be covered up. Thus, unobservable delivery quality triggers the moral hazard action of 3PL, and strengthens the inequities in a serial logistics service chain. Blockchain technology can be an effective tool to resolve the moral hazard problem. We employ game theory-based models to investigate the blockchain adoption issue in serial logistics service chains. Adopting blockchain technology might bring Pareto improvement in delivery quality and total profit of the service chain. However, 3PL’s profit may be hurt because of blockchain adoption. Therefore, successful blockchain implementation depends on whether the initiator of a blockchain programme can properly incentivise 3PLs.
Journal: International Journal of Production Research
Pages: 4374-4401
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2132312
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2132312
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# input file: TPRS_A_2079013_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ruize Ma
Author-X-Name-First: Ruize
Author-X-Name-Last: Ma
Author-Name: Lin Jiang
Author-X-Name-First: Lin
Author-X-Name-Last: Jiang
Author-Name: Tianyue Wang
Author-X-Name-First: Tianyue
Author-X-Name-Last: Wang
Author-Name: Xuping Wang
Author-X-Name-First: Xuping
Author-X-Name-Last: Wang
Author-Name: Junhu Ruan
Author-X-Name-First: Junhu
Author-X-Name-Last: Ruan
Title: How do manufacturing companies and service providers share knowledge in the context of servitization? An evolutionary-game model of complex networks
Abstract: 
 The digital capabilities driven by Internet of Things and affiliated techniques have enabled the prevailing service-oriented business models, among which servitization has been well recognised as one of the most competitive strategies for manufacturing companies. However, manufacturing companies usually show a lack of knowledge regarding the service offering associated to their manufactured products. Acquiring external knowledge from service providers is one effective way to tackle this problem, but due to the information asymmetry, the process of knowledge sharing between the two is often faced with a prisoner’s dilemma game. Meanwhile, the company’s game strategy will change with the evolution of the knowledge sharing network structure. We therefore consider the influence of group spatial structure on individual game strategy, marry a canonical evolutionary game model on the decision-making mechanism of individuals to the complex network theory on the interaction behaviour among individuals in the groups. By analysing the model, we reveal the influence of various factors under the dimensions of ability and benefit on the willingness of companies to share knowledge. We also demonstrate the divergence in the influence of various factors on different types of companies.
Journal: International Journal of Production Research
Pages: 4279-4301
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2079013
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2079013
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# input file: TPRS_A_2207956_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Author-Name: Kai Ding
Author-X-Name-First: Kai
Author-X-Name-Last: Ding
Title: Industrial intelligence-driven production and operations management
Journal: International Journal of Production Research
Pages: 4215-4219
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2023.2207956
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2207956
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# input file: TPRS_A_2123057_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lin Gui
Author-X-Name-First: Lin
Author-X-Name-Last: Gui
Author-Name: Ling Fu
Author-X-Name-First: Ling
Author-X-Name-Last: Fu
Author-Name: Xinyu Li
Author-X-Name-First: Xinyu
Author-X-Name-Last: Li
Author-Name: Wei Zhou
Author-X-Name-First: Wei
Author-X-Name-Last: Zhou
Author-Name: Liang Gao
Author-X-Name-First: Liang
Author-X-Name-Last: Gao
Author-Name: Zhimou Xiang
Author-X-Name-First: Zhimou
Author-X-Name-Last: Xiang
Author-Name: Wei Zhu
Author-X-Name-First: Wei
Author-X-Name-Last: Zhu
Title: Optimisation framework and method for solving the serial dual-shop collaborative scheduling problem
Abstract: 
 Due to the production process or environment, most products need to go through multiple production workshops, from raw materials to finished products. For example, a large structural part must go through a blanking workshop and a machining workshop. However, the research on the serial multi-shop cooperative scheduling problem is insufficient. Different from the single shop scheduling problem, the multi-shop scheduling problem can be regarded as a scheduling problem composed of multiple sub-problems. Therefore, optimisation processes between subproblems may be the key to solving this kind of problem. This paper focuses on the optimisation framework for the serial multi-shop cooperative scheduling problem. A specific serial dual-shop collaborative scheduling problem is abstracted from the production, whose first and second shop is the hybrid flow shop and the job shop, respectively. A disjunctive graph model of this specific problem is constructed. After that, four different optimisation frameworks are proposed, and testing instances are designed to compare these frameworks. Under different optimisation frameworks, the same tabu search algorithm with an efficient neighbourhood structure is used to optimize this problem. Finally, the optimisation results of different frameworks are compared and the results of each optimisation framework are analyzed.
Journal: International Journal of Production Research
Pages: 4341-4357
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2123057
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2123057
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# input file: TPRS_A_2051766_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jianghua Zhang
Author-X-Name-First: Jianghua
Author-X-Name-Last: Zhang
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Author-Name: Xinsheng Xu
Author-X-Name-First: Xinsheng
Author-X-Name-Last: Xu
Title: Data-driven analysis on optimal purchasing decisions in combined procurement
Abstract: 
 With the development of information technology, big data analysis has been highlighted in operations and management. From this viewpoint, this paper studies a buyer's optimal purchasing decisions in combined procurement. For combined procurement, a buyer first signs a long-term contract with a supplier to guarantee a certain level of commodity supply, and can then replenish the commodities from the spot market if necessary. The optimal purchasing quantity in the long-term contract is examined to maximise the buyer's expected profit from combined procurement. In view of the imperfectness in the spot market, the spot trading liquidity is considered in the buyer's optimal purchasing decision. The properties of the two optimal purchasing quantities are examined and several interesting results are obtained. For example, it is illustrated that a buyer's expected profit may decrease in the spot capacity, a result that has never appeared in the existing literature, which reveals the importance of a buyer's optimal order decision in the presence of spot replenishment. Numerical results and sensitivity analysis are performed to verify the results. Management insights are suggested for a buyer's optimal purchasing decisions in combined procurement with a long-term contract and spot replenishment.
Journal: International Journal of Production Research
Pages: 4265-4278
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2051766
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2051766
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# input file: TPRS_A_2152895_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Neslihan Top
Author-X-Name-First: Neslihan
Author-X-Name-Last: Top
Author-Name: Ismail Sahin
Author-X-Name-First: Ismail
Author-X-Name-Last: Sahin
Author-Name: Sachin Kumar Mangla
Author-X-Name-First: Sachin Kumar
Author-X-Name-Last: Mangla
Author-Name: Muruvvet Deniz Sezer
Author-X-Name-First: Muruvvet Deniz
Author-X-Name-Last: Sezer
Author-Name: Yigit Kazancoglu
Author-X-Name-First: Yigit
Author-X-Name-Last: Kazancoglu
Title: Towards sustainable production for transition to additive manufacturing: a case study in the manufacturing industry
Abstract: 
 Additive Manufacturing (AM) has emerged as an important digital technology in improving production efficiency by analysing possible environmental impacts of the operations. Therefore, this study aims to investigate the impacts of redesigned products for transition to AM on sustainable production processes. In this study, an industrial-scale product was redesigned according to AM principles and manufactured using the Fused Deposition Modelling (FDM) technique. The environmental impacts of the production methods were evaluated in terms of material consumption and carbon dioxide (CO2) emissions using the Life Cycle Assessment (LCA) method. Thus, according to LCA results, the use of a single type of material and production method for the redesigned product, as well as reducing the amount of material used by eliminating the fasteners, resulted in a 60.45% reduction in material consumption and 85.59% reduction in CO2 emissions compared to CM. Although the production time in CM is shorter than FDM, the necessity of a mould design and manufacture by pre-processing resulted in an increase in delivery time. Results show that the material unit costs for both manufacturing methods are very similar. This study provides various implications that create sustainable development in the manufacturing industry for the transition to AM.ABBREVIATIONS: AM, Additive Manufacturing; CAD, Computer-Aided Design; CAE, Computed-Aided Engineering; CM, Conventional Manufacturing; CNC, Computer Numerical Control; CO2, Carbon Dioxide; DFAM, Design for Additive Manufacturing; DIY, Do It Yourself; FDM, Fused Deposition Modelling; LCA, Life Cycle Assessment; LEM, Laser Engraving Machine; PLA, Polylactic Acid; SLA – Stereolithography; SLS, Selective Laser Sintering; 3D – Three Dimensional
Journal: International Journal of Production Research
Pages: 4450-4471
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2152895
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152895
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# input file: TPRS_A_2160501_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yixin Li
Author-X-Name-First: Yixin
Author-X-Name-Last: Li
Author-Name: Fu Hu
Author-X-Name-First: Fu
Author-X-Name-Last: Hu
Author-Name: Ying Liu
Author-X-Name-First: Ying
Author-X-Name-Last: Liu
Author-Name: Michael Ryan
Author-X-Name-First: Michael
Author-X-Name-Last: Ryan
Author-Name: Ray Wang
Author-X-Name-First: Ray
Author-X-Name-Last: Wang
Title: A hybrid model compression approach via knowledge distillation for predicting energy consumption in additive manufacturing
Abstract: 
 Recently, additive manufacturing (AM) has received increased attention due to its high energy consumption. By extracting hidden information or highly representative features from energy-relevant data, knowledge distillation (KD) reduces predictive model complexity and computational load. By using almost predetermined and fixed models, the distillation process restricts students and teachers from learning from one model to another. To reduce computational costs while maintaining acceptable performance, a teacher assistant (TA) was added to the teacher-student architecture. Firstly, a teacher ensemble was combined with three baseline models to enhance accuracy. In the second step, a teacher ensemble (TA) was formed to bridge the capacity gap between the ensemble and the simplified model. As a result, the complexity of the student model was reduced. Using geometry-based features derived from layer-wise image data, a KD-based predictive model was developed to evaluate the feasibility and effectiveness of two independently trained student models. In comparison with independently trained student models, the performance of the proposed method has the lowest RMSE, MAE, and training time.
Journal: International Journal of Production Research
Pages: 4525-4547
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2160501
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2160501
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# input file: TPRS_A_2187243_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Min Guo
Author-X-Name-First: Min
Author-X-Name-Last: Guo
Author-Name: Xiang T. R. Kong
Author-X-Name-First: Xiang T. R.
Author-X-Name-Last: Kong
Author-Name: Hing Kai Chan
Author-X-Name-First: Hing Kai
Author-X-Name-Last: Chan
Author-Name: Dimple R. Thadani
Author-X-Name-First: Dimple R.
Author-X-Name-Last: Thadani
Title: Integrated inventory control and scheduling decision framework for packaging and products on a reusable transport item sharing platform
Abstract: 
 This study considers the problem of inventory and scheduling decisions on a reusable transport item (RTI) sharing platform with the collaborative recovery of used RTIs and replenishment of products in a two-tier container management centre (CMC). The products (packaged as full RTIs) are pre-positioned at the regional CMC (R-CMC), and empty RTIs are stored at the CMC hub. Moreover, the CMC replenishes the products and recycles RTIs respectively and periodically. The RTI and products are a set of complementary products, and the replenishment task requires sufficient empty RTIs in stock. Untimely and insufficient RTI returns without considering product inventory changes often result in RTI out-of-stock situations that harm the customer's lean productivity. This paper proposes a machine learning and simulation optimisation (MSO) decision framework to collaboratively assist RTI inventory and scheduling decisions in a two-tier CMC. Based on a case study, we can conclude the decision framework has better performance on the profitability and inventory control capability. Moreover, different inventory and scheduling parameter settings in the two-tier CMCs impact the platform's profitability to derive corresponding management insights, and a decision system can be built based on the above framework.
Journal: International Journal of Production Research
Pages: 4575-4591
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2023.2187243
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2187243
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# input file: TPRS_A_2089929_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jiewu Leng
Author-X-Name-First: Jiewu
Author-X-Name-Last: Leng
Author-Name: Weinan Sha
Author-X-Name-First: Weinan
Author-X-Name-Last: Sha
Author-Name: Zisheng Lin
Author-X-Name-First: Zisheng
Author-X-Name-Last: Lin
Author-Name: Jianbo Jing
Author-X-Name-First: Jianbo
Author-X-Name-Last: Jing
Author-Name: Qiang Liu
Author-X-Name-First: Qiang
Author-X-Name-Last: Liu
Author-Name: Xin Chen
Author-X-Name-First: Xin
Author-X-Name-Last: Chen
Title: Blockchained smart contract pyramid-driven multi-agent autonomous process control for resilient individualised manufacturing towards Industry 5.0
Abstract: 
 The production control for the mass individualisation paradigm of R&D-stage products is challenging due to the mix-flow and frequently-disturbed environment. With the convergence of the sustainable development goals and the increasing individualised demands in products, resilient manufacturing is envisioned in Industry 5.0 proposition. Concerning that conventional centralised production control methods suffer from low stability and inefficiency of decisions under frequent disruptions, this paper establishes a blockchained smart contract pyramid-driven multi-agent autonomous process control (BSCP-MAAPC) approach for improving the timeliness and adaptability of control towards resilient individualised manufacturing. Firstly, a blockchain-based multi-agent system architecture is designed based on agent encapsulation of manufacturing units. Blockchained smart contracts are used as the enabler of the multi-agent system for peer-to-peer negotiation and coordination of tasks. Secondly, a quad-play blockchained smart contract pyramid together with a series of decentralised control patterns are designed to enable the initial task dispatching of various individualised demands, as well as rapid dynamic adjustment of schedule in response to internal random disruptions. Finally, a blockchained smart contract pyramid-driven multi-agent autonomous process control system prototype is built in the ManuChain system, and experiments are conducted to analyze the proposed BSCP-MAAPC approach in different environments.HIGHLIGHTSA blockchained smart contract pyramid-driven multi-agent autonomous process control (BSCP-MAAPC) approach.A quad-play blockchained smart contract pyramid together with a series of decentralized control patterns.Blockchained smart contracts as the enabler of the multi-agent system for peer-to-peer negotiation and coordination of tasks.
Journal: International Journal of Production Research
Pages: 4302-4321
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2089929
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2089929
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# input file: TPRS_A_2157064_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ying Peng
Author-X-Name-First: Ying
Author-X-Name-Last: Peng
Author-Name: Xu Chen
Author-X-Name-First: Xu
Author-X-Name-Last: Chen
Author-Name: Xiaojun Wang
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Wang
Title: Enhancing supply chain flows through blockchain: a comprehensive literature review
Abstract: 
 Applications of blockchain in supply chain management (SCM) have received extensive attention among academics and industrial practitioners. Most current blockchain-related review papers focus on the values, methodologies, barriers, trends, and challenges of blockchain applications in the supply chain (SC) context. Despite some papers discussing blockchain’s role in SCs from a specific perspective, the existing review papers mainly concentrate on blockchain’s influence on one of the three critical SC flows. Hence, this study comprehensively reviews 251 academic papers to capture the precise impacts of blockchain on the material, information, and money flows in SCM. Following the above analyses, a conceptual framework is put forward to accentuate blockchain’s influence on SCM. By unveiling a comprehensive research landscape, this study offers valuable viewpoints and vital information for scholars and practitioners to better identify research frontiers and themes of blockchain applications in SCM.
Journal: International Journal of Production Research
Pages: 4503-4524
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2157064
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2157064
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# input file: TPRS_A_2168309_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Shuai Zhao
Author-X-Name-First: Shuai
Author-X-Name-Last: Zhao
Author-Name: Wenli Li
Author-X-Name-First: Wenli
Author-X-Name-Last: Li
Title: Blockchain-based traceability system adoption decision in the dual-channel perishable goods market under different pricing policies
Abstract: 
 The blockchain-based traceability system (BTS) can reduce product losses in the perishable goods market, which yields a loss-reduction effect, and offer authentic information, which triggers a premium effect. In a dual-channel perishable goods supply chain (DPGSC), including one supplier and retailer each, the supplier can operate the price of the direct channel, different or non-different from that of the traditional channel. To study the adoption of BTS in the supplier-led DPGSC, we employed a game-theoretical model to capture BTS adoption strategy under the differential and non-differential pricing policies and proposed an improved cost-sharing contract to boost the DPGSC performance. The results indicated that both the supplier and the retailer are willing to improve product quality, broaden the saleable region, and lower the production cost. The adoption of BTS mainly depends on the losses-reduction effect, premium effect, production cost, and tag cost, which is affected more by the premium effect than by the loss-reduction effect. Furthermore, their adoption is not always easier when the production cost is higher. Except for symmetric base demands, they benefit asynchronously from BTS. Synchronised adoptions can be realised only when the improved cost-sharing contract generates more profits and introduces excess momentum.Highlights
Blockchain-based traceability system handles product losses and forged informationAdoption decision-making processes under two different pricing policies are studiedIn the adoption process, the premium effect outweighs the loss-reduction effectContract may introduce insufficient momentum, excess momentum, or new inefficiencyOnce excess momentum is formed, supply chain members' adoptions become synchronised
Journal: International Journal of Production Research
Pages: 4548-4574
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2023.2168309
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2168309
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# input file: TPRS_A_2154406_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Abdelrahman E.E. Eltoukhy
Author-X-Name-First: Abdelrahman E.E.
Author-X-Name-Last: Eltoukhy
Author-Name: Mohamed Hussein
Author-X-Name-First: Mohamed
Author-X-Name-Last: Hussein
Author-Name: Min Xu
Author-X-Name-First: Min
Author-X-Name-Last: Xu
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Title: Data-driven Game-theoretic Model Based on Blockchain for Managing Resource Allocation and Vehicle Routing in Modular Integrated Construction
Abstract: 
 In modular integrated construction (MiC), the resource allocation problem (RAP) adopted by construction sites and vehicle routing problem (VRP) adopted by logistics companies are highly interdependent. However, this interdependence has been overlooked in the literature. Thus, the plans determined by each problem cannot be achieved practically. Moreover, there is no existing VRP model suitable for the MiC application. This study aims to propose a VRP model suitable for MiC, investigate the interdependence between the RAP and proposed VRP model, and develop a blockchain system to secure information sharing between the RAP and VRP. The first two objectives are achieved by developing a coordinated system formulated as a leader-follower Stackelberg game model (LFSGM). This model is presented as a bi-level optimisation model and solved using a nested ant colony optimisation-based algorithm. The effectiveness of the LFSGM is validated using a real case study. The results show that using the traditional approach (i.e. a separate RAP and proposed VRP) succeeds in providing a plan for the construction sites but not for the logistics company. In contrast, the LFSGM offers applicable plans for both the construction sites and logistics company. Lastly, some managerial implications are identified and discussed.
Journal: International Journal of Production Research
Pages: 4472-4502
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2154406
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2154406
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# input file: TPRS_A_2148769_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lin Ma
Author-X-Name-First: Lin
Author-X-Name-Last: Ma
Author-Name: Ting Qu
Author-X-Name-First: Ting
Author-X-Name-Last: Qu
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Zaoqi Wang
Author-X-Name-First: Zaoqi
Author-X-Name-Last: Wang
Author-Name: Mingze Yuan
Author-X-Name-First: Mingze
Author-X-Name-Last: Yuan
Author-Name: Lei Liu
Author-X-Name-First: Lei
Author-X-Name-Last: Liu
Title: An integrated spatial-temporal neural network for proactive throughput bottleneck prediction in high-variety shops with complex job routings
Abstract: 
 Throughput bottlenecks remain a main concern for managers in practice since they affect production output and throughput times. A large literature on bottleneck detection and prediction consequently emerged. Bottleneck prediction is specifically important in context where bottlenecks shift since it allows for counteracting the potential impact. The literature on throughput bottleneck prediction largely focusses on temporal aspects. Although this reflects the relation among stations if the routing of jobs is fairly directed, the relative station position constantly changes for more complex routings. A station maybe upstream, downstream or have no relation to another station dependent on the mix of jobs currently on the shop floor. In these high-variety contexts, both temporal and spatial features should be considered when predicting bottlenecks. In response, this study proposes a new neural network model that systematically connects multiple independent workstations into a system by extracting the spatial features between workstations. The new approach is different from traditional stacking mechanisms applied in the literature, and it allows for a better integration of spatial and temporal neural networks. Experimental results show that the proposed model outperforms alternative models and provides good prediction performance. Findings have important implications for research and practice.
Journal: International Journal of Production Research
Pages: 4437-4449
Issue: 13
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2148769
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2148769
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# input file: TPRS_A_10110445_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: A. Scholl
Author-X-Name-First: A.
Author-X-Name-Last: Scholl
Author-Name: R. Klein
Author-X-Name-First: R.
Author-X-Name-Last: Klein
Title: ULINO: Optimally balancing U-shaped JIT assembly lines
Abstract: 
 Traditionally, assembly lines are arranged in a straight line. The design of such a line requires tasks to be grouped into stations such that the line efficiency is maximized. This problem is known as the assembly line balancing problem. However, as a consequence of introducing the just-in-time production principle, it has been recognized that arranging the stations in a U-line has several advantages over the traditional configuration. For solving different versions of the U-line assembly line balancing problem, we propose the branch and bound procedure ULINO which is applied directly and in the framework of search methods. Experimental results indicate that these procedures perform well and that the U-line configuration frequently improves the line efficiency compared to traditional lines.
Journal: International Journal of Production Research
Pages: 721-736
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191481
File-URL: http://hdl.handle.net/10.1080/002075499191481
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# input file: TPRS_A_10110446_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: S. H. Steiner
Author-X-Name-First: S. H.
Author-X-Name-Last: Steiner
Title: Confirmation sample control charts
Abstract: 
 Traditional X and R control charts are used widely in industry, but do not respond quickly to small or moderate changes in the process output. Confirmation sample control (CSC) charts to detect changes in the process mean and process variability are proposed. These new control charts have substantially better operating characteristics than X and R charts. CSC charts require that any unusual observed sample be confirmed through an independent confirmation sample taken from the process. This makes CSC charts appealing to production personnel since the charts require the verification of bad news. The implementation of CSC charts is illustrated, and figures are given that allow the determination of appropriate design parameters.
Journal: International Journal of Production Research
Pages: 737-748
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191490
File-URL: http://hdl.handle.net/10.1080/002075499191490
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# input file: TPRS_A_10110447_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: S. Hamamoto
Author-X-Name-First: S.
Author-X-Name-Last: Hamamoto
Author-Name: Y. Yih
Author-X-Name-First: Y.
Author-X-Name-Last: Yih
Author-Name: G. Salvendy
Author-X-Name-First: G.
Author-X-Name-Last: Salvendy
Title: Development and validation of genetic algorithm-based facility layout a case study in the pharmaceutical industry
Abstract: 
 In the layout design of pharmaceutical factories, several important objectives often need to be considered, such as operation cost, maintenance cost, material handing cost, throughput rate, etc. Most of the existing algorithms for facility layout design were developed based on pre-determined single objectives; namely, the distance-based objectives or the adjacency-based objectives. In this paper, we propose a genetic algorithm approach with an embedded simulation model which allows the user to select the objectives that are important in each particular layout design in the pharmaceutical industry. To verify the feasibility of the proposed method, the layout designs of two pharmaceutical plants for solid dosage forms were used as a test bed. One represents a typical small-size pharmaceutical plant and the other represents a medium-size plant. The objectives are to maximize throughput rate and to minimize travelling time per trip. A simulation model was developed, and the efficiency of the layouts generated by human designers CORELAP, CRAFT, and BLOCPLAN, is compared. The comparison indicates that the proposed genetic algorithm method significantly outperforms human designers and other computer algorithms in minimizing travelling time per trip under the same throughput rate.
Journal: International Journal of Production Research
Pages: 749-768
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191508
File-URL: http://hdl.handle.net/10.1080/002075499191508
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# input file: TPRS_A_10110448_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: R. R. Gung
Author-X-Name-First: R. R.
Author-X-Name-Last: Gung
Title: A workload balancing model for determining set-up time and batch size reductions in GT flow line workcells
Abstract: 
 Set-up time and batch size reductions cornerstones of Quick Response Manufacturing (QRM) are often viewed as pathways leading to lower workin-process (WIP) inventory levels and reduced manufacturing lead times. However, set-up time and batch size reductions may not always yield such improvements. Increased workload due to the additional set-ups can lead to a violation of the system's capacity constraints and cause system instability, which results in increased manufacturing lead times and WIP inventory levels. A workload balancing model in conjunction with a heuristic model is presented to determine the required set-up time reduction schemes for different levels of batch size reduction. The model is based on the Theory of Constraints to balance the flow line and limit the workload of each workstation such that each workstation meets the reserved capacity constraint. It is shown that a reduction plan determined by the workload balancing model will maintain the cell's system stability and improve its performance. Incorporating the workload balancing and simulation models, a general approach for selecting the most appropriate reduction plan is illustrated through an example of a gear manufacturing cell. The implications for management are: (1) that pre-established levels for set-up time and batch size reductions are not always effective; and (2) that effective reduction plans need to be preceded by system capacity and performance analysis to determine the effects of such reductions prior to implementation.
Journal: International Journal of Production Research
Pages: 769-791
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191517
File-URL: http://hdl.handle.net/10.1080/002075499191517
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# input file: TPRS_A_10110449_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: V. N. Narayanan Namboothiri
Author-X-Name-First: V. N. Narayanan
Author-X-Name-Last: Namboothiri
Title: On determination of sample size in form error evaluation using coordinate metrology
Abstract: 
 During form error evaluation, as the accuracy requirement increases the measurement sample size should also be increased, thereby increasing the measurement time. In this paper, a new parameter is introduced based on the asymptotic distribution of the range of errors. This new parameter gives the probability that the form error (range of errors) is less than a predicted value based on the current sample size and the corresponding errors. Simulation studies are carried out and the results are presented.
Journal: International Journal of Production Research
Pages: 793-804
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191526
File-URL: http://hdl.handle.net/10.1080/002075499191526
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# input file: TPRS_A_10110450_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: O. Duran
Author-X-Name-First: O.
Author-X-Name-Last: Duran
Title: Automatic PLC software generator with a natural interface
Abstract: 
 This paper presents an object-oriented textual language designed to specify programmable logic controller software. This methodology, called OOST, allows users to specify the control logic in a natural manner, using a collection of objects that represent machines and other devices within a manufacturing system. The object-oriented specification technique may be used during the whole control software life cycle, and could be considered as a requirement definition language or an implementation one. An automatic PLC program generation system that uses descriptions written in OOST is also presented. A brief literature review is presented and the implementation details are discussed. The final part presents some future improvements and a few remarks.
Journal: International Journal of Production Research
Pages: 805-819
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191535
File-URL: http://hdl.handle.net/10.1080/002075499191535
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# input file: TPRS_A_10110451_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Vincent G. Duffy
Author-X-Name-First: Vincent G.
Author-X-Name-Last: Duffy
Title: Relating company performance to staff perceptions: The impact of concurrent engineering on time to market
Abstract: 
 A study of 103 electronics manufacturers in the United States has demonstrated a relationship between staff perceptions and actual performance for concurrent engineering. Information was gathered in each company from the manager of the concurrent engineering effort, the team leader and a design, manufacturing and marketing team member. The use of concurrent engineering reduced, on average, the time to market. Companies were grouped into the 'upper third' and 'lower third' with respect to overall effectiveness, based on the mean rating or perception of the respondents. Companies in the 'upper third' and 'lower third' of effectiveness in implementing and using concurrent engineering were found to have engineering change requests occur 45% and 27% earlier, respectively, in the product development process through their concurrent engineering effort. Companies in the 'upper third' in overall concurrent engineering effectiveness reduced time to market by 40% , while the 'lower third' reduced time to market by only 16% . The top one-third of companies in concurrent engineering reduce, on average, the time to market of products by 4.8 months in relation to companies in the bottom one-third. The implications of the findings are discussed for researchers and practitioners in the light of difficulties experienced by reengineering efforts in the 1990s.
Journal: International Journal of Production Research
Pages: 821-834
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191544
File-URL: http://hdl.handle.net/10.1080/002075499191544
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# input file: TPRS_A_10110452_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Y. H. Lee
Author-X-Name-First: Y. H.
Author-X-Name-Last: Lee
Title: An economic machining process model using fuzzy non-linear programming and neural network
Abstract: 
 This paper describes a computer-aided approach for the optimum selection of cutting conditions for a turning process. The approach includes a fuzzy non-linear programming and neural network model. In this paper, the fuzzy non-linear programming is employed to predict optimum cutting conditions in uncertain, ill-defined and vague situations of machining operations. The fuzzy non-linear programming provides ease of implementation, flexibility and a tolerant nature to arbitrary complexity in machining operations. In addition, in this paper, the output from the fuzzy non-linear programming model is also utilized to develop a neural network model for machinability assessment.
Journal: International Journal of Production Research
Pages: 835-847
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191553
File-URL: http://hdl.handle.net/10.1080/002075499191553
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# input file: TPRS_A_10110453_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Laura Swanson
Author-X-Name-First: Laura
Author-X-Name-Last: Swanson
Title: The impact of new production technologies on the maintenance function: An empirical study
Abstract: 
 Firms are increasingly using advanced manufacturing technology and just-in-time production to improve their competitiveness. However, little consideration has been given to the effect of these technologies on the maintenance function. This paper reports the results of a study of maintenance practices. Based on the responses of 222 plant managers and maintenance managers in 180 manufacturing plants, the analysis shows several direct relationships between advanced manufacturing technology and just-in-time and choice of maintenance practices. Advanced manufacturing technology is associated with more extensive use of computerized maintenance management systems, worker training, professional maintenance staff and preventive maintenance. Just-in-time manufacturing is associated with more extensive operator involvement in performing simple maintenance tasks.
Journal: International Journal of Production Research
Pages: 849-869
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191562
File-URL: http://hdl.handle.net/10.1080/002075499191562
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# input file: TPRS_A_10110454_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: N. Bateman
Author-X-Name-First: N.
Author-X-Name-Last: Bateman
Title: Measuring the mix response flexibility of manufacturing systems
Abstract: 
 This paper is concerned with a particular flexibility parameter, referred to as mix response flexibility. This is a measure of the difficulty of processing different products on the same equipment, where a different set-up is required for each product type. A mathematical model for measuring mix response flexibility is described, and its results are compared with a simulation. The model is found to give meaningful results for both single machines and multiple machine systems.
Journal: International Journal of Production Research
Pages: 871-880
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191571
File-URL: http://hdl.handle.net/10.1080/002075499191571
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# input file: TPRS_A_10110455_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: T. S. Vaughan
Author-X-Name-First: T. S.
Author-X-Name-Last: Vaughan
Title: The effect of warehouse cross aisles on order picking efficiency
Abstract: 
 This paper investigates the effects of adding cross aisles to the layout of an order consolidation warehouse, with respect to order picking efficiency. Intuitively, cross aisles provide greater flexibility in the routing of order pickers, thus providing shorter order picking travel distances. However, this effect may be negated when the number of cross aisles becomes excessive, as the cross aisles themselves must be traversed in order to reach the required items. A shortest path pick sequencing model is developed which allows for any number of cross aisles in the warehouse. The optimal routing is computed for a large number of randomly generated picking requests, over a variety of warehouse layout and order picking parameters. The results are used to characterize the optimal number of warehouse cross aisles, as well as the conditions under which cross aisles generate the greatest benefit.
Journal: International Journal of Production Research
Pages: 881-897
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191580
File-URL: http://hdl.handle.net/10.1080/002075499191580
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# input file: TPRS_A_10110456_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: J. Wang
Author-X-Name-First: J.
Author-X-Name-Last: Wang
Title: Fuzzy outranking approach to prioritize design requirements in quality function deployment
Abstract: 
 Identification of important design requirements for product development is critical because it leads to successful products with shorter development time. The quality function deployment (QFD) is a tool to help the product development team systematically determine the design requirements for developing a product with higher customer satisfaction. However, it is more difficult to assess the performance of a design with accurate quantitative values, due to the imprecise and incomplete information available at the early design stage. A decision model is needed to assist team members in selecting the critical design requirements for product development. This paper considers the QFD planning as a multi-criteria decision problem and proposes a new fuzzy outranking approach to prioritize design requirements recognized in QFD. The inputs required for QFD are represented with linguistic terms that are characterized by fuzzy sets. The fuzzy outranking relation is used to model the imprecise preference relations between design requirements. Consequently, the critical design requirements are identified for the focus of design to achieve not only customer satisfaction but also the balanced design of a product. Moreover, the sensitivity analysis is applied to examine the robustness of the result. Finally, an example of a car design is used to illustrate the approach developed.
Journal: International Journal of Production Research
Pages: 899-916
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191599
File-URL: http://hdl.handle.net/10.1080/002075499191599
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# input file: TPRS_A_10110457_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: A. K. Sheikh
Author-X-Name-First: A. K.
Author-X-Name-Last: Sheikh
Title: Optimal tool replacement and resetting strategies in automated manufacturing systems
Abstract: 
 As a result of tool wear in machining processes there is a change in the dimensions of parts produced. To minimize the cost of producing parts out of specifications and to minimize the overall tooling cost, the optimal tool resetting and replacement intervals need to be determined. In this paper, the optimal cost models are proposed for tool replacement and resetting by using renewal functions. The tool life as well as tool reset times are modelled as inverted normal distributions. Numerical solutions are presented for the proposed models. To illustrate the application of the models, a case study of machining a part on a Mazak CNC machine is presented. The dimensional changes of various surfaces of the machined parts are monitored along with the corresponding tool wear as a function of time. The data obtained have demonstrated the validity of the proposed models, their underlying assumptions, and they illustrate the utilization of such an analysis in a flexible manufacturing system, where such CNC machines are the integral part of the system.
Journal: International Journal of Production Research
Pages: 917-937
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191607
File-URL: http://hdl.handle.net/10.1080/002075499191607
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# input file: TPRS_A_10110458_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: T. S. Baines
Author-X-Name-First: T. S.
Author-X-Name-Last: Baines
Title: Manufacturing technology sourcing practices in the USA
Abstract: 
 Some companies are heavily reliant on the capabilities of their manufacturing technology for product competitiveness. Likewise, the capabilities of a manufacturing technology are dependent on the sourcing policy that the host company practices. This paper describes research that has explored a wide variety of US companies to understand manufacturing technology sourcing policies and how they have been formed. This research finds that there is a preference amongst the US organizations studied not to become involved with equipment manufacture, though some examples of full integration do occur. These policies are not determined by formalized decision processes, rather they are formed implicitly during technology choice. In this research, factors that influence a technology source have been identified. These drivers are then used to establish a methodology that will help practising managers to form a technology sourcing decision. This methodology takes into account the business demands placed on a technology, along with the characteristics of the host company's supplier base.
Journal: International Journal of Production Research
Pages: 939-956
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191616
File-URL: http://hdl.handle.net/10.1080/002075499191616
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# input file: TPRS_A_10110459_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: The Editors
Title: Book reviews
Journal: International Journal of Production Research
Pages: 957-960
Issue: 4
Volume: 37
Year: 1999
Month: 3
X-DOI: 10.1080/002075499191625
File-URL: http://hdl.handle.net/10.1080/002075499191625
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# input file: TPRS_A_1928319_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Adegboyega Oyedijo
Author-X-Name-First: Adegboyega
Author-X-Name-Last: Oyedijo
Author-Name: Ying Yang
Author-X-Name-First: Ying
Author-X-Name-Last: Yang
Author-Name: Adebayo Serge Francois Koukpaki
Author-X-Name-First: Adebayo Serge Francois
Author-X-Name-Last: Koukpaki
Author-Name: Nishikant Mishra
Author-X-Name-First: Nishikant
Author-X-Name-Last: Mishra
Title: The role of fairness in multi-tier sustainable supply chains
Abstract: 
 Fairness is an important topic that forms part of an organisation’s sustainability practice and agenda, particularly from a social dimension. However, past studies have rarely considered the role of fairness as a driver of sustainability in multi-tier supply chains. The purpose of this paper is two-fold. First, it examines the impact of fairness perceptions on the relationship between multi-tier supply chain partners. Second, it investigates the dynamics of on-going fairness formations in different stages of the vibrant multi-tier supply chain relationship development process. These gaps have been addressed by reporting the findings of qualitative research. Primary data were obtained from 18 procurement and supply practitioners of buying firms and their top tier-1 & 2 suppliers. Findings show that fairness perceptions have an impact on collaborative activities between multi-tier supply chain partners. These collaborative responses such as information sharing, joint relationship effort, and dedicated investment can also impact critical aspects of the multi-tier supply chain relationship such as trust, commitment, satisfaction, and conflict resolution. The findings show that multi-tier supply chain partners have different expectations but usually evaluate fairness at the review phase of the relationship development process. These considerations offer theoretical and practical guidance towards the advancement of sustainable multi-tier supply chain relationships.
Journal: International Journal of Production Research
Pages: 4893-4917
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1928319
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1928319
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# input file: TPRS_A_1988749_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Vahid Mirzabeiki
Author-X-Name-First: Vahid
Author-X-Name-Last: Mirzabeiki
Author-Name: Qile He
Author-X-Name-First: Qile
Author-X-Name-Last: He
Author-Name: David Sarpong
Author-X-Name-First: David
Author-X-Name-Last: Sarpong
Title: Sustainability-driven co-opetition in supply chains as strategic capabilities: drivers, facilitators, and barriers
Abstract: 
 Co-opetition is gaining increasing attention as a potentially useful form of inter-organisational collaboration model to improve firms’ sustainable performance. However, limited previous studies have provided a clear substantive theory or offered empirical evidence for the process of sustainability-driven co-opetition. This paper explores how competing companies can collaborate in their supply chains (SCs) to achieve a higher level of sustainability performance by identifying drivers, facilitators and barriers of co-opetition. Based on two explorative case studies of co-opetition in the UK, the findings of this paper lead to a number of propositions and a theoretical framework for sustainability-driven co-opetition in SCs. This study contributes to the literature by providing a more in-depth understanding of co-opetition as a strategic capability for firms. This paper also proves the feasibility of a combined use of Resource-Based View and Network Theory perspectives in explaining a paradoxical inter-organisational relationship like co-opetition. A road map for sustainability-driven co-opetition in SCs is also provided as a heuristic decision model for practitioners.
Journal: International Journal of Production Research
Pages: 4826-4852
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1988749
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1988749
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# input file: TPRS_A_1924412_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Li Cui
Author-X-Name-First: Li
Author-X-Name-Last: Cui
Author-Name: Hao Wu
Author-X-Name-First: Hao
Author-X-Name-Last: Wu
Author-Name: Jing Dai
Author-X-Name-First: Jing
Author-X-Name-Last: Dai
Title: Modelling flexible decisions about sustainable supplier selection in multitier sustainable supply chain management
Abstract: 
 Supplier selection is crucial decision for buying companies to develop sustainable supply chain strategy. Not only first-tier suppliers but also lower-tier suppliers would influence the buyer’s sustainability performance. Thus, buying companies need to consider extending their sustainable supply chain plan to multitier suppliers, and develop multitier sustainable supply chain management (MT-SSCM). Sustainable supplier selection (SSS), as an important SSCM practice, can effectively enhance the sustainable competitiveness of supply chains. However, there are few theoretical studies on SSS under MT-SSCM, which affects the decision-making efficiency of organisations. In general, there are three multitier supply chain (MTSC) structures: open MTSC, closed MTSC and transitional MTSC structures. Because some traditional decision models cannot deal with a variety of structures at the same time, this study proposes a hybrid model that integrates fuzzy set theory, stepwise weight assessment ratio analysis and a Bayesian network to evaluate the critical SSS criteria in three MTSC structures. Finally, a case of a Chinese buying company is used to verify the flexibility and applicability of the proposed model, and some suggestions are provided for the practitioners to select sustainable suppliers in different MTSC structures.
Journal: International Journal of Production Research
Pages: 4603-4624
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1924412
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1924412
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# input file: TPRS_A_2002966_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Junjun Liu
Author-X-Name-First: Junjun
Author-X-Name-Last: Liu
Author-Name: Yunting Feng
Author-X-Name-First: Yunting
Author-X-Name-Last: Feng
Author-Name: Qinghua Zhu
Author-X-Name-First: Qinghua
Author-X-Name-Last: Zhu
Title: Involving second-tier suppliers in Green supply chain management: drivers and heterogenous understandings by firms along supply chains
Abstract: 
 Leading manufacturers have struggled to extend their green supply chain management (GSCM) efforts to low-tier (the second- and even lower-tier) suppliers, but how to motivate low-tier suppliers to be involved is still a big challenge. This paper develops a low-tier GSCM model for managing second-tier suppliers. Based on stakeholder theory and literature review, this paper develops 25 drivers for the ìnvolvement of second-tier suppliers in low-tier GSCM by a manufacturer. Using data collected from 29 second-tier suppliers of a leading automobile manufacturer, this study identified 17 critical drivers. The Grey-DEMATEL method was used to examine the cause-effect relationships to reveal prominent and elemental drivers. Based on the evaluation by managers from the manufacturer, one first-tier supplier, and six second-tier suppliers, comparative analysis of the DEMATEL results show that the manufacturer understands the prominent role of second-tier suppliers for its low-tier GSCM implementation while second-tier suppliers know little about the manufacturer’s requirements and the first-tier supplier ignores the importance of internal drivers by second-tier suppliers. In the long term, the manufacturer considers itself as the crucial firm for low-tier GSCM, but according to first- and second-tier suppliers, promoting policies by the government such as GSCM-related demonstration projects are also elemental. This study provides directions for multi-tier GSCM studies on the theoretical development about how to effectively involve second-tier suppliers by unveiling the difference in the understanding of drivers among firms along supply chains.
Journal: International Journal of Production Research
Pages: 4765-4785
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.2002966
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2002966
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# input file: TPRS_A_1834160_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Carlos Mena
Author-X-Name-First: Carlos
Author-X-Name-Last: Mena
Author-Name: Tobias Schoenherr
Author-X-Name-First: Tobias
Author-X-Name-Last: Schoenherr
Title: The green contagion effect: an investigation into the propagation of environmental practices across multiple supply chains tiers
Abstract: 
 The phenomenon of green contagion refers to the diffusion of sustainability practices across multi-tier supply chains. In this research, we propose a model of green contagion, theorising that both collaborative and coercive mechanisms play a role in the propagation of environmental sustainability across supply chains. Hypotheses are tested using a structural equation model with a multinational dataset of 616 manufacturing organisations reporting on their green practices, both internally within the firm and externally with suppliers and customers. From a theoretical perspective, the results lend support to the green contagion effect, with five out of the seven hypotheses being supported. The rejected hypotheses refer to a firm’s internal adoption of green practices influencing green collaborative practices with suppliers, and a customer’s use of coercive mechanisms towards a firm influencing the adoption of green collaborative practices between the firm and its suppliers. The findings have theoretical and practical implications for production research, as they highlight the challenges that organisations face when trying to influence green practices beyond tier 1 suppliers, and show that collaborative practices may prove more effective than coercive practices.
Journal: International Journal of Production Research
Pages: 4808-4825
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2020.1834160
File-URL: http://hdl.handle.net/10.1080/00207543.2020.1834160
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# input file: TPRS_A_1938276_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: K. Mathiyazhagan
Author-X-Name-First: K.
Author-X-Name-Last: Mathiyazhagan
Author-Name: Venkatesh Mani
Author-X-Name-First: Venkatesh
Author-X-Name-Last: Mani
Author-Name: Deepak Mathivathanan
Author-X-Name-First: Deepak
Author-X-Name-Last: Mathivathanan
Author-Name: Sonu Rajak
Author-X-Name-First: Sonu
Author-X-Name-Last: Rajak
Title: Evaluation of antecedents to social sustainability practices in multi-tier Indian automotive manufacturing firms
Abstract: 
 In the current time, social sustainability is directed by market turbulence and growing societal and environmental awareness among customers and employees. Manufacturing industries with multi-tier supply chains, especially in developing nations, such as India, are plagued with various social issues, as it employs large manpower. The present study attempts to identify the key social sustainability practices (SSP) and the method to evaluate SSP in multi-tier manufacturing firms. The approach was pilot tested in Indian manufacturing industry. A total of 16 SSP were identified through the process of literature survey and discussions with the domain experts. Furthermore, based on five practitioners’ inputs, the relationship between various practices of social sustainability is modelled using Total Interpretive Structural Modelling (TISM). The vagueness in the model and identified relationships are compensated by experts’ (practitioners’) validation. The practices are classified on the basis of driving and dependence power by adopting the MICMAC analysis. Customer management, information sharing, corporate sustainability reporting and standardisation, and monitoring practices are found to be the most influential practices that drive social sustainability in multi-tier automotive chains. Production managers could adopt these SSP to establish supply chain social sustainability in multi-tier global supply chains and achieve strategic advantage over others.
Journal: International Journal of Production Research
Pages: 4786-4807
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1938276
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1938276
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# input file: TPRS_A_1890260_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bo Feng
Author-X-Name-First: Bo
Author-X-Name-Last: Feng
Author-Name: Xueyan Hu
Author-X-Name-First: Xueyan
Author-X-Name-Last: Hu
Author-Name: Ifeyinwa Juliet Orji
Author-X-Name-First: Ifeyinwa Juliet
Author-X-Name-Last: Orji
Title: Multi-tier supply chain sustainability in the pulp and paper industry: a framework and evaluation methodology
Abstract: 
 The pulp and paper industry has significant sustainability implications and necessarily requires a careful consideration of direct and lower-tier suppliers for effective sustainable supply chain management. This paper utilized an extensive literature review and semi-structured interviews of experts in the Chinese pulp and paper industry to unearth the factors that highly influence multi-tier supply chain sustainability. A Technological-Organizational-Environmental (TOE) and Human-Organizational-Technological (HOT-fit) based theoretical framework was employed to classify the identified factors. Then, an Analytical Hierarchy Process (AHP) based methodology was applied to determine the relative importance of the factors. A comparison analysis of the relative importance of the factors as determined by the experts in the focal companies, Tier-1 suppliers and Tier-2 suppliers of the Chinese pulp and paper industry is presented. The results show that institutional and technological factors are most critical to actualizing multi-tier supply chain sustainability. Thus, the study outcomes present relevant theoretical and practical implications for the managers and practitioners in the pulp and paper industry on how to facilitate multi-tier supply chain sustainability for increased competitiveness. Furthermore, this study provides guidelines for other industries as well and sets the stage for subsequent theorization and exploration of multi-tier supply chain sustainability for expected performance gains.
Journal: International Journal of Production Research
Pages: 4657-4683
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1890260
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1890260
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# input file: TPRS_A_2216831_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Simonov Kusi-Sarpong
Author-X-Name-First: Simonov
Author-X-Name-Last: Kusi-Sarpong
Author-Name: Yu (Jack) Gong
Author-X-Name-First: Yu (Jack)
Author-X-Name-Last: Gong
Author-Name: Steve Brown
Author-X-Name-First: Steve
Author-X-Name-Last: Brown
Author-Name: Himanshu Gupta
Author-X-Name-First: Himanshu
Author-X-Name-Last: Gupta
Author-Name: Chunguang Bai
Author-X-Name-First: Chunguang
Author-X-Name-Last: Bai
Author-Name: Ifeyinwa Juliet Orji
Author-X-Name-First: Ifeyinwa Juliet
Author-X-Name-Last: Orji
Title: Multi-tier sustainable supply chains management for global sustainability
Abstract: 
 The growing concerns around sustainability along the supply chains are global. The complexity of supply chain sustainability becomes even more pronounced across the multiple tiers of organisations and networks and has imposed heavy pressures on organisations. Dealing with these pressures on society and the environment requires supply chains to lessen their socio-environmental impact. Multi-tier sustainable supply chains are a vehicle to aid in this important global goal. However, addressing these issues and concerns in the production processes and consumption of businesses and organisations is still in its early stages. In light of this, this Special Issue published in the International Journal of Production Research advances this important research agenda. Seventeen articles which were accepted for this Special Issue employed various methodologies/methods, theories, and contexts to respond to the need for research and provided valuable insights that address some of the pressing multi-tier supply chain sustainability problems. This Editorial provides an overview of these works, highlighting opportunities for future search directions.
Journal: International Journal of Production Research
Pages: 4592-4602
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2023.2216831
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2216831
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# input file: TPRS_A_2025944_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bill Wang
Author-X-Name-First: Bill
Author-X-Name-Last: Wang
Author-Name: Zhiyu Lin
Author-X-Name-First: Zhiyu
Author-X-Name-Last: Lin
Author-Name: Michael Wang
Author-X-Name-First: Michael
Author-X-Name-Last: Wang
Author-Name: Fangyi Wang
Author-X-Name-First: Fangyi
Author-X-Name-Last: Wang
Author-Name: Peng Xiangli
Author-X-Name-First: Peng
Author-X-Name-Last: Xiangli
Author-Name: Zhi Li
Author-X-Name-First: Zhi
Author-X-Name-Last: Li
Title: Applying blockchain technology to ensure compliance with sustainability standards in the PPE multi-tier supply chain
Abstract: 
 Because of the Covid-19 pandemic, urgent surging demand for healthcare products such as personal protective equipment (PPE) has caused significant challenges for multi-tier supply chain management. Although a given firm may predominantly focus on an arms-length solution by targeting the first-tier supplier, the firm can still struggle with extended multi-tier suppliers it cannot choose which use unsustainable practices. One key goal is compliance across various dimensions with production, environmental and labour standards across the multi-tier supply chain, a goal that blockchain technology can be applied to manage. Based on a comprehensive literature review, this research develops a system architecture of blockchain-based multi-tier sustainable supply chain management in the PPE industry designed to identify and coordinate standards in production and social and environmental sustainability in multi-tier PPE supply chains. The architecture was validated by theoretical basis, expert opinions and technical solutions. We conclude with managerial implications for implementing blockchain technology to advance sustainable multi-tier supply chain practices.
Journal: International Journal of Production Research
Pages: 4934-4950
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2025944
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2025944
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# input file: TPRS_A_1939456_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Baozhuang Niu
Author-X-Name-First: Baozhuang
Author-X-Name-Last: Niu
Author-Name: Zihao Mu
Author-X-Name-First: Zihao
Author-X-Name-Last: Mu
Author-Name: Lei Chen
Author-X-Name-First: Lei
Author-X-Name-Last: Chen
Title: Procurement sharing decision for sustainable and regular products in a multi-tier production system
Abstract: 
 Many sustainable products require innovative design techniques but the same materials as regular products. In practice, whether pooling the material procurement orders via procurement sharing can be a strategic decision when an OEM produces both sustainable and regular products. In this paper, we formulate a multi-tier production system comprising of an OEM, a CM, and two material suppliers, and study two typical strategies: (1) procurement sharing, where the procurement functions of the sustainable and regular products are outsourced to the CM, and (2) independent procurement, where the OEM independently procures materials for the sustainable product. We solve the four-stage-four-player optimisation problem and find that the change of the market potential of the sustainable product heavily determines the OEM’s overall procurement cost, and consequently the procurement sharing decisions. Under independent procurement, the wholesale prices of the sustainable and regular products show opposite characteristics when the market potential of the sustainable product varies, because the two suppliers have opposite pricing incentives. We derive three interactive effects that alter the OEM’s procurement sharing incentives, which makes the OEM prefer independent procurement only when the market potential of the sustainable product is in a moderate range.
Journal: International Journal of Production Research
Pages: 4871-4892
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1939456
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1939456
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# input file: TPRS_A_1990432_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mohammad Najjar
Author-X-Name-First: Mohammad
Author-X-Name-Last: Najjar
Author-Name: Mahmoud M. Yasin
Author-X-Name-First: Mahmoud M.
Author-X-Name-Last: Yasin
Title: The management of global multi-tier sustainable supply chains: a complexity theory perspective
Abstract: 
 Global supply chains feature multi-tier systems encompassing many geographically dispersed and sequential partners operating across diversified product chains. This research attempts to examine the different mechanisms that reinforce the management of sustainability throughout complex multi-tier supply chain. Using a multi-case study of a sample of eight firms and relying on the foundations of complexity theory, this research recognises the complex operating environment of global multi-tier supply chains and reveals various mechanisms to effectively manage and facilitate the relationships with first- and lower-tier suppliers. Although institutional controls are important to manage the sustainability of first-tier suppliers, the findings posit that due to the inherent complexities of global multi-tier supply chains, duplicating institutional controls to lower-tier suppliers might not be effective. Therefore, firms should attempt to foster modest mechanisms that reinforce adaptation and self-organisation, for example, collaboration and guiding mechanisms, to effectively manage the sustainability of lower-tier suppliers. The research contributes to multi-tier sustainable supply chain management literature by exploring the different mechanisms to manage multi-tier supply chains and the inherent complexities that may impact on firms’ endeavours in achieving their sustainability goals. Managers can utilise different contingent mechanisms to effectively manage the relationships with suppliers that are beyond their immediate visibility.
Journal: International Journal of Production Research
Pages: 4853-4870
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1990432
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1990432
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# input file: TPRS_A_2088425_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Damla Durak Uşar
Author-X-Name-First: Damla
Author-X-Name-Last: Durak Uşar
Author-Name: Mehmet Ali Soytas
Author-X-Name-First: Mehmet Ali
Author-X-Name-Last: Soytas
Title: Sustainability outcomes in multi-tier supply chains: an empirical study of Turkish manufacturing firms
Abstract: 
 To formulate multi-tier supply chain management strategies with global impact, understanding the roles of various supply chain partners in disseminating sustainability along the supply chain is crucial. We analyze the influence of different supply chain positions on sustainability and financial outcomes of Turkish manufacturing companies listed in İstanbul Stock Exchange (BIST). We propose a sustainability measure, and rank firms according to their sustainability practices in relation to their financial outcomes using data envelopment analysis (DEA). We estimate Seemingly Unrelated Regression (SUR) equations to control for the common financial shocks that can affect sustainability and financial outcomes simultaneously. Our analysis reveals that first-tier and sub-supplier (second-tier and lower-tiers) firms’ financial performance is substantially better compared to Original Equipment Manufacturer (OEM) firms while their sustainability outcomes stay behind. We find that this latter effect is more profound for first-tier firms. Although the supplier firms generally comply with the OEM’s product standards, our results show that they are not aligned with the OEM in terms of the environmental and social impact of their operations. Given the crucial role of first-tier suppliers in sustainability dissemination along the supply chain, policies should be formulated in this industry amid these characteristics of the sustainability dissemination.
Journal: International Journal of Production Research
Pages: 4625-4656
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2088425
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2088425
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# input file: TPRS_A_1936263_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Luai Jraisat
Author-X-Name-First: Luai
Author-X-Name-Last: Jraisat
Author-Name: Arvind Upadhyay
Author-X-Name-First: Arvind
Author-X-Name-Last: Upadhyay
Author-Name: Thaana Ghalia
Author-X-Name-First: Thaana
Author-X-Name-Last: Ghalia
Author-Name: Mohannad Jresseit
Author-X-Name-First: Mohannad
Author-X-Name-Last: Jresseit
Author-Name: Vikas Kumar
Author-X-Name-First: Vikas
Author-X-Name-Last: Kumar
Author-Name: David Sarpong
Author-X-Name-First: David
Author-X-Name-Last: Sarpong
Title: Triads in sustainable supply-chain perspective: why is a collaboration mechanism needed?
Abstract: 
 This research explores focal actors and their dyads, addressing their sustainable collaboration in triads and its relevance in the agri-triads that share information along the supply chains. We employ a multiple-case approach and presents two triads through 42 interviews, observation and documentaries. An abductive approach, Transaction Cost Economics (TCE), conceptually guides the analytical iteration stages between theory and data. The findings describe the collaboration mechanisms of focal actors at triad levels and the development of their dyads capabilities for sustainable supply chains. Eight triad approaches emerge in the present research; these are grouped into three aggregated levels according to the intensity of information-sharing between focal and associate actors in each triad. The research has identified six contextual factors that are linked to the TCE dimensions of asset specificity, uncertainty and frequency, and offers key propositions. The research gained insights into how focal actors in dyadic triads choose between the available approaches based on different intensity levels of information-sharing. This research presents a conceptual framework informing the choice of triad approaches reflecting collaboration mechanism strategies, and thus the intensity of information-sharing and sustainability performance. The study elaborates on the application of TCE and extends it empirically to the literature.
Journal: International Journal of Production Research
Pages: 4725-4741
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1936263
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1936263
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# input file: TPRS_A_2059719_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ming Zeng
Author-X-Name-First: Ming
Author-X-Name-Last: Zeng
Author-Name: Keivan Sadeghzadeh
Author-X-Name-First: Keivan
Author-X-Name-Last: Sadeghzadeh
Author-Name: Tao Xiong
Author-X-Name-First: Tao
Author-X-Name-Last: Xiong
Title: A three-echelon based sustainable supply chain scheduling decision-making framework under the blockchain environment
Abstract: 
 The Supply Chain Scheduling (SCS) decision making is a challenging task under the blockchain environment because the supply chain is composed of multi-players in all layers. To utilise the information sharing by multiplayers with equal rights in all layers to maximise the supply chain’s utility for reducing the carbon emission, this study proposed a three-echelon supply chain integrated scheduling model that considers the production capacity and multi-product with different delivery time factors. The objective is to minimise the total cost incurred in production and transportation under the blockchain environment. To cope with the complexity arising from multiplayers with equal rights in all layers, a metaheuristic based sequential brain storm optimisation (SBSO) algorithm with a novel encoding scheme and the hybrid crossover and mutation strategy is proposed to enhance the performance. A case study comparing the proposed decision-making framework with the artificial bee colony algorithm (ABC) and the backtracking search algorithm (BSA) is conducted, and results show the superiority of the proposed framework. With the help of the proposed SCS decision-making framework, not only can the SCS decision be made, but also the low efficient nodes within the supply chain under the blockchain environment can be identified for potential sustainable upgrading.
Journal: International Journal of Production Research
Pages: 4951-4971
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2059719
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2059719
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# input file: TPRS_A_1930238_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yu Gong
Author-X-Name-First: Yu
Author-X-Name-Last: Gong
Author-Name: Yan Jiang
Author-X-Name-First: Yan
Author-X-Name-Last: Jiang
Author-Name: Fu Jia
Author-X-Name-First: Fu
Author-X-Name-Last: Jia
Title: Multiple multi-tier sustainable supply chain management: a social system theory perspective
Abstract: 
 A multi-tier supply chain is a complex system as it covers a focal company and multiple tiers of suppliers in a complex supply chain network. This study explores the complexity in multi-tier sustainable supply chain management (SSCM) through a social systems theory perspective. We carried out a case study on IKEA China’s sustainable cotton initiative and examined its five cotton-textile supply chains. The primary data were collected through 22 semi-structured interviews with managers of IKEA China and their multi-tier suppliers. The findings suggest that in order to cope with environmental complexity in implementing multi-tier sustainable initiatives, focal companies tend to create both internal complexity and collaborative complexity in a variety of governance mechanisms. In addition, environmental overlap and available collaborative complexity increase in this process and can feed back into systems to facilitate further creation of requisite variety. We contribute to the multi-tier SSCM literature through providing an in-depth understanding of nuanced mechanisms of managing different tiers of suppliers to cope with complexities by adopting a social systems theory perspective. We also contribute to multi-tier supply chain governance mechanisms from an evolution perspective.
Journal: International Journal of Production Research
Pages: 4684-4701
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1930238
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1930238
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# input file: TPRS_A_1946194_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: P. K. Senyo
Author-X-Name-First: P. K.
Author-X-Name-Last: Senyo
Author-Name: Ellis L. C. Osabutey
Author-X-Name-First: Ellis L. C.
Author-X-Name-Last: Osabutey
Title: Transdisciplinary perspective on sustainable multi-tier supply chains: a triple bottom line inspired framework and future research directions
Abstract: 
 Global sourcing and increased interdependencies between organisations have created more complex multi-tier supply chains. While these supply chains have been instrumental in keeping the world moving, they equally pose sustainability issues. In the extant literature, there is a growing number of studies on sustainable multi-tier supply chains. However, there has been limited effort to take stock of existing research to set an agenda for future studies. To address this gap, this study reviews 64 articles through the lens of the triple bottom line theory. Based on the findings, the study develops a framework for sustainable multi-tier supply chains and provides direction for future research.
Journal: International Journal of Production Research
Pages: 4918-4933
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.1946194
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1946194
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# input file: TPRS_A_2017053_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jörg H. Grimm
Author-X-Name-First: Jörg H.
Author-X-Name-Last: Grimm
Author-Name: Joerg S. Hofstetter
Author-X-Name-First: Joerg S.
Author-X-Name-Last: Hofstetter
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: Corporate sustainability standards in multi-tier supply chains – an institutional entrepreneurship perspective
Abstract: 
 This study extends research on buyer firm roles in improving supplier sustainability practices by considering institutions – norms and rules – in the organisational field in which suppliers and sub-suppliers operate, exerting pressures on these actors to align their respectivepractices. We introducethe resource-based view to arrive at a framework outlining key capabilities for institutional entrepreneurs that seek institutionalisation of corporate sustainability standards (CSS) as a new institution across a multi-tier supply chain. The paper draws on the results of an exploratory research study using six comparative case studies within four industries. While institutional entrepreneurship explains how organisations drive institutional change, the resource-based view outlines criteria for organisational capabilities enabling the focal firm to achieve the targeted institutional change. Our analysis suggests five key capabilities enabling a buying firm to effectively institutionalise their requirements in multi-tier supply chains: (1) inter-firm dialogue, (2) risk management, (3) external stakeholder collaboration, (4) cross-functional integration, and (5) continuous improvement. The key organisational capabilities identified help to extend the theory of institutional entrepreneurship with concepts that facilitate institutional change in multi-tier supply chains with respect to corporate sustainability. This exploratory work opens up avenues of additional research in general and supply chain theory development.
Journal: International Journal of Production Research
Pages: 4702-4724
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2021.2017053
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2017053
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# input file: TPRS_A_2025942_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yigit Kazançoglu
Author-X-Name-First: Yigit
Author-X-Name-Last: Kazançoglu
Author-Name: Yucel Ozturkoglu
Author-X-Name-First: Yucel
Author-X-Name-Last: Ozturkoglu
Author-Name: Sachin Kumar Mangla
Author-X-Name-First: Sachin Kumar
Author-X-Name-Last: Mangla
Author-Name: Melisa Ozbiltekin-Pala
Author-X-Name-First: Melisa
Author-X-Name-Last: Ozbiltekin-Pala
Author-Name: Alessio Ishizaka
Author-X-Name-First: Alessio
Author-X-Name-Last: Ishizaka
Title: A proposed framework for multi-tier supplier performance in sustainable supply chains
Abstract: 
 Over the past few years, supply chains have become globalised and multi-tiered. These factors complicate their structure as the focal company is responsible for the problems experienced at each stage in the multi-tier supply chain. The critical issue for focal companies in managing their multi-tier supply chain is to adopt sustainability standards. One of the study's contributions is the role of weight determination in the tiers and evaluation of alternative suppliers in facilitating the effective management of multi-tier supply chains, especially in complex industries such as the food industry. The other contribution of this study is its proposition for a multi-stage framework based on sustainability concerns. The study identifies 14 criteria for companies in diffusing sustainability standards throughout multi-tier supply chains. The weights of these criteria are determined for each tier of the food supply chain using the Best Worst Method. Results show that the ‘environmental’ criteria are most important for supply chain tiers in the food industry. Supply chain visibility/traceability is the most important criteria for the first tier, followed by environmental responsibilities, for the second and environmental competencies for the third. Finally, for the food company, PROMETHEE is used to evaluate three alternative suppliers for each tier.
Journal: International Journal of Production Research
Pages: 4742-4764
Issue: 14
Volume: 61
Year: 2023
Month: 07
X-DOI: 10.1080/00207543.2022.2025942
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2025942
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# input file: TPRS_A_2098871_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jinling Leng
Author-X-Name-First: Jinling
Author-X-Name-Last: Leng
Author-Name: Xingyuan Wang
Author-X-Name-First: Xingyuan
Author-X-Name-Last: Wang
Author-Name: Shiping Wu
Author-X-Name-First: Shiping
Author-X-Name-Last: Wu
Author-Name: Chun Jin
Author-X-Name-First: Chun
Author-X-Name-Last: Jin
Author-Name: Meng Tang
Author-X-Name-First: Meng
Author-X-Name-Last: Tang
Author-Name: Rui Liu
Author-X-Name-First: Rui
Author-X-Name-Last: Liu
Author-Name: Alexander Vogl
Author-X-Name-First: Alexander
Author-X-Name-Last: Vogl
Author-Name: Huiyu Liu
Author-X-Name-First: Huiyu
Author-X-Name-Last: Liu
Title: A multi-objective reinforcement learning approach for resequencing scheduling problems in automotive manufacturing systems
Abstract: 
 This study investigated a multi-objective resequencing scheduling problem in the automotive manufacturing systems due to operational requirements on the color-batching of the paint shop and sequential requirements on the sequence adherence of an assembly shop. Resequencing cars as color-oriented batches reduced the costs of color changes and operational costs for paint shops. Also, assembly shops required paint shops to complete cars with fewer delays so that high sequence adherence with its demand was assured. Based on real-world applications, we investigated two contradictory objectives-color change costs and sequence tardiness-in a single-machine flowshop scheduling environment. A multi-objective-deep-Q-network algorithm was developed to determine the Pareto frontier. Reward shaping was designed to improve the convergence of the neural network. The 2D-folded-normal distribution was designed to sample the preference, which made the exploration and exploitation of the neural network more comprehensive and improved the training efficiency. Two experiments were conducted and showed that the proposed approach outperformed the meta-heuristic algorithm and the envelope Q-learning algorithm in solving time, performance, the convergence of the neural network, and the diversity of the Pareto frontier. Therefore, the proposed approach can be used in automotive paint shops to improve scheduling efficiency and reduce operational costs.
Journal: International Journal of Production Research
Pages: 5156-5175
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2098871
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2098871
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# input file: TPRS_A_2098074_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: David Damand
Author-X-Name-First: David
Author-X-Name-Last: Damand
Author-Name: Youssef Lahrichi
Author-X-Name-First: Youssef
Author-X-Name-Last: Lahrichi
Author-Name: Marc Barth
Author-X-Name-First: Marc
Author-X-Name-Last: Barth
Title: Parameterisation of demand-driven material requirements planning: a multi-objective genetic algorithm
Abstract: 
 Demand-Driven Material Requirements Planning (DDMRP) is a recent inventory management method that has generated considerable interest in both academia and industry. Many recent papers have demonstrated the superiority of DDMRP over classical methods like MRP or Kanban, an observation confirmed by companies that have implemented DDMRP. However, DDMRP depends on many parameters that affect its performance. Only general rules are given by the authors of the method to fix these parameters but no algorithm. The present paper aims to fill this gap by proposing a multi-objective optimisation algorithm to fix a set of eight identified parameters. The suggested genetic algorithm is coupled with a simulation algorithm that computes the objective functions. Two opposing objective functions are considered: first, the maximisation of orders delivered on-time to the customer and, second, the minimisation of on-hand inventory. A set of data instances was generated to test the suggested method. Fronts of non-dominated solutions are found for all these instances.
Journal: International Journal of Production Research
Pages: 5134-5155
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2098074
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2098074
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# input file: TPRS_A_2099319_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Minjae Park
Author-X-Name-First: Minjae
Author-X-Name-Last: Park
Author-Name: Hoang Pham
Author-X-Name-First: Hoang
Author-X-Name-Last: Pham
Title: Condition-based maintenance for a degradation-shock dependence system under warranty
Abstract: 
 In this paper, we derive a condition-based maintenance strategy for a degradation-shock dependence system subject to two causes of failure, degradation and random shocks. We develop a reliability model for a system under warranty for failure in which we consider the dependence between the degradation process and random shocks and do a warranty cost analysis based on the suggested model. We consider a degradation-shock dependence system that is under warranty with three separate services: repair, replacement, and preventive maintenance. These are triggered when a product degradation crosses one of three predetermined degradation thresholds. We also investigate the dependence between random shocks and degradation modelled by a time-scaled covariate factor. We study the random shock considering fatal shocks that require replacement and nonfatal shocks that require only repair and the degradation caused by nonfatal shocks. The condition-based maintenance strategy for a degradation-shock dependence system is a novel approach to analysing system degradation, with a goal of optimising warranty costs; we also minimise the expected total system cost to find an optimal warranty length. We present several numeric examples and real-world applications to illustrate our proposed approach.
Journal: International Journal of Production Research
Pages: 5212-5227
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2099319
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2099319
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# input file: TPRS_A_2101031_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Camilla Lundgren
Author-X-Name-First: Camilla
Author-X-Name-Last: Lundgren
Author-Name: Cecilia Berlin
Author-X-Name-First: Cecilia
Author-X-Name-Last: Berlin
Author-Name: Anders Skoogh
Author-X-Name-First: Anders
Author-X-Name-Last: Skoogh
Author-Name: Anders Källström
Author-X-Name-First: Anders
Author-X-Name-Last: Källström
Title: How industrial maintenance managers perceive socio-technical changes in leadership in the Industry 4.0 context
Abstract: 
 Innovations and advancements in technology create new opportunities to run and maintain manufacturing plants, which we refer to as digitalised manufacturing. This development is recognised as a socio-technical system (STS) change, where a change in the production system’s goals, technology, processes, people, or environment may lead to ripple effects between those sub-systems. Despite this, technology development and technology use cases account for most of the research within digitalised manufacturing, while little attention has been devoted to leadership practices considering digitalised manufacturing from a socio-technical perspective. This paper focuses on the maintenance organisation, whose mission in a company is to keep production systems functional. We aim to describe leadership in industrial maintenance from an STS perspective. This is a unique interview study where twenty maintenance managers from Swedish manufacturing industry offer their perspective on the changing leadership within maintenance, providing a unique insight into the challenges facing leaders of maintenance in digitalised manufacturing. We frame the empirical findings using an STS framework and propose an overall consideration model for leadership that supports the development of a functional maintenance organisation in the face of pervasive digitalisation.
Journal: International Journal of Production Research
Pages: 5282-5301
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2101031
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2101031
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# input file: TPRS_A_2092430_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yongcong Liu
Author-X-Name-First: Yongcong
Author-X-Name-Last: Liu
Author-Name: Yixuan Xiao
Author-X-Name-First: Yixuan
Author-X-Name-Last: Xiao
Author-Name: Yue Dai
Author-X-Name-First: Yue
Author-X-Name-Last: Dai
Title: Omnichannel retailing with different order fulfillment and return options
Abstract: 
 The omnichannel strategies buy-online-and-return-in-store (BORS) and buy-online-and-pick-up-in-store (BOPS) have attracted attention from both industry and academia. In practice, major retailers adopt BORS and BOPS both individually and jointly, which motivates us to explore when it is profitable for a retailer to adopt BORS or/and BOPS strategy. We formulate a stylised model that captures (1) consumers' uncertainty about product match, (2) the offline search cost for consumers, and (3) the cross-selling effect of the consumers' store visit. We find that the cross-selling benefit and the offline search cost have a significant impact on the retailer's optimal omnichannel strategy. When the cross-selling benefit is sufficiently low, adopting BORS alone is optimal for the retailer. When the cross-selling benefit is moderate and the offline search cost is high, adopting both strategies has a complementary effect, and it is optimal for the retailer to adopt both omnichannel strategies jointly. However, when the cross-selling benefit is sufficiently high, adopting both strategies could be less profitable to the retailer than adopting the BOPS strategy alone. Moreover, consumer surplus may decrease in this case, suggesting that adopting both omnichannel strategies could result in a lose-lose situation for both the retailer and the consumers.
Journal: International Journal of Production Research
Pages: 5053-5074
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2092430
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2092430
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# input file: TPRS_A_2099321_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ravi Kalaiarasan
Author-X-Name-First: Ravi
Author-X-Name-Last: Kalaiarasan
Author-Name: Tarun Kumar Agrawal
Author-X-Name-First: Tarun Kumar
Author-X-Name-Last: Agrawal
Author-Name: Jan Olhager
Author-X-Name-First: Jan
Author-X-Name-Last: Olhager
Author-Name: Magnus Wiktorsson
Author-X-Name-First: Magnus
Author-X-Name-Last: Wiktorsson
Author-Name: Jannicke Baalsrud Hauge
Author-X-Name-First: Jannicke Baalsrud
Author-X-Name-Last: Hauge
Title: Supply chain visibility for improving inbound logistics: a design science approach
Abstract: 
 Supply chain visibility (SCV) has been gaining recognition in recent years as a key factor for achieving analytical capabilities and improving supply chain performance. However, levels of SCV implementation lag behind current technological advances. This research was motivated by the lack of visibility in inbound logistics, which limits the possibility of managing deviation, in particular concerning changes in arrival time of incoming goods, in large industrial firms. We addressed this problem by adopting a design science approach. In particular, we followed context–intervention–mechanism–outcome (CIMO) logic to map and analyse material and information flows. The problems areas were successively translated via business and functional requirements into technological solutions. We evaluated alternative technologies using controlled experiments that mimicked real-life situations. This study provides guidance for manufacturing companies aiming to enhance deviation management and predictive capabilities by improving visibility in their inbound logistics and potentially extending visibility to other areas, such as internal and outbound flows.
Journal: International Journal of Production Research
Pages: 5228-5243
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2099321
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2099321
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# input file: TPRS_A_2100840_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mayank Shukla
Author-X-Name-First: Mayank
Author-X-Name-Last: Shukla
Author-Name: S.P. Sarmah
Author-X-Name-First: S.P.
Author-X-Name-Last: Sarmah
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: A multi-objective framework for the identification and optimisation of factors affecting cybersecurity in the Industry 4.0 supply chain
Abstract: 
 Digital assets are highly vulnerable and always prone to malicious intervention. Identification of causes of such intervention for timely support and assistance remains a key challenge for businesses to remain functional and thrive with the competition. A framework is proposed in this paper for identifying cyber risk, threat, and countermeasure, based on breach databases and textual information processing. Alongside, a multi-objective optimisation of a mixed-integer non-linear problem (MINLP) is made post linearisation to find out a suitable trade-off between cyber risk and investment. The model helps in effective decision-making by finding the proneness of suppliers (as nodes) in the sequence of reducing vulnerability and pairing of categorised factors. The web scrapping and historical databases are processed to extract relationships among categorised factors using natural language processing (NLP). Pareto optimal pairs are obtained to explain the application of the current contribution in terms of risk-cost trade-off. It helps in forming preventive strategies with a suitable amount of investment and the required order of precedence or susceptibility.
Journal: International Journal of Production Research
Pages: 5266-5281
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2100840
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2100840
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# input file: TPRS_A_2093682_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ehsan Badakhshan
Author-X-Name-First: Ehsan
Author-X-Name-Last: Badakhshan
Author-Name: Peter Ball
Author-X-Name-First: Peter
Author-X-Name-Last: Ball
Title: Applying digital twins for inventory and cash management in supply chains under physical and financial disruptions
Abstract: 
 Supply chains (SCs) operate in a highly disruptive environment, where they face a variety of disruptions in product and cash flows. In such an environment, determining suitable inventory and cash replenishment policies ensures that cash and inventory are at the right place at the right time and provides a productive SC with high customer service levels. In this study, we first examine the impact of the disruptions in physical and financial flows on SC performance. We then, investigate the potential of a SC digital twin framework to help decision-makers in managing inventory and cash throughout the SC during disruption, currently absent from the literature. The proposed SC digital twin framework integrates machine learning (ML) and simulation to identify the inventory and cash replenishment policies that minimise the impact of the disruptions on SC performance. This approach proves effective in a SC disrupted by demand increase, capacity reduction, and credit purchase increase. Results show that employing the SC digital twin leads to a noticeable reduction in the cash conversion cycle for upstream members of the SCs. We observe that the cash conversion cycle for the upstream SC members is greatly impacted by the inventory policy employed by their immediate downstream members.
Journal: International Journal of Production Research
Pages: 5094-5116
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2093682
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2093682
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# input file: TPRS_A_2093681_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Elaheh Ghasemi
Author-X-Name-First: Elaheh
Author-X-Name-Last: Ghasemi
Author-Name: Nadia Lehoux
Author-X-Name-First: Nadia
Author-X-Name-Last: Lehoux
Author-Name: Mikael Rönnqvist
Author-X-Name-First: Mikael
Author-X-Name-Last: Rönnqvist
Title: Coordination, cooperation, and collaboration in production-inventory systems: a systematic literature review
Abstract: 
 In a competitive environment, effective management of production and inventory decisions is critical to maintain an efficient and balanced flow of the supply chain system. Manufacturing companies across supply chains have recognised that inventories can be managed more effectively through increased collaboration and better coordination. In practice, production planning and inventory control decisions are not separated, and supply chain members can significantly reduce costs through the coordination of production and inventory decisions. Research in this field has received much attention in recent years. This study aims to review coordination, cooperation, and collaboration (CCC) mechanisms in production-inventory studies. By using an established research methodology, a total of 118 articles were reviewed and the implemented CCC mechanisms were classified into three main categories: contractual practices, joint decision-making practices, and information-sharing practices. By examining the selected articles according to the implemented methodologies and their impact on the sustainably of supply chains, research gaps and future directions for academics and practitioners were identified. This study shows that more research is needed to discover the impact of combining different CCC mechanisms on supply chain efficiency in terms of economic, environmental, and social concerns.
Journal: International Journal of Production Research
Pages: 5322-5353
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2093681
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2093681
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# input file: TPRS_A_2101400_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Siqiang Guo
Author-X-Name-First: Siqiang
Author-X-Name-Last: Guo
Author-Name: Manjeet Singh
Author-X-Name-First: Manjeet
Author-X-Name-Last: Singh
Author-Name: Shadi Goodarzi
Author-X-Name-First: Shadi
Author-X-Name-Last: Goodarzi
Title: Enhance picking viability in E-commerce warehouses under pandemic
Abstract: 
 The COVID-19 pandemic has caused critical challenges for e-commerce warehouses that strive to fulfill surging customer demand while facing a high virus infection risk. Current literature on picking optimization overlooks warehouse safety under pandemic conditions. Meanwhile, scattered storage and zone-wave-batch picking have been used in parallel by many large e-commerce warehouses, these two operational policies have not been considered together in picking optimization studies. This paper fills these gaps by solving an order batching problem considering scattered storage, zone-wave-batch picking, and pickers’ proximity simultaneously. We formulate and solve the mathematical model of the discussed problem and propose the Aisle-Based Constructive Batching Algorithm (ABCBA) to help warehouses pick more efficiently and safely. Experiments with extensive datasets from a major third-party logistics (3PL) company show that, compared to the current picking strategy, ABCBA can reduce the total picking time and the virus infection risk due to pickers’ proximity by 46% and 72%, respectively. Compared to other heuristics like tabu + nLSA3 (Yang, Zhao, and Guo 2020), ABCBA gets better results using less computation time.
Journal: International Journal of Production Research
Pages: 5302-5321
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2101400
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2101400
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# input file: TPRS_A_2089607_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Weiwei Ge
Author-X-Name-First: Weiwei
Author-X-Name-Last: Ge
Author-Name: Hongcheng Li
Author-X-Name-First: Hongcheng
Author-X-Name-Last: Li
Author-Name: Xuanhao Wen
Author-X-Name-First: Xuanhao
Author-X-Name-Last: Wen
Author-Name: Chengchao Li
Author-X-Name-First: Chengchao
Author-X-Name-Last: Li
Author-Name: Huajun Cao
Author-X-Name-First: Huajun
Author-X-Name-Last: Cao
Author-Name: Bin Xing
Author-X-Name-First: Bin
Author-X-Name-Last: Xing
Title: Mathematical modelling of carbon emissions and process parameters optimisation for laser welding cell
Abstract: 
 Laser welding has been widely employed for aluminum alloy body-in-white. However, owing to the low utilisation efficiency of energy and material, the carbon emission of laser welding is serious. In this paper, the mathematical modelling of carbon emissions and process parameters optimisation for laser welding cells are studied. The carbon emission characteristics of the laser welding system are analysed, and the carbon emission model of the laser welding cell considering both welding features and welding transfers is established. Besides, the process parameters optimisation model of laser welding cell is developed. To obtain optimal welding sequence, a combinatorial algorithm based on Culture Algorithm and Ant Colony Algorithm is proposed. Based on the optimal welding sequence, the optimal transfer speed is obtained through mathematical theory. Furthermore, a case study is performed to verify the feasibility and reliability of the process parameters optimisation model. Additionally, compared with the Ant Colony Algorithm, the proposed solution algorithm has better comprehensive performance in terms of convergence speed and optimisation accuracy. This study lays a theoretical foundation for carbon emission modelling of the laser welding cell, and can support the automobile enterprise to make processing parameters selection of the laser welding line in the design stage.
Journal: International Journal of Production Research
Pages: 5009-5028
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2089607
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2089607
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# input file: TPRS_A_2098872_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Qi Zhang
Author-X-Name-First: Qi
Author-X-Name-Last: Zhang
Author-Name: Shixin Liu
Author-X-Name-First: Shixin
Author-X-Name-Last: Liu
Author-Name: MengChu Zhou
Author-X-Name-First: MengChu
Author-X-Name-Last: Zhou
Title: A robust optimization approach to steel grade design problem subject to uncertain yield and demand
Abstract: 
 This work formulates and investigates a steel grade design problem (SGDP) arising from a production process of steelmaking continuous casting. For the first time, we consider uncertain yield and demand in SGDP and construct a two-stage robust optimisation model accordingly. Then, we propose an enhanced column-and-constraint generation algorithm to obtain high-quality solutions. By exploiting the problem characteristics, we first use a Lagrangian relaxation method to decompose SGDP into multiple subproblems and then apply a standard column-and-constraint generation algorithm to solve the latter. At last, we test the proposed algorithm by extensive instances constructed based on actual production rules of a steelmaking shop. Numerical results show that it can effectively solve large-scale SGDPs. The obtained plan is better than those obtained by a commonly-used and standard column-and-constraint generation algorithm.
Journal: International Journal of Production Research
Pages: 5176-5192
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2098872
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2098872
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# input file: TPRS_A_2092041_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Salama Shady
Author-X-Name-First: Salama
Author-X-Name-Last: Shady
Author-Name: Toshiya Kaihara
Author-X-Name-First: Toshiya
Author-X-Name-Last: Kaihara
Author-Name: Nobutada Fujii
Author-X-Name-First: Nobutada
Author-X-Name-Last: Fujii
Author-Name: Daisuke Kokuryo
Author-X-Name-First: Daisuke
Author-X-Name-Last: Kokuryo
Title: Feature selection approach for evolving reactive scheduling policies for dynamic job shop scheduling problem using gene expression programming
Abstract: 
 Dispatching rules are one of the most widely applied methods for solving Dynamic Job Shop Scheduling problems (DJSSP) in real-world manufacturing systems. Hence, the automated design of effective rules has been an important subject in the scheduling literature for the past several years. High computational requirements and difficulty in interpreting generated rules are limitations of literature methods. Also, feature selection approaches in the field of automated design of scheduling policies have been developed for the tree-based GP approach only. Therefore, the aim of this study is to propose a feature selection approach for the Gene Expression Programming (GEP) algorithm to evolve high-quality rules in simple structures with an affordable computational budget. This integration speeds up the search process by restricting the GP search space using the linear representation of the GEP algorithm and creates concise rules with only meaningful features using the feature selection approach. The proposed algorithm is compared with five algorithms and 30 rules from the literature under different processing conditions. Three performance measures are considered including total weighted tardiness, mean tardiness, and mean flow time. The results show that the proposed algorithm can generate smaller rules with high interpretability in a much shorter training time.
Journal: International Journal of Production Research
Pages: 5029-5052
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2092041
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2092041
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# input file: TPRS_A_2093684_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Celso Gustavo Stall Sikora
Author-X-Name-First: Celso Gustavo Stall
Author-X-Name-Last: Sikora
Author-Name: Christian Weckenborg
Author-X-Name-First: Christian
Author-X-Name-Last: Weckenborg
Title: Balancing of assembly lines with collaborative robots: comparing approaches of the Benders’ decomposition algorithm
Abstract: 
 In recent years, human workers in manual assembly lines are increasingly being supported by the deployment of complementary technology. Collaborative robots (or cobots) represent a low-threshold opportunity for partial automation and are increasingly being utilised by manufacturing corporations. As collaborative robots can be used to either conduct tasks in parallel to the human worker or collaborate with the worker on an identic task, industrial planners experience an increasingly complex environment of assembly line balancing. This contribution proposes three different decomposition approaches for Benders’ decomposition algorithms exploring the multiple possible partitions of the formulation variables. We evaluate the performance of the algorithms by conducting extensive computational experiments using test instances from literature and compare the findings with results generated by a commercial solver and a metaheuristic solution procedure. The results demonstrate the Benders’ decomposition algorithms’ efficiency of finding exact solutions even for large instances, outperforming the benchmark procedures in computational effort and solution quality.
Journal: International Journal of Production Research
Pages: 5117-5133
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2093684
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2093684
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2093142_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Peng Ma
Author-X-Name-First: Peng
Author-X-Name-Last: Ma
Author-Name: Yue Meng
Author-X-Name-First: Yue
Author-X-Name-Last: Meng
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Mingdu Li
Author-X-Name-First: Mingdu
Author-X-Name-Last: Li
Title: Optimal models for sustainable supply chain finance: evidence from electric vehicle industry
Abstract: 
 Prior research studies sustainable supply chain (SC) management for the electric vehicle (EV) industry in which SC members have sufficient funds. However, many EV firms always face the problems of financial constraints, which lead to the importance and urgency for the research of sustainable SC finance. To address this new problem, we consider the members of the electric vehicle supply chain (EVSC) can be risk averse because of the financial risks from uncertain demands. The EV retailer has limited liability and can obtain loans through a bank or an EV manufacturer. We first address a base model in which the EV manufacturer invests in the green research and development (R&D) effort and investigate operational decisions and sustainable SC finance strategies for the EVSC and members. Using the real data from a top-four EV manufacturer in the world, we do a case study to verify the outcomes of the base model and find that the EVSC and members can derive higher profits with MF strategy for the most cases. Furthermore, we extend the base model to consider government subsidies and the EV retailer's service levels, and find that government subsidies and the EV retailer's service are beneficial to the EVSC.
Journal: International Journal of Production Research
Pages: 5075-5093
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2093142
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2093142
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# input file: TPRS_A_2098874_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mingxing Li
Author-X-Name-First: Mingxing
Author-X-Name-Last: Li
Author-Name: Daqiang Guo
Author-X-Name-First: Daqiang
Author-X-Name-Last: Guo
Author-Name: Ming Li
Author-X-Name-First: Ming
Author-X-Name-Last: Li
Author-Name: Ting Qu
Author-X-Name-First: Ting
Author-X-Name-Last: Qu
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Operation twins: production-intralogistics synchronisation in Industry 4.0
Abstract: 
 The widespread adoption of Industry 4.0 technologies is revolutionising how manufacturing operations are managed and done. This revolution drives manufacturing practitioners to reevaluate their current manufacturing planning and control (MPC) strategies to maintain global competitiveness. The production and intralogistics (PiL) operations within traditional MPC systems are organised separately, which results in inferior overall solutions. PiL operations in a single factory are inherently coupled and interact with each other throughout the entire process, which needs synchronous organisation and operations. This paper introduces a novel concept of operations twins (OT), with vertical twinning and horizontal twining, for achieving PiL synchronisation by leveraging Industry 4.0 technologies and innovative operations management strategies. An Internet-of-Things (IoT)-based vertical twinning method is developed for real-time object-level data collection and information-sharing between PiL. A horizontal twinning mechanism is proposed to support real-time coordination of production and intralogistics operations with real-time information-sharing. A numerical study is carried out, and the results show that OT outperforms the widely used static and dynamic methods regarding the overall stability and typical measures such as makespan, average manufacturing time, and average tardiness under different levels of uncertainties.
Journal: International Journal of Production Research
Pages: 5193-5211
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2098874
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2098874
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# input file: TPRS_A_2099769_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Nuno Falcão e Cunha
Author-X-Name-First: Nuno
Author-X-Name-Last: Falcão e Cunha
Author-Name: Thiam-Soon Gan
Author-X-Name-First: Thiam-Soon
Author-X-Name-Last: Gan
Author-Name: Eduardo Curcio
Author-X-Name-First: Eduardo
Author-X-Name-Last: Curcio
Author-Name: Pedro Amorim
Author-X-Name-First: Pedro
Author-X-Name-Last: Amorim
Author-Name: Bernardo Almada-Lobo
Author-X-Name-First: Bernardo
Author-X-Name-Last: Almada-Lobo
Author-Name: Martin Grunow
Author-X-Name-First: Martin
Author-X-Name-Last: Grunow
Title: Robust supply chain design with suppliers as system integrators: an aerospace case study
Abstract: 
 Original Equipment Manufacturers (OEMs) have sought new supply chain paradigms that allowed them to focus on core activities, i.e. overall product design and commercialisation. This pursuit led to partnerships with a new generation of tier-1 strategic suppliers acting as integrators. Integrators are not only responsible for system supply, but also for system design. However, critical integrators were not able to live up to their new roles, which led to costly delays in development and production. These failures highlight the ineptitude of current risk management practices employed by OEMs. To support OEMs in implementing a more differentiated and suitable approach to the use of integrators, this paper proposes a mathematical programming model for Supply Chain Design (SCD). Instead of looking at the introduction of integrators as a dichotomous decision, the model suggests the optimal number of integrators, i.e. systems, and individual part suppliers. We propose new measures for integration risk, which build upon current risk assessment practices. Robust optimisation is used to study the effect of uncertainty over baseline risk values. All approaches were tested using both randomly generated instances and real data from a large European OEM in the aerospace industry.
Journal: International Journal of Production Research
Pages: 5244-5265
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2099769
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2099769
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# input file: TPRS_A_2087568_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jakob Marolt
Author-X-Name-First: Jakob
Author-X-Name-Last: Marolt
Author-Name: Simona Šinko
Author-X-Name-First: Simona
Author-X-Name-Last: Šinko
Author-Name: Tone Lerher
Author-X-Name-First: Tone
Author-X-Name-Last: Lerher
Title: Model of a multiple-deep automated vehicles storage and retrieval system following the combination of Depth-First storage and Depth-First relocation strategies
Abstract: 
 This paper studies a multiple-deep automated vehicles storage and retrieval system (AVS/RS) rack following a Depth-First storage and a Depth-First relocation strategy. We propose an analytical model based on a novel approach that utilises the Markov chain stochastic steady-state model. To verify the analytical model, a numerical simulation is developed. We also derive an empirical model using first- and second-order polynomial functions that are accurately fitted with regression equations and examined with MAPE and RMSE prediction accuracy measurements from a large-scale simulation study. The empirical model enables a straightforward calculation of the expected number of location movements of shuttle carriers and the attached satellite vehicles from which the AVS/RS throughput performance can be calculated. We present threefold and sixfold deep AVS/RS case study scenarios with an equal number of storage locations and estimate the cycle times. The evaluation of the case study results reveals that the analytical and empirical models achieve less than 2% error in the case of a dual command cycle time prediction compared to the simulation results. This proves that our approach allows an accurate estimation of multiple-depth AVS/RS throughput performance.
Journal: International Journal of Production Research
Pages: 4991-5008
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2087568
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2087568
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# input file: TPRS_A_2086085_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Rodrigo Romero-Silva
Author-X-Name-First: Rodrigo
Author-X-Name-Last: Romero-Silva
Author-Name: Margarita Hurtado-Hernández
Author-X-Name-First: Margarita
Author-X-Name-Last: Hurtado-Hernández
Title: The effects of supply variability on the performance of assembly systems
Abstract: 
 Assembly processes play a big role in the current business context as global supply chains depend on many subcomponents to produce a single finished product. Previous studies have shown contrasting results regarding the effect that supply variability (the variability of feeding stations) has on the performance of assembly systems, as opposed to the variability of the station matching and assembling the components. This paper aims to close this gap by studying the behaviour of simple assembly systems with differing degrees of variability allocation among the stations through an experimental simulation study. Results suggest that a reduction in feeding station variability results in higher throughput, even in systems where the variability of one of the feeding stations increases while the other decreases. Furthermore, in scenarios with high total variance, the highest throughput is reached by transferring both variance and work from one of the feeding stations to any other station, whereas in low variance systems symmetrical work transfer to the feeding stations results in the highest throughput, as previously shown. Finally, reducing feeding station variability decreased the time spent in the assembly station (waiting time for component matching plus time for the assembly operation) only in experiments with high total variance.
Journal: International Journal of Production Research
Pages: 4973-4990
Issue: 15
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2086085
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2086085
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# input file: TPRS_A_2103749_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Francesco Zangaro
Author-X-Name-First: Francesco
Author-X-Name-Last: Zangaro
Author-Name: Stefan Minner
Author-X-Name-First: Stefan
Author-X-Name-Last: Minner
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Title: The multi-manned joint assembly line balancing and feeding problem
Abstract: 
 The Joint Assembly Line Balancing and Feeding Problem (JALBFP) assigns a line feeding mode to each component (Assembly Line Feeding Problem) and each task to a workplace of a station (Assembly Line Balancing Problem). Current literature offers numerous optimisation models that solve these problems sequentially. However, only few optimisation models, provide a joint solution. To solve the JALBFP for a multi-manned assembly line, we propose a Mixed Integer Linear Programming (MILP) model and a heuristic that relies on the Adaptive Large Neighborhood Search (ALNS) framework by considering multiple workplaces per station and three different feeding policies: line stocking, travelling kitting and sequencing. The objective function minimises the cost of the whole assembly system which considers supermarket, transportation, assembly operations, and investment costs. Although the JALBFP requires higher computation times, it leads to a higher total cost reduction compared to the sequential approach. Through a numerical study, we validate the heuristic approach and find that the average deviation to the MILP model is around 1%. We also compare the solution of the JALBFP with that of the sequential approach and find an average total cost reduction of 10.1% and a maximum total cost reduction of 43.8%.
Journal: International Journal of Production Research
Pages: 5543-5565
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2103749
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2103749
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# input file: TPRS_A_2104179_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Sara Babaee
Author-X-Name-First: Sara
Author-X-Name-Last: Babaee
Author-Name: Mojtaba Araghi
Author-X-Name-First: Mojtaba
Author-X-Name-Last: Araghi
Author-Name: Ignacio Castillo
Author-X-Name-First: Ignacio
Author-X-Name-Last: Castillo
Author-Name: Borzou Rostami
Author-X-Name-First: Borzou
Author-X-Name-Last: Rostami
Title: Attractiveness factors in retail category space location-allocation problem
Abstract: 
 We study the problem of category space location-allocation in the retail industry. We introduce a new attractiveness factor to reflect the product-based visibility level in designing the optimal allocation policy. This factor will be determined for each aisle by the lineup of product categories allocated to that aisle and all other aisles sharing a shopping path with it. We explore how considering the classical location-based attractiveness and the proposed product-based attractiveness can improve a retailer's overall space profitability. We develop a modelling framework that integrates both location-based and product-based attractiveness factors in a mixed-integer nonlinear program. Due to the non-linearity and non-convexity of the proposed model, large-scale instances are computationally challenging to solve using the state-of-the-art commercial solvers. We thus introduce a two-stage heuristic solution method that generates a near-optimal solution in a reasonable amount of time. Using the two-stage model, we explore the optimal store design for an illustrative case study. The results couple the optimal category space allocation to customers' shopping paths and create a profitability-maximising balance between the placement of high-demand and high-impulse product categories. We show that focussing on product-based attractiveness exposes the store to congestion risks, which can be prevented by adding constraints limiting congestion in different aisles of the store.
Journal: International Journal of Production Research
Pages: 5566-5584
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2104179
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2104179
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# input file: TPRS_A_2111614_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ralph Richter
Author-X-Name-First: Ralph
Author-X-Name-Last: Richter
Author-Name: Marius Syberg
Author-X-Name-First: Marius
Author-X-Name-Last: Syberg
Author-Name: Jochen Deuse
Author-X-Name-First: Jochen
Author-X-Name-Last: Deuse
Author-Name: Peter Willats
Author-X-Name-First: Peter
Author-X-Name-Last: Willats
Author-Name: David Lenze
Author-X-Name-First: David
Author-X-Name-Last: Lenze
Title: Creating lean value streams through proactive variability management
Abstract: 
 Complex product and production systems often result in high variability in the production flow, prohibiting the sustainable implementation of lean practices. In this paper the authors introduce a PDCA cycle to analyse and reduce variability in value streams. The value stream is divided into zones, which are then qualified as stable or unstable. Lean practices can be applied in stable zones, unstable zones remain expert-driven. Measures are introduced to reduce variability in unstable zones with the ultimate target, to turn them into stable zones, extending sustainable lean activities in the value stream, step by step. An IT system is developed to acquire, process and visualise the vast amount of data to provide structured information for experts and management for the reduction of variability in production.
Journal: International Journal of Production Research
Pages: 5692-5703
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2111614
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2111614
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# input file: TPRS_A_2110536_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Timo Lehmann
Author-X-Name-First: Timo
Author-X-Name-Last: Lehmann
Author-Name: Jakob Hußmann
Author-X-Name-First: Jakob
Author-X-Name-Last: Hußmann
Title: Travel time model for multi-deep automated storage and retrieval systems with different storage strategies
Abstract: 
 Travel time models for automated storage and retrieval systems (AS/RS) are used to define average travel times during storage/retrieval operations in an AS/RS. With an increasing depth of AS/RS racks, storage goods are stored in front of each other. This can lead to relocation operations of blocking goods causing higher travel times. This paper derives analytically and presents four travel time models for multi-deep AS/RS following four storage allocation strategies. Two models handle random strategies, one minimises the variance of storage channel fillings and the fourth maximises this variance. Evaluation and comparison of different models is followed by a discrete event simulation to verify these models. It is shown that the minimal variance strategy achieves the lowest relocation numbers and also the lowest total travel times, the random strategies perform between the minimal and maximal variance strategy.
Journal: International Journal of Production Research
Pages: 5676-5691
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2110536
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2110536
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# input file: TPRS_A_2110017_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Rakshit Kumar Singh
Author-X-Name-First: Rakshit Kumar
Author-X-Name-Last: Singh
Author-Name: A. R. Singh
Author-X-Name-First: A. R.
Author-X-Name-Last: Singh
Author-Name: R. K. Yadav
Author-X-Name-First: R. K.
Author-X-Name-Last: Yadav
Author-Name: Rajeev Kumar Upadhyay
Author-X-Name-First: Rajeev Kumar
Author-X-Name-Last: Upadhyay
Title: A station crashing-based recursive approach for disassembly line balancing problem in the presence of task failure
Abstract: 
 Disassembly recovers the valuable parts/subassemblies or materials from old and outdated products. The collected old and outdated products have inherent variability in quality, which frequently results in task failure. In disassembly line balancing literature, the authors have handled task failure situations using a predictive-reactive approach which relaxes the cycle time constraint. This relaxation disturbs the paced setting of the disassembly line, which chokes or blocks the workflow in downstream stations. In this manuscript, a station crashing-based recursive solution approach is proposed and a mathematical model is presented to address the task failure problem without relaxing the cycle time constraint. The aim of the proposed approach is to maximise the profit of the disassembly line and minimise the number of workstations required for accommodating all corrective actions. The proposed algorithm is demonstrated with the help of a case study of a toy car. Numerical experiments are performed on the proposed recursive solution framework to (i) test its compatibility with other evolutionary algorithms; (ii) compare its performance with the predictive-reactive approach; and (iii) validate the use of a probability-based station crashing scheme. The results indicate that the proposed approach can consistently produce a significantly better solution (19–28.5% improvement) than the PR approach.
Journal: International Journal of Production Research
Pages: 5659-5675
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2110017
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2110017
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# input file: TPRS_A_2102450_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yini Zheng
Author-X-Name-First: Yini
Author-X-Name-Last: Zheng
Author-Name: Qi Fu
Author-X-Name-First: Qi
Author-X-Name-Last: Fu
Author-Name: Juan Li
Author-X-Name-First: Juan
Author-X-Name-Last: Li
Author-Name: Lianmin Zhang
Author-X-Name-First: Lianmin
Author-X-Name-Last: Zhang
Title: Demand forecasts with judgement bias in a newsvendor problem
Abstract: 
 We explore the impact of judgement bias on demand forecast accuracy and profit to identify the driving force of decision-makers to be biased. We study the accuracy-maximising forecasts and the profit-maximising forecasts, which results in the least error of demand forecasts and minimum deviation from the optimal order decision, respectively. Under the assumption that period-to-period demand is independent over time, we find that both types of forecasts are biased. It implies that a newsvendor has the motivation to be biased to obtain either a more accurate demand forecast or a higher profit. Moreover, the decision error under the accuracy-maximising forecasts can be lower than that under unbiased demand forecasts and be bounded by twice of the error under profit-maximising forecasts. It suggests that the biased accuracy-maximising forecasts can perform satisfactorily in both forecasts and decisions. We further relax the assumption of independent demand by considering correlated and trended demand processes, and show the robustness of the positive impact of judgement bias. We then propose a method to solve pure data-driven newsvendor problem and examine its performance with empirical evidence. Our paper contributes to the literature on behavioural operations management by investigating the rationality of judgement bias and its implications.
Journal: International Journal of Production Research
Pages: 5468-5482
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2102450
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2102450
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# input file: TPRS_A_2112105_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Harry Sisley
Author-X-Name-First: Harry
Author-X-Name-Last: Sisley
Author-Name: Guvenc Dik
Author-X-Name-First: Guvenc
Author-X-Name-Last: Dik
Author-Name: James McGree
Author-X-Name-First: James
Author-X-Name-Last: McGree
Author-Name: Paul Corry
Author-X-Name-First: Paul
Author-X-Name-Last: Corry
Title: Multi-product multi-region supply chain optimisation for seasonal crops
Abstract: 
 There is a large demand for seasonal crops year-round within Australia, even when they are considered out of season. The demand is satisfied by continually moving production throughout the year to climates where the crops are in season. Management of the supply chain for a major national grower is challenging for several reasons. Due to the large number of planting decisions, it is standard practice for a team of production planners to create the annual production plan. For fresh food production, the supply chain does not contain intermediate storage requiring that the production plan is carefully timed not to waste resources with overproduction. In this paper, we develop a supply chain model that simultaneously manages the production of multiple crops across many growing regions. Production is set to satisfy the demand of multiple end-products while considering the packing plants' throughput capacity, each growing region's harvest capacity, and farm capacity. A time delay may be applied when moving between stages of the supply chain due to the geographic scale being modelled. A deterministic Mixed Integer Program is used to find the optimal planting plan, which minimises the deviation from demand for all products year-round at a minimal cost. Due to the excessive runtime for solving the model, a heuristic solution method is introduced. Numerical experiments demonstrate the advantage of the proposed model over the current manual planning process, which can solve the problem faster and with less deviation across the planning horizon.
Journal: International Journal of Production Research
Pages: 5704-5722
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2112105
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2112105
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# input file: TPRS_A_2102449_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: M. Vimala Rani
Author-X-Name-First: M.
Author-X-Name-Last: Vimala Rani
Author-Name: Muthu Mathirajan
Author-X-Name-First: Muthu
Author-X-Name-Last: Mathirajan
Title: A state-of-art review and a simple meta-analysis on deterministic scheduling of diffusion furnaces in semiconductor manufacturing
Abstract: 
 This paper provides a systematic review of research works on deterministic scheduling of diffusion furnaces (D-SDF) in the semiconductor manufacturing industry. After our screening process, we have identified 72 research articles published during the period 1992 to 2021 in various journals, conference proceedings, etc. This study proposes various classification schemes to systematically organise all the identified studies and to get micro-level details of D-SDF research. Further, various simple meta-analyses in the form of summary counts and percentages are carried out w.r.t (a) proposed classification schemes, and (b) various parameters such as data source, the maximum number of jobs in the instances, benchmark procedure considered, number of articles published, number of contributed authors over the years, top researchers in terms of number of publications, highly cited articles, publication outlets and publishers. From the detailed review analyses, this study suggests/shows future research opportunities/unexplored research problems considering problem configuration/objective(s)/solution methodologies in D-SDF research. Further, mapping of all references of 72 papers on D-SDF w.r.t. proposed classifications schemes would ease new researchers in D-SDF, in multiple perspectives. Finally, meta-analyses presented based on proposed classification schemes and various parameters, considered related to D-SDF problem, provide many important inferences to related researchers.
Journal: International Journal of Production Research
Pages: 5744-5771
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2102449
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2102449
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# input file: TPRS_A_2101401_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yijing Liang
Author-X-Name-First: Yijing
Author-X-Name-Last: Liang
Author-Name: Xin Wang
Author-X-Name-First: Xin
Author-X-Name-Last: Wang
Author-Name: Zhixing Luo
Author-X-Name-First: Zhixing
Author-X-Name-Last: Luo
Author-Name: Dezhi Zhang
Author-X-Name-First: Dezhi
Author-X-Name-Last: Zhang
Title: Integrated optimisation of loading schedules and delivery routes
Abstract: 
 In warehouses, routing decisions for vehicles are highly related to the schedule of docks and loading operations. To mind the gap that most existing studies consider the routing decisions solely, this study investigates the vehicle routing problem with time windows and loading scheduling (VRPTW-LS). In this problem, the loading schedules at the loading docks and the visiting sequences for vehicles are determined to minimise the total travelled distance. To solve this problem, an adaptive large neighbourhood search algorithm, embedded with a tailored solution representation and an efficient feasibility check mechanism, is developed. In addition, the results of extensive computational experiments verify the effectiveness and efficiency of the proposed algorithm, and some analyses are conducted to obtain managerial insights.
Journal: International Journal of Production Research
Pages: 5354-5371
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2101401
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2101401
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2101403_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jonny Herwan
Author-X-Name-First: Jonny
Author-X-Name-Last: Herwan
Author-Name: Takashi Misaka
Author-X-Name-First: Takashi
Author-X-Name-Last: Misaka
Author-Name: Yoshiyuki Furukawa
Author-X-Name-First: Yoshiyuki
Author-X-Name-Last: Furukawa
Author-Name: Ichiro Ogura
Author-X-Name-First: Ichiro
Author-X-Name-Last: Ogura
Author-Name: Hitoshi Komoto
Author-X-Name-First: Hitoshi
Author-X-Name-Last: Komoto
Title: A proposal for improving production efficiency of existing machining line through a hybrid monitoring and optimisation process
Abstract: 
 In a machining line with a Lean manufacturing environment, such as one used for mass production of automotive components, tool life is determined by a tool counter that is set on the safe side to avoid producing a failed product, so the cutting tools are typically underutilised. On the other hand, cutting parameters optimisation, which has a significant impact on tool life, is not feasible due to the rule that prohibits changing the cutting parameters during mass production to maintain the quality standard. To address both issues, this paper proposes a hybrid monitoring and optimisation process that can be carried out concurrently without interfering with production activities. The monitoring process involves two methods, namely threshold limit-based monitoring and machine learning-based monitoring, for ensuring product quality during the optimisation process. Meanwhile, Bayesian optimisation (BO) is used for the optimisation process due to its capability for autonomous search for the optimum condition of an unknown and expensive objective function. The case study demonstrated BO’s ability to find the optimal condition with a small number of samples, while the machine learning method used can monitor tool wear and surface roughness with average errors of 5.5% and 7.7%, respectively.
Journal: International Journal of Production Research
Pages: 5392-5410
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2101403
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2101403
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# input file: TPRS_A_2102448_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jun Pei
Author-X-Name-First: Jun
Author-X-Name-Last: Pei
Author-Name: Haoxin Wang
Author-X-Name-First: Haoxin
Author-X-Name-Last: Wang
Author-Name: Min Kong
Author-X-Name-First: Min
Author-X-Name-Last: Kong
Author-Name: Nenad Mladenovic
Author-X-Name-First: Nenad
Author-X-Name-Last: Mladenovic
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Title: Bi-level scheduling in high-end equipment R&D: when more algorithm strategies may not be better
Abstract: 
 Motivated by the practical research and development (R&D) process in high-end equipment manufacturing, this study investigates a bi-level scheduling problem in a complex R&D project network, where each project contains multiple modules with a complete task network. In the bi-level scheduling problem, the upper-level problem is that the R&D project leader makes the decision on allocating all R&D project modules to limited R&D researchers and the objective is to minimise the total penalty cost of all projects, and the lower-level problem is that the researchers schedule and sort the assigned tasks to minimise their minimum makespan. The different capacity of researchers is considered, and some structural properties are derived based on the capacity analytics. To tackle this complex scheduling problem, an effective Variable Neighborhood Search algorithm based on the ‘less is more' concept is proposed, where a Multi-Greedy Heuristic is incorporated. Interestingly, we observe that simpler algorithmic strategies may lead to better algorithmic performance. Computational experiments are carried out to demonstrate that the performance of the proposed algorithm is efficient and stable.
Journal: International Journal of Production Research
Pages: 5436-5467
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2102448
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2102448
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2103472_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Wei Qin
Author-X-Name-First: Wei
Author-X-Name-Last: Qin
Author-Name: Zilong Zhuang
Author-X-Name-First: Zilong
Author-X-Name-Last: Zhuang
Author-Name: Yanning Sun
Author-X-Name-First: Yanning
Author-X-Name-Last: Sun
Author-Name: Yang Liu
Author-X-Name-First: Yang
Author-X-Name-Last: Liu
Author-Name: Miying Yang
Author-X-Name-First: Miying
Author-X-Name-Last: Yang
Title: An available-to-promise stochastic model for order promising based on dynamic resource reservation policy
Abstract: 
 Facing uncertain future customer orders, a pull-based available-to-promise (ATP) mechanism will deteriorate the overall profit since it allocates critical resources only to current customer orders. To prevent current less-profitable customer orders from over-consuming critical resources, this study investigates a push–pull based ATP problem with two time stages and three profit margin levels, and develops a dynamic resource reservation policy to maximise the expected total profit. Then, a corresponding push–pull based stochastic ATP model is established with known independent demand distributions, and the optimal reservation level is derived by the genetic algorithm to maximise the expected total profit. Finally, a series of simulation experiments are conducted to reveal the impact of some key factors, and the experiment results provide theoretical guidance and implementation methods for companies to maximise overall profits.
Journal: International Journal of Production Research
Pages: 5525-5542
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2103472
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2103472
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2102447_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Dmitry Kucharavy
Author-X-Name-First: Dmitry
Author-X-Name-Last: Kucharavy
Author-Name: David Damand
Author-X-Name-First: David
Author-X-Name-Last: Damand
Author-Name: Marc Barth
Author-X-Name-First: Marc
Author-X-Name-Last: Barth
Title: Technological forecasting using mixed methods approach
Abstract: 
 How can strategic decision-making be reinforced through reliable forecasts of technological change? Observations of strategic forecasts have shown that they mainly rely upon expert opinions. To turn these opinions into consistent knowledge about the future, we need to manage cognitive biases using provable models. Observed forecasting methods provide useful tools for exploiting expert knowledge and data, but management of cognitive bias remains underdeveloped. To improve the situation with cognitive biases in technology forecasting, the Researching Future method (RFm) offers a mixed methods approach. This article introduces RFm, a method that combines a problem-based approach and a logistic function, unified by an applied resources paradigm. A practical case study is described to illustrate and validate RFm, and the results, limitations, and perspectives of RFm are then examined. The article contributes to the technology forecasting methodology and is of interest to copper mining technology R&D specialists, among others.
Journal: International Journal of Production Research
Pages: 5411-5435
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2102447
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2102447
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2101960_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Foivos Psarommatis
Author-X-Name-First: Foivos
Author-X-Name-Last: Psarommatis
Author-Name: Gokan May
Author-X-Name-First: Gokan
Author-X-Name-Last: May
Title: A literature review and design methodology for digital twins in the era of zero defect manufacturing
Abstract: 
 In this paper, we analyze the literature concerning the implementation of digital twins (DTs) for zero-defect manufacturing (ZDM) following a systematic method and, guided by a preliminary finding that a structured and standardised approach to the development of the DT applications is lacking, we provide a standardised design methodology to guide researchers and practitioners in their efforts to develop DTs regardless of the domain. After examination and interpretation of the literature, we also present the results of our state-of-the-art analysis, discuss the current state and limitations of research and practice, and provide useful insights on this important and complex topic. The design methodology proposed in our study will benefit both practitioners and academicians by covering the essential elements to be considered when developing DTs for ZDM for any applications in this domain. The study also contributes to knowledge by presenting a structured overview of the specific research area with a comprehensive, systematic, and critical analysis of the literature and by providing answers to some fundamental questions in the context of DTs for ZDM. Finally, we provide suggestions for further developments in research and practice.
Journal: International Journal of Production Research
Pages: 5723-5743
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2101960
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2101960
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# input file: TPRS_A_2104180_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ana Esteso
Author-X-Name-First: Ana
Author-X-Name-Last: Esteso
Author-Name: David Peidro
Author-X-Name-First: David
Author-X-Name-Last: Peidro
Author-Name: Josefa Mula
Author-X-Name-First: Josefa
Author-X-Name-Last: Mula
Author-Name: Manuel Díaz-Madroñero
Author-X-Name-First: Manuel
Author-X-Name-Last: Díaz-Madroñero
Title: Reinforcement learning applied to production planning and control
Abstract: 
 The objective of this paper is to examine the use and applications of reinforcement learning (RL) techniques in the production planning and control (PPC) field addressing the following PPC areas: facility resource planning, capacity planning, purchase and supply management, production scheduling and inventory management. The main RL characteristics, such as method, context, states, actions, reward and highlights, were analysed. The considered number of agents, applications and RL software tools, specifically, programming language, platforms, application programming interfaces and RL frameworks, among others, were identified, and 181 articles were sreviewed. The results showed that RL was applied mainly to production scheduling problems, followed by purchase and supply management. The most revised RL algorithms were model-free and single-agent and were applied to simplified PPC environments. Nevertheless, their results seem to be promising compared to traditional mathematical programming and heuristics/metaheuristics solution methods, and even more so when they incorporate uncertainty or non-linear properties. Finally, RL value-based approaches are the most widely used, specifically Q-learning and its variants and for deep RL, deep Q-networks. In recent years however, the most widely used approach has been the actor-critic method, such as the advantage actor critic, proximal policy optimisation, deep deterministic policy gradient and trust region policy optimisation.
Journal: International Journal of Production Research
Pages: 5772-5789
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2104180
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2104180
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# input file: TPRS_A_2105763_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Roohollah YounesSinaki
Author-X-Name-First: Roohollah
Author-X-Name-Last: YounesSinaki
Author-Name: Azadeh Sadeghi
Author-X-Name-First: Azadeh
Author-X-Name-Last: Sadeghi
Author-Name: Hadi Mosadegh
Author-X-Name-First: Hadi
Author-X-Name-Last: Mosadegh
Author-Name: Najat Almasarwah
Author-X-Name-First: Najat
Author-X-Name-Last: Almasarwah
Author-Name: Gursel Suer
Author-X-Name-First: Gursel
Author-X-Name-Last: Suer
Title: Cellular manufacturing design 1996–2021: a review and introduction to applications of Industry 4.0
Abstract: 
 As globalisation and competition grow rapidly, adopting a flexible manufacturing philosophy becomes more critical for manufacturers. Cellular Manufacturing System (CMS) is among one of the most favourable ones which has been deeply studied in academia since this philosophy was coined in 1925. To design the manufacturing system efficiently and effectively, the management team needs to have a comprehensive representation of the definitions, classifications, solution approach to cellular manufacturing design problems. In this study, exact methods, heuristic approaches, metaheuristic techniques, and artificial intelligence strategies for cellular manufacturing design are reviewed. A comparison of solution approaches is discussed and based on this analysis, some suggestions for future research are proposed. Moreover, we tried to highlight the importance of investigating sustainability decisions related to CMS problems, and integration of supply chain decisions with CMS decisions which have not been sufficiently studied to identify a research direction for researchers to model and analyse those issues. Finally, we briefly discuss the placement of CMS as one of the major production systems in the industry 4.0 evolution paradigm. Reviewing the adoption of industry 4.0 techniques by CMS sheds light on the contribution of methodological approaches in transition to intelligent CMS.
Journal: International Journal of Production Research
Pages: 5585-5636
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2105763
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2105763
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# input file: TPRS_A_2102451_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Kunpeng Li
Author-X-Name-First: Kunpeng
Author-X-Name-Last: Li
Author-Name: Peiyang He
Author-X-Name-First: Peiyang
Author-X-Name-Last: He
Author-Name: P. N. Ram Kumar
Author-X-Name-First: P. N.
Author-X-Name-Last: Ram Kumar
Title: A column generation based approach for an integrated production and transportation scheduling problem with dual delivery modes
Abstract: 
 3D printing technology is fundamentally transforming how companies are run and managed today. This work analyzes the problem of integrated production and transportation of automotive spare parts in the context of 3D printing. We consider two sets of customers – scheduled and breakdown maintenance – serviced by the same resource but with distinct delivery modes. We propose a mixed-integer programming (MIP) formulation for optimally solving small problem instances. We develop an exact approach based on column generation (CG) for large cases by reformulating the MIP model as a set-covering problem through Dantzig-Wolfe decomposition. We design and deploy two acceleration strategies for the quicker convergence of the CG approach. Through extensive computational experiments, we establish the superiority and suitability of the proposed solution methodology for solving real-life problems at terse computational times.
Journal: International Journal of Production Research
Pages: 5483-5501
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2102451
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2102451
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# input file: TPRS_A_2101402_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jully Jeunet
Author-X-Name-First: Jully
Author-X-Name-Last: Jeunet
Author-Name: Fabio Salassa
Author-X-Name-First: Fabio
Author-X-Name-Last: Salassa
Title: The discrete time break scheduling problem under fatigue and no preemption: solution methods and impact of work regulations
Abstract: 
 We address the discrete time break scheduling problem with no preemption when workers' fatigue impacts their productivity. We propose a Mixed Integer Linear Programming model to solve the one break problem to optimality, using a lexicographic approach where the production amount is maximised first, and then the break length over a discrete time horizon. We develop a Variable Neighbourhood Search algorithm to solve the multiple break problem. In addition to proposing efficient solution methods to the problem, our incentive is to assess the impact on the production amount and on workers' welfare of rest break regulations laid down in legislation or collective agreements. We conducted an extensive simulation study to represent a wide range of workers' profiles defined in terms of fatigability and recovery speed. Simulation results show that regulations slightly affect the production amount whereas they allow for large improvements of workers' welfare as long as breaks are optimised as a second objective. The production amount is also shown to be quite sensitive to the break timing. Finally, multiple breaks can improve the production amount and workers' welfare in many situations, which questions the widespread belief that endowing workers with a single short break would optimise the production amount.
Journal: International Journal of Production Research
Pages: 5372-5391
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2101402
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2101402
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# input file: TPRS_A_2109219_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ahlam Azzamouri
Author-X-Name-First: Ahlam
Author-X-Name-Last: Azzamouri
Author-Name: Pierre Baptiste
Author-X-Name-First: Pierre
Author-X-Name-Last: Baptiste
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Author-Name: Guillaume Dessevre
Author-X-Name-First: Guillaume
Author-X-Name-Last: Dessevre
Title: Impact of the continuous and periodic assessment of a buffer replenishment on the DDMRP method
Abstract: 
 Like Kanban or classic inventory management, Demand Driven Material Requirements Planning (DDMRP) assumes that an order is created when the stock level drops below a given level. The assessment of this level can be continuous or periodic. A periodic evaluation can force better repartition of the load over time. DDMRP characterizes the demand for a product by its average daily demand. This aggregation specifies neither the average size of the elementary demands nor the average duration between two elementary demands. Based on a discrete event simulation model, this study suggests that, at least for a flow-shop organization, the DDMRP method, with continuous order generation, is suitable for large mean time between elementary orders, while periodic observation improves the method for small values of it.
Journal: International Journal of Production Research
Pages: 5637-5658
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2109219
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2109219
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2102948_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ioannis Avgerinos
Author-X-Name-First: Ioannis
Author-X-Name-Last: Avgerinos
Author-Name: Ioannis Mourtos
Author-X-Name-First: Ioannis
Author-X-Name-Last: Mourtos
Author-Name: Stavros Vatikiotis
Author-X-Name-First: Stavros
Author-X-Name-Last: Vatikiotis
Author-Name: Georgios Zois
Author-X-Name-First: Georgios
Author-X-Name-Last: Zois
Title: Scheduling unrelated machines with job splitting, setup resources and sequence dependency
Abstract: 
 We examine the parallel machine scheduling problem where a set of jobs are to be processed by a set of unrelated parallel machines. We examine the most general among the variations for which an exact method has been proposed regarding makespan minimisation. This is because, apart from unrelated machines, we allow for (i) job splitting: each job's quantity can be split and processed by multiple machines simultaneously; (ii) sequence- and machine-dependent setup times: the setup time when job j succeeds k is different than the time when k succeeds j and varies also per machine m; and (iii) setup resource constraints: the number of setups that can be performed simultaneously on different machines is restricted. We present novel lower bound formulations and a heuristic that solves instances of up to 1000 jobs in a few minutes at an average gap of less than 
 $ 20\% $ 20%. Then, we propose a logic-based Benders decomposition, which, coupled with our heuristic, solves instances of up to 200 jobs and 20 machines to near optimality in less than two hours. Our method is used for a broad range of instances from textile manufacturing, thus yielding valuable managerial insights on makespan's versatility under varying machines or resources.
Journal: International Journal of Production Research
Pages: 5502-5524
Issue: 16
Volume: 61
Year: 2023
Month: 08
X-DOI: 10.1080/00207543.2022.2102948
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2102948
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# input file: TPRS_A_2118891_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yuan Chen
Author-X-Name-First: Yuan
Author-X-Name-Last: Chen
Author-Name: Qinghua Zhu
Author-X-Name-First: Qinghua
Author-X-Name-Last: Zhu
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: Green supply chain management practice adoption sequence: a cumulative capability perspective
Abstract: 
 Corporate environmental responsibilities have expanded to include their supply chains. Green supply chain management (GSCM) practices can be extensive – including both intra- and inter-organisational environmental management practices. Selecting and sequencing GSCM practices is an important issue given resource and strategic organisational considerations. Using the cumulative capabilities theory, this study empirically explores GSCM implementation sequences, following which firms can build cumulative capabilities. Correlation, sequential test, and path analysis are used to identify GSCM practice implementation sequence from secondary data. The results show that firms should first encourage suppliers to disclose their environmental data and respond to inquiries on environmental violations by their suppliers (the order of the two is exchangeable), then encourage suppliers to comply with environmental regulations, extend practices to lower-tier suppliers, and engage in responsible recycling. This study is one of the first to apply cumulative capability theory to analyse environmental practices and provides a framework for future research on GSCM sequences. The paper also offers practical implications for firms to adjust their strategies in order to adopt GSCM more effectively and successfully.
Journal: International Journal of Production Research
Pages: 5918-5933
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2118891
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2118891
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2118387_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Quentin Christ
Author-X-Name-First: Quentin
Author-X-Name-Last: Christ
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Guillaume Lepelletier
Author-X-Name-First: Guillaume
Author-X-Name-Last: Lepelletier
Title: A three-step approach for decision support in operational production planning of complex manufacturing systems
Abstract: 
 In this paper, a practical relevant operational production planning problem in complex manufacturing systems is addressed. In this problem, lots are planned individually to provide a more detailed plan than approaches that only consider production quantities. A three-step approach, which is currently fully integrated and used in a Decision Support System, is then introduced. This work follows the one of Mhiri et al. [2018. “Heuristic Algorithm for a WIP Projection Problem at Finite Capacity in Semiconductor Manufacturing.” IEEE Transactions on Semiconductor Manufacturing 31 (1): 62–75] who addressed this problem. We push the approach a step further by introducing new optimisation possibilities through new smoothing rules, whose performance is studied according to different indicators. Furthermore, we present the production planning process in which the decision support tool is embedded and how it bridges the gap between the upper and lower planning levels.
Journal: International Journal of Production Research
Pages: 5860-5885
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2118387
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2118387
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2117869_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jongsung Lee
Author-X-Name-First: Jongsung
Author-X-Name-Last: Lee
Author-Name: Byung-In Kim
Author-X-Name-First: Byung-In
Author-X-Name-Last: Kim
Author-Name: Mihee Nam
Author-X-Name-First: Mihee
Author-X-Name-Last: Nam
Title: Novel method for welding gantry robot scheduling at shipyards
Abstract: 
 Welding is the most critical operation in the shipbuilding process and has a significant influence on the production cost and quality of ships. Therefore, the welding operation must be optimised. This paper presents a real-world welding gantry robot scheduling problem at shipyards, in which three gantry robots function in parallel. Welding gantry robots cannot cross each other and should operate over a certain distance to avoid collisions. To minimise the makespan, the welding tasks given by line segments should be evenly distributed among the three gantry robots. The welding tasks assigned to each robot should be optimally sequenced to minimise the completion time, including the waiting time required to prevent collisions with neighbouring robots. In addition, long welding edges are split, and the split small length edges are assigned to the gantry robots. This paper proposes a mixed-integer linear programming model, three-stage solution approach, and variable neighbourhood search algorithm to solve this problem. Experimental tests conducted on 20 real problem instances revealed that the proposed approach can reduce the makespan by 14% on average when compared with the conventional method.
Journal: International Journal of Production Research
Pages: 5842-5859
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2117869
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2117869
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# input file: TPRS_A_2116734_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mingdong Li
Author-X-Name-First: Mingdong
Author-X-Name-Last: Li
Author-Name: Shanhe Lou
Author-X-Name-First: Shanhe
Author-X-Name-Last: Lou
Author-Name: Yicong Gao
Author-X-Name-First: Yicong
Author-X-Name-Last: Gao
Author-Name: Hao Zheng
Author-X-Name-First: Hao
Author-X-Name-Last: Zheng
Author-Name: Bingtao Hu
Author-X-Name-First: Bingtao
Author-X-Name-Last: Hu
Author-Name: Jianrong Tan
Author-X-Name-First: Jianrong
Author-X-Name-Last: Tan
Title: A cerebellar operant conditioning-inspired constraint satisfaction approach for product design concept generation
Abstract: 
 Conceptual design is a pivotal stage of new product development. The function-behaviour-structure framework is adopted in this stage to help designers search design space and generate conceptual solutions iteratively. Computer-aided methods developed within this framework will yield significant insight into facilitating the cognitive activities of designers. In order to solve the mapping process from behaviours to structures which is a typical constraint satisfaction problem, a cerebellar operant conditioning-inspired constraint satisfaction approach is proposed in this paper. The design constraints-driven operant conditioning and its regulation mechanism by the cerebellum are analysed for the first time. Proposition logic is applied to transfer the constraint satisfaction problem into a propositional satisfiability problem while an undirected graph is utilised to model design space. Inspired by the modularised cerebellar structure, a modularised constraint satisfaction neural network is constructed to determine the satisfiability of design problems. Conceptual solutions can be generated by clustering the embedding of nodes in this network. The proposed approach imitates the design constraint-driven operant conditioning to narrow down design space without assigning specific values to design components. It reduces design iterations and avoids combinatorial explosions during conceptual design.
Journal: International Journal of Production Research
Pages: 5822-5841
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2116734
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2116734
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# input file: TPRS_A_2119294_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Zhaohui Li
Author-X-Name-First: Zhaohui
Author-X-Name-Last: Li
Author-Name: Guohua Wan
Author-X-Name-First: Guohua
Author-X-Name-Last: Wan
Title: Batching and scheduling in a continuous-discrete hybrid flowshop: Lagrangian relaxation-based heuristic algorithms
Abstract: 
 We study a two-stage hybrid flow shop problem arising from a fine chemicals production facility, where the first stage is a continuous chemical reaction process and the second stage is a discrete filling-packaging process. The objective is to minimise the total weighted completion time through batching of the jobs and scheduling of the batches at first stage and scheduling of the jobs at second stage. We formulate the problem as a mixed integer programming model and develop a Lagrangian relaxation-based framework for solving it, where the original problem is decomposed into family-level subproblems, and each subproblem is transformed into a set-partitioning problem. The subproblems are solved to optimality via branch and price algorithm. We also propose two heuristic algorithms for reducing computational efforts without much loss of solution quality. Finally, we conduct computational experiments with both randomly generated and real data sets to test the performance of the three proposed algorithms and demonstrate that the algorithms perform efficiently.
Journal: International Journal of Production Research
Pages: 5934-5955
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2119294
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2119294
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# input file: TPRS_A_2115575_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Luca Mattia Gelsomino
Author-X-Name-First: Luca Mattia
Author-X-Name-Last: Gelsomino
Author-Name: Saskia Sardesai
Author-X-Name-First: Saskia
Author-X-Name-Last: Sardesai
Author-Name: Miia Pirttilä
Author-X-Name-First: Miia
Author-X-Name-Last: Pirttilä
Author-Name: Michael Henke
Author-X-Name-First: Michael
Author-X-Name-Last: Henke
Title: Addressing the relation between transparency and supply chain finance schemes
Abstract: 
 In the wake of technological innovation, supply chain transparency has become a concrete avenue for long-awaited improvements to supply chain processes and practices. Transparency is of particular interest to Supply Chain Finance; however, it is yet empirically unknown whether and how benefits would materialise. Being at the interface of finance and operations, Supply Chain Finance aims at improving the inter-company management of financial flows. Nowadays, different financing schemes are offered foremost by cooperation between financial institutions and fintechs. Uncertainty remains on whether and how supply chain transparency would benefit these schemes to allow the adoption of more sophisticated, higher-value schemes. By applying the Gioia method, we analysed a series of interviews with experts from the Supply Chain Finance industry regarding transaction cost economics, agency theory, and dynamic capability. The resulting series of pragmatic, theory-grounded but practice-inspired propositions untangle the relationship and barriers between supply chain transparency and Supply Chain Finance. The propositions provide advances in the theoretical understanding of Supply Chain Finance and uncover relevant directions for future research. This poses the base for actionable results in future research and leads to an impact in research by addressing the concerns and tensions raised by Supply Chain Finance experts.
Journal: International Journal of Production Research
Pages: 5806-5821
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2115575
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2115575
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# input file: TPRS_A_2122620_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Andrew Kusiak
Author-X-Name-First: Andrew
Author-X-Name-Last: Kusiak
Title: Predictive models in digital manufacturing: research, applications, and future outlook
Abstract: 
 Data has become a high-value commodity in manufacturing. There is a growing realisation that the data-driven applications could become strong differentiators of manufacturing enterprises. To guide the developments in digitisation, a widely accepted framework is needed. In the absence of the universal framework, the components making a digital enterprise are captured in an example framework that is introduced in the paper. The adoption of new technology and software solutions has increased complexity of manufacturing systems. In addition, new product introductions have become more frequent and the demand more variable. A digital space enables optimisation and simulation of decisions before their realisation in the physical space. Predictive modelling with its time dimension is a valuable actor in the digital space. Three challenges of predictive modelling such as model complexity, model interpretability, and model reuse are identified in this paper. The coverage of each challenge in the literature is illustrated with the recently published papers. The main aspects of these challenges and the synthesis of the developments in digital manufacturing are articulated in the form of eight observations that could guide the future research.
Journal: International Journal of Production Research
Pages: 6052-6062
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2122620
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2122620
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# input file: TPRS_A_2118888_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Thiago Cantos Lopes
Author-X-Name-First: Thiago Cantos
Author-X-Name-Last: Lopes
Author-Name: Adalberto Sato Michels
Author-X-Name-First: Adalberto Sato
Author-X-Name-Last: Michels
Author-Name: Nadia Brauner
Author-X-Name-First: Nadia
Author-X-Name-Last: Brauner
Author-Name: Leandro Magatão
Author-X-Name-First: Leandro
Author-X-Name-Last: Magatão
Title: Balancing-sequencing paced assembly lines: a multi-objective mixed-integer linear case study
Abstract: 
 This paper considers the optimisation of Mixed-model assembly lines with continuous paced line control. The two minimisation goals have a mixed-integer linear multi-objective dispute. The paper proposes a criterion-space method to define the Pareto front for this class of problems. The method combines Pareto fronts obtained from integer solutions and gradually refines them until the instance's global front is determined. Comparing paced to unpaced line controls can be challenging, since they can produce the same cycle time given sufficiently long line lengths or buffers. Hence, determining Pareto fronts between cycle time and line length for paced lines allows meaningful comparisons between line controls. An industrial case study shows that line length acts as continuously distributable buffers for paced lines, leading to weaker diminishing returns. This result suggests that paced lines are more efficient than unpaced ones for lower cycle time ranges.
Journal: International Journal of Production Research
Pages: 5901-5917
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2118888
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2118888
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# input file: TPRS_A_2120923_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Marie-Christin Schmidt
Author-X-Name-First: Marie-Christin
Author-X-Name-Last: Schmidt
Author-Name: Johannes W. Veile
Author-X-Name-First: Johannes W.
Author-X-Name-Last: Veile
Author-Name: Julian M. Müller
Author-X-Name-First: Julian M.
Author-X-Name-Last: Müller
Author-Name: Kai-Ingo Voigt
Author-X-Name-First: Kai-Ingo
Author-X-Name-Last: Voigt
Title: Industry 4.0 implementation in the supply chain: a review on the evolution of buyer-supplier relationships
Abstract: 
 This paper analyses extant literature on how Industry 4.0 impacts Social Capital in Buyer-Supplier Relationships. We conduct a systematic literature review and identify 36 academic articles that are analysed in the research process. The study uncovers strategic changes Industry 4.0 implies for Social Capital in Buyer-Supplier Relationships. These include transformations in cognitive, structural and relational capital in terms of a shared vision, social interaction and trust. Therein, Social Capital in Buyer-Supplier Relationships is needed and further invested in aspects like common decision-making, information sharing and cross-company integration in Industry 4.0 contexts. We propose that Industry 4.0 implementation does require and foster Social Capital in Buyer-Supplier Relationships and that two diametrically opposed elementary forms of Buyer-Supplier Relationships co-exist in an Industry 4.0 context. The systematic literature review is the first to analyse the extant body of literature on Buyer-Supplier Relationships in Industry 4.0 to synthesise detailed transformations against the backdrop of Social Capital. It provides a comprehensive overview of the current state of research and develops several suggestions for future research and managerial practice, for example, concerning the role of humans in strategic tasks in Industry 4.0.
Journal: International Journal of Production Research
Pages: 6063-6080
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2120923
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2120923
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# input file: TPRS_A_2122619_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lei Liu
Author-X-Name-First: Lei
Author-X-Name-Last: Liu
Author-Name: Ting Qu
Author-X-Name-First: Ting
Author-X-Name-Last: Qu
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Lin Ma
Author-X-Name-First: Lin
Author-X-Name-Last: Ma
Author-Name: Zhongfei Zhang
Author-X-Name-First: Zhongfei
Author-X-Name-Last: Zhang
Author-Name: Mingze Yuan
Author-X-Name-First: Mingze
Author-X-Name-Last: Yuan
Title: A new knowledge-guided multi-objective optimisation for the multi-AGV dispatching problem in dynamic production environments
Abstract: 
 The efficiency of material supply for workstations using Automatic Guided Vehicles (AGVs) is largely determined by the performance of the AGV dispatching scheme. This paper proposes a new solution approach for the AGV dispatching problem (AGVDP) for material replenishment in a general manufacturing workshop where workstations are in a matrix layout, and where uncertainty in replenishment time of workstations and stochastic unloading efficiencies of AGVs are dynamic contextual factors. We first extend the literature proposing a mixed integer optimisation model with a delivery satisfaction soft constraint of material orders and two objectives: transportation costs and delivery time deviation. We then develop a new knowledge-guided estimation of distribution algorithm with delivery satisfaction evaluation for solving the model. Our algorithm fuses three knowledge-guided strategies to enhance optimisation capabilities at its respective execution stages. Comprehensive numerical experiments with instances built from a real-world scenario validate the proposed model and algorithm. Results demonstrate that the new algorithm outperforms three popular multi-objective evolutionary algorithms, a discrete version of a recent multi-objective particle swarm optimisation, and a multi-objective estimation of distribution algorithm. Findings of this work provide major implications for workshop management and algorithm design.
Journal: International Journal of Production Research
Pages: 6030-6051
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2122619
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2122619
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# input file: TPRS_A_2120924_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Franco Quezada
Author-X-Name-First: Franco
Author-X-Name-Last: Quezada
Author-Name: Céline Gicquel
Author-X-Name-First: Céline
Author-X-Name-Last: Gicquel
Author-Name: Safia Kedad-Sidhoum
Author-X-Name-First: Safia
Author-X-Name-Last: Kedad-Sidhoum
Title: A stochastic dual dynamic integer programming based approach for remanufacturing planning under uncertainty
Abstract: 
 We seek to optimize the production planning of a three-echelon remanufacturing system under uncertain input data. We consider a multi-stage stochastic integer programming approach and use scenario trees to represent the uncertain information structure. We introduce a new dynamic programming formulation that relies on a partial nested decomposition of the scenario tree. We then propose a new approximate stochastic dual dynamic integer programming algorithm based on this partial decomposition. Our numerical results show that the proposed solution approach is able to provide near-optimal solutions for large-size instances with a reasonable computational effort.
Journal: International Journal of Production Research
Pages: 5992-6012
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2120924
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2120924
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# input file: TPRS_A_2118887_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yusheng Wang
Author-X-Name-First: Yusheng
Author-X-Name-Last: Wang
Author-Name: Ada Che
Author-X-Name-First: Ada
Author-X-Name-Last: Che
Author-Name: Jianguang Feng
Author-X-Name-First: Jianguang
Author-X-Name-Last: Feng
Title: Energy-efficient unrelated parallel machine scheduling with general position-based deterioration
Abstract: 
 This paper investigates an energy-efficient scheduling problem on unrelated parallel machines considering general position-based deterioration which arises from the labour-intensive textile industry. The actual processing time of a job is not only associated with the job and the machine but also with its position in the processing sequence. The objective is to minimise the total energy consumption with a bounded makespan. To address this problem, we first establish a mixed-integer linear programming (MILP) model. Afterwards, the initial model is improved by deriving lower and upper bounds on the makespan, and an upper bound on the number of jobs processed on each machine. We also develop an iterative heuristic embedded with a variable neighbourhood search procedure (IHVNS). The algorithm obtains initial solutions iteratively by solving assignment problems and then repairs and improves them with the VNS procedure. Computational results demonstrate that the improved model is up to 230 times faster than the original one. Moreover, the proposed heuristic yields excellent solutions with average gaps of less than 0.73% for large-scale instances. Especially, the results reveal that the IHVNS algorithm is more suitable than MILP models for solving large-scale problems with tight makespan restrictions.
Journal: International Journal of Production Research
Pages: 5886-5900
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2118887
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2118887
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# input file: TPRS_A_2120922_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Qiang Zhang
Author-X-Name-First: Qiang
Author-X-Name-Last: Zhang
Author-Name: Ping Liu
Author-X-Name-First: Ping
Author-X-Name-Last: Liu
Author-Name: Yu Chen
Author-X-Name-First: Yu
Author-X-Name-Last: Chen
Author-Name: Quan Deng
Author-X-Name-First: Quan
Author-X-Name-Last: Deng
Author-Name: Jürgen Pannek
Author-X-Name-First: Jürgen
Author-X-Name-Last: Pannek
Title: An improved event-triggered predictive control for capacity adjustment in reconfigurable job-shops
Abstract: 
 In order to regulate work in process (WIP) to the desired value in the job shop production control system, capacity adjustment as an effective and efficient measure, which is typically achieved by flexible staffs and working time. In this paper, instead of traditional labour-oriented approaches, we consider a machinery-based capacity adjustment via reconfigurable machine tools (RMTs) to compensate for unpredictable events. To this end, we employ model predictive control (MPC) in combination with genetic algorithm (GA) to explicitly consider complex reconfiguration strategies and address the related integer assignment optimisation problems. To further reduce energy consumption and avoid frequent and unnecessary reconfigurations while keeping a certain level of performance, we adopt an event-triggered MPC scheme with the proposed ‘Double-layer event-triggering conditions’. Through extensively illustrated simulations, we demonstrate the effectiveness and plug-and-play availability of the proposed method for a six-workstation four-product job shop system and compare it to a state-of-the-art method.
Journal: International Journal of Production Research
Pages: 5974-5991
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2120922
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2120922
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# input file: TPRS_A_2121869_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Axel Lopez-Esteve
Author-X-Name-First: Axel
Author-X-Name-Last: Lopez-Esteve
Author-Name: Federico Perea
Author-X-Name-First: Federico
Author-X-Name-Last: Perea
Author-Name: Juan C. Yepes-Borrero
Author-X-Name-First: Juan C.
Author-X-Name-Last: Yepes-Borrero
Title: GRASP algorithms for the unrelated parallel machines scheduling problem with additional resources during processing and setups
Abstract: 
 This paper addresses an unrelated parallel machines scheduling problem with the need of additional resources during the processing of the jobs, as well as during the setups that machines need between the processing of any two jobs. This problem is highly complex, and therefore in this paper we propose several constructive heuristics to solve it. To improve the performance of these heuristics, we propose several variations, including randomisation with different probability distributions and a local search phase, having this way GRASP algorithms. The results of extensive experiments over randomly generated instances show several findings on the different parameters that characterise our constructive algorithms. In particular, we highlight the fact that non-uniform probability distributions might be advisable for choosing elements of a restricted candidate list in GRASP algorithms.
Journal: International Journal of Production Research
Pages: 6013-6029
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2121869
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2121869
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# input file: TPRS_A_2112989_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xin Wen
Author-X-Name-First: Xin
Author-X-Name-Last: Wen
Author-Name: Yige Sun
Author-X-Name-First: Yige
Author-X-Name-Last: Sun
Author-Name: Hoi-Lam Ma
Author-X-Name-First: Hoi-Lam
Author-X-Name-Last: Ma
Author-Name: Sai-Ho Chung
Author-X-Name-First: Sai-Ho
Author-X-Name-Last: Chung
Title: Green smart manufacturing: energy-efficient robotic job shop scheduling models
Abstract: 
 Smart manufacturing has boosted the wide application of mobile robots in robotic cells for automated material delivery. However, the mismatching between machine production process and robot movement process causes extensive energy waste. Nevertheless, most existing robotic job-shop scheduling (RJSP) studies mainly focus on minimising makespan but overlook the low energy efficiency problem faced by robotic cells. Motivated by the importance of green smart manufacturing, in this study, we innovatively propose to achieve robotic cell energy saving through coordinating the machine production process and robot movement process. Specifically, both machines and the mobile robot can flexibly adjust operating speeds with a V-scale speed framework. Two novel energy-efficient RJSP approaches (i.e. the RJSP-E and the RJSP-EM) are thus proposed. The RJSP-E focuses on minimising energy consumption, while the RJSP-EM simultaneously considers makespan (i.e. productivity) and energy consumption. Through computational experiments, the RJSP-E demonstrates superior performances in reducing energy consumption (15% on average), at a loss of productivity (20% on average). On the other hand, the RJSP-EM can select the most suitable energy-saving operating speeds without much sacrifice in productivity. Notably, the RJSP-EM can reduce energy consumption by a mean of 10% even without increasing makespan. The RJSP-EM also demonstrates higher solution efficiency.
Journal: International Journal of Production Research
Pages: 5791-5805
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2112989
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2112989
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# input file: TPRS_A_2120107_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Fatemeh Safaei
Author-X-Name-First: Fatemeh
Author-X-Name-Last: Safaei
Author-Name: Jafar Ahmadi
Author-X-Name-First: Jafar
Author-X-Name-Last: Ahmadi
Author-Name: Mitra Fouladirad
Author-X-Name-First: Mitra
Author-X-Name-Last: Fouladirad
Title: Optimal N-policy for the maintenance of k-out-of-n systems with dynamic minor repairs considering second-hand component income
Abstract: 
 This paper proposes a maintenance policy for a k-out-of-n: F system operating to fulfil several jobs without interruptions. The system is replaced when the Nth job completes or at the kth failure, whichever occurs first. So, there are some non-failed components when a replacement is done. These components can be sold as second-hand products to continue working in other systems for a while. The price of them is also considered in the proposed maintenance policy. An optimal maintenance policy is studied to minimise long-run average cost under the constraint of relative mean operating time. Comprehensive numerical studies are done to assess the effect of the model parameters on the optimal solutions. Also, to demonstrate the applicability of the proposed plan, a data set related to wind turbine generator failures is considered as a case study.
Journal: International Journal of Production Research
Pages: 5956-5973
Issue: 17
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2120107
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2120107
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# input file: TPRS_A_2023833_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Tongshui Xia
Author-X-Name-First: Tongshui
Author-X-Name-Last: Xia
Author-Name: Yuyan Wang
Author-X-Name-First: Yuyan
Author-X-Name-Last: Wang
Author-Name: Lingxue Lv
Author-X-Name-First: Lingxue
Author-X-Name-Last: Lv
Author-Name: Liang Shen
Author-X-Name-First: Liang
Author-X-Name-Last: Shen
Author-Name: T.C.E. Cheng
Author-X-Name-First: T.C.E.
Author-X-Name-Last: Cheng
Title: Financing decisions of low-carbon supply Chain under Chain-to-Chain competition
Abstract: 
 Fierce market competition and consumers’ environmental awareness prompt manufacturers to gain competitive advantages through low-carbon production. However, many firms stay away from low carbon because of financial constraints. Considering chain-to-chain competition, this paper constructs three financing strategic models. The impacts of market competition intensity and consumers’ low-carbon preference on equilibrium decisions and corporate profits are analyzed. Then, comparative analysis is conducted to find the optimal financing strategy. Finally, numerical simulation is used for further analysis and robustness tests. It is indicated that under chain-to-chain competition, low-carbon production cannot improve the negative impact of increased competition intensity on corporate profits. Intense competition weakens the manufacturer’s emission reduction efforts. Moreover, the manufacturer does not always benefit more from internal financing though the low-carbon level is high. When the probability of obtaining a bank loan exceeds the threshold, bank financing is superior to internal financing. An increased low-carbon investment cost coefficient will lower the threshold, which is counterintuitive. Since the preference interval for the downstream retailer to provide prepayments is larger than the interval for the low-carbon manufacturer to choose internal financing, both parties have the incentive to negotiate prepayments. Under internal financing, the wholesale price discount does not affect corporate profits.
Journal: International Journal of Production Research
Pages: 6153-6176
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2021.2023833
File-URL: http://hdl.handle.net/10.1080/00207543.2021.2023833
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# input file: TPRS_A_2232652_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: S. C. Lenny Koh
Author-X-Name-First: S. C. Lenny
Author-X-Name-Last: Koh
Author-Name: Fu (Jeff) Jia
Author-X-Name-First: Fu (Jeff)
Author-X-Name-Last: Jia
Author-Name: Yu (Jack) Gong
Author-X-Name-First: Yu (Jack)
Author-X-Name-Last: Gong
Author-Name: Xiaoxue Zheng
Author-X-Name-First: Xiaoxue
Author-X-Name-Last: Zheng
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Achieving carbon neutrality via supply chain management: position paper and editorial for IJPR special issue
Abstract: 
 This special issue of the International Journal of Production Research, focuses on the ‘Carbon Neutrality’ and ‘SCM’. Nine articles have been selected for this special issue, and they cover various aspects to understand the manifestation of ‘Carbon Neutrality’ in supply chains, and to further illuminate how to achieve ‘Carbon Neutrality’ with supply chain innovation. This editorial provides a brief overview of the research domain, then introduces each article in the context of the state-of-the-art and highlights the contributions of selected papers to the field. Finally, the research perspectives are discussed.
Journal: International Journal of Production Research
Pages: 6081-6092
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2023.2232652
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2232652
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# input file: TPRS_A_2058434_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Chong Huang
Author-X-Name-First: Chong
Author-X-Name-Last: Huang
Author-Name: Shaofu Du
Author-X-Name-First: Shaofu
Author-X-Name-Last: Du
Author-Name: Bill Wang
Author-X-Name-First: Bill
Author-X-Name-Last: Wang
Author-Name: Wenzhi Tang
Author-X-Name-First: Wenzhi
Author-X-Name-Last: Tang
Title: Accelerate or hinder it? Manufacturer transformation under competition and carbon emission trading
Abstract: 
 Strengthening carbon regulations and competitive pressures are forcing supply chains to provide environmental (e-) products to replace traditional (t-) products. However, cap-and-trade policy allows manufacturers, the main carbon emission emitters, to trade their emission permits freely. Considering manufacturers' power and key role in producing and carbon trading, we develop a duopoly model consisting of two competing manufacturers. Despite asymmetrical carbon emission reduction efficiencies, the two manufacturers can independently and simultaneously decide their respective t-/e-products outputs, emission reduction levels, and permits trade quotas. The unique Nash equilibrium is derived with the overall cap. We find that the low-cost manufacturer uses its cost advantage to invest more in emission reduction, then sells the excess emission permits to its rival, but makes its rival more competitive in product market. Interestingly, our results show that cap-and-trade policy triggers an industry collusion in which manufacturers reduce competition and improve the power and profits by reducing overall output and adopting differentiated product strategy. Furthermore, the cost advantage and high product substitution can accelerate low-cost manufacturer's transformation but hinder high-cost manufacturers. The impacts of cap-and-trade policy on consumer surplus and social welfare are also discussed to provide guidance for policy makers.
Journal: International Journal of Production Research
Pages: 6230-6250
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2058434
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2058434
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# input file: TPRS_A_2104182_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mustafa Ali
Author-X-Name-First: Mustafa
Author-X-Name-Last: Ali
Author-Name: S. C. Lenny Koh
Author-X-Name-First: S. C. Lenny
Author-X-Name-Last: Koh
Author-Name: Lingxuan Liu
Author-X-Name-First: Lingxuan
Author-X-Name-Last: Liu
Author-Name: Jing Zhang
Author-X-Name-First: Jing
Author-X-Name-Last: Zhang
Author-Name: William Roberts
Author-X-Name-First: William
Author-X-Name-Last: Roberts
Author-Name: Dawn Robins
Author-X-Name-First: Dawn
Author-X-Name-Last: Robins
Author-Name: Dave Cooper
Author-X-Name-First: Dave
Author-X-Name-Last: Cooper
Title: Assessing pre-pandemic carbon footprint of diet transitions in UK nations and regions
Abstract: 
 Food supply chains hold significant embodied carbon emissions that need to be mitigated and neutralized. This study aimed to explore the historical Greenhouse Gas (GHG) emissions associated with household food consumption at a local scale i.e. across the eight English regions and the four nations that comprise the United Kingdom (UK). UK EatWell guidelines were used to explore the potential change in emissions and food costs in a scenario of transitions to healthier diets across the study areas. These emissions were calculated based on food consumption data before the advent of the Covid-pandemic i.e. between the years 2001 and 2018. Spatial data analysis was used to explore if the study areas had any significant correlations with respect to the emissions during the study period. The results displayed a potential reduction in GHG emissions for all study areas in the explored scenario. Further impacts include a reduction in household food costs across a majority of the areas during the study period. However, a consistent trend of significant correlations among the study areas was absent. This study concludes that local or regional policymaking should take precedence over national regulations to achieve healthier diets that are both carbon-neutral and affordable for the households.
Journal: International Journal of Production Research
Pages: 6115-6130
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2104182
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2104182
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# input file: TPRS_A_2153940_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Siyue Zhang
Author-X-Name-First: Siyue
Author-X-Name-Last: Zhang
Author-Name: Zhenghan Zhou
Author-X-Name-First: Zhenghan
Author-X-Name-Last: Zhou
Author-Name: Rui Luo
Author-X-Name-First: Rui
Author-X-Name-Last: Luo
Author-Name: Runze Zhao
Author-X-Name-First: Runze
Author-X-Name-Last: Zhao
Author-Name: Yiyong Xiao
Author-X-Name-First: Yiyong
Author-X-Name-Last: Xiao
Author-Name: Yuchun Xu
Author-X-Name-First: Yuchun
Author-X-Name-Last: Xu
Title: A low-carbon, fixed-tour scheduling problem with time windows in a time-dependent traffic environment
Abstract: 
 Traffic congestion is a major concern in urban transportation in supply chain management. Road-based logistic companies can mitigate their Carbon dioxide (CO2) emissions effectively by optimising their operation. In this study, we observed a low-carbon, fixed-tour scheduling problem with time windows (LC-FTSP-TW) that is designed to consider the factors that can minimise the greenhouse-gas emissions of logistics systems. Through better planning of the delivery times, we delineated a system to control the schedules of two vehicle types: fossil-fuel-powered and electric-powered vehicles. We formulated the LC-FTSP-TW as a mixed-integer linear programming model that can take into consideration time-varying traffic conditions, customer time windows, and vehicle energy-consumption functions. The proposed model was observed to be convenient for practical use, as it could be solved directly using commercial optimisation toolboxes, such as CPLEX and Gurobi, with continuous optimal results. In addition, we developed an efficient dynamic programming algorithm for solving large-sized problems with discrete optimal results. Computational experiments were conducted on a group of test instances to verify the proposed model and algorithm, which demonstrated considerable reductions in CO2 emissions compared to non-optimised solutions for both the tested fossil-fuel-powered and electric-powered vehicles.
Journal: International Journal of Production Research
Pages: 6177-6196
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2153940
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2153940
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# input file: TPRS_A_2063087_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Shigui Ma
Author-X-Name-First: Shigui
Author-X-Name-Last: Ma
Author-Name: Yong He
Author-X-Name-First: Yong
Author-X-Name-Last: He
Author-Name: Ran Gu
Author-X-Name-First: Ran
Author-X-Name-Last: Gu
Title: Low-carbon tourism supply chain network optimisation with vertical and horizontal cooperations
Abstract: 
 We consider a low-carbon tourism supply chain (LTSC) network composed of two low-carbon scenic spots (LSSs) and two travel agencies (TAs). The LSSs as leaders and the TAs as followers play Stackelberg games in the vertical direction. Meanwhile, the competing LSSs play Nash game to determine emission reduction efforts and ticket prices, and the competing TAs play Nash game to conduct retail prices. We establish four kinds of differential game models with different LTSC network structures, derive the equilibrium decision-makings of the LSSs and TAs, and explore the influences of competition or cooperation at vertical and horizontal level of the LTSC network members on the equilibrium solutions of the LSSs and TAs, low-carbon level of tourism products and performance of the LTSC network. Then, we find that the low-carbon preference of tourists improves the low-carbon level of tourism products, while the competition intensity between the LSSs leads to the decrease of the low-carbon level of tourism products. In addition, the results indicate that horizontal or vertical cooperations among the LTSC network members are not always conducive to the performance of the whole LTSC network. Only when the sensitivity of tourist demand to retail price meets certain conditions, these cooperations can develop tourism products with higher low-carbon level and bring higher revenues.
Journal: International Journal of Production Research
Pages: 6251-6270
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2063087
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2063087
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# input file: TPRS_A_2030067_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Na He
Author-X-Name-First: Na
Author-X-Name-Last: He
Author-Name: Zhong-Zhong Jiang
Author-X-Name-First: Zhong-Zhong
Author-X-Name-Last: Jiang
Author-Name: Song Huang
Author-X-Name-First: Song
Author-X-Name-Last: Huang
Author-Name: Kunyang Li
Author-X-Name-First: Kunyang
Author-X-Name-Last: Li
Title: Evolutionary game analysis for government regulations in a straw-based bioenergy supply chain
Abstract: 
 Many countries are devoting considerable efforts to replace fossil energy with renewable energy to achieve ‘Carbon Neutrality’. Straw-based bioenergy is considered as a potential substitute of fossil energy. This paper investigates the government regulations (i.e. penalty and subsidy policy) for a straw-based bioenergy supply chain consisting of power plants and farmers, in which the three parties are of bounded rationality. We develop a three-party evolutionary game model and obtain the evolutionary stable strategies of the three parties. We establish the dynamic penalty model and show that the dynamic penalty policy can encourage power plants to use bioenergy and farmers to collect bioenergy than the existing static penalty policy. Our results further demonstrate if the proportion of the farmers choosing the ‘Collecting bioenergy’ strategy is low, the government should choose the ‘Penalizing the farmer’ strategy; otherwise, the government should choose the ‘Penalizing the power plant’ strategy. We also extend our model to the government's subsidy policy and compare it with the penalty policy. Specially, when the proportion of the power plants (farmers) using (collecting) bioenergy is high, if the government's subsidies are lower than penalties, the government should choose the subsidy policy; otherwise, the government should choose the penalty policy.
Journal: International Journal of Production Research
Pages: 6093-6114
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2030067
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2030067
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# input file: TPRS_A_2063088_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Junbin Wang
Author-X-Name-First: Junbin
Author-X-Name-Last: Wang
Author-Name: Changping Zhao
Author-X-Name-First: Changping
Author-X-Name-Last: Zhao
Title: Reducing carbon footprint in a resilient supply chain: examining the critical influencing factors of process integration
Abstract: 
 Carbon neutrality and resilience are two of important goals pursued by supply chains today. This study seeks to determine how carbon footprint reduction (CFR) can be achieved in a resilient supply chain from a process integration perspective. Based on contingency theory, we employed the decision-making trial and evaluation laboratory (DEMATEL) approach to examine the critical influencing factors of process integration using evaluations from academic and professional experts. Our findings reveal that, first, at the strategic level, supply chain collaboration (SCC) and supply chain agility and responsiveness (SCAR) have the highest contributions to process integration. Second, process and control risks have the highest contributions in supply chain risk management; herein, collaborative planning, forecasting, and replenishment (CPFR) holds the highest contribution in the SCC, visibility and velocity have the highest contributions in the SCAR, and supply chain efficiency holds the highest contribution in supply chain flexibility (SCF). Finally, CPFR has a significant influence on both supplier and customer engagement, with supply chain intelligence influencing customer engagement in the SCC. Both the standardisation and parallel processes influence supplier spending in the SCF. These findings provide a new conceptual framework for empirical research and an action plan for supply chains to pursue carbon neutrality.
Journal: International Journal of Production Research
Pages: 6197-6214
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2063088
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2063088
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# input file: TPRS_A_2088426_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hongyan Sheng
Author-X-Name-First: Hongyan
Author-X-Name-Last: Sheng
Author-Name: Taiwen Feng
Author-X-Name-First: Taiwen
Author-X-Name-Last: Feng
Author-Name: Ling Liu
Author-X-Name-First: Ling
Author-X-Name-Last: Liu
Title: The influence of digital transformation on low-carbon operations management practices and performance: does CEO ambivalence matter?
Abstract: 
 Although digital transformation has aroused the interest of scholars and practitioners, how to reach a win-win situation between economic and carbon performance in the context of carbon neutrality has not been well addressed. Based on organizational information processing theory, this study investigates how digital transformation affects economic and carbon performance via low-carbon operations management practices (LOMP) and the moderating role of CEO ambivalence. We test research hypotheses using hierarchical regression analysis by collecting data from 297 Chinese manufacturing firms. Our results reveal that all three dimensions of LOMP mediate the impact of digital transformation on carbon performance, and low-carbon products mediate the impact of digital transformation on economic performance. In addition, CEO ambivalence weakens the impacts of digital transformation on three dimensions of LOMP. The findings extend the digital transformation and LOMP literature and provide theoretical guidance for managers to achieve the goals of economic development and carbon reduction.
Journal: International Journal of Production Research
Pages: 6215-6229
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2088426
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2088426
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# input file: TPRS_A_2088427_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yudan Kong
Author-X-Name-First: Yudan
Author-X-Name-Last: Kong
Author-Name: Jiaguo Liu
Author-X-Name-First: Jiaguo
Author-X-Name-Last: Liu
Author-Name: Jihong Chen
Author-X-Name-First: Jihong
Author-X-Name-Last: Chen
Title: Exploring the carbon abatement measures in maritime supply chain: a scenario-based system dynamics approach
Abstract: 
 The rapid growth of the global economy has boosted the shipping industry, but it has also increased energy consumption and exhaust emissions. Based on the system dynamics method, we construct a carbon abatement model of maritime supply chain, in which the interaction among company, economy, energy, environment, and policy is deeply analysed. The effect of various carbon abatement measures is simulated with a case study of Shanghai Port. The results prove that the shore power has tremendous potential for reducing emissions. Interestingly, the emission trading scheme has little effect on emission reduction. Conversely, it will increase CO2 emissions because of the vicious circle of higher CO2 production and decreased CO2 treatment capability. Case 4 is the best alternative for reducing CO2 emissions in maritime supply chain when combined measures are applied, regardless of the emission reduction effect or carbon emission intensity. Thus, it is most effective to mobilise all kinds of resources to reduce CO2 emissions when conditions permit.
Journal: International Journal of Production Research
Pages: 6131-6152
Issue: 18
Volume: 61
Year: 2023
Month: 09
X-DOI: 10.1080/00207543.2022.2088427
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2088427
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# input file: TPRS_A_2128922_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lauren Van De Ginste
Author-X-Name-First: Lauren
Author-X-Name-Last: Van De Ginste
Author-Name: Alexander De Cock
Author-X-Name-First: Alexander
Author-X-Name-Last: De Cock
Author-Name: Axl Van Alboom
Author-X-Name-First: Axl
Author-X-Name-Last: Van Alboom
Author-Name: Stijn Huysentruyt
Author-X-Name-First: Stijn
Author-X-Name-Last: Huysentruyt
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Author-Name: Johannes Cottyn
Author-X-Name-First: Johannes
Author-X-Name-Last: Cottyn
Title: A formal skill model to enable reconfigurable assembly systems
Abstract: 
 As assembly systems move into the era of mass customisation, the complexity of design processes, (re)configurations and operations rises. Well-structured data are key in keeping this complexity manageable. Here to, this paper presents a multidimensional formal skill model designed to deliver generic descriptions of needs and capacities with skills as the connector between products, processes and resources. The model formalises resource structures in relation to the processes they master and products they can produce. This paper discusses the case-based evaluation in a reconfigurable assembly system and highlights the added-value of a skill-based modelling approach. The presented formal model combines concepts coming from both offline and online modelling perspectives and allows for various applications and levels of detail. The resource structures embedded in the prerequisites of a skill enable matchmaking of resources for workspace design and reconfigurations. The mapping of the model to standardised ISA-95 models couples production needs to the resources allowing for more optimal production planning, control and a structured interface between enterprise and control systems. The possibility to couple states to the assembly environment allows for optimal runtime orchestration.
Journal: International Journal of Production Research
Pages: 6451-6466
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2128922
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2128922
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# input file: TPRS_A_2131925_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Soumyatanu Mukherjee
Author-X-Name-First: Soumyatanu
Author-X-Name-Last: Mukherjee
Author-Name: Sidhartha S. Padhi
Author-X-Name-First: Sidhartha S.
Author-X-Name-Last: Padhi
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Title: Designing socially optimal rates of tax and rebate structures in directing migration of risk-averse suppliers towards sustainable products
Abstract: 
 This study offers design of the ‘socially optimal’ rebate and tax structures, corresponding to the maximum expected gain and minimum risk from migration of prospective risk-averse suppliers towards supplying sustainable products. Risk-averse behaviour is caused by small and medium-sized suppliers who are financially constrained from the perspective of a textile company. This study addresses the unexplored but serious issue of suppliers’ willingness-to-pay for renouncing the option of migrating towards sustainable practices under uncertain market conditions for sustainable products, by using a mean-variance utility framework. The analytical model is validated using case-based real data collected from an Indian retailer who works with two types of suppliers in India: one natural fibre supplier and another chemical-based synthetic fibre supplier. Our model helps explain the effects of loss in expected market share and sudden increase in variability in market share for sustainable products respectively on the ‘socially optimal’ rate of tax and rebate. Also, we establish that with rate of tax increases, the ‘socially optimal’ rate of rebate on sustainable product must increase at an increasing rate to induce potential migration of suppliers towards sustainable practices. The implications of our findings on academics and practice are offered.
Journal: International Journal of Production Research
Pages: 6485-6500
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2131925
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2131925
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# input file: TPRS_A_2135629_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jiaxin Fan
Author-X-Name-First: Jiaxin
Author-X-Name-Last: Fan
Author-Name: Chunjiang Zhang
Author-X-Name-First: Chunjiang
Author-X-Name-Last: Zhang
Author-Name: Weiming Shen
Author-X-Name-First: Weiming
Author-X-Name-Last: Shen
Author-Name: Liang Gao
Author-X-Name-First: Liang
Author-X-Name-Last: Gao
Title: A matheuristic for flexible job shop scheduling problem with lot-streaming and machine reconfigurations
Abstract: 
 Multi-variety and small-batch production mode enables manufacturing industries to expeditiously satisfy customers' personalised demands, where a large amount of identical jobs can be split into several sublots, and be processed by reconfigurable machines with multiple machining technics. However, such highly flexible manufacturing environments bring some intractable problems to the production scheduling. Mathematical programming and meta-heuristic methods become less efficient when a scheduling problem contains both discrete and continuous optimisation attributes. Therefore, matheuristic, which combines advantages of the two methodologies, is regarded as a promising solution. This paper investigates a flexible job shop scheduling problem with lot-streaming and machine reconfigurations (FJSP-LSMR) for the total weighted tardiness minimisation. First, a monolithic mixed integer linear programming (MILP) model is established for the FJSP-LSMR. Afterwards, a matheuristic method with a variable neighbourhood search component (MH-VNS) is developed to address the problem. The MH-VNS adopts the classical genetic algorithm (GA) as the framework, and introduces two MILP-based lot-streaming optimisation strategies, LSO1 and LSO2, to improve lot-sizing plans with varying degrees. Four groups of instances are extended from the well-known Fdata benchmark to evaluate the performance of proposed MILP model, LSO1 and LSO2 components, and MH-VNS. Numerical experimental results suggest that LSO1 and LSO2 are efficient in different scenarios, and the proposed MH-VNS can well balance the solution quality and computational costs for reasonably integrating the GA- and MILP-based local search strategies. In addition, a complicated FJSP-LSMR case is abstracted from a real-world shop floor for processing large-sized structural parts to further validate the MH-VNS.
Journal: International Journal of Production Research
Pages: 6565-6588
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2135629
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Handle: RePEc:taf:tprsxx:v:61:y:2023:i:19:p:6565-6588



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# input file: TPRS_A_2224903_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Esra Koca
Author-X-Name-First: Esra
Author-X-Name-Last: Koca
Author-Name: G. Irmak Koksalan
Author-X-Name-First: G. Irmak
Author-X-Name-Last: Koksalan
Title: Capacitated lot sizing problem with periodic carbon emission constraints and multiple resources
Abstract: 
 We study the single item capacitated lot sizing problem with multiple resources and periodic carbon emission constraints that impose an upper bound for the average emission per product produced in any period. Although the uncapacitated version of this problem can be solved in polynomial time, generalisation of the problem including the resource capacities is NP-Hard, in general. We present important structural properties for the optimal solutions of the problem. We consider the special cases with two resources and under non-speculative costs, construct the piecewise linear total production cost function when the resource capacities, and the emission and cost parameters are time-invariant, and develop a polynomial time dynamic programming algorithm (DP) to solve them. Then, we generalise the procedure to construct the total production cost function and the DP for the general setting with fixed number of capacitated resources. We test our algorithm for different problem instances, and compare it with a commercial solver and a DP available in the literature for solving the lot sizing problem with piecewise concave production cost functions. The results reveal that our DP outperforms the other one, and it performs better than the commercial solver when the number of breakpoints of the total production cost function is small.
Journal: International Journal of Production Research
Pages: 6589-6601
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2023.2224903
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2224903
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2132313_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Puwadol Oak Dusadeerungsikul
Author-X-Name-First: Puwadol Oak
Author-X-Name-Last: Dusadeerungsikul
Author-Name: Shimon Y. Nof
Author-X-Name-First: Shimon Y.
Author-X-Name-Last: Nof
Title: Cyber collaborative warehouse with dual-cycle operations design
Abstract: 
 Warehouse operations have been significantly improved because of the rapid advancement of cyber-physical system technologies, preparing for Work-of-the-Future. The challenge, however, is how to design a collaborative system to deliver optimal performance by multiple agents who are highly distributed but interconnected and operate with technologies that provide massive amounts of real-time data. To address the challenge, in this article, the Cyber Collaborative Protocol for Dual-Cycle Task in Future Warehouse is developed to minimise total operation cost and time. The problem is addressed in two phases; the Global and Local phases. The global phase has higher computational power, maintaining a mathematical model, while the local phase has limited computational power and time, utilising heuristics to deliver the outcome. Computer experiments are utilised for validating the designed protocol compared with other alternatives. The results show that, in all given scenarios, the newly designed protocol outperforms alternatives with statistical significance. The original contribution of this research is the design and control of Cyber Collaborative Warehouse operations with a new focus on collaborative multi-agent interactions. In addition, a major implication is that future warehouses can benefit competitively by operating with Task Administration Protocols such as the new Cyber Collaborative Protocol for Dual-Cycle Task in Future Warehouse.
Journal: International Journal of Production Research
Pages: 6552-6564
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2132313
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2132313
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Handle: RePEc:taf:tprsxx:v:61:y:2023:i:19:p:6552-6564



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2127959_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hugo Hissashi Miyata
Author-X-Name-First: Hugo Hissashi
Author-X-Name-Last: Miyata
Author-Name: Marcelo Seido Nagano
Author-X-Name-First: Marcelo Seido
Author-X-Name-Last: Nagano
Author-Name: Jatinder N. D. Gupta
Author-X-Name-First: Jatinder N. D.
Author-X-Name-Last: Gupta
Title: Solutions methods for m-machine blocking flow shop with setup times and preventive maintenance costs to minimise hierarchical objective-function
Abstract: 
 In this article, maintenance operations were incorporated to the sequence-dependent setup blocking flow shop to minimise total completion time subject to total maintenance costs. A mixed integer linear programming and procedures to incorporate maintenance to job sequence were developed. A constructive heuristic and three metaheuristics, greedy randomised adaptative search procedure (GRASP), discrete artificial bee colony (DABC), variable block insertion heuristic (VBIH) and iterated greedy algorithm (IG), designed to the blocking flow shop with total completion time minimisation were adapted to minimise total maintenance costs and the hierarchical function, respectively.All the methods were applied to solve small and medium and large size instance sets, with respective 1920 and 2200 problems. Experimental results shows that for small size instances set, DABC with 
 $ \alpha = 20 $ α=20 (DABC(20)) obtained the best trade-off between effectiveness and efficiency. For medium and large size instances set, DABC(20) VBIH with 
 $ \alpha = 20 $ α=20 (VBIH(20)) generated the best trade-off between quality of solution and computational time. Considering both instances set together, both DABC(20) and VBIH(20) obtained the best performance between quality of solution and computational time.
Journal: International Journal of Production Research
Pages: 6308-6335
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2127959
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2127959
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# input file: TPRS_A_2128918_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Anders Haug
Author-X-Name-First: Anders
Author-X-Name-Last: Haug
Title: Factors influencing knowledge sharing in new product development in high-tech manufacturing firms
Abstract: 
 Knowledge sharing is considered an important promotor of new product development (NPD) performance. However, studies have shown that making experts share knowledge in new product development (NPD) projects is often a challenging task. Consequently, this topic has attracted substantial attention in academic research. However, although studies have produced valuable insights, more detailed accounts of the mechanisms shaping knowledge sharing processes in NPD projects are sparse. To add to the knowledge on this topic, this study conducts a series of interviews with NPD professionals at manufacturers of high-tech industrial products to identify ‘factors influencing knowledge sharing’ (FIKS). The identified FIKS are explained through the socio-physiological theory, the ‘reasoned action approach’ (RAA). This involves several contributions. First, the study provides a detailed explanation of the role of FIKS by describing how they affect the behaviour of knowledge providers and receivers in NPD processes. Second, by identifying 161 FIKS in NPD processes, organised under 18 categories, the study offers the so far most extensive account of FIKS in NPD processes. Third, the findings suggest a special characteristic of knowledge sharing in NPD contexts concerning the relatively high importance of knowledge receiver behaviour.
Journal: International Journal of Production Research
Pages: 6418-6433
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2128918
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2128918
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# input file: TPRS_A_2125595_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Abhijeet Ghadge
Author-X-Name-First: Abhijeet
Author-X-Name-Last: Ghadge
Author-Name: Michael Bourlakis
Author-X-Name-First: Michael
Author-X-Name-Last: Bourlakis
Author-Name: Sachin Kamble
Author-X-Name-First: Sachin
Author-X-Name-Last: Kamble
Author-Name: Stefan Seuring
Author-X-Name-First: Stefan
Author-X-Name-Last: Seuring
Title: Blockchain implementation in pharmaceutical supply chains: A review and conceptual framework
Abstract: 
 Research on Blockchain implementation in the Pharmaceutical Supply Chains (PSC) is lacking despite its strong potential to overcome conventional supply chain challenges. Thus, this study aims to provide critical insight into the nexus between Blockchain and PSC and further build a conceptual framework for implementation within the pharmaceutical industry. Following a systematic literature review and text mining approach, 65 interdisciplinary articles published between 2010 and 2021 were studied to capture the decade long developments. Descriptive and thematic analysis showcases nascent developments of Blockchain in PSC. The drivers and barriers to adoption, implementation stages, and applications identified through the thematic analysis guide in setting the agenda for future research, primarily focussing on the use of Blockchain for drug counterfeiting, recall issues, along with other sector-specific challenges such as patient privacy, regulations and clinical trials. Research on Blockchain for PSC has been slow compared to other sectors, but has accelerated since the Covid-19 pandemic. Identified influential factors, implementation process and apparent applications are expected to influence researchers and practitioners in developing a roadmap for adopting Blockchain in the pharmaceutical industry. The proposed conceptual framework is novel and provides valuable directions to producers, regulators and governments to implement Blockchain in the pharmaceutical industry.
Journal: International Journal of Production Research
Pages: 6633-6651
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2125595
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2125595
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2127963_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yuqiang Feng
Author-X-Name-First: Yuqiang
Author-X-Name-Last: Feng
Author-Name: Yanju Chen
Author-X-Name-First: Yanju
Author-X-Name-Last: Chen
Author-Name: Yankui Liu
Author-X-Name-First: Yankui
Author-X-Name-Last: Liu
Title: Optimising two-stage robust supplier selection and order allocation problem under risk-averse criterion
Abstract: 
 This paper studies the supplier selection and order allocation (SS&OA) problem, where risks include a series of disruption scenarios with uncertain probability of occurrence. It is a challenge for industry decision-makers to balance the average cost and the level of risk under the ambiguity set for probabilities. To address this challenge, a two-stage distributionally robust (DR) Mean-CVaR model is presented for the SS&OA problem. A procedure is developed for constructing the ambiguity set, and Polyhedral and Box ambiguity sets are constructed to characterise the uncertain probabilities. The worst-case Mean-CVaR criterion is employed for the second-stage cost within the ambiguity set to trade off the expected cost and CVaR value. Three measures are incorporated to increase the resilience of the supply chain. The proposed robust model is reformulated into two mixed-integer linear programming models. A real case of the Huawei cell phone manufacturer is used to illustrate the validity of the proposed approach in numerical settings. Experimental results show that the new optimising approach can provide a robust SS&OA solution to immunise against the influence caused by uncertain probabilities. By comparative analyses, some management insights are obtained for industry decision-makers.
Journal: International Journal of Production Research
Pages: 6356-6380
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2127963
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2127963
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# input file: TPRS_A_2126019_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Georgiana Sandu
Author-X-Name-First: Georgiana
Author-X-Name-Last: Sandu
Author-Name: Olga Varganova
Author-X-Name-First: Olga
Author-X-Name-Last: Varganova
Author-Name: Behzad Samii
Author-X-Name-First: Behzad
Author-X-Name-Last: Samii
Title: Managing physical assets: a systematic review and a sustainable perspective
Abstract: 
 Contemporary organisations recognise the need for Anthropocene disruptions and transform their business models, restructure their operations, and re-engineer their supply chains to attain greater sustainable objectives and a strong ESG (environmental-social-governance) proposition. Indeed, physical asset management shifted from the negative image associated with asset failure, expensive maintenance, and decommissioning to an enabler of sustainability that allows us to create and capture value from extended lifetime, renewed functions, and increased awareness. In this direction, this study follows a systematic reviewing process enabled by text analytics methods to identify the means and approaches to build a sustainable perspective for physical asset management. Our key contributions and insights are supported by statistics and key features extracted from over 2800 journal articles. We particularly emphasise the research footprint, the evolution, and research trends of the two most asset-intensive sectors (i.e. construction and energy) represented as barriers and enablers of sustainable development. Lacking a unified perspective of the field, this study proposes a conceptual framework that adopts an asset-within-a-system perspective, recognises the links between the stakeholders and holistically integrates the extracted research trends. The knowledge provided here positions physical asset management as a key resource in achieving competitive advantage in the framework of sustainable development.
Journal: International Journal of Production Research
Pages: 6652-6674
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2126019
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2126019
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2131929_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Shuaishuai Fu
Author-X-Name-First: Shuaishuai
Author-X-Name-Last: Fu
Author-Name: Weida Chen
Author-X-Name-First: Weida
Author-X-Name-Last: Chen
Author-Name: Junfei Ding
Author-X-Name-First: Junfei
Author-X-Name-Last: Ding
Title: Can carbon asset pledge financing be beneficial for carbon emission-dependent engineering machinery remanufacturing?
Abstract: 
 Under the carbon trading mechanism, carbon asset has become an important resource and new production factor for enterprises, and are one of the key factors for production operations. As an emerging mortgage-loan model, carbon asset pledge financing (CAPF) can not only revitalize the carbon assets, but also address insufficient capital for enterprises. For carbon emission-dependent engineering machinery enterprises, this paper examines the impacts of CAPF on the performances of an emission-dependent and capital-constrained remanufacturer. Based on the benchmark without financing, the pure carbon asset pledge financing (PCAPF) strategy and the hybrid carbon asset pledge financing (HCAPF) strategy, are explored. The results show that: (i) Whether the remanufacturer chooses CAPF depends on initial capital, only when its initial capital is below a threshold, it can benefit from the CAPF loan. (ii) The choice of PCAPF and HCAPF for a remanufacturer depends on the quantity of carbon assets, compared with no capital constraint, the PCAPF and HCAPF are all conducive to increasing the quantity of remanufactured products and reducing carbon emissions. (iii) The HCAPF always has a higher contribution rate to the remanufactured quantity and consumer surplus than PCAPF, while the former strategy contributes less than the latter in terms of reducing carbon emission and gaining profit. (iv) Due to the relatively high interest, the HCAPF strategy can realize higher environmental performances and consumer welfare than the strategy of PCAPF.
Journal: International Journal of Production Research
Pages: 6533-6551
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2131929
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2131929
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# input file: TPRS_A_2125593_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Marko Vještica
Author-X-Name-First: Marko
Author-X-Name-Last: Vještica
Author-Name: Vladimir Dimitrieski
Author-X-Name-First: Vladimir
Author-X-Name-Last: Dimitrieski
Author-Name: Milan Mirko Pisarić
Author-X-Name-First: Milan Mirko
Author-X-Name-Last: Pisarić
Author-Name: Slavica Kordić
Author-X-Name-First: Slavica
Author-X-Name-Last: Kordić
Author-Name: Sonja Ristić
Author-X-Name-First: Sonja
Author-X-Name-Last: Ristić
Author-Name: Ivan Luković
Author-X-Name-First: Ivan
Author-X-Name-Last: Luković
Title: Production processes modelling within digital product manufacturing in the context of Industry 4.0
Abstract: 
 Industry 4.0 aims to establish highly flexible production, enabling effective and efficient mass customisation of products. Modelling techniques and simulation of production processes are among the core techniques of the manufacturing industry that facilitate flexibility and automation of a shop floor in the era of Industry 4.0. In this paper, we present an approach to support production process modelling and process model management. The approach is based on Model-Driven (MD) principles and comprises a Domain-Specific Modelling Language (DSML) named Multi-Level Production Process Modelling Language (MultiProLan). MultiProLan uses a set of concepts to specify production process models suitable for automatic instruction generation and execution of the instructions in a simulation or on a shop floor. By using MultiProLan, process designers may create process models independent of the specific production system. Such process models can either be automatically enriched by matching and scheduling algorithms or manually enriched by a process designer via MultiProLan’s modelling tool. In this paper, we also present an application of our approach in the assembly industry to showcase its dynamic resource management, generation of production documentation, error handling and process monitoring.
Journal: International Journal of Production Research
Pages: 6271-6290
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2125593
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2125593
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# input file: TPRS_A_2127958_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xianpei Hong
Author-X-Name-First: Xianpei
Author-X-Name-Last: Hong
Author-Name: Meiling Zhou
Author-X-Name-First: Meiling
Author-X-Name-Last: Zhou
Author-Name: Yeming (Yale) Gong
Author-X-Name-First: Yeming (Yale)
Author-X-Name-Last: Gong
Author-Name: Wanying Chen
Author-X-Name-First: Wanying
Author-X-Name-Last: Chen
Title: Quality information disclosure and advertising strategy in a supply chain
Abstract: 
 Existing research on advertising structures in a supply chain has mainly been conducted with symmetric quality information and the interaction between quality information disclosure and advertising has not been clarified. To identify the optimal advertising structure and disclosure strategy for a manufacturer, we explore manufacturer advertising and cooperative advertising in the context of product quality information asymmetry. We examine the implications of the manufacturer’s product quality information disclosure on his advertising strategies and the impact of advertising on quality information disclosure decisions. When cooperative advertising is more effective than manufacturer advertising and the product quality is low, the manufacturer should adopt manufacturer advertising, which leads to higher perceived quality and improves the retailer’s economic condition. We find that advertising can inspire the manufacturer to disclose more product quality information regardless of the advertising structure, which occurs when the effectiveness of advertising is large. Furthermore, the manufacturer, the retailer, and consumers can benefit from cooperative advertising when cooperative advertising is more effective than manufacturer advertising and the product quality is high. We also consider an extension where the manufacturer and retailer advertise simultaneously and find that advertising leads to more quality information being disclosed when the disclosure cost is low.
Journal: International Journal of Production Research
Pages: 6291-6307
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2127958
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2127958
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2131926_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Narain Gupta
Author-X-Name-First: Narain
Author-X-Name-Last: Gupta
Author-Name: Goutam Dutta
Author-X-Name-First: Goutam
Author-X-Name-Last: Dutta
Author-Name: Krishnendranath Mitra
Author-X-Name-First: Krishnendranath
Author-X-Name-Last: Mitra
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj
Author-X-Name-Last: Kumar Tiwari
Title: Analytics with stochastic optimisation: experimental results of demand uncertainty in process industries
Abstract: 
 This study reports the test results of a two-stage stochastic linear programming (SLP) model with recourse using a user-friendly generic decision support system (DSS) in a North American steel company. This model has the flexibility to configure multiple material facilities, activities and storage areas in a multi-period and multi-scenario environment. The value of stochastic solution (VSS) with a real-world example has a potential benefit of US$ 24.61 million. Experiments were designed according to the potential joint probability distribution scenarios and the magnitude of demand variability. Overall, 144 SLP optimisation model instances were solved across four industries, namely, steel, aluminium, polymer and pharmaceuticals. The academic contribution of this research is two-fold: first, the potential contribution to profit in a steel company using an SLP model; and second, the optimisation empirical experiments confirm a pattern that the VSS and expected value of perfect information (EVPI) increase with the increase in demand variability. This study has implications for practicing managers seeking business solutions with prescriptive analytics using stochastic optimisation-based DSS. This study will attract more industry attention to business solutions, and the prescriptive analytics discipline will garner more scholarly and industry attention.
Journal: International Journal of Production Research
Pages: 6501-6518
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2131926
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2131926
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2122622_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Dan Luo
Author-X-Name-First: Dan
Author-X-Name-Last: Luo
Author-Name: Simon Thevenin
Author-X-Name-First: Simon
Author-X-Name-Last: Thevenin
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: A state-of-the-art on production planning in Industry 4.0
Abstract: 
 The Industry 4.0 revolution is changing the manufacturing landscape. A broad set of new technologies emerged (including software and connected equipment) that digitise manufacturing systems. These technologies bring new vitality and opportunities to the manufacturing industry, but they also bring new challenges. This paper focuses on the impact of Industry 4.0 on production planning approaches and software. We first propose a digital twin framework that integrates production planning systems and frontier technologies. The frontier technologies that may impact production planning software are the internet of things, cloud manufacturing, blockchain, and big data analytics. Second, we provide a state-of-the-art on the application of each technology in the production planning, as well as a detailed analysis of the benefit and application status. Finally, this paper discusses the future research and application directions in the production planning. We conclude that Industry 4.0 will lead to the construction of data-driven models for production planning software. These tools will include models built accurately from data, account for uncertainty, and partially actuate the decision autonomously.
Journal: International Journal of Production Research
Pages: 6602-6632
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2122622
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2122622
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2127962_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ting Wang
Author-X-Name-First: Ting
Author-X-Name-Last: Wang
Author-Name: Jian Wang
Author-X-Name-First: Jian
Author-X-Name-Last: Wang
Author-Name: Guixiang Jin
Author-X-Name-First: Guixiang
Author-X-Name-Last: Jin
Author-Name: Hiroaki Matsukawa
Author-X-Name-First: Hiroaki
Author-X-Name-Last: Matsukawa
Title: Product platform configuration decision in NPD with uncertain demands and module options
Abstract: 
 Platform-based product development is a cost-efficient approach to satisfy wide range of customer preferences. One important problem is the product platform configuration, in which two types of platform configuration are widely used, either module selection or module integration. The platform configuration based on module selection provides a broader solution space of platform selection, while module integration facilitates product platform commonality to gain economic benefits. Up to date, most research focused on the platform configuration based on module selection with a given module set. In this paper, we propose a new model to determine the optimal platform configuration for an external product family, considering both module selection and integration. The demand for the external product family is uncertain and assumed to follow normal distribution. A hybrid methodology combining simulated annealing and variable neighbourhood search is proposed. A numerical examination is carried out for the purpose of evaluation. The results show that the proposed model can provide a practically good solution. Main contributions of this research are two folds, one is the balance point between module selection and module integration in the platform configuration and the other is that we take into account the operation cost of module acquisition to the platform configuration problem.
Journal: International Journal of Production Research
Pages: 6336-6355
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2127962
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2127962
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2129501_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Adrian Barwasser
Author-X-Name-First: Adrian
Author-X-Name-Last: Barwasser
Author-Name: Joachim Lentes
Author-X-Name-First: Joachim
Author-X-Name-Last: Lentes
Author-Name: Oliver Riedel
Author-X-Name-First: Oliver
Author-X-Name-Last: Riedel
Author-Name: Nikolas Zimmermann
Author-X-Name-First: Nikolas
Author-X-Name-Last: Zimmermann
Author-Name: Manfred Dangelmaier
Author-X-Name-First: Manfred
Author-X-Name-Last: Dangelmaier
Author-Name: Jingyi Zhang
Author-X-Name-First: Jingyi
Author-X-Name-Last: Zhang
Title: Method for the development of Software-Defined Manufacturing equipment
Abstract: 
 Customer demands force manufacturing companies to offer individualised products to remain competitive. This results in a demand for flexibility and adaptability in product development and production, which causes a rise in complexity. Simultaneously, manufacturers strive to further automatise production and assembly lines to increase cost efficiency and optimise output. This leads to a conflict of interest between two different approaches, ‘streamlined and cost-efficient’ or ‘individualised and costly’. Software-Defined Manufacturing (SDM) is a new approach that seeks to reconcile these diametrical goals by increasing the adaptability of automated manufacturing. This is achieved by virtualising key functionalities of production machines, which permit the configuration of system functionality via software. With current production equipment, this is difficult, because it was designed for a specific process and because there is no meaningful separation between the executing physical part of the machine and the controlling software. This article presents a new method for the development of SDM-ready production machines and processes. The application of the method on a production use-case demonstrates its usefulness in the improvement of existing production facilities and processes. It further addresses the wider trend of Software-Defined Anything (SDx) and outlines the role SDM could play on the pathway towards autonomous manufacturing.
Journal: International Journal of Production Research
Pages: 6467-6484
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2129501
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2129501
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# input file: TPRS_A_2127964_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Huifang Zhou
Author-X-Name-First: Huifang
Author-X-Name-Last: Zhou
Author-Name: Shuyou Zhang
Author-X-Name-First: Shuyou
Author-X-Name-Last: Zhang
Author-Name: Lemiao Qiu
Author-X-Name-First: Lemiao
Author-X-Name-Last: Qiu
Author-Name: Zili Wang
Author-X-Name-First: Zili
Author-X-Name-Last: Wang
Author-Name: Kerui Hu
Author-X-Name-First: Kerui
Author-X-Name-Last: Hu
Title: A factorisation-based recommendation model for customised products configuration design
Abstract: 
 Product configuration design combines the existing configurable components of enterprises to quickly form a new product that meets customised requirements. However, the representation, maintenance, and update of the configuration knowledge, and the mismatch problem restrict the rationality and efficiency of existing configuration design methods. In this paper, a recommendation model is developed for customised product configuration design, which takes personalised customer requirements and product component information as input and outputs a ranked list of component instances. It consists of two sub-models: a retrieval sub-model and a ranking sub-model. The retrieval sub-model selects a set of component instance candidates from all possible candidates, and then the ranking sub-model ranks them and selects the best possible candidate. To boost the ranking sub-model performance, we propose a novel interacting network, DualAdap, to extract meaningful low-order, high-order, and adaptive-order cross features. Based on learned cross features, the ranking sub-model computes the adoption scores of all candidates and then selects the best possible candidate according to adoption scores. The configuration design of the elevator traction machine is taken as a case study. Results verify that our recommendation model can identify similar component instances and then accurately pick out the best possible candidate that meets customer requirements.
Journal: International Journal of Production Research
Pages: 6381-6402
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2127964
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2127964
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# input file: TPRS_A_2128919_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yuri N. Sotskov
Author-X-Name-First: Yuri N.
Author-X-Name-Last: Sotskov
Title: Stability of a schedule minimising the makespan for processing jobs on identical machines
Abstract: 
 A set of jobs has to be processed on identical machines. Every job may be processed on any available machine without preemptions. The criterion is to minimise the makespan (i.e. the completion time of the last job in a schedule). During the realisation of a schedule, durations of some jobs may deviate from the initial values estimated before scheduling. Other jobs have fixed durations that are known before scheduling. We conduct a stability analysis of the optimal semi-active schedule. First, we derive necessary and sufficient conditions for an optimal schedule to be unstable with respect to infinitely small variations of the non-fixed durations (the stability radius of an unstable schedule is equal to zero). Second, we show that the stability radius of an optimal schedule could be infinitely large. Furthermore, several lower and upper bounds on the stability radius have been established. Third, we derive a formula and develop an algorithm for calculating stability radii.
Journal: International Journal of Production Research
Pages: 6434-6450
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2128919
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2128919
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# input file: TPRS_A_2131928_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yang Li
Author-X-Name-First: Yang
Author-X-Name-Last: Li
Author-Name: Kunpeng Li
Author-X-Name-First: Kunpeng
Author-X-Name-Last: Li
Author-Name: Amir Gharehgozli
Author-X-Name-First: Amir
Author-X-Name-Last: Gharehgozli
Title: Optimal return and refund polices for perishable food items with online grocery shopping
Abstract: 
 The purpose of this paper is to help online grocery retailers determine the optimal return and refund policies for perishable grocery items. Three refund policies and two return requirements are modelled: no-refund, full-refund and partial-refund, with or without product return. We first derive the optimal refund policy under two scenarios, where either product return is or is not required for refund. We further analyse how market conditions impact the optimal policies. Lastly, we investigate when product return should be required for refund. Our results show that a more generous refund policy should be offered if the product has a higher profit margin, if an unsatisfactory product has a large negative impact on consumer utility, and if consumers have high return costs when product return is required for refund. Our results also show that it is optimal not to require the unwanted product to be returned when consumer’s return cost and product return rate are above certain threshold values. This paper fills the gap in the literature on return and refund policies in an online grocery setting. The findings of this paper provide explicit guidance to online grocery businesses on how to optimally determine the return and refund policies.
Journal: International Journal of Production Research
Pages: 6519-6532
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2131928
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2131928
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# input file: TPRS_A_2127965_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Nan Du
Author-X-Name-First: Nan
Author-X-Name-Last: Du
Author-Name: Yan Yang
Author-X-Name-First: Yan
Author-X-Name-Last: Yang
Author-Name: Hesuan Hu
Author-X-Name-First: Hesuan
Author-X-Name-Last: Hu
Title: Robust deadlock control in automated manufacturing systems with unreliable resources based on an algebraic way
Abstract: 
 In automated manufacturing systems (AMSs), because of unpredictable failures, resources can lose functions such that the deadlock control methods, in existence, are invalidated. In this paper, a robust deadlock control approach is proposed for AMSs with multiple unreliable resources. The considered AMSs modelled by Petri nets (PNs) allow to acquire different types of resources at each processing stage. In order to visualise the fact that resource failures occur in AMSs, recovery subnets are designed for the modelling AMSs to depict the failures and recoveries of resources. Based on a siphon detection method performed by a set of integer linear programming formulations, a control specification is proposed. Control places (monitors) with their control variables are designed for the detected unmarked siphons at a marking to guarantee that they are always marked even if some unreliable resources break down. Iteratively, all unmarked siphons are detected and controlled. Therefore, a robust deadlock supervisor is synthesised to ensure the controlled system's liveness no matter there exist resource failures or not. The theoretical analyses and proof are given to verify the correctness of the proposed method. Finally, the comparative studies are presented to expound the proposed method's effectiveness and efficiency.
Journal: International Journal of Production Research
Pages: 6403-6417
Issue: 19
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2127965
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2127965
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# input file: TPRS_A_2140221_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Benjamin Rolf
Author-X-Name-First: Benjamin
Author-X-Name-Last: Rolf
Author-Name: Ilya Jackson
Author-X-Name-First: Ilya
Author-X-Name-Last: Jackson
Author-Name: Marcel Müller
Author-X-Name-First: Marcel
Author-X-Name-Last: Müller
Author-Name: Sebastian Lang
Author-X-Name-First: Sebastian
Author-X-Name-Last: Lang
Author-Name: Tobias Reggelin
Author-X-Name-First: Tobias
Author-X-Name-Last: Reggelin
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: A review on reinforcement learning algorithms and applications in supply chain management
Abstract: 
 Decision-making in supply chains is challenged by high complexity, a combination of continuous and discrete processes, integrated and interdependent operations, dynamics, and adaptability. The rapidly increasing data availability, computing power and intelligent algorithms unveil new potentials in adaptive data-driven decision-making. Reinforcement Learning, a class of machine learning algorithms, is one of the data-driven methods. This semi-systematic literature review explores the current state of the art of reinforcement learning in supply chain management (SCM) and proposes a classification framework. The framework classifies academic papers based on supply chain drivers, algorithms, data sources, and industrial sectors. The conducted review revealed a few critical insights. First, the classic Q-learning algorithm is still the most popular one. Second, inventory management is the most common application of reinforcement learning in supply chains, as it is a pivotal element of supply chain synchronisation. Last, most reviewed papers address toy-like SCM problems driven by artificial data. Therefore, shifting to industry-scale problems will be a crucial challenge in the next years. If this shift is successful, the vision of data-driven decision-making in real-time could become a reality.
Journal: International Journal of Production Research
Pages: 7151-7179
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2140221
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2140221
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# input file: TPRS_A_2141907_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mario Rapaccini
Author-X-Name-First: Mario
Author-X-Name-Last: Rapaccini
Author-Name: Veronica Loew Cadonna
Author-X-Name-First: Veronica Loew
Author-X-Name-Last: Cadonna
Author-Name: Leonardo Leoni
Author-X-Name-First: Leonardo
Author-X-Name-Last: Leoni
Author-Name: Filippo De Carlo
Author-X-Name-First: Filippo
Author-X-Name-Last: De Carlo
Title: Application of machine learning techniques for cost estimation of engineer to order products
Abstract: 
 Cost engineering capabilities are becoming increasingly important for the competitiveness of industrial firms, especially for engineer to order products (ETOPs). Despite this relevance, the literature on the use of advanced data-driven methodologies, such as machine learning (ML), for early cost estimation (CE) of ETOPs is quite sparse. Furthermore, ML has still seen little use in real industrial applications due to several challenges. Accordingly, the objective of this paper is threefold: (a) to develop a solid early CE approach for ETOPs, including feature selection; (b) to investigate the benefits of adopting ML for ETOPs’ CE; (c) to identify how ML can be introduced into real industrial context with little knowledge on ML. Long action research has been carried out with a large industrial company that produces Oil & Gas ETOPs. We observed how ML facilitates the exploration of the relationships between the choices of early design stages and the CE. ML algorithms also allowed to both capture the high variability of the data and test different combinations of cost drivers in very effective ways. The project resulted in an accurate CE framework with an iterative feature selection process and an approach for introducing ML into a real industrial context.
Journal: International Journal of Production Research
Pages: 6978-7000
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2141907
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2141907
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# input file: TPRS_A_2145516_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Erna Engebrethsen
Author-X-Name-First: Erna
Author-X-Name-Last: Engebrethsen
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Title: Transportation strategies for dynamic lot sizing: single or multiple modes?
Abstract: 
 The complexity of decision-making for companies buying transportation services has increased due to the presence of more options and pricing schedules for transportation. Many companies make transportation and inventory decisions in an uncoordinated way and select only one transportation mode, missing opportunities for logistics cost savings. The experimental study in this paper is based on a real-world decision problem faced by a Scandinavian company that distributes fast-moving consumer goods and wants to determine its transportation strategy. We propose a novel multi-mode lot-sizing model with dynamic deterministic demand to illustrate the cost impact of accurately modelling piecewise-linear transportation costs and allowing a more flexible usage of transportation modes when planning order replenishments. We compare three transportation strategies with increasing degrees of flexibility: two single mode strategies, where one strategy is more flexible than the other, and a multi-mode strategy. We conclude that managers can significantly reduce costs by increasing the flexibility of mode selection in transportation strategies.
Journal: International Journal of Production Research
Pages: 7064-7084
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2145516
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2145516
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# input file: TPRS_A_2144525_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Beatrice Bolsi
Author-X-Name-First: Beatrice
Author-X-Name-Last: Bolsi
Author-Name: Vinícius Loti de Lima
Author-X-Name-First: Vinícius Loti
Author-X-Name-Last: de Lima
Author-Name: Thiago Alves de Queiroz
Author-X-Name-First: Thiago
Author-X-Name-Last: Alves de Queiroz
Author-Name: Manuel Iori
Author-X-Name-First: Manuel
Author-X-Name-Last: Iori
Title: Heuristic algorithms for integrated workforce allocation and scheduling of perishable products
Abstract: 
 We study a problem from a real-world application, in which a daily set of orders must be processed following two stages, consisting of preparing perishable products on benches and allocating them to conveyors to be packed in disposable trays. Daily decisions must be made regarding the number and start time of working shifts, the number of workers and their allocation to machines, and the scheduling of orders in a two-stage flexible flow shop environment. The flow shop environment of the studied problem is common in many industries of perishable products, making the problem very general. The problem involves a number of operational constraints, and three objective functions that are minimised in a lexicographic way. To solve the problem, we implement a constructive heuristic and embed it within three metaheuristics: a Random multi-start algorithm (MR), a Biased random key genetic algorithm (BRKGA), and a Variable neighbourhood search (VNS) based one. We perform computational experiments over a set of realistic instances, and present a lower bound obtained from a constraint programming model for the scheduling counterpart. The results of the experiments show that the BRKGA is the most effective in practice for the integrated problem of workforce allocation and scheduling.
Journal: International Journal of Production Research
Pages: 7048-7063
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2144525
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2144525
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# input file: TPRS_A_2139002_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Maude Beauchemin
Author-X-Name-First: Maude
Author-X-Name-Last: Beauchemin
Author-Name: Marc-André Ménard
Author-X-Name-First: Marc-André
Author-X-Name-Last: Ménard
Author-Name: Jonathan Gaudreault
Author-X-Name-First: Jonathan
Author-X-Name-Last: Gaudreault
Author-Name: Nadia Lehoux
Author-X-Name-First: Nadia
Author-X-Name-Last: Lehoux
Author-Name: Stéphane Agnard
Author-X-Name-First: Stéphane
Author-X-Name-Last: Agnard
Author-Name: Claude-Guy Quimper
Author-X-Name-First: Claude-Guy
Author-X-Name-Last: Quimper
Title: Dynamic allocation of human resources: case study in the metal 4.0 manufacturing industry
Abstract: 
 Industry 4.0 concepts make it possible to rethink human resources allocation, even for more traditional environments like metal machining. While parts machining on Computer Numerical Control (CNC) machines is automated, some manual tasks must still be executed by operators. The current approach is typically that operators are statically allocated to one or many machines. This causes avoidable bottlenecks. We propose an optimisation model to dynamically assign tasks to the operators with the objective of minimising production delays. Three different scenarios are compared; one representing the current widely used static allocation method and two others that allow more flexibility in the operators’ allocation. The dynamic task assignment problem is solved using a constraint programming model. The model was applied to a case study from a high-precision metal manufacturing job shop. Experimental results show that switching from a static allocation to a dynamic one reduces by 76% the average production delays caused by human operators. Supposing more versatile operators under the dynamic allocation leads to further improvements.
Journal: International Journal of Production Research
Pages: 6891-6907
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2139002
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2139002
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# input file: TPRS_A_2146228_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Khaled Medini
Author-X-Name-First: Khaled
Author-X-Name-Last: Medini
Title: A framework for agility improvement projects in the post mass customisation era
Abstract: 
 Changing customer requirements and turbulent markets require suitably adapted capabilities to proactively cope with rapid changes. Agile manufacturing emerged in the late 1990s as a competitive concept to respond to these business challenges. While several seminal research works address agility in terms of concept definition, drivers and strategic capabilities, there is a lack of implementation frameworks of agile manufacturing. The current paper is concerned with the question of how to improve the agility of manufacturing companies. To address this question, a framework is iteratively developed with the aim of supporting decision makers in planning and implementing agility improvement projects. To this end, Design Science Research (DSR) methodology is used in conjunction with CIMO-logic (Context, Intervention, Mechanism, Outcome). The iterative development of the framework relies heavily on insights from case studies and from practitioners in the broad manufacturing sector. The paper provides evidence of the validity of the framework as well as outlining further research perspectives.
Journal: International Journal of Production Research
Pages: 7105-7121
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2146228
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2146228
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# input file: TPRS_A_2138610_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yupeng Li
Author-X-Name-First: Yupeng
Author-X-Name-Last: Li
Author-Name: Mengting Zhang
Author-X-Name-First: Mengting
Author-X-Name-Last: Zhang
Author-Name: Na Zhang
Author-X-Name-First: Na
Author-X-Name-Last: Zhang
Author-Name: Hongyan Jiang
Author-X-Name-First: Hongyan
Author-X-Name-Last: Jiang
Title: Towards product evolution: from the perspective of user knowledge
Abstract: 
 In the field of engineering design, design for evolution is an economic and effective tactic to deal with changing customer requirements, in which the quantification of the product evolution degree between adjacent product generations is vital. Under the knowledge economy environment, user knowledge includes personalised experience, which can be used to develop competitive and creative products. The evolution of user knowledge can be applied to monitor product evolution to a certain extent. Thus, an evolution model is established to quantify the product evolution degree by integrating a user knowledge network, the Girven–Newman algorithm, latent Dirichlet allocation, an information axiom, and an evolution map. These methods are adopted to determine the knowledge topics for each product generation and to quantify the evolution degree of the current product generation, while the inheritance relation between each pair of knowledge clusters in two adjacent product generations is considered. Finally, the evolution process modelling of iPhone is performed as a case study to evaluate the effectiveness of the proposed method. The results show that the evolution map and curve to visualise the evolution process, and the evolution patterns and mechanisms are deduced to assist designers in forecasting future trends.
Journal: International Journal of Production Research
Pages: 6829-6846
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2138610
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2138610
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# input file: TPRS_A_2138609_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Dandan Gao
Author-X-Name-First: Dandan
Author-X-Name-Last: Gao
Author-Name: Nengmin Wang
Author-X-Name-First: Nengmin
Author-X-Name-Last: Wang
Author-Name: Zhengwen He
Author-X-Name-First: Zhengwen
Author-X-Name-Last: He
Author-Name: Li Zhou
Author-X-Name-First: Li
Author-X-Name-Last: Zhou
Title: Analysis of bullwhip effect and inventory cost in the online closed-loop supply chain
Abstract: 
 This paper focuses on the impact of return decisions on the bullwhip effect in the online closed-loop supply chain. We investigate the optimal return modes when the inspection system is undertaken by the logistics centre or the remanufacturer. Then, we optimise the online retailers’ return decisions of minimising the inventory cost and bullwhip effect under different supply chain circumstances. Distinctive from previous conclusion that the inspection operation is usually undertaken by the remanufacturer to sort the returned products, the analysis results reveal that the optimal decision of mitigating the bullwhip effect in most cases is to set the inspection system on logistics centre. Besides, consumers’ return and exchange behaviours in e-commerce have different impacts on the supply chain efficiency. The product return can not necessarily mitigate the information distortion in online closed-loop supply chain. The research provides insights for managers to strategise about return policies and resource allocation in different e-commerce contexts.
Journal: International Journal of Production Research
Pages: 6808-6828
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2138609
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2138609
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2140219_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Niloofar Katiraee
Author-X-Name-First: Niloofar
Author-X-Name-Last: Katiraee
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Serena Finco
Author-X-Name-First: Serena
Author-X-Name-Last: Finco
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Title: Assembly line balancing and worker assignment considering workers’ expertise and perceived physical effort
Abstract: 
 In manual assembly systems, workers’ differences in terms of skills, level of expertise and perceived physical effort largely affect the assembly line balancing and system performance. Traditional long-term strategic decisions may not respond to workforce changes and needs, resulting in frequent requests for line rebalancing. In this study, we propose a methodological framework and an easy-to-use Assembly Line Worker Assignment and Rebalancing Problem with different options: workers’ assignment considering their performance variability, integration of worker dependent physical exertion constraints and possibility to use trainers to assist inexperienced workers. A bi-objective linear programming model is proposed aiming to minimise the cycle time and the number of reassigned tasks to respect the initial design while integrating new workers with different characteristics. The 
 $ \varepsilon $ ϵ-constraint approach is used to build Pareto frontiers for this bi-objective problem. This approach is applied to three real cases. The obtained results show that the developed model can be successfully used in manufacturing companies to help the production managers to deal with workforce turnover and skills heterogeneity.
Journal: International Journal of Production Research
Pages: 6939-6959
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2140219
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2140219
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# input file: TPRS_A_2139005_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Foivos Psarommatis
Author-X-Name-First: Foivos
Author-X-Name-Last: Psarommatis
Author-Name: Gokan May
Author-X-Name-First: Gokan
Author-X-Name-Last: May
Title: A standardized approach for measuring the performance and flexibility of digital twins
Abstract: 
 Numerous studies have focused on digital twins (DTs) and their applications. However, a common method for evaluating the performance of DTs is lacking. Digital twins performance assessment mechanism is crucial when improving or monitoring any process or system in a business, such a strategy could serve as a guide to help researchers and practitioners create more effective digital twins. Guided by these challenges, we propose a structured method for measuring the performance and flexibility of digital twins, and our study provides a procedure for quantitative calculation of the performance of DTs based on four key performance indicators (KPIs). Moreover, we propose a new KPI, DTflex, for determining the flexibility of digital twins. We evaluated the performance of DTflex as a KPI to demonstrate its use as a simple tool for designers and practitioners to quickly compare different DT methodologies, which might provide valuable input for the iterative improvement of DTs to increase their efficiency in future applications. The knowledge provided along with the method proposed in this paper is expected to help researchers and practitioners working in different fields to compare DT methodologies and DT performance which will lead to higher efficiency DT solutions and increased re-usage of existing DTs.
Journal: International Journal of Production Research
Pages: 6923-6938
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2139005
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2139005
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# input file: TPRS_A_2099320_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Junhai Ma
Author-X-Name-First: Junhai
Author-X-Name-Last: Ma
Author-Name: Fengshan Si
Author-X-Name-First: Fengshan
Author-X-Name-Last: Si
Author-Name: Qin Zhang
Author-X-Name-First: Qin
Author-X-Name-Last: Zhang
Author-Name:  Huijiang
Author-X-Name-First: 
Author-X-Name-Last: Huijiang
Title: Evolution delayed decision game based on carbon emission and capacity sharing in the Chinese market
Abstract: 
 Based on the carbon emission policy and low-carbon capacity sharing, this paper studies the optimal product pricing and capacity matching strategies of competition and cooperation between two companies in a duopoly market. And the optimal strategies with or without capacity sharing are discussed. In addition, a differential game model based on carbon emission constraints, low-carbon capacity sharing, and delayed decision-making is established. We also study the evolution of duopoly enterprises from the initial state to the equilibrium state. Besides, the influence of delayed decision variables, price adjustment speed and decision weights on the stability of the game system is analyzed. The results show that the government can effectively intervene and guide the enterprises’ low-carbon production strategy through carbon emission restriction policy. Low-carbon capacity sharing is beneficial to both enterprises, and the demand side benefits more than the supply side. We discuss the impact of stable and unstable systems on enterprises’ decisions. When the system is stable, enterprises can converge from different initial game states to equilibrium states. The adoption of a delay strategy will not affect the tendency of convergence to the equilibrium. Furthermore, the system using the variable feedback control method is of higher stability.
Journal: International Journal of Production Research
Pages: 6675-6690
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2099320
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2099320
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2138611_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jože M. Rožanec
Author-X-Name-First: Jože M.
Author-X-Name-Last: Rožanec
Author-Name: Inna Novalija
Author-X-Name-First: Inna
Author-X-Name-Last: Novalija
Author-Name: Patrik Zajec
Author-X-Name-First: Patrik
Author-X-Name-Last: Zajec
Author-Name: Klemen Kenda
Author-X-Name-First: Klemen
Author-X-Name-Last: Kenda
Author-Name: Hooman Tavakoli Ghinani
Author-X-Name-First: Hooman
Author-X-Name-Last: Tavakoli Ghinani
Author-Name: Sungho Suh
Author-X-Name-First: Sungho
Author-X-Name-Last: Suh
Author-Name: Entso Veliou
Author-X-Name-First: Entso
Author-X-Name-Last: Veliou
Author-Name: Dimitrios Papamartzivanos
Author-X-Name-First: Dimitrios
Author-X-Name-Last: Papamartzivanos
Author-Name: Thanassis Giannetsos
Author-X-Name-First: Thanassis
Author-X-Name-Last: Giannetsos
Author-Name: Sofia Anna Menesidou
Author-X-Name-First: Sofia Anna
Author-X-Name-Last: Menesidou
Author-Name: Ruben Alonso
Author-X-Name-First: Ruben
Author-X-Name-Last: Alonso
Author-Name: Nino Cauli
Author-X-Name-First: Nino
Author-X-Name-Last: Cauli
Author-Name: Antonello Meloni
Author-X-Name-First: Antonello
Author-X-Name-Last: Meloni
Author-Name: Diego Reforgiato Recupero
Author-X-Name-First: Diego Reforgiato
Author-X-Name-Last: Recupero
Author-Name: Dimosthenis Kyriazis
Author-X-Name-First: Dimosthenis
Author-X-Name-Last: Kyriazis
Author-Name: Georgios Sofianidis
Author-X-Name-First: Georgios
Author-X-Name-Last: Sofianidis
Author-Name: Spyros Theodoropoulos
Author-X-Name-First: Spyros
Author-X-Name-Last: Theodoropoulos
Author-Name: Blaž Fortuna
Author-X-Name-First: Blaž
Author-X-Name-Last: Fortuna
Author-Name: Dunja Mladenić
Author-X-Name-First: Dunja
Author-X-Name-Last: Mladenić
Author-Name: John Soldatos
Author-X-Name-First: John
Author-X-Name-Last: Soldatos
Title: Human-centric artificial intelligence architecture for industry 5.0 applications
Abstract: 
 Human-centricity is the core value behind the evolution of manufacturing towards Industry 5.0. Nevertheless, there is a lack of architecture that considers safety, trustworthiness, and human-centricity at its core. Therefore, we propose an architecture that integrates Artificial Intelligence (Active Learning, Forecasting, Explainable Artificial Intelligence), simulated reality, decision-making, and users' feedback, focussing on synergies between humans and machines. Furthermore, we align the proposed architecture with the Big Data Value Association Reference Architecture Model. Finally, we validate it on three use cases from real-world case studies.
Journal: International Journal of Production Research
Pages: 6847-6872
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2138611
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2138611
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# input file: TPRS_A_2139004_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hyeon-Il Kim
Author-X-Name-First: Hyeon-Il
Author-X-Name-Last: Kim
Author-Name: Dong-Ho Lee
Author-X-Name-First: Dong-Ho
Author-X-Name-Last: Lee
Title: Scheduling algorithms for multi-stage flow shops with reworks under overlapped queue time limits
Abstract: 
 This study addresses a multi-stage flow shop scheduling problem in which a job is reworked when its queue time between two arbitrary stages exceeds an upper limit. The problem is to determine the start times of jobs and rework setups/operations if incurred for the objective of minimising makespan. As an extension of the previous studies, multiple overlapped queue time limits are considered, i.e. some in-between stages of queue time limits for a job are overlapped. A mixed integer programming model is developed and its performance is reported for small-sized test instances. Then, due to the limited applications of optimal solution approaches, a variable neighbourhood search (VNS) algorithm is proposed that generates an initial solution and improves it using a shaking and a local search improvement methods. In addition, it is extended to the general variable neighbourhood search (GVNS) algorithms with variable neighbourhood descent (VND) methods. Computational results show that the GVNS algorithms outperform the VNS algorithm significantly and also give near optimal solutions for small-sized test instances within a reasonable amount of computation times.
Journal: International Journal of Production Research
Pages: 6908-6922
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2139004
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2139004
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Handle: RePEc:taf:tprsxx:v:61:y:2023:i:20:p:6908-6922



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2136283_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Qing Yan
Author-X-Name-First: Qing
Author-X-Name-Last: Yan
Author-Name: Jiansha Lu
Author-X-Name-First: Jiansha
Author-X-Name-Last: Lu
Author-Name: Hongtao Tang
Author-X-Name-First: Hongtao
Author-X-Name-Last: Tang
Author-Name: Yan Zhan
Author-X-Name-First: Yan
Author-X-Name-Last: Zhan
Author-Name: Xuemei Zhang
Author-X-Name-First: Xuemei
Author-X-Name-Last: Zhang
Author-Name: Yingde Li
Author-X-Name-First: Yingde
Author-X-Name-Last: Li
Title: Travel time analysis and dimension optimisation design of double-ended compact storage system
Abstract: 
 Considering the storage increasing demand of ‘multi-variety, small-batch' characteristic goods, we developed a new type of compact warehouse a three-dimensional double-ended compact storage system. Compared with the traditional three-dimensional automated storage and retrieval system (AS/RS) and existing three-dimensional compact AS/RS model, the storage system we designed exhibits excellent characteristics such as high density, high throughput efficiency, and more flexible configuration. There are three key points in our work listed as follows. Firstly, we establish the continuous travel time model under specific operating conditions in this new three-dimensional compact warehouse. Secondly, the three-dimensional size of the storage rack is optimised. The optimal three-dimensional proportion of the storage rack is obtained based on the model’s optimal solution. Finally, numerical examples are given to analyse the influence of the I/O port layouts and related parameters on the system throughput efficiency. According to the optimisation results of the system model, a more reasonable rack dimension can be designed, which can provide an effective reference for the construction of a three-dimensional double-ended compact warehouse.
Journal: International Journal of Production Research
Pages: 6718-6745
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2136283
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2136283
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# input file: TPRS_A_2142689_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Daisy Valle Enrique
Author-X-Name-First: Daisy Valle
Author-X-Name-Last: Enrique
Author-Name: Giuliano Almeida Marodin
Author-X-Name-First: Giuliano Almeida
Author-X-Name-Last: Marodin
Author-Name: Fernando Bigares Charrua Santos
Author-X-Name-First: Fernando Bigares Charrua
Author-X-Name-Last: Santos
Author-Name: Alejandro G. Frank
Author-X-Name-First: Alejandro G.
Author-X-Name-Last: Frank
Title: Implementing industry 4.0 for flexibility, quality, and productivity improvement: technology arrangements for different purposes
Abstract: 
 Productivity, quality, and flexibility are key production targets pursued by companies that adopt Industry 4.0. However, it is unclear how Industry 4.0 technologies can help achieve these different and sometimes competing targets. This study investigates this relationship through a survey of 92 manufacturers. The study employs Exploratory Factor Analysis to define four main technology arrangements based on 18 Industry 4.0 technologies: Vertical Integration, Virtual Manufacturing, Advanced Manufacturing Processing Technologies, and Online Traceability. Then, independent samples tests were conducted to compare the implementation status of these arrangements when manufacturing flexibility, process quality, and productivity are (or are not) pursued as the main production targets. The results show that Vertical Integration is a general-purpose technology arrangement because it supports all targets. On the other hand, Virtual Manufacturing and Online Traceability are specific-purpose arrangements, adopted especially for flexibility and productivity targets, respectively. Advanced Manufacturing Processing Technologies, in turn, is an integrative-purpose technology arrangement since it is adopted when two competing targets are pursued: productivity and manufacturing flexibility. The study ends with a decision model to implement Industry 4.0 based on the production targets a company may pursue. It shows the interconnection and trade-offs between these production targets and the Industry 4.0 technologies adopted.
Journal: International Journal of Production Research
Pages: 7001-7026
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2142689
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2142689
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# input file: TPRS_A_2137595_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Zhaoxiang Chen
Author-X-Name-First: Zhaoxiang
Author-X-Name-Last: Chen
Author-Name: Zhen Chen
Author-X-Name-First: Zhen
Author-X-Name-Last: Chen
Author-Name: Di Zhou
Author-X-Name-First: Di
Author-X-Name-Last: Zhou
Author-Name: Chi Shao
Author-X-Name-First: Chi
Author-X-Name-Last: Shao
Author-Name: Ershun Pan
Author-X-Name-First: Ershun
Author-X-Name-Last: Pan
Title: Optimal replacement policy for multi-state manufacturing system with economic and resource dependence under epistemic uncertainty
Abstract: 
 This paper develops an optimal replacement policy V* for a multi-state manufacturing system. The manufacturing system would be repaired imperfectly once its performance cannot meet the production demand, and would be replaced when the production demand is not met for the V*-th time. Due to imprecise state assignments and unpredictable external working conditions, the performance and transition intensity of the multi-state machine cannot be accurately identified and then inevitably lead to epistemic uncertainty. In addition, the economic dependence and resource dependence that prevailed in the manufacturing system should be considered. In this paper, economic dependence is described as the time and cost saved by simultaneously repairing multiple identical machines, and resource dependence is caused by finite capacity buffers. To take these into account, the fuzzy Markov model and fuzzy stochastic flow manufacturing network (FSFMN) are tailored to evaluate the fuzzy reliability of machines and manufacturing systems, respectively. To obtain the optimal replacement policy V*, we derive the expression of the long run fuzzy profit rate under epistemic uncertainty. The replacement policy is demonstrated on the ferrite phase shifting unit manufacturing system, and the results of the subsequent comparative study and sensitivity analysis show that this policy is more effective.
Journal: International Journal of Production Research
Pages: 6772-6790
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2137595
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2137595
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# input file: TPRS_A_2137594_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Huu Du Nguyen
Author-X-Name-First: Huu Du
Author-X-Name-Last: Nguyen
Author-Name: Adel Ahmadi Nadi
Author-X-Name-First: Adel Ahmadi
Author-X-Name-Last: Nadi
Author-Name: Kim Duc Tran
Author-X-Name-First: Kim Duc
Author-X-Name-Last: Tran
Author-Name: Philippe Castagliola
Author-X-Name-First: Philippe
Author-X-Name-Last: Castagliola
Author-Name: Giovanni Celano
Author-X-Name-First: Giovanni
Author-X-Name-Last: Celano
Author-Name: Kim Phuc Tran
Author-X-Name-First: Kim Phuc
Author-X-Name-Last: Tran
Title: The Shewhart-type RZ control chart for monitoring the ratio of autocorrelated variables
Abstract: 
 In many industrial manufacturing processes, the quality of products can depend on the relative amount between two quality characteristics X and Y. Often, this calls for the on-line monitoring of the ratio 
 $ Z=X/Y $ Z=X/Y as a quality characteristic itself by means of a control chart. A large number of control charts monitoring the ratio have been investigated in the literature under the assumption of independent normal observations of the two quality characteristics. In practice, due to the high frequency in sensor data collection, both autocorrelation and cross-correlation between consecutive observations can exist for X and Y and should be modelled to protect against the false alarm rate inflation when implementing a control chart for monitoring the ratio 
 $ Z=X/Y $ Z=X/Y. In this paper, we tackle this problem by investigating the performance of the Phase II Shewhart-type RZ control chart monitoring the ratio of two normal variables whose relationship is captured by a bivariate time series autoregressive model VAR(1), which can also account for the cross-correlation between the two quality characteristics. With the numerical study, we discuss how the design and the statistical performance of the Shewhart-type RZ control chart change with the VAR(1) model's parameters. We also provide an example to illustrate the use of the Shewhart-type RZ control chart with bivariate time series of observations in a furnace process.
Journal: International Journal of Production Research
Pages: 6746-6771
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2137594
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2137594
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# input file: TPRS_A_2145517_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Author-Name: Hanyu Zhang
Author-X-Name-First: Hanyu
Author-X-Name-Last: Zhang
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Li Yu
Author-X-Name-First: Li
Author-X-Name-Last: Yu
Title: A relax-and-fix method for clothes inventory balancing scheduling problem
Abstract: 
 The clothes inventory balancing scheduling problem (CIBSP) among branch stores with the allowance of lateral transshipments has gained increasing attentions in fast-fashion apparel industry, especially for the trial sale of new products. To solve the CIBSP faced by a leading apparel company in China, a mixed integer linear programming (MILP) model is first formulated, based on which a relax-and-fix (R&F) method is developed. Several heuristic cuts based on practical experience and observations are further integrated into the R&F method to speed up the searching. The effectiveness of the method is demonstrated through extensive computational experiments: it is able to provide near-optimal solutions with average optimality gap 1.15% with less computation time, compared to solving the MILP model directly in a commercial solver. Case studies also demonstrate that the developed R&F method can obtain high-quality solutions with average optimality gap 0.09% with much less computation time.
Journal: International Journal of Production Research
Pages: 7085-7104
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2145517
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2145517
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# input file: TPRS_A_2146773_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Azmat Ullah
Author-X-Name-First: Azmat
Author-X-Name-Last: Ullah
Author-Name: Qingyun Xu
Author-X-Name-First: Qingyun
Author-X-Name-Last: Xu
Author-Name: Yi He
Author-X-Name-First: Yi
Author-X-Name-Last: He
Author-Name: Benjamin Lev
Author-X-Name-First: Benjamin
Author-X-Name-Last: Lev
Title: Supply chain strategy of adopting blockchain in post-sale customer care outsourcing in a competitive environment
Abstract: 
 Post-sale customer care (PSCC) outsourcing is an effective supply chain strategy to reduce costs, but traditional outsourcing methods cannot ensure consumers’ belief in PSCC quality, harming the firms’ competitive strategy. To ensure consumer satisfaction through transparency, this article examines evolving supply chain strategies of leveraging blockchain to outsource PSCC operations of competing manufacturers to third-party agents. Based on consumers’ beliefs and blockchain adoption cost, manufacturers have two choices; to outsource the PSCC operations with or without blockchain, resulting in multiple outsourcing strategies. Results show that the consumers’ belief in one manufacturer’s outsourcing strategy has detrimental effects on the stance of another manufacturer. Moreover, the blockchain cost and consumers’ beliefs dictate the manufacturers’ strategies for PSCC outsourcing, resulting in a ‘quadruple zone of strategic fit’, where both manufacturers adopt blockchain or neither adopt blockchain, or one adopts while the other does not. Interestingly, despite the low or zero blockchain cost, both manufacturers will outsource without blockchain if their traditional business models satisfy consumers. The extended analysis reveals contradictory results that manufacturers should outsource more often with blockchain to facilitate consumers when a long-term warranty is offered, or the product has a higher failure rate, even though, overall these factors increase costs.
Journal: International Journal of Production Research
Pages: 7122-7150
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2146773
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2146773
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2138615_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Erbao Cao
Author-X-Name-First: Erbao
Author-X-Name-Last: Cao
Author-Name: Haodong Luo
Author-X-Name-First: Haodong
Author-X-Name-Last: Luo
Author-Name: Yuan Ma
Author-X-Name-First: Yuan
Author-X-Name-Last: Ma
Author-Name: Kevin Lü
Author-X-Name-First: Kevin
Author-X-Name-Last: Lü
Title: Dynamic pricing in the presence of strategic consumers with ‘experience-in-store-and-buy-online’
Abstract: 
 Experience-in-store-and-buy-online (ESBO) is a popular omni-channel strategy. This paper studies the effects of inspection service provision on the interactions of a dynamic-pricing retailer and strategic consumers, i.e., the effects of the ESBO initiative on store operations. Selling a seasonal product over two periods, the omni-channel retailer may allow consumers to inspect this product offline only in the first period (first-period inspection) or in both periods (two-period inspection). First, we find that allowing first-period inspection makes the retailer better off. The retailer will price the product higher in the first period but probably lower in the second period. Even so, more consumers will purchase in the first period: that is, allowing first-period inspection can somewhat deter strategic deferral. Meanwhile, the seemingly negative intertemporal showrooming behavior (i.e., inspect the product offline in the first period but defer online purchase to the second period) benefits the retailer. Compared to first-period inspection, allowing two-period inspection increases the retailer’s prices in both periods as well as profit, provided that inspection is definitely available in the second period. On the other hand, when inspection is possible in the second period, it may be profitable to allow inspection only in the first period..
Journal: International Journal of Production Research
Pages: 6873-6890
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2138615
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2138615
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2142861_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Qussay Jarrar
Author-X-Name-First: Qussay
Author-X-Name-Last: Jarrar
Author-Name: Farouk Belkadi
Author-X-Name-First: Farouk
Author-X-Name-Last: Belkadi
Author-Name: Remy Blanc
Author-X-Name-First: Remy
Author-X-Name-Last: Blanc
Author-Name: Kenan Kestaneci
Author-X-Name-First: Kenan
Author-X-Name-Last: Kestaneci
Author-Name: Alain Bernard
Author-X-Name-First: Alain
Author-X-Name-Last: Bernard
Title: Knowledge reuse for decision aid in additive manufacturing: application on cost quotation support
Abstract: 
 The expeditiously growing interest in Additive Manufacturing (AM) in various domains and applications leads to different challenges in terms of management and optimisation. These issues are due to the vast amount and type variety of data and knowledge generated across the AM value chain. Therefore, it becomes essential to deliver useful help to support information management and critical decisions along the AM product realisation. This paper proposes a knowledge-based Framework for traceability and decision aid in AM processes. The proposed solution is applied in a critical phase concerning process generation and cost estimation at the beginning of AM project. A software demonstrator is deployed in a real industrial case study: Heat Exchanger for Aircraft.
Journal: International Journal of Production Research
Pages: 7027-7047
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2142861
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2142861
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2137596_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Vahid Babaveisi
Author-X-Name-First: Vahid
Author-X-Name-Last: Babaveisi
Author-Name: Ebrahim Teimoury
Author-X-Name-First: Ebrahim
Author-X-Name-Last: Teimoury
Author-Name: Mohammad Reza Gholamian
Author-X-Name-First: Mohammad Reza
Author-X-Name-Last: Gholamian
Author-Name: Bahman Rostami-Tabar
Author-X-Name-First: Bahman
Author-X-Name-Last: Rostami-Tabar
Title: Integrated demand forecasting and planning model for repairable spare part: an empirical investigation
Abstract: 
 Efficient resource management methods are essential for spare parts used in the maintenance and repair of equipment. Forecasting plays a critical role in planning, especially under demand uncertainty. Existing works regarding spare parts with intermittent demand focus on the mere forecasting model while integrating the planning and forecasting models are not sufficiently investigated. We examine the interaction between two models to optimise planning and forecasting decisions and prevent sub-optimality. This paper presents two mathematical models, including a planning model that determines stock level, spare part order assignment to suppliers, equipment repair assignment, and the number of intervals over the planning horizon. The second model is the forecasting model by Support Vector Machine (SVM). Considering uncertainty, demand estimation is performed by piecewise linearisation considering the optimal number of intervals in the planning model used in forecasting. An interactive procedure is developed to optimise models. We use an empirical investigation from an oil company providing the spare part supply chain data. The analyses show that demand estimation by piecewise method and integrating the decisions optimises the cost, improves the forecasting accuracy, and planning performance. Moreover, we offer several insights to practitioners that shed light on spare part planning and forecasting decisions.
Journal: International Journal of Production Research
Pages: 6791-6807
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2137596
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2137596
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# input file: TPRS_A_2136279_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Eduardo Curcio
Author-X-Name-First: Eduardo
Author-X-Name-Last: Curcio
Author-Name: Vinícius L. de Lima
Author-X-Name-First: Vinícius L.
Author-X-Name-Last: de Lima
Author-Name: Flávio K. Miyazawa
Author-X-Name-First: Flávio K.
Author-X-Name-Last: Miyazawa
Author-Name: Elsa Silva
Author-X-Name-First: Elsa
Author-X-Name-Last: Silva
Author-Name: Pedro Amorim
Author-X-Name-First: Pedro
Author-X-Name-Last: Amorim
Title: The integrated lot-sizing and cutting stock problem under demand uncertainty
Abstract: 
 Interest in integrating lot-sizing and cutting stock problems has been increasing over the years. This integrated problem has been applied in many industries, such as paper, textile and furniture. Yet, there are only a few studies that acknowledge the importance of uncertainty to optimise these integrated decisions. This work aims to address this gap by incorporating demand uncertainty through stochastic programming and robust optimisation approaches. Both robust and stochastic models were specifically conceived to be solved by a column generation method. In addition, both models are embedded in a rolling-horizon procedure in order to incorporate dynamic reaction to demand realisation and adapt the models to a multistage stochastic setting. Computational experiments are proposed to test the efficiency of the column generation method and include a Monte Carlo simulation to assess both stochastic programming and robust optimisation for the integrated problem. Results suggest that acknowledging uncertainty can cut costs by up to 39.7%, while maintaining or reducing variability at the same time.
Journal: International Journal of Production Research
Pages: 6691-6717
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2136279
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2136279
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# input file: TPRS_A_2140364_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Di Liu
Author-X-Name-First: Di
Author-X-Name-Last: Liu
Author-Name: Heeseon Kim
Author-X-Name-First: Heeseon
Author-X-Name-Last: Kim
Author-Name: Seong-Hee Kim
Author-X-Name-First: Seong-Hee
Author-X-Name-Last: Kim
Author-Name: Taeheung Kim
Author-X-Name-First: Taeheung
Author-X-Name-Last: Kim
Author-Name: Dongki Lee
Author-X-Name-First: Dongki
Author-X-Name-Last: Lee
Author-Name: Yao Xie
Author-X-Name-First: Yao
Author-X-Name-Last: Xie
Title: Distribution-free multivariate time-series monitoring with analytically determined control limits
Abstract: 
 We consider the problem of detecting a shift in the mean of a multivariate time-series process with general marginal distributions and general cross- and auto-correlation structures. We propose a distribution-free monitoring procedure that does not need model fitting or trial-and-error calibration for control limits, which makes the procedure convenient to be implemented when a facility consists of many processes to be monitored. The main idea is to convert each observation vector into a one-dimensional 
 $ T^2 $ T2 quantity that captures cross-correlation. The 
 $ T^2 $ T2 quantities form a univariate auto-correlated process, and CUSUM statistics are constructed on the 
 $ T^2 $ T2 quantities. Then using the fact that the CUSUM statistics on the auto-correlated process behave as a reflected Brownian motion asymptotically under some conditions, the control limits of the CUSUM procedure are analytically determined by setting the first-passage time of the Brownian motion equal to a target in-control average run length. We compare the performance of our procedure with three competing procedures on simulated data with various cross- and auto-correlation and real data from a wafer etching process. The proposed procedure delivers actual in-control average run lengths close to the target and shows comparable or better performance in detecting a shift in mean than the competitors.
Journal: International Journal of Production Research
Pages: 6960-6977
Issue: 20
Volume: 61
Year: 2023
Month: 10
X-DOI: 10.1080/00207543.2022.2140364
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2140364
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# input file: TPRS_A_2151659_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Fei Yu
Author-X-Name-First: Fei
Author-X-Name-Last: Yu
Author-Name: Jinfeng Fu
Author-X-Name-First: Jinfeng
Author-X-Name-Last: Fu
Author-Name: Jing Guo
Author-X-Name-First: Jing
Author-X-Name-Last: Guo
Author-Name: Runhua Tan
Author-X-Name-First: Runhua
Author-X-Name-Last: Tan
Author-Name: Bojun Yang
Author-X-Name-First: Bojun
Author-X-Name-Last: Yang
Title: An approach for radical innovative design based on cross-domain technology mining in patents
Abstract: 
 The key to radical innovation lies in technological breakthroughs, and the key to technical breakthroughs lies in the application of cross-domain knowledge. However, in the conceptual design stage of new product development, the designer’s cognition and knowledge are limited and the retrieval and evaluation of cross-domain technologies is often subjective, making it difficult to generate radical concepts. To address the above issues, this paper proposes a method for cross-domain technology recommendation based on patent analysis. In this method, feature words in various domains of patents are used to generalise the abstract functions of product core subsystems, where designers can obtain more comprehensive cross-domain technologies. This is conducive to breaking the design fixation of designers. Subject–Action–Object structural and functional similarity are combined to quickly extract cross-domain technologies in patents. Then multiple technical indicators are used to objectively evaluate and rank cross-domain technologies. This approach helps designers objectively select cross-domain technologies to change the way next-generation products work, enabling early planning of production conditions and a head start in the market. The method has been verified in a new product development project on peeling equipment, a new product that meets radical indicators is finally obtained.
Journal: International Journal of Production Research
Pages: 7502-7523
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2151659
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2151659
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# input file: TPRS_A_2148011_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Zhun Xu
Author-X-Name-First: Zhun
Author-X-Name-Last: Xu
Author-Name: Liyun Xu
Author-X-Name-First: Liyun
Author-X-Name-Last: Xu
Author-Name: Xufeng Ling
Author-X-Name-First: Xufeng
Author-X-Name-Last: Ling
Author-Name: Beikun Zhang
Author-X-Name-First: Beikun
Author-X-Name-Last: Zhang
Title: Data-driven hierarchical learning and real-time decision-making of equipment scheduling and location assignment in automatic high-density storage systems
Abstract: 
 Automated high-density storage systems (AHDSS) have attracted widespread attention in recent years owing to their advantages of high throughput and space utilisation. However, owing to the characteristics of large-scale, multi-disturbance, and short-period task scenarios, a system is required to make instant and efficient decisions. To this end, this paper proposes a data-driven real-time decision-making method to solve the real-time equipment scheduling and dynamic location assignment problem in AHDSS. The proposed method comprises two phases: decision scheme learning and real-time decision-making. The operation state attribute features of the AHDSS were constructed to generate training data for equipment scheduling and location assignment scheme learning. Thereafter, a hierarchical learning and decision-making mechanism based on the deep belief network (DBN) is proposed. The integrated learning of better scheduling solutions was realised by establishing three-stage models of lift selection, shuttle selection, and location priority. Additionally, the Taguchi method was adopted to determine the best performance parameters for DBNs at different learning stages. Compared with other well-known machine learning algorithms, DBNs have a higher learning accuracy. Finally, a real-world AHDSS problem is studied, and the results demonstrate that the proposed approach outperforms existing dispatching rules.
Journal: International Journal of Production Research
Pages: 7333-7352
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2148011
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2148011
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# input file: TPRS_A_2150907_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ran Shneor
Author-X-Name-First: Ran
Author-X-Name-Last: Shneor
Author-Name: Sigal Berman
Author-X-Name-First: Sigal
Author-X-Name-Last: Berman
Title: The Rαβγ categorisation framework for dexterous robotic manufacturing processes
Abstract: 
 Dexterous robotics systems integrate advanced manipulation and perception capabilities, facilitating advanced process automation. However, the inherent complexities of such processes may induce vulnerabilities, impeding overall performance. A parsimonious categorisation of dexterous robotic processes can disambiguate process attributes and highlight intricacies. Existing robotic categorisations focusing on a single attribute (e.g. manipulator structure) lack a processes view. Existing production process categorisations lack valuation of robotic characteristics. The current work suggests Rαβγ, a holistic categorisation of dexterous robotic processes. Rαβγ integrates robotic concepts within the classical [α|β|γ] production process categorisation and is similarly divided into tiers: Workcell, Task, and Objective. Each tier is defined by qualitative descriptors and quantitative characteristics. The intricacies of each characteristic were quantified by an analytic hierarchical process (AHP), semi-structured interviews with robotic experts were conducted for validation, and utility is demonstrated by three case studies. The AHP results are consistent and interpretable. The interviewees determined that Rαβγ is valuable and comprehensive. The case studies demonstrate the categorisation’s ability to highlight major process attributes. The analysis asserts that Rαβγ can be valuable during different product life cycle phases, e.g. designing, commissioning, etc. Rαβγ uniquely integrates the manufacturing and robotic domains, offering a holistic mechanism for highlighting characteristics of dexterous robotic processes.
Journal: International Journal of Production Research
Pages: 7467-7482
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2150907
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2150907
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# input file: TPRS_A_2148767_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bartu Arslan
Author-X-Name-First: Bartu
Author-X-Name-Last: Arslan
Author-Name: Banu Yetkin Ekren
Author-X-Name-First: Banu Yetkin
Author-X-Name-Last: Ekren
Title: Transaction selection policy in tier-to-tier SBSRS by using Deep Q-Learning
Abstract: 
 This paper studies a Deep Q-Learning (DQL) method for transaction sequencing problems in an automated warehousing system, Shuttle-based Storage and Retrieval System (SBSRS), in which shuttles can move between tiers flexibly. Here, the system is referred to as tier-to-tier SBSRS (t-SBSRS), developed as an alternative design to tier-captive SBSRS (c-SBSRS). By the flexible travel of shuttles between tiers in t-SBSRS, the number of shuttles in the system may be reduced compared to its simulant c-SBSRS design. The flexible travel of shuttles makes the operation decisions more complex in that system, motivating us to explore whether integration of a machine learning approach would help to improve the system performance. We apply the DQL method for the transaction selection of shuttles in the system to attain process time advantage. The outcomes of the DQN are confronted with the well-applied heuristic approaches: first-come-first-serve (FIFO) and shortest process time (SPT) rules under different racking and numbers of shuttles scenarios. The results show that DQL outperforms the FIFO and SPT rules promising for the future of smart industry applications. Especially, compared to the well-applied SPT rule in industries, DQL improves the average cycle time per transaction by roughly 43% on average.
Journal: International Journal of Production Research
Pages: 7353-7366
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2148767
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2148767
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# input file: TPRS_A_2150906_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ben A. Chaouch
Author-X-Name-First: Ben A.
Author-X-Name-Last: Chaouch
Title: Optimal stocking policies for inventory systems with uncertain returns
Abstract: 
 The purpose of this paper is to enlarge the scope of existing EOQ-type models by incorporating uncertain product returns that may include time or quantity restrictions. In this inventory control problem, the item’s demand is deterministic and occurs at a known constant rate over time. Product returns arrive according to a Poisson process. The amount returned to the seller at each return epoch is a random or fixed fraction of the accumulated number of units (net of previous returns) that have been demanded so far within a stock cycle. The ordering policy is a continuous review policy that orders a fixed quantity every time an order is placed. The replenishment lead time is instantaneous, and shortages are not allowed. The objective is to find optimal order quantities by minimising the long-run average total costs per unit time. Costs include a fixed plus proportional cost per order, and a holding cost per unit held in inventory per unit time. A level-crossing approach is used to derive a closed-form expression for the expected ordering and inventory holding costs as a function of the order size and other relevant parameters.
Journal: International Journal of Production Research
Pages: 7453-7466
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2150906
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2150906
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# input file: TPRS_A_2149873_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Qiqi Miao
Author-X-Name-First: Qiqi
Author-X-Name-Last: Miao
Author-Name: Zhaoyang Bai
Author-X-Name-First: Zhaoyang
Author-X-Name-Last: Bai
Author-Name: Xiaobing Liu
Author-X-Name-First: Xiaobing
Author-X-Name-Last: Liu
Author-Name: Muhammad Awais
Author-X-Name-First: Muhammad
Author-X-Name-Last: Awais
Title: Modelling and numerical analysis for seru system balancing with lot splitting
Abstract: 
 Lot splitting is one of the effective technologies of time-based strategy and has been widely studied in a variety of production environments. Nevertheless, the literature on its application in seru production has been highly scarce until now. Seru system is composed of simple equipment and multi-skilled workers, which can be quickly converted from the traditional assembly line to seru units. As an innovative production mode, seru production inevitably allows applying lot splitting in the real world. Therefore, a multi-objective model is studied for line–cell conversion with lot splitting, aiming at determining the trade-off among makespan, inter-seru system balancing, and intra-seru system balancing. Due to the proposed model's NP-hard nature, an improved NSGA-II was developed to solve it. Finally, extensive numerical simulations are conducted. Compared to no lot splitting, lot splitting is improved by 4.2% and 3.7% in terms of inter-seru system balancing and makespan respectively. The better efficiency and effectiveness of the improved NSGA-II are proved by comparisons with other state-of-the-art algorithms. Additionally, a sensitivity analysis is conducted to ascertain the degree of contribution of the model parameters towards the value of objectives, which provides management implications to support the decision-making of seru production for the enterprise.
Journal: International Journal of Production Research
Pages: 7410-7433
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2149873
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2149873
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# input file: TPRS_A_2149874_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jianbo Yu
Author-X-Name-First: Jianbo
Author-X-Name-Last: Yu
Author-Name: Shijin Li
Author-X-Name-First: Shijin
Author-X-Name-Last: Li
Author-Name: Xing Liu
Author-X-Name-First: Xing
Author-X-Name-Last: Liu
Author-Name: Yanfeng Gao
Author-X-Name-First: Yanfeng
Author-X-Name-Last: Gao
Author-Name: Shijin Wang
Author-X-Name-First: Shijin
Author-X-Name-Last: Wang
Author-Name: Changhui Liu
Author-X-Name-First: Changhui
Author-X-Name-Last: Liu
Title: Dynamic convolutional gated recurrent unit attention auto-encoder for feature learning and fault detection in dynamic industrial processes
Abstract: 
 The dynamic characteristics (i.e. autocorrelation and cross-correlation) in modern industrial systems have raised great challenges to process fault detection. To cope with the dynamics and uncertainty of dynamic industrial processes, this paper proposes a new process control method, dynamic convolutional gated recurrent unit attention auto-encoder (DCGRUA-AE) for fault detection in dynamic processes. Firstly, DCGRUA-AE integrates a convolutional gated recurrent unit (CGRU) with a local convolution layer to learn both global and local features of dynamic process data in an unsupervised fashion. Secondly, a dual attention module is embedded in the deep network to preserve effective features. Finally, DeconvGRU combined with a dense layer is used as the encoder to reconstruct the original process data. Two statistics (i.e. T-square (T2) and squared prediction error (SPE)) based on DCGRUA-AE are used to set the control limits for fault detection. The feasibility and superiority of DCGRUA-AE-based fault detection method have been verified on four industrial processes. The experimental results indicate that the CGRU and dual attention mechanism can significantly improve the fault detection performance of DCGRUA-AE in dynamic processes. The hybrid of CGRU, attention mechanism and auto-encoder provides a new method for fault detection in dynamic industrial processes.
Journal: International Journal of Production Research
Pages: 7434-7452
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2149874
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2149874
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# input file: TPRS_A_2150908_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Fatma Ben Khalifa
Author-X-Name-First: Fatma Ben
Author-X-Name-Last: Khalifa
Author-Name: Chaaben Kouki
Author-X-Name-First: Chaaben
Author-X-Name-Last: Kouki
Author-Name: Imen Safra
Author-X-Name-First: Imen
Author-X-Name-Last: Safra
Author-Name: Zied Jemai
Author-X-Name-First: Zied
Author-X-Name-Last: Jemai
Title: Analysis and optimisation of periodic inventory models for perishable items with a general lifetime
Abstract: 
 We considered two periodic review perishable inventory systems. The first system is controlled by a periodic review 
 $ ({T,S} ) $ (T,S) policy, where orders are triggered at each review period 
 $ T $ T and when the stock is less than 
 $ S $ S. The second one is controlled by a periodic review 
 $ ({s,S} ) $ (s,S) policy, where orders are triggered only if the stock level is below 
 $ s $ s. For both models, the lifetime of each product was assumed to follow a general distribution, whereas the lead time was constant. The demands followed a Poisson process, and all unsatisfied demand was lost. Using an approximate solution of the steady-state probabilities of the inventory level, we obtained a closed form of cost expression. Next, we conducted a simulation study to identify our solution accuracy. Finally, we performed a sensitivity analysis to evaluate the effect of the lifetime variation and cost parameters on the best policy and its cost. The obtained results were close to those of the optimal policy with an average accuracy of 3.7% for the periodic review 
 $ ({T,S} ) $ (T,S) policy and 3.8% for the periodic review 
 $ ({s,S} ) $ (s,S) policy. For the worst cases, where the accuracy is higher than 7%, we provided an analytical approach to improve the system accuracy.
Journal: International Journal of Production Research
Pages: 7483-7501
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2150908
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2150908
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# input file: TPRS_A_2148010_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Swapnil Bhalla
Author-X-Name-First: Swapnil
Author-X-Name-Last: Bhalla
Author-Name: Erlend Alfnes
Author-X-Name-First: Erlend
Author-X-Name-Last: Alfnes
Author-Name: Hans-Henrik Hvolby
Author-X-Name-First: Hans-Henrik
Author-X-Name-Last: Hvolby
Author-Name: Olumide Oluyisola
Author-X-Name-First: Olumide
Author-X-Name-Last: Oluyisola
Title: Sales and operations planning for delivery date setting in engineer-to-order manufacturing: a research synthesis and framework
Abstract: 
 Sales and operations planning (S&OP) has emerged as a planning approach that integrates tactical level decisions across functions and supply chains while aligning day-to-day operations with long-term strategy through these decisions. The extant knowledge on S&OP has evolved primarily based on the needs of mass production contexts, and applications of S&OP in engineer-to-order (ETO) contexts have not been explored by previous research. Arguing that the cross-functionally coordinated planning enabled by S&OP can improve the effectiveness of the challenging and competitively critical tendering process, this paper develops an S&OP framework for the tactical planning process design to support delivery date setting in ETO contexts. The paper adopts a systematic literature review approach for identifying the main tactical planning activities managers in ETO companies should consider while designing the S&OP process and the information inputs required for performing and coordinating these planning activities. The identified planning activities and planning inputs are synthesised to develop the proposed S&OP framework for delivery date setting in ETO contexts. The proposed framework can support managers in assessing which tactical planning activities are strategically essential in their respective companies and redesigning or reconfiguring existing planning processes to address the planning needs of their environment.
Journal: International Journal of Production Research
Pages: 7302-7332
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2148010
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2148010
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2152126_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yuqing Zhang
Author-X-Name-First: Yuqing
Author-X-Name-Last: Zhang
Author-Name: Min Xie
Author-X-Name-First: Min
Author-X-Name-Last: Xie
Author-Name: Yihai He
Author-X-Name-First: Yihai
Author-X-Name-Last: He
Author-Name: Xiao Han
Author-X-Name-First: Xiao
Author-X-Name-Last: Han
Title: Capability-based remaining useful life prediction of machining tools considering non-geometry and tolerancing features with a hybrid model
Abstract: 
 Machining tools are vital components of intelligent manufacturing systems whose state and remaining useful life (RUL) determine product quality. Specifically, the wearing of tool reduces its capability of production yield and diminishes product quality. Therefore, a capability-based RUL prediction approach is proposed in this paper to thoroughly evaluate the state and RUL of machining tools. First, the connotation of tool capability is discussed, and a framework for quality assurance capability-based RUL prediction is proposed. Product quality, which can be used to assess the capability of tool, is modelled and expanded to consider non-geometric dimensioning and tolerancing (non-GD&T) features based on the classic geometric dimensioning and tolerancing (GD&T) system. Second, a physics-based model of process is developed to estimate the non-GD&T features and calculate tool wear. Third, a hybrid data-driven and physics-based model is developed to quantitatively assess the capability of tool based on the comprehensive quality estimation. Finally, a case study of rolling machining tool is carried out to verify the effectiveness and proactiveness of the proposed framework, and the final result highlights its rationality and accuracy in estimating the RUL of machining tools with better interpretation.
Journal: International Journal of Production Research
Pages: 7540-7556
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2152126
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152126
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# input file: TPRS_A_2147233_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Camille Gras
Author-X-Name-First: Camille
Author-X-Name-Last: Gras
Author-Name: Nathalie Herr
Author-X-Name-First: Nathalie
Author-X-Name-Last: Herr
Author-Name: Alantha Newman
Author-X-Name-First: Alantha
Author-X-Name-Last: Newman
Title: A decision aid algorithm for long-haul parcel transportation based on hierarchical network structure
Abstract: 
 With the explosion of e-commerce, optimising parcel transportation has become increasingly important. We study the long-haul stage of parcel transportation which takes place between sorting centres and delivery depots and is performed on a two-level hierarchical network. In our case study, we describe the application framework of this industrial problem faced by a French postal company: There are two vehicle types that must be balanced over the network on a daily basis, and there are two possible sorting points for each parcel, which allows a better consolidation of parcels. These industrial constraints are formalised in the Long-Haul Parcel Transportation Problem (LHPTP). We present a Mixed Integer Linear Program (MILP) and a hierarchical algorithm with aggregation of demands which uses the MILP as a subroutine. We perform numerical experiments on large-size datasets provided by a postal company, which consist of approximately 2500 demands on a network of 225 sites. These tests enable the tuning of certain parameters resulting in a tailored heuristic for the LHPTP. Our algorithm can serve as a decision aid tool for transportation managers to build daily transportation plans, modeled on solutions produced given daily demand forecasts and can also be used to improve the network design.
Journal: International Journal of Production Research
Pages: 7198-7212
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2147233
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2147233
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# input file: TPRS_A_2149872_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Kai Zhang
Author-X-Name-First: Kai
Author-X-Name-Last: Zhang
Author-Name: Chuanhou Gao
Author-X-Name-First: Chuanhou
Author-X-Name-Last: Gao
Title: Improved formulations of the joint order batching and picker routing problem
Abstract: 
 Order picking is the process of retrieving ordered products from storage locations in warehouses. In picker-to-parts order picking systems, two or more customer orders may be grouped and assigned to a single picker. Then routing decisions regarding the visiting sequence of items during a picking tour must be made. Won and Olafsson (2005) found that solving the integrated problem of batching and routing enables warehouse managers to organize order picking operations more efficiently compared with solving the two problems separately and sequentially. We therefore investigate the mathematical programming formulation of this integrated problem.We present several improved formulations of the problem based on the findings of Valle, Beasley, and Salles da Cunha (2017), that can significantly improve computational results. More specifically, we reconstruct the connectivity constraints and generate new cutting planes in our branch-and-cut framework. We also discuss some problem properties by studying the structure of a graphical representation of the warehouse, and we present two types of additional constraints. We also consider the no-reversal case of this problem. We present efficient formulations by building different auxiliary graphs. Finally, we present computational results for publicly available test problems for single-block and multiple-block warehouse configurations.
Journal: International Journal of Production Research
Pages: 7386-7409
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2149872
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2149872
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# input file: TPRS_A_2148768_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Manuel Iori
Author-X-Name-First: Manuel
Author-X-Name-Last: Iori
Author-Name: Alberto Locatelli
Author-X-Name-First: Alberto
Author-X-Name-Last: Locatelli
Author-Name: Marco Locatelli
Author-X-Name-First: Marco
Author-X-Name-Last: Locatelli
Title: A GRASP for a real-world scheduling problem with unrelated parallel print machines and sequence-dependent setup times
Abstract: 
 We consider a real-world scheduling problem arising in the colour printing industry. The problem consists in assigning print jobs to a heterogeneous set of flexographic printer machines and finding a processing sequence for the jobs assigned to each machine. The machines are characterised by a limited sequence of colour groups and can equip additional components (e.g. embossing rollers and perforating rolls) to process jobs that require specific treatments. The process to equip a machine with an additional component or to clean a colour group takes a long time, with the effect of significantly raising the setup times. The aim is to minimise a weighted sum of total weighted tardiness and total setup time. The problem derives from the activities of an Italian food packaging company. To solve it, we developed a greedy randomised adaptive search procedure equipped with several local search procedures. The excellent performance of the algorithm is proved by extensive computational experiments on real-world instances, for which it produced good-quality solutions within a limited computing time. The algorithm is currently in use at the company to support their weekly scheduling decisions.
Journal: International Journal of Production Research
Pages: 7367-7385
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2148768
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2148768
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# input file: TPRS_A_2151661_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Min Zhang
Author-X-Name-First: Min
Author-X-Name-Last: Zhang
Author-Name: Keke Wei
Author-X-Name-First: Keke
Author-X-Name-Last: Wei
Author-Name: Shuguang He
Author-X-Name-First: Shuguang
Author-X-Name-Last: He
Author-Name: Zhen He
Author-X-Name-First: Zhen
Author-X-Name-Last: He
Author-Name: Wei Yan
Author-X-Name-First: Wei
Author-X-Name-Last: Yan
Title: Performance-based maintenance contract for mission-critical equipment considering spare parts inventory cost-sharing and suppliers' risk attitudes
Abstract: 
 In capital-intensive industries, it is becoming common practice for operators to outsource the mission-critical equipment maintenance to service suppliers. Performance-based contracts (PBCs) are widely used and the equipment availability is considered as an important performance indicator. In this paper, we studied a kind of mission-critical equipment that has a major component. When a failure occurred in the major component, it is replaced by a spare part and repaired offline. We consider suppliers' risk attitudes (i.e. risk-averse, risk-neutral, and risk-seeking) and the spare parts inventory cost-sharing between the supplier and the operator to design a PBC. Specifically, from the operator's perspective, we use a principal-agent analysis framework to construct a contract model which considers different suppliers' risk attitudes. We further explore the impact of inventory cost-sharing proportion on the operator's profit and contract parameters. The results show that it is more incentive to provide larger fixed payments and performance penalties (rewards) for risk-seeking (risk-averse) suppliers as the increasing of risk coefficient under no cost-sharing. Moreover, a large cost-sharing proportion has no impact on the operator's optimal profit, but affects the contract option of different risk attitudes' suppliers. Finally, a numeric example is used to illustrate the proposed models.
Journal: International Journal of Production Research
Pages: 7524-7539
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2151661
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2151661
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# input file: TPRS_A_2147238_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xing Wan
Author-X-Name-First: Xing
Author-X-Name-Last: Wan
Author-Name: Jing Chen
Author-X-Name-First: Jing
Author-X-Name-Last: Chen
Author-Name: Bintong Chen
Author-X-Name-First: Bintong
Author-X-Name-Last: Chen
Title: The manufacturer’s encroachment strategy in the presence of the retailer’s in-store service
Abstract: 
 We examine the manufacturer’s encroachment strategy in the supply chain in the presence of the retailer’s in-store service. The manufacturer has the option of encroachment with a direct channel, and the retailer has the option of providing in-store service. If the retailer decides to offer service, it sets the service level. We show that in the presence of in-store service, the manufacturer is less likely to encroach on the retail market than in the absence of in-store service. The retailer always prefers to provide in-store service. If the manufacturer decides to encroach, it will strategically use its direct channel with no sales as a threat to the retailer, independent of whether or not the retailer provides in-store service. The retailer can be better off with manufacturer encroachment, but it can be worse off when consumer sensitivity to in-store service is very low. We show that the retailer can strategically employ in-store service to deter the manufacturer’s encroachment when the consumer sensitivity to in-store service is sufficiently high.
Journal: International Journal of Production Research
Pages: 7263-7280
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2147238
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2147238
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# input file: TPRS_A_2147237_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Junbin Wang
Author-X-Name-First: Junbin
Author-X-Name-Last: Wang
Author-Name: Yangyan Shi
Author-X-Name-First: Yangyan
Author-X-Name-Last: Shi
Author-Name: Changping Zhao
Author-X-Name-First: Changping
Author-X-Name-Last: Zhao
Author-Name: V. G. Venkatesh
Author-X-Name-First: V. G.
Author-X-Name-Last: Venkatesh
Author-Name: Weiwei Chen
Author-X-Name-First: Weiwei
Author-X-Name-Last: Chen
Title: Impact of pricing leadership on blockchain data acquisition efforts in a circular supply chain
Abstract: 
 Motivated by the industrial observation of the increasing application of blockchain in the supply chain and its improvement in terms of consumer demand, this study examines the impact of investment decisions of blockchain data acquisition nodes upstream and downstream of the supply chain on firms’ product recycling and pricing, market demand, and profits. The influences of different pricing leadership (i.e. supplier-led vs. retailer-led) in a supply chain are also thoroughly investigated. First, the presence of a strong retailer dramatically reduces suppliers’ incentive to invest in blockchain. However, the supplier is still likely to invest more in a retailer-led supply chain than that in a supply chain led by itself under certain conditions; that is, the cost of blockchain is relatively small, or consumers’ sensitivity to blockchain or product recycling benefits is rather large. Second, the total number of blockchain data acquisition nodes, market demand, and supply chain profit in a retailer-led supply chain are higher than in a supplier-led supply chain. Finally, interestingly, the supplier will be better off in a retailer-led supply chain when the return effect of product recycling is relatively high, while the cost-effectiveness of blockchain investment is relatively low.
Journal: International Journal of Production Research
Pages: 7248-7262
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2147237
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2147237
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# input file: TPRS_A_2147236_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: To-Cheng Wang
Author-X-Name-First: To-Cheng
Author-X-Name-Last: Wang
Author-Name: Ming-Hung Shu
Author-X-Name-First: Ming-Hung
Author-X-Name-Last: Shu
Title: Development of an adaptive sampling system based on a process capability index with flexible switching mechanism
Abstract: 
 The quick-switch sampling system (QSS) and tightened-normal-tightened sampling system (TSS) are efficient schemes for dispositioning a series of lots. However, the QSS mechanism for switching decision rules is too simple to satisfy the requirements of suppliers and buyers. Conversely, the TSS is more flexible due to its adaptable switching mechanism. The TSS was recently developed based on process capability indices (PCIs) to help practitioners make more reliable and accurate decisions in practice. The existing PCI-based TSSs are the required sample-size type (TSS-n). However, the TSS-n requires a large sample size for the tightened inspection, which is costly and time-consuming. We propose the acceptance-benchmark type TSS (TSS-k) based on the most commonly used PCI, to improve the lot-disposition sampling efficiency. The TSS-k adjusts the acceptance benchmark instead of the sample size to constitute tightened and normal inspections. We investigated combinations of TSS-k switching mechanism parameters and provided managerial suggestions for practitioners. Compared with the existing TSS-n, the proposed TSS-k can reduce the average sample number by more than 60% and has superior discrimination power. Moreover, we developed a cloud-computing programme to calculate the optimal system design online. Finally, we illustrate an industrial case to demonstrate the applicability of the proposed TSS-k.
Journal: International Journal of Production Research
Pages: 7233-7247
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2147236
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2147236
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# input file: TPRS_A_2147234_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Min Cai
Author-X-Name-First: Min
Author-X-Name-Last: Cai
Author-Name: Rensheng Liang
Author-X-Name-First: Rensheng
Author-X-Name-Last: Liang
Author-Name: Xinggang Luo
Author-X-Name-First: Xinggang
Author-X-Name-Last: Luo
Author-Name: Chunlai Liu
Author-X-Name-First: Chunlai
Author-X-Name-Last: Liu
Title: Task allocation strategies considering task matching and ergonomics in the human-robot collaborative hybrid assembly cell
Abstract: 
 With the increased use of collaborative robots, a new production model of the human-robot collaborative hybrid assembly cell (HRCHAC) is becoming a new trend in customised production. Collaborative assembly between workers and robots in assembly cells can significantly increase productivity and improve the well-being of workers once the distribution of tasks and resources is optimised. This paper proposes a new integrated task allocation model to better utilise human-robot collaboration to increase productivity and improve worker well-being. The developed model enables the skills of both workers and robots to be fully utilised while ensuring economic efficiency and the effective protection of workers’ physiological and psychological health. First, the product assembly process is decomposed into several assembly tasks, and the characteristics of each task are analysed. Second, a bi-objective mixed-integer planning model is developed with the objectives of minimising unit product assembly time and maximising total task matching. The ergonomics-related objectives are considered in terms of both the physiological and psychological fatigue of the worker, and relevant constraints are established. An improved NSGA-II algorithm is developed to determine the final task allocation scheme. Finally, the proposed method is applied to a real industrial case to verify the effectiveness of the approach.
Journal: International Journal of Production Research
Pages: 7213-7232
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2147234
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2147234
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# input file: TPRS_A_2148009_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Xin Li
Author-X-Name-First: Xin
Author-X-Name-Last: Li
Author-Name: Jianbang Du
Author-X-Name-First: Jianbang
Author-X-Name-Last: Du
Author-Name: Pei Liu
Author-X-Name-First: Pei
Author-X-Name-Last: Liu
Author-Name: Chao Wang
Author-X-Name-First: Chao
Author-X-Name-Last: Wang
Author-Name: Xiaoqian Hu
Author-X-Name-First: Xiaoqian
Author-X-Name-Last: Hu
Author-Name: Pezhman Ghadimi
Author-X-Name-First: Pezhman
Author-X-Name-Last: Ghadimi
Title: Optimal choice of power battery joint recycling strategy for electric vehicle manufacturers under a deposit-refund system
Abstract: 
 In recent years, worldwide electric vehicle (EV) sales have experienced rapid growth, and recycling an enormous quantity of spent power batteries has become a challenge. This study aims to explore the optimal joint recycling strategy from the EV manufacturer’s perspective by using game theory-based models. The model investigates four kinds of joint recycling strategies: 1) nonalliance (NA) mode, 2) alliance with the power battery manufacturer (APBM) mode, 3) alliance with the third-party recycler (ATPR) mode, and 4) integrated alliance (IA) mode. The results show that: 1) A deposit-refund system can effectively increase the recycling rate. However, an excessive upfront disposal fee will reduce overall profits. 2) For the closed-loop supply chain, the optimal alliance mode depends on the intensity of recycling competition. When recycling competition is fierce, the IA mode is the best alliance mode. When recycling competition is weak, the NA mode is the optimal choice from the recycling rate perspective, and the APBM mode is the optimal choice from the total profit perspective. 3) For the EV manufacturer, the alliance in which its proportion of the extra joint profit is highest tends to be the optimal choice.
Journal: International Journal of Production Research
Pages: 7281-7301
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2148009
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2148009
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# input file: TPRS_A_2147232_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yajaira Cardona-Valdés
Author-X-Name-First: Yajaira
Author-X-Name-Last: Cardona-Valdés
Author-Name: Samuel Nucamendi-Guillén
Author-X-Name-First: Samuel
Author-X-Name-Last: Nucamendi-Guillén
Author-Name: Luis Ricardez-Sandoval
Author-X-Name-First: Luis
Author-X-Name-Last: Ricardez-Sandoval
Title: A capacitated lot-sizing problem in the industrial fashion sector under uncertainty: a conditional value-at-risk framework
Abstract: 
 In this study, we present a multi-product, multi-period inventory control problem under uncertainty in product demands that emerges in the fashion industry. A two-stage stochastic model is proposed to design a planning strategy where the total cost incurred by purchase orders, inventory and shortage is minimised. We incorporate the Conditional Value at Risk (CVaR) within the formulation to address exogenous uncertainty. An industrial case study involving a Mexican fashion retail company was considered to assess the performance of the two-stage stochastic model. Scenarios were considered using historical data provided by the company. A sensitivity analysis was also conducted on risk-aversion parameters to assess how the values of these parameters affect the behaviour of the proposed formulation. The results show that the proposed two-stage stochastic formulation is an efficient and practical approach to handle exogenous uncertainty in industrial-scale capacitated lot-sizing problems.
Journal: International Journal of Production Research
Pages: 7181-7197
Issue: 21
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2147232
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2147232
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# input file: TPRS_A_2166140_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jessica Ulmer
Author-X-Name-First: Jessica
Author-X-Name-Last: Ulmer
Author-Name: Sebastian Braun
Author-X-Name-First: Sebastian
Author-X-Name-Last: Braun
Author-Name: Chi-Tsun Cheng
Author-X-Name-First: Chi-Tsun
Author-X-Name-Last: Cheng
Author-Name: Steve Dowey
Author-X-Name-First: Steve
Author-X-Name-Last: Dowey
Author-Name: Jörg Wollert
Author-X-Name-First: Jörg
Author-X-Name-Last: Wollert
Title: A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation
Abstract: 
 Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.
Journal: International Journal of Production Research
Pages: 7760-7775
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2023.2166140
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2166140
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# input file: TPRS_A_2221344_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Etieno Enang
Author-X-Name-First: Etieno
Author-X-Name-Last: Enang
Author-Name: Mahdi Bashiri
Author-X-Name-First: Mahdi
Author-X-Name-Last: Bashiri
Author-Name: David Jarvis
Author-X-Name-First: David
Author-X-Name-Last: Jarvis
Title: Exploring the transition from techno centric industry 4.0 towards value centric industry 5.0: a systematic literature review
Abstract: 
 This systematic literature review synthesises the literature on human centric IN 4.0 and IN 5.0 while exploring driving forces behind the transition from technocentric IN 4.0 to value centric IN 5.0 using the principles of the multiple level perspective (MLP). Works that discuss contextual, regime and niche level factors which impact on the transition were explored. The Covid- 19 pandemic and Climate change are identified as key contextual, ‘Landscape’, factors impacting the transition while Trust, Mass personalisation and Autonomy are highlighted as key Regime factors. In terms of Niche innovations, Advanced Extended reality technologies, Cobots/ Advanced Robotics, and Advanced AI are often connected with landscape or regime issues. Drawing on MLP theory, the study demonstrates that the transition from IN 4.0 towards IN 5.0 is occurring through a reconfiguration pattern. The paper further emphasises aspects that both practitioners and academics need to be cognisant of in order to affect a transition from IN 4.0 to IN 5.0.
Journal: International Journal of Production Research
Pages: 7866-7902
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2023.2221344
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2221344
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# input file: TPRS_A_2153941_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Li Li
Author-X-Name-First: Li
Author-X-Name-Last: Li
Author-Name: Yanfei Kang
Author-X-Name-First: Yanfei
Author-X-Name-Last: Kang
Author-Name: Fotios Petropoulos
Author-X-Name-First: Fotios
Author-X-Name-Last: Petropoulos
Author-Name: Feng Li
Author-X-Name-First: Feng
Author-X-Name-Last: Li
Title: Feature-based intermittent demand forecast combinations: accuracy and inventory implications
Abstract: 
 Intermittent demand forecasting is a ubiquitous and challenging problem in production systems and supply chain management. In recent years, there has been a growing focus on developing forecasting approaches for intermittent demand from academic and practical perspectives. However, limited attention has been given to forecast combination methods, which have achieved competitive performance in forecasting fast-moving time series. The current study examines the empirical outcomes of some existing forecast combination methods and proposes a generalised feature-based framework for intermittent demand forecasting. The proposed framework has been shown to improve the accuracy of point and quantile forecasts based on two real data sets. Further, some analysis of features, forecasting pools and computational efficiency is also provided. The findings indicate the intelligibility and flexibility of the proposed approach in intermittent demand forecasting and offer insights regarding inventory decisions.
Journal: International Journal of Production Research
Pages: 7557-7572
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2153941
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2153941
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2161022_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yi Yang
Author-X-Name-First: Yi
Author-X-Name-Last: Yang
Author-Name: Chen Peng
Author-X-Name-First: Chen
Author-X-Name-Last: Peng
Title: A prediction-based supply chain recovery strategy under disruption risks
Abstract: 
 This paper proposes a prediction-based product change recovery strategy for the SC (supply chain) under long-term disruptions. A real-world case composed of multi-period planning and dynamic customer demand is considered. First, to forecast dynamic customer demand, a data-based demand predictive method with feedback errors is designed. Second, to schedule procurement and production in advance, based on the predicted demand, the selection of the supply portfolio is transformed into a bi-objective mixed integer programming problem incorporating product change. Furthermore, goods allocation and customer order fulfillment strategy is also designed to finish the transportation of goods and delivery of customer orders. To systematically synthesise and address the problems aforementioned, a three-stage heuristic method is further developed. Finally, a case study is presented to substantiate the reliability of the proposed strategy via an actual SC model of Dongsheng Electronics Co., Ltd. Based on the results obtained after one month, the proposed disruption recovery strategy can reduce the unit product cost and improve the service level, which outperforms the original method adopted by Dongsheng. Additionally, sensitivity analysis of unit product change cost is conducted to reveal the effect of different unit product change costs on SC performance.
Journal: International Journal of Production Research
Pages: 7670-7684
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2161022
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2161022
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# input file: TPRS_A_2246783_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Author-Name: Cecilia Berlin
Author-X-Name-First: Cecilia
Author-X-Name-Last: Berlin
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Title: Human-centric production and logistics system design and management: transitioning from Industry 4.0 to Industry 5.0
Abstract: 
 Industry 4.0 was presented more than a decade ago as the fourth industrial revolution, aiming to significantly raise the level of sophistication of interconnected technologies and thus increase manufacturing industries’ profits. However, because the technology-driven narrow focus of Industry 4.0 on performance and profit fails to explain how to increase prosperity for all the stakeholders involved, the European Commission has introduced the concept of Industry 5.0. This vision overcomes the weaknesses of Industry 4.0 by paying explicit attention to outcomes for humans in the system and establishing an environment to create human-centric, resilient, and sustainable systems. Considering these developments, this position paper and editorial introducing the special issue of the International Journal of Production Research elaborates on the transition from Industry 4.0 to 5.0 through 10 papers focusing on the human-centric pillar of Industry 5.0 and its impacts on production and logistics system design and management. This work presents guidance for a more systemic approach needed in future research: to include empirically grounded works and data-driven multimethod approaches that consider diversity in system operators and human factors demands holistically in order to incorporate ethical implications missing from Industry 4.0 – in the pursuit of Industry 5.0 systems.
Journal: International Journal of Production Research
Pages: 7749-7759
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2023.2246783
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2246783
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# input file: TPRS_A_2162145_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bilal Messaoudi
Author-X-Name-First: Bilal
Author-X-Name-Last: Messaoudi
Author-Name: Ammar Oulamara
Author-X-Name-First: Ammar
Author-X-Name-Last: Oulamara
Author-Name: Said Salhi
Author-X-Name-First: Said
Author-X-Name-Last: Salhi
Title: A decomposition approach for the periodic consistent vehicle routeing problem with an application in the cleaning sector
Abstract: 
 This study is inspired by a challenging logistic problem encountered in the cleaning service sector. The company wishes to solve the consistent vehicle routeing problem over a three-month planning horizon. The company has a heterogeneous vehicle fleet to guarantee multiple frequencies of visits to its customers. The objective is to minimise the number of vehicles used and the total distance travelled. This problem is a generalisation of the periodic vehicle routeing problem. We decompose the problem into two sub-problems, namely, the planning and routeing optimisation sub-problems. We construct a mathematical model for the former and a large neighbourhood search for the latter. We evaluate the performance of our approach using the results of the industrial partner and instances from the literature on problems that are closely related to our case study. Our approach is found to be effective and robust. Our results outperform the existing company's plan in terms of solution quality, and staff convenience, and speed. We also discovered new best solutions on some of the instances from the literature.
Journal: International Journal of Production Research
Pages: 7727-7748
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2162145
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2162145
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# input file: TPRS_A_2160502_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Rubing Chen
Author-X-Name-First: Rubing
Author-X-Name-Last: Chen
Author-Name: Yuan Gao
Author-X-Name-First: Yuan
Author-X-Name-Last: Gao
Author-Name: Zhichao Geng
Author-X-Name-First: Zhichao
Author-X-Name-Last: Geng
Author-Name: Jinjiang Yuan
Author-X-Name-First: Jinjiang
Author-X-Name-Last: Yuan
Title: Revisit the scheduling problem with assignable or generalized due dates to minimize total weighted late work
Abstract: 
 We revisit the single-machine scheduling for minimising the total weighted late work with assignable due dates (ADD-scheduling) and generalised due dates (GDD-scheduling). In particular, we consider the following three problems: (i) the GDD-scheduling problem for minimising the total weighted late work, (ii) the ADD-scheduling problem for minimising the total weighted late work, and (iii) the ADD-scheduling problem for minimising the total late work. In the literature, the above three problems are proved to be NP-hard, but their exact complexity (unary NP-hardness or pseudo-polynomial-time solvability) are unknown. In this paper, we address these open problems by showing that the first two problems are unary NP-hard and the third problem admits pseudo-polynomial-time algorithms. For the third problem, we also present a 2-approximation solution and a fully polynomial-time approximation scheme. Computational experiments show that our algorithms and solutions are efficient. When the jobs have identical processing times, we further present more efficient polynomial-time algorithms.
Journal: International Journal of Production Research
Pages: 7630-7648
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2160502
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2160502
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# input file: TPRS_A_2153942_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Huosong Xia
Author-X-Name-First: Huosong
Author-X-Name-Last: Xia
Author-Name: Yuan Wang
Author-X-Name-First: Yuan
Author-X-Name-Last: Wang
Author-Name: Sajjad Jasimuddin
Author-X-Name-First: Sajjad
Author-X-Name-Last: Jasimuddin
Author-Name: Justin Zuopeng Zhang
Author-X-Name-First: Justin Zuopeng
Author-X-Name-Last: Zhang
Author-Name: Andrew Thomas
Author-X-Name-First: Andrew
Author-X-Name-Last: Thomas
Title: A big-data-driven matching model based on deep reinforcement learning for cotton blending
Abstract: 
 China’s cotton textile industry is undergoing a critical period of digital transformation and upgrading to cope with pressure and challenges such as rising labour costs and large fluctuations in raw material prices. Developing a cost-based competitive advantage while ensuring a high-quality product is a critical problem in intelligent manufacturing. From the perspective of big data and reinforcement learning, the authors designed a reward value combining transaction, interaction, and measurement data by combining the reward mechanism and Markov decision for a combination of different raw materials in the intelligent textile factory. The authors propose a big data-driven application to the depth of the reinforcement learning to solve problems and build a big-data-driven matching model based on deep reinforcement learning to cotton matching. The offline strategy is designed to construct a memory bank and neural network, and the incentive mechanism of reinforcement learning is used to iterate the optimal yarn matching scheme to achieve the goal of intelligent cotton matching. The results show that deep reinforcement learning can be optimised using big data on the premise of quality assurance. Manufacturing costs can be optimised using a matching model of big data based on a deep reinforcement learning model.
Journal: International Journal of Production Research
Pages: 7573-7591
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2153942
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2153942
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# input file: TPRS_A_2160503_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jing Qin
Author-X-Name-First: Jing
Author-X-Name-Last: Qin
Author-Name: Desheng Dash Wu
Author-X-Name-First: Desheng
Author-X-Name-Last: Dash Wu
Author-Name: Kun Qin
Author-X-Name-First: Kun
Author-X-Name-Last: Qin
Author-Name: Yaoxiang Nie
Author-X-Name-First: Yaoxiang
Author-X-Name-Last: Nie
Title: Financing the retailers with default probabilities: capital constrained supplier vs. bank
Abstract: 
 In this paper, we examine a supply chain consisting of a supplier with capital constraint and multiple retailers with no working capital. The retailers can get either trade credit from the supplier or loan from banks. All the retailers are differentiated by their credit scores, which measure the possibility that they default. We show that when the retailer's default probability is high compared with the marginal cost, the retailer cannot get financial support. If the retailers only get money from banks, the more reliable a retailer is, the higher the wholesale price the supplier may charge him. We also find out that the supplier has the motivation to provide trade credit even when the retailers can get money from banks. And no matter where the retailers get money from, when the initial capital is a little insufficient, the supplier will reduce the quantity of the products provided to all retailers. As the initial capital becomes less, the supplier will cut off all the supply to the lowest-score retailer first no matter whether the supplier undertakes the default risk or not. In other words, when the retailers are heterogeneous, for supplier, it is not always the more retailers, the better.
Journal: International Journal of Production Research
Pages: 7649-7669
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2160503
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2160503
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# input file: TPRS_A_2240912_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jéssica de Assis Dornelles
Author-X-Name-First: Jéssica de Assis
Author-X-Name-Last: Dornelles
Author-Name: Néstor F. Ayala
Author-X-Name-First: Néstor F.
Author-X-Name-Last: Ayala
Author-Name: Alejandro G. Frank
Author-X-Name-First: Alejandro G.
Author-X-Name-Last: Frank
Title: Collaborative or substitutive robots? Effects on workers’ skills in manufacturing activities
Abstract: 
 Collaborative robots (cobots) are a type of Industry 4.0 technology designed to support manufacturing workers and create smart working environments (also called as Industry 5.0). However, little is known about how the use of cobots shapes workers’ skills. We analyse this in four types of human-cobot interaction: coexistence, synchronism, cooperation, and collaboration. We examine the implementation of cobots by a leading global provider using a qualitative research based on: (i) analysis of reports regarding the implementation of 200 cobots in 138 companies, (ii) interviews with the team and customers, (iii) six-month follow-up of cobot implementation in a manufacturing plant, and (iv) interviews with two cobot competitors. Our findings demonstrate how each type of human-cobot interaction influences workers’ skills in various manufacturing activities. We observe that most companies are in early stages of implementation, focusing on worker substitution. However, we identify a range of effects, including deskilling or reskilling, depending on the type of manufacturing activity analysed. The upskilling effect is particularly evident in the most advanced types of human-cobot interaction, regardless of the company's size. As a main contribution, this paper sheds light on how companies can enhance workers’ skills through other levels of interaction between workers and cobots.
Journal: International Journal of Production Research
Pages: 7922-7955
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2023.2240912
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2240912
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# input file: TPRS_A_2154402_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Simen T. Vadseth
Author-X-Name-First: Simen T.
Author-X-Name-Last: Vadseth
Author-Name: Henrik Andersson
Author-X-Name-First: Henrik
Author-X-Name-Last: Andersson
Author-Name: Magnus Stålhane
Author-X-Name-First: Magnus
Author-X-Name-Last: Stålhane
Author-Name: Masoud Chitsaz
Author-X-Name-First: Masoud
Author-X-Name-Last: Chitsaz
Title: A multi-start route improving matheuristic for the production routeing problem
Abstract: 
 This paper considers the multi-vehicle production routeing problem with a maximum-level replenishment policy. This is a well-established problem within vendor managed inventory where production, inventory and routeing decisions are made simultaneously. We present a novel method to solve the problem that outperforms existing methods both in terms of solution gaps and the number of best-known solutions. The proposed matheuristic is tested on three different sets of benchmark instances consisting of 1218 instances and finds or improves the best-known solution for 632 of them. For the remaining instances, the matheuristic is less than 2.5% from the best-known solutions. The method is particularly proficient on large instances and is also efficient for the inventory routeing problem. The success of the method is largely due to its improvement phase where a novel path-flow-inspired mathematical model is introduced. Here, a route set obtained from the current solution is used and retailers can be simultaneously inserted and removed from a route, making the method flexible even when a small route set is used. In addition, we introduce a new production subproblem that approximates the costs of using a vehicle instead of approximating the costs of visiting a retailer, making it very fast to solve.
Journal: International Journal of Production Research
Pages: 7608-7629
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2154402
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2154402
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# input file: TPRS_A_2153943_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme Luz
Author-X-Name-Last: Tortorella
Author-Name: Michel J. Anzanello
Author-X-Name-First: Michel J.
Author-X-Name-Last: Anzanello
Author-Name: Flavio S. Fogliatto
Author-X-Name-First: Flavio S.
Author-X-Name-Last: Fogliatto
Author-Name: Jiju Antony
Author-X-Name-First: Jiju
Author-X-Name-Last: Antony
Author-Name: Daniel Nascimento
Author-X-Name-First: Daniel
Author-X-Name-Last: Nascimento
Title: Effect of Industry 4.0 technologies adoption on the learning process of workers in a quality inspection operation
Abstract: 
 This study examines the effect of Industry 4.0 (I4.0) technologies on the learning process of operators. We collected data from the training of new operators in a quality inspection workstation. Two distinct scenarios were considered: before and after the adoption of I4.0 technologies. Data from 10 operators were collected in each scenario; the quality inspection cycle was repeated by each operator 30 consecutive times. A 2-parameter hyperbolic learning curve model was used to assess the learning process in the two groups. Results indicated that operators supported by I4.0 technologies had a significantly higher learning rate than those performing the same tasks without I4.0 support. No significant difference was found in the final performance level between groups. Our study bridges a theoretical gap in the relationship between I4.0 and learning by directly comparing the effect of digital support on the training of new employees in a manufacturing environment. We also offer arguments to support managerial decisions with regards to I4.0 adopti-on at an operational level. That allows organisations to prioritise their digitalisation efforts so that the training of operators in workstations can be expedited.
Journal: International Journal of Production Research
Pages: 7592-7607
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2153943
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2153943
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# input file: TPRS_A_2183343_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Alexandros Pasparakis
Author-X-Name-First: Alexandros
Author-X-Name-Last: Pasparakis
Author-Name: Jelle De Vries
Author-X-Name-First: Jelle
Author-X-Name-Last: De Vries
Author-Name: René De Koster
Author-X-Name-First: René
Author-X-Name-Last: De Koster
Title: Assessing the impact of human–robot collaborative order picking systems on warehouse workers
Abstract: 
 Robotisation is increasing in warehouse operations, but human employment continues to be relevant. Traditionally manual activities, such as order picking, are being re-designed into collaborative human–robot tasks. This trend exemplifies the transition towards a human-centric Industry 5.0, focusing on synergy instead of seeking human replacement. However, human workers are increasingly hard to recruit and retain. We contribute to the underrepresented literature on human factors within the domain of operations and production management research and investigate the deployment of robotic technologies alongside human workers in a sustainable way. With a unique real-effort experiment, we investigate how the manipulation of picker’s experienced levels of autonomy affects their job satisfaction and core self-evaluations, two key behavioural outcomes that determine employee turnover intentions. We establish that the introduction of human–robot collaboration positively affects job satisfaction for the contrasting collaboration dynamics of (i) gaining control (the human leading the robot) and (ii) ceding control (the human following the robot). This positive effect is larger when the human is following the robot. We additionally find that following the robot positively affects pickers’ self-esteem and that self-efficacy related to human–robot interaction benefits from the introduction of collaborative robotics, regardless of the setup dynamics.
Journal: International Journal of Production Research
Pages: 7776-7790
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2023.2183343
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2183343
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# input file: TPRS_A_2153185_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mohammed-Amine Abdous
Author-X-Name-First: Mohammed-Amine
Author-X-Name-Last: Abdous
Author-Name: Xavier Delorme
Author-X-Name-First: Xavier
Author-X-Name-Last: Delorme
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Sandrine Berger-Douce
Author-X-Name-First: Sandrine
Author-X-Name-Last: Berger-Douce
Title: Multi-objective collaborative assembly line design problem with the optimisation of ergonomics and economics
Abstract: 
 Manufacturing systems are socio-technical systems, with explicit interactions between humans and technologies in shared workspaces. These shared workspaces could also be called hybrid collaborative manufacturing systems, which involve workers as well as technological equipment and combine the benefits of human workers and new Industry 4.0 technologies, such systems are particularly useful in a context requiring flexibility and adaptability. Furthermore, the new Industry 5.0 approach has the objective to shift toward more human-centric and resilient manufacturing systems. The key problems to solve in the design of collaborative manufacturing systems are the combinatorial assembly line balancing problem and the equipment selection problem. An efficient and sustainable line requires a cost-effective choice of equipment while improving the ergonomics and the safety of workers. Both decisions of balancing workload and the assignment of equipment impact the ergonomics of a collaborative system and present conflicting criteria. To this end, we propose a multi-objective approach, the objectives are the optimisation of the investment costs and the ergonomics with a fatigue and recovery criterion. We propose to linearise the fatigue and recovery to formulate a new Mixed Integer Linear Programming formulation. We developed an exact multi-objective solving algorithm based on the ϵ-constraint to obtain the trade-off between these objectives. We conducted numerical experiments with different instances from the literature with promising results for instances with up to 45 operations. Finally, we discuss insightful managerial conclusions and future research perspectives.
Journal: International Journal of Production Research
Pages: 7830-7845
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2153185
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2153185
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# input file: TPRS_A_2161113_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Latéfa Ghomri
Author-X-Name-First: Latéfa
Author-X-Name-Last: Ghomri
Author-Name: Ali Rimouche
Author-X-Name-First: Ali
Author-X-Name-Last: Rimouche
Title: Modelling and optimisation of single-cycle time for mobile rack AS/RS
Abstract: 
 This paper deals with mobile-rack automated storage/retrieval systems (AS/RS) that are a particular physical configuration of unit-deep AS/RS, i.e. the class of systems where each cell is designed to contain a single load. There are two main contributions in this paper: the first one is the analytical modelling of the average single-cycle time for mobile-rack AS/RS. The approach adopted for modelling is based on a continuous approximation, which is not recent, however, the approach proposed here for the transition from the discrete to the continuous models is different from those used previously in the literature. In a certain way, the multi-aisle and unit-load configurations can be seen as special cases of the mobile-rack configuration. This allows to deduce analytical models for the average single-cycle time for these two configurations from the one developed for mobile rack. The second main contribution of this paper is to find the dimensions of the AS/RS that minimise the average single-cycle time. The optimisation has been studied formally for the multi-aisle and unit-load configurations, and numerically for the mobile-rack configuration.
Journal: International Journal of Production Research
Pages: 7685-7706
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2161113
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2161113
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# input file: TPRS_A_2175310_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Nils Thylén
Author-X-Name-First: Nils
Author-X-Name-Last: Thylén
Author-Name: Carl Wänström
Author-X-Name-First: Carl
Author-X-Name-Last: Wänström
Author-Name: Robin Hanson
Author-X-Name-First: Robin
Author-X-Name-Last: Hanson
Title: Challenges in introducing automated guided vehicles in a production facility – interactions between human, technology, and organisation
Abstract: 
 Previous research on automated guided vehicles (AGVs) and Industry 4.0 has mainly focused on technical aspects, while the humans who work with AGVs as well as the influences on the organisation have received limited attention. This paper aims to explore human- and organisation-related challenges in the introduction of AGVs in production facilities. Two cases are examined and analysed using the Human, Technology, and Organisation (HTO) model, which highlights the interactions between the three subsystems: human, technology, and organisation. The paper shows that several human- and organisation-related challenges arise when introducing AGVs, such as supporting the AGVs with new work procedures for managing AGV errors, determining what different operators need to know about AGVs, and developing acceptance among employees. The identified challenges complement the technical focus in previous research. Actions are proposed to facilitate the introduction of AGVs to avoid or manage the identified challenges. The findings of this study can help managers involved in the introduction of AGVs to consider human- and organisation-related aspects to improve AGV performance and employee well-being.
Journal: International Journal of Production Research
Pages: 7809-7829
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2023.2175310
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2175310
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# input file: TPRS_A_2154403_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bas van Oudenhoven
Author-X-Name-First: Bas
Author-X-Name-Last: van Oudenhoven
Author-Name: Philippe Van de Calseyde
Author-X-Name-First: Philippe
Author-X-Name-Last: Van de Calseyde
Author-Name: Rob Basten
Author-X-Name-First: Rob
Author-X-Name-Last: Basten
Author-Name: Evangelia Demerouti
Author-X-Name-First: Evangelia
Author-X-Name-Last: Demerouti
Title: Predictive maintenance for industry 5.0: behavioural inquiries from a work system perspective
Abstract: 
 Predictive Maintenance (PdM) solutions assist decision-makers by predicting equipment health and scheduling maintenance actions, but their implementation in industry remains problematic. Specifically, prior research repeatedly indicates that decision-makers often refuse to adopt the data-driven, system-generated advice in their working procedures. In this paper, we address these acceptance issues by studying how PdM implementation changes the nature of decision-makers’ work and how these changes affect their acceptance of PdM systems. We build on the human-centric Smith-Carayon Work System model to synthesise literature from research areas where system acceptance has been explored in more detail. Consequently, we expand the maintenance literature by investigating the human-, task-, and organisational characteristics of PdM implementation. Following the literature review, we distil ten propositions regarding decision-making behaviour in PdM settings. Next, we verify each proposition’s relevance through in-depth interviews with experts from both academia and industry. Based on the propositions and interviews, we identify four factors that facilitate PdM adoption: trust between decision-maker and model (maker), control in the decision-making process, availability of sufficient cognitive resources, and proper organisational allocation of decision-making. Our results contribute to a fundamental understanding of acceptance behaviour in a PdM context and provide recommendations to increase the effectiveness of PdM implementations.
Journal: International Journal of Production Research
Pages: 7846-7865
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2154403
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2154403
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# input file: TPRS_A_2232469_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Vivek Vijayakumar
Author-X-Name-First: Vivek
Author-X-Name-Last: Vijayakumar
Author-Name: Ahmad Sobhani
Author-X-Name-First: Ahmad
Author-X-Name-Last: Sobhani
Title: Performance optimisation of pick and transport robot in a picker to parts order picking system: a human-centric approach
Abstract: 
 Picker to parts order picking (OP) systems are one of the most labour-intensive warehouse operations, accounting for 55% of warehouse expenses in the e-commerce industry. For this reason, the e-commerce industry has invested in fully automated and robotised warehouses. However, these warehouse solutions are very expensive. Furthermore, with the advent of Industry 5.0 with a human-centric focus, the OP system's automation should be designed and implemented in ways to improve the working conditions of the order pickers rather than replacing them completely. A pick and transport robot (PTR) is a solution for OP systems which is compatible with Industry 5.0. An example of such a solution is Grab™ by SOLWR. Previous studies have barely investigated the human factor effects of using PTRs in OP systems while optimising the performance of the systems. This research develops a mathematical model to optimise the performance of a picker to parts OP system using PTRs in terms of productivity, quality, and the well-being of the order pickers. The developed model is tested by using data from a case company. The results of this study support managerial decisions by achieving a better knowledge of how to set up such PTR solutions.
Journal: International Journal of Production Research
Pages: 7791-7808
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2023.2232469
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2232469
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# input file: TPRS_A_2195957_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jaakko Peltokorpi
Author-X-Name-First: Jaakko
Author-X-Name-Last: Peltokorpi
Author-Name: Steven Hoedt
Author-X-Name-First: Steven
Author-X-Name-Last: Hoedt
Author-Name: Thomas Colman
Author-X-Name-First: Thomas
Author-X-Name-Last: Colman
Author-Name: Kim Rutten
Author-X-Name-First: Kim
Author-X-Name-Last: Rutten
Author-Name: El-Houssaine Aghezzaf
Author-X-Name-First: El-Houssaine
Author-X-Name-Last: Aghezzaf
Author-Name: Johannes Cottyn
Author-X-Name-First: Johannes
Author-X-Name-Last: Cottyn
Title: Manual assembly learning, disability, and instructions: an industrial experiment
Abstract: 
 Cognitive assistance systems help people with learning disabilities to increase their skills and consequently their employment opportunities in the regular labour market. Research on advanced work instructions has encouraged training disabled workers in cognitively demanding production tasks, especially manual assembly. However, studies lack evidence on the effect of repetition or work cycle alongside the form of instruction and type of disability. This paper addresses this gap and reports on an experiment conducted at a sheltered workplace. Four forms of instruction (paper-based, animations, projection, adaptive projection) were tested to assist operators with three types of disability (illiterate, psychosocial, cognitive) with a manual assembly task. The results show that projection enhances the first assembly cycle. Challenging operators by filtering the content of the instruction with increased experience leads to greater independence and a better understanding of their tasks. However, adaptive instructions can form a barrier for those operators who are most dependent on mentor support. The form of instruction should thus be considered carefully for each operator as their adaptation to changes and cognitive assistance systems varies. The results are discussed in light of the Industry 5.0 human-centric and socially sustainable production agenda with managerial and research implications and future research priorities.
Journal: International Journal of Production Research
Pages: 7903-7921
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2023.2195957
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2195957
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# input file: TPRS_A_2162144_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Eleftherios G. Manousakis
Author-X-Name-First: Eleftherios G.
Author-X-Name-Last: Manousakis
Author-Name: Christos D. Tarantilis
Author-X-Name-First: Christos D.
Author-X-Name-Last: Tarantilis
Author-Name: Emmanouil E. Zachariadis
Author-X-Name-First: Emmanouil E.
Author-X-Name-Last: Zachariadis
Title: The cyclic production routing problem
Abstract: 
 This paper introduces the Cyclic Production Routing Problem (CPRP). The CPRP is an extension of the well-known NP-hard Production Routing Problem (PRP), which is a hard-to-solve combinatorial optimisation problem with numerous practical applications in the field of freight transportation, logistics and supply chain management. Under the PRP setting, a manufacturer is responsible for determining production decisions, as well as the timing and quantity of replenishment services offered to a set of geographically dispersed customers over a multi-period time horizon. The problem calls for jointly optimising the production, inventory, distribution and routing decisions. In this paper, the basic PRP model is modified to generate repeatable cyclic production and delivery schedules. A two-commodity flow formulation is proposed along with valid inequalities. Extensive comparisons between the basic PRP and the proposed cyclic variant on well-known benchmark instances are provided. The new variant is significantly harder to solve, especially when the vehicle fleet is limited. From a managerial perspective, the generation of cyclic production-routing schedules significantly increases all costs, whereas the number of vehicle routes required to implement a cyclic schedule is higher.
Journal: International Journal of Production Research
Pages: 7707-7726
Issue: 22
Volume: 61
Year: 2023
Month: 11
X-DOI: 10.1080/00207543.2022.2162144
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2162144
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# input file: TPRS_A_2165190_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Truong Van Nguyen
Author-X-Name-First: Truong
Author-X-Name-Last: Van Nguyen
Author-Name: Hiep Cong Pham
Author-X-Name-First: Hiep
Author-X-Name-Last: Cong Pham
Author-Name: Minh Nhat Nguyen
Author-X-Name-First: Minh
Author-X-Name-Last: Nhat Nguyen
Author-Name: Li Zhou
Author-X-Name-First: Li
Author-X-Name-Last: Zhou
Author-Name: Mohammadreza Akbari
Author-X-Name-First: Mohammadreza
Author-X-Name-Last: Akbari
Title: Data-driven review of blockchain applications in supply chain management: key research themes and future directions
Abstract: 
 Blockchain (BC) applications in supply chain management (SCM) have recently received extensive attention. It is important to synthesise the extant literature on the field to identify key research themes and navigate potential future directions. This study thus develops an efficient, scalable data-driven review approach that uses text mining and Latent Dirichlet Allocation (LDA)-based topic modelling for automatic content analysis of full-text documents. Our method overcomes the drawbacks of traditional systematic literature reviews using either manual coding or bibliographic analysis for article classifications, which are highly time-consuming and biased when dealing with large amounts of text. 108 papers published between 2017 and 2022 were analysed which identified 10 key research themes, including revenue management, sustainability, traceability, manufacturing system, scheduling in cloud manufacturing, healthcare SCM, anti-counterfeit system, logistics and transportation, system architecture development, and food & agriculture SC. Five future directions are then suggested, including (1) integration of BC and other emerging technologies for global and scalable SCM, (2) crypto-X applications in SCM, (3) BC-enabled closed-loop SCM, (4) the environmental and social impacts of BC-based SCM and (5) decentralised autonomous organisations in SCM.
Journal: International Journal of Production Research
Pages: 8213-8235
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2023.2165190
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2165190
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# input file: TPRS_A_2164375_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Chunguang Bai
Author-X-Name-First: Chunguang
Author-X-Name-Last: Bai
Author-Name: Hua Zhou
Author-X-Name-First: Hua
Author-X-Name-Last: Zhou
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: Evaluating Industry 4.0 technology and sustainable development goals – a social perspective
Abstract: 
 Organisations are having difficulty in determining and integrating Industry 4.0 technologies (I4.0T) to improve social dimensions of sustainable performance. We address this issue by showing how to identify the impact degree and path of I4.0T using the United Nations sustainable development goals (SDGs). First, we identify the SDGs associated with I4.0 and establish an evaluation framework. Second, we introduce an evaluation method that integrates hesitant fuzzy sets, rough sets, decision-making, trial evaluation laboratory (DEMATEL) and interpretative structural modelling methods to identify the impact degree and path of I4.0T on SDGs. Third, we confirm the effectiveness of our framework and method using secondary case data from World Economic Forum reports. The case results show that I4.0T have varying direct and indirect influences on SDGs. Policy makers should consider that ‘Big Data and Analytics’ and ‘Cloud Computing’ are central I4.0T that link other technologies and SDGs. The prioritisation of I4.0T can lead to contributions to addressing ‘Responsible consumption and production’ and indirectly improve SDGs. The findings set an initial stage to help sequence investment in various technologies depending on SDGs. We identify sequential paths that can aid in planning for and investing in adopting I4.0T to better achieve SDGs.
Journal: International Journal of Production Research
Pages: 8094-8114
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2164375
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2164375
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# input file: TPRS_A_2162997_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Guillaume Dessevre
Author-X-Name-First: Guillaume
Author-X-Name-Last: Dessevre
Author-Name: Jacques Lamothe
Author-X-Name-First: Jacques
Author-X-Name-Last: Lamothe
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Author-Name: Maha Ben Ali
Author-X-Name-First: Maha Ben
Author-X-Name-Last: Ali
Author-Name: Pierre Baptiste
Author-X-Name-First: Pierre
Author-X-Name-Last: Baptiste
Author-Name: Vincent Pomponne
Author-X-Name-First: Vincent
Author-X-Name-Last: Pomponne
Title: Comparison of pull management policies for a divergent process with DDMRP buffers: an industrial case study
Abstract: 
 Production planning and scheduling for companies with divergent processes, where a single component can be transformed into several finished products, are challenging as planners might face material misallocation issues. In this paper, we address the problem of managing a divergent process with DDMRP stock buffers, where different finished products are bottled with the same component having a fixed batch size. An allocation decision needs to be made to determine the quantities of finished products to be bottled. This study is motivated by a real-life problem faced by a dermo-cosmetic company. We compare and analyze by simulation nine different policies triggering allocation decisions. The first policy is the classic DDMRP rule, while the others are new policies, including a virtual buffer of a generic finished product and ConWIP loops, delaying the allocation decision. Our results show that the policy combining the classic DDMRP rule and a ConWIP loop surrounding a part of the process reduces the work-in-process by 34% compared to the classic DDMRP while ensuring high customer service rates and control of flow times.
Journal: International Journal of Production Research
Pages: 8022-8042
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2162997
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2162997
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# input file: TPRS_A_2104181_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Pratik Maheshwari
Author-X-Name-First: Pratik
Author-X-Name-Last: Maheshwari
Author-Name: Sachin Kamble
Author-X-Name-First: Sachin
Author-X-Name-Last: Kamble
Author-Name: Amine Belhadi
Author-X-Name-First: Amine
Author-X-Name-Last: Belhadi
Author-Name: Venkatesh Mani
Author-X-Name-First: Venkatesh
Author-X-Name-Last: Mani
Author-Name: Ashok Pundir
Author-X-Name-First: Ashok
Author-X-Name-Last: Pundir
Title: Digital twin implementation for performance improvement in process industries- A case study of food processing company
Abstract: 
 In recent years, the emerging Digital Twin (DT) paradigm under Industry 4.0 has been attracting more attention from both practitioners and academia due to its dynamic capabilities. Most DT studies are theoretical and deal with hypothetical analysis, whereas fewer studies are available on real-life empirical cases. Due to dynamic problem-solving capabilities, DT technologies are widely used in performance improvement analysis in food processing companies (FPC) despite limited implication’s for business strategies. Our study incorporates the DT technologies with an implementation case study on FPC and accomplishes the real-life problem of the food processing company (FPC). Moreover, the proposed DT research framework demonstrates the various DT implementation stages, such as strategic mapping and physical-virtual space replica, with rigorous analysis. The results show that DT enhances the existing system’s machine availability, allocation efficiency, technical efficiency, worker efficiency, utilization rate, effectiveness, step ratio, and throughput rate. The proposed physical-virtual interface model is executed using AnyLogic software with JAVA-enabled programming.
Journal: International Journal of Production Research
Pages: 8343-8365
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2104181
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2104181
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# input file: TPRS_A_2164088_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Liang Chen
Author-X-Name-First: Liang
Author-X-Name-Last: Chen
Author-Name: Liuxing Chu
Author-X-Name-First: Liuxing
Author-X-Name-Last: Chu
Author-Name: Cuicui Ge
Author-X-Name-First: Cuicui
Author-X-Name-Last: Ge
Author-Name: Yueyuan Zhang
Author-X-Name-First: Yueyuan
Author-X-Name-Last: Zhang
Title: A general tool-based multi-product model for high-mixed production in semiconductor manufacturing
Abstract: 
 Concerning the high-mixed nature in modern semiconductor manufacturing, the original ‘tool-based’ exponentially weighted moving average (EWMA) controller is proved to be unstable when the plant-model mismatches are diverse for different products, leading to large variations and lots of wastes. Hence, this paper proposes a general multi-product model for ‘tool-based’ EWMA control. The core of the model lies in the algorithm on how to estimate the noise disturbance accurately, i.e. the noise is considered as the sum of the following two parts: the estimated noise after the thread has been processed in the last cycle and the cumulative noise during the period when the thread is not on production between the two cycles. In this way, the production for a particular thread is isolated from that of others to avoid instability existing in the traditional tool-based EWMA control. Superiorities of the proposed model are demonstrated through theoretical analysis, simulation experiment and industrial case study.
Journal: International Journal of Production Research
Pages: 8062-8079
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2164088
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2164088
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# input file: TPRS_A_2164628_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ge Zheng
Author-X-Name-First: Ge
Author-X-Name-Last: Zheng
Author-Name: Lingxuan Kong
Author-X-Name-First: Lingxuan
Author-X-Name-Last: Kong
Author-Name: Alexandra Brintrup
Author-X-Name-First: Alexandra
Author-X-Name-Last: Brintrup
Title: Federated machine learning for privacy preserving, collective supply chain risk prediction
Abstract: 
 The use of Artificial Intelligence (AI) for predicting supply chain risk has gained popularity. However, proposed approaches are based on the premise that organisations act alone, rather than a collective when predicting risk, despite the interconnected nature of supply chains. This yields a problem: organisations that have inadequate datasets cannot predict risk. While data-sharing has been proposed to evaluate risk, in practice this does not happen due to privacy concerns. We propose a federated learning approach for collective risk prediction without the risk of data exposure. We ask: Can organisations who have inadequate datasets tap into collective knowledge? This raises a second question: Under what circumstances would collective risk prediction be beneficial? We present an empirical case study where buyers predict order delays from their shared suppliers before and after Covid-19. Results show that federated learning can indeed help supply chain members predict risk effectively, especially for buyers with limited datasets. Training data-imbalance, disruptions, and algorithm choice are significant factors in the efficacy of this approach. Interestingly, data-sharing or collective risk prediction is not always the best choice for buyers with disproportionately larger order-books. We thus call for further research on on local and collective learning paradigms in supply chains.
Journal: International Journal of Production Research
Pages: 8115-8132
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2164628
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2164628
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# input file: TPRS_A_2032860_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jianyu Long
Author-X-Name-First: Jianyu
Author-X-Name-Last: Long
Author-Name: Yibin Chen
Author-X-Name-First: Yibin
Author-X-Name-Last: Chen
Author-Name: Zhe Yang
Author-X-Name-First: Zhe
Author-X-Name-Last: Yang
Author-Name: Yunwei Huang
Author-X-Name-First: Yunwei
Author-X-Name-Last: Huang
Author-Name: Chuan Li
Author-X-Name-First: Chuan
Author-X-Name-Last: Li
Title: A novel self-training semi-supervised deep learning approach for machinery fault diagnosis
Abstract: 
 Fault diagnosis is an indispensable basis for the collaborative maintenance in prognostic and health management. Most of existing data-driven fault diagnosis approaches are designed in the framework of supervised learning, which requires a large number of labelled samples. In this paper, a novel self-training semi-supervised deep learning (SSDL) approach is proposed to train a fault diagnosis model together with few labelled and abundant unlabelled samples. The addressed SSDL approach is realised by initialising a stacked sparse auto-encoder classifier using the labelled samples, and subsequently updating the classifier via sampling a few candidates with most reliable pseudo labels from the unlabelled samples step by step. Unlike the commonly used static sampling strategy in existing self-training semi-supervised frameworks, a gradually exploiting mechanism is proposed in SSDL to increase the number of selected pseudo-labelled candidates gradually. In addition, instead of using the prediction accuracy as the confidence estimation for pseudo-labels, a distance-based sampling criterion is designed to assign the label for each unlabelled sample by its nearest labelled sample based on their Euclidean distances in the deep feature space. The experimental results show that the proposed SSDL approach can achieve good prediction accuracy compared to other self-training semi-supervised learning algorithms.
Journal: International Journal of Production Research
Pages: 8238-8251
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2032860
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2032860
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# input file: TPRS_A_2162618_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hassan Dehghan Shoorkand
Author-X-Name-First: Hassan
Author-X-Name-Last: Dehghan Shoorkand
Author-Name: Mustapha Nourelfath
Author-X-Name-First: Mustapha
Author-X-Name-Last: Nourelfath
Author-Name: Adnène Hajji
Author-X-Name-First: Adnène
Author-X-Name-Last: Hajji
Title: A deep learning approach for integrated production planning and predictive maintenance
Abstract: 
 This paper considers a multi-period multi-product capacitated lot-sizing problem. It develops an integrated predictive maintenance and production planning framework using deep learning and mathematical programming. The objective is to minimise the sum of maintenance, setup, holding, backorder, and production costs, while satisfying the demand for all products over the horizon under consideration. Based on a rolling horizon approach, the model dynamically integrates data-driven predictive maintenance and production planning. The used maintenance policy includes replacements and minimal repairs that are considered as preventive and corrective maintenance, respectively. To select preventive maintenance actions, a long short-term memory model is employed to accurately predict the health condition of the machine. Each rolling horizon consists of ordinary and forecast stages, and by collecting new sensor data, the maintenance and production decisions are simultaneously updated. The resulting integrated framework is validated using a benchmarking data set. The results are compared for different approaches to highlight the advantages of the proposed framework.
Journal: International Journal of Production Research
Pages: 7972-7991
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2162618
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2162618
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# input file: TPRS_A_2142312_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hongyan Dui
Author-X-Name-First: Hongyan
Author-X-Name-Last: Dui
Author-Name: Xingju Yang
Author-X-Name-First: Xingju
Author-X-Name-Last: Yang
Author-Name: Meng Liu
Author-X-Name-First: Meng
Author-X-Name-Last: Liu
Title: Importance measure-based maintenance analysis and spare parts storage configuration in two-echelon maintenance and supply support system
Abstract: 
 The development of society has put forward higher requirements for the supply of maintenance spare parts. However, the current support index is not comprehensive enough to evaluate the system ability. Meanwhile, the influence of horizontal supply time on spare parts storage is not fully reflected. Therefore, the problem of spare parts storage configuration in two-echelon maintenance and supply support systems is analysed in the paper. First, the state transition rates of different parts are studied under the context. Then a system-level comprehensive support rate based on importance measure is proposed. To determine the number of different spare parts, an optimisation model is established to maximise system support efficiency. Furthermore, a site importance measure based on horizontal supply time is proposed to measure the site priority over spare parts storage. Next, a two-stage decision method is presented for determining the location of spare parts. Finally, the feasibility of the proposed method is verified with the help of an example for the aircraft maintenance and supply support system.
Journal: International Journal of Production Research
Pages: 8325-8342
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2142312
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2142312
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# input file: TPRS_A_2166622_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yishu Bai
Author-X-Name-First: Yishu
Author-X-Name-Last: Bai
Author-Name: Liang Zhang
Author-X-Name-First: Liang
Author-X-Name-Last: Zhang
Title: Recursive decomposition/aggregation algorithms for performance metrics calculation in multi-level assembly/disassembly production systems with exponential reliability machines
Abstract: 
 Developing accurate and computationally efficient algorithms for system performance metrics calculation is critical to implementing effective control and optimization in manufacturing system operations. In this paper, we propose a recursive decomposition/aggregation-based method for calculating the performance metrics of assembly/disassembly systems with multiple merge/split operations and sub-assemblies. It is assumed that the machines follow the exponential reliability model and the buffers are of finite capacity. To achieve this, we first consider assembly systems with multiple component lines merging at a single assembly operation. By decomposing the system into a set of virtual serial lines, we derive an analytical procedure to approximate the starvation and blockage probabilities of the merge operation, which are used to recursively update the parameters of the virtual serial lines. Then, the performance metrics of the original assembly system are approximated based on the corresponding machines and buffers in these virtual serial lines. Next, we extend the algorithm to assembly/disassembly systems with multiple merge/split operations and sub-assemblies. This is accomplished by identifying the so-called assembly/disassembly units formed based on the virtual serial lines and applying the calculations derived earlier recursively. Simulation experiments are carried out to justify the convergence, computational efficiency, and approximation accuracy of the proposed algorithms. An industrial case study is presented to demonstrate the theoretical methods in practical applications.
Journal: International Journal of Production Research
Pages: 8133-8158
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2023.2166622
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2166622
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# input file: TPRS_A_2216310_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Jinsu Gim
Author-X-Name-First: Jinsu
Author-X-Name-Last: Gim
Author-Name: Lih-Sheng Turng
Author-X-Name-First: Lih-Sheng
Author-X-Name-Last: Turng
Title: Interpretation of the effect of transient process data on part quality of injection molding based on explainable artificial intelligence
Abstract: 
 This paper proposes an interpretation methodology for the effect of transient process data on quality of injection molded parts. The transient process data measured in the actual processing space have been regarded as the most relevant information to manufacturing processes and product quality. However, its interpretation to pinpoint which feature in the data would affect part quality has traditionally relied on knowledge and understanding of the manufacturing process. The main objective of this method is to reduce the dependency of the transient process data analysis on process knowledge and understanding by using explainable artificial intelligence (XAI). The contribution of the ‘section-wise' features in the transient process data to the quality prediction of machine learning (ML) models was investigated for the first time. The interpretation results of the effect of cavity pressure and mold surface temperature on four different quality factors represented reasonable explanations of the characteristics of the polymer materials, product geometry, and molding process. Due to the intermediate relationship of the transient process data with the user-specified process parameters and the resulting quality variables, the interpretation results can be further utilized to optimize the process and provide the optimal transient process data profile for best part quality.
Journal: International Journal of Production Research
Pages: 8192-8212
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2023.2216310
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2216310
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# input file: TPRS_A_2167013_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Abhijeet S. Bhardwaj
Author-X-Name-First: Abhijeet S.
Author-X-Name-Last: Bhardwaj
Author-Name: Dharmaraj Veeramani
Author-X-Name-First: Dharmaraj
Author-X-Name-Last: Veeramani
Author-Name: Shiyu Zhou
Author-X-Name-First: Shiyu
Author-X-Name-Last: Zhou
Title: Confidently extracting hierarchical taxonomy information from unstructured maintenance records of industrial equipment
Abstract: 
 Maintenance records of complex industrial equipment contain a large amount of unstructured data (e.g. technician notes) pertaining to repair actions and associated equipment sub-components, degradation conditions, failure mechanisms, etc. These unstructured data can yield valuable insights to improve the equipment design and maintenance plans, resulting in higher productivity and lower operating costs. Since manual review of information is time-consuming, companies make limited use of the maintenance records. To address this opportunity, we propose a taxonomy-guided method for automatically analysing the unstructured data and inferring critical information, specifically the hierarchy of the equipment's sub-assemblies and constituent parts that malfunctioned or failed during a breakdown event. Our method leverages syntactic (related to word frequency) as well as semantic (related to word co-occurrence and their meaning) knowledge. A novel contribution of our work is that we provide a confidence score for the information inferred by our method. Only the maintenance records which receive a low confidence score will require manual review to confirm the automated method's results, thus ensuring minimal use of human resources. We demonstrate the performance of our method using a real-world data set from equipment used in oil rigs.
Journal: International Journal of Production Research
Pages: 8159-8178
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2023.2167013
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2167013
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# input file: TPRS_A_2164374_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Audrey Cerqueus
Author-X-Name-First: Audrey
Author-X-Name-Last: Cerqueus
Author-Name: Xavier Delorme
Author-X-Name-First: Xavier
Author-X-Name-Last: Delorme
Title: Evaluating the scalability of reconfigurable manufacturing systems at the design phase
Abstract: 
 To face market volatility, reconfigurable manufacturing systems (RMS) aim to efficiently and cost-effectively react to changes. We focus on one characteristic of RMS: the scalability (ability to adapt the volume of throughput). In the literature, the only few indicators for scalability are not always formally defined and usually only consider a partial view of scalability. Moreover, most of them are actually more suited for the configuration planning rather than for the design. However, the design of the RMS has a high impact on its scalability. We propose the first combinatorial definition of this problem and a new measure to fully assess the scalability of a system at the design phase. This measure, based on a multi-objective approach, can assess the scalability of single-product manufacturing systems, analysing all configurations that it can implement. We present numerical experiments to compare this indicator with a state-of-the-art scalability indicator and with some classical production line design indicators, and we show that future research should focus on scalability as a specific criterion to optimise during the design of an RMS. In addition, the results obtained allow us to infer some managerial insights on the best levers to use when performing a reconfiguration for scalability purpose.
Journal: International Journal of Production Research
Pages: 8080-8093
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2164374
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2164374
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# input file: TPRS_A_2168083_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Melek Rodoplu
Author-X-Name-First: Melek
Author-X-Name-Last: Rodoplu
Author-Name: Stéphane Dauzère-Pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-Pérès
Author-Name: Philippe Vialletelle
Author-X-Name-First: Philippe
Author-X-Name-Last: Vialletelle
Title: Integrated planning of maintenance operations and workload allocation
Abstract: 
 Motivated by a practical problem, this paper investigates the integrated planning of maintenance operations and workload allocation on a set of machines in a workshop. Given quantities of products to be produced per period on a planning horizon must be processed on unrelated flexible machines. Moreover, each machine has to undergo one or more maintenance operations that must be planned within a given time window and impact products differently. The main goal is to find a feasible plan that satisfies the machine capacity by allocating the production quantities to machines and assigning maintenance operations as late as possible in their time windows. Various original mathematical models are presented. In particular, we propose models that allow maintenance operations and some production quantities to overlap two consecutive periods. Computational experiments based on industrial data show that allowing this overlapping helps the earliness of maintenance operations to be significantly reduced in the most difficult instances, going for example from a total of 14 periods to only 1 period, and by more than 35% on average.
Journal: International Journal of Production Research
Pages: 8291-8308
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2023.2168083
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2168083
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# input file: TPRS_A_2127163_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hongyan Dui
Author-X-Name-First: Hongyan
Author-X-Name-Last: Dui
Author-Name: Xingju Yang
Author-X-Name-First: Xingju
Author-X-Name-Last: Yang
Author-Name: Yining Fang
Author-X-Name-First: Yining
Author-X-Name-Last: Fang
Title: Evaluation methodology for preventive maintenance in multi-state manufacturing systems considering different costs
Abstract: 
 In a multi-state manufacturing system, preventive maintenance is performed on other machines once the performance of a machine falls below a threshold state. Many investigations have been performed on the maintenance of manufacturing systems. However, studies on preventive maintenance for manufacturing systems that account for the different costs involved are limited. This paper focuses on the analysis of multi-state machines in a manufacturing system considering different costs. Subsequently, a cost-based preventive maintenance prioritisation method for multi-state machines is proposed. Based on the buffer capacity, three maintenance policies on the machines are discussed. Different machine failures lead to different maintenance priorities. The real-time buffer capacity greatly influences the selection of machines for preventive maintenance. The set of the optimal machines for preventive maintenance is determined based on the constraints of machine running time and different preventive maintenance costs. Finally, a numerical example is used to demonstrate the effectiveness of the proposed method.
Journal: International Journal of Production Research
Pages: 8309-8324
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2127163
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2127163
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# input file: TPRS_A_2162619_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Imene Elhachfi Essoussi
Author-X-Name-First: Imene Elhachfi
Author-X-Name-Last: Essoussi
Author-Name: Malek Masmoudi
Author-X-Name-First: Malek
Author-X-Name-Last: Masmoudi
Author-Name: M. Zied Babai
Author-X-Name-First: M. Zied
Author-X-Name-Last: Babai
Title: Multi-criteria decision-making for collaborative COVID-19 surge management and inter-hospital patients’ transfer optimisation
Abstract: 
 The rapid spread of the COVID-19 virus and the massive influx of patients exceeded the intensive care units capacity limit. Hospitals have engaged community partners to request resources or transfer patients to facilities with available resources. This setting fosters the need for rationing decisions to allocate scarce resources consistently, rather than basing decisions on clinicians’ intuition in the heat of the moment. In this paper, we identify the inter-hospital COVID-19 patients’ transfer criteria, and we apply a multi-criteria decision-making methodology to classify and rank these criteria in order to determine the transfer priority scores between hospitals. We then develop an optimisation model for patient systematic referral from saturated to recipient hospitals with contingency capacity expansion and a ventilator donation scheme. To deal with the uncertainty related to the number of ill patients requesting beds in hospitals, a two-stage stochastic model is presented and solved using the sample average approximation. A case with real data related to the COVID-19 French context is presented, which allows us to assess the resilience of the hospital network under the proposed solutions. The results show how local and regional coalitions can avert the saturation of the hospital system and reduce the number of rejected patients.
Journal: International Journal of Production Research
Pages: 7992-8021
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2162619
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2162619
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# input file: TPRS_A_2240900_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: Metaverse supply chain and operations management
Abstract: 
 The metaverse and Web 3.0 have created a new digital world with specific properties and behaviours replicating and influencing the behaviours and processes of physical entities. This study aims to advance our understanding of how the metaverse will impact supply chain and operations management (SCOM). Using elements of a structured literature search and building on the concepts of cyber-physical systems, digital supply chain twins, cloud supply chains, and Industry 4.0/Industry 5.0, we propose a framework for metaverse SCOM encompassing multiple socio-technological dimensions. We conclude that further metaverse developments could result in a co-existence of physical SCOM, metaverse SCOM, and SCOM for coordination of the physical and metaverse worlds. We offer a structured future research agenda pointing to new research questions and topics stemming from metaverse-driven visibility, computational power for data analytics, digital collaboration, and connectivity. New research areas can emerge for the novel metaverse SCOM processes and decision-making areas (e.g. joint demand forecasting for metaverse and physical products, digital inventory allocation in the metaverse, integrated production planning for the metaverse and physical worlds, and pricing and contracting for digital products), as well as new performance measures (e.g. virtual customer experience level, availability of digital products, and digital resilience and sustainability).
Journal: International Journal of Production Research
Pages: 8179-8191
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2023.2240900
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2240900
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2164087_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Lilla Hortovanyi
Author-X-Name-First: Lilla
Author-X-Name-Last: Hortovanyi
Author-Name: Robert E. Morgan
Author-X-Name-First: Robert E.
Author-X-Name-Last: Morgan
Author-Name: Iva Vuksanovic Herceg
Author-X-Name-First: Iva Vuksanovic
Author-X-Name-Last: Herceg
Author-Name: Dragan Djuricin
Author-X-Name-First: Dragan
Author-X-Name-Last: Djuricin
Author-Name: Robert Hanak
Author-X-Name-First: Robert
Author-X-Name-Last: Hanak
Author-Name: Dora Horvath
Author-X-Name-First: Dora
Author-X-Name-Last: Horvath
Author-Name: Marian L. Mocan
Author-X-Name-First: Marian L.
Author-X-Name-Last: Mocan
Author-Name: Anita Romanova
Author-X-Name-First: Anita
Author-X-Name-Last: Romanova
Author-Name: Roland Z. Szabo
Author-X-Name-First: Roland Z.
Author-X-Name-Last: Szabo
Title: Assessment of digital maturity: the role of resources and capabilities in digital transformation in B2B firms
Abstract: 
 Digital transformation is a major organisational challenge for manufacturing firms due to the extremely low success rate of such transformations to date. Capability Maturity theory suggests that firms need to develop digital transformation capability incrementally by focusing on a ‘vital few’ improvement priorities for advancing progress. The practitioner literature lacks empirical studies that validate extant capability maturity models (CMM) for digital transformation despite their importance. Moreover, there is a lack of assessment methods, and those that exist do not specify improvement points explicitly, nor prioritise them. Our research aims to address this gap through a systematic, quantitative analysis of digital capability by understanding the deployment of IT-enabled resources. Based on a sample of 302 manufacturing firms, results indicate that the digital transformation stages are punctuated by various resource-capability combinations. Results highlight that strategy- and organisation-related IT-enabled resources are the key drivers of digital transformation. We also observe that as a firm’s digital capability grows at each maturity stage, successively greater IT-enabled resources are required to support this in a stepwise function. To succeed, firms should be incentivised and supported to think beyond technology and develop five specific digital capabilities simultaneously. We also indicate the limitations that underlie our empirical work.
Journal: International Journal of Production Research
Pages: 8043-8061
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2164087
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2164087
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# input file: TPRS_A_2162146_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Gabriela Sánchez-Yepez
Author-X-Name-First: Gabriela
Author-X-Name-Last: Sánchez-Yepez
Author-Name: M. Angélica Salazar-Aguilar
Author-X-Name-First: M.
Author-X-Name-Last: Angélica Salazar-Aguilar
Author-Name: Pamela J. Palomo-Martínez
Author-X-Name-First: Pamela J.
Author-X-Name-Last: Palomo-Martínez
Title: Team orienteering problem with nonidentical agents and balanced score
Abstract: 
 In this work, we study a variant of the team orienteering problem motivated by a real-world situation faced by a Mexican telecommunications company. The problem consists of the daily assignment and scheduling of service orders to crews, aiming to balance their wages, and considering the compatibility between service orders and crews. We present a mixed-integer linear formulation with two different metrics to achieve balanced scores and two valid inequalities leveraging the structure of the problem. Afterward, we propose a practical adaptive multi-start heuristic that integrates the learning mechanism of a reactive Greedy Randomized Adaptive Search Procedure. We test the performance of the models and the proposed algorithm on a benchmark of instances adapted from the literature and in a case study based on real data. The results confirm the effectiveness of the proposed algorithm to support the decision-making process.
Journal: International Journal of Production Research
Pages: 7957-7971
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2162146
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2162146
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# input file: TPRS_A_2180301_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Eduyn López-Santana
Author-X-Name-First: Eduyn
Author-X-Name-Last: López-Santana
Author-Name: Germán Méndez
Author-X-Name-First: Germán
Author-X-Name-Last: Méndez
Author-Name: Carlos Franco
Author-X-Name-First: Carlos
Author-X-Name-Last: Franco
Title: On the multi-period combined maintenance and routing optimisation problem
Abstract: 
 This paper focuses on the combined maintenance and routing optimisation problem in a multi-period environment that consists of scheduling maintenance operations for a set of geographically distributed machines, subject to non-deterministic failures with a set of technicians that perform preventive maintenance and corrective operations. This study uses a two-step approach based on column generation. The first step consists of a maintenance model that determines the optimal time until the next preventive maintenance operation, and each machine’s maintenance frequency while minimising the total expected maintenance costs. The second step involves a routing model that assigns and schedules maintenance operations for each technician over the planning horizon while minimising the routing and maintenance costs. We formulate the second step problem as a periodic vehicle routing problem and to solve it, we propose a column generation approach. The master problem is a set partitioning formulation that indicates which machines must be visited in the planning horizon. This decomposition has two auxiliary problems: the first one is an elementary shortest-path problem to find a feasible path for each period and the second one finds a set of visiting periods for each machine. Our approach balances the maintenance cost, routing cost, and failure probabilities.
Journal: International Journal of Production Research
Pages: 8265-8290
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2023.2180301
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2180301
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# input file: TPRS_A_2244844_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bin Liu
Author-X-Name-First: Bin
Author-X-Name-Last: Liu
Author-Name: Kerem Akartunali
Author-X-Name-First: Kerem
Author-X-Name-Last: Akartunali
Author-Name: Stéphane Dauzère-pérès
Author-X-Name-First: Stéphane
Author-X-Name-Last: Dauzère-pérès
Author-Name: Shaomin Wu
Author-X-Name-First: Shaomin
Author-X-Name-Last: Wu
Title: Special issue on collaborative production and maintenance in the environment of big data and industry 4.0
Journal: International Journal of Production Research
Pages: 8236-8237
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2023.2244844
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2244844
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# input file: TPRS_A_2122621_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Hanting Zhou
Author-X-Name-First: Hanting
Author-X-Name-Last: Zhou
Author-Name: Wenhe Chen
Author-X-Name-First: Wenhe
Author-X-Name-Last: Chen
Author-Name: Changqing Shen
Author-X-Name-First: Changqing
Author-X-Name-Last: Shen
Author-Name: Longsheng Cheng
Author-X-Name-First: Longsheng
Author-X-Name-Last: Cheng
Author-Name: Min Xia
Author-X-Name-First: Min
Author-X-Name-Last: Xia
Title: Intelligent machine fault diagnosis with effective denoising using EEMD-ICA- FuzzyEn and CNN
Abstract: 
 With the advances in smart sensing and data mining technologies of Industry 4.0, condition monitoring of key equipment in manufacturing has brought transformations in production and maintenance management. However, in practical applications, noise from both the working environment and the sensing devices is inevitable, which causes the low performance of data-driven fault diagnosis. To address this challenge, the paper develops a robust two-stage joint denoising method by integrating ensemble empirical mode decomposition (EEMD) and independent component analysis (ICA), with fuzzy entropy discriminant as a threshold. The developed method can filter noisy components from decomposed modal components and reconstruct a new signal with denoised independent components. Moreover, an improved convolutional neural network (CNN) model based on the VGG structure has been constructed as a classifier to achieve end-to-end fault diagnosis. The experimental results demonstrate the high accuracy and superior anti-interference capability of the proposed method for rolling bearing fault diagnosis under various noise levels. Compared with state-of-the-art denoising methods and fault diagnosis methods, the proposed method achieves higher accuracy and robustness under variable noise interference. The proposed method can be applied to broader fault diagnosis tasks of production equipment in complex practical environments.
Journal: International Journal of Production Research
Pages: 8252-8264
Issue: 23
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2122621
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2122621
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# input file: TPRS_A_2036381_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Leili Soltanisehat
Author-X-Name-First: Leili
Author-X-Name-Last: Soltanisehat
Author-Name: Nafiseh Ghorbani-Renani
Author-X-Name-First: Nafiseh
Author-X-Name-Last: Ghorbani-Renani
Author-Name: Andrés D. González
Author-X-Name-First: Andrés D.
Author-X-Name-Last: González
Author-Name: Kash Barker
Author-X-Name-First: Kash
Author-X-Name-Last: Barker
Title: Assessing production fulfillment time risk: application to pandemic-related health equipment
Abstract: 
 Manufacturing companies strive to identify and manage the effects of unexpected disruptions (risks) on their production processes, which affect their performance and resilience. In this study, we propose a decision framework to capture the impact of interconnected risk sources, on the efficiency of manufacturing companies. The proposed framework utilises a novel mixed-integer linear programming (MILP) model to minimize the time of satisfying the orders while it considers the risk associated with suppliers and manufacturers. The MILP model considers the relationships among (i) material and suppliers and (ii) work centers to measure the propagation of risks throughout the production system. The proposed framework also utilises the Monte Carlo simulation to calculate the associated likelihood of delay and the distribution of the delivery time of orders. To show the complication of the propagation of risk, two distinct scenarios are compared. The first scenario considers zero risks, while the second one assigns probabilistic risk to the suppliers and work centers. The results highlight the magnitude and the complexity of the risk propagation from various interconnected sources through the production system. It also identifies the most vulnerable components of the production system affected more by various types of risk.
Journal: International Journal of Production Research
Pages: 8401-8422
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2036381
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2036381
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# input file: TPRS_A_2152897_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ercihan Kiraci
Author-X-Name-First: Ercihan
Author-X-Name-Last: Kiraci
Author-Name: Arnab Palit
Author-X-Name-First: Arnab
Author-X-Name-Last: Palit
Author-Name: Alex Attridge
Author-X-Name-First: Alex
Author-X-Name-Last: Attridge
Author-Name: Mark A. Williams
Author-X-Name-First: Mark A.
Author-X-Name-Last: Williams
Title: The effect of clamping sequence on dimensional variability of a manufactured automotive sheet metal sub-assembly
Abstract: 
 The use of holding and inspection fixtures is common across many sectors of manufacturing. The concept of a fixture for holding a component, for the purposes of assembly or inspection, is straightforward. The fixture design and the associated clamping strategy can have a significant impact on the process. This paper presents a methodology for investigating the effects of clamping sequence for a production inspection fixture, on the dimensional variability of an automotive production-representative sheet metal sub-assembly, along with experimental findings and analysis of measurement data. The study utilises both a coordinate measuring machine and laser tracker to capture a range of features and surface points, and compares four different clamping sequences, including the manufacturer’s defined sequence, to evaluate their effect on the dimensional results from a predetermined measurement plan. The results from the study show that there was significant variation in measurements taken from the four different clamping sequences, and these variations can show the same points and/or features being within tolerance for one clamping sequence and out of tolerance for another. This clearly has major implications for product development and subsequent volume manufacture, so needs to be considered and optimised in the measurement planning process.
Journal: International Journal of Production Research
Pages: 8547-8559
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2152897
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152897
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# input file: TPRS_A_2152894_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Chiara Cimini
Author-X-Name-First: Chiara
Author-X-Name-Last: Cimini
Author-Name: Alexandra Lagorio
Author-X-Name-First: Alexandra
Author-X-Name-Last: Lagorio
Author-Name: Paolo Gaiardelli
Author-X-Name-First: Paolo
Author-X-Name-Last: Gaiardelli
Title: The evolution of operators’ role in production: how Lean Manufacturing and Industry 4.0 affect Job Enlargement and Job Enrichment
Abstract: 
 In modern manufacturing systems, operators’ role is evolving continuously in relation to the main production paradigms affecting how companies approach their manufacturing and logistics operations. If the introduction of Lean Manufacturing principles has affected workers’ well-being directly, the adoption of digital technologies is modifying how factory work is organised and performed. As a result, digitalised and Lean Manufacturing contexts require operators to enhance their skills increasingly to perform several tasks and functions. This paper examines the evolution of operators’ role in production by recalling two main work design paradigms that originated in the 1960s: Job Enlargement and Job Enrichment. Indeed, through a literature review and development of a causal loop diagram (CLD), this research points out how the main features of Industry 4.0 and Lean Manufacturing jointly affect the Job Enlargement and Job Enrichment concepts. The study significantly helps reshape work design in next-generation production systems, shedding light on the implications and relationships of the most widespread manufacturing paradigm, i.e. Lean Manufacturing and Industry 4.0, using Job Enrichment and Job Enlargement strategies. A CLD also can be a helpful tool for practitioners to understand what factors to leverage to increase efficiency and worker satisfaction.
Journal: International Journal of Production Research
Pages: 8493-8511
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2152894
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152894
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# input file: TPRS_A_2152127_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Oktay Karabağ
Author-X-Name-First: Oktay
Author-X-Name-Last: Karabağ
Author-Name: Burak Gökgür
Author-X-Name-First: Burak
Author-X-Name-Last: Gökgür
Title: Integrated optimisation of pricing, manufacturing, and procurement decisions of a make-to-stock system operating in a fluctuating environment
Abstract: 
 Manufacturers experience random environmental fluctuations that influence their supply and demand processes directly. To cope with these environmental fluctuations, they typically utilise operational hedging strategies in terms of pricing, manufacturing, and procurement decisions. We focus on this challenging problem by proposing an analytical model. Specifically, we study an integrated problem of procurement, manufacturing, and pricing strategies for a continuous-review make-to-stock system operating in a randomly fluctuating environment with exponentially distributed processing times. The environmental changes are driven by a continuous-time discrete state-space Markov chain, and they directly affect the system's procurement price, raw material flow rate, and price-sensitive demand rate. We formulate the system as an infinite-horizon Markov decision process with a long-run average profit criterion and show that the optimal procurement and manufacturing strategies are of state-dependent threshold policies. Besides that, we provide several analytical results on the optimal pricing strategies. We introduce a linear programming formulation to numerically obtain the system's optimal decisions. We, particularly, investigate how production rate, holding cost, procurement price and demand variabilities, customers' price sensitivity, and interaction between supply and demand processes affect the system's performance measures through an extensive numerical study. Furthermore, our numerical results demonstrate the potential benefits of using dynamic pricing compared to that of static pricing. In particular, the profit enhancement being achieved with dynamic pricing can reach up to 15%, depending on the problem parameters.
Journal: International Journal of Production Research
Pages: 8423-8450
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2152127
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152127
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# input file: TPRS_A_2158243_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Bella Belerivana Nujen
Author-X-Name-First: Bella Belerivana
Author-X-Name-Last: Nujen
Author-Name: Nina Pereira Kvadsheim
Author-X-Name-First: Nina Pereira
Author-X-Name-Last: Kvadsheim
Author-Name: Deodat Mwesiumo
Author-X-Name-First: Deodat
Author-X-Name-Last: Mwesiumo
Author-Name: Eivind Reke
Author-X-Name-First: Eivind
Author-X-Name-Last: Reke
Author-Name: Daryl Powell
Author-X-Name-First: Daryl
Author-X-Name-Last: Powell
Title: Knowledge obstacles when transitioning towards circular economy: an industrial intra-organisational perspective
Abstract: 
 Circular economy (CE) is necessary for achieving sustainability goals. Nonetheless, the distillation of CE practices into business operations has been unsatisfactory as firms struggle to transition to CE. There is an increase in studies that have attempted to identify challenges impeding the implementation of CE practices. However, most of these studies focus on technical and external aspects affecting CE, leaving intra-organisational aspects such as organisational learning and knowledge largely unexplored. The latter aspects can play a significant role in CE transitions, and thus warrants further research. To address this research gap, this study draws on lean thinking as an organisational learning system and accentuates knowledge obstacles, seen as wastes, that can stifle a transition to CE. Subsequently, it deploys action-learning research, involving collaboration between researchers and the participants in the action to generate actionable knowledge. The analysis of the findings is used to develop a novel framework including six measures that can be implemented to counteract knowledge obstacles and lay a foundation for a CE transition. The proposed framework can be the basis for further research on lean and intra-organisational aspects that can help firms restructure the current linear mode of production, and thus accelerate a smooth CE transition.
Journal: International Journal of Production Research
Pages: 8618-8633
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2158243
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2158243
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# input file: TPRS_A_2152890_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yunfang Peng
Author-X-Name-First: Yunfang
Author-X-Name-Last: Peng
Author-Name: Lijun Zhang
Author-X-Name-First: Lijun
Author-X-Name-Last: Zhang
Author-Name: Beixin Xia
Author-X-Name-First: Beixin
Author-X-Name-Last: Xia
Author-Name: Yajuan Han
Author-X-Name-First: Yajuan
Author-X-Name-Last: Han
Title: Research on balancing and sequencing problems of flexible mixed model assembly lines with alternative precedence relations
Abstract: 
 To tackle the balancing and sequencing problems of flexible mixed model assembly lines with alternative precedence relations, If–then rules and AND/OR graphs are adopted as modelling tools to replace precedence graphs that have limitations in representing alternative precedence relations. Mixed integer linear programming (MILP) and constraint programming (CP) models are established respectively. Moreover, an iterative decomposition method is developed to deal with large-sized problems. Computational experiments on different scales are carried out to test those methods. The computational results reveal that the performance of CP is better than MILP especially when more OR relations exist. And the iterative decomposition method outperforms MILP and CP in terms of solution quality and time.
Journal: International Journal of Production Research
Pages: 8451-8467
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2152890
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152890
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# input file: TPRS_A_2154404_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Levi R. Abreu
Author-X-Name-First: Levi R.
Author-X-Name-Last: Abreu
Author-Name: Marcelo S. Nagano
Author-X-Name-First: Marcelo S.
Author-X-Name-Last: Nagano
Author-Name: Bruno A. Prata
Author-X-Name-First: Bruno A.
Author-X-Name-Last: Prata
Title: A new two-stage constraint programming approach for open shop scheduling problem with machine blocking
Abstract: 
 In this paper, a variant of the open shop scheduling problem is considered in which the intermediate storage is forbidden among two adjacent production stages (zero buffer or machine blocking constraint). The performance measure is to minimise the maximal completion time of the jobs (makespan). Since this is an NP-hard problem, a two-stage constraint programming approach is proposed as a new exact method. Computational experiments were carried out on 222 literature problem instances in order to test the performance of the proposed algorithm. The relative deviation is adopted as the performance criteria. Computational results point to the ability of the proposed method to solve large-sized instances in comparison with the developed mixed-integer linear programming model and a simple constraint programming model, both with user cuts. In all set of instances, the proposed two-stage method performed better than benchmarking methods and integer programming models, with average relative deviation regarding objective values as lower as 12%. In addition, the results point to a competitive efficiency in computational times of the proposed method with less than 200 s in the most instances to obtain the optimal solution, in comparison to competitive metaheuristics from literature of the problem, for the tested test instances.
Journal: International Journal of Production Research
Pages: 8560-8579
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2154404
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2154404
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# input file: TPRS_A_2159562_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Simon Schumacher
Author-X-Name-First: Simon
Author-X-Name-Last: Schumacher
Author-Name: Roland Hall
Author-X-Name-First: Roland
Author-X-Name-Last: Hall
Author-Name: Andreas Bildstein
Author-X-Name-First: Andreas
Author-X-Name-Last: Bildstein
Author-Name: Thomas Bauernhansl
Author-X-Name-First: Thomas
Author-X-Name-Last: Bauernhansl
Title: Lean Production Systems 4.0: systematic literature review and field study on the digital transformation of lean methods and tools
Abstract: 
 Lean Production Systems are enterprise-specific, methodical frameworks for the continuous orientation of all enterprise processes to the customer in order to achieve overall objectives. Due to an increasing complexity of the digital transformation, the design of Lean Production Systems 4.0 is a challenging task for industrial engineering practice. For this, academia and industrial practice were analysed in a combined approach of a systematic literature review and a field study. The systematic literature review of 62 out of 1600 scientific papers shows that especially the tools, processes, and methods in Lean Production Systems are subject to digital transformation. By involving industrial practice in a field study, quantitative and qualitative insights were used to check scientific hypotheses and identify practical requirements by industrial engineers. As a result, 10 guidelines for the design of future Lean Production Systems 4.0 are derived. The practical implications of this paper enhance the evolution of enterprise-specific Lean Production System 4.0 frameworks.
Journal: International Journal of Production Research
Pages: 8751-8773
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2159562
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2159562
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# input file: TPRS_A_2159563_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Sven F. Falkenberg
Author-X-Name-First: Sven F.
Author-X-Name-Last: Falkenberg
Author-Name: Stefan Spinler
Author-X-Name-First: Stefan
Author-X-Name-Last: Spinler
Title: Integrating operational and human factors to predict daily productivity of warehouse employees using extreme gradient boosting
Abstract: 
 The majority of warehouse expenses is driven by labour cost. Therefore, efficient management of labour resources is required. To do so, workforce planning is used to match the workforce capacity with the incoming workload. While doing so, it is often wrongly assumed that each worker has the same and constant capacity or performance. Addressing this, we build a model to predict the employee-based productivity of newly hired warehouse personnel that will support workforce planning by incorporating multiple data sources. To this end, we develop a framework to identify relevant variables in four categories: warehouse, operator, shift and product. We demonstrate that Extreme Gradient Boosting, using these variables may reduce the root mean squared error of the prediction by more than 50%. A comprehensive scenario analysis shows that improving productivity predictions translates into substantial cost savings. Furthermore, a sensitivity analysis identifies which variable categories should be favoured in the data collection process to achieve the best prediction results.Abbreviations: CMA: Cumulative Moving Averages; EGB: Extreme Gradient Boosting; GB: Gradient Boosting; LSP: Logistics Service Provider; MAE: Mean Absolute Error; RF: Random Forest; RMSE: Root Mean Squared Error; SMA: Simple Moving Averages
Journal: International Journal of Production Research
Pages: 8654-8673
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2159563
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2159563
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# input file: TPRS_A_1967501_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Leandro Miletto Tonetto
Author-X-Name-First: Leandro Miletto
Author-X-Name-Last: Tonetto
Author-Name: Tarcísio Abreu Saurin
Author-X-Name-First: Tarcísio Abreu
Author-X-Name-Last: Saurin
Author-Name: Flavio Sanson Fogliatto
Author-X-Name-First: Flavio Sanson
Author-X-Name-Last: Fogliatto
Author-Name: Guilherme Luz Tortorella
Author-X-Name-First: Guilherme Luz
Author-X-Name-Last: Tortorella
Author-Name: Gopalakrishnan Narayanamurthy
Author-X-Name-First: Gopalakrishnan
Author-X-Name-Last: Narayanamurthy
Author-Name: Valentina Marques da Rosa
Author-X-Name-First: Valentina Marques
Author-X-Name-Last: da Rosa
Author-Name: Jeslyn Tengkawan
Author-X-Name-First: Jeslyn
Author-X-Name-Last: Tengkawan
Title: Information and communication technologies in emergency care services for patients with COVID-19: a multi-national study
Abstract: 
 Information and communication technologies (ICTs) are known for supporting healthcare services in dealing with adverse situations. However, little is known on the contribution of ICTs in a prolonged crisis involving a new disease, such as the COVID-19 pandemic. In this study, we carry out an exploratory investigation of which ICTs contribute the most to the emergency care of patients diagnosed with COVID-19 according to healthcare technology experts and how physicians perceive these contributions. Initially, we applied an online survey to 109 healthcare technology experts. Then, we conducted 16 in-depth follow-up interviews with emergency medicine professionals from 10 countries to identify the ICTs contributing the most to treat COVID-19 patients. Results from the survey indicated four ICTs as the most useful to support the treatment of COVID-19 patients; they are remote consultations, digital platforms for data sharing, digital non-invasive care, and interconnected medical decision support. The interviews provided insight into the applicability of those ICTs for the studied context. The four main ICTs were also found to be logically compatible with the complexity of the pandemic, reducing undesirable complexity attributes (e.g. physical proximity between caregivers and infected patients) and amplifying desirable ones  (e.g. interactions that support collaborative work and knowledge sharing).
Journal: International Journal of Production Research
Pages: 8384-8400
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2021.1967501
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1967501
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# input file: TPRS_A_2152506_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Shenghao Xie
Author-X-Name-First: Shenghao
Author-X-Name-Last: Xie
Author-Name: Yu Gong
Author-X-Name-First: Yu
Author-X-Name-Last: Gong
Author-Name: Martin Kunc
Author-X-Name-First: Martin
Author-X-Name-Last: Kunc
Author-Name: Zongguo Wen
Author-X-Name-First: Zongguo
Author-X-Name-Last: Wen
Author-Name: Steve Brown
Author-X-Name-First: Steve
Author-X-Name-Last: Brown
Title: The application of blockchain technology in the recycling chain: a state-of-the-art literature review and conceptual framework
Abstract: 
 More practitioners are embracing blockchain technology to improve recycling performance. However, current research on the use of blockchain is mostly confined to general discussions on sustainable supply chains and circular economy, with limited studies specifically focusing on the recycling chain. This paper conducts a thorough content-based review of the literature related to the application of blockchain technology in the recycling chain with the objective to identify a conceptual framework. Although descriptive and thematic analyses show limited developments, blockchain technology can offer four distinct functions in the recycling chain: transparency, integration, behaviour channelisation, and service transformation. The adoption of blockchain in this area has technical, organisational, and environmental limitations that have not been overcome yet. In terms of benefits, blockchain technology improves recycling performance in terms of cost, dependability, flexibility, sustainability, and risk reduction. To summarise the findings, the paper proposes a novel conceptual framework for blockchain implementations in the recycling chain to support practitioners and guide scholars in further blockchain technology exploration.
Journal: International Journal of Production Research
Pages: 8692-8718
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2152506
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152506
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# input file: TPRS_A_2158244_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Yugang Yu
Author-X-Name-First: Yugang
Author-X-Name-Last: Yu
Author-Name: Jingjing Yang
Author-X-Name-First: Jingjing
Author-X-Name-Last: Yang
Author-Name: Xiaolong Guo
Author-X-Name-First: Xiaolong
Author-X-Name-Last: Guo
Title: Retrieval sequencing in autonomous vehicle storage and retrieval systems
Abstract: 
 Autonomous vehicle storage and retrieval systems (AVS/RSs) are widely used in e-commerce warehouses due to their high throughput and flexibility. In such systems, storage and retrieval transactions are performed by lifts and vehicles. This paper focuses on the sequencing retrievals problem in an AVS/RS, which is an important problem for daily operations. We formulate this sequencing problem as a mixed-integer program to determine a retrieval sequence for the lift and the vehicles, one that minimises the makespan. A dynamic programming approach is proposed to solve the sequencing problem to optimality. However, the solution time of the dynamic programming method is exponentially increasing in the number of retrieval requests. To be more practical, we present a beam search heuristic that can solve large-sized instances in reasonable time. Computational experiments verify that near-optimal solutions can be found by the beam search heuristic. Compared to commonly used heuristics and straightforward heuristics, the beam search decreases the makespan by up to 15%. Finally, we analyse how vehicle modes impact the makespan, showing evidence that a small makespan can be achieved when considering a realistic mode of vehicles.
Journal: International Journal of Production Research
Pages: 8634-8653
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2158244
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2158244
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# input file: TPRS_A_2152892_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Kayvan Miri Lavassani
Author-X-Name-First: Kayvan Miri
Author-X-Name-Last: Lavassani
Author-Name: Zachary M. Boyd
Author-X-Name-First: Zachary M.
Author-X-Name-Last: Boyd
Author-Name: Bahar Movahedi
Author-X-Name-First: Bahar
Author-X-Name-Last: Movahedi
Author-Name: Jason Vasquez
Author-X-Name-First: Jason
Author-X-Name-Last: Vasquez
Title: Ten-tier and multi-scale supply chain network analysis of medical equipment: random failure & intelligent attack analysis
Abstract: 
 Motivated by the COVID-19 pandemic, this paper explores the supply chain viability of medical equipment, an industry whose supply chain was put under a crucial test during the pandemic. This paper includes an empirical network-level analysis of supplier reachability under Random Failure Experiments (RFE) and Intelligent Attack Experiments (IAE). Specifically, this study investigates the effect of RFE and IAE across multiple tiers and scales. The global supply chain data was mined and analysed from about 45,000 firms with about 115,000 intertwined relationships spanning across 10 tiers of the backward supply chain of medical equipment. This complex supply chain network was analysed at four scales, namely: firm, country-industry, industry, and country. A notable contribution of this study is the application of a supply chain tier optimisation tool to identify the lowest tier of the supply chain that can provide adequate resolution for the study of the supply chain pattern. We also developed data-driven-tools to identify the thresholds for breakdown and fragmentation of the medical equipment supply chain when faced with random failures or different intelligent attack scenarios. The novel network analysis tools utilised in the study can be applied to the study of supply chain reachability and viability in other industries.
Journal: International Journal of Production Research
Pages: 8468-8492
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2152892
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152892
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# input file: TPRS_A_2152896_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Ajit Sharma
Author-X-Name-First: Ajit
Author-X-Name-Last: Sharma
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj
Author-X-Name-Last: Kumar Tiwari
Title: Digital twin design and analytics for scaling up electric vehicle battery production using robots
Abstract: 
 As electric vehicle adoption accelerates and demand increases, the inability to produce batteries in sufficient quantities has emerged as a critical bottleneck in the electric vehicle supply chain. Given the impending climate change crisis, resolving this bottleneck is imperative to accelerate the transition to a zero-emission electric mobility future. One potential solution is the use of robotics for fast and cost-effective assembly of batteries at scale. This study proposes a three-stage digital twin design and analysis method to develop robotic workcells for fast and cost-effective assembly of electric vehicle battery modules. Using digital twin design and simulation, robotic assembly line configurations have been developed for battery module production at different scales. Digital twin analytics was used to evaluate and optimise the proposed robotic battery assembly system for speed and cost. Industrial automation experts were consulted to further improve robotic work cell layouts to minimise investment in robots. Because digital twins of robotic workcells have been used, the configurations of the battery assembly line, as designed and validated, are ready for immediate implementation. For practitioners, this study offers heuristic methods to determine the appropriate assembly line configuration, the required number of robots and humans, for a desired production volume. For researchers, this study outlines promising areas for future investigation.
Journal: International Journal of Production Research
Pages: 8512-8546
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2152896
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152896
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# input file: TPRS_A_2152893_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Mageed Ghaleb
Author-X-Name-First: Mageed
Author-X-Name-Last: Ghaleb
Author-Name: Sharareh Taghipour
Author-X-Name-First: Sharareh
Author-X-Name-Last: Taghipour
Title: Evidence-based study of the impacts of maintenance practices on asset sustainability
Abstract: 
 In practice, without clear evidence of the positive impacts of maintenance on sustainability, organisations/companies are not encouraged to look at (or invest in) maintenance as an effective tool to enhance sustainability. Therefore, it is essential to show them that such evidence exists, which is the aim of this paper. The paper reviews and analyses evidence from the literature about maintenance’s social, environmental, and economic impacts. It identifies the required sustainability-related indicators associated with these impacts and provides aggregate quantified percentages for them (positively or negatively), as shown in the reviewed papers. An evidence-based research is conducted in this paper to achieve this purpose. The search process results in a research sample of 58 publications that have been surveyed and analysed. Based on the conducted analysis, the results show that maintenance positively impacts economic, environmental, and social sustainability. Many reviewed cases appear in manufacturing and buildings (both residential and commercial) and primarily consider environmental and economic sustainability indicators. The cases with social sustainability indicators are limited. Regardless, these results bring adequate evidence to encourage researchers and practitioners to view maintenance as a practical approach to improve sustainability and to investigate more in this domain.
Journal: International Journal of Production Research
Pages: 8719-8750
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2152893
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2152893
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# input file: TPRS_A_2154405_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Theodor Borangiu
Author-X-Name-First: Theodor
Author-X-Name-Last: Borangiu
Author-Name: Silviu Răileanu
Author-X-Name-First: Silviu
Author-X-Name-Last: Răileanu
Title: A smart palletising planning and control model in Logistics 4.0 framework
Abstract: 
 The paper describes a smart model for palletising as main intra-logistics task for product-on-pallet distribution, and its development in Logistics 4.0 framework aligned to Industry 4.0. The model is developed in holonic paradigm as a 2-layer Holonic Logistics Execution System (HLES) in semi-heterarchical topology. Scheduling of logistics activities and allocation to resources are optimised for global efficiency on compact time periods. The logistics model virtualises physical entities: resources, pallets and orders as holons implemented with digital twin software, and categories of task workloads: resource health monitoring, dispatching and tracking pallet orders, re-assigning jobs at resource failure, which grants reality-awareness and robustness. Global workload optimisation uses Constraint Programming as decision making technology with ILOG optimiser engine as situation-specific solver tool in SaaS cloud model, and delegate multi-agent system (MAS) technology for intelligence distribution. The optimised objective function is a combination of palletising cost weighted by robot speed limits and pallet storage cost in payable stocks. The main constructs are exemplified and validated on a real-life structure with multiple palletising resources in which programmable logic controllers (PLC) coordinate locally the parallel execution of order holons according to their globally optimised sequence.
Journal: International Journal of Production Research
Pages: 8580-8597
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2154405
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2154405
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# input file: TPRS_A_1936261_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Soheyl Khalilpourazari
Author-X-Name-First: Soheyl
Author-X-Name-Last: Khalilpourazari
Author-Name: Hossein Hashemi Doulabi
Author-X-Name-First: Hossein
Author-X-Name-Last: Hashemi Doulabi
Title: Robust modelling and prediction of the COVID-19 pandemic in Canada
Abstract: 
 Since the beginning of COVID-19, more than 13,036,550 people have been infected, and 571,574 died because of the disease by July 13, 2020. Developing new methodologies to predict the COVID-19 pandemic will help policymakers plan to contain the spread of the virus. In this research, we develop a Stochastic Fractal Search algorithm combined with a mathematical model to forecast the pandemic. To enhance the algorithm, we employed a design of the experiments approach for tuning. We applied our algorithm to public datasets to model the COVID-19 pandemic in Canada in the upcoming months. Our algorithm predicts the number of symptomatic, asymptomatic, life-threatening, recovered, and death cases. The outcomes reveal that asymptomatic cases play the main role in the transmission of the virus. We also show that increasing the testing capacity would enhance the detection of asymptomatic cases and limit community transmission. Moreover, we performed sensitivity analyses to discover the effects of changes in transmission rates on pandemic growth. The sensitivity analyses provide a realistic overview of the future number of cases if the transmission rates change due to the emergence of new variants or change in social measures. Considering the outcomes, we provide several managerial insights to minimize community transmission.
Journal: International Journal of Production Research
Pages: 8367-8383
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2021.1936261
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1936261
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# input file: TPRS_A_2160026_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Juan De Antón
Author-X-Name-First: Juan
Author-X-Name-Last: De Antón
Author-Name: Félix Villafáñez
Author-X-Name-First: Félix
Author-X-Name-Last: Villafáñez
Author-Name: David Poza
Author-X-Name-First: David
Author-X-Name-Last: Poza
Author-Name: Adolfo López-Paredes
Author-X-Name-First: Adolfo
Author-X-Name-Last: López-Paredes
Title: A framework for production planning in additive manufacturing
Abstract: 
 Additive manufacturing (AM) introduces a set of technology-specific problems, such as the proper orientation of parts or the placement of several heterogeneous parts in the same build cycle, which are not addressed by traditional approaches to production planning and scheduling. Although these new production subproblems have been implicitly addressed by several works according to generic nesting and scheduling concepts, a literature review revealed that there is no uniformity in identifying and, thus, solving all these subproblems. For this reason, and as a result of an in-depth analysis of the existent literature on AM production planning and an analogy with classic cutting and packing typologies, the present paper offers a framework to formalise the production planning problem in AM at the operational level. This framework can be used as a reference to focus on and address these AM-related problems for efficient production planning. It is designed at the subproblem level and centres on production order processing in AM. A coding strategy is specifically developed for the framework, which is applied to a review of relevant works that propose models for the production planning of AM systems. Finally, the review results are discussed and possible extensions of the framework are proposed.
Journal: International Journal of Production Research
Pages: 8674-8691
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2160026
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2160026
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# input file: TPRS_A_2157904_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20230119T200553 git hash: 724830af20
Author-Name: Su Xiu Xu
Author-X-Name-First: Su Xiu
Author-X-Name-Last: Xu
Author-Name: Jianghong Feng
Author-X-Name-First: Jianghong
Author-X-Name-Last: Feng
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Author-Name: Yue Zhai
Author-X-Name-First: Yue
Author-X-Name-Last: Zhai
Author-Name: Meng Cheng
Author-X-Name-First: Meng
Author-X-Name-Last: Cheng
Title: Toward efficient waste electric vehicle battery recycling via auction-based market trading mechanisms
Abstract: 
 This paper proposes an auction-based market trade mechanism for the electric vehicle battery recycling (EVBR) problem, which aims to realise the optimal resource allocation and pricing of EVBR. The main motivation of this paper is to attempt to explore an approach to achieving efficient battery recycling. We first consider an EVBR market with m buyers and n sellers, and develop the multi-unit trade reduction (MTR) mechanism in the EVBR market. According to the supply and demand relationship in the EVBR market, we consider three market scenarios of supply and demand balance, oversupply, and overdemand, and formulated corresponding auction allocation rules. Numerical study results show that the proposed MTR mechanism can achieve efficient resource allocation. We also observed that not all results increased with the number of sellers/buyers. Second, considering the distance between sellers and buyers, we developed a stochastic multiple MTR (SM-MTR) mechanism to enable sellers and buyers within the region to conduct transactions. Finally, we propose an integrated MTR, SM-MTR and one-sided Vickrey–Clarke–Groves auction mechanism that is feasible in both one-sided and bilateral environments. Furthermore, our work can provide novel managerial implications for EVBR market stakeholders in terms of practical application.
Journal: International Journal of Production Research
Pages: 8598-8617
Issue: 24
Volume: 61
Year: 2023
Month: 12
X-DOI: 10.1080/00207543.2022.2157904
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2157904
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# input file: TPRS_A_2248280_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Georgios Karagiannis
Author-X-Name-First: Georgios
Author-X-Name-Last: Karagiannis
Author-Name: Ioannis Minis
Author-X-Name-First: Ioannis
Author-X-Name-Last: Minis
Author-Name: Christina Arampantzi
Author-X-Name-First: Christina
Author-X-Name-Last: Arampantzi
Author-Name: Georgios Dikas
Author-X-Name-First: Georgios
Author-X-Name-Last: Dikas
Title: Warehousing and distribution network design from a third-party logistics (3PL) company perspective
Abstract: 
 This paper deals with the problem of optimising the network of a Third-Party Logistics (3PL) company, placing emphasis on the distinct characteristics of the 3PL environment. The goal is to minimise the warehousing and distribution costs for both forward and reverse product flows. A new Mixed Integer Linear Program (MILP) model is proposed to address this interesting problem. The related decisions include: selection of (a) warehouse(s) and the related product inventory quantities, (b) product unit loads transported, (c) truck combinations employed to perform the corresponding forward and reverse trips. The model was applied in a case study of a 3PL company to optimise part of its forward supply chain that comprises three warehouses, 23 suppliers and 53 customers. The results obtained were very encouraging, since overall warehousing and distribution costs were lowered by 10.8%. Sensitivity analysis indicated that additional savings may result from optimising warehousing capacities. The main contributions of this work are the inclusiveness of key aspects of the 3PL environment in the proposed model, as well as placing emphasis on warehousing costs and on management of truck capacities. A secondary contribution is the validation of the model’s value through a comprehensive case study.
Journal: International Journal of Production Research
Pages: 260-270
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2248280
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2248280
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# input file: TPRS_A_2233621_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Title: A new MIP approach for balancing and scheduling of mixed model assembly lines with alternative precedence relations
Abstract: 
 In this paper, a new mixed integer programming (MIP) formulation is developed for balancing and scheduling of mixed model assembly lines with disjunctive precedence constraints among assembly tasks. To represent alternative precedence relations, AND/OR assembly graph was adopted. In case of alternative precedence relations, for each product multiple assembly plans exist, which can be represented by a set of alternative precedence subgraphs and only one of such subgraphs should be selected for each product. As the number of subgraphs exponentially increases with the number of disjunctive relations among the tasks, the computational complexity of simultaneous balancing and scheduling along with the assembly subgraph selection increases with the number of alternative precedence relations. Unlike the other MIP approaches known from the literature, the new model does not need the alternative assembly subgraphs to be to explicitly enumerated as input data and then used for indexing the variables. Instead, a new disjunctive precedence selection and task assignment variable and new constraints are introduced to optimally choose one relation for each subset of alternative precedence relations. The optimal solutions for computational examples of balancing and scheduling problems illustrate a superior performance of the new modelling approach.
Journal: International Journal of Production Research
Pages: 110-121
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2233621
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2233621
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# input file: TPRS_A_2228922_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Xin Feng
Author-X-Name-First: Xin
Author-X-Name-Last: Feng
Author-Name: Hongjun Peng
Author-X-Name-First: Hongjun
Author-X-Name-Last: Peng
Title: Robust identical parallel machine scheduling with two-stage time-of-use tariff and not-all-machine option
Abstract: 
 Time-of-use (TOU) tariff has been implemented in the manufacturing industry to improve energy efficiency by regulating the electricity imbalance between supply and demand. Besides, not-all-machine (NAM) option is another way of energy-saving by using only a subset of all the available machines. This study investigates a robust identical parallel machine scheduling problem with a two-stage TOU tariff and NAM option. Only interval bounds on job processing times are known. The problem is first formulated into a min–max regret model to maximise the robustness. Based on problem properties, both an iterative relaxation-based exact algorithm and a memetic differential evolution-based heuristic are developed to solve the problem. Computational experiments on 240 randomly generated instances with up to 20 jobs are conducted to evaluate the performance of the developed methods. Besides, 900 large-sized randomly generated instances with up to 150 jobs are tested for sensitivity analysis and to identify managerial insights for achieving energy-efficient schedules.
Journal: International Journal of Production Research
Pages: 380-403
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2228922
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2228922
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# input file: TPRS_A_2285424_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Riccardo Aldrighetti
Author-X-Name-First: Riccardo
Author-X-Name-Last: Aldrighetti
Author-Name: Martina Calzavara
Author-X-Name-First: Martina
Author-X-Name-Last: Calzavara
Author-Name: Michele Martignago
Author-X-Name-First: Michele
Author-X-Name-Last: Martignago
Author-Name: Ilenia Zennaro
Author-X-Name-First: Ilenia
Author-X-Name-Last: Zennaro
Author-Name: Daria Battini
Author-X-Name-First: Daria
Author-X-Name-Last: Battini
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: A methodological framework for the design of efficient resilience in supply networks
Abstract: 
 Disruptions can adversely affect profitability, service level, and even the viability of supply networks (SNs). Natural disasters, the COVID-19 pandemic, and geopolitical tensions heightened disruption risks for SNs. We propose a methodological framework to guide the design of resilient SNs, with a focus on efficient resilience. In fact, despite an increasing economic and social interest in SN resilience and a large variety of qualitative resilience frameworks, there is a lack of model-based frameworks to guide decision makers in the complex task of designing resilient SNs. Differently to the existing literature, that mostly focuses on industry- or disruption-specific approaches, the framework of this paper is general, independent from sectors and causes. It consists of three steps to guide practitioners through model-based stress testing of their SNs: it integrates and organises methods from the literature, from the selection of data to be collected to the validation of the resilient and efficient SN. We illustrate the application of descriptive, predictive, and prescriptive analytics at each phase using real-life case studies data supplemented by literature references. Finally, we present an industrial case study with the step-by-step application of the framework highlighting its strengths and objectives.
Journal: International Journal of Production Research
Pages: 271-290
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2285424
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2285424
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# input file: TPRS_A_2287400_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Rakesh Nagi
Author-X-Name-First: Rakesh
Author-X-Name-Last: Nagi
Author-Name: Xiaolan Xie
Author-X-Name-First: Xiaolan
Author-X-Name-Last: Xie
Title: Special issue in memory of Dr. Jean-Marie Proth (7.12.1938–17.06.2021)
Abstract: 
 Issues 1 and 2 of 2024 are composed of papers selected for the special section in memory of Dr. Jean-Marie Proth. Some papers are extended versions of articles presented at the 10th IFAC MIM 2022 conference (hub.imt-atlantique.fr/mim2022/) in the invited sessions in memory of Dr. Proth.
Journal: International Journal of Production Research
Pages: 1-6
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2287400
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2287400
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# input file: TPRS_A_2276825_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Amina Haned
Author-X-Name-First: Amina
Author-X-Name-Last: Haned
Author-Name: Abida Kerdali
Author-X-Name-First: Abida
Author-X-Name-Last: Kerdali
Author-Name: Mourad Boudhar
Author-X-Name-First: Mourad
Author-X-Name-Last: Boudhar
Title: Scheduling on identical machines with preemption and setup times
Abstract: 
 In this paper, we address the problem of scheduling jobs on identical machines for minimising the maximum completion time (makespan). Each job requires a sequence-independent setup time, which represents the time needed to prepare the machines for job execution. Then, we introduce a dynamic programme to solve the case with two machines, and show that this problem admits a fully polynomial time approximation scheme. For the case of m machines, we propose heuristics and an adapted genetic algorithm. Some numerical experiments are done to evaluate the proposed algorithms.
Journal: International Journal of Production Research
Pages: 444-459
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2276825
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2276825
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# input file: TPRS_A_2289182_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Nikolai Guschinsky
Author-X-Name-First: Nikolai
Author-X-Name-Last: Guschinsky
Title: An exact method for machining lines design with equipment selection and line balancing
Abstract: 
 We consider the context of machining systems design where both equipment selection and line balancing decisions have to be taken in order to minimise the total cost of the system. The designed flow line employs multi-positional machines with rotary tables where vertical and horizontal machining modules can be used for the realisation of machining processes. For this challenging optimisation problem in production research, we develop an innovative mathematical model based on a mixed-integer linear programme and a heuristic algorithm for an approximate solution. An extensive numerical experiment is conducted in order to evaluate the performances of the proposed mathematical model and the developed heuristic. The obtained results show that the decision makers can use the elaborated methods for solving efficiently even large-scale industrial problems.
Journal: International Journal of Production Research
Pages: 71-91
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2289182
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2289182
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# input file: TPRS_A_2275634_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Ioannis Avgerinos
Author-X-Name-First: Ioannis
Author-X-Name-Last: Avgerinos
Author-Name: Ioannis Mourtos
Author-X-Name-First: Ioannis
Author-X-Name-Last: Mourtos
Author-Name: Stavros Vatikiotis
Author-X-Name-First: Stavros
Author-X-Name-Last: Vatikiotis
Author-Name: Georgios Zois
Author-X-Name-First: Georgios
Author-X-Name-Last: Zois
Title: Weighted tardiness minimisation for unrelated machines with sequence-dependent and resource-constrained setups
Abstract: 
 Motivated by the need of quick job (re-)scheduling, we examine an elaborate scheduling environment under the objective of total weighted tardiness minimisation. The examined problem variant moves well beyond existing literature, as it considers unrelated machines, sequence-dependent and machine-dependent setup times, and a renewable resource constraint on the number of simultaneous setups. For this variant, we provide a relaxed MILP to calculate lower bounds, thus estimating a worst-case optimality gap. As a fast exact approach appears not plausible for instances of practical importance, we extend known (meta-)heuristics to deal with the problem at hand, coupling them with a Constraint Programming (CP) component – vital to guarantee the non-violation of the problem's constraints – which optimally allocates resources with respect to tardiness minimisation. The validity and versatility of employing different (meta-)heuristics exploiting a relaxed MILP as a quality measure are revealed by our extensive experimental study, which shows that the methods deployed have complementary strengths depending on the instance parameters. Since the problem description has been obtained from a textile manufacturer where jobs of diverse size arrive continuously under tight due dates, we also discuss the practical impact of our approach in terms of both tardiness decrease and broader managerial insights.
Journal: International Journal of Production Research
Pages: 359-379
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2275634
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2275634
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# input file: TPRS_A_2223725_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Sihan Huang
Author-X-Name-First: Sihan
Author-X-Name-Last: Huang
Author-Name: Jiaxin Tan
Author-X-Name-First: Jiaxin
Author-X-Name-Last: Tan
Author-Name: Yuqian Lu
Author-X-Name-First: Yuqian
Author-X-Name-Last: Lu
Author-Name: Shokraneh K. Moghaddam
Author-X-Name-First: Shokraneh K.
Author-X-Name-Last: Moghaddam
Author-Name: Guoxin Wang
Author-X-Name-First: Guoxin
Author-X-Name-Last: Wang
Author-Name: Yan Yan
Author-X-Name-First: Yan
Author-X-Name-Last: Yan
Title: A multi-objective joint optimisation method for simultaneous part family formation and configuration design in delayed reconfigurable manufacturing system (D-RMS)
Abstract: 
 In the era of Industry 4.0, the demand fluctuation has become fiercer due to the characteristics of diversification, customisation, and uncertainty. Reconfigurability of manufacturing systems has been proven to be a useful and necessary feature when it comes to handling demand uncertainty. This feature can be achieved through the implementation of reconfigurable manufacturing system (RMS) and delayed reconfigurable manufacturing system (D-RMS). D-RMS is a subclass of RMS that focuses primarily on improving the convertibility of the manufacturing system. The two main phases involved in implementing D-RMS are part family formation and configuration design. Therefore, we proposed a multi-objective joint optimisation method of part family formation and configuration design according to the philosophy of D-RMS. Firstly, we develop a multi-objective joint optimisation model that takes into account investment cost, reconfiguration cost, similarity coefficient, and delayed reconfiguration to optimise the part family and configuration of D-RMS simultaneously. Three types of machine tools namely dedicated machine tools, flexible machine tools, and reconfigurable machine tools are considered in the optimisation model. Secondly, the non-dominated sorting genetic algorithm-III (NSGA-III) is adopted to solve the proposed multi-objective integer programming problem. Finally, numerical experiments are presented to demonstrate the effectiveness of the proposed multi-objective joint optimisation method.
Journal: International Journal of Production Research
Pages: 92-109
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2223725
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:1-2:p:92-109



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# input file: TPRS_A_2238084_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: M. Thenarasu
Author-X-Name-First: M.
Author-X-Name-Last: Thenarasu
Author-Name: K. Rameshkumar
Author-X-Name-First: K.
Author-X-Name-Last: Rameshkumar
Author-Name: M. Di Mascolo
Author-X-Name-First: M.
Author-X-Name-Last: Di Mascolo
Author-Name: S.P. Anbuudayasankar
Author-X-Name-First: S.P.
Author-X-Name-Last: Anbuudayasankar
Title: Multi-criteria scheduling of realistic flexible job shop: a novel approach for integrating simulation modelling and multi-criteria decision making
Abstract: 
 Increased flexibility in job shops leads to more complexity in decision-making for shop floor engineers. Partial Flexible Job Shop Scheduling (PFJSS) is a subset of Job shop problems and has substantial application in the real world. Priority Dispatching Rules (PDRs) are simple and easy to implement for making quick decisions in real-time. The present study proposes a novel method of integrating Multi-Criteria Decision Making (MCDM) methods and the Discrete Event Simulation (DES) Model to define job priorities in large-scale problems involving multiple criteria. DES approach is employed to model the PFJSS to evaluate Makespan, Flow Time, and Tardiness-based measures considering static and dynamic job arrivals. The proposed approach is implemented in a benchmark problem and large-scale PFJSS. The integration of MCDM methods and simulation models offers the flexibility to choose the parameters that need to govern the ranking of jobs. The solution given by the proposed methods is tested with the best-performing Composite Dispatching Rules (CDR), combining several PDR, which are available in the literature. Proposed MCDM approaches perform well for Makespan, Flow Time, and Tardiness-based measures for large-scale real-world problems. The proposed methodology integrated with the DES model is easy to implement in a real-time shop floor environment.
Journal: International Journal of Production Research
Pages: 336-358
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2238084
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2238084
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# input file: TPRS_A_2279129_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Paula Terán-Viadero
Author-X-Name-First: Paula
Author-X-Name-Last: Terán-Viadero
Author-Name: Antonio Alonso-Ayuso
Author-X-Name-First: Antonio
Author-X-Name-Last: Alonso-Ayuso
Author-Name: F. Javier Martín-Campo
Author-X-Name-First: F.
Author-X-Name-Last: Javier Martín-Campo
Title: A 2-dimensional guillotine cutting stock problem with variable-sized stock for the honeycomb cardboard industry
Abstract: 
 This paper introduces novel mathematical optimisation models for the 2-Dimensional guillotine Cutting Stock Problem with Variable-Sized Stock that appears in a Spanish company in the honeycomb cardboard industry. This problem mainly differs from the classical cutting stock problems in the stock, which is considered variable-sized, i.e. we have to decide the panel dimensions, width, and length. This approach is helpful in industries where the stock is produced simultaneously with the cutting process. The stock is then cut into smaller rectangular pieces that must meet the customers' requirements, such as the type of item, dimensions, demands, and technical specifications. Furthermore, in the problem tackled in this paper, the cuts are guillotine, performed side to side. The proposed mathematical models are validated using real data from the company, obtaining results that drastically reduce the produced material and leftovers, reducing operation times and economic costs.
Journal: International Journal of Production Research
Pages: 483-500
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2279129
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2279129
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:1-2:p:483-500



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# input file: TPRS_A_2238083_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Andrew Kusiak
Author-X-Name-First: Andrew
Author-X-Name-Last: Kusiak
Title: Federated explainable artificial intelligence (fXAI): a digital manufacturing perspective
Abstract: 
 The industry has embraced digitalisation leading to a greater reliance on models derived from data. Understanding and getting insights into the models generated by machine learning algorithms is a challenge due to their non-explicit nature. Explainable artificial intelligence (XAI) is to enhance understanding of the digital models and confidence in the results they produce. The paper makes two contributions. First, the XRule algorithm proposed in the paper generates explicit rules meeting user’s preferences. A user may control the nature of the rules generated by the XRule algorithm, e.g. degree of redundancy among the rules. Second, in analogy to federated learning, the concept of federated explainable artificial intelligence (fXAI) is proposed. Besides providing insights into the models built from data and explaining the predicted decisions, the fXAI provides additional value. The user-centric knowledge generated in support of fXAI may lead to discovery of previously unknown parameters and subsequently models that may benefit the non-explicit and explicit perspectives. The insights from fXAI could translate into new ways of modelling the phenomena of interest. A numerical example and three industrial applications illustrate the concepts presented in the paper.
Journal: International Journal of Production Research
Pages: 171-182
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2238083
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2238083
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# input file: TPRS_A_2284833_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Marvin Carl May
Author-X-Name-First: Marvin
Author-X-Name-Last: Carl May
Author-Name: Christian Nestroy
Author-X-Name-First: Christian
Author-X-Name-Last: Nestroy
Author-Name: Leonard Overbeck
Author-X-Name-First: Leonard
Author-X-Name-Last: Overbeck
Author-Name: Gisela Lanza
Author-X-Name-First: Gisela
Author-X-Name-Last: Lanza
Title: Automated model generation framework for material flow simulations of production systems
Abstract: 
 Owing to increasingly important drivers for change, such as automation, digitisation, and dynamic demand patterns, simulation models of production systems become outdated rapidly. At the same time, building simulation models often requires much time, cost, and expertise, especially when dealing with complex job shop production systems. To address these challenges, an automated simulation model generation (ASMG) framework for material flow simulation of production systems is presented. This framework contains multiple approaches to infer routeing, control and temporal aspects from event-based data. To achieve this, methods from process mining (PM) and machine learning (ML) are applied. Additionally, the suitability of Coloured Petri Nets (CPNs) to serve as conceptual and operational simulation models is examined. The inferred simulation models have high validity when compared to the real system concerning the KPIs machine utilisation, throughput, and work in process. It is shown, that most model elements can be inferred very well, in particular process routes, processing times, and resource selection rules. This proof of concept serves as a foundation for research on detection approaches inferring further model elements such as setup times accurately.
Journal: International Journal of Production Research
Pages: 141-156
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2284833
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2284833
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# input file: TPRS_A_2242968_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Alain Bensoussan
Author-X-Name-First: Alain
Author-X-Name-Last: Bensoussan
Author-Name: Fouad El Ouardighi
Author-X-Name-First: Fouad
Author-X-Name-Last: El Ouardighi
Title: Voluntary environmental effort under (s,S) inventory policy*
Abstract: 
 Prior research on inventory control has been wide ranging, yet the environmental implications of an 
 $ ({s,S} ) $ (s,S) inventory policy remain uninvestigated. This paper seeks to bridge the gap by characterising a firm’s voluntary environmental policy in the setup of an 
 $ ({s,S} ) $ (s,S) inventory control policy. We suggest a mixed model structure wherein, due to the presence of fixed production costs, the inventory is determined continuously by sales and impulsively with ordering decisions obeying an optimal stopping process, while the uncertain sales process is controlled by continuous-time environmental goodwill-related decisions. We show that a firm should successively use voluntary environmental efforts to stimulate its sales when there is inventory and to increase backlogging to improve its production efficiency. Given the recurrent pattern of this policy, we conclude that voluntary environmental efforts under an 
 $ ({s,S} ) $ (s,S) inventory control is not compatible with using these efforts as a means to generate ephemeral reputation insurance.
Journal: International Journal of Production Research
Pages: 522-535
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2242968
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2242968
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:1-2:p:522-535



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# input file: TPRS_A_2233626_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Ibrahim Kucukkoc
Author-X-Name-First: Ibrahim
Author-X-Name-Last: Kucukkoc
Author-Name: Gulsen Aydin Keskin
Author-X-Name-First: Gulsen
Author-X-Name-Last: Aydin Keskin
Author-Name: Aslan Deniz Karaoglan
Author-X-Name-First: Aslan Deniz
Author-X-Name-Last: Karaoglan
Author-Name: Sevgi Karadag
Author-X-Name-First: Sevgi
Author-X-Name-Last: Karadag
Title: A hybrid discrete differential evolution – genetic algorithm approach with a new batch formation mechanism for parallel batch scheduling considering batch delivery
Abstract: 
 Scheduling is an important decision-making problem in production planning and the resulting decisions have a direct impact on reducing waste, including energy and idle capacity. Batch scheduling problems occur in various industries from automotive to food and energy. This paper introduces the parallel p-batch scheduling problem with batch delivery, content-dependent loading/unloading times and energy-aware objective function. The problem has been motivated by a real system used for freezing products in a food processing company. A mixed-integer linear programming model (MILP) has been developed and explained through a numerical example. As it is not practical to solve large-size instances via a mathematical model, the discrete differential evolution algorithm has been improved (iDDE) and hybridised with the genetic algorithm (GA). A release-oriented vector generation procedure and a heuristic batch formation mechanism have been developed to efficiently solve the problem. The performance of the proposed approach (iDDEGA) has been compared with CPLEX, iDDE and GA through a comprehensive computational study. A case study was conducted based on real data collected from the freezing process of the company, which also verified the practical use and advantages of the proposed methodology.
Journal: International Journal of Production Research
Pages: 460-482
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2233626
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2233626
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# input file: TPRS_A_2267693_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Ruilin Pan
Author-X-Name-First: Ruilin
Author-X-Name-Last: Pan
Author-Name: Qiong Wang
Author-X-Name-First: Qiong
Author-X-Name-Last: Wang
Author-Name: Jianhua Cao
Author-X-Name-First: Jianhua
Author-X-Name-Last: Cao
Author-Name: Chunliu Zhou
Author-X-Name-First: Chunliu
Author-X-Name-Last: Zhou
Title: Deep reinforcement learning for solving steelmaking-continuous casting scheduling problems under time-of-use tariffs
Abstract: 
 This paper proposes a novel intelligent scheduling method based on deep reinforcement learning (DRL) to solve the multi-objective steelmaking-continuous casting (SCC) scheduling problem, under time-of-use (TOU) tariffs for the first time. The intelligent scheduling system architecture is designed, and a mathematical model is established to minimise the total sojourn time and electricity cost. To effectively reduce production costs by avoiding peak periods of electricity consumption, the ‘start time’ of the system is generated based on the Markov Decision Process (MDP), and heuristic scheduling rules related to power cost are used as the action space, with corresponding reward functions designed according to the characteristics of these two objectives. To satisfy the continuous casting which is a particular SCC constraint, a backward strategy is developed. Additionally, a branching duelling double deep Q-network (BD3QN) is adapted to guide action selection and avoid blind search in the iteration process, and then applied to real-time scheduling. Numerical experiments demonstrate that the proposed method outperforms comparison algorithms in terms of solution quality and CPU times by a large margin.
Journal: International Journal of Production Research
Pages: 404-420
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2267693
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2267693
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# input file: TPRS_A_2252937_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Li Xue
Author-X-Name-First: Li
Author-X-Name-Last: Xue
Author-Name: Yantong Li
Author-X-Name-First: Yantong
Author-X-Name-Last: Li
Author-Name: Zheng Wang
Author-X-Name-First: Zheng
Author-X-Name-Last: Wang
Author-Name: Sai-Ho Chung
Author-X-Name-First: Sai-Ho
Author-X-Name-Last: Chung
Author-Name: Xin Wen
Author-X-Name-First: Xin
Author-X-Name-Last: Wen
Title: Distributed appointment assignment and scheduling under uncertainty
Abstract: 
 We investigate a stochastic distributed appointment assignment and scheduling problem, which consists of assigning appointments to distributed service units and determining service sequences at each service unit. In particular, the service time duration and release time uncertainties are well-considered. The solution to this generic problem finds interesting applications in distributed production systems, healthcare systems, and post-disaster operations. We formulate the problem as a two-stage stochastic program to minimise the total transportation cost and expected makespan, idle time or overtime, and apply the sample average approximation method to make the problem tractable. We then develop a stochastic logic-based Benders decomposition method, decomposing the problem into a master problem and a subproblem. The master problem determines the appointment assignment variables, and the subproblem handles the sequence and service start time variables. Benders optimality cuts are generated from the subproblem's solution and added to the master problem. The developed stochastic logic-based method is advantageous since it can manage many scenarios in parallel. We further consider each appointment's due date, minimise the weighted earliness and tardiness, and adjust the developed method to solve this variant. Experiments on random instances demonstrate the excellent performance of the proposed model and methods.
Journal: International Journal of Production Research
Pages: 318-335
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2252937
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2252937
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# input file: TPRS_A_2230324_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yunqiang Yin
Author-X-Name-First: Yunqiang
Author-X-Name-Last: Yin
Author-Name: Jie Wang
Author-X-Name-First: Jie
Author-X-Name-Last: Wang
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Dujuan Wang
Author-X-Name-First: Dujuan
Author-X-Name-Last: Wang
Title: Distributionally robust multi-period humanitarian relief network design integrating facility location, supply inventory and allocation, and evacuation planning
Abstract: 
 Facility location, supply inventory and distribution, and evacuation planning are key operational functions in a humanitarian relief network, it is critical to integrate these three functions and schedule their activities jointly in a coordinated manner. Considering uncertain demands and evacuation rates of injured people, we develop a distributionally robust model for the multi-period humanitarian relief network design with multiple types of relief supplies. To solve the problem, we reformulate the proposed model into a mixed integer linear programme, and develop an enhanced branch-and-Benders-cut algorithm that incorporates some algorithm enhancements to solve the resulting model. Extensive numerical experiments show that: (i) the distributionally robust model provides more reliable and flexible solutions that perform the best when faced uncertainty over the deterministic and stochastic models; (ii) the algorithm enhancements are very effective to enhance the performance of the proposed algorithm, which can reduce the CPU time by up to 9.75%∼41.64% on average; (iii) the integrated solution approach is more beneficial to solve the problem when comparing with a sequential solution approach; and (iv) some model parameters have significant impact on the solution structure, which can help decision maker set proper parameters to achieve the desired trade-off among the considered metrics.
Journal: International Journal of Production Research
Pages: 45-70
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2230324
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2230324
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# input file: TPRS_A_2254408_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Francesco Facchini
Author-X-Name-First: Francesco
Author-X-Name-Last: Facchini
Author-Name: Giorgio Mossa
Author-X-Name-First: Giorgio
Author-X-Name-Last: Mossa
Author-Name: Claudio Sassanelli
Author-X-Name-First: Claudio
Author-X-Name-Last: Sassanelli
Author-Name: Salvatore Digiesi
Author-X-Name-First: Salvatore
Author-X-Name-Last: Digiesi
Title: IoT-based milk-run routing for manufacturing system: an application case in an automotive company
Abstract: 
 The Internet of Things (IoT) provides new opportunities to improve manufacturing lines’ performance and in-plant logistic processes. The digital milk-run system represents the new frontier to optimize material handling strategies but is still not fully exploited to address material distribution depending on the time slots required by the manufacturing lines. Therefore, to fill this gap, this paper investigates the actual integration of the milk-run system with an IoT system. An analytical model for planning a dynamic routing strategy for tugger trains to deliver the materials to different workstations of a production line has been developed. The proposed model provides a materials distribution consistent with the time slot required by the manufacturing line, ensuring the minimisation of the total distance of the routes. An algorithm developed in Python is proposed to solve the NP-hard problem (nondeterministic polynomial time problem). The model has been applied to a real case of a worldwide automotive company to validate and prove its efficacy and efficiency. Indeed, compared to the current in-plant logistic strategy, (i) the inventory stock of each workstation was ensured, (ii) the average utilization rate of the tugger trains’ fleet was improved, and (iii) the daily path was minimized.
Journal: International Journal of Production Research
Pages: 536-555
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2254408
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2254408
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# input file: TPRS_A_2217310_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Sanchit Singh
Author-X-Name-First: Sanchit
Author-X-Name-Last: Singh
Author-Name: Subhash C. Sarin
Author-X-Name-First: Subhash C.
Author-X-Name-Last: Sarin
Title: Modeling and analysis of a new production methodology for achieving mass customization
Abstract: 
 In this paper, we address a Stochastic-Demand Assembly Job Shop Scheduling Problem (SD-AJSSP) in the presence of the commonality of sub-assemblies across products. We propose a new production methodology, named Assemble-to-Order with Commonality of Sub-Assemblies (ATO-CS) to not only solve the SD-AJSSP, but also, achieve a successful implementation of a mass customisation system by collectively aiming to (1) keep the production costs low by leveraging upon commonality of sub-assemblies in products’ BOM and producing sub-assemblies on a mass scale during one of the two stages of production, (2) minimise the loss due to excess inventory build-up in anticipation of stochastic demand of products by postponing the production of certain apex sub-assemblies in products’ BOM until the actual demand is realised, and (3) reduce the time of the products’ delivery to customers. The ATO-CS method determines optimum production levels as well as schedules assembly operations/jobs over the machines at each stage of production, where the second stage is an assembly job shop and is shown to outperform commonly-used production methodologies. We also develop an algorithm for its implementation and show its efficacy over the use of the state-of-the-art commercial solver CPLEX® in obtaining a lower solution cost and smaller optimality gap.
Journal: International Journal of Production Research
Pages: 183-203
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2217310
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217310
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# input file: TPRS_A_2217285_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Oliver Antons
Author-X-Name-First: Oliver
Author-X-Name-Last: Antons
Author-Name: Julia C. Arlinghaus
Author-X-Name-First: Julia C.
Author-X-Name-Last: Arlinghaus
Title: Designing distributed decision-making authorities for smart factories – understanding the role of manufacturing network architecture
Abstract: 
 The availability of cyber-physical systems (CPS) in modern manufacturing networks provides a multitude of interesting opportunities from a manufacturing control perspective. Providing sensors, data gathering, local computation and communication capabilities modern CPS fulfil the technical requirements to act completely autonomously in a manufacturing network. While the distribution of decision-making authority to autonomous entities is feasible given such requirements, practice often sees the monopolisation of decision-making authority for centralised control. However, distributed production control approaches might be better suited given current manufacturing challenges, ranging from unreliable supply chains over highly volatile markets, to the demand for increasingly efficient and highly customisable production. In this article, we extend an existing scheduling complexity framework which enables practitioners and researchers alike to assess the aptitude of given manufacturing networks for both centralised and distributed control. In particular, we study the influence of a manufacturing network's topology ranging from assembly line to job shops on the aforementioned aptitude, with total production costs as objective.We utilise a multi-agent-based discrete-event simulation comparing an MILP-based centralised control approach and an autonomy based distributed control approach with weighted costs as decision function to evaluate this framework. Our results provide novel insights regarding the influence of manufacturing network topologies on the scheduling complexity of manufacturing networks.
Journal: International Journal of Production Research
Pages: 204-222
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2217285
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217285
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2283577_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Rocío Alfaro-Pozo
Author-X-Name-First: Rocío
Author-X-Name-Last: Alfaro-Pozo
Author-Name: Joaquín Bautista-Valhondo
Author-X-Name-First: Joaquín
Author-X-Name-Last: Bautista-Valhondo
Title: Impact of limiting the ergonomic risk on the economic and productive efficiency of an assembly line
Abstract: 
 Considering ergonomics at the design phase can lead to assembly lines that protect and improve workers’ health and well-being. However, this may reduce efficiency and productivity. Evaluating the potential benefits of incorporating ergonomics into line design versus the additional costs associated with the number of extra stations required or increased idle time, as well as exploring other ergonomic design alternatives, is critical for decision-makers. An assembly line balancing problem considering time, space and ergonomics, is used to evaluate the impact of ergonomic considerations. A model for maximising line efficiency is proposed and linearised for solution by the solver CPLEX. The mixed-integer linear model is compared to an alternative linearisation approach in which a decision variable is parameterised and then iteratively solved. An example and a case study are used to observe the competitiveness of both solution methods, where the iterative approach is shown to be superior for real size problems. The results show that ergonomic evaluation in line design leads to safer but less productive lines, which in turn increases the number of workstations and costs. Specifically, limiting ergonomic risk to a moderate level for the engine assembly line examined in this study, means maximum daily drop of 27 engines.
Journal: International Journal of Production Research
Pages: 122-140
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2283577
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2283577
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2284207_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Ketan Date
Author-X-Name-First: Ketan
Author-X-Name-Last: Date
Author-Name: Rakesh Nagi
Author-X-Name-First: Rakesh
Author-X-Name-Last: Nagi
Title: Optimal placement of multiple finite-size rectangular facilities in an existing layout
Abstract: 
 In this paper, we investigate a new problem of optimal placement of multiple finite-size rectangular facilities with known dimensions in the presence of existing rectangular facilities. This problem has applications in facility layout (re)design in manufacturing, distribution systems, services, and electronic circuit design. Three types of facility interactions are considered: between new facilities and existing facilities; between pairs of existing facilities; and between pairs of new facilities. All interactions are serviced through a finite number of input/output points located on the facility boundaries. Travel is assumed to occur according to the rectilinear (or Manhattan) metric and travel through facilities is prohibited. The objective is to find the simultaneous and non-overlapping placement of new facilities, which minimises the total weighted distance (Minisum objective) between the interacting facilities. To arrive at a solution, we divide the feasible region into sub-regions and prove that the candidates for optimal placement of the new facilities can be drawn from the sub-region boundaries. Being a continuous generalisation of the quadratic assignment problem, the solution complexity of this procedure is exponential in the number of new facilities. Our main contribution is the rigorous treatment of an important problem that unifies facility location and layout theories with minisum objective and rectilinear metrics.
Journal: International Journal of Production Research
Pages: 7-23
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2284207
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2284207
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:1-2:p:7-23



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# input file: TPRS_A_2276808_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Lei Wang
Author-X-Name-First: Lei
Author-X-Name-Last: Wang
Author-Name: Haoxun Chen
Author-X-Name-First: Haoxun
Author-X-Name-Last: Chen
Title: A decomposition and coordination method for optimising (Q, S) policies in a two-echelon distribution system with joint replenishment
Abstract: 
 A continuous-review, two-echelon distribution system with one central distribution centre (CDC) and multiple regional distribution centres (RDCs) is studied. The CDC jointly replenishes its inventories of multiple items from an external supplier, while each RDC replenishes its inventories of the items from the CDC. Each RDC faces a Poisson demand for each item, and the inventories of each stock in the system are controlled by a (Q, S) policy. Under this policy, an order is placed by a stock whenever its aggregate demand since the last order reaches a given quantity, and the inventory position of each item is raised up to its order-up-to level after the order placement. The objective is to optimise these (Q, S) policies so that the expected total cost of this system is minimised. We propose a decomposition and coordination method for this optimisation after deriving analytically the cost function of the system. Our extensive numerical experiments demonstrate the effectiveness of the proposed method. Furthermore, a parameter sensitivity analysis is conducted to analyse the impacts of some key system parameters on the performance of the method, and managerial insights are provided for optimising distribution systems with joint replenishment and real applications of the method.
Journal: International Journal of Production Research
Pages: 556-573
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2276808
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2276808
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# input file: TPRS_A_2219768_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Daqin Wang
Author-X-Name-First: Daqin
Author-X-Name-Last: Wang
Author-Name: Ou Tang
Author-X-Name-First: Ou
Author-X-Name-Last: Tang
Author-Name: Lihua Zhang
Author-X-Name-First: Lihua
Author-X-Name-Last: Zhang
Title: Inventory stacking with partial information
Abstract: 
 An inventory stacking decision assigns positions to items which are stacked vertically, such as containers in container terminals and steel plates in steel plants. The performance of stacking decisions is greatly affected by the arrival and departure information on items. We study an inventory stacking problem with partial information based on industrial observation in a steel plant. On the inbound side, we investigate three levels of information on future arriving items and their effect on performance. On the outbound side, we study the impact of the retrieval sequence, which is often random. We develop models incorporating different availabilities of information and determine stacking strategies. The study shows that the stacking strategy and stacking performance depend highly on information quality and space utilisation. Especially, when the space utilisation is high, low-quality information deteriorates the performance and such information should be ignored. This contradicts the general belief that more information should bring better performance. The study further proposes a time window allocation approach to reduce the uncertainty in retrieval, and it is effective in improving stacking performance.
Journal: International Journal of Production Research
Pages: 586-604
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2219768
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2219768
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:1-2:p:586-604



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# input file: TPRS_A_2300340_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Suresh P. Sethi
Author-X-Name-First: Suresh P.
Author-X-Name-Last: Sethi
Author-Name: Anshuman Chutani
Author-X-Name-First: Anshuman
Author-X-Name-Last: Chutani
Title: Forecast and decision horizons in a commodity trading model
Abstract: 
 Forecasts of demands or prices become increasingly unreliable as the future becomes more distant. It is, therefore, beneficial to show that optimal decisions during an initial time interval are either partially or wholly independent of the forecasted data from some future time onwards. Using a commodity trading model as an example, we obtain conditions that allow us to make optimal buying and selling decisions for a commodity in some initial time interval without knowing its price forecast beyond some future time. Such an initial time interval is called a decision horizon and the time up to which the forecasted data is required to make the optimal decisions during the decision horizon is called a forecast horizon. We use the maximum principle to solve the example and show that the decision and forecast horizons in the problem arise from lower and upper bounds imposed on the on-hand inventory of the commodity.
Journal: International Journal of Production Research
Pages: 245-259
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2300340
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2300340
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:1-2:p:245-259



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2288722_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Milad Elyasi
Author-X-Name-First: Milad
Author-X-Name-Last: Elyasi
Author-Name: Başak Altan
Author-X-Name-First: Başak
Author-X-Name-Last: Altan
Author-Name: Ali Ekici
Author-X-Name-First: Ali
Author-X-Name-Last: Ekici
Author-Name: Okan Örsan Özener
Author-X-Name-First: Okan Örsan
Author-X-Name-Last: Özener
Author-Name: İhsan Yanıkoğlu
Author-X-Name-First: İhsan
Author-X-Name-Last: Yanıkoğlu
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Production planning with flexible manufacturing systems under demand uncertainty
Abstract: 
 This paper delves into the impacts of an ongoing global crisis on the resilience of supply chains. Furthermore, it proposes measures to address and mitigate the disruptions caused by the prevailing uncertainties. For example, while the economy has started to recover after the pandemic and demand has increased, companies have not fully returned to their pre-pandemic levels. To enhance their supply chain resilience and effectively manage disruptions, one viable strategy is the implementation of flexible/hybrid manufacturing systems. This research is motivated by the specific requirements of Vestel Electronics, a household appliances company, which seeks a flexible/hybrid manufacturing production setup involving dedicated machinery to meet regular demand and the utilisation of flexible manufacturing system (FMS) to handle surges in demand. We employ a scenario-based approach to model demand uncertainty, enabling the company to make immediate and adaptive decisions that take advantage of the cost-effectiveness of standard production and the responsiveness of FMS. To solve the problem, we propose a heuristic algorithm based on column generation. The numerical results demonstrate that our optimisation model provides solutions with an average optimality gap of less than 6% while also reducing the average cost of standard production schemes without FMS by over 12%.
Journal: International Journal of Production Research
Pages: 157-170
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2288722
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2288722
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# input file: TPRS_A_2240440_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Davide Castellano
Author-X-Name-First: Davide
Author-X-Name-Last: Castellano
Author-Name: Mosè Gallo
Author-X-Name-First: Mosè
Author-X-Name-Last: Gallo
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Title: A single-vendor, multiple-buyer coordinated supply chain model with unequal-sized batch shipments and cycle-dependent safety stocks
Abstract: 
 This paper investigates a single-vendor, multiple-buyer coordinated supply chain under stochastic demand. Each buyer implements a continuous review policy, and the shortage quantity is fully back-ordered. The lead time for the first shipment includes setup, production, and transportation times, while the lead time for the remaining shipments includes only transportation time. The production time is a function of production lot and production rate, which are both decision variables, and the setup and transportation times are controllable as well. For each buyer, the safety stock in the first replenishment cycle is not necessarily identical to that in the remaining cycles. Two successive shipments from the vendor to a buyer may have different sizes, and their ratio is a decision variable. The problem is finding the production and inventory replenishment policy, production rate, and lead times that minimise the long-run expected total cost per time unit. We demonstrate properties satisfied by the cost function and develop an optimisation algorithm, whose performance is compared to a benchmark algorithm based on a commercial solver in a numerical experiment. The experiments also investigate the benefits stemming from the proposed model when compared to models reproducing situations that leverage some or any of the controlled factors.
Journal: International Journal of Production Research
Pages: 223-244
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2240440
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2240440
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# input file: TPRS_A_2275639_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yipei Zhang
Author-X-Name-First: Yipei
Author-X-Name-Last: Zhang
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Ada Che
Author-X-Name-First: Ada
Author-X-Name-Last: Che
Author-Name: Yantong Li
Author-X-Name-First: Yantong
Author-X-Name-Last: Li
Title: Closed-loop inventory routing problem for perishable food with returnable transport items selection
Abstract: 
 Urged by the necessity to establish sustainable supply chains (SCs), this study focuses on exploring the closed-loop inventory routing problem (CIRP) for perishable food packed by multi-type returnable transport items (RTIs). The selling revenue of perishable food is dependent on food's remaining shelf life and the specific type of RTIs used for packaging. RTI selection decisions need to be jointly considered in the CIRP to weigh the potential benefits against associated costs. For this problem, we first develop an integer linear programme (ILP) to maximise the total profit of the holistic SC. Subsequently, we design a tailored kernel search (KS) matheuristic as an efficient solution. A real CIRP with multi-type RTIs for fresh strawberries is used to demonstrate the practicality of the ILP. For this case study, we perform extensive sensitivity analysis of the relevant parameters, extracting valuable managerial insights. Finally, experiments are conducted on 170 randomly generated instances. Computational results show that the proposed KS manages to achieve competitive solutions for instances with up to 10 retailers much more efficiently than CLPEX. For instances with up to 40 retailers, the KS algorithm significantly outperforms CPLEX in terms of solution quality, improving the obtained profit by 80.03% on average under the same computational time.
Journal: International Journal of Production Research
Pages: 501-521
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2275639
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2275639
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# input file: TPRS_A_2188646_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Xinyue Wang
Author-X-Name-First: Xinyue
Author-X-Name-Last: Wang
Author-Name: Tao Ren
Author-X-Name-First: Tao
Author-X-Name-Last: Ren
Author-Name: Danyu Bai
Author-X-Name-First: Danyu
Author-X-Name-Last: Bai
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Yaodong Yu
Author-X-Name-First: Yaodong
Author-X-Name-Last: Yu
Author-Name: Fanchun Meng
Author-X-Name-First: Fanchun
Author-X-Name-Last: Meng
Author-Name: Chin-Chia Wu
Author-X-Name-First: Chin-Chia
Author-X-Name-Last: Wu
Title: Scheduling a multi-agent flow shop with two scenarios and release dates
Abstract: 
 Cloud computing is widely applied in modern industrial areas due to its technological advancement, cost reduction, and applicability. Packets (tasks) belonging to different applications (agents) compete to share the common cloud resource through a series of edge nodes (processors) in pursuit of fast transmission. This paper abstracts the cloud computing system as a multi-agent flow-shop scheduling (MAFS) problem. The objective is to minimise the total completion time of several agents with the restriction that the maximum lateness cannot exceed a given bound. Given the complexity of the considered problem, a branch and bound algorithm combined with several pruning rules and lower bounds is proposed to obtain optimal solutions. Furthermore, the considered problem is generalised to a bi-scenario version, and a bi-population cooperative co-evolutionary (BCCE) algorithm is proposed to solve it. A reinforcement learning-based method is presented to generate the initial population. Several problem-specific intensification strategies are constructed to explore promising solutions. Comprehensive experiments verified the effectiveness of the proposed algorithms. The industrial data from the China Earthquake Network Centre further confirmed the superiority of the BCCE algorithm. Overall, the MAFS model and the proposed algorithms effectively enhance the user experience and reasonably guarantee revenue.
Journal: International Journal of Production Research
Pages: 421-443
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2188646
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2188646
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2245919_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Marzieh Khakifirooz
Author-X-Name-First: Marzieh
Author-X-Name-Last: Khakifirooz
Author-Name: Michel Fathi
Author-X-Name-First: Michel
Author-X-Name-Last: Fathi
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Panos M. Pardalos
Author-X-Name-First: Panos M.
Author-X-Name-Last: Pardalos
Title: Scheduling in Industrial environment toward future: insights from Jean-Marie Proth
Abstract: 
 According to [Dolgui, Alexandre, and Jean Marie Proth. 2010. Supply Chain Engineering: Useful Methods and Techniques. Vol. 539. Springer.], advancing tactical levels in production systems has led to the disappearance of static scheduling in favour of dynamic scheduling. Additionally, the evolving challenges in the supply chain paradigm have significantly impacted the organisation of production systems. This shift has moved scheduling issues from the tactical to the strategic level, resulting in linear organisations encompassing scheduling decisions. [Proth, Jean Marie. 2007. “Scheduling: New Trends in Industrial Environment.” Annual Reviews in Control 31 (1): 157–166. https://doi.org/10.1016/j.arcontrol.2007.03.005.] emphasised that real-time scheduling in production systems has become a pivotal area of research. He presented several open problems for researchers to address in this context, including (1) the development of real-time algorithms capable of handling multiple operations on the same product and unrelated resources, (2) adapting previous schedules with certain modifications, (3) addressing unforeseen actions that arise randomly in real-time planning, and (4) exploring cyclic scheduling problems with size limits as alternative solutions to heuristic approaches. This paper reviews the evolving trends in light of J.M. Proth's predictions and advice within the aforementioned domains.
Journal: International Journal of Production Research
Pages: 291-317
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2245919
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2245919
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# input file: TPRS_A_2276818_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Manolis N. Kritikos
Author-X-Name-First: Manolis N.
Author-X-Name-Last: Kritikos
Author-Name: George Ioannou
Author-X-Name-First: George
Author-X-Name-Last: Ioannou
Title: Valid inequalities for the non-unit demand capacitated minimum spanning tree problem with arc time windows and flow costs
Abstract: 
 In this paper, we introduce the non-unit demand capacitated minimum spanning tree problem with arc time windows and flow costs. The problem is a variant of the capacitated minimum spanning tree problem with arc time windows (CMSTP_ATW). We devise a mixed integer programming (MIP) formulation to model the problem and solve it using CPLEX. Furthermore, we propose three sets of inequalities, and we prove that they are valid. These valid inequalities tighten the model and lead to better lower bounds. To examine the quality of the solutions obtained, we convert the original data sets of Solomon (1987, “Algorithms for the Vehicle Routing and Scheduling Problem with Time Window Constraints.” Operations Research 35 (2): 254–265. https://doi.org/10.1287/opre.35.2.254) to approximate the non-unit demand CMSTP_ATW instances and provide results for the problems with 100 nodes. We execute extensive computational experiments, and the results show the positive effect of the inclusion of valid inequalities in the MIP.
Journal: International Journal of Production Research
Pages: 574-585
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2276818
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2276818
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2284203_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Ketan Date
Author-X-Name-First: Ketan
Author-X-Name-Last: Date
Author-Name: Rakesh Nagi
Author-X-Name-First: Rakesh
Author-X-Name-Last: Nagi
Title: Optimal and heuristic solutions for placing multiple finite-size rectangular facilities in an existing layout
Abstract: 
 In a companion paper (Date, K., and R. Nagi. [(2023) Optimal Placement of Multiple Finite-size Rectangular Facilities in an Existing Layout. International Journal of Production Research, THIS ISSUE]) we investigated a new problem of optimal placement of multiple finite-size rectangular facilities with known dimensions in the presence of existing rectangular facilities. We introduced the requisite theory to arrive at a solution by dividing the feasible region into sub-regions whose boundaries provide the candidates for the optimal placement. In this paper, we focus on developing optimal and heuristic solution methods for solving problem instances with various facility counts. To solve small instances with fewer facilities, we develop two optimal methods: (1) efficient explicit enumeration based on a tree state-space representation and (2) an implicit enumeration scheme that uses a flow-decomposition-based lower bound to reduce the search space and time. To solve industrial-sized instances, we have to resort to a family of construction and improvement heuristics given that the problem is NP-hard. The heuristic procedures perform well for non-pathological cases with an acceptable optimality gap. The main contribution of this paper is a range of optimal to heuristic methods that can be applied by the practitioner depending on their problem characteristics and desired efficiency.
Journal: International Journal of Production Research
Pages: 24-44
Issue: 1-2
Volume: 62
Year: 2024
Month: 01
X-DOI: 10.1080/00207543.2023.2284203
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2284203
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2173503_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Behdin Vahedi-Nouri
Author-X-Name-First: Behdin
Author-X-Name-Last: Vahedi-Nouri
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Author-Name: Zdeněk Hanzálek
Author-X-Name-First: Zdeněk
Author-X-Name-Last: Hanzálek
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Production scheduling in a reconfigurable manufacturing system benefiting from human-robot collaboration
Abstract: 
 Nowadays, the manufacturing sector needs higher levels of flexibility to confront the extremely volatile market. Accordingly, exploiting both machine and workforce reconfigurability as two critical sources of flexibility is advantageous. In this regard, for the first time, this paper explores an integrated production scheduling and workforce planning problem in a Reconfigurable Manufacturing System (RMS) benefiting from reconfigurable machines and human-robot collaboration. A new Mixed-Integer Linear Programming (MILP) model and an efficient Constraint Programming (CP) model are developed to formulate the problem, minimising the makespan as the performance metric. Due to the high complexity of the problem, the MILP model cannot handle large-sized instances. Hence, to evaluate the performance of the CP model in large-sized instances, a lower bound is derived based on the relaxation of the problem. Finally, extensive computational experiments are carried out to assess the performance of the devised MILP and CP models and provide general recommendations for managers dealing with such a complex problem. The results reveal the superiority of the CP model over the MILP model in small- and medium-sized instances. Moreover, the CP model can find high-quality solutions for large-sized instances within a reasonable computational time.
Journal: International Journal of Production Research
Pages: 767-783
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2173503
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2173503
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# input file: TPRS_A_2175174_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Shupeng Huang
Author-X-Name-First: Shupeng
Author-X-Name-Last: Huang
Author-Name: Haiyan Lu
Author-X-Name-First: Haiyan
Author-X-Name-Last: Lu
Author-Name: Junyi Lin
Author-X-Name-First: Junyi
Author-X-Name-Last: Lin
Author-Name: Borja Ponte
Author-X-Name-First: Borja
Author-X-Name-Last: Ponte
Title: On the dynamics of return collection in closed-loop supply chains
Abstract: 
 The effective operations of closed-loop supply chains (CLSCs) can help companies achieve sustainability goals and boost economic performance. In practice, CLSCs must collect used products, a complex process that is often constrained by collection station capacity. However, how collection station capacity influences the bullwhip effect and the dynamic performance of CLSCs remains unclear. Here, we develop a system dynamics model for CLSCs that integrates traditional manufacturing with remanufacturing and explore the effects of the stochastic capacity constraint of the collection station on the bullwhip effect of CLSCs. We find that, generally speaking, a collection station with looser or more stable capacity constraints tends to reduce bullwhip of CLSCs. However, pertinent interactions emerge between the relevant parameters; in some situations, reducing the capacity level of a collection station may be reasonable and beneficial when the stochastic capacity constraint is very stable, or when customer demand is highly variable. We also consider the partial backlog in return collection, a phenomenon associated with the stochastic capacity constraint of a collection station, and identify a new trade-off between CLSC sustainability and economic performance. Ultimately, our findings provide evidence that will guide managers’ plans for the capacity management of return collection in CLSCs.
Journal: International Journal of Production Research
Pages: 909-932
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2175174
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2175174
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# input file: TPRS_A_2172474_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Honghan Ye
Author-X-Name-First: Honghan
Author-X-Name-Last: Ye
Author-Name: Ziqian Zheng
Author-X-Name-First: Ziqian
Author-X-Name-Last: Zheng
Author-Name: Jing-Ru C. Cheng
Author-X-Name-First: Jing-Ru C.
Author-X-Name-Last: Cheng
Author-Name: Brock Hable
Author-X-Name-First: Brock
Author-X-Name-Last: Hable
Author-Name: Kaibo Liu
Author-X-Name-First: Kaibo
Author-X-Name-Last: Liu
Title: Online monitoring of high-dimensional asynchronous and heterogeneous data streams for shifts in location and scale
Abstract: 
 Recent advancement of sensor technology has made it possible to monitor high-dimensional data streams in various manufacturing systems for quality improvement. However, existing monitoring schemes commonly assume that all data streams have the same sampling interval. This assumption does not always hold in practice, which poses new and unique challenges for multivariate statistical process control. In this paper, we propose a generic nonparametric monitoring framework to online monitor high-dimensional asynchronous and heterogeneous data streams, where sampling intervals of data streams are different from each other, and measurements of each data stream follow arbitrary distributions. In particular, we first propose a quantile-based nonparametric framework to monitor each data stream locally for possible shifts in both location and scale. Then, for unsampled measurements due to different sampling intervals, a compensation strategy based on the Bayesian approach is introduced. Furthermore, we develop a global monitoring scheme using the sum of top-
 $ r $ r local statistics, which can quickly detect a wide range of possible shifts in all directions. Simulations and case studies are conducted to evaluate the performance and demonstrate the superiority of the proposed method.
Journal: International Journal of Production Research
Pages: 720-736
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2172474
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2172474
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# input file: TPRS_A_2172473_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Sotirios Panagou
Author-X-Name-First: Sotirios
Author-X-Name-Last: Panagou
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Author-Name: Fabio Fruggiero
Author-X-Name-First: Fabio
Author-X-Name-Last: Fruggiero
Title: A scoping review of human robot interaction research towards Industry 5.0 human-centric workplaces
Abstract: 
 Interaction between humans and robots in the workplace garners interest in recent years due to the introduction of Industry 4.0 and Industry 5.0 frameworks. A scoping review was performed aimed at investigating the effect of robot design features on their human counterparts. In the analysis of the 32 identified articles, the robot design features used in the literature are shown along with the effects on the operators. Results showcased the many to many relationships between robot design features and effects on operators. Robot appearance, for example, and capabilities play a role in the operators’ perception and expectations of their capabilities based on the task and subsequently perceived reliability and safety. Communication capabilities between operators and robots is an integral part for teamwork and performance as it can affect work processes. The paucity of papers empirically addressing human robot interaction as a system is consistent with results from previous literature, indicating the need for more research. The results of this investigation can prove useful in the form of advice to designers and practitioners, such as the operator’s involvement in implementation, knowledge on robots’ capabilities and training. Research gaps identified are discussed, as well as future research directions.
Journal: International Journal of Production Research
Pages: 974-990
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2172473
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2172473
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# input file: TPRS_A_2169383_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Title: Application of supportive and substitutive technologies in manual warehouse order picking: a content analysis
Abstract: 
 Order picking in warehouses is a labour- and time-intensive logistical process that significantly impacts the efficiency of supply chains. Although technical progress facilitates the automation of specific order picking tasks, human workers remain the primary actors of order picking. Owing to high operating costs associated with manual order picking, its design and management have been increasingly researched for decades. Because manual order picking systems are socio-technical systems, human factors and workers’ interaction with technology are essential for operational success. As innovative technologies become increasingly utilised, such as augmented reality or exoskeletons, warehouse managers need to consider the effects of supportive and substitutive technologies on operational outcomes. However, the potentials and obstacles of using technologies in manual order picking require further investigations. Therefore, this study analyses literature content on supportive and substitutive technologies in manual warehouse order picking and investigates the existing state of research in this field. Text mining is employed to enhance the insights regarding the content analysis. Additionally, future research opportunities on the integration of supportive and substitutive technologies are proposed for manual order picking improvement and development of sustainable and human-centered logistics systems, according to the Industry 5.0 vision.
Journal: International Journal of Production Research
Pages: 685-704
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2169383
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2169383
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# input file: TPRS_A_2169382_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Vanessa Simard
Author-X-Name-First: Vanessa
Author-X-Name-Last: Simard
Author-Name: Mikael Rönnqvist
Author-X-Name-First: Mikael
Author-X-Name-Last: Rönnqvist
Author-Name: Luc LeBel
Author-X-Name-First: Luc
Author-X-Name-Last: LeBel
Author-Name: Nadia Lehoux
Author-X-Name-First: Nadia
Author-X-Name-Last: Lehoux
Title: Improving the decision-making process by considering supply uncertainty – a case study in the forest value chain
Abstract: 
 Planning decisions are generally subject to some level of uncertainty. In forestry, data describing the resources available have a major impact on operations performance and productivity. This paper aims to present a method to improve decision-making in the forest supply chain by taking supply uncertainty into account using the results of data quality assessments. The case study describes the operations planning process of a Canadian forest products company dealing with an uncertain volume of wood supply. Three approaches to constructing probability distributions based on data quality are tested. Each approach offers a different level of precision: (1) a frequency distribution of accuracy, (2) a normal distribution based on average accuracy, and (3) a normal distribution based on data quality classification. Using stochastic programming to plan transport and production shows that lower costs can be achieved with a general characterisation of the data accuracy. Not considering uncertainty when planning operations leads to a significant replanning transportation cost. Using classes of data quality to include uncertainty in operations planning contributes to reducing the transportation cost from $15.90/m3 down to $15.32/m3 representing 3.6%.
Journal: International Journal of Production Research
Pages: 665-684
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2169382
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2169382
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# input file: TPRS_A_2173502_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Lara Schilling
Author-X-Name-First: Lara
Author-X-Name-Last: Schilling
Author-Name: Stefan Seuring
Author-X-Name-First: Stefan
Author-X-Name-Last: Seuring
Title: Linking the digital and sustainable transformation with supply chain practices
Abstract: 
 The digital transformation involves both risks and opportunities for the sustainability of global supply chains. This systematic literature review of 64 peer-reviewed English journal articles aims to show how the adoption of digital technologies is related to (sustainable) supply chain management practices and associated sustainable outcomes. (Non)existing relationships between these constructs will be examined, which has not been done previously. Content, frequency, and contingency analyses are conducted from a practice-based view. The study reveals three main topics in the literature: (1) a mainstream eco-efficiency debate; (2) supplemented by a data-driven, comprehensive long-term perspective on environmental sustainability; and (3) hard-to-measure substantive sustainability aspects that can be fostered by communication, selective monitoring and certification. An integrated perspective of these three topics is proposed to facilitate a more viable sustainability approach. Based on the identified (non)existing relationships, researchers and practitioners learn about the digital technologies and practices they can use to improve supply chain sustainability. Importantly, it should be recognised that hardly quantifiable targets and related practices are obscured by large datasets. Future research should focus on the integration of economic aspects to ensure the compatibility of long-term substantial sustainability goals and the profitability of the entire supply chain.
Journal: International Journal of Production Research
Pages: 949-973
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2173502
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2173502
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# input file: TPRS_A_2173508_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Arijit Maji
Author-X-Name-First: Arijit
Author-X-Name-Last: Maji
Author-Name: Indrajit Mukherjee
Author-X-Name-First: Indrajit
Author-X-Name-Last: Mukherjee
Title: An efficient adaptive r-MD multivariate single control chart for nonlinear multiple quality characteristics
Abstract: 
 An efficient multivariate single control chart to simultaneously monitor ‘location or mean’ and ‘scale or variabilities’, based on individual observations of multiple quality characteristics (MQC), is a continuous research endeavour. Compared to rational subgroups, time-ordered individual sample observations of MQC are common in manufacturing. However, few researchers proposed parametric and nonparametric multivariate control charts to monitor individual observations in this context. The proposed parametric approach has limited applicability due to the restrictive distribution assumption of MQC. In addition, most of the suggested parametric or nonparametric approaches recommend multiple charts to monitor process ‘location’ and ‘scale’ parameters simultaneously. Multiple charts can increase the control complexities and overall false-alarm-rate . MQC can also have significant nonlinear correlation structures and follow unknown or nonnormal distributions in real-life scenarios. Single parametric or nonparametric multivariate charts for individual observations can exhibit poor performance in such situations. In this study, an adaptive Mahalanobis depth and k-nearest neighbour (k-NN) rule-based r-AMD chart is proposed and verified to address the lacuna mentioned above. Monte-Carlo simulation studies are used to evaluate the performance of the r-AMD chart. Four real-life manufacturing scenarios are also considered to validate the suitability and superiority of r-AMD over the existing ‘r-MD’ and other competing charts.
Journal: International Journal of Production Research
Pages: 784-822
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2173508
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2173508
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# input file: TPRS_A_2262050_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Dhruv Patel
Author-X-Name-First: Dhruv
Author-X-Name-Last: Patel
Author-Name: Chandan Kumar Sahu
Author-X-Name-First: Chandan Kumar
Author-X-Name-Last: Sahu
Author-Name: Rahul Rai
Author-X-Name-First: Rahul
Author-X-Name-Last: Rai
Title: Security in modern manufacturing systems: integrating blockchain in artificial intelligence-assisted manufacturing
Abstract: 
 Process automation and mass customisation requirements of modern manufacturing systems are driven by artificial intelligence (AI). As AI derives decisions from data, securing the data against tampering is crucial to prevent ensuing operational risks. Additionally, manufacturing systems necessitate collaboration, transparency, and trust among participants while preserving a competitive advantage. Thus, we position blockchain, an enabler of transparent and secure operations, as a security solution for AI-assisted manufacturing systems. In this conceptual viewpoint paper, we present a framework to integrate blockchain in AI-assisted manufacturing systems. We highlight the special needs of manufacturing BCs over generic BCs. We delineate the ways in which manufacturing can be a beneficiary of the synergy between AI and BC. We discuss how BC and AI can accelerate early-phase product design, collaboration, and manufacturing processes and secure supply chains against counterfeit products and for ethical consumerism. Lastly, we identify the needs of modern manufacturing systems and cite a few examples of organisational failures to underscore the importance of security while delineating the significant challenges in adopting blockchain-based solutions in the manufacturing industry.
Journal: International Journal of Production Research
Pages: 1041-1071
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2262050
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2262050
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# input file: TPRS_A_2173511_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Qiangda Yang
Author-X-Name-First: Qiangda
Author-X-Name-Last: Yang
Author-Name: Hongbo Gao
Author-X-Name-First: Hongbo
Author-X-Name-Last: Gao
Author-Name: Ning Dong
Author-X-Name-First: Ning
Author-X-Name-Last: Dong
Author-Name: Peng Liu
Author-X-Name-First: Peng
Author-X-Name-Last: Liu
Title: An elitist cuckoo search algorithm for combined heat and power economic dispatch
Abstract: 
 Combined heat and power economic dispatch (CHPED) is one of the foremost subjects in the operation of power systems. In this article, a new variant of cuckoo search (CS) algorithm, elitist CS (yECS), is advanced to tackle CHPED. During the optimisation process of the original CS as well as lots of its variants, the guidance of search directions relies merely upon the best individual, causing the loss of other beneficial information and further influencing their performance potentials. Therefore, in yECS, an elitist mechanism is developed to fully utilise the beneficial information of other elite individuals. Specifically, three new iterative strategies are developed, one for the global search phase and the other two for the local search phase. Further, a coordinated mechanism is put forward to effectively integrate the local iterative strategies, thus helping yECS in maintaining an appropriate balance between exploitation and exploration. The superior performance of yECS is firstly substantiated via CEC 2017 test suite and two engineering design problems and then it is utilised to address CHPED problems. All optimal dispatch results acquired by yECS are feasible and in most cases display remarkable improvements over the results determined by other CS variants and some recently-published literature results.
Journal: International Journal of Production Research
Pages: 846-866
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2173511
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2173511
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# input file: TPRS_A_2168310_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Khelil Kassoul
Author-X-Name-First: Khelil
Author-X-Name-Last: Kassoul
Author-Name: Naoufel Cheikhrouhou
Author-X-Name-First: Naoufel
Author-X-Name-Last: Cheikhrouhou
Author-Name: Nicolas Zufferey
Author-X-Name-First: Nicolas
Author-X-Name-Last: Zufferey
Title: Simultaneous allocation of buffer capacities and service times in unreliable production lines
Abstract: 
 Simultaneous allocation of service times and buffer capacities in manufacturing systems in a random environment is a NP-hard combinatorial optimisation problem. This paper presents a sophisticated simulation-based optimisation approach for the design of unreliable production lines to maximise the production rate. The proposed method allows for a global search using a Genetic Algorithm (GA), which is coupled with Finite Perturbation Analysis (FPA) as a local search technique. Traditional techniques based on perturbation analysis optimise decision variables of the same nature (e.g. service time only, buffer capacity only), whereas the proposed technique simultaneously provides an allocation of service times and buffer capacities. One of the main focuses of this paper is the investigation of the persistence or absence of the buffer and service rate allocation patterns which are among the most essential insights that come from designing production lines. The results show the superiority of the combined GA-FPA approach regarding GA and FPA in terms of solution quality and convergence behaviour. Moreover, considering instances ranging from 3 to 100 machines, our numerical experiments are in line with the literature for small instances (as similar allocation patterns are identified in our work), but important differences are highlighted for medium/large instances.
Journal: International Journal of Production Research
Pages: 644-664
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2168310
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2168310
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# input file: TPRS_A_2167015_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Benedikt Zipfel
Author-X-Name-First: Benedikt
Author-X-Name-Last: Zipfel
Author-Name: Janis Neufeld
Author-X-Name-First: Janis
Author-X-Name-Last: Neufeld
Author-Name: Udo Buscher
Author-X-Name-First: Udo
Author-X-Name-Last: Buscher
Title: An iterated local search for customer order scheduling in additive manufacturing
Abstract: 
 This paper studies the customer order scheduling problem in the context of additive manufacturing. The study discusses an integrated problem involving the nesting of parts as well as the scheduling of batches of nested parts onto unrelated parallel machines. A mixed-integer programming model is presented, based on existing formulations from the literature, that integrates different materials and sequence-dependent setup times. Additionally, a metaheuristic based on an iterated local search is proposed for the problem configuration under consideration. Focusing on minimizing the total weighted tardiness of orders, the efficiency of the heuristic approach is evaluated using comprehensive test data. Further, we show the importance of the considered order-related objective by using qualitative analysis.
Journal: International Journal of Production Research
Pages: 605-625
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2167015
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2167015
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# input file: TPRS_A_2172472_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Abderrazzak Sabri
Author-X-Name-First: Abderrazzak
Author-X-Name-Last: Sabri
Author-Name: Hamid Allaoui
Author-X-Name-First: Hamid
Author-X-Name-Last: Allaoui
Author-Name: Omar Souissi
Author-X-Name-First: Omar
Author-X-Name-Last: Souissi
Title: Reinforcement learning and stochastic dynamic programming for jointly scheduling jobs and preventive maintenance on a single machine to minimise earliness-tardiness
Abstract: 
 This paper addresses the problem of stochastic jointly scheduling of resumable jobs and preventive maintenance on a single machine, subject to random breakdowns, to minimise the earliness-tardiness cost. The main objective is to investigate using trending machine learning-based methods compared to stochastic optimisation approaches. We propose two different methods from both fields as we solve the same problem firstly with a stochastic dynamic programming model in an approximation way, then with an attention-based deep reinforcement learning model. We conduct a detailed experimental study according to solution quality, run time, and robustness to analyse their performances compared to those of an existing approach in the literature as a baseline. Both algorithms outperform the baseline. Moreover, the machine learning-based algorithm outperforms the stochastic dynamic programming-based heuristic as we report up to 30.5% saving in total cost, a reduction of computational time from 67 min to less than 
 $ 1s $ 1s on big instances, and a better robustness. These facts highlight clearly its potential for solving such problems.
Journal: International Journal of Production Research
Pages: 705-719
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2172472
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2172472
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# input file: TPRS_A_2172968_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Ming Liu
Author-X-Name-First: Ming
Author-X-Name-Last: Liu
Author-Name: Hao Tang
Author-X-Name-First: Hao
Author-X-Name-Last: Tang
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Zhanguo Zhu
Author-X-Name-First: Zhanguo
Author-X-Name-Last: Zhu
Author-Name: Chengbin Chu
Author-X-Name-First: Chengbin
Author-X-Name-Last: Chu
Title: Food inspector scheduling with outcome and daily-schedule effects
Abstract: 
 Food-safety inspection is regularly executed by the government for quality assessment. Evidence from recent research demonstrates that inspection accuracy and consistency are affected by inspection biases that result from an operational decision: inspector scheduling. More precisely, an inspector's stringency in an inspection is affected by the inspection results at the previous-inspected establishment (outcome effects) and when this inspection occurs within a workday (daily-schedule effects). To our best knowledge, the impact of these effects on scheduling decisions has not been studied in the scheduling literature. In this paper, we study a novel food inspector scheduling problem with these effects, where the inspector should scrutinise establishments with different locations. The problem is viewed as a single-machine scheduling problem with a complex objective function including (i) inspection accuracy, (ii) inspection consistency and (iii) workload of the inspector. To facilitate quantitative analyses of these effects, we model them by sequence-dependent functions and formulate a mixed integer linear programming model. To overcome the computational difficulty in large-scale problems, an efficient Tabu Search algorithm is developed. Experiment results on 135 randomly generated instances with up to 50 establishments and 10 workdays validate the efficiency of the solution method. Besides, managerial insights are drawn.
Journal: International Journal of Production Research
Pages: 737-766
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2172968
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2172968
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# input file: TPRS_A_2175172_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Dalila B.M.M. Fontes
Author-X-Name-First: Dalila B.M.M.
Author-X-Name-Last: Fontes
Author-Name: Seyed Mahdi Homayouni
Author-X-Name-First: Seyed Mahdi
Author-X-Name-Last: Homayouni
Author-Name: João Chaves Fernandes
Author-X-Name-First: João Chaves
Author-X-Name-Last: Fernandes
Title: Energy-efficient job shop scheduling problem with transport resources considering speed adjustable resources
Abstract: 
 This work extends the energy-efficient job shop scheduling problem with transport resources by considering speed adjustable resources of two types, namely: the machines where the jobs are processed on and the vehicles that transport the jobs around the shop-floor. Therefore, the problem being considered involves determining, simultaneously, the processing speed of each production operation, the sequence of the production operations for each machine, the allocation of the transport tasks to vehicles, the travelling speed of each task for the empty and for the loaded legs, and the sequence of the transport tasks for each vehicle. Among the possible solutions, we are interested in those providing trade-offs between makespan and total energy consumption (Pareto solutions). To that end, we develop and solve a bi-objective mixed-integer linear programming model. In addition, due to problem complexity we also propose a multi-objective biased random key genetic algorithm that simultaneously evolves several populations. The computational experiments performed have show it to be effective and efficient, even in the presence of larger problem instances. Finally, we provide extensive time and energy trade-off analysis (Pareto front) to infer the advantages of considering speed adjustable machines and speed adjustable vehicles and provide general insights for the managers dealing with such a complex problem.
Journal: International Journal of Production Research
Pages: 867-890
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2175172
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2175172
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# input file: TPRS_A_2239376_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Kristiaan Kerstens
Author-X-Name-First: Kristiaan
Author-X-Name-Last: Kerstens
Author-Name: Jafar Sadeghi
Author-X-Name-First: Jafar
Author-X-Name-Last: Sadeghi
Title: Plant capacity notions: review, new definitions, and existence results at firm and industry levels
Abstract: 
 This study investigates the existence of solutions for the key plant capacity utilisation (PCU) concepts using general nonparametric technologies. This is done via a theoretical review of existing and some new PCU concepts. Focusing on short-run and long-run output-oriented, attainable output-oriented, and input-oriented PCU notions, we first investigate the existence of solutions at the firm level. Under mild axioms, this question regarding the existence of solutions for these PCU concepts at the firm level is affirmatively answered under variable and constant returns to scale as well as under convex and nonconvex assumptions. However, short-run and long-run output-oriented and attainable output-oriented PCU concepts may not be implementable depending on certain conditions. There are no such reservations for the input-oriented PCU. Then, for this same range of PCU concepts, we explore the more difficult question as to the existence of solutions at the industry level. The output-oriented and attainable output-oriented PCU exist at the industry level under strict conditions: existence and attainability are interwoven at this level. The industry input-oriented PCU is always feasible at the industry model. This theoretical review is supplemented by a semi-systematic empirical review, and an empirical application. We conclude that input-oriented PCU is clearly the best concept.
Journal: International Journal of Production Research
Pages: 1017-1040
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2239376
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2239376
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# input file: TPRS_A_2173509_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yaniv Proselkov
Author-X-Name-First: Yaniv
Author-X-Name-Last: Proselkov
Author-Name: Jie Zhang
Author-X-Name-First: Jie
Author-X-Name-Last: Zhang
Author-Name: Liming Xu
Author-X-Name-First: Liming
Author-X-Name-Last: Xu
Author-Name: Erik Hofmann
Author-X-Name-First: Erik
Author-X-Name-Last: Hofmann
Author-Name: Thomas Y. Choi
Author-X-Name-First: Thomas Y.
Author-X-Name-Last: Choi
Author-Name: Dale Rogers
Author-X-Name-First: Dale
Author-X-Name-Last: Rogers
Author-Name: Alexandra Brintrup
Author-X-Name-First: Alexandra
Author-X-Name-Last: Brintrup
Title: Financial ripple effect in complex adaptive supply networks: an agent-based model
Abstract: 
 Tightening lending standards are motivating companies to adopt supply chain financing, with invoice backed lending to remedy financial stress. These financial objects depend on company-to-company relationships. The accumulation of these dyadic relationships creates complex supply network topologies. Companies within these networks are selfish and have varying degrees of bargaining power. To remain operational, they maximise their liquidity by negotiating longer repayment terms and cheaper financing, thus distributing risk onto weaker companies and propagating financial stress. To study this phenomenon, we created an agent-based supply network simulation model capturing these behaviours. We investigate structural conditions that make supply networks vulnerable to financial stress propagation and the resultant financial ripple effects using survivability analysis. We found firms with higher bargaining power are disproportionately more exposed to network risk. In diamond-shaped networks, firms occupying lower tiers are critical in financial stress propagation, becoming deep-tier nexus suppliers. Our results are relevant to industries with heterogeneous network composition. Practitioners must mitigate the effects of vulnerable network structures with careful supply chain financing design.
Journal: International Journal of Production Research
Pages: 823-845
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2173509
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2173509
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# input file: TPRS_A_2168308_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Pablo Pérez-Gosende
Author-X-Name-First: Pablo
Author-X-Name-Last: Pérez-Gosende
Author-Name: Josefa Mula
Author-X-Name-First: Josefa
Author-X-Name-Last: Mula
Author-Name: Manuel Díaz-Madroñero
Author-X-Name-First: Manuel
Author-X-Name-Last: Díaz-Madroñero
Title: A bottom-up multi-objective optimisation approach to dynamic facility layout planning
Abstract: 
 Dynamic facility layout planning (DFLP) involves determining an appropriate arrangement scheme of the elements making up the production system for each time period into which the planning horizon is divided. When formulating the problem as an optimisation model, using the traditional top-down approach is usual, which firstly determines the block layout (BL) and then the detailed layout (DL) of each work cell. However by this approach, the BL generates area constraints in the detailed phase, which sometimes limit its implementation. In this context, the present paper presents a multi-objective mixed integer non-linear programming (MOMINLP) model that allows the problem to be addressed by considering an alternative approach, known in the literature as the bottom-up approach. The proposed model, called bottom-up mDFLP, considers three objective functions: (1) minimise the total material handling cost (TMHC) and the total rearrangement cost (TRAC); (2) maximise the total closeness rating (TCR) between departments; (3) maximise the area utilisation ratio (AUR). The original MOMINLP is transformed into a more computationally efficient multi-objective mixed integer linear programming (MOMILP) model. The proposed model is applied and validated in a case study of a company in the metal-mechanic sector with 12 departments for three 4-month periods.
Journal: International Journal of Production Research
Pages: 626-643
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2168308
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2168308
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# input file: TPRS_A_2236241_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yanhu Han
Author-X-Name-First: Yanhu
Author-X-Name-Last: Han
Author-Name: Xiao Fang
Author-X-Name-First: Xiao
Author-X-Name-Last: Fang
Title: Systematic review of adopting blockchain in supply chain management: bibliometric analysis and theme discussion
Abstract: 
 Traditional supply chain management faces challenges such as low level of information sharing and lack of transparency. Due to the features such as tamper-proof, reliability and traceability, the blockchain technology enhances the trust among stakeholders and enables transparent transactions and open collaboration, which can reduce the risk of supply chain disruptions. Accordingly, blockchain technology-based supply chain management has attracted more attention from academics and practitioners. However, existing review studies mainly focus on different industries or topics and lack a more comprehensive analysis. Therefore, this paper presents a systematic review integrating bibliometric analysis with theme analysis to understand the current research state in BT-SCM and discuss its future research trends. On the one hand, VOSviewer is used to conduct bibliometric analysis to explore the influences of existing studies from six aspects: publication year, author, country, keyword, journal, and article citation. On the other hand, the functional application of BT-SCM is discussed from logistics traceability, supply chain finance, supply chain collaboration, sustainable management and risk management to determine the research status, and the enablers and barriers of blockchain application in SCM are summarised to facilitate practitioners to adopt BT, and finally the potential research directions are proposed for scholars in this field.
Journal: International Journal of Production Research
Pages: 991-1016
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2236241
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2236241
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# input file: TPRS_A_2175175_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Nicla Frigerio
Author-X-Name-First: Nicla
Author-X-Name-Last: Frigerio
Author-Name: Barış Tan
Author-X-Name-First: Barış
Author-X-Name-Last: Tan
Author-Name: Andrea Matta
Author-X-Name-First: Andrea
Author-X-Name-Last: Matta
Title: Simultaneous control of multiple machines for energy efficiency: a simulation-based approach
Abstract: 
 Energy efficiency is crucial in contemporary industry and controlling the resource power state by switching off/on commands is a promising measure. The control problem of deciding when to switch off/on the machines depending on the state of the system at a given time is not trivial due to the effect the control might have on the system production rate. Threshold-based policies using buffer occupancy information to control the machines can be effectively used to reduce energy consumption. Nevertheless, highly complex control policies are difficult to be applied and costly to be managed in practice. Buffer-based threshold policies to control multiple machines simultaneously in a serial production line for energy efficiency purposes are analysed in this work. The optimal control minimises the energy consumption while assuring a certain target production rate for the system. The effects of controlling different combinations of machines simultaneously with different number of thresholds have been investigated through numerical experiments with discrete event simulation. Insights regarding the trade-off between the complexity of the control and the performance gains are provided. The proposed policy works effectively and the effect of a proper selection of the controlled machines or thresholds is significant.
Journal: International Journal of Production Research
Pages: 933-948
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2175175
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2175175
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# input file: TPRS_A_2175173_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Zhangwei Feng
Author-X-Name-First: Zhangwei
Author-X-Name-Last: Feng
Author-Name: Na Luo
Author-X-Name-First: Na
Author-X-Name-Last: Luo
Author-Name: Timofey Shalpegin
Author-X-Name-First: Timofey
Author-X-Name-Last: Shalpegin
Author-Name: Huan Cui
Author-X-Name-First: Huan
Author-X-Name-Last: Cui
Title: The influence of carbon emission reduction instruments on blockchain technology adoption in recycling batteries of the new energy vehicles
Abstract: 
 The new energy vehicle (NEV) is emerging as an important alternative in the automobile industry in its potential to alleviate environmental pollution and contribute to carbon neutrality. The rapid growth of NEVs has been reflected in the scaling up of electric vehicle battery production. The dramatic increase of retired batteries, however, exposes the technological limitations in current recycling operations, which will ultimately impede the sustainable development of the NEV supply chain. Blockchain technology (BT) adoption provides a solution by contributing to the construction of an efficient recycling network. Our research investigates the influence of carbon reduction instruments on the uptake of BT. The key findings are as follows. Under a carbon tax system, (1) carbon emission reduction encourages the battery supplier to adopt BT; (2) BT adoption increases the profits of NEV supply chain stakeholders. Under carbon cap-and-trade regulations, (1) the unit outsourcing fee and the performance of the BT impact the investment decision of the manufacturer; (2) the profit of the third-party enterprise is increased by introducing the BT. Under both policies, improving the efficiency of BT helps to upgrade the traceability level and contribute to carbon neutrality in the NEV supply chain.
Journal: International Journal of Production Research
Pages: 891-908
Issue: 3
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2175173
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2175173
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# input file: TPRS_A_2276811_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Ilya Jackson
Author-X-Name-First: Ilya
Author-X-Name-Last: Jackson
Author-Name: Maria Jesus Saenz
Author-X-Name-First: Maria
Author-X-Name-Last: Jesus Saenz
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: From natural language to simulations: applying AI to automate simulation modelling of logistics systems
Abstract: 
 Our research strives to examine how simulation models of logistics systems can be produced automatically from verbal descriptions in natural language and how human experts and artificial intelligence (AI)-based systems can collaborate in the domain of simulation modelling. We demonstrate that a framework constructed upon the refined GPT-3 Codex is capable of generating functionally valid simulations for queuing and inventory management systems when provided with a verbal explanation. As a result, the language model could produce simulation models for inventory and process control. These results, along with the rapid improvement of language models, enable a significant simplification of simulation model development. Our study offers guidelines and a design of a natural language processing-based framework on how to build simulation models of logistics systems automatically, given the verbal description. In generalised terms, our work offers a technological underpinning of human-AI collaboration for the development of simulation models.
Journal: International Journal of Production Research
Pages: 1434-1457
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2276811
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2276811
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# input file: TPRS_A_2179346_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Devinder Kumar
Author-X-Name-First: Devinder
Author-X-Name-Last: Kumar
Author-Name: Rajesh Kr Singh
Author-X-Name-First: Rajesh Kr
Author-X-Name-Last: Singh
Author-Name: Ruchi Mishra
Author-X-Name-First: Ruchi
Author-X-Name-Last: Mishra
Author-Name: Ilias Vlachos
Author-X-Name-First: Ilias
Author-X-Name-Last: Vlachos
Title: Big data analytics in supply chain decarbonisation: a systematic literature review and future research directions
Abstract: 
 Supply chain decarbonisation has become a strategic requirement in the era of a net-zero economy. Despite the significant role of Big Data Analytics (BDA) in decarbonising the supply chain (SC), no prior study has evaluated it systematically. The present study aims to provide a systematic literature review on the applications and outcomes of big data analytics in SC decarbonisation. A total of 69 papers on applying BDA technology for supply chain decarbonisation published between 2016 and 2021 have been selected following the PRISMA protocol. The findings show that the topic is evolving. Studies employed methods such as surveys (30), case studies (11), and conceptual research designs (8). Thematic analysis reveals that 65% of the studies are grounded in resource-advantage theories, organisational theories, and system theories. Studies from India and China (35%) dominate the topic, while most studies have been conducted on the food and manufacturing industries. Further, this study applied the Antecedent-Decision-Outcomes (ADO) framework in BDA-based SC decarbonisation. Antecedents include BDA resources and capabilities, workforce skills, and supplier capabilities. Decisions refer to improving decision-making across the supply chain. Outcomes refer to improving decarbonisation, sustainable growth, and sustainable innovativeness. Future research directions and questions are provided using the Theory-Context-Methodology (TCM) framework.
Journal: International Journal of Production Research
Pages: 1489-1509
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2179346
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2179346
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# input file: TPRS_A_2178370_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Anding Zhu
Author-X-Name-First: Anding
Author-X-Name-Last: Zhu
Author-Name: Yunyan Han
Author-X-Name-First: Yunyan
Author-X-Name-Last: Han
Author-Name: Hong Liu
Author-X-Name-First: Hong
Author-X-Name-Last: Liu
Title: Effects of adaptive cooperation among heterogeneous manufacturers on supply chain viability under fluctuating demand in post-COVID-19 era: an agent-based simulation
Abstract: 
 Supply chain viability (SCV) is associated with systematic and dynamic approaches to responding to COVID-19 disruptions. The supply chain has been disturbed due to the recurrent nature of the pandemic. In the post-pandemic era, large and small- and medium-sized manufacturers have both advantages and disadvantages, complementing each other. This study proposes an agent-based model to simulate the viable situation of heterogeneous supply systems by considering three behavioural rules (i.e. cooperation establishment, win-win cooperation, and cooperation priority). The results demonstrate that the viability will be improved if large manufacturers cooperate closely with small- and medium-sized manufacturers. The viability is also associated with two adjustment parameters of production capacity, indicating that large manufacturers need to become more scalable, flexible, and adaptable to survive a rapidly changing environment. In addition, when the cooperation is more widely-connected, the viability will be higher. When facing severe fluctuations, large and small- and medium-sized manufacturers can cooperate, acting as a ‘sponge system’ to flatten the fluctuations. Finally, the simulation results of an empirical network also support this conclusion. Therefore, we suggest that a viable supply chain design should consider integrating supply resources to improve the overall viability of the supply system.
Journal: International Journal of Production Research
Pages: 1162-1188
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2178370
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2178370
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# input file: TPRS_A_2183718_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Chen Wang
Author-X-Name-First: Chen
Author-X-Name-Last: Wang
Author-Name: Mengchu Li
Author-X-Name-First: Mengchu
Author-X-Name-Last: Li
Author-Name: Nanfang Cui
Author-X-Name-First: Nanfang
Author-X-Name-Last: Cui
Title: Improving reliability of assembly supply chains with disruption risk: stakeholders' subsidy interplay
Abstract: 
 We consider a decentralised assembly supply chain that consists of an assembler and multiple suppliers. The cooperation between the assembler and each supplier is organised under a pull contract, which indicates that the suppliers bear the overstock risk. One of the suppliers may suffer disruption and endogenously builds the reliability, and the assembler could provide the subsidy for this unreliable supplier to improve the reliability. We reveal that in addition to the assembler, a reliable supplier with a sufficiently high wholesale price also has incentives to jointly offer subsidy for the ex ante reliability improvement. The reliable supplier's participation in reliability improvement could benefit all the supply chain members. Furthermore, we examine a subsequent reliable supplier's incentives to offer subsidy based on the previous one's. It suggests that it is not necessary for a subsequent reliable supplier with a lower wholesale price than the previous one's to provide the subsidy. Higher reliability for the whole supply chain could be achieved if the previous reliable supplier with a higher wholesale price provides the subsidy. We finally examine the impact of multiple unreliable suppliers and show that a larger number of unreliable suppliers would discourage a reliable supplier's subsidy.
Journal: International Journal of Production Research
Pages: 1336-1357
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2183718
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2183718
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# input file: TPRS_A_2175308_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Guodong Huang
Author-X-Name-First: Guodong
Author-X-Name-Last: Huang
Author-Name: Yacob Khojasteh
Author-X-Name-First: Yacob
Author-X-Name-Last: Khojasteh
Title: Using an incentive-compatibility due-date quotation to improve the performance for one-of-a-kind production shop floors controlled by load-based pull systems
Abstract: 
 For one-of-a-kind production (OKP) manufacturers adopting an engineer-to-order or make-to-order marketing strategy, it is very important to set an appropriate due date. We design an incentive-compatibility due-date quotation procedure to help OKP manufacturers obtain the rational due-date quotation from OKP customers. Based on the rational due-date quotation decision-making, the performance of an OKP shop floor controlled by load-based pull systems is evaluated in simulation. Our findings show that if the collaboration of due-date quotations and load-based pull control is effective, the order profit of OKP manufacturers will not be reduced when the delivery delay occurs. This study can provide more insights on order quotation decision-making and pull production control for OKP manufacturers.
Journal: International Journal of Production Research
Pages: 1072-1091
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2175308
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2175308
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# input file: TPRS_A_2179342_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Herbert Jodlbauer
Author-X-Name-First: Herbert
Author-X-Name-Last: Jodlbauer
Author-Name: Shailesh Tripathi
Author-X-Name-First: Shailesh
Author-X-Name-Last: Tripathi
Title: Due date quoting and rescheduling in a fixed production sequence
Abstract: 
 In this article, the due date setting problem consisting of due date quoting, order insertion and rescheduling with relevant sequence-dependent setups and a frozen zone is considered. A differential equation model is introduced. The differential equation can be solved analytically and requires low computing effort. Explicit expressions are gained concerning the earliest possible due date (due date quoting problem) and the latest possible insertion position (rescheduling problem) in order to meet the customer requested due date. The differential equation model is compared with an approach based on a recently introduced hybrid binomial inverse hypergeometric probability distribution for the due date quoting problem. The analytical results of the proposed model are very close to the expectation values (these cannot be explicitly calculated, and high computation effort is required) of the recently introduced approach.
Journal: International Journal of Production Research
Pages: 1206-1220
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2179342
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2179342
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# input file: TPRS_A_2178833_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Qi Qi
Author-X-Name-First: Qi
Author-X-Name-Last: Qi
Author-Name: Shanling Li
Author-X-Name-First: Shanling
Author-X-Name-Last: Li
Author-Name: Ren-Qian Zhang
Author-X-Name-First: Ren-Qian
Author-X-Name-Last: Zhang
Title: Optimal joint decisions of production and emission reduction considering firms’ risk aversion and carbon tax rate
Abstract: 
 Carbon tax represents governments’ approach to steering the economy towards a greener future. Our research question focuses on the impact of carbon tax policy on a firm’s production decision and revenue and on total social welfare. In particular, we assume that a firm’s decision is subject to its behavioural considerations or, in other words, its risk attitude. We model a government plan to charge a carbon tax, and a risk-averse (or risk-neutral) firm needs to plan its production and estimate its profit if the carbon tax policy is implemented. We show that it is possible for a risk-averse firm’s optimal profit, in some cases, to be higher than that of a risk-neutral firm when facing a carbon tax. This implies that the risk-averse attitude is not necessarily harmful to the firm’s profit. For operations management scholars, our model highlights the importance of integrating firms’ behavioural responses into the carbon tax price. Our model suggests that for governments to implement carbon tax policy effectively, they should make carbon prices vary under certain conditions and not worry about price variation antagonising firms at large.
Journal: International Journal of Production Research
Pages: 1189-1205
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2178833
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2178833
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# input file: TPRS_A_2180308_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Ajit Sharma
Author-X-Name-First: Ajit
Author-X-Name-Last: Sharma
Title: Making electric vehicle batteries safer through better inspection using artificial intelligence and cobots
Abstract: 
 High quality, safe, and reliable batteries are essential for widespread adoption of electric vehicles. Current Li-ion battery pack manufacturing processes rely on manual inspections to ensure electric vehicle battery quality. Such manual quality control is prone to errors, increasing the chances of defective batteries. This is likely to increase safety and reliability concerns in the public imagination, slowing down the adoption of electric vehicles. Furthermore, manual inspection is time-consuming and likely to become a bottleneck in scaling up electric vehicle battery production. A potential solution to address this need for fast and accurate inspection of batteries is the use of machine vision and robotics. In this study, we use digital twin design and simulation to develop a battery module inspection system that uses cobots and machine vision to inspect electric vehicle batteries for defects. Our proposed system can automate visual quality checks that are currently being done by human operators. The proposed cobotic system has been simulated and validated for a variety of battery defects to achieve fast and reliable detection. Since a digital twin of the cobotic inspection workcell has been used, the battery inspection system, as designed and validated, is ready for immediate implementation.
Journal: International Journal of Production Research
Pages: 1277-1296
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2180308
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2180308
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# input file: TPRS_A_2182148_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Chunguang Bai
Author-X-Name-First: Chunguang
Author-X-Name-Last: Bai
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Author-Name: Sherwat Ibrahim
Author-X-Name-First: Sherwat
Author-X-Name-Last: Ibrahim
Title: An analytical method for investigating multi-tier sustainable supply chains: simplifying the complex
Abstract: 
 Multi-tier sustainable supply chain relationships (MSSCR) are complex with involvement of multiple organisations, practices, objectives, and interconnectivities. These complexities make it difficult to effectively study MSSCR using traditional empirical statistical correlative research. In MSSCR the relationship between the focal firm and sub-supplier may be affected by the relationship between the focal firm and direct-supplier, and the relationship between the direct-supplier and the sub-supplier. This paper introduces a research methodology, based on K-Means clustering, rough set theory, and cluster membership to investigate complex relationships across multi-tier sustainable supply chain triads. Collaborative advantage variables including knowledge-sharing routines, relation-specific investments, complementary capabilities, effective governance mechanisms, and long-term commitment are conceptually presented to evaluate relationships among MSSCR practices and sustainability performance. Insights for practitioners and researchers are provided. Research insights can be gained by analytically providing alternative explanatory and equifinality relationships amongst variables and multi-pair organisations. The methodology can mitigate the endogeneity problem, such as omitted factors (variables), measurement error, even in small sample data situations. Directions for future research are discussed.
Journal: International Journal of Production Research
Pages: 1318-1335
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2182148
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2182148
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# input file: TPRS_A_2281663_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Edward Elson Kosasih
Author-X-Name-First: Edward Elson
Author-X-Name-Last: Kosasih
Author-Name: Emmanuel Papadakis
Author-X-Name-First: Emmanuel
Author-X-Name-Last: Papadakis
Author-Name: George Baryannis
Author-X-Name-First: George
Author-X-Name-Last: Baryannis
Author-Name: Alexandra Brintrup
Author-X-Name-First: Alexandra
Author-X-Name-Last: Brintrup
Title: A review of explainable artificial intelligence in supply chain management using neurosymbolic approaches
Abstract: 
 Artificial Intelligence (AI) has emerged as a complementary technology in supply chain research. However, the majority of AI approaches explored in this context afford little to no explainability, which is a significant barrier to a broader adoption of AI in supply chains. In recent years, the need for explainability has been a strong impetus for research in hybrid AI methodologies that combine neural architectures with logic-based reasoning, which are collectively referred to as Neurosymbolic AI. The aim of this paper is to provide a comprehensive overview of supply chain management literature that employs approaches within the neurosymbolic AI spectrum. To that end, a systematic review is conducted, followed by bibliometric, descriptive and thematic analyses on the identified studies. Our findings indicate that researchers have primarily focused on the limited subset of neurofuzzy approaches, while some supply chain applications, such as performance evaluation and sustainability, and sectors such as pharmaceutical and construction have received less attention. To help address these gaps, we propose five pillars of neurosymbolic AI research for supply chains and provide four use cases of applying unexplored neurosymbolic AI approaches to address typical problems in supply chain management, including a discussion of prerequisites for adopting such technologies. We envision that the findings and contributions of this survey will help encourage further research in neurosymbolic AI for supply chains and increase adoption of such technologies within supply chain practice.
Journal: International Journal of Production Research
Pages: 1510-1540
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2281663
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2281663
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# input file: TPRS_A_2180307_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Laureano F. Escudero
Author-X-Name-First: Laureano F.
Author-X-Name-Last: Escudero
Author-Name: M. Araceli Garín
Author-X-Name-First: M. Araceli
Author-X-Name-Last: Garín
Author-Name: Aitziber Unzueta
Author-X-Name-First: Aitziber
Author-X-Name-Last: Unzueta
Title: On solving the cross-dock door assignment problem
Abstract: 
 A class of strong lower bounds on the solution value of a Linearised Integer Programming reformulation is introduced for the binary quadratic optimisation model to assign origin and destination nodes to strip and stack doors, resp., in a cross-dock infrastructure. The goal is to minimise the transportation cost of the commodities to be handled at the cross-dock. Strip- and stack-related decomposition submodels are developed by taking benefit of the Integer Linearisation Property that appears in the new model. A linear search heuristic is also provided for obtaining feasible solutions by exploiting the special structure of the problem. We present an extensive computational study on a testbed of 55 instances to show that the proposed joint scheme for lower bounding and feasible solution providing is very efficient. The results obtained by our proposal are similar to those obtained by CPLEX in the 50 instances taken from the literature, but usually the time is much smaller for the large instances. The comparison with CPLEX is particularly good for the new five largest instances, which make it very promising for its application in real-life cases.
Journal: International Journal of Production Research
Pages: 1262-1276
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2180307
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2180307
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# input file: TPRS_A_2181025_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Duo Wang
Author-X-Name-First: Duo
Author-X-Name-Last: Wang
Author-Name: Junlong Zhang
Author-X-Name-First: Junlong
Author-X-Name-Last: Zhang
Title: Flow shop scheduling with human–robot collaboration: a joint chance-constrained programming approach
Abstract: 
 Human–robot collaboration has been incorporated into production and assembly processes to promote system flexibility, changeability and adaptability. However, it poses new challenges to resource allocation and production scheduling due to its intrinsic uncertainty and also the increasing complexity of resources. This paper investigates a stochastic flow shop scheduling problem in the context of human–robot collaboration. The goal is to achieve efficient utilisation of flexible resources including human workers and cobots and take full advantage of human–robot collaboration in production scheduling. A stochastic Cobb–Douglas production function is utilised to evaluate the production efficiency of human–robot collaboration considering instabilities of human performance. A joint chance-constrained programming model is formulated to ensure that the required system performance can be achieved. A CVaR approximation-based approach is proposed to solve the formulated model with mixed-integer variables and a nonconvex constraint. The effectiveness of the formulated model and the efficiency of the proposed solution approach are evaluated via numerical experiments. Computational results show the superiority of our solution approach over three other approaches including Bonferroni approximation, scenario approach and individual chance-constrained programming.
Journal: International Journal of Production Research
Pages: 1297-1317
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2181025
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2181025
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# input file: TPRS_A_2191143_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Qing Yue
Author-X-Name-First: Qing
Author-X-Name-Last: Yue
Author-Name: Shenghai Zhou
Author-X-Name-First: Shenghai
Author-X-Name-Last: Zhou
Author-Name: Haiyan Yan
Author-X-Name-First: Haiyan
Author-X-Name-Last: Yan
Title: Due-date assignment scheduling with only mean and support of processing times
Abstract: 
 We consider a single-machine scheduling problem with due-date assignment and stochastic processing times, where only the mean and support (i.e. an interval bounded with lower and upper values) of processing times are known to the decision maker. The objective is to jointly determine a scheduling policy and a set of due dates for all jobs, so as to minimise the total expected individually weighted costs of earliness, tardiness and due-date assignment. By identifying an upper bound with the robust optimisation approach and a lower bound, and using a linear function of them to approximate the studied objective function, we establish an approximated problem. Then, a branch-and-bound algorithm is proposed to find an optimal solution for the approximated problem. Finally, a series of computational experiments are conducted to examine the performance of problem approximation and two developed heuristic algorithms.HIGHLIGHTS
Study due-date assignment scheduling problem with stochastic processing times.Apply the mean and support (interval data) to model stochastic processing times.Use a linear function of identified lower and upper bounds to make an approximation.Derive optimal due-date assignment and develop branch-and-bound algorithms.Evaluate the efficiency of branch-and-bound algorithm and heuristic algorithms.
Journal: International Journal of Production Research
Pages: 1358-1381
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2191143
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2191143
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# input file: TPRS_A_2180304_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Lorenzo Tiacci
Author-X-Name-First: Lorenzo
Author-X-Name-Last: Tiacci
Title: Assigning rest times to workers in assembly lines with ergonomically hazardous tasks: an approach to defend companies’ profitability
Abstract: 
 In the context of assembly lines, the term ‘rest time’ refers to those time of inactivity allowed to a worker after the completion of his/her tasks on a product. Rest times are often assigned to workers that perform ergonomically hazardous tasks, to prevent their occupational diseases. When rest times are assigned after balancing the line, the line becomes unbalanced and the ergonomic load of workers is reduced at the price of deteriorated line performance. In this paper, an approach able to assign rest times during the balancing procedure is presented. The approach consists of a genetic algorithm coupled with a discrete event simulator to evaluate the fitness function of individuals, which considers the performance, the ergonomic, and the cost aspects. The OCRA index has been utilised to assess the ergonomic risk of workers. Results show that the presented approach can significantly support firms in designing manual assembly lines: the possibility to assign rest times during the balancing procedure allows for increasing the quality of solutions in 103 out of 135 benchmark instances. The greatest improvements are obtained when the ergonomic load of tasks is relevant, by achieving good performances of the line with limited costs, thus defending companies’ profitability.
Journal: International Journal of Production Research
Pages: 1239-1261
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2180304
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# input file: TPRS_A_2229992_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: The Editors
Title: Correction Notice
Journal: International Journal of Production Research
Pages: (i)-(ii)
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2229992
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2229992
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# input file: TPRS_A_2176698_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Congying Deng
Author-X-Name-First: Congying
Author-X-Name-Last: Deng
Author-Name: Jielin Tang
Author-X-Name-First: Jielin
Author-X-Name-Last: Tang
Author-Name: Sheng Lu
Author-X-Name-First: Sheng
Author-X-Name-Last: Lu
Author-Name: Ying Ma
Author-X-Name-First: Ying
Author-X-Name-Last: Ma
Author-Name: Lijun Lin
Author-X-Name-First: Lijun
Author-X-Name-Last: Lin
Author-Name: Jianguo Miao
Author-X-Name-First: Jianguo
Author-X-Name-Last: Miao
Title: Improved milling stability analysis for chatter-free machining parameters planning using a multi-fidelity surrogate model and transfer learning with limited experimental data
Abstract: 
 Decision-making on chatter-free machining parameters is essential for process planning since chatter significantly affects production quality and efficiency. Stability lobe diagram (SLD) is commonly used for selecting chatter-free machining parameters, but its analytical prediction often has poor accuracy and experiment-based prediction is time-consuming. This paper proposes a multi-fidelity (MF) surrogate model and transfer learning-based method to improve the milling stability analysis. Firstly, an analytical stability model is constructed to predict low-fidelity (LF) SLDs for key combinations of radial cutting width (ae) and feed rate per tooth (ft). A few spindle speeds (ns) are selected from each key LF SLD to detect high-fidelity (HF) stability limits (aplim) through milling experiments. Subsequently, sufficient LF and limited HF combinations of ns, ae, ft, and aplim are taken to construct additive scaling function-based MF stability models. Predicted MF combinations of ns, ae, ft, and aplim are combined with limited HF combinations to construct more accurate stability models through transfer learning. Then, a neural network is ultimately trained to predict aplim values for arbitrary combinations of ns, ae, and ft. A detailed experimental validation indicates that the proposed method can provide more accurate lobe boundaries for machining parameters selection by introducing fewer experimental samples.
Journal: International Journal of Production Research
Pages: 1126-1143
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2176698
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2176698
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# input file: TPRS_A_2176179_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yingjie Fan
Author-X-Name-First: Yingjie
Author-X-Name-Last: Fan
Author-Name: Frank Schwartz
Author-X-Name-First: Frank
Author-X-Name-Last: Schwartz
Author-Name: Stefan Voß
Author-X-Name-First: Stefan
Author-X-Name-Last: Voß
Author-Name: David L. Woodruff
Author-X-Name-First: David L.
Author-X-Name-Last: Woodruff
Title: Catastrophe insurance and flexible planning for supply chain disruption management: a stochastic simulation case study
Abstract: 
 Catastrophe-related insurance (e.g. business interruption insurance) is an effective financing tool for global corporations to reduce economic losses caused by high impact events. Flexible operational planning is an often-used tool enabling rapid adjustment of operational plans for reducing catastrophe-related damage costs. The interaction between catastrophe insurance and flexible operations planning has rarely been studied. In this paper, we develop a stochastic programming model for a multi-echelon global supply chain network that we solve to investigate the impact of purchasing catastrophe insurance on supply chain operational planning in a catastrophe-prone environment. Computational simulations are developed for evaluating solution quality and measuring catastrophe-related damage costs. We find that it may be optimal for supply chains to scrap redundant products in catastrophes when customer demand falls below the expected level. Purchasing catastrophe insurance may encourage supply chains to scrap more products, which results in more catastrophe-related damages. From analysing supply chain costs, catastrophe-related damage costs, and operational plans, we find that a higher compensation rate of catastrophe insurance triggers more production activities being planned at the vulnerable node just before the vulnerable time period, especially for low residual value products. Finally, we give managerial insights to help reduce unnecessary damages in catastrophes.
Journal: International Journal of Production Research
Pages: 1108-1125
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2176179
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2176179
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# input file: TPRS_A_2180302_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Pranesh Saisridhar
Author-X-Name-First: Pranesh
Author-X-Name-Last: Saisridhar
Author-Name: Matthias Thürer
Author-X-Name-First: Matthias
Author-X-Name-Last: Thürer
Author-Name: Balram Avittathur
Author-X-Name-First: Balram
Author-X-Name-Last: Avittathur
Title: Assessing supply chain responsiveness, resilience and robustness (Triple-R) by computer simulation: a systematic review of the literature
Abstract: 
 Ever more interconnected and complex supply chains increase the risk of disruptions and their propagation. Companies need to simultaneously develop capabilities such as responsiveness, resilience, and robustness (Triple-R) to hedge against these risks, while staying competitive. This requires careful investment decisions on which portfolio of Triple-R strategies to create. Being a dynamic, transient phenomena, analytical tools are often not feasible to quantify effects. Computer simulation provides an important alternative, which led to a surge of literature in recent years. This study conducted a systematic literature review of studies that use computer simulation for assessing Triple-R capabilities. Based on a final sample of 174 full articles, we found that classical means to create Triple-R capabilities have been widely assessed for a broad set of different disruption characteristics, including type of disruption and type of propagation. But, while there exists a broad literature that focusses on engineering resilience and adaptation, more research is needed that focusses on resilience as transformation. Recent disruptions are social-ecological disruptions that require new mitigation strategies. To appropriately design and assess these strategies, which need to consider societal impacts towards Industry 5.0, hybrid simulations, online simulations, and physical simulations are required that can model social-ecological aspects and contexts.
Journal: International Journal of Production Research
Pages: 1458-1488
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2180302
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2180302
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# input file: TPRS_A_2179350_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Zhen-Yu Chen
Author-X-Name-First: Zhen-Yu
Author-X-Name-Last: Chen
Title: Data-driven risk-averse newsvendor problems: developing the CVaR criteria and support vector machines
Abstract: 
 Incorporating decision-makers' risk preferences into data-driven newsvendor models and developing machine learning methods to solve the models are the challenging problems addressed in this study. To consider different distributions and decision-makers' different risk preferences for the two losses of the total cost newsvendor model, the symmetrical, the partial symmetrical and the asymmetrical CVaR criteria are introduced. The regularisation, the primal-dual approach and the kernels in support vector machines are used to transform the data-driven risk-averse newsvendor problems under the CVaR criterion into the convex quadratic programming problems with good theoretical properties. Computational experiments are conducted on a real-world dataset. The models under the partial symmetrical and the asymmetrical CVaR criteria obtained good performances, but that under the symmetrical CVaR criterion suffered the underfitting problem. Two factors including the degrees of risk aversion for the two losses in the total cost newsvendor model and the empirical errors of data-driven models affect order decisions. The degrees of risk aversion for the two losses have anti-directional effects on order quantities. The introduction of asymmetrical CVaR criterion paves a new way to reveal the effects of different risk references for different losses on order decisions, and has the potential to improve newsvendor decisions.
Journal: International Journal of Production Research
Pages: 1221-1238
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2179350
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# input file: TPRS_A_2177087_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yuhong Ren
Author-X-Name-First: Yuhong
Author-X-Name-Last: Ren
Author-Name: Jiafu Tang
Author-X-Name-First: Jiafu
Author-X-Name-Last: Tang
Author-Name: Yang Yu
Author-X-Name-First: Yang
Author-X-Name-Last: Yu
Author-Name: Xiaolong Li
Author-X-Name-First: Xiaolong
Author-X-Name-Last: Li
Title: A two-stage stochastic programming model and parallel Master–Slave adaptive GA for flexible Seru system formation
Abstract: 
 High flexibility is an important feature of seru system that has received less attention. In this paper, we discuss how to do such flexible seru system formation, especially focusing on the strategic decision phase. We formulate the flexible seru system formation problem (FSFP) as a nonlinear programming model to evaluate flexibility performance in terms of flexibility–investment cost and flexibility–loss cost. To exactly obtain the optimal solution of the FSFP, we transform the nonlinear model into a linear one and solve it with Gurobi solver. For the large-scale problem, we proposed a parallel Master–Slave adaptive genetic algorithm (PMSA-GA) by transforming it into a two-stage stochastic programming model. The adaptive selection is used to improve the quality of solutions in PMSA-GA. To reduce the computational time, multiple populations of seru formation evolve in parallel with the assistance of the Master–Slave mechanism. Extensive experiments are tested to evaluate the performance of the proposed model and algorithm, and the effect of cost parameters on the system performance is discussed. The results show that the FSFP model takes the property of dynamic demand into account and is more suitable for dynamic demand environments than the task-oriented seru formation (TOSF) strategy from the previous literature.
Journal: International Journal of Production Research
Pages: 1144-1161
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2177087
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# input file: TPRS_A_2192294_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Pengwen Hou
Author-X-Name-First: Pengwen
Author-X-Name-Last: Hou
Author-Name: Chi Zhang
Author-X-Name-First: Chi
Author-X-Name-Last: Zhang
Author-Name: Yating Li
Author-X-Name-First: Yating
Author-X-Name-Last: Li
Title: The interplay of manufacturer encroachment and blockchain adoption to combat counterfeits in a platform supply chain
Abstract: 
 Consumers’ perception of product value when purchasing is a critical issue relative to online platform commerce. This is especially true when the brand manufacturer authorises only a third-party reseller to sell through the platform, a practice that may provide opportunities to counterfeiters. To address this issue, we establish a theoretical model in which one brand manufacturer wholesales its products to a third-party reseller who then sells through an online platform. The platform acts as a marketplace, while multiple counterfeiters also exist on the platform, which may deceive consumers. In particular, we consider that the manufacturer can encroach with a direct channel and that the platform can adopt blockchain technology to help consumers identify authenticity. The results show that the platform could induce the brand manufacturer to encroach by deploying blockchain technology. Furthermore, an interesting result indicates that although either manufacturer encroachment or blockchain technology used alone can effectively boycott counterfeits, the coexistence of two strategies can raise the demand for counterfeit products. Finally, we find that when the brand manufacturer encroaches on the platform and the platform adopts blockchain technology, the brand manufacturer, platform, reseller and social welfare can achieve Pareto improvement, while the consumer surplus may be worse off.
Journal: International Journal of Production Research
Pages: 1382-1398
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2192294
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2192294
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# input file: TPRS_A_2175591_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Ahmed Maged
Author-X-Name-First: Ahmed
Author-X-Name-Last: Maged
Author-Name: Chun Fai Lui
Author-X-Name-First: Chun Fai
Author-X-Name-Last: Lui
Author-Name: Salah Haridy
Author-X-Name-First: Salah
Author-X-Name-Last: Haridy
Author-Name: Min Xie
Author-X-Name-First: Min
Author-X-Name-Last: Xie
Title: Variational AutoEncoders-LSTM based fault detection of time-dependent high dimensional processes
Abstract: 
 In modern large-scale industrial processes, data are often high dimensional time-dependent due to the frequent sampling, dynamic nature and large number of variables. Appropriate monitoring of such processes allows for efficient decision-making that can improve the baseline of manufacturing companies either through decreasing production costs or enhancing production efficiency. Various latent variable-based control charts have been proposed for addressing high dimensional data; however, many of these methods assume that the data are independent and normally distributed. The violation of these assumptions results in an increased false alarm rate, in addition to the deterioration in the performance of such methods. In this study, we propose a Variational Autoencoder-Long Short Term Memory (VAE-LSTM) deep learning based 
 $ {T^2} $ T2 chart that integrates the unique features of both VAE and LSTM for intelligent fault detection of time-dependent high dimensional processes. The effectiveness and applicability of the proposed model are demonstrated through extensive simulations, an open-source online dataset, and a real case study.
Journal: International Journal of Production Research
Pages: 1092-1107
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2175591
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# input file: TPRS_A_2270586_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Emilia Vann Yaroson
Author-X-Name-First: Emilia
Author-X-Name-Last: Vann Yaroson
Author-Name: Soumyadeb Chowdhury
Author-X-Name-First: Soumyadeb
Author-X-Name-Last: Chowdhury
Author-Name: Sachin Kumar Mangla
Author-X-Name-First: Sachin Kumar
Author-X-Name-Last: Mangla
Author-Name: Prasanta Dey
Author-X-Name-First: Prasanta
Author-X-Name-Last: Dey
Author-Name: Felix T. S. Chan
Author-X-Name-First: Felix T. S.
Author-X-Name-Last: Chan
Author-Name: Melanie Roux
Author-X-Name-First: Melanie
Author-X-Name-Last: Roux
Title: A systematic literature review exploring and linking circular economy and sustainable development goals in the past three decades (1991–2022)
Abstract: 
 Amid the escalating environmental crises and economic disparities, Circular Economy (CE) has garnered recognition as a pragmatic mechanism for achieving Sustainable Development Goals (SDGs). In response, several supply chain organisations are integrating CE strategies into their business operations and production processes. Despite these developments and since the introduction of Business Charter for Sustainable Development by the International Chamber of Commerce in 1991, the academic corpus comprehensively connecting CE research themes, catalysts, deterrents, practices with the SDGs has remained limited. To bridge this gap, we present a systematic literature review (SLR) of CE research in operations, supply chain and production management encompassing a time span of 31 years (January 1991 – June 2022), by sourcing, screening, and analysing articles obtained from multiple research databases. Our thematic coding analysis generated ten research themes, and subsequently linking them with relevant SDGs. Additionally, we interweaved CE catalysts and deterrents, establishing a connection with the SDGs. This is further enriched with CE strategies aimed at equipping business practitioners to enhance sustainable business performance and contributing to specific SDGs. Lastly, we delineate CE knowledge data management and priority actions frameworks to aid organisations to enhance employee capability and actively leverage digital technologies for implementing CE strategies.
Journal: International Journal of Production Research
Pages: 1399-1433
Issue: 4
Volume: 62
Year: 2024
Month: 02
X-DOI: 10.1080/00207543.2023.2270586
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:4:p:1399-1433

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# input file: TPRS_A_2200556_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Jianqiang Tang
Author-X-Name-First: Jianqiang
Author-X-Name-Last: Tang
Author-Name: Chao Qi
Author-X-Name-First: Chao
Author-X-Name-Last: Qi
Author-Name: Hongwei Wang
Author-X-Name-First: Hongwei
Author-X-Name-Last: Wang
Title: Integrated optimization of order splitting and distribution routing for the front warehouse mode e-retailing
Abstract: 
 Along with the rapid growth of online purchasing, more and more e-retailers tend to adopt the front warehouse mode to improve the performance of customer service by locating multiple front warehouses with limited space and storage capacity closer to consumers. In this context, order splitting and distribution become increasingly crucial decisions that might impact the efficiency of order fulfillment. These two issues are investigated in the related works commonly as two independent problems, although they are inherently coupled with each other. This study established an integrated optimization model for order splitting and distribution routing for the front warehouse mode e-retailing. The model considers practical features, including order splitting constraints based on product type and quantity, finite inventory, heterogeneous vehicle routing constraints, and time windows. A branch-price-and-cut algorithm is proposed to solve the problem. Two logic-based Benders cuts are designed to deal with the infeasible distribution routes. The efficiency of the proposed algorithm is verified in an experimental study by considering CPLEX and two heuristic algorithms as benchmark methods. The dominance of our proposed algorithm is observed, especially for large-scale cases. The impacts of overlapping inventory levels, the combination of heterogeneous vehicles, and the width of time windows are also examined.
Journal: International Journal of Production Research
Pages: 1715-1736
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2200556
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2200556
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# input file: TPRS_A_2201939_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Alessandra Cantini
Author-X-Name-First: Alessandra
Author-X-Name-Last: Cantini
Author-Name: Mirco Peron
Author-X-Name-First: Mirco
Author-X-Name-Last: Peron
Author-Name: Filippo De Carlo
Author-X-Name-First: Filippo
Author-X-Name-Last: De Carlo
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Title: A data-driven methodology for the periodic review of spare parts supply chain configurations
Abstract: 
 Configuring supply chains (SCs) is critical to spare parts retailers’ success, entailing two key aspects: stock deployment into distribution centres (DCs) (i.e. inventory centralisation or decentralisation) and stock supply in each DC (how many spare parts to supply and how often). Given the unpredictability of spare parts demand, stock deployment and supply policies should be regularly reviewed, adapting to fluctuations in customer needs. A viable way to do this is to adopt a multi-criteria ABC criticality classification. However, the multi-criteria ABC criticality classification has often been used to plan stock supply policies in a single DC, but only once to plan spare parts deployment. Nevertheless, the available literature methodology presents major limitations, being not applicable in real companies. Therefore, this paper provides a novel methodology, called SP-LACE, which first reviews the configuration of spare parts SCs based on a multi-criteria criticality classification. Then, allows, for the first time, to evaluate the economic benefits of the reviewed SC configuration. SP-LACE was tested on two case studies and compared with the literature methodology. The results indicate that it provides economic benefits (in terms of total SC cost), overcoming the limitations of the literature methodology and ensuring high service levels.
Journal: International Journal of Production Research
Pages: 1818-1845
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2201939
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2201939
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# input file: TPRS_A_2197079_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Kangzhou Wang
Author-X-Name-First: Kangzhou
Author-X-Name-Last: Wang
Author-Name: Hui Jing
Author-X-Name-First: Hui
Author-X-Name-Last: Jing
Author-Name: Dong-dong Wang
Author-X-Name-First: Dong-dong
Author-X-Name-Last: Wang
Author-Name: Feng Jiang
Author-X-Name-First: Feng
Author-X-Name-Last: Jiang
Title: Joint quality and maintenance decisions under servitization business model
Abstract: 
 Under servitization (one paradigm of non-ownership-transfer) business model such as sharing, a manufacturer is responsible not only for product design but also for maintenance. This paper deals with joint decision of product quality and maintenance under servitization. A model minimising total cost is formulated to obtain the optimal product quality, maintenance effort and maintenance times. We find that the total cost first decreases then increases with product quality, maintenance effort and maintenance times. Moderate quality and maintenance effort level are the best for the manufacturer, because too high or too low quality and effort cause too high total cost. However, preventive maintenance should be implemented as many times as possible until the failure cost is reduced to zero as long as each maintenance can save cost. Moreover, in the optimal joint decision, the product quality, maintenance effort and maintenance times are negatively correlated in pairs. In addition, we explore the impact of unit failure cost, product lifecycle, production cost, maintenance cost, and failure intensity on the manufacturer’s optimal decisions. In extensions, we further take penalty cost, exponential failure distribution, discount rate, and customer usage into account. This paper provides insight for the manufacturer to jointly consider product design and maintenance under servitization.
Journal: International Journal of Production Research
Pages: 1567-1585
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2197079
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2197079
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# input file: TPRS_A_2290229_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Xiaoshao Mu
Author-X-Name-First: Xiaoshao
Author-X-Name-Last: Mu
Author-Name: Maxwell Fordjour Antwi-Afari
Author-X-Name-First: Maxwell Fordjour
Author-X-Name-Last: Antwi-Afari
Title: The applications of Internet of Things (IoT) in industrial management: a science mapping review
Abstract: 
 With the rise of Internet of Things (IoT) technology, the seamless connection between the physical and digital worlds has been realized. This review paper aims to conduct a science mapping review of IoT applications in industrial management and to identify mainstream research topics, research gaps, and future research directions. Using VOSviewer as a visualization tool, 142 articles retrieved from the Scopus database were quantitatively discussed using scientometric analysis. Additionally, a follow-up qualitative discussion was focused on mainstream research topics, existing research gaps, and future research directions as the main research goals. The results revealed influential findings for the co-occurrence of keywords, journals, countries, authors, and documents analyses. Moreover, it was found that the existing research mainly focused on four main research topics including (1) application of IoT in manufacturing based on cyber-physical systems, (2) IoT-related technologies on logistics and supply chain management, (3) The impact of IoT on business models, and (4) Industrial IoT (IIoT) in the context of Industry 4.0. On this basis, the existing research gaps and future research directions are proposed. This review paper would help relevant practitioners and researchers to better understand the existing body of knowledge and lay the foundation for further research.
Journal: International Journal of Production Research
Pages: 1928-1952
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2290229
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2290229
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# input file: TPRS_A_2201352_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Tengfei Wu
Author-X-Name-First: Tengfei
Author-X-Name-Last: Wu
Author-Name: Zeqiang Zhang
Author-X-Name-First: Zeqiang
Author-X-Name-Last: Zhang
Author-Name: Yanqing Zeng
Author-X-Name-First: Yanqing
Author-X-Name-Last: Zeng
Author-Name: Yu Zhang
Author-X-Name-First: Yu
Author-X-Name-Last: Zhang
Title: Mixed-integer programming model and hybrid local search genetic algorithm for human–robot collaborative disassembly line balancing problem
Abstract: 
 Human–robot collaborative technology maximises the advantages of the capabilities of humans and robots, and provides diverse operating scenarios for the remanufacturing industry. Accordingly, this paper proposes an innovative human–robot collaborative disassembly line balancing problem (HRC-DLBP). First, a mixed-integer programming (MIP) model is devised for the HRC-DLBP to minimise the number of workstations, smoothness index, and various costs. Second, a hybrid local search genetic algorithm (HLSGA) is developed to solve the proposed HRC-DLBP efficiently. According to the problem characteristics, a four-layer encoding and decoding strategy was constructed. The search mechanism of the local search operator was improved, and its search strategy was adjusted to suit the genetic algorithm structure better. Furthermore, the accuracy of the proposed MIP model and HLSGA is verified through two HRC-DLBP examples. Subsequently, three HRC-DLBP examples are used to prove that the HLSGA is superior to five other excellent algorithms. The case of the two-sided disassembly line problem reported in the literature is also solved using the HLSGA. The results are found to be significantly better than the reported outputs of the improved whale optimisation algorithm. Besides, HLSGA also outperforms the results reported in the literature in solving EOL state-oriented DLBP. Finally, the HLSGA is applied to a power battery disassembly problem, and several optimal allocation schemes are obtained.
Journal: International Journal of Production Research
Pages: 1758-1782
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2201352
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2201352
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# input file: TPRS_A_2201860_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Zhibo Zhang
Author-X-Name-First: Zhibo
Author-X-Name-Last: Zhang
Author-Name: Chandan Kumar Sahu
Author-X-Name-First: Chandan Kumar
Author-X-Name-Last: Sahu
Author-Name: Shubhendu Kumar Singh
Author-X-Name-First: Shubhendu Kumar
Author-X-Name-Last: Singh
Author-Name: Rahul Rai
Author-X-Name-First: Rahul
Author-X-Name-Last: Rai
Author-Name: Zhuo Yang
Author-X-Name-First: Zhuo
Author-X-Name-Last: Yang
Author-Name: Yan Lu
Author-X-Name-First: Yan
Author-X-Name-Last: Lu
Title: Machine learning based prediction of melt pool morphology in a laser-based powder bed fusion additive manufacturing process
Abstract: 
 Laser-based powder bed fusion (L-PBF) has become the de facto choice for metal additive manufacturing (AM) processes. Even after considerable research investments, components manufactured using L-PBF lack consistency in their quality. Realizing the crucial role of the melt pool in controlling the final build quality, we predict the morphology of the melt pool directly from the build commands in an L-PBF process. We leverage machine learning techniques to predict quantitative attributes like the size as well as qualitative attributes like the shape of the melt pool. The area of the melt pool is predicted using an LSTM network. The outlined LSTM-based approach estimates the area with 
 $ 90.7\% $ 90.7% accuracy. The shape is inferred by synthesising the images of the melt pool by using a Melt Pool Generative Adversarial Network (MP-GAN). The synthetic images attain a structural similarity score of 0.91. The precision and accuracy of the results showcase the efficacy of the outlined approach and pave the way for real-time monitoring and control of the melt pool to build products with consistently better quality.
Journal: International Journal of Production Research
Pages: 1803-1817
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2201860
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2201860
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# input file: TPRS_A_2128462_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Junhyeok Lee
Author-X-Name-First: Junhyeok
Author-X-Name-Last: Lee
Author-Name: Changseong Ko
Author-X-Name-First: Changseong
Author-X-Name-Last: Ko
Author-Name: Ilkyeong Moon
Author-X-Name-First: Ilkyeong
Author-X-Name-Last: Moon
Title: E-commerce supply chain network design using on-demand warehousing system under uncertainty
Abstract: 
 During the COVID-19 pandemic, e-commerce retailers have had trouble satisfying the growing demand because of limited warehouse capacity constraints. Fortunately, an on-demand warehousing system has emerged as a new alternative to mitigate warehouse capacity issues. In recent years, several studies have focused on the supply chain problem considering on-demand warehousing. However, there is no study that deals simultaneously with inherent uncertainties and the property of commitment, which is the main advantage of on-demand warehousing. To fill these research gaps, this paper presents an e-commerce supply chain network design problem considering an on-demand warehousing and decisions for commitment periods. We propose the two-stage stochastic programming model that captures the inherent uncertainties to formulate the presented problem. We solve the proposed model utilizing sample average approximation combined with the Benders decomposition algorithm. Of particular note, we develop a method to generate effective initial cuts for improving the convergence speed of the Benders decomposition algorithm. Computational results show that the developed method could find an effective feasible solution within a reasonable computational time for problems of practical size. Furthermore, we show the significant cost-saving effects, based on experiment results, that occur when an on-demand warehousing system is used for designing supply chain networks.
Journal: International Journal of Production Research
Pages: 1901-1927
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2022.2128462
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2128462
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# input file: TPRS_A_2199438_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Mengfei Chen
Author-X-Name-First: Mengfei
Author-X-Name-Last: Chen
Author-Name: Richard Furness
Author-X-Name-First: Richard
Author-X-Name-Last: Furness
Author-Name: Rajesh Gupta
Author-X-Name-First: Rajesh
Author-X-Name-Last: Gupta
Author-Name: Saumuy Puchala
Author-X-Name-First: Saumuy
Author-X-Name-Last: Puchala
Author-Name: Weihong (Grace) Guo
Author-X-Name-First: Weihong (Grace)
Author-X-Name-Last: Guo
Title: Hierarchical RNN-based framework for throughput prediction in automotive production systems
Abstract: 
 Throughput analysis plays an important role in the operations and management of automotive manufacturing. Predicting how the system throughput changes over time helps the plant managers to make timely operational decisions to meet the daily production requirement. In today’s automotive production systems, the availability of sensing data reflecting process variables and machine status across the plant floor raises new opportunities for improving the throughput prediction accuracy. However, challenges exist in extracting the most important features from the high-dimensional data and capturing the complicated time-vary interdependency among different assets in the system. To overcome such challenges, in this paper we propose a hierarchical Recurrent Neural Network (RNN)-based framework that is composed of clustering, dimension reduction and feature selection, regression, and prediction pruning/adjustment. In addition to predicting end-of-line throughput, our framework then identifies the associations for low throughput to facilitate downtime prevention and maintenance decision-making. The proposed framework is applied to an automotive production system, and its effectiveness is demonstrated by comparison with conventional methods.
Journal: International Journal of Production Research
Pages: 1699-1714
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2199438
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2199438
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# input file: TPRS_A_2196352_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yingjia Wang
Author-X-Name-First: Yingjia
Author-X-Name-Last: Wang
Author-Name: Xiaoyan Xu
Author-X-Name-First: Xiaoyan
Author-X-Name-Last: Xu
Author-Name: Tsan-Ming Choi
Author-X-Name-First: Tsan-Ming
Author-X-Name-Last: Choi
Author-Name: Bin Shen
Author-X-Name-First: Bin
Author-X-Name-Last: Shen
Title: Will the presence of ‘fashion knockoffs’ benefit the original-designer-label product supply chain?
Abstract: 
 Fashion knockoffs, which refer to the copycat behaviours of some brands in fashion apparel, are widely seen. It is commonly believed that the presence of fashion knockoffs harms the original-designer-label (ODL) product seller. Motivated by the industrial interviews and real-world observations, we build game-theoretical models to examine the impacts of fashion knockoffs on the ODL product supply chain and its agents with the consideration of risk attitudes. Explicitly, in the basic model, we consider a common manufacturer producing for both a knockoff product seller and a risk sensitive ODL product seller. The ODL product seller and the knockoff product seller make pricing decisions to optimise their own profits. We interestingly find that the presence of fashion knockoffs benefits the ODL product supply chain and its agents when (i) the ODL product seller is risk averse and the ratio of demand uncertainty is relatively small or (ii) the ODL product seller is risk seeking and the ratio of demand uncertainty is sufficiently large. The findings indicate that a risk averse (seeking) ODL product seller is more prone to benefit from the presence of fashion knockoffs when selling fashionable (classic) products.
Journal: International Journal of Production Research
Pages: 1541-1566
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2196352
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2196352
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# input file: TPRS_A_2197515_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Pablo Becerra
Author-X-Name-First: Pablo
Author-X-Name-Last: Becerra
Author-Name: Josefa Mula
Author-X-Name-First: Josefa
Author-X-Name-Last: Mula
Author-Name: Raquel Sanchis
Author-X-Name-First: Raquel
Author-X-Name-Last: Sanchis
Title: Optimising location, inventory and transportation in a sustainable closed-loop supply chain
Abstract: 
 Operations management researchers and practitioners have shown increasing interest in incorporating sustainability into supply chain (SC) design models. This means that sustainability must be considered in all aspects of the SC, including location, inventory and transportation (LIT) decisions. Hence the aim of this article is to propose an optimisation model that incorporates: (i) LIT decisions in an integrated manner; (ii) the three sustainability (3S) aspects, i.e. economic, environmental and social, into each named decisions; and (iii) a closed-loop supply chain (CLSC) structure. The proposed formulation is a multi-objective mixed integer non-linear programming (MO-MINLP) model whose objectives consider minimisation of economic and social costs (economic aspect) and carbon emissions (environmental aspect), and maximisation of the social impact of SC operations (social aspect). A transformation technique is applied to one of the objective functions, which results in an MO-MILP model solved by the lexicographic method. This article focuses on commodity industries where only one finished product is manufactured. Hence the 3S-LIT model is validated with a randomly generated dataset and against a recently published alternative model applied to the copper mining industry.
Journal: International Journal of Production Research
Pages: 1609-1632
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2197515
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2197515
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# input file: TPRS_A_2202275_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Xiaojun Zhou
Author-X-Name-First: Xiaojun
Author-X-Name-Last: Zhou
Author-Name: Xurui Ben
Author-X-Name-First: Xurui
Author-X-Name-Last: Ben
Title: Maintenance modelling for work rolls in hot finishing mill group with constraint of thermal character
Abstract: 
 A maintenance model is specially developed for the work rolls equipped in the hot finishing mill group, with the purpose to decrease the total maintenance cost for the roll group under the constraint of the production batches and the roll thermal character. During the maintenance modelling at roll level, the impacts of the surface wear of the work roll on its failure rate state, the production quality and the preventive maintenance cost are deeply discussed. Then, a preventive maintenance grouping method is further proposed at roll group level, with the mutual restriction between the adjustable replacement time of the roll group and the optimal maintenance time of each work roll involved. The case study shows that the proposed maintenance model is practical for the maintenance scheduling of the work rolls in the real rolling production scenario. The total maintenance cost under the proposed maintenance method is always lower that the ones under the individual OM method and the maintenance window-based OM method.
Journal: International Journal of Production Research
Pages: 1846-1861
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2202275
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2202275
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# input file: TPRS_A_2200567_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Mingjie Bi
Author-X-Name-First: Mingjie
Author-X-Name-Last: Bi
Author-Name: Ilya Kovalenko
Author-X-Name-First: Ilya
Author-X-Name-Last: Kovalenko
Author-Name: Dawn M. Tilbury
Author-X-Name-First: Dawn M.
Author-X-Name-Last: Tilbury
Author-Name: Kira Barton
Author-X-Name-First: Kira
Author-X-Name-Last: Barton
Title: Dynamic distributed decision-making for resilient resource reallocation in disrupted manufacturing systems
Abstract: 
 The COVID-19 pandemic brings many unexpected disruptions, such as frequently shifting markets and limited human workforce, to manufacturers. To stay competitive, flexible and real-time manufacturing decision-making strategies are needed to deal with such highly dynamic manufacturing environments. One essential problem is dynamic resource allocation to complete production tasks, especially when a resource disruption (e.g. machine breakdown) occurs. Though multi-agent methods have been proposed to solve the problem in a flexible and agile manner, the agent internal decision-making process and resource uncertainties have rarely been studied. This work introduces a model-based resource agent (RA) architecture that enables effective agent coordination and dynamic agent decision-making. Based on the RA architecture, a rescheduling strategy that incorporates risk assessment via a clustering agent coordination strategy is also proposed. A simulation-based case study is implemented to demonstrate dynamic rescheduling using the proposed multi-agent framework. The results show that the proposed method reduces the computational efforts while losing some throughput optimality compared to the centralised method. Furthermore, the case study illustrates that incorporating risk assessment into rescheduling decision-making improves the throughput.
Journal: International Journal of Production Research
Pages: 1737-1757
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2200567
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2200567
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# input file: TPRS_A_2118890_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Jaeseok Lee
Author-X-Name-First: Jaeseok
Author-X-Name-Last: Lee
Author-Name: Min Kyung Lee
Author-X-Name-First: Min Kyung
Author-X-Name-Last: Lee
Author-Name: Seongkyoon Jeong
Author-X-Name-First: Seongkyoon
Author-X-Name-Last: Jeong
Author-Name: Brandon Lee
Author-X-Name-First: Brandon
Author-X-Name-Last: Lee
Author-Name: Minseok Park
Author-X-Name-First: Minseok
Author-X-Name-Last: Park
Title: Responding to epidemic-driven demand: the role of supply channels
Abstract: 
 Matching the supply of medical equipment with soaring demand caused by an epidemic event is a daunting challenge. Focusing on medical equipment manufacturers, this study empirically examines how supply chain management impacts manufacturers’ responses to epidemic-driven demand. This study employs novel supply chain data from South Korea collected before and after the MERS (Middle East Respiratory Syndrome) epidemic event. In the results, we show that such an epidemic positively influences the sales performance of medical equipment manufacturers (i.e. a 10.2 percentage-point increase). To identify the mechanism behind this result, we provide evidence that increasing the supply base (i.e. the number of supply channels) enables medical equipment manufacturers to better respond to epidemic-driven demand and ultimately improves their sales performance. More interestingly, we find that medical equipment manufacturers with lower market status (i.e. lower market shares and lower supplier shares) expand their supply bases more extensively than other medical equipment manufacturers with higher market status do. Interpreting these results, we offer managerial insights into how medical equipment manufacturers can effectively manage their supply chains and improve their performance when responding to epidemic-driven demand.
Journal: International Journal of Production Research
Pages: 1879-1900
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2022.2118890
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2118890
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# input file: TPRS_A_2199435_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Kamal Sanguri
Author-X-Name-First: Kamal
Author-X-Name-Last: Sanguri
Author-Name: Sabyasachi Patra
Author-X-Name-First: Sabyasachi
Author-X-Name-Last: Patra
Author-Name: Konstantinos Nikolopoulos
Author-X-Name-First: Konstantinos
Author-X-Name-Last: Nikolopoulos
Author-Name: Sushil Punia
Author-X-Name-First: Sushil
Author-X-Name-Last: Punia
Title: Intermittent demand, inventory obsolescence, and temporal aggregation forecasts
Abstract: 
 Forecasting for intermittent demand is considered a difficult task and becomes even more challenging in the presence of obsolescence. Traditionally the problem has been dealt with modifications in the conventional parametric methods such as Croston. However, these methods are generally applied at the observed frequency, ignoring any additional information, such as trend that becomes prominent at higher levels of aggregation. We evaluate established Temporal Aggregation (TA) methods: ADIDA, Forecast Combination, and Temporal Hierarchies in the said context. We further employ restricted least-squares estimation and propose two new combination approaches tailored to decreasing demand scenarios. Finally, we test our propositions on both simulated and real datasets. Our empirical findings support the use of variable forecast combination weights to improve TA’s performance in intermittent demand items with a risk of obsolescence.
Journal: International Journal of Production Research
Pages: 1663-1685
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2199435
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2199435
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# input file: TPRS_A_2201637_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Thibaut Cerabona
Author-X-Name-First: Thibaut
Author-X-Name-Last: Cerabona
Author-Name: Frederick Benaben
Author-X-Name-First: Frederick
Author-X-Name-Last: Benaben
Author-Name: Benoit Montreuil
Author-X-Name-First: Benoit
Author-X-Name-Last: Montreuil
Author-Name: Matthieu Lauras
Author-X-Name-First: Matthieu
Author-X-Name-Last: Lauras
Author-Name: Louis Faugère
Author-X-Name-First: Louis
Author-X-Name-Last: Faugère
Author-Name: Miguel R. Campos
Author-X-Name-First: Miguel R.
Author-X-Name-Last: Campos
Author-Name: Julien Jeany
Author-X-Name-First: Julien
Author-X-Name-Last: Jeany
Title: The physics of decision approach: a physics-based vision to manage supply chain resilience
Abstract: 
 As instability becomes the norm, supply chain management is becoming increasingly complex and critical. As a result, supply chain managers must adapt to complex situations. Managing instability is a key expectation for these managers. One way to help them to manage this instability is to study resilience. Resilience is related to in the literature as the ability of a system to resist, adapt and recover from disruptions. Measuring and controlling supply chain resilience has therefore become a key issue for managers, especially in a context of instability. In 2013, the World Economic Forum [2013. Global Risks 2013. Davos, Switzerland: World Economic Forum] highlighted in its study, this priority for the surveyed companies to master this concept of resilience. To address this need, this paper presents an innovative approach to disruption and resilience management based on physics principles. It considers disruptions as forces that impact supply chain performance. These forces are created as a result of changes in the internal or external attributes of the supply chain. In this approach, supply chain performance is represented and visualised as a physical trajectory modelled in the framework of its performance indicators. Thus, disturbances are considered as forces that displace and deviate the supply chain's performance trajectory in its performance framework.
Journal: International Journal of Production Research
Pages: 1783-1802
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2201637
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2201637
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# input file: TPRS_A_2127960_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Marco Ardolino
Author-X-Name-First: Marco
Author-X-Name-Last: Ardolino
Author-Name: Andrea Bacchetti
Author-X-Name-First: Andrea
Author-X-Name-Last: Bacchetti
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Author-Name: Guglielmo Franchini
Author-X-Name-First: Guglielmo
Author-X-Name-Last: Franchini
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Author-Name: Anand Nair
Author-X-Name-First: Anand
Author-X-Name-Last: Nair
Title: The impacts of digital technologies on coping with the COVID-19 pandemic in the manufacturing industry: a systematic literature review
Abstract: 
 The COVID-19 pandemic’s impacts have been devastating for the global economy, and particularly for manufacturing companies. Many firms were unprepared for a crisis of this magnitude and adapted their operations in an ad-hoc manner. Some of these adaptations were facilitated by digital technologies (DTs). This article examines extant literature using a systematic review methodology in order to extend our understanding of what DTs have been used in manufacturing companies during the pandemic, how DTs have helped manufacturing companies cope with the pandemic, and how these innovations can be used in the post-pandemic world. The major outcome of our study is a novel classification of DT applications in the pandemic setting in the manufacturing industry. In addition, we propose an agenda for future research.
Journal: International Journal of Production Research
Pages: 1953-1976
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2022.2127960
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2127960
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# input file: TPRS_A_2245272_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: The Editors
Title: Correction
Journal: International Journal of Production Research
Pages: (I)-(I)
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2245272
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2245272
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# input file: TPRS_A_2197513_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Peirui Qiao
Author-X-Name-First: Peirui
Author-X-Name-Last: Qiao
Author-Name: Ming Luo
Author-X-Name-First: Ming
Author-X-Name-Last: Luo
Author-Name: Yizhong Ma
Author-X-Name-First: Yizhong
Author-X-Name-Last: Ma
Author-Name: Abdul Jabbar
Author-X-Name-First: Abdul
Author-X-Name-Last: Jabbar
Title: Optimal warranty option and post-warranty maintenance strategy under a warranty menu: from a consumer perspective
Abstract: 
 As manufacturers continue to provide new and unique products and services for their customers, we argue that warranty menus with differentiated options are an often-overlooked unique selling point. Meanwhile, there is a huge swathe of customers who own durable products which are still in use even after the expiration of a warranty. It is in this area that we develop a research perspective which urges customers to consider warranty plans and post-warranty maintenance strategies simultaneously when making a purchasing decision. In this paper, through the lens of a consumer, we propose an integrated model of warranty and post-warranty maintenance under a ﬂexible renewable warranty. This model takes into account repair limits and multiple failure types with time-varying probabilities. As part of this, a new post-warranty maintenance strategy is designed, in which the repair time-based corrective replacement and the age-based preventive replacement are combined. The life cycle cost rate of the product is minimised by a synthetic decision-making about the consumer’s warranty purchase and post-warranty maintenance strategy. Numerical studies show that there exists a joint optimal solution, which can help the customer to develop an optimal overall warranty-maintenance strategy under the warranty menu with minimised cost rate.Highlights
An integrated model of warranty and post-warranty maintenance is developed.The warranty product has minor and catastrophic failures with time-varying probabilities.A ﬂexible renewable warranty is considered for the consumer.A post-warranty maintenance strategy with the repair time limit is proposed.The optimal warranty-maintenance strategy is derived to minimise the Life cycle cost rate.
Journal: International Journal of Production Research
Pages: 1586-1608
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2197513
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2197513
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# input file: TPRS_A_2202280_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Chun Su
Author-X-Name-First: Chun
Author-X-Name-Last: Su
Author-Name: Lin Wu
Author-X-Name-First: Lin
Author-X-Name-Last: Wu
Title: Opportunistic maintenance optimisation for offshore wind farm with considering random wind speed
Abstract: 
 A joint maintenance decision-making framework is proposed to optimise the long-term maintenance plan and lower the maintenance cost for offshore wind farms. The historical wind speed data are screened by using the method of k-means clustering, and Markov chains are established for the wind speed in different seasons. On this basis, the approach of Markov chain Monte Carlo is applied to simulate the distribution of repair vessel's waiting time for maintenance, where the impact of wind speed on maintenance availability is considered. Moreover, the components in wind turbines are divided into four states according to their effective ages, i.e. young, mature, old and failed, respectively. A maintenance decision model is established, with the objective to minimise maintenance cost. Besides, three types of opportunistic maintenance are considered, i.e. failure-based opportunistic maintenance (FBOM), event-based opportunistic maintenance (EBOM) and age-based opportunistic maintenance (ABOM), respectively. The enhanced elitist genetic algorithm (SEGA) is adopted to solve the optimisation problem. The results indicate that among the three types of opportunistic maintenance, ABOM can reduce maintenance cost more effectively, and it is more suitable for long-term maintenance plans of offshore wind farm.
Journal: International Journal of Production Research
Pages: 1862-1878
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2202280
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2202280
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# input file: TPRS_A_2199101_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Banu Yetkin Ekren
Author-X-Name-First: Banu
Author-X-Name-Last: Yetkin Ekren
Author-Name: Tone Lerher
Author-X-Name-First: Tone
Author-X-Name-Last: Lerher
Author-Name: Melis Küçükyaşar
Author-X-Name-First: Melis
Author-X-Name-Last: Küçükyaşar
Author-Name: Boris Jerman
Author-X-Name-First: Boris
Author-X-Name-Last: Jerman
Title: Cost and performance comparison of tier-captive SBS/RS with a novel AVS/RS/ML
Abstract: 
 This paper introduces a novel autonomous vehicle-based storage and retrieval system that utilizes movable lifts (AVS/RS/ML), proposed as an alternative to the tier-captive shuttle-based storage and retrieval system (SBS/RS). The newly proposed system aims to provide an affordable solution with highly utilised AGVs, that can also perform operations out of warehouse. The performance of this novel system is compared with the equivalent tier-captive SBS/RS warehouse design, where each shuttle is dedicated in a specific tier in that design. The comparison is based on the initial system investments costs, throughput rates, and average utilisation of lifts/MLs in the system. Collision prevention rules are also applied to AVS/RS/ML, and its performance is tested through simulation. The results show that the tier-captive SBS/SR system becomes cost-efficient under high throughput rate requirements, while the AVS/RS/ML technology is preferred for relatively moderate and low process rate requirements. The unit-cost per month performance metric of AVS/RS/ML is less sensitive to an increase in number of tiers in the system, compared to the tier-captive SBS/RS case, indicating that AVS/RS/ML may be promising for high-tier warehouse system designs.
Journal: International Journal of Production Research
Pages: 1648-1662
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2199101
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2199101
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# input file: TPRS_A_2198614_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Azin Setayesh
Author-X-Name-First: Azin
Author-X-Name-Last: Setayesh
Author-Name: Eric H. Grosse
Author-X-Name-First: Eric H.
Author-X-Name-Last: Grosse
Author-Name: Michael A. Greig
Author-X-Name-First: Michael A.
Author-X-Name-Last: Greig
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Author-Name: W. Patrick Neumann
Author-X-Name-First: W. Patrick
Author-X-Name-Last: Neumann
Title: Evaluating usability, functionality, and usefulness of the warehousing error prevention tool
Abstract: 
 This paper presents an evaluation of the usability, functionality, and usefulness of the Warehouse Error Prevention (WEP) tool that consists of seven modules. The WEP tool is framed in a simple yes/no form, which can be used to identify human factors related to sources of pick errors in a warehouse. Thirty-three participants in 27 organisations from three different countries participated in a trial application and evaluation of the tool. The evaluation included a survey study and semi-structured interviews. Survey results show that participants agreed on the usability and functionality of the WEP tool. In the interviews, participants generally reported the WEP tool as being both accurate and functional with the potential to support engineers, ergonomists, and warehouse managers to improve order picking quality. Further quantitative field testing of the WEP tool’s potential to identify costly warehouse errors is needed.
Journal: International Journal of Production Research
Pages: 1633-1647
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2198614
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2198614
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# input file: TPRS_A_2199436_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yunzhi Chen
Author-X-Name-First: Yunzhi
Author-X-Name-Last: Chen
Author-Name: Blake W. Billings
Author-X-Name-First: Blake W.
Author-X-Name-Last: Billings
Author-Name: Kody M. Powell
Author-X-Name-First: Kody M.
Author-X-Name-Last: Powell
Title: Industrial processes and the smart grid: overcoming the variability of renewables by using built-in process storage and intelligent control strategies
Abstract: 
 Manufacturers are facing pressure to reduce electricity costs. Onsite renewable energy generation may be a solution, but its high capital cost and intermittent power generation limit its use. Grid-responsive smart manufacturing could effectively incorporate renewables in industrial processes. This study integrates grid-responsive smart manufacturing with renewables on an industrial plant scale and demonstrates both a favourable economic and environmental outcome. A user-friendly decision-aid model for energy management is provided to manufacturers. A case study shows how solar panels, industrial batteries, smart pumping strategies, and various combinations of those elements can save on electricity costs. Dynamic simulation results demonstrate that grid-responsive smart manufacturing can effectively lower peak demand. The economic results show that grid-responsive smart manufacturing and renewables synergistically optimise cost reductions. The solar coupled with smart pumping scenario shows annual cost savings of $755,200, accounting for 4.6% of the total electricity cost. Smart pumping alone saves $371,900 annually with a 0.7-year payback period, demonstrating how the manufacturing sector can utilise its own processes in load shifting. This study supports that incorporating grid-responsive smart manufacturing with renewables can effectively reduce electricity costs and emissions for industry.Abbreviations: e: Equivalent; GHG: Greenhouse gas; PBP: Payback period; PV: Photovoltaics; SP: Setpoint; VFD: Variable speed drives
Journal: International Journal of Production Research
Pages: 1686-1698
Issue: 5
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2199436
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2199436
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# input file: TPRS_A_2217282_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yifan Xie
Author-X-Name-First: Yifan
Author-X-Name-Last: Xie
Author-Name: Tianhui Wang
Author-X-Name-First: Tianhui
Author-X-Name-Last: Wang
Author-Name: Young-Seon Jeong
Author-X-Name-First: Young-Seon
Author-X-Name-Last: Jeong
Author-Name: Ali Tosyali
Author-X-Name-First: Ali
Author-X-Name-Last: Tosyali
Author-Name: Myong K. Jeong
Author-X-Name-First: Myong K.
Author-X-Name-Last: Jeong
Title: True sparse PCA for reducing the number of essential sensors in virtual metrology
Abstract: 
 In the semiconductor industry, virtual metrology (VM) is a cost-effective and efficient technique for monitoring the processes from one wafer to another. This technique is implemented by generating a predictive model that uses real-time data from equipment sensors in conjunction with measured wafer quality characteristics. Before establishing a prediction model for the VM system, appropriate selection of relevant input variables should be performed to maintain the efficiency of subsequent analyses considering the large dimensionality of the sensor data inputs. However, wafer production processes usually employ multiple sensors, which leads to cost escalations. Herein, we propose a variant of the sparse principal component analysis (PCA) called true sparse PCA (TSPCA). The proposed method uses a small number of input variables in the first few principal components. The main contribution of the proposed TSPCA is reducing the number of essential sensors. Our experimental results demonstrate that compared to the existing sparse PCA methods, the proposed approach can reduce the number of sensors required while explaining an approximately equivalent amount of variance.
Journal: International Journal of Production Research
Pages: 2142-2157
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217282
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217282
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# input file: TPRS_A_2204967_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yenny Alexandra Paredes-Astudillo
Author-X-Name-First: Yenny Alexandra
Author-X-Name-Last: Paredes-Astudillo
Author-Name: Valérie Botta-Genoulaz
Author-X-Name-First: Valérie
Author-X-Name-Last: Botta-Genoulaz
Author-Name: Jairo R. Montoya-Torres
Author-X-Name-First: Jairo R.
Author-X-Name-Last: Montoya-Torres
Title: Impact of learning effect modelling in flowshop scheduling with makespan minimisation based on the Nawaz-Enscore-Ham algorithm
Abstract: 
 Inspired by real-life applications, mainly in hand-intensive manufacturing, the incorporation of learning effects into scheduling problems has garnered attention in recent years. This paper deals with the flowshop scheduling problem with a learning effect, when minimising the makespan. Four approaches to model the learning effect, well-known in the literature, are considered. Mathematical models are providing for each case. A solver allows us to find the optimal solution in small problem instances, while a Simulated Annealing algorithm is proposed to deal with large problem instances. In the latter, the initial solution is obtained using the well-known Nawaz-Enscore-Ham algorithm, and two local search operators are evaluated. Computational experiments are carried out using benchmark datasets from the literature. The Simulated Annealing algorithm shows a better result for learning approaches with fast learning effects as compared to slow learning effects. Finally, for industrial decision makers, some insights about how the learning effect model might affect the makespan minimisation flowshop scheduling problem are presented.
Journal: International Journal of Production Research
Pages: 1999-2014
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2204967
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2204967
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# input file: TPRS_A_2217288_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Tianzhu Ye
Author-X-Name-First: Tianzhu
Author-X-Name-Last: Ye
Author-Name: Liping Zhou
Author-X-Name-First: Liping
Author-X-Name-Last: Zhou
Author-Name: Shan Jiang
Author-X-Name-First: Shan
Author-X-Name-Last: Jiang
Author-Name: Zhibin Jiang
Author-X-Name-First: Zhibin
Author-X-Name-Last: Jiang
Title: Business model selection for durable products based on price optimisation with a two-dimensional description of customers’ usage patterns
Abstract: 
 Business models play a key role in companies’ profit growth and competitiveness. A growing number of companies not only sell products but also provide leasing services. In traditional leasing models, companies usually charge customers for the time they occupy the product, but ignore differences in how long and how often customers actually use the product. In practice, customers have different product usage patterns, which will affect their purchase choice. Considering the pooling effect in the leasing service network, this paper describes customers’ usage patterns in two dimensions (product occupancy time and utilisation rate) and determines the optimal pricing under three models (selling, leasing, and their hybrid model) to maximise corporate profits. Through comparative analysis, the optimal business model selection decision is obtained, and its market performance is also analysed. The results show that when the leasing service operational capability is strong, the pure leasing service model is superior; otherwise, the result also depends on the product value creation capability. When this capability is high, the hybrid model will be selected; otherwise, the pure selling model will be better. This result differs from the generally held result in previous studies that the hybrid model is more profitable in most cases.
Journal: International Journal of Production Research
Pages: 2176-2201
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217288
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217288
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# input file: TPRS_A_2217277_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Gur Mosheiov
Author-X-Name-First: Gur
Author-X-Name-Last: Mosheiov
Author-Name: Assaf Sarig
Author-X-Name-First: Assaf
Author-X-Name-Last: Sarig
Title: A common due-date assignment problem with job rejection on parallel uniform machines
Abstract: 
 We study a common due-date assignment problem on two parallel uniform machines. The jobs are assumed to have identical processing times, and job-dependent and asymmetric earliness and tardiness unit costs. The scheduler may process only a subset of the jobs, i.e. the option of job-rejection is allowed. The objective function consists of three cost components: the total earliness-tardiness cost of all scheduled jobs, the cost of the common due-date, and total rejection cost. For a given number of rejected jobs and a given due-date, the problem is reduced to a non-standard linear assignment problem. Consequently, the optimal solution is shown to be obtained in polynomial time in the number of jobs. The case of a given (possibly restrictive) due-date, the extension to a setting of more than two machines, and a number of special cases, are also discussed.
Journal: International Journal of Production Research
Pages: 2083-2092
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217277
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217277
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# input file: TPRS_A_2217279_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Lei Liu
Author-X-Name-First: Lei
Author-X-Name-Last: Liu
Author-Name: Marcello Urgo
Author-X-Name-First: Marcello
Author-X-Name-Last: Urgo
Title: A branch-and-bound approach to minimise the value-at-risk of the makespan in a stochastic two-machine flow shop
Abstract: 
 Planning and scheduling approaches in real manufacturing environments entail the need to cope with random attributes and variables to match the characteristics of real scheduling problems where uncertain events are frequent. Moreover, the capability of devising robust schedules, which are less sensitive to the disruptive effects of unexpected events, is a major request in real applications. In this paper, a branch-and-bound approach is proposed to solve the two-machine permutation flow shop scheduling problem with stochastic processing times. The objective is the minimisation of the value-at-risk of the makespan, to support decision-makers in the trade-off between the expected performance and the mitigation of the impact of extreme scenarios. A Markovian Activity Network (MAN) model is adopted to estimate the distribution of the makespan and assess the value-at-risk for both partial and complete schedules. Phase-type distributions are used to enable general distributions for processing times while maintaining the capability to exploit a Markovian approach. The effectiveness and performance of the proposed approach are demonstrated through a set of computational experiments.
Journal: International Journal of Production Research
Pages: 2107-2123
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217279
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217279
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# input file: TPRS_A_2217272_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Yumin He
Author-X-Name-First: Yumin
Author-X-Name-Last: He
Author-Name: Milton L. Smith
Author-X-Name-First: Milton L.
Author-X-Name-Last: Smith
Title: Investigation of scheduling integration of flexible manufacturing systems for mass customisation
Abstract: 
 In contemporary manufacturing and supply chain environments, there are various challenges that companies have to face. Many companies are facing challenges to respond quickly to customers’ requirements and to provide customised products cost effectively. Mass customisation (MC) can help companies to provide customised products and services quickly at a low price. Integrated decision-making can obtain performance improvement in many situations. This paper investigates the problem of scheduling integration of flexible manufacturing systems (FMSs) for mass customisation. A mathematical model is formulated for the problem. A set-based dynamic algorithm is developed. Numerical studies are made on the proposed algorithm by simulation and by statistical analysis. Conclusions, managerial implications, and future research suggestions are provided.
Journal: International Journal of Production Research
Pages: 2060-2082
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217272
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217272
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# input file: TPRS_A_2250204_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: The Editors
Title: Correction
Journal: International Journal of Production Research
Pages: 2305-2305
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2250204
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# input file: TPRS_A_2217289_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Liangyan Tao
Author-X-Name-First: Liangyan
Author-X-Name-Last: Tao
Author-Name: Ailin Liang
Author-X-Name-First: Ailin
Author-X-Name-Last: Liang
Author-Name: Maxim A. Bushuev
Author-X-Name-First: Maxim A.
Author-X-Name-Last: Bushuev
Title: Supply chain delivery performance improvement: a white-box perspective
Abstract: 
 This paper proposes a white-box perspective that portrays a supply chain delivery process as a network of related activities which remains to be improved. It addresses a critical disadvantage of supply chain delivery performance models, namely considering a delivery process as a whole and ignoring characteristics and relationships between activities in the delivery process. A delivery process is modeled using the Graphical Evaluation and Review Technique based on the characteristic function (CF-GERT). Based on the CF-GERT model, a framework for applying managerial effort to activities to improve overall delivery performance is proposed. Then, particle swarm optimization (PSO) based on the penalty function is used to solve the delivery performance improvement framework. Finally, a numerical case shows how applying efforts to activities can effectively improve delivery performance and demonstrates the influence of several parameters on the related costs.
Journal: International Journal of Production Research
Pages: 2202-2219
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217289
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217289
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# input file: TPRS_A_2205969_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Christopher Münch
Author-X-Name-First: Christopher
Author-X-Name-Last: Münch
Author-Name: Manuel Wehrle
Author-X-Name-First: Manuel
Author-X-Name-Last: Wehrle
Author-Name: Tobias Kuhn
Author-X-Name-First: Tobias
Author-X-Name-Last: Kuhn
Author-Name: Evi Hartmann
Author-X-Name-First: Evi
Author-X-Name-Last: Hartmann
Title: The research landscape around the physical internet – a bibliometric analysis
Abstract: 
 The concept of the Physical Internet (PI) has been introduced as a vision for globally efficient and sustainable logistics. Examining the activities of the PI since its foundation, enormous efforts can be recognised in the political and business spheres. Furthermore, the topic has received considerable attention from logistics and supply chain management scientists. In this context, a wide variety of dimensions of the PI concept has been investigated. In contrast to some existing qualitative literature reviews, this study focuses on a quantitative review methodology to provide a holistic overview of the PI concept and its underlying dimensions and interrelations. Based on bibliometric performance analysis and science mapping, this research maps and connects the extant PI literature landscape. In doing so, the most important journals, researchers, and institutions in the PI field are identified. Furthermore, eight research topics are grouped thematically, including PI benefits and the challenge of its operationalisation, carriers and shippers in the PI network, PI foundations, smart product-service systems and services, hyperconnected city logistics, information and communication technology requirements, modular PI containers, and organisation and control of PI hubs. Based on the clustering of existing research, the study concludes by providing directions for future research.
Journal: International Journal of Production Research
Pages: 2015-2033
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2205969
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2205969
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# input file: TPRS_A_2217280_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Bingxin Miao
Author-X-Name-First: Bingxin
Author-X-Name-Last: Miao
Author-Name: Qianwang Deng
Author-X-Name-First: Qianwang
Author-X-Name-Last: Deng
Author-Name: Like Zhang
Author-X-Name-First: Like
Author-X-Name-Last: Zhang
Author-Name: Zhangwen Huo
Author-X-Name-First: Zhangwen
Author-X-Name-Last: Huo
Author-Name: Weifeng Han
Author-X-Name-First: Weifeng
Author-X-Name-Last: Han
Title: Joint scheduling of spare parts production and service engineers based on progressive Pareto algorithm
Abstract: 
 We analyse the joint scheduling of spare parts production and service engineers in a multi-site maintenance system. In the system, for each failure, a service engineer with the required spare part needs to be allocated for on-site maintenance. If one of the required resources is not readily available, the maintenance task can be satisfied via an external channel with quick responsiveness but high involved costs. Service providers need to make an efficient plan, including production scheduling of spare parts, allocation of service engineers and outsourcing strategy. First, a mathematical model with the objectives of minimum total outsourcing costs and minimum weighted tardiness is formulated. Then, a novel and knowledge-based heuristic algorithm is developed, namely progressive Pareto algorithm based on step-size (PPAS). To verify the performance of PPAS, it is compared against other well-known algorithms, including NSGA-II, MOEA/D, NNIA, RIPG, MMOIG and MNNIA. Finally, the effectiveness of the joint scheduling mode is demonstrated by comparing it with the separate optimisation mode of spare parts production and workforce allocation.Highlights
Analyse the joint scheduling of spare parts production and service engineersConstruct a bi-objective optimisation modelDevelop a progressive Pareto algorithm based on step-sizeVerify the superiority of the proposed algorithm and joint scheduling mode
Journal: International Journal of Production Research
Pages: 2124-2141
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217280
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# input file: TPRS_A_2217296_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Rebeca Arista
Author-X-Name-First: Rebeca
Author-X-Name-Last: Arista
Author-Name: Fernando Mas
Author-X-Name-First: Fernando
Author-X-Name-Last: Mas
Author-Name: Domingo Morales-Palma
Author-X-Name-First: Domingo
Author-X-Name-Last: Morales-Palma
Author-Name: Carpoforo Vallellano
Author-X-Name-First: Carpoforo
Author-X-Name-Last: Vallellano
Title: An Ontology-based Engineering methodology applied to aerospace Reconfigurable Manufacturing Systems design
Abstract: 
 Reconfigurable Manufacturing Systems (RMS) have gained attention in the aerospace industry in the past years, as post-pandemic context shows drastic production capacity changes and new environmental regulations to which it must adapt quicker than before to maintain competitiveness. Nevertheless, current RMS design methods have not thoroughly considered this industry specificities, nor industrial resources requirements in the current concurrent design practice. These limitations have been identified in several recent research works. Ontology-based Engineering (OBE) systems can stand overly complex collaborative design processes involving multidisciplinary stakeholders and various digital tools, integrating different levels of decision. Models for Manufacturing (MfM) is an OBE methodology aiming to enable industrial design and decision-making in manufacturing by preserving the company knowledge in ontology models, usable as knowledge base to generate and integrate the aircraft and manufacturing systems design. This paper presents an MfM application for RMS design in aerospace, introducing innovative design concepts that allow implementing RMS in a collaborative engineering process of an aerospace product. An implementation is shown designing the RMS of a model aircraft family to illustrate the concepts introduced and considerations are given to transfer this knowledge base into an OBE system to support complex real-life applications.
Journal: International Journal of Production Research
Pages: 2286-2304
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217296
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217296
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# input file: TPRS_A_2217293_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Vincent Ciancio
Author-X-Name-First: Vincent
Author-X-Name-Last: Ciancio
Author-Name: Lazhar Homri
Author-X-Name-First: Lazhar
Author-X-Name-Last: Homri
Author-Name: Jean-Yves Dantan
Author-X-Name-First: Jean-Yves
Author-X-Name-Last: Dantan
Author-Name: Ali Siadat
Author-X-Name-First: Ali
Author-X-Name-Last: Siadat
Title: Development of a flexible data management system, to implement predictive maintenance in the Industry 4.0 context
Abstract: 
 In recent years, the way that maintenance is carried out has evolved due to the incorporation of digital tools and Industry 4.0 concepts. By connecting to and communicating with their production system, companies can now gather information about the current and future health of the equipment, enabling more efficient control through a process called predictive maintenance (PdM). The goal of PdM is to reduce unplanned downtimes and proactively address maintenance needs before failures occur. However, it can be challenging for industrial practitioners to implement an intelligent maintenance system that effectively manages data. This paper presents a methodology for developing and implementing a PdM system in the automotive industry, using open standards and scalable data management capabilities. The platform is validated through the presentation of two industry use cases.
Journal: International Journal of Production Research
Pages: 2255-2271
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217293
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# input file: TPRS_A_2204958_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Caio Paziani Tomazella
Author-X-Name-First: Caio Paziani
Author-X-Name-Last: Tomazella
Author-Name: Maristela Oliveira Santos
Author-X-Name-First: Maristela Oliveira
Author-X-Name-Last: Santos
Author-Name: Douglas Alem
Author-X-Name-First: Douglas
Author-X-Name-Last: Alem
Author-Name: Raf Jans
Author-X-Name-First: Raf
Author-X-Name-Last: Jans
Title: Service-level-driven procurement and production lot-sizing problem with demand fulfilment
Abstract: 
 This paper presents novel models for the Integrated Procurement and Lot-Sizing Problem with multiple customers and backlogging. Since allowing backlog in a traditional cost minimisation model involves dealing with intangible costs of not fulfilling the demand on time, we propose optimising service-levels while keeping the costs minimal using a budget constraint. The motivation of this study emanates from a manufacturing company that assembles commercial and industrial refrigeration equipment, using both purchased materials and in-house products. Instead of considering an aggregate demand, we consider the specific demand from various customers. This allows us to incorporate demand fulfilment decisions into the model in case of stock-outs by deciding which customers will have their orders backlogged. The fill-rate, or β service-level, is considered both globally and for customers and products individually. Computational experiments show that the service-level-driven models improve service when compared to the traditional cost model and also end up enforcing service equity among different customers at the expense of a deterioration in the global fill-rate.
Journal: International Journal of Production Research
Pages: 1977-1998
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2204958
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2204958
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# input file: TPRS_A_2217292_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Kangqian Zheng
Author-X-Name-First: Kangqian
Author-X-Name-Last: Zheng
Author-Name: Kai Ding
Author-X-Name-First: Kai
Author-X-Name-Last: Ding
Author-Name: Jizhuang Hui
Author-X-Name-First: Jizhuang
Author-X-Name-Last: Hui
Author-Name: Fuqiang Zhang
Author-X-Name-First: Fuqiang
Author-X-Name-Last: Zhang
Author-Name: Jingxiang Lv
Author-X-Name-First: Jingxiang
Author-X-Name-Last: Lv
Author-Name: Felix T.S. Chan
Author-X-Name-First: Felix T.S.
Author-X-Name-Last: Chan
Title: Blockchain-based credible manufacturing data sharing for a collaborative manufacturing supply chain
Abstract: 
 Core enterprises are entering into close collaborations with multi-level manufacturing service providers to create and share value. However, credible data sharing in collaborative manufacturing supply chains is rare, which can lead to uncontrollable production distortions and delayed operational adjustments. Driven by blockchain technology, this study proposes a systematic framework for credible manufacturing data sharing for a cross-enterprise collaborative manufacturing supply chain (CMSC). To develop the needed method, a blockchain network system with blockchain nodes, distributed ledger, and Raft-based distributed node ordering service system was first modelled. Then, two automatic data upload algorithms were studied to ensure the reliability of off-chain manufacturing data sources from core enterprises, suppliers, and customers. Then, two types of smart contracts were designed to ensure the standardisation and co-validation of manufacturing data storage and query processes in the blockchain network. A demonstrative case was studied to validate the proposed blockchain-based credible manufacturing data sharing method. The results show that our work is effective for credible data sharing in CMSC, which makes it easier for core enterprises to better operate the CMSC and further stimulate enterprises to create a credible social community.
Journal: International Journal of Production Research
Pages: 2233-2254
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217292
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217292
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# input file: TPRS_A_2217286_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Stephanie Beyer Díaz
Author-X-Name-First: Stephanie
Author-X-Name-Last: Beyer Díaz
Author-Name: Kristof Coussement
Author-X-Name-First: Kristof
Author-X-Name-Last: Coussement
Author-Name: Arno De Caigny
Author-X-Name-First: Arno
Author-X-Name-Last: De Caigny
Author-Name: Luis Fernando Pérez
Author-X-Name-First: Luis Fernando
Author-X-Name-Last: Pérez
Author-Name: Stefan Creemers
Author-X-Name-First: Stefan
Author-X-Name-Last: Creemers
Title: Do the US president's tweets better predict oil prices? An empirical examination using long short-term memory networks
Abstract: 
 The price of oil is highly complex to predict as it is impacted by global demand and supply, geopolitical events, and market sentiment. The accuracy of such predictions, however, has far-reaching implications for supply chain performance, portfolio management, and expected stock market returns. This paper contributes to the oil price prediction literature by evaluating the predictive impact of the US President's communication on Twitter, while benchmarking various Natural Language Processing (NLP) techniques, including Term Frequency-Inverse Document Frequency (TF-IDF), Word2Vec, Doc2Vec, Global Vectors for Word Representation (GloVe), and Bidirectional Encoder Representations from Transformers (BERT). These techniques are combined with a deep neural network Long Short-Term Memory (LSTM) architecture using a five-day lag for both the oil price and the textual Twitter data. The data was collected during the term of US President Donald Trump, resulting in 1449 days of crude oil price prediction and a total of 16,457 tweets. The study is validated for Brent and West Texas Intermediate blends, using the daily price of a barrel of crude oil as the target variable. The results confirm that including the US President's tweets significantly increases the predictive power of oil price prediction models, and that an LSTM architecture with BERT as NLP technique has the best performance.
Journal: International Journal of Production Research
Pages: 2158-2175
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217286
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217286
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# input file: TPRS_A_2217278_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Barbara Tropschuh
Author-X-Name-First: Barbara
Author-X-Name-Last: Tropschuh
Author-Name: Julien Cegarra
Author-X-Name-First: Julien
Author-X-Name-Last: Cegarra
Author-Name: Olga Battaïa
Author-X-Name-First: Olga
Author-X-Name-Last: Battaïa
Title: Integrating physiological and mental aspects in employee scheduling: an overview for practitioners in production management
Abstract: 
 Production companies are facing increasing production complexity and demographic change. Therefore, with its decreasing physiological and mental performance prerequisites, the aging workforce is often confronted with overload at the workplace leading to fatigue and work errors in the short term and increasing sick days in the long term. Integrating physiological and mental aspects into existing employee scheduling is one way to maintain employees’ health and performance. Incorporating these aspects is often very complex due to the need for multiple disciplines and the lack of supporting methods and tools. Therefore, this paper provides a practical-oriented overview for including physiological and mental aspects in existing employee scheduling. The intercorrelation between workload, individual performance prerequisites and strain, their measurement methods, and standardised alternatives are explained to support industrial practitioners in production management, like planners. A four-step method for integrating physiological and mental aspects in employee scheduling is presented. With the help of this method, the interaction between the ergonomics/human factors departments and production management can be improved, resulting in a more human-oriented employee scheduling. A practical example from manual assembly illustrates the application of the presented approach.
Journal: International Journal of Production Research
Pages: 2093-2106
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217278
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# input file: TPRS_A_2206923_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Lu Xu
Author-X-Name-First: Lu
Author-X-Name-Last: Xu
Author-Name: Yanhui Li
Author-X-Name-First: Yanhui
Author-X-Name-Last: Li
Author-Name: Yanwei Lin
Author-X-Name-First: Yanwei
Author-X-Name-Last: Lin
Author-Name: Chaofeng Tang
Author-X-Name-First: Chaofeng
Author-X-Name-Last: Tang
Author-Name: Qi Yao
Author-X-Name-First: Qi
Author-X-Name-Last: Yao
Title: Supply chain cybersecurity investments with interdependent risks under different information exchange modes
Abstract: 
 Cybersecurity presents non-negligible challenges for firm collaboration and supply chain viability, as information exchange among nodes introduces potential interdependent risks. How to make appropriate decisions on security investments and information exchange modes is a significant issue for supply chain members. Considering two information exchange modes: system interconnection and system independence, this study develops two game models to investigate the cybersecurity investments in a vertical supply chain composed of a retailer and n suppliers. Initial analysis shows that although firms learn investment decisions mutually in the face of a changing cybersecurity environment, suppliers always take a free ride on the efforts of retailer in two cases and the increased interdependent risks will damp nodes enthusiasm for security investments. Next, to compare the two cases, we introduce information exchange efficiency as the mediate parameter to link degree of system interconnection and proportion of information shared. We found that under the system independence mode, firms with high information-exchanging demand in the large-scale supply chain are more motivated to invest in cybersecurity. Furthermore, we extend our models to a centralised decision-making scenario. We find that security investment efficiency is greatly improved, and the free-riding behaviour of supplier is significantly reduced when systems are interconnected.
Journal: International Journal of Production Research
Pages: 2034-2059
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2206923
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2206923
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# input file: TPRS_A_2217291_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: Conceptualisation of a 7-element digital twin framework in supply chain and operations management
Abstract: 
 Digital twins became of greater interest to researchers and practitioners in supply chain and operations management (SCOM). Literature has addressed the need to understand digital twins in SCOM, mostly focusing on fragmented technological solutions and use cases. We start with an integrative literature review to determine which elements belong to research on digital twins in SCOM. We define the seven major elements of a digital twin in SCOM: technology, people, management, organisation, scope, task, and modelling. We also distinguish five major types of digital twins in SCOM: product, process, organisation, supply chain and network-of-networks. Illustration of a SCOM digital twin is provided using an anyLogistix example. We conclude that digital twins in SCOM are not merely a simulation-based replica of a real object but a complex socio-technical phenomenon involved in continuous human-artificial intelligence interactions. This leads to an understanding of the role of digital twins through the lens of Industry 5.0, reconfigurable and viable supply chains. Researchers and practitioners alike can use our framework to structure the knowledge on SCOM digital twins and consider all seven elements when designing and using digital twins.
Journal: International Journal of Production Research
Pages: 2220-2232
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217291
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217291
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# input file: TPRS_A_2217294_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20231214T103247 git hash: d7a2cb0857
Author-Name: Hajar Nouinou
Author-X-Name-First: Hajar
Author-X-Name-Last: Nouinou
Author-Name: Taha Arbaoui
Author-X-Name-First: Taha
Author-X-Name-Last: Arbaoui
Author-Name: Alice Yalaoui
Author-X-Name-First: Alice
Author-X-Name-Last: Yalaoui
Title: Minimising total weighted completion time for semi-online single machine scheduling with known arrivals and bounded processing times
Abstract: 
 This paper addresses the semi-online scheduling problem of minimising the total weighted completion time on a single machine, where a combination of information on jobs release dates and processing times is considered. In this study, jobs can only arrive at known future times and a lower bound on jobs processing times is known in advance. A new semi-online algorithm is presented and is shown to be the best possible for the considered problem. In order to make this statement, a new lower bound on the competitive ratio of any semi-online algorithm for the problem is developed and, using competitive analysis, the proposed semi-online algorithm is shown to have a competitive ratio that matches the lower bound.
Journal: International Journal of Production Research
Pages: 2272-2285
Issue: 6
Volume: 62
Year: 2024
Month: 03
X-DOI: 10.1080/00207543.2023.2217294
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217294
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# input file: TPRS_A_2247092_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yuhan Guo
Author-X-Name-First: Yuhan
Author-X-Name-Last: Guo
Author-Name: Wenhua Li
Author-X-Name-First: Wenhua
Author-X-Name-Last: Li
Author-Name: Linfan Xiao
Author-X-Name-First: Linfan
Author-X-Name-Last: Xiao
Author-Name: Hamid Allaoui
Author-X-Name-First: Hamid
Author-X-Name-Last: Allaoui
Title: A prediction-based iterative Kuhn-Munkres approach for service vehicle reallocation in ride-hailing
Abstract: 
 Online ride-hailing services provide additional transportation capability by recruiting private vehicles to meet people’s growing travel demand. To ensure the profitability of drivers and platforms, pick-up efficiency and frequency must be maintained at high levels. Therefore, consistency between the spatial distribution of drivers and that of travel demand becomes a key issue to address. This paper proposes a prediction-based iterative Kuhn-Munkres approach for service vehicle reallocation in the context of large-scale online ride-hailing. Firstly, preliminaries are formally defined and a novel mathematical model for the problem is proposed. Secondly, a deep spatio-temporal residual perception network is designed to accurately predict travel demand. Thirdly, an iterative Kuhn-Munkres approach combined with an improved A-Star algorithm is developed to reallocate service vehicles to spatial locations according to their distinct travel demand densities. Finally, extensive experiments are conducted to evaluate and verify the performance of the proposed approach.
Journal: International Journal of Production Research
Pages: 3690-3715
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2247092
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2247092
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# input file: TPRS_A_2241132_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Ruiwen Liao
Author-X-Name-First: Ruiwen
Author-X-Name-Last: Liao
Author-Name: Céline Gicquel
Author-X-Name-First: Céline
Author-X-Name-Last: Gicquel
Title: Integrated lot-sizing and energy supply planning with onsite generation of intermittent renewable energy
Abstract: 
 This work considers an industrial production site partially powered by a decentralised energy system based on intermittent renewable energy sources. Our objective is to simultaneous plan the industrial production and the energy supply in this site so as to minimise the total cost. A new way of modelling this combinatorial optimisation problem is proposed: it relies on the extension of a multi-product single-resource small-bucket lot-sizing model called the proportional lot-sizing and scheduling problem. This extension involves among others sequence-dependent changeover times overlapping multiple periods and energy-related constraints. Our numerical results show that the resulting mixed-integer linear programming model enables to obtain good-quality production and energy supply plans with a computational effort much smaller than the one required by a previously published large-bucket lot-sizing model.
Journal: International Journal of Production Research
Pages: 3483-3503
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2241132
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2241132
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# input file: TPRS_A_2245918_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: David Tremblet
Author-X-Name-First: David
Author-X-Name-Last: Tremblet
Author-Name: Simon Thevenin
Author-X-Name-First: Simon
Author-X-Name-Last: Thevenin
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Makespan estimation in a flexible job-shop scheduling environment using machine learning
Abstract: 
 A production plan gives the quantity of products to release on the shop floor in each period, where a period may represent a week or a month. The plan is the basis for negotiating order acceptance and delivery dates with customers and suppliers. The production plan must respect the available capacity on the shop floor, as underloading the shop floor leads to a loss of opportunity, and thus, a loss of competitiveness for the company. To properly manage the production capacity while negotiating with suppliers and customers, the production planners need a tool to accurately estimate the capacity consumption in each period. The computation of capacity consumption requires creating a detailed production schedule which is a complex task. Algorithms that find close to optimal schedules in a complex manufacturing environment are often time-consuming, which is impractical in a negotiation context. We investigate machine learning models to predict capacity consumption. We consider a flexible job-shop as commonly encountered in practice, and proposed several machine learning models. Namely, several variants of linear regression, decision trees, and artificial neural networks. Numerical experiments showed that our models outperform those found by both an exact approach and dispatching rules when computation time is short.
Journal: International Journal of Production Research
Pages: 3654-3670
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2245918
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2245918
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# input file: TPRS_A_2245487_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Shengbo Wang
Author-X-Name-First: Shengbo
Author-X-Name-Last: Wang
Author-Name: Yu Guo
Author-X-Name-First: Yu
Author-X-Name-Last: Guo
Author-Name: Shaohua Huang
Author-X-Name-First: Shaohua
Author-X-Name-Last: Huang
Author-Name: Daoyuan Liu
Author-X-Name-First: Daoyuan
Author-X-Name-Last: Liu
Author-Name: Pengzhou Tang
Author-X-Name-First: Pengzhou
Author-X-Name-Last: Tang
Author-Name: Litong Zhang
Author-X-Name-First: Litong
Author-X-Name-Last: Zhang
Title: A spatial-temporal feature fusion network for order remaining completion time prediction in discrete manufacturing workshop
Abstract: 
 The enterprises of the make-to-order production mode are required to make accurate judgments and reasonable decisions when dealing with the disturbance factors in the manufacturing process to ensure the timely completion of orders. Order remaining completion time (ORCT) prediction can quantify the production process and is an important basis to ensure the delivery date of orders. However, an accurate prediction model of the ORCT is challenging because of the spatial and temporal (ST) characteristics of the manufacturing process. An ST features-based prediction method is proposed to solve this problem. Firstly, the ST data sets are established on the basis of analysing ST characteristics of the manufacturing process. Secondly, the spatial feature extraction network and temporal feature extraction network are built to make a more comprehensive analysis. Finally, the prediction model of the ORCT is proposed by fusing the spatial and temporal features and validated in a practical workshop. Experimental results show that considering the spatial and temporal characteristics of the manufacturing process can significantly improve the prediction model’s performance, and the proposed prediction model is superior to graph convolutional neural network, gated recurrent unit network, deep auto-encoder, deep neural network, and back propagation neural network.
Journal: International Journal of Production Research
Pages: 3638-3653
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2245487
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2245487
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# input file: TPRS_A_2243623_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Haihua Zhu
Author-X-Name-First: Haihua
Author-X-Name-Last: Zhu
Author-Name: Jianjie Wang
Author-X-Name-First: Jianjie
Author-X-Name-Last: Wang
Author-Name: Changchun Liu
Author-X-Name-First: Changchun
Author-X-Name-Last: Liu
Author-Name: Wei Shi
Author-X-Name-First: Wei
Author-X-Name-Last: Shi
Author-Name: Qixiang Cai
Author-X-Name-First: Qixiang
Author-X-Name-Last: Cai
Title: An MBD-driven order remaining completion time prediction method based on SSA-BiLSTM in the IoT-enabled manufacturing workshop
Abstract: 
 The transformation of production mode leads to the need to strictly ensure the order in-time delivery. The global control ability of manufacturing workshops has become a necessary capability for enterprises. The real-time accurate Order Remaining Completion Time (ORCT) prediction allows managers to master the production schedule fluctuation, which provides criteria for workshop management. Due to the widespread deployment of Internet of Things (IoT) devices in the workshop, the difficulty of systematic processing and analysis of multi-dimensional heterogeneous data has been the main pain point of ORCT prediction. To tackle these problems, a Manufacturing Big Data (MBD)-driven ORCT prediction method based on Salp Swarm Algorithm (SSA) and Bidirectional Long Short-Term Memory (BiLSTM) is proposed. An attribute selection algorithm combined with max-relevance and min-redundancy and regularisation is used to mine key data from MBD. An SSA-BiLSTM model is proposed to achieve efficient and accurate ORCT prediction. The prediction model is supported by BiLSTM, and the hyperparameters are optimised by SSA. Finally, a case study about ORCT prediction in the IoT-enabled manufacturing workshop is presented. The result verifies that the proposed ORCT prediction method has obvious advantages over the other three traditional methods in accuracy and efficiency.
Journal: International Journal of Production Research
Pages: 3559-3584
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2243623
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2243623
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# input file: TPRS_A_2248279_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Rafael A. Campos
Author-X-Name-First: Rafael A.
Author-X-Name-Last: Campos
Author-Name: Aakil M. Caunhye
Author-X-Name-First: Aakil M.
Author-X-Name-Last: Caunhye
Author-Name: Douglas Alem
Author-X-Name-First: Douglas
Author-X-Name-Last: Alem
Author-Name: Pedro Munari
Author-X-Name-First: Pedro
Author-X-Name-Last: Munari
Title: Fragility-based lot-sizing in veterinary pharmaceutical plants under demand uncertainty
Abstract: 
 We study a production lot-sizing problem inspired by a veterinary pharmaceutical plant in which demands are uncertain. First, we develop a deterministic capacitated lot-sizing model for the production of animal pesticides, performed in three machine-specific stages. Second, we propose a traditional robust optimisation formulation following the popular budget-of-uncertainty approach. Third, we derive a novel fragility-based approach that circumvents well-known issues with traditional robust optimisation approaches, such as the estimation of budgets of uncertainty, the over-conservatism of robust solutions and the sensitivity of solutions to the decision maker's risk attitude. The fragility-based approach is grounded in the idea of minimising violations, over the full uncertainty support, from a user-specified cost target. It avoids the estimation of budgets of uncertainty and produces less conservative solutions via explicit modelling of constraint violation. We demonstrate the effectiveness of our approach on instances built upon real data provided by our industrial partner, a major player in the Brazilian veterinary pharmaceutical sector. The results show that our fragility-based approach reduces average total costs across all instances and maintains greater model stability under different target estimations. It also preserves cost savings when bottlenecks are introduced in production and when inventory costs and capacities are varied.
Journal: International Journal of Production Research
Pages: 3716-3752
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2248279
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2248279
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# input file: TPRS_A_2248523_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: R. Stefanini
Author-X-Name-First: R.
Author-X-Name-Last: Stefanini
Author-Name: G. Vignali
Author-X-Name-First: G.
Author-X-Name-Last: Vignali
Title: The influence of Industry 4.0 enabling technologies on social, economic and environmental sustainability of the food sector
Abstract: 
 In the context of great changes in the food industry, the aim of this research is to investigate if and how the implementation of 4.0 enabling technologies can enhance the economic, environmental and social sustainability of the food sector. A systematic literature review, using a combination of 12 keywords, was carried out on Scopus database with defined inclusion and exclusion criteria in order to answer four selected research questions. Overall, 50 relevant papers were retrieved and analysed by Mendeley and Excel with descriptive statistics. VOSviewer was used for co-occurrence and co-authorship analysis. Results illustrate that the interest in the topic has grown, in particular in Italy, and resume the benefits achievable by the implementation of 4.0 technologies in food industries. Social impacts are new job positions, ergonomic design of workplaces, changes in educational institutions, improved nutrition and better animal welfare. Positive aspects are related even to economic growth, improving food chain performances and decreasing companies’ costs. Finally, it allows energy, water, CO2 emissions and food savings. Overall, the work provides a helpful overview to food manufacturers and producers, recommending the introduction of I4.0 technologies to positively influence the sustainable development of the sector and remain competitive in the market.
Journal: International Journal of Production Research
Pages: 3800-3817
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2248523
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2248523
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# input file: TPRS_A_2239393_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Rodrigue Fokouop
Author-X-Name-First: Rodrigue
Author-X-Name-Last: Fokouop
Author-Name: Evren Sahin
Author-X-Name-First: Evren
Author-X-Name-Last: Sahin
Author-Name: Zied Jemai
Author-X-Name-First: Zied
Author-X-Name-Last: Jemai
Author-Name: Yves Dallery
Author-X-Name-First: Yves
Author-X-Name-Last: Dallery
Title: A heuristic approach for multi-echelon inventory optimisation in a closed-loop supply chain
Abstract: 
 This study deals with a closed-loop supply chain where inventory levels are controlled by an order-up-to inventory policy. The system under consideration is the cylinder-packaged gas supply chain of Air Liquide company, where empty cylinders used by customers are returned to be filled again by company plants. First, we examine the goodness of fit for demand distributions based on company real data. This enables us to better characterise demands pertaining to different classes of products. Then, we formulate the multi-echelon serial inventory model to be optimised and propose a heuristic to compute the target inventory levels that helps in achieving the desired customer service level while minimising the total inventory cost. The proposed heuristic is easy to implement in the field and gives results close those obtained using a simulation-optimisation approach that is more time-consuming. Finally, we perform a numerical analysis based on company real data and compare several methods that can be used to compute the target inventory levels by varying mainly two assumptions: parameters regarding demand distributions and metrics used to assess customer service levels.
Journal: International Journal of Production Research
Pages: 3435-3459
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2239393
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2239393
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# input file: TPRS_A_2243634_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Liyang Xiao
Author-X-Name-First: Liyang
Author-X-Name-Last: Xiao
Author-Name: Peng Sun
Author-X-Name-First: Peng
Author-X-Name-Last: Sun
Author-Name: Li Wang
Author-X-Name-First: Li
Author-X-Name-Last: Wang
Author-Name: Mengyu He
Author-X-Name-First: Mengyu
Author-X-Name-Last: He
Title: Multi-class pilot dispatching problem with stochastic pilotage duration
Abstract: 
 In most seaports, pilotage is compulsory for incoming and outgoing vessels to use pilotage services. Maritime pilots play a critical role in providing local knowledge and assistance to ensure the safety of vessels and seafarers. Typically, pilots are classified into multiple classes on the basis of their experiences and qualifications. Moreover, pilotage duration is usually stochastic due to various factors, including harsh weather conditions, visibility, and traffic changes. In this study, we address a multi-class pilot dispatching problem with stochastic pilotage duration. We formulate this problem as a stochastic programming model that considers the expected penalty cost for late arrival at each task's location. To solve this problem, we develop a branch-and-price algorithm that integrates column generation within the branch and bound framework. Additionally, we develop a novel labelling algorithm and several effective acceleration techniques to enhance the efficiency of the proposed algorithm. Extensive numerical experiments demonstrate the effectiveness of the proposed algorithm and show that it can handle realistic-sized instances while outperforming a metaheuristic search method.
Journal: International Journal of Production Research
Pages: 3585-3605
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2243634
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2243634
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# input file: TPRS_A_2248522_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Valentina Bonomi
Author-X-Name-First: Valentina
Author-X-Name-Last: Bonomi
Author-Name: Renata Mansini
Author-X-Name-First: Renata
Author-X-Name-Last: Mansini
Author-Name: Roberto Zanotti
Author-X-Name-First: Roberto
Author-X-Name-Last: Zanotti
Title: Mediating governance goals with patients and nurses satisfaction: a multi-actor multi-objective problem including fairness
Abstract: 
 Balancing conflicting goals among different stakeholders is a challenging problem in various application domains. In this paper, we analyse it in the context of home healthcare. Fairness objective functions for nurses and patients are combined with system-level governance goals of the territorial centers in charge of the assistance service. From the solution of several multi-objective problems including one objective for each actor hierarchically ordered, the best goal for each stakeholder is identified and interesting managerial conclusions are drawn. To efficiently solve large-size instances, we introduce a parallel Adaptive Large Neighborhood Search algorithm with destroy and repair operators customised to solve multi-objective multi-actor problems. The algorithm proves to be highly efficient and effective when compared to a commercial Mixed Integer Programming solver, either in its plain form or enforced by a mild start and a primal heuristic. Additionally, we devise a metaheuristic method to generate the Pareto frontier of an instance.
Journal: International Journal of Production Research
Pages: 3753-3780
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2248522
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2248522
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# input file: TPRS_A_2244604_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Ehsan Badakhshan
Author-X-Name-First: Ehsan
Author-X-Name-Last: Badakhshan
Author-Name: Peter Ball
Author-X-Name-First: Peter
Author-X-Name-Last: Ball
Title: Deploying hybrid modelling to support the development of a digital twin for supply chain master planning under disruptions
Abstract: 
 Supply chains operate in a highly distuptive environment where a SC master plan should be updated in line with disruptions to ensure that a high service level is provided to customers while total cost is minimised. There is an absence of knowledge of how a SC master plan should be updated to cope with disruptions using hybrid modelling. To fill this gap, we present a hybrid modelling framework to update a SC master plan in presence of disruptions. The proposed framework, which is a precursor to a SC digital twin, integrates simulation, machine learning, and optimisation to identify the production, storage, and distribution values that maximise SC service level while minimising total cost under disruptions. This approach proves effective in a SC disrupted by demand increase and lead time extension. Results show that employing hybrid modelling leads to a noticeable improvement in service level and total cost. The outcome of the new knowledge on using hybrid modelling for managing disruptions provides essential learning for the extension of modelling through a digital twin for SC master planning. We observe that in the presence of disruptions it is more economical to keep higher inventory at downstream SC members than the upstream SC members.
Journal: International Journal of Production Research
Pages: 3606-3637
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2244604
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2244604
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# input file: TPRS_A_2241563_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Liangxing Shi
Author-X-Name-First: Liangxing
Author-X-Name-Last: Shi
Author-Name: Xiaolei Lv
Author-X-Name-First: Xiaolei
Author-X-Name-Last: Lv
Author-Name: Yingdong He
Author-X-Name-First: Yingdong
Author-X-Name-Last: He
Author-Name: Zhen He
Author-X-Name-First: Zhen
Author-X-Name-Last: He
Title: Optimising production, maintenance, and quality control for imperfect manufacturing systems considering timely replenishment
Abstract: 
 To optimise production planning, maintenance strategies, and quality control in imperfect manufacturing systems, most existing works set the buffer stocking time at the cycle start time. However, excess inventory holding costs will be incurred if the buffer is stocked too early. This means that while the abovementioned setting can make the optimisation model simple, it might increase costs. Taking the uncertain practical buffer stocking time of an imperfect manufacturing system into account, this study aimed to find the production cycle, maintenance frequency, quality inspection cycle, and number of inspections that will minimise the expectation unit cost of the system. To this end, we developed a new model to optimise production, maintenance, and quality control considering timely replenishment. First, excess inventory holding and shortage costs were considered and the production process was divided into five scenarios based on the buffer stocking time and inspection time for assignable causes. Second, the link between production, maintenance, and quality was addressed by capturing the dynamic and random behaviour of production systems. An x-bar control chart was integrated into the model to monitor quality. A case study and sensitivity analysis were undertaken to verify the effectiveness and superiority of the proposed optimisation strategy.
Journal: International Journal of Production Research
Pages: 3504-3525
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2241563
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2241563
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# input file: TPRS_A_2242525_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Leonard Overbeck
Author-X-Name-First: Leonard
Author-X-Name-Last: Overbeck
Author-Name: Stephen C. Graves
Author-X-Name-First: Stephen C.
Author-X-Name-Last: Graves
Author-Name: Gisela Lanza
Author-X-Name-First: Gisela
Author-X-Name-Last: Lanza
Title: Development and analysis of digital twins of production systems
Abstract: 
 Production systems have to be adapted continuously to changing circumstances. This means that the responsible production planner has to frequently make decisions about reconfiguring complex systems under uncertainty whose outcome greatly affects the company’s business success. Discrete-event simulation is one powerful tool to support the necessary analysis and scenario evaluation, but still remains time-consuming and tricky to set up and to maintain. When implemented as a digital twin of the production system, the simulation model can maintain a high degree of accuracy over a long time period. An approach to realise this potential is presented and illustrated in this paper with a use case from the automotive industry. This paper contributes several new methods and findings to the development of digital twins of production systems: Firstly, it demonstrates how exceptional events in the validation of the digital twin can be handled. Secondly, it shows how structural changes in the system can be discovered using data on machine activity and process mining. Thirdly, the paper introduces a possibility on how to assess the accuracy of the digital twin. Furthermore, it demonstrates how to assess the robustness of the digital twin to estimation errors in machine processing times.
Journal: International Journal of Production Research
Pages: 3544-3558
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2242525
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2242525
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# input file: TPRS_A_2249125_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Margherita Molinaro
Author-X-Name-First: Margherita
Author-X-Name-Last: Molinaro
Author-Name: Guido Orzes
Author-X-Name-First: Guido
Author-X-Name-Last: Orzes
Author-Name: Marco Sartor
Author-X-Name-First: Marco
Author-X-Name-Last: Sartor
Author-Name: Guido Nassimbeni
Author-X-Name-First: Guido
Author-X-Name-Last: Nassimbeni
Title: A sand cone model of sustainability performance: an empirical analysis
Abstract: 
 The purpose of this paper is to shed light on the relationship between environmental, social and financial performance. In particular, based on the literature, we hypothesise the existence of a ‘sand cone’ model of sustainability that implies cumulative and sequential effects among the three performance dimensions. The hypothesis is tested using the fixed effects model on a longitudinal dataset of secondary data covering the period 2010–2019. The dataset includes 661 companies operating in the manufacturing industry and located in Europe, North America and Asia. The findings show that environmental, social and financial performance do not conflict but cumulate. The sequence of performance improvements that outlines a ‘sand cone’ starts with environmental sustainability and ends with financial performance, while social performance fully mediates the relationship between the two. Any other sequence is not confirmed by the data. These results are however valid only in Western countries (i.e. Europe and North America). Based on these findings, this research informs managers that the three pillars of sustainability have a cumulative effect, but only if a specific implementation sequence is followed. However, managers should be aware that these cumulative effects need some time to show up.
Journal: International Journal of Production Research
Pages: 3781-3799
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2249125
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2249125
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# input file: TPRS_A_2237609_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Towfique Rahman
Author-X-Name-First: Towfique
Author-X-Name-Last: Rahman
Author-Name: Sanjoy Kumar Paul
Author-X-Name-First: Sanjoy Kumar
Author-X-Name-Last: Paul
Author-Name: Renu Agarwal
Author-X-Name-First: Renu
Author-X-Name-Last: Agarwal
Author-Name: Nagesh Shukla
Author-X-Name-First: Nagesh
Author-X-Name-Last: Shukla
Author-Name: Firouzeh Taghikhah
Author-X-Name-First: Firouzeh
Author-X-Name-Last: Taghikhah
Title: A viable supply chain model for managing panic-buying related challenges: lessons learned from the COVID-19 pandemic
Abstract: 
 The COVID-19 pandemic exposed the vulnerabilities of global supply chains (SCs) and highlighted the need for more resilient and viable SCs. Panic-buying, in particular, has been a major challenge for SCs as it can create sudden surges in demand that are difficult to anticipate and manage. However, the literature lacks viable SC models and strategies to address panic-buying related challenges. As such, this research aims to identify and model viable recovery strategies to increase SC’s agility, resilience, and survivability and reduce panic-buying’s impact during a large-scale disruption in critical SCs. This study contributes by developing an integrated agent-based modeling (ABM) and optimisation method to simulate the behaviour of SCs under different scenarios and evaluating the effectiveness of four proposed strategies and three recovery plans. The findings reveal that increasing production at decentralised manufacturing facilities can be achieved by increasing order frequency to multiple suppliers and by partnering with third-party transporters, which can mitigate the effects of panic-buying. This results in higher output and availability of essential goods in the market, significantly managing panic-buying related challenges. Lastly, the study recommends practical solutions for businesses to enhance their SCs’ responsiveness to sudden demand surges from panic-buying.
Journal: International Journal of Production Research
Pages: 3415-3434
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2237609
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# input file: TPRS_A_2240433_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Fatima Ezzahra Achamrah
Author-X-Name-First: Fatima Ezzahra
Author-X-Name-Last: Achamrah
Author-Name: Ali Attajer
Author-X-Name-First: Ali
Author-X-Name-Last: Attajer
Title: Multi-objective reinforcement learning-based framework for solving selective maintenance problems in reconfigurable cyber-physical manufacturing systems
Abstract: 
 Unlike mass production manufacturing systems, where configurations are rarely changed after the initial design, reconfigurable cyber-physical systems (RCPMS) self-change their structures throughout missions and thus self-adjust production in response to demand requirements. Accordingly, such a paradigm requires enhancing selective maintenance strategy to optimise scheduling maintenance actions, selecting configuration layouts for capacity and product family changes, and achieving maintenance cost reduction and reliability maximisation. This paper is the first to propose a robust model for a selective maintenance problem with imperfect repairs in the RCPMS context. The model also integrates uncertainties originating from the imperfect observations of components' health status. The model's objectives are to maximise the expected reliability and minimise the variance and maintenance cost under maintenance resource constraints. Moreover, we propose a new deep reinforcement learning framework for solving the resulting multi-objective and combinatorial optimisation problem. In addition, we use decision values to enhance the scalarisation process by permitting the priorities of specific objectives to be adjusted after the learning process. Furthermore, we employ Analytical Hierarchy Process to adjust the static priorities with respect to the objective functions and the actual learning context. Finally, broad experiments are conducted to highlight the performance of the proposed model and resolution framework.
Journal: International Journal of Production Research
Pages: 3460-3482
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2240433
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2240433
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# input file: TPRS_A_2241565_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: G. N. Nikolov
Author-X-Name-First: G. N.
Author-X-Name-Last: Nikolov
Author-Name: A. N. Thomsen
Author-X-Name-First: A. N.
Author-X-Name-Last: Thomsen
Author-Name: A. F. Mikkelstrup
Author-X-Name-First: A. F.
Author-X-Name-Last: Mikkelstrup
Author-Name: Morten Kristiansen
Author-X-Name-First: Morten
Author-X-Name-Last: Kristiansen
Title: Computer-aided process planning system for laser forming: from CAD to part
Abstract: 
 Laser forming is a highly flexible and iterative contactless thermomechanical forming process that utilises a defocused laser beam to induce material shortening and bending. There is a high potential for the use of laser forming in rapid prototyping, small and unique batch production; however, to achieve that potential a certain level of automation is required. The presented work seeks to address this need of automation by proposing an end-to-end sheet-metal manufacturing system utilising laser forming and cutting, where the input for the system is a 3D CAD model and the output is a manufactured product. The contribution of the presented work is interconnected laser forming and cutting framework. The presented framework consists of subsystems for automatic extraction of geometrical information from a CAD model, process planning and generation of manufacturing information, scheduling of tasks and a feedback control loop for laser forming. The framework is experimentally validated and has shown consistent forming and cutting behaviour on two types of parts with variation in cutting features, bend angle and lengths of the bend's free edge.
Journal: International Journal of Production Research
Pages: 3526-3543
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2241565
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# input file: TPRS_A_2246161_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Chao Zhang
Author-X-Name-First: Chao
Author-X-Name-Last: Zhang
Author-Name: Jingjing Li
Author-X-Name-First: Jingjing
Author-X-Name-Last: Li
Author-Name: Guanghui Zhou
Author-X-Name-First: Guanghui
Author-X-Name-Last: Zhou
Author-Name: Qian Huang
Author-X-Name-First: Qian
Author-X-Name-Last: Huang
Author-Name: Min Zhang
Author-X-Name-First: Min
Author-X-Name-Last: Zhang
Author-Name: Yifan Zhi
Author-X-Name-First: Yifan
Author-X-Name-Last: Zhi
Author-Name: Zhibo Wei
Author-X-Name-First: Zhibo
Author-X-Name-Last: Wei
Title: A multi-level modelling and fidelity evaluation method of digital twins for creating smart production equipment in Industry 4.0
Abstract: 
 Rapid advances in new-generation information technologies have been the main driving force for the transformation of manufacturing enterprises in Industry 4.0. Digital twin (DT), as a key technology to promote intelligent manufacturing, has shown great potential for manufacturing enterprises to create an industrial intelligence-driven production equipment through in-depth integration of cyber-physical systems. However, the lack of a systematic effective DT modelling method with a supporting evaluation metric is the most important factor restricting the application of DT in manufacturing enterprises. To bridge the gap, this paper proposes a novel multi-level modelling and fidelity evaluation (MLM&FE) method of DT for creating smart production equipment in manufacturing enterprises, which could help enterprises establish an industrial intelligence-driven production environment to quickly respond to changes in the customised global market, thus greatly improving competitiveness of the enterprises. Specifically, this paper firstly designs a reference framework for DT-enhanced smart production equipment, on which an MLM&FE architecture is proposed. Then, key implementation methodologies and tools for MLM&FE are introduced from the perspective of data space modelling, virtual space modelling, knowledge space modelling, model integration and evaluation. Finally, the developed smart production equipment prototype demonstrates the feasibility and effectiveness of DT MLM&FE.
Journal: International Journal of Production Research
Pages: 3671-3689
Issue: 10
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2246161
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2246161
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# input file: TPRS_A_2221750_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Nenad Kosanić
Author-X-Name-First: Nenad
Author-X-Name-Last: Kosanić
Author-Name: Jakob Marolt
Author-X-Name-First: Jakob
Author-X-Name-Last: Marolt
Author-Name: Nenad Zrnić
Author-X-Name-First: Nenad
Author-X-Name-Last: Zrnić
Author-Name: Tone Lerher
Author-X-Name-First: Tone
Author-X-Name-Last: Lerher
Title: Travel time model for multiple-deep shuttle-based storage and retrieval systems
Abstract: 
 The paper presents an analytical model for travel time evaluation in double-deep, triple-deep, quadruple-deep and fivefold-deep tier-captive shuttle-based storage and retrieval system (SBS/RS). Under the assumption of the deepest location rule for the storage process and the nearest neighbour rule for the retrieval process, the expressions for single-command and dual-command cycle times of the shuttle vehicle and elevator are developed, from which the SBS/RS performance can be estimated. The model based on the probability theory enables the evaluation of all individual times that make up the cycle times and assessment of the average number of totes relocated during a retrieval process. Special attention is devoted to the modelling of the relocation of totes which block access to the requested tote during the retrieval process. The validity of the analytical model is examined via the developed simulation model. The given case study shows that the proposed analytical travel time model results match the results of the simulation model. The presented modelling strategy could be applied to bigger system racking depths following the same modelling logic.
Journal: International Journal of Production Research
Pages: 2606-2639
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2221750
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2221750
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# input file: TPRS_A_2151660_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Kun Wang
Author-X-Name-First: Kun
Author-X-Name-Last: Wang
Author-Name: Yongjian Li
Author-X-Name-First: Yongjian
Author-X-Name-Last: Li
Author-Name: Xiaohang Yue
Author-X-Name-First: Xiaohang
Author-X-Name-Last: Yue
Author-Name: Chunxing Fan
Author-X-Name-First: Chunxing
Author-X-Name-Last: Fan
Title: Leasing, trade-in for new, or the mixed of both: an analysis of new recycling modes driven by industry 4.0 technologies
Abstract: 
 The circular economy has become a promising solution to electronic product reuse . The advanced technology of Industry 4.0 drives the recycling platform (RP) to carry out a variety of new business modes, which are important ways to realise a circular economy. In this article, we consider a monopolistic RP under trade-in for new mode, leasing mode, or their mixed mode, respectively. We develop a discrete-time game with infinite periods and use the Markov decision and Bellman equation to obtain the consumer’s perfect equilibria consumption strategies . By comparing different modes under RP’s profits, consumer surplus, and environment impact perspectives, we find that when the durability of leased refurbished product exceeds that of the resold refurbished ones, the mixed mode is better than the trade-in for new mode, which can achieve more platform profits, more consumer surplus, and less environment impact. By considering the three perspectives together, the mixed mode is not always better than the other two modes. The mixed mode is optimal only when the durability of leased refurbished one is relatively high. We also conduct extensive numerical research, show optimal service mode under three perspectives, and extend the effects of different qualities of recycled used products on optimal mode.
Journal: International Journal of Production Research
Pages: 2350-2369
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2022.2151660
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2151660
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# input file: TPRS_A_2037779_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Chunguang Bai
Author-X-Name-First: Chunguang
Author-X-Name-Last: Bai
Author-Name: Qingyun Zhu
Author-X-Name-First: Qingyun
Author-X-Name-Last: Zhu
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: Circular economy and circularity supplier selection: a fuzzy group decision approach
Abstract: 
 The circular economy (CE) seeks to maintain products and materials at their highest utility and value. The organisational and governmental policy have seised onto the CE philosophy to advance socio-economic and environmental development. CE remains an essentially contested concept – making its utilisation as a foundation for managerial and policy decisions challenging. Circularity assessment has not been systematically adopted, especially within supply chain management. Using critical scholarly and practical evidential foundation, we proposed a comprehensive set of metrics that can be utilised in supplier selection, monitoring, and development for circularity. These metrics include the macro, meso, and micro levels. A group decision-making method integrating best-worst method (BWM), regret theory (RT), and dual hesitant fuzzy sets (DHFS) for circular economy and circularity (CEC) supplier evaluation and selection is introduced – providing instrumental value for the identified metrics typology. The proposed BWM-DHFE-RT integrative analytical method can accommodate decisionmaker psychological behaviour under uncertainty while simultaneously capturing divergent or conflicting opinions of different decision-makers. An illustrative business scenario is utilised to demonstrate the application of the proposed method. Though the proposed CE performance metrics and methodology are used for CEC supplier management reasons they have broader applicability. Future research and application directions are discussed.
Journal: International Journal of Production Research
Pages: 2307-2330
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2022.2037779
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2037779
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# input file: TPRS_A_2224446_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xavier Delorme
Author-X-Name-First: Xavier
Author-X-Name-Last: Delorme
Author-Name: Gérard Fleury
Author-X-Name-First: Gérard
Author-X-Name-Last: Fleury
Author-Name: Philippe Lacomme
Author-X-Name-First: Philippe
Author-X-Name-Last: Lacomme
Author-Name: Damien Lamy
Author-X-Name-First: Damien
Author-X-Name-Last: Lamy
Title: Modelling and solving approaches for scheduling problems in reconfigurable manufacturing systems
Abstract: 
 Reconfigurable manufacturing systems (RMS) intend to bridge the gap between dedicated and flexible manufacturing systems. If the literature is mainly focused on the design step and tactical planning of such systems, few research projects have addressed scheduling at the operational level. While setup times may occur in flexible manufacturing systems, reconfiguration times considered in RMS may affect several resources at once, and hence require specific modelling and solving approaches to be considered. This paper first formalises the problem at hand through integer linear programming. An iterative search method is then provided to obtain solutions to larger-scale instances. Results obtained on generated instances show that managing even few possible configurations can yield significant improvements in solutions’ quality. Meanwhile, the extended search space implied by the increase in available configurations hinders the convergence to a good solution in a reasonable computation time, which suggests further investigations.
Journal: International Journal of Production Research
Pages: 2683-2704
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2224446
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2224446
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# input file: TPRS_A_2117870_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Zhenxia Cheng
Author-X-Name-First: Zhenxia
Author-X-Name-Last: Cheng
Title: Stochastic dynamic production planning in hybrid manufacturing and remanufacturing system with random usage durations
Abstract: 
 This paper studies a multi-period dynamic production planning problem in a hybrid manufacturing and remanufacturing system (HMRS), where new and remanufactured products are perfect substitutes. The HMRS encounters uncertain return amounts due to products' random usage durations. As returns are from previous sales, production planning in each period impacts both current sales and future returns. The random return amount and the correlation among different periods make it a complex system. To solve the problem, we first utilise the hazard rate function and in-use products' information to derive an estimator of the return amount. Then, we formulate a dynamic programming model and prove a threshold policy is optimal under uniformly distributed demand. We employ marginal analysis to derive an approximation of the optimal threshold value. Through simulating all alternatives, the derived threshold is verified to be a good approximation as it achieves more than 99% of the optimal revenue in most scenarios. In addition, the calculated return amount based on the hazard rate function is almost identical to the return amount obtained via simulation. Compared to other return measurements, our method achieves the highest revenue in all considered scenarios, including heterogeneous usage durations and general demand distributions.
Journal: International Journal of Production Research
Pages: 2331-2349
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2022.2117870
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2117870
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# input file: TPRS_A_2217938_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: José Renatho da Silva Santana
Author-X-Name-First: José Renatho
Author-X-Name-Last: da Silva Santana
Author-Name: Helio Yochihiro Fuchigami
Author-X-Name-First: Helio Yochihiro
Author-X-Name-Last: Fuchigami
Title: Production scheduling problem with assembly flow shop systems: mathematical optimisation models
Abstract: 
 This work presents four mixed integer linear programming (MILP) models for the assembly flow shop problem in order to minimize the makespan. This production environment has two stages: production and assembly. The first stage consists of different machines designed to manufacture parts of a product. The second stage is intended for a final assembly. The performance measure considered is highly essential for industries from different segments, as it focuses on the best use of the time available for production. Statistical analysis with different tools was used to assess the performance and efficiency of mathematical models, emphasizing the analysis of performance profiles. Results showed that mathematical models are efficient, and the position-based model presented the best results for small and large instances during computational experimentation. All mathematical models can be used as direct tools in decision-making for the production sequencing problem in the approached environment.
Journal: International Journal of Production Research
Pages: 2483-2498
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2217938
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217938
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# input file: TPRS_A_2219345_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Maolin Yang
Author-X-Name-First: Maolin
Author-X-Name-Last: Yang
Author-Name: Yuqian Yang
Author-X-Name-First: Yuqian
Author-X-Name-Last: Yang
Author-Name: Pingyu Jiang
Author-X-Name-First: Pingyu
Author-X-Name-Last: Jiang
Title: A design method for edge–cloud collaborative product service system: a dynamic event-state knowledge graph-based approach with real case study
Abstract: 
 Product service system (PSS) is an effective approach to achieve win–win situation between service providers and consumers, and the design of PSS is the first step of its application. However, on the one hand, PSS is relatively an abstract concept, and what exactly should be considered when designing a PSS still require further exploration; on the other hand, the fast development of information and web technologies bring both opportunities and challenges for PSS design. For example, how to efficiently design the smart & connected products that support remote monitoring and control of service operation, how to build the dynamic service activity flow model that can be intuitively and visually read by human engineers and also can be conveniently deployed on computers, and how to realise edge–cloud collaboration between service providers and consumers. In this regard, a service requirement-oriented four-step generic PSS design method is established, including service mode selection and structured service order generation → smart & connected service product configuration → dynamic event-state knowledge graph-based service activity flow and service resource network configuration → industrial internet-based edge–cloud collaborative service delivering. Finally, a real design case of carbon block grinding and polishing PSS is used for verification.ABBREVIATIONS: AS: assembly service; C: controlling targets or objectives; I: input; M: enabling methods or mechanisms; MRO: maintenance, repair, and operation; MS: maintenance service; O: output; OEE: overall equipment effectiveness; PSS: product service system; PV: processing volume; RxEy-Sz: the relation from Event y to the State z of Service activity x; RxSz-Ey: the relation from the State z of Service activity x to Event y; StateAiCurrent: the current state of Service activity i; StateAiFuturek: the kth possible future state of Service activity i; StateAiHistoryj: the jth historical state of service activity i; StateEy: the state of Event y; Tq: the qth time point in the time line.
Journal: International Journal of Production Research
Pages: 2584-2605
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2219345
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2219345
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# input file: TPRS_A_2217298_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Chenglong Li
Author-X-Name-First: Chenglong
Author-X-Name-Last: Li
Author-Name: Junjie Wang
Author-X-Name-First: Junjie
Author-X-Name-Last: Wang
Author-Name: Xiao-Lin Wang
Author-X-Name-First: Xiao-Lin
Author-X-Name-Last: Wang
Title: Monitoring aggregate warranty claims with dynamically designed CUSUM and EWMA charts
Abstract: 
 Statistical monitoring of warranty claims data using dynamic probability control limits has been shown to be effective in early detection of unforeseen reliability problems that emerge at the design and manufacturing phases. As the discrepancy between abnormal patterns and the normal pattern in aggregate warranty claims is usually small (especially at the early stage), we develop two new dynamic monitoring schemes that adopt CUSUM-type and EWMA-type statistics, named DyCUSUM and DyEWMA, respectively, to better address the warranty claims monitoring problem. Three effective algorithms – that is, the Monte Carlo simulation, Markov chain, and near-enumeration algorithms – are proposed to progressively determine control limits for the two schemes. In particular, comparison studies show that the near-enumeration algorithm can attain a higher approximation accuracy with a lower computational burden and is thus recommended. In-depth simulation experiments are then conducted to assess the performance of the schemes. We find that the DyEWMA scheme has superior and robust detection performance in various situations, whereas the DyCUSUM scheme is less effective and could even be ineffective in certain cases, compared with a Shewhart-type counterpart. Some specific suggestions are also provided to facilitate implementation of the proposed monitoring schemes. Improved schemes by combining the moving window approach to mitigate the ‘inertia’ problem is further discussed. Finally, a real case study is presented.
Journal: International Journal of Production Research
Pages: 2370-2397
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2217298
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217298
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# input file: TPRS_A_2219343_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xinxin Ren
Author-X-Name-First: Xinxin
Author-X-Name-Last: Ren
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Yacine Rekik
Author-X-Name-First: Yacine
Author-X-Name-Last: Rekik
Author-Name: Xianhao Xu
Author-X-Name-First: Xianhao
Author-X-Name-Last: Xu
Title: Anticipatory shipping versus emergency shipment: data-driven optimal inventory models for online retailers
Abstract: 
 The inventory levels of pickup points play an important role for the same-day or next-day pickup and delivery services. The previous inventory optimisation research usually makes an assumption about demand distribution, does not use the real dataset or consider shipping strategies for this problem. In this study, we introduce a new strategy, mixture of anticipatory and emergency shipping, and propose forecasting-optimisation integrated approach to optimise multi-items' inventories in each pickup point based on big data analysis. We explore a real dataset including 23,808,261 records with 54 pickup points and 4018 items. We first cluster the dataset based on the distances between pickup points and the warehouse, then, implement the forecasting-optimisation integrated algorithms to select the more profitable strategy for each group. The result indicates that compared with the original algorithms, our proposed approach can effectively increase the profits, particularly, the novel algorithm, Long Short-Term Memory networks – Quantile Regression, performs better. Additionally, we find that the 100% anticipatory shipping is not necessarily superior to emergency shipment, when the pickup point is farther from the warehouse, the advantage of emergency shipment is more significant. However, the mixture of anticipatory and emergency shipping can contribute to higher profits for online retailers.
Journal: International Journal of Production Research
Pages: 2548-2565
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2219343
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2219343
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# input file: TPRS_A_2218942_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xavier Schepler
Author-X-Name-First: Xavier
Author-X-Name-Last: Schepler
Author-Name: Nabil Absi
Author-X-Name-First: Nabil
Author-X-Name-Last: Absi
Author-Name: Antoine Jeanjean
Author-X-Name-First: Antoine
Author-X-Name-Last: Jeanjean
Title: Refurbishment and remanufacturing planning model for pre-owned consumer electronics
Abstract: 
 In this paper, we are interested in modelling and solving a flow and resource planning problem related to the trade-in, treatment and resale of pre-owned consumer electronic products. This problem is motivated and inspired by the flows and the processes of the company Recommerce Group, which mainly handles traded-in used smartphones in Europe, but also used tablets, smartwatches, game consoles, laptops, etc. Collected products must be directed to refurbishment centres. After having been recorded, cleaned, tested and reset, they may be refurbished, or remanufactured by a subcontractor. They may also remain in their initial state. Finally, they are sold on diversified channels. This problem can be generalised to other refurbishment and remanufacturing activities of used consumer electronic products. We first formulate the problem as a mixed-integer linear program and show its NP-hardness. In order to solve large size real-life instances, mixed-integer programming based heuristic approaches are proposed. Extensive computational experiments on realistic instances are conducted to show the advantages and the limits of the proposed approaches. Several managerial insights are investigated and analysed.
Journal: International Journal of Production Research
Pages: 2499-2521
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2218942
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2218942
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# input file: TPRS_A_2218947_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Amandine Herbe
Author-X-Name-First: Amandine
Author-X-Name-Last: Herbe
Author-Name: Zarah Estermann
Author-X-Name-First: Zarah
Author-X-Name-Last: Estermann
Author-Name: Valentin Holzwarth
Author-X-Name-First: Valentin
Author-X-Name-Last: Holzwarth
Author-Name: Jan vom Brocke
Author-X-Name-First: Jan
Author-X-Name-Last: vom Brocke
Title: How to effectively use distributed ledger technology in supply chain management?
Abstract: 
 Distributed Ledger Technology (DLT) refers to multi-party systems that enables saving encrypted data across a peer-to-peer network of nodes, without central authority. While DLT applications have been mainly studied in finance, we conduct empirical research on DLT application in supply chain management, combining theory testing and theory elaborating case research. Applying the Theory of Affordance Actualisation, we identify five DLT affordances: (1) verify product origin and history, (2) exchange data on digital product models, (3) track and trace products’ logistics, (4) simplify supply chain finance, and (5) automate payments. We identify and evaluate these affordances and also outline how these affordances can be actualised. We contribute to the discourse of DLT value creation and provide practical guidance to assess DLT potential in supply chains. We integrate our findings into the academic discussion on collaboration in viable, intertwined supply networks.
Journal: International Journal of Production Research
Pages: 2522-2547
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2218947
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# input file: TPRS_A_2223701_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xiaoyue Zhang
Author-X-Name-First: Xiaoyue
Author-X-Name-Last: Zhang
Author-Name: Wenqiang Dai
Author-X-Name-First: Wenqiang
Author-X-Name-Last: Dai
Author-Name: Xiaoqiang Cai
Author-X-Name-First: Xiaoqiang
Author-X-Name-Last: Cai
Title: Inventory replenishment decisions with uncertain price and demand
Abstract: 
 This paper studies the multiple period inventory replenishment problem for a capacitated warehouse when procurement prices and market demands are both uncertain, with the goal to minimise the procuring and holding costs. We analyse this problem under the framework of competitive analysis, where neither probabilistic distributions nor sets are available to characterise the unknown price and demand parameters. An efficient online real-time replenishment algorithm is developed, which is free of any distribution assumption, and the decisions are made based entirely on past and present information. We derive an instance-independent competitive ratio of the algorithm, which provides a worst-case theoretical performance guarantee, and shows that the proposed algorithm performs well for situations with high volatility uncertainty over time and is naturally risk-averse. Finally, a set of numerical experiments further verifies the effectiveness of the algorithm.
Journal: International Journal of Production Research
Pages: 2663-2682
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2223701
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# input file: TPRS_A_2217937_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Wei Pu
Author-X-Name-First: Wei
Author-X-Name-Last: Pu
Author-Name: Shuang Ma
Author-X-Name-First: Shuang
Author-X-Name-Last: Ma
Author-Name: Xiangbin Yan
Author-X-Name-First: Xiangbin
Author-X-Name-Last: Yan
Title: Geographical relevance-based multi-period optimization for e-commerce supply chain resilience strategies under disruption risks
Abstract: 
 With the fierce competition in e-commerce, e-tailers are required to rapid responses to a variety of customised orders with multiple frequencies and strict delivery times. The delay or insufficient supply caused by disruptions might result in lost sales during long-term processes. To address this problem, a two-stage stochastic programming model considering profits, consumer service level (CSL) as well as market priorities is developed to manage long-term disruptions. We analyse multi-period consumer transaction data and formulate geographical relevance (GR) to link each marketplace with historical data in related regions and then prioritise market segments. A GR-based two-stage stochastic programming with multi-period is proposed, which (1) considers both proactive mitigation decisions before disruption and reactive recovery plans after disruption; (2) collaborates three resilience strategies; (3) optimises the e-tailer's profits considering market priorities during long-term disruptions. Using a real case of Chinese e-commerce under the COVID-19 pandemic, it is illustrated (1) the applicability and performance of the proposed GR-based model for multi-period resilience optimisation improving both the CSL and the total profit; (2) the efficiency and robustness of the developed sequential particle swarm optimisation with social structures algorithm. The proposed method could optimise e-tailers' response strategies for managing long-term disruptions in practice.
Journal: International Journal of Production Research
Pages: 2455-2482
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2217937
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217937
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# input file: TPRS_A_2219344_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Chayan Maiti
Author-X-Name-First: Chayan
Author-X-Name-Last: Maiti
Author-Name: Sreekumar Muthuswamy
Author-X-Name-First: Sreekumar
Author-X-Name-Last: Muthuswamy
Title: Classification of materials in cylindrical workpieces using image processing and machine learning techniques
Abstract: 
 Smart machine tools must be able to recognise the materials they interact with, in order to independently decide on what actions to be taken whenever needed. The purpose of this research is to offer a generic method to automate material identification and classification task utilising image processing and machine learning techniques so as to improve the cognitive capabilities of machine tools. A dataset of four material surfaces; Copper, Aluminium, Stainless Steel, and Bronze is generated and the RGB data are extracted. These colour channels are utilised as input features to train the machine learning algorithms. Convolutional Neural Network (CNN) and other classification methods like Support Vector Machine (SVM), Decision Trees, and k-Nearest Neighbour are also used to classify material images based on the generated dataset. A unique generalised technique, based on CNN, has been proposed to accurately recognise and categorise round surfaced materials during machining. The accuracy achieved by the classifier has reached 100% during training and testing. Test images are used to confirm the proposed methodology's capability to distinguish between materials based on various illumination environments and camera positions.
Journal: International Journal of Production Research
Pages: 2566-2583
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2219344
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# input file: TPRS_A_2222011_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yasemin Limon
Author-X-Name-First: Yasemin
Author-X-Name-Last: Limon
Author-Name: Tugce Martagan
Author-X-Name-First: Tugce
Author-X-Name-Last: Martagan
Author-Name: Ananth Krishnamurthy
Author-X-Name-First: Ananth
Author-X-Name-Last: Krishnamurthy
Title: Contracts for biopharmaceutical manufacturing based on production cost and capabilities
Abstract: 
 Strategic collaborations are critical to the success of efforts aimed at discovering new drugs and therapies in the biopharmaceutical industry. These collaborations aim to leverage domain expertise, asymmetries in production costs and/or capabilities to improve efficiency. Despite increasing collaborations, the biopharmaceutical industry lacks a structured guideline for choosing contracts. We present contract models with effort-based formulations that capture the key characteristics of biopharmaceutical operations and analyse incentive mechanisms such as fixed payment, revenue-sharing, risk-sharing, and cost-sharing in biopharmaceutical collaborations. We show that traditional incentive schemes do not achieve supply chain coordination, although they are commonly used in the industry. We introduce a new contract model called fee-for-effort-and-output contract that encourages the parties to exert higher efforts by offering discounts on their operating costs, and show that this contract achieves coordination with an appropriate selection of contract parameters. We also investigate the efficiency of noncoordinating contracts with traditional incentive schemes and identify the capability and cost structures under which they achieve the highest efficiency possible, to both determine the next-best alternatives and explain their popularity in practice.
Journal: International Journal of Production Research
Pages: 2640-2662
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2222011
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2222011
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# input file: TPRS_A_2217299_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Carlos Henrique dos Santos
Author-X-Name-First: Carlos Henrique
Author-X-Name-Last: dos Santos
Author-Name: Afonso Teberga Campos
Author-X-Name-First: Afonso Teberga
Author-X-Name-Last: Campos
Author-Name: José Arnaldo Barra Montevechi
Author-X-Name-First: José Arnaldo Barra
Author-X-Name-Last: Montevechi
Author-Name: Rafael de Carvalho Miranda
Author-X-Name-First: Rafael
Author-X-Name-Last: de Carvalho Miranda
Author-Name: Antonio Fernando Branco Costa
Author-X-Name-First: Antonio Fernando Branco
Author-X-Name-Last: Costa
Title: Digital Twin simulation models: a validation method based on machine learning and control charts
Abstract: 
 The adoption of simulation models as Digital Twins (DTs) has been standing out in recent years and represents a revolution in decision-making. In this context, we note increasingly faster and more efficient decisions by mirroring the behaviour of physical systems. On the other hand, we highlight the challenges to ensure the simulation models validity over time since traditional validation approaches have limitations when we consider the periodic update of the model. Thus, the present work proposes an approach based on the constant assessment of these models through Machine Learning and control charts. To this end, we suggest a monitoring tool using the K-Nearest Neighbors (K-NN) classifier, combined with a p-control chart, to periodically assess the validity of DT simulation models. The proposed approach was tested in several theoretical cases and also implemented in a real case study. The findings suggest that the proposed tool can monitor the DT functioning and identify possible special causes that could compromise its results. Finally, we highlight the wide applicability of the proposed tool, which can be used in different DT models, including near/real-time models with different characteristics regarding connection, integration, and complexity.
Journal: International Journal of Production Research
Pages: 2398-2414
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2217299
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# input file: TPRS_A_2217306_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Dezhi Zhang
Author-X-Name-First: Dezhi
Author-X-Name-Last: Zhang
Author-Name: Yarui Zhang
Author-X-Name-First: Yarui
Author-X-Name-Last: Zhang
Author-Name: Shuanglin Li
Author-X-Name-First: Shuanglin
Author-X-Name-Last: Li
Author-Name: Shuangyan Li
Author-X-Name-First: Shuangyan
Author-X-Name-Last: Li
Author-Name: Wanru Chen
Author-X-Name-First: Wanru
Author-X-Name-Last: Chen
Title: Bi-objective robust optimisation on relief collaborative distribution considering secondary disasters
Abstract: 
 Developing an effective emergency collaborative distribution system is critical to improve on-time response performance, especially considering secondary disasters. To address the challenge, this paper investigates a bi-objective robust optimisation model on relief collaborative distribution among three echelons of authorities, the province, the municipality, and the county, which aims to minimise the total travel time and the total humanitarian logistics cost simultaneously. The optimal location of relief supply facilities and the relief distribution schemes will be determined by the optimisation model, which considers uncertain demand and travel time. Moreover, two robust optimisation methods are utilised to deduce the robust counterparts of the proposed model. An epsilon-constraint-based approach is used to solve the bi-objective optimisation model. A real-world case study based on an earthquake and aftershocks with different magnitudes in Yunnan Province is provided. The results show that incorporating secondary disaster scenarios contributes to reducing the total travel time and cost. For making full use of emergency resources and preventing situations from worsening, the centralised decision scheme is more effective than the decentralised one. The uncertainty of demand of primary disaster relief has a higher impact on the optimal solution than that of travel time.
Journal: International Journal of Production Research
Pages: 2435-2454
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2217306
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217306
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# input file: TPRS_A_2217301_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Hubert Missbauer
Author-X-Name-First: Hubert
Author-X-Name-Last: Missbauer
Author-Name: Raik Stolletz
Author-X-Name-First: Raik
Author-X-Name-Last: Stolletz
Author-Name: Manuel Schneckenreither
Author-X-Name-First: Manuel
Author-X-Name-Last: Schneckenreither
Title: Order release optimisation for time-dependent and stochastic manufacturing systems
Abstract: 
 Order release optimisation is essential in production planning, especially in discrete manufacturing. Order release planning models with load-dependent lead times must anticipate the time-dependent work-in-process and output for any given release schedule and thus require an anticipation model that approximates the time-dependent behaviour of queueing systems. We present a generic optimisation model for order release planning in stochastic, non-stationary manufacturing systems that includes a well-defined interface for the anticipation model. We develop two stationary backlog carryover (SBC) approaches to approximate time-dependent queueing behaviour and prove their consistency with the order release model. The resulting nonlinear programming model is shown to be a special case of the well-known clearing function models. A numerical study demonstrates that the optimised order releases for different demand patterns are close to the optimum that results from simulation-based optimisation even for extreme demand and release patterns. The resulting output closely matches the simulated output with some deviations.
Journal: International Journal of Production Research
Pages: 2415-2434
Issue: 7
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2217301
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# input file: TPRS_A_2316476_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Author-Name: Bopaya Bidanda
Author-X-Name-First: Bopaya
Author-X-Name-Last: Bidanda
Author-Name: Joseph Geunes
Author-X-Name-First: Joseph
Author-X-Name-Last: Geunes
Author-Name: Kiran Fernandes
Author-X-Name-First: Kiran
Author-X-Name-Last: Fernandes
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Supply chain digitisation and management
Abstract: 
 In the rapidly evolving landscape, digitising the operations and facilities in a supply chain network is essential to make the system autonomous and develop strategies for enhancing resilience, transparency, and efficiency. The COVID-19 pandemic highlights the necessity of sustainable solutions for the hybrid mode of operations. To overcome several challenges, including price optimisation, demand forecasting under uncertainty, supply-demand gap reduction, take into account vulnerability, competitive business environment and risk, the supply chain needs to be streamlined with technology-driven infrastructures incorporating physical and information flow into overall supply chain processes. The digitisation aspect encompasses adopting cutting-edge technologies such as enterprise resource planning (ERP) for supply chain visibility, e-hailing platforms, real-time data analytics, the Internet of Things (IoT) and Internet of Behaviour (IoB), blockchain-driven technology, as well as additive manufacturing, enabling seamless connectivity and communication among diverse stakeholders. This revolution enables strategic integration of various entities and state of the art data-driven decision-making, providing real-time insights into logistics movements, demand forecasting, production planning and inventory levels. Supply chain digitisation and management emphasises collaboration with supply chain partners to identify important factors, optimise costs and enhance overall supply chain resilience. Digitisation and management are technological evolutions and strategic shifts integrating analytical tools, allowing businesses to formulate models to improve performance. The implementation of blockchain-driven technology solidifies trust and safety transactions by creating an immutable and transparent log, mitigating threats and enhancing traceability. Digitisation and management exemplify a transformative journey towards a more connected, data-driven, and agile global supply chain ecosystem.
Journal: International Journal of Production Research
Pages: 2918-2926
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2024.2316476
File-URL: http://hdl.handle.net/10.1080/00207543.2024.2316476
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# input file: TPRS_A_2234052_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Lorenzo Tiacci
Author-X-Name-First: Lorenzo
Author-X-Name-Last: Tiacci
Author-Name: Andrea Rossi
Author-X-Name-First: Andrea
Author-X-Name-Last: Rossi
Title: The sand-casting process: a meta-heuristic approach for an environment-friendly and profitable scheduling
Abstract: 
 Sand-casting is a process with a high-environmental impact in terms of both energy consumption and pollution emission. This work presents a meta-heuristic approach for the typical scheduling problem of mid-size sand casting foundries, with the objective to minimise the costs associated with labour, energy and wastes of melted material. Mid-size foundries usually have multiple parallel melting lines, each composed by a rotary and an electric furnace, and a single casting line which is the bottleneck of the process. The proposed approach has been tested on data related to a real industrial case study. Results show that, with respect to the scheduling implemented by the company, the proposed algorithm achieves a 3.2% reduction in emissions and a 4.1% reduction in energy consumption. Furthermore, these environment-friendly results are achieved while also increasing the company's profitability, by reducing total costs of more than 1% on the total revenue.
Journal: International Journal of Production Research
Pages: 2769-2791
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2234052
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2234052
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# input file: TPRS_A_2026004_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xuehao Feng
Author-X-Name-First: Xuehao
Author-X-Name-Last: Feng
Author-Name: Baolin Wen
Author-X-Name-First: Baolin
Author-X-Name-Last: Wen
Author-Name: Wenming Shi
Author-X-Name-First: Wenming
Author-X-Name-Last: Shi
Author-Name: Ilkyeong Moon
Author-X-Name-First: Ilkyeong
Author-X-Name-Last: Moon
Title: Universal point scheme with a platform and multiple retailers
Abstract: 
 This paper studies the universal point scheme with multiple retailers and a platform that implements the points within a channel. First, we analysed the equilibriums of the channel under the decentralised control and the mode of lateral cost-sharing among retailers. We found that retailers are willing to set the lowest point conversion ratios under the lateral cost-sharing mode compared with the decentralised and centralised control modes. The optimal conversion ratio of a retailer under the decentralised control is greater than the one under the centralised control when the cost spillover and double marginalisation are not significant. Next, we extended the model by considering the participation of new retailer. In this dynamic channel, the impact of the cost spillover phenomenon on the channel members’ preferences is discussed. Third, we showed that the wholesale price contract for point management used in the real world has a limitation in terms of profit split. Following this, we proposed a buyback contract and showed the optimal contract parameters under which the channel’s profit could be maximised and arbitrarily split. The managerial insights we obtained shed light on how to design a universal point scheme and select channel members to achieve an all-win scenario.
Journal: International Journal of Production Research
Pages: 2943-2962
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2022.2026004
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2026004
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# input file: TPRS_A_2235020_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yi Liu
Author-X-Name-First: Yi
Author-X-Name-Last: Liu
Author-Name: Justin Zuopeng Zhang
Author-X-Name-First: Justin Zuopeng
Author-X-Name-Last: Zhang
Author-Name: Sajjad Jasimuddin
Author-X-Name-First: Sajjad
Author-X-Name-Last: Jasimuddin
Author-Name: M. Zied Babai
Author-X-Name-First: M. Zied
Author-X-Name-Last: Babai
Title: Exploring servitization and digital transformation of manufacturing enterprises: evidence from an industrial internet platform in China
Abstract: 
 Servitization is vital to manufacturing enterprises’ competitive advantages and financial performance in contemporary digitalisation environments. Enterprises are increasingly relying on industrial Internet platforms to satisfy potential customers’ needs as well as to create superior value, but the literature has neglected to explain how enterprises can leverage such digital platform to improve the efficiency and effectiveness of servitization. This study aims at describing how the industrial Internet platform can enable servitization of manufacturers. Based upon the meta-theoretical foundations of service-dominant logic, we identify the ‘sense and respond’ servitization strategy enabled by the industrial Internet platform. By performing a questionnaire survey, we find that the industrial Internet platform approach based on the connectivity and compatibility architecture can enable manufacturers to improve the efficiency of resource integration and resource reconfiguration, which facilitates the implementation of servitization via market perception . We argue that the industrial Internet platform affects an organisation’s ability to sense the market and resource management actions; these operational resource actions are a significant antecedent of the servitization strategy.
Journal: International Journal of Production Research
Pages: 2812-2831
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2235020
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# input file: TPRS_A_2098873_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Tarun Kumar Agrawal
Author-X-Name-First: Tarun Kumar
Author-X-Name-Last: Agrawal
Author-Name: Ravi Kalaiarasan
Author-X-Name-First: Ravi
Author-X-Name-Last: Kalaiarasan
Author-Name: Jan Olhager
Author-X-Name-First: Jan
Author-X-Name-Last: Olhager
Author-Name: Magnus Wiktorsson
Author-X-Name-First: Magnus
Author-X-Name-Last: Wiktorsson
Title: Supply chain visibility: A Delphi study on managerial perspectives and priorities
Abstract: 
 Visibility across supply chains has been a key concern for organisations for many years, but the tools and information systems to achieve real-time visibility have not been available until recently. In response to uncertainty and complexity, advanced information and communication technologies have been explored for supply chain visibility (SCV). However, managerial perspectives are largely absent from the current literature. In response, this paper systematically documents managerial factors influencing SCV and information that should be collected and shared among supply chain partners for better visibility. A multi-stage Delphi analysis was conducted with 26 supply chain experts from various globally recognised enterprises with manufacturing units located worldwide. The results provide details on prioritised managerial perspectives and experiences within (1) factors affecting SCV (drivers, enablers, challenges and contingencies), (2) SCV content (supplier, internal and customer information) and (3) implications of SCV (capabilities and performance effects). One observation was that forecasting is not deemed as important due to severe disruptions in supply chains. Real-time visibility for better predictability emerged as the top priority. This study is among the few that empirically explores factors influencing supply chain visibility and generates new insights into why barriers can be difficult to overcome in complex supply chain settings.
Journal: International Journal of Production Research
Pages: 2927-2942
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2022.2098873
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2098873
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# input file: TPRS_A_2237120_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Kevin A. Bunn
Author-X-Name-First: Kevin A.
Author-X-Name-Last: Bunn
Author-Name: José A. Ventura
Author-X-Name-First: José A.
Author-X-Name-Last: Ventura
Title: Reformulations to improve the Lagrangian relaxation approach for the capacitated multi-product dynamic lot sizing problem with batch ordering
Abstract: 
 In this work, we study the multi-product dynamic lot-sizing problem with capacity constraints and batch ordering. This problem arises in short to medium range production scheduling for several products over a finite number of periods to meet known demand. Each period has a capacity for placing orders, and every order for each product must have a fixed quantity, or batch size, though multiple orders can be placed for each product. We define three mixed-integer linear programming (MILP) models and apply Lagrangian relaxation to formulate the corresponding dual problems by relaxing the capacity constraints. The aim is to identify the dual problem that is the easiest to solve and provides the solution with the smallest duality gap. Subgradient optimisation is applied to solve the preferred Lagrangian dual model, which uses one of two heuristics to find good feasible solutions. We also show that the special case, where the batch sizes for all products are the same, can be modeled as a transportation problem. A set of numerical experiments is designed to compare the performance of the Lagrangian relaxation approach with a commercial MILP solver to identify the version of the subgradient algorithm and the MILP model that provide the best solutions.
Journal: International Journal of Production Research
Pages: 2868-2887
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2237120
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2237120
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# input file: TPRS_A_2236726_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Tadeusz Sawik
Author-X-Name-First: Tadeusz
Author-X-Name-Last: Sawik
Author-Name: Bartosz Sawik
Author-X-Name-First: Bartosz
Author-X-Name-Last: Sawik
Title: Risk-averse decision-making to maintain supply chain viability under propagated disruptions
Abstract: 
 In this paper, stochastic optimisation of CVaR is applied to maintain risk-averse viability and improve resilience of a supply chain under propagated disruptions. In order to establish the risk-averse boundaries on supply chain viability space, two stochastic optimisation models are developed with the two conflicting objectives: minimisation of Conditional Cost-at-Risk and maximisation of Conditional Service-at-Risk. Then, the risk-averse viable production trajectory between the two boundaries is selected using a stochastic mixed integer quadratic programming model. The proposed approach is applied to maintain the supply chain viability in the smartphone manufacturing and the results of computational experiments are provided. The findings indicate that when the decision-making is more risk-aversive, the size of the viability space between the two boundaries is greater. As a result, more room is available for selecting viable production trajectories under severe disruptions. Moreover, the larger is viability space, the higher is both worst-case and average resilience of the supply chain. Risk-neutral, single-objective decision-making may reduce the supply chain viability. A single-objective supply chain optimisation which moves production to the corresponding boundary of the viability space, should not be applied under severe disruption risks to avoid greater losses.
Journal: International Journal of Production Research
Pages: 2853-2867
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2236726
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2236726
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# input file: TPRS_A_2232890_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xu Tian
Author-X-Name-First: Xu
Author-X-Name-Last: Tian
Author-Name: Joseph Sarkis
Author-X-Name-First: Joseph
Author-X-Name-Last: Sarkis
Title: Towards greener trade and global supply chain environmental accounting. An embodied environmental resources blockchain design
Abstract: 
 International trade, through global supply chains, is central to global sustainable production and consumption. Redistribution of environmental resources impacts through international trade has become apparent in ecological research – and may have long-term design and planning implications for production and supply chain management. However, current trade and production accounting methods are still incapable of providing accurate and reliable results for policymakers and organisational decision makers to manage global and supply chain trade issues. In this study, a blockchain-based conceptual framework for embodied environmental resources accounting in trade is proposed to address global supply chain and trade issues. Framework design, benefits, and challenges are also discussed. Future research and linkage to theory are also provided. This study provides a strong systemic foundation for managing environmental resources at the nexus of international trade, sustainable production, and global supply chains.
Journal: International Journal of Production Research
Pages: 2705-2724
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2232890
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2232890
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# input file: TPRS_A_2233625_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Jelena Milisavljevic-Syed
Author-X-Name-First: Jelena
Author-X-Name-Last: Milisavljevic-Syed
Author-Name: Jiahong Li
Author-X-Name-First: Jiahong
Author-X-Name-Last: Li
Author-Name: Hanbing Xia
Author-X-Name-First: Hanbing
Author-X-Name-Last: Xia
Title: Realisation of responsive and sustainable reconfigurable manufacturing systems
Abstract: 
 There is a lack of a design method for the manufacturing system reconfiguration to cope with the changing demand and evolving production technologies while minimising energy consumption. The key drivers for the new industrial paradigm are flexibility and sustainable manufacturing, which have been studied independently in the prior research. The aim of this research is to study two drivers simultaneously by designing robust models and analysing manufacturing system configurations to achieve feasible solutions in any scenario that may arise due to evolving, incomplete, and unforeseen production requirements, while minimising energy usage during product manufacture. To achieve this goal, this research develops a robustly validated pre-emptive decision engineering framework (DEF) for the manufacturing system reconfiguration process to manage future uncertainty of future conditions and identifies current production vulnerabilities and alternative production portfolios. In this research, a robust RMS reconfiguration strategy is designed using a compromise decision support problem (cDSP), and decentralised decision-making designs are explored through the use of game theory. The findings provide a new production system for adaptable, responsive, and sustainable manufacturing processes in the dynamic global economy. These results can empower stakeholders to make timely design decisions that lead to significant cost savings and sustainable manufacturing.
Journal: International Journal of Production Research
Pages: 2725-2746
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2233625
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2233625
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# input file: TPRS_A_2065550_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Jasashwi Mandal
Author-X-Name-First: Jasashwi
Author-X-Name-Last: Mandal
Author-Name: Adrijit Goswami
Author-X-Name-First: Adrijit
Author-X-Name-Last: Goswami
Author-Name: Sushma Kumari
Author-X-Name-First: Sushma
Author-X-Name-Last: Kumari
Author-Name: Nishikant Mishra
Author-X-Name-First: Nishikant
Author-X-Name-Last: Mishra
Title: A multi-agent framework for container booking and slot allocation in maritime shipping
Abstract: 
 Digitalization is constantly altering company paradigms and expanding cross-border supply chain prospects. Maritime transportation plays an increasingly essential part in the global supply network. Since maritime shipping services need to exchange a huge number of papers and paperwork across numerous companies, the usage of a unified platform for inter-organisational communication and information sharing is required. To develop an integrative, adaptive, and intelligent container booking system, a multi-agent architecture is designed in this article. The proposed architecture will aid the maritime industry in establishing real-time information interchange between autonomous agents, shippers, freight forwarders, and shipping lines. The process outlined in this paper reveals how the agents communicate with one another to resolve underlying inconsistencies. With the multi-agent framework, the article also presents a container slot optimisation problem considering market segmentation, different booking periods, heterogeneous containers and port congestion scenarios. Using this model the managers can find the booking limit for each type of containers and accordingly they can accept or reject the incoming booking requests. Furthermore, a simulated case study is also provided to validate the model.
Journal: International Journal of Production Research
Pages: 3044-3058
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2022.2065550
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2065550
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# input file: TPRS_A_2042612_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Bishnu Prasad Dash
Author-X-Name-First: Bishnu Prasad
Author-X-Name-Last: Dash
Author-Name: Vijaya Dixit
Author-X-Name-First: Vijaya
Author-X-Name-Last: Dixit
Title: Disaster supply chain with information and digital technology integrated in its institutional framework
Abstract: 
 The Indian subcontinent is highly susceptible to natural disasters. To abate the effect of the disasters, the government emanates institutional mechanisms and strategies for disaster preparedness, mitigation and response. Although there is well-established institutional framework in India for disaster management, there is no study that proposes a disaster supply chain structure under the institutional framework and integrates information and digital technologies (IDT) of industry 4.0 within it. The present study overcomes this research gap. It introduces an IDT structure within the institutional framework of India for multi-agency information sharing, coordination and decision making. It formulates a mathematical model and analyses the impact of IDT on the total response time through three scenarios. The results of scenario analysis reveal the significance of IDT on the disaster supply chains and its capability to handle information delays and IDT failure. The present study can be adopted by disaster management institutions to construct and implement better response practices at the operational, planning and strategic levels. Furthermore, the proposed model in the study can be used for vaccination planning, which includes vaccine distribution, monitoring, regulation and effective implmentation as a response against the current pandemic situation caused due to SARS-CoV-2.
Journal: International Journal of Production Research
Pages: 3003-3022
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2022.2042612
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2042612
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# input file: TPRS_A_2233641_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Marcel Panzer
Author-X-Name-First: Marcel
Author-X-Name-Last: Panzer
Author-Name: Benedict Bender
Author-X-Name-First: Benedict
Author-X-Name-Last: Bender
Author-Name: Norbert Gronau
Author-X-Name-First: Norbert
Author-X-Name-Last: Gronau
Title: A deep reinforcement learning based hyper-heuristic for modular production control
Abstract: 
 In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.
Journal: International Journal of Production Research
Pages: 2747-2768
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2233641
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2233641
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# input file: TPRS_A_2190816_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Huida Zhao
Author-X-Name-First: Huida
Author-X-Name-Last: Zhao
Author-Name: Jiaguo Liu
Author-X-Name-First: Jiaguo
Author-X-Name-Last: Liu
Author-Name: Guoqing Zhang
Author-X-Name-First: Guoqing
Author-X-Name-Last: Zhang
Title: Blockchain-driven operation strategy of financial supply chain under uncertain environment
Abstract: 
 The emergence of blockchain creates a new possibility to solve the fraudulent problem of financial supply chain. We construct a game model to verify the strategic choice of the financial supply chain in an uncertain environment. We derive the equilibrium results and investigate the strategic choice of blockchain service for the financial supply chain. We also study the product price, product quantity, financing interest rate, and supply chain risk transmission, respectively. Specifically, when the blockchain is not considered, the financial model of supply chain led by core enterprises depends on firms’ reputation. The retail and wholesale prices increase when fraud occurs or consideration payment increases. Besides, the market stability reduces price performance. In the blockchain environment, the strategic choices are divided into two cases: when choosing the core enterprise model and the third-party service model, the third-party service model is the equilibrium strategy; when choosing the third-party service model and the platform model, the platform model is the equilibrium strategy.
Journal: International Journal of Production Research
Pages: 2982-3002
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2190816
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2190816
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# input file: TPRS_A_1987554_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Arulanantha Prabu Ponnachiyur Maruthasalam
Author-X-Name-First: Arulanantha Prabu Ponnachiyur
Author-X-Name-Last: Maruthasalam
Author-Name: Debjit Roy
Author-X-Name-First: Debjit
Author-X-Name-Last: Roy
Author-Name: Prahalad Venkateshan
Author-X-Name-First: Prahalad
Author-X-Name-Last: Venkateshan
Title: Modelling driver's reactive strategies in e-hailing platforms: an agent-based simulation model and an approximate analytical model
Abstract: 
 For an e-hailing taxi operation, we analyse a driver's profit-maximising reactive strategy (to either accept or refuse a ride request) in response to the ride request broadcast by the platform. We analyse four operating modes, each of which is a combination of either of two reactive strategies: no refusal and refusal based on proximity, and either of two broadcasting methods. In an operating mode, our objective is to evaluate the expected total profit in a shift. We adopt a two-stage methodology to answer the research questions. In the first stage, we develop an agent-based simulation model to capture the effect of multiple taxis on driver's reactive strategy. Using real trip data, we find that a driver could follow a strategy of refusal based on proximity and earn approximately 25% more than the baseline no refusal strategy. In the second stage, we develop an approximate analytical model for a single taxi operation and compare the performance against the agent-based simulation model. We develop closed-form expressions of the expected total profit for each operating mode and topology of the service region. We find that our approximate analytical model provides an upper bound, and the profit deviation lies within 20% of the agent-based simulation model.
Journal: International Journal of Production Research
Pages: 2963-2981
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2021.1987554
File-URL: http://hdl.handle.net/10.1080/00207543.2021.1987554
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# input file: TPRS_A_2237122_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Anas Neumann
Author-X-Name-First: Anas
Author-X-Name-Last: Neumann
Author-Name: Adnene Hajji
Author-X-Name-First: Adnene
Author-X-Name-Last: Hajji
Author-Name: Monia Rekik
Author-X-Name-First: Monia
Author-X-Name-Last: Rekik
Author-Name: Robert Pellerin
Author-X-Name-First: Robert
Author-X-Name-Last: Pellerin
Title: Genetic algorithms for planning and scheduling engineer-to-order production: a systematic review
Abstract: 
 This paper provides a systematic review of the Genetic Algorithm (GA)s proposed to solve planning and scheduling problems in Engineer-To-Order (ETO) contexts. Our review focuses on how the key characteristics of ETO projects affect both the problem studied and the GA algorithmic features. Typical ETO projects consist of one-of-a-kind products with complex structures and uncertain designs. A deep analysis of the papers published between 2000 and 2022 enables identifying 10 main characteristics of ETO projects, six activity types, 10 decision types, eight groups of constraints, and 10 optimisation objectives. Our study shows that none of the reported papers integrates all 10 ETO characteristics. The less studied ETO characteristics are incorporating design and engineering information in the problem definition and the design uncertainty. Our review also identifies 10 recurrent encoding formats and emphasises the most frequently used genetic operators. We observed that most planning and scheduling problems consider objectives and decisions related to product customisation or supply chain configuration yielding multi-objective problems. Most multi-objective GAs use a weighted sum or are based on NSGAII. Diversity maintenance methods, adaptive and parameter tunning mechanisms, or hybridisation with machine learning models are still not used in this context.A systematic review of genetic algorithms dedicated to industrial planning and schedulingAnalysis on how the characteristics of ETO projects impact the design of genetic representation and operatorsRecommendation on approaches employed to reach high-quality solutions
Journal: International Journal of Production Research
Pages: 2888-2917
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2237122
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2237122
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# input file: TPRS_A_2041757_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Alessandra Cantini
Author-X-Name-First: Alessandra
Author-X-Name-Last: Cantini
Author-Name: Mirco Peron
Author-X-Name-First: Mirco
Author-X-Name-Last: Peron
Author-Name: Filippo De Carlo
Author-X-Name-First: Filippo
Author-X-Name-Last: De Carlo
Author-Name: Fabio Sgarbossa
Author-X-Name-First: Fabio
Author-X-Name-Last: Sgarbossa
Title: A decision support system for configuring spare parts supply chains considering different manufacturing technologies
Abstract: 
 A well-configured spare parts supply chain (SC) can reduce costs and increase the competitiveness of spare parts retailers. A structured method for configuring spare parts SCs should be used to determine whether to centralise or decentralise inventory management, also considering hybrid configurations. Moreover, such a method should define whether or not to switch the production of spare parts from Conventional Manufacturing (CM) technologies to Additive Manufacturing (AM) ones. Indeed, AM is considered the next revolution in the field of spare parts, and the adoption of AM technologies strongly affects the characteristics of SCs. However, the choice between centralisation and decentralisation is not the subject of much scientific research, and it is also not clear when AM would be the preferable manufacturing technology for spare parts. This paper aims to assist managers and practitioners in determining how to design their spare parts SCs, thus defining both the spare parts SC configuration and the manufacturing technology to adopt through the development of a decision support system (DSS). The proposed DSS is a user-friendly decision tree, and, for the first time, it allows comparison of the total costs of SCs characterised by different degrees of centralisation with both AM and CM spare parts.
Journal: International Journal of Production Research
Pages: 3023-3043
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2022.2041757
File-URL: http://hdl.handle.net/10.1080/00207543.2022.2041757
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# input file: TPRS_A_2235019_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Liukai Wang
Author-X-Name-First: Liukai
Author-X-Name-Last: Wang
Author-Name: Xinyi Kong
Author-X-Name-First: Xinyi
Author-X-Name-Last: Kong
Author-Name: Weiqing Wang
Author-X-Name-First: Weiqing
Author-X-Name-Last: Wang
Author-Name: Yu Gong
Author-X-Name-First: Yu
Author-X-Name-Last: Gong
Title: Pursuing supply chain ecosystem health under environmental turbulence: a supply chain learning approach
Abstract: 
 Although supply chain ecosystem health (SCE Health) is receiving attention in relation to environmental uncertainty, its conception and measurement are largely undocumented, and how to pursue SCE Health under environmental turbulence is unclear. Supply chain learning (SCL) is an important way to build dynamic capabilities, and whether it can empower the achievement of SCE Health is worthy of investigative study. Therefore, grounded in the dynamic capabilities theory, a survey data-based structural equation modelling (SEM) approach is employed. Based on four experts’ opinions and an in-depth literature review, 47 measurement items (11 for SCL, 28 for SCE Health, and 8 for environmental turbulence) were identified in the questionnaire design. Further, 208 valid questionnaires from the field survey of supply chain management (SCM)-related firms in China were collected and used for SEM analysis. The results show that the internal learning of SCL stimulates its external learning. SCL empowers the pursuit of SCE Health, which is strengthened under higher environmental turbulence. The theoretical framework and results also derive practical insights and support from 11 interviewees of five companies.
Journal: International Journal of Production Research
Pages: 2792-2811
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2235019
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2235019
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# input file: TPRS_A_2235027_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Minh-Tuan Truong
Author-X-Name-First: Minh-Tuan
Author-X-Name-Last: Truong
Author-Name: Hai-Canh Vu
Author-X-Name-First: Hai-Canh
Author-X-Name-Last: Vu
Author-Name: Phuc Do
Author-X-Name-First: Phuc
Author-X-Name-Last: Do
Author-Name: Benoit Iung
Author-X-Name-First: Benoit
Author-X-Name-Last: Iung
Author-Name: Alexandre Voisin
Author-X-Name-First: Alexandre
Author-X-Name-Last: Voisin
Title: Modelling and application of joint maintenance grouping and workload smoothing for an automotive plant
Abstract: 
 In the maintenance optimisation framework, grouping maintenance is a promising solution for maintenance planning of multi-component systems, in which maintenance activities are performed together to reduce maintenance costs. One of the most widely identified challenges in real applications of grouping maintenance is that it may disturb the maintenance workload balance (smoothness), causing many difficulties in production and/or labour scheduling and inventory management. In this study, we propose a joint optimisation approach for maintenance grouping and workload balancing to address the above challenge. First, a mathematical model of the joint optimisation problem was derived. A multi-objective grouping optimisation approach based on the Weighted Sum model and Genetic Algorithm was implemented to determine the Pareto-optimal grouping solution. The proposed approach was applied to a real case study of an automotive plant comprising 40 production lines with 1090 components. The results highlighted the advantages, effectiveness, and flexibility of the proposed maintenance approach in real-world applications.
Journal: International Journal of Production Research
Pages: 2832-2852
Issue: 8
Volume: 62
Year: 2024
Month: 04
X-DOI: 10.1080/00207543.2023.2235027
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2235027
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:8:p:2832-2852

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# input file: TPRS_A_2218499_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Aishwarya Dash
Author-X-Name-First: Aishwarya
Author-X-Name-Last: Dash
Author-Name: Pushpesh Pant
Author-X-Name-First: Pushpesh
Author-X-Name-Last: Pant
Author-Name: S. P. Sarmah
Author-X-Name-First: S. P.
Author-X-Name-Last: Sarmah
Author-Name: M. K. Tiwari
Author-X-Name-First: M. K.
Author-X-Name-Last: Tiwari
Title: The impact of IoT on manufacturing firm performance: the moderating role of firm-level IoT commitment and expertise
Abstract: 
 The Internet of Things has received enormous attention. Despite the lucrative potential, this study tries to look beyond the hype to understand how IoT impacts firm performance. Based on the information processing theory, we intend to explore how IoT influences the financial performance of firms. Firms, which realise the urgent need to adopt IoT might encounter a diverse set of challenges, like whether adoption will be profitable, the level of commitment they should devote, and whether to adopt as a first or second-mover. We want to comprehend such adoption challenges on the Indian manufacturing firm's financial performance. This study uses panel data from BSE 500 listed manufacturing firms and conducts multivariate analysis to understand the relationship between the IoT implementation proxies: IoT adoption, first-mover advantage, and firm performance in the light of IoT commitment and experts. The result indicates that IoT implementation has an insignificant effect on manufacturing firm performance. Meanwhile, the consideration of IoT commitment and experts jointly can enable a manufacturing firm to reap significantly positive financial outcomes. In other words, the IoT commitment and expertise positively moderate the relationship. The finding is useful to the decision-makers to address the firm-level adjustment before the mere introduction of IoT.
Journal: International Journal of Production Research
Pages: 3120-3145
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2218499
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2218499
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# input file: TPRS_A_2230317_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yang Hu
Author-X-Name-First: Yang
Author-X-Name-Last: Hu
Author-Name: Yu Yang
Author-X-Name-First: Yu
Author-X-Name-Last: Yang
Author-Name: Feng Wu
Author-X-Name-First: Feng
Author-X-Name-Last: Wu
Title: Dynamic cloud manufacturing service composition with re-entrant services: an online policy perspective
Abstract: 
 Cloud manufacturing (CMfg) emerges as a promising manufacturing paradigm, where service composition (SC) is a critical process concentrating on matching tasks and services. Existing studies usually ignore the dynamic nature of the CMfg environment, where task information is not always known before. Moreover, CMfg services are re-entrant, i.e. after being occupied for a period of service time, these services re-enter the CMfg platform (i.e. be available again). Re-entrant services significantly complicate CMfg platform revenue management. In this regard, we study the dynamic SC problem of CMfg (CMfg-DSC) incorporating re-entrant services within an online setting for the first time. CMfg-DSC is reformulated as an online packing problem. If a task is accepted, each requested service will be occupied until service time terminates. We propose online policies with performance guarantees, namely, static online packing policy (Static), opportunity-cost-based policy (Oppo), and dual-based policy with/without known distribution (Dual-k & Dual-u). Experiment results show that (1) Static is applicable for most cases; (2) Oppo has the potential for decent performance but at the cost of time; (3) Dual-u is reliable when only past observations are available; (4) Dual-k performs well given abundant service provision, but its performance would deteriorate if we lower the reward-cost threshold.
Journal: International Journal of Production Research
Pages: 3263-3287
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2230317
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2230317
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:9:p:3263-3287



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2226778_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Peter Burggräf
Author-X-Name-First: Peter
Author-X-Name-Last: Burggräf
Author-Name: Fabian Steinberg
Author-X-Name-First: Fabian
Author-X-Name-Last: Steinberg
Author-Name: Tim Weißer
Author-X-Name-First: Tim
Author-X-Name-Last: Weißer
Author-Name: Ognjen Radisic-Aberger
Author-X-Name-First: Ognjen
Author-X-Name-Last: Radisic-Aberger
Title: Deciding on when to change – a benchmark of metaheuristic algorithms for timing engineering changes
Abstract: 
 Changes to components, known as engineering changes (ECs), rarely occur on their own. In fact, in complex assembly systems, most ECs are introduced in batches to ensure that changed components match. As a result, to implement ECs optimally, multiple component’s stock must be considered until the change is executed on the EC effectivity date. This problem is known as the EC effectivity date optimisation problem, a variation of the general inventory control problem with deterministic and dynamic demand. As optimisation and monitoring of this problem is computationally expensive, research has suggested to investigate whether metaheuristics can provide adequate support. To fill this research gap, we present the results of a benchmark on basic metaheuristics for EC effectivity date optimisation. To do so, we have compared five common metaheuristics in their basic form (Ant Colony Optimisation, Genetic Algorithm, Particle Swarm Optimisation, Tabu Search, and Simulated Annealing) on a real-world test set. Of the tested algorithms the Genetic Algorithm identified most best solutions and returned good average results for the test cases. However, as its reliability was comparatively low, our research suggests a sequential application of the Genetic Algorithm and Tabu Search.
Journal: International Journal of Production Research
Pages: 3230-3250
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2226778
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2226778
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2225652_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Mohammad Shahin
Author-X-Name-First: Mohammad
Author-X-Name-Last: Shahin
Author-Name: F. Frank Chen
Author-X-Name-First: F. Frank
Author-X-Name-Last: Chen
Author-Name: Ali Hosseinzadeh
Author-X-Name-First: Ali
Author-X-Name-Last: Hosseinzadeh
Author-Name: Hamed Bouzary
Author-X-Name-First: Hamed
Author-X-Name-Last: Bouzary
Author-Name: Awni Shahin
Author-X-Name-First: Awni
Author-X-Name-Last: Shahin
Title: Waste reduction via image classification algorithms: beyond the human eye with an AI-based vision
Abstract: 
 Modern manufacturing is the world's largest and most automated industrial sector. The rise of Industry 4.0 technologies such as Big Data, Internet of Things (IoT) devices, and Machine Learning has enabled a better connection with machines and factory systems. Data harvesting allowed for a more seamless and comprehensive implementation of the knowledge-based decision-making process. New models that provide a competitive edge must be created by combining the Lean paradigm with the new technologies of Industry 4.0. This paper presents novel computer-based vision models for automated detection and classification of damaged packages from intact packages. In high-volume production environments, the package manual inspection process through the human eye consumes inordinate amounts of time poring over physical packages. Our proposed three different computer-based vision approaches detect damaged packages to prevent them from moving to shipping operations that would otherwise incur waste in the form of wasted operating hours, wasted resources and lost customer satisfaction. The proposed approaches were carried out on a data set consisting of package images and achieved high precision, accuracy, and recall values during the training and validation stage, with the resultant trained YOLO v7 model.
Journal: International Journal of Production Research
Pages: 3193-3211
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2225652
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2225652
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2231098_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Rony Mitra
Author-X-Name-First: Rony
Author-X-Name-Last: Mitra
Author-Name: Priyam Saha
Author-X-Name-First: Priyam
Author-X-Name-Last: Saha
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj
Author-X-Name-Last: Kumar Tiwari
Title: Sales forecasting of a food and beverage company using deep clustering frameworks
Abstract: 
 The competition among Food & Beverage companies has substantially increased in today's age of digitization. Sales forecasting is one of their main challenges. Due to space limitations, employee shortages, and rising online demand, retail sales forecasting became extremely important for Food and Beverage companies. This research analyzed the sales data of a multinational Food & Beverage Company. It proposed a framework using Gaussian Mixture Model (GMM) clustering, Hierarchical Agglomerative Clustering (HAC), and Random Forest algorithm for forecasting sales. This model analyzes the impact of the weekends, holidays, promotional activities, customer sentiments, festivals, and socio-economic situations in sales data and is able to forecast sales ranging from one to 15 months. An investigation of the suggested model's performance compared to numerous cutting-edge sales forecasting techniques is carried out to show its efficacy. Here, we demonstrate that the proposed hybrid model surpasses current predicting and computing efficiency methods. The results of this study can help retail managers to allocate resources and manage inventories in well-informed ways. The findings suggest that combining many strategies may produce the most precise forecasts.
Journal: International Journal of Production Research
Pages: 3320-3332
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2231098
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2231098
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2226772_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Funda Güner
Author-X-Name-First: Funda
Author-X-Name-Last: Güner
Author-Name: Abdül K. Görür
Author-X-Name-First: Abdül K.
Author-X-Name-Last: Görür
Author-Name: Benhür Satır
Author-X-Name-First: Benhür
Author-X-Name-Last: Satır
Author-Name: Levent Kandiller
Author-X-Name-First: Levent
Author-X-Name-Last: Kandiller
Author-Name: John. H. Drake
Author-X-Name-First: John. H.
Author-X-Name-Last: Drake
Title: A constraint programming approach to a real-world workforce scheduling problem for multi-manned assembly lines with sequence-dependent setup times
Abstract: 
 For over five decades, researchers have presented various assembly line problems. Recently, assembly lines with multiple workers at each workstation have become very common in the literature. These lines are often found in the manufacturing of large vehicles, where workers at a workstation may perform their assigned tasks at the same time. Most research on multi-manned assembly lines focuses on balancing tasks and workers among workstations and scheduling tasks for workers. This study, however, concentrates on assigning tasks to workers already assigned to a specific workstation, rather than balancing the entire line. The problem was identified through an industrial case study at a large vehicle manufacturing company. The study presents two methods, one using mixed integer linear programming and the other using constraint programming, to minimise the number of workers required on a multi-manned assembly line with sequence-dependent setup times. The results of the computational experiments indicate that the constraint programming method performs better than the mixed integer linear programming method on several modified benchmark instances from the literature. The constraint programming model is also tested on the real-world scenario of our industrial case study and leads to significant improvements in the productivity of the workstations.
Journal: International Journal of Production Research
Pages: 3212-3229
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2226772
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2226772
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2230489_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Amir Ahmadi-Javid
Author-X-Name-First: Amir
Author-X-Name-Last: Ahmadi-Javid
Author-Name: Maryam Haghi
Author-X-Name-First: Maryam
Author-X-Name-Last: Haghi
Author-Name: Pedram Hooshangi-Tabrizi
Author-X-Name-First: Pedram
Author-X-Name-Last: Hooshangi-Tabrizi
Title: Integrated job-shop scheduling in an FMS with heterogeneous transporters: MILP formulation, constraint programming, and branch-and-bound
Abstract: 
 Current studies on scheduling of machines and transporters assume that either a single transporter or an infinite number of homogeneous transporters such as AGVs or mobile robots are available to transport semi-finished jobs, which seems very restrictive in practice. This paper addresses this gap by studying a job-shop scheduling problem that incorporates a limited number of heterogeneous transporters, where the objective is to minimize the makespan. The problem is modelled using mixed-integer linear programming and constraint programming. Different structure-based branch-and-bound algorithms with two lower-bounding strategies are also developed. A comprehensive numerical study evaluates the proposed models and algorithms. The research demonstrates that the adjustment of the proposed MILP model outperforms the existing formulation when applied to the homogeneous case. The study also uncovers interesting practical implications, including the analysis of the impact of different transporter types in the system. It shows that utilizing a fleet of heterogeneous transporters can improve the overall performance of the job shop compared to a relevant homogeneous case. The importance of the study is emphasized by highlighting the negative consequences of disregarding transporters' differences during the scheduling phase.
Journal: International Journal of Production Research
Pages: 3288-3304
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2230489
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2230489
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:9:p:3288-3304



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2232471_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Taha J. Alhindi
Author-X-Name-First: Taha J.
Author-X-Name-Last: Alhindi
Author-Name: Jaeseung Baek
Author-X-Name-First: Jaeseung
Author-X-Name-Last: Baek
Author-Name: Young-Seon Jeong
Author-X-Name-First: Young-Seon
Author-X-Name-Last: Jeong
Author-Name: Myong K. Jeong
Author-X-Name-First: Myong K.
Author-X-Name-Last: Jeong
Title: Orthogonal binary singular value decomposition method for automated windshield wiper fault detection
Abstract: 
 For automobile manufacturers, reducing vehicle interior noise is essential for increasing customer satisfaction and vehicle quality. Windshield wipers are one of the major components that generate such noises, and faulty wipers could negatively affect passengers’ psychological and physiological perceptions while driving. Thus, identifying faulty wipers during the manufacturing process would improve the driving experience and vehicle and road safety as well as reduce driver distraction. However, the existing windshield wiper noise-detection process is entirely manual, relies upon human subjectivity, and is time-consuming. Accordingly, this paper develops a novel automated windshield wiper fault-detection system. First, a novel binarization approach is used to effectively binarize the transformed spectrograms of sound signals from windshield wiper operation to segment nAoisy regions. Then, a new matrix-factorisation approach called orthogonal binary singular value decomposition is proposed to decompose binarized mel spectrograms into uncorrelated binary eigenimages to extract meaningful features and identify faulty wipers. Then, the 
 $ k $ k-nearest neighbour classifier is utilised to classify the extracted features into normal or faulty windshield wipers. Finally, to demonstrate the effectiveness of the proposed system, it was validated on real-life windshield wiper reversal and squeal noise datasets, where it outperformed existing methods and achieved accuracies of 95% and 94%, respectively.
Journal: International Journal of Production Research
Pages: 3383-3397
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2232471
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2232471
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2222186_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Michal Koren
Author-X-Name-First: Michal
Author-X-Name-Last: Koren
Author-Name: Yael Perlman
Author-X-Name-First: Yael
Author-X-Name-Last: Perlman
Author-Name: Matan Shnaiderman
Author-X-Name-First: Matan
Author-X-Name-Last: Shnaiderman
Title: Inventory management for stockout-based substitutable products under centralised and competitive settings
Abstract: 
 Inventory planning in fashion markets is highly challenging, owing to uncertain demand; yet, in making inventory decisions, retailers may be able to capitalise on high substitutability between products. This research develops single-period inventory-management models describing a market with two substitutable products, under stockout-based substitution; i.e. when a customer’s preferred product is out-of-stock, s/he may choose to purchase the substitute. Two settings are considered: centralised (a single retailer who sells both products) and competitive (two retailers, each selling one product). For each setting, we derive closed-form analytical solutions for the inventory levels that maximise expected profit. The model is further enriched with sales data from an online apparel retailer offering substitutable products (a sneaker in different colours), and we analyse the sensitivity of the optimal inventory levels and profits to parameter values. Key findings include the following: (i) Under competitive conditions, both retailers always order positive inventory so as not to lose customers. However, in a single-retailer setting, there are situations in which the retailer orders inventory for only one product. (ii) The optimal inventory levels and corresponding profits are highly sensitive to consumers’ willingness to substitute between products. These findings provide concrete insights that can guide fashion brands’ inventory-management decisions.
Journal: International Journal of Production Research
Pages: 3176-3192
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2222186
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2222186
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2232470_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Dimitris Mourtzis
Author-X-Name-First: Dimitris
Author-X-Name-Last: Mourtzis
Author-Name: John Angelopoulos
Author-X-Name-First: John
Author-X-Name-Last: Angelopoulos
Author-Name: Nikos Panopoulos
Author-X-Name-First: Nikos
Author-X-Name-Last: Panopoulos
Title: Unmanned Aerial Vehicle (UAV) path planning and control assisted by Augmented Reality (AR): the case of indoor drones
Abstract: 
 Following the recent advances in Industry 4.0 and the upcoming Industry 5.0, the use of multiple UAVs for indoor tasks has risen, particularly in real-time remote monitoring, wireless coverage, and remote sensing. As a result, UAVs can be viewed as proactive problem solvers and can support Internet of Things (IoT) platforms by collecting and monitoring data cost-effectively and efficiently, leading to better decision-making. Moreover, sophisticated drone operations require specialised software and data processing abilities. However, the utilisation of drones has been mainly focused on outdoor environments, thus creating a literature gap regarding indoor navigation and operation. Therefore, the design and development of a method for remote planning and control of drones based on the utilisation of AR is presented in this paper. The proposed method is based on the utilisation of drones for remote monitoring. The suggested approach involves engineers designing a sequence of actions and transmitting them wirelessly to the drone, eliminating the need for human intervention. Thus, the proposed method contributes towards enabling engineers visualise the drone path with the use of Augmented Reality and provides the flexibility of adding multiple way points. The applicability of the developed framework is tested in a laboratory-based machine shop.
Journal: International Journal of Production Research
Pages: 3361-3382
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2232470
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2232470
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2217300_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Spyros I. Vlastos
Author-X-Name-First: Spyros I.
Author-X-Name-Last: Vlastos
Author-Name: A. S. Xanthopoulos
Author-X-Name-First: A. S.
Author-X-Name-Last: Xanthopoulos
Author-Name: D. E. Koulouriotis
Author-X-Name-First: D. E.
Author-X-Name-Last: Koulouriotis
Title: Stochastic modelling and analysis of a deteriorating serial production–inventory network
Abstract: 
 This study focuses on the stochastic modelling and analysis of a serial production network consisting of two manufacturing stations operating under a make-to-stock inventory policy. The outcome is a single type of product and every manufacturing station includes a machine and an output buffer. Both machines are gradually deteriorating during their operation. Deterioration results in a reduced production rate. Continuous-time Markov chain was used to model all the possible states the network transits over time due to the occurrence of certain events, such as client arrival, deterioration failure, production or repair completion. The structure of the Markov chain was thoroughly studied providing useful information, supporting the effort of numerical solving to determine the steady-state probabilities enabling the calculation of useful performance metrics like equipment availability, down time, idle time, utilisation and average inventory. Through a series of numerical experiments, the behaviour of the serial production network was examined while alternating its parameters. Interesting conclusions emerged regarding the factors affecting the operation of such production systems subjected to gradual deterioration.
Journal: International Journal of Production Research
Pages: 3084-3098
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2217300
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217300
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2217304_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xiong Zhao
Author-X-Name-First: Xiong
Author-X-Name-Last: Zhao
Author-Name: Lianyu Zheng
Author-X-Name-First: Lianyu
Author-X-Name-Last: Zheng
Author-Name: Maoyuan Shi
Author-X-Name-First: Maoyuan
Author-X-Name-Last: Shi
Author-Name: Xuexin Zhang
Author-X-Name-First: Xuexin
Author-X-Name-Last: Zhang
Author-Name: Yuehong Zhang
Author-X-Name-First: Yuehong
Author-X-Name-Last: Zhang
Title: Unified modelling for continuous–discrete hybrid adaptive machining CPS of large thin-walled parts
Abstract: 
 Traditional machining is transforming to digital and intelligent machining, in which adaptive machining cyber-physical system (CPS) provides a useful approach to control the machining quality of large thin-walled parts. And the running of adaptive machining CPS is a complex multi-processes execution flow, which can be regarded as a continuous–discrete hybrid system. To realise adaptive controlling of machining quality and adaptive managing of process flow, a unified model for continuous–discrete hybrid adaptive machining CPS is constructed. Firstly, an architecture of adaptive machining CPS is proposed. Next, the cutting process in adaptive machining CPS is modelled as a continuous-variable system (CVS), while the process flow in adaptive machining CPS is modelled as a discrete-events system (DES). Then, the finite state machine is adopted to integrate the CVS and DES to form the unified model of adaptive machining CPS. Finally, an adaptive machining CPS is developed based on the unified model, and the machining results demonstrate that machining quality is efficiently controlled, as well as the process flow is orderly managed. The built unified model has four features, respectively universality, integrability, scalability, and reconfigurability, which can be reconstructed to form a new instancing model according to the different machining requirements.The cutting process in adaptive machining CPS is modelled as a continuous-variable system (CVS), while the process flow in adaptive machining CPS is modelled as a discrete-events system (DES). The finite state machine is adopted to integrate the CVS and DES to form the unified model of adaptive machining CPS.
Journal: International Journal of Production Research
Pages: 3099-3119
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2217304
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2217304
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2217297_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Satie L. Takeda-Berger
Author-X-Name-First: Satie L.
Author-X-Name-Last: Takeda-Berger
Author-Name: Enzo M. Frazzon
Author-X-Name-First: Enzo M.
Author-X-Name-Last: Frazzon
Title: An inventory data-driven model for predictive-reactive production scheduling
Abstract: 
 Scheduling is a complex task due to the need to optimise multiple competing objectives and react to unpredictable events that may occur during production execution. The strategy of predictive-reactive scheduling can be used to reconcile the conflict between the original schedule and the current shop floor situation. This study seeks to present an inventory data-driven predictive-reactive production scheduling model that supports the evolving concepts of the Industry 4.0. Periodically, a machine learning technique provides predictive scheduling considering a best-case scenario according to an established Key Performance Indicator (KPI). Then, material non-availability causes disruptions in production, which triggers the Simulation-Based Optimization (SBO) method to handle these events. Thus, SBO provides a reactive schedule with the best set of priority rules to sequence jobs on each machine according to the data on the shop floor. This model was validated with a real case study using data collected from a metal-mechanical company. Considering the service level KPI, the results showed that the model is able to find a better solution in the compared scenarios. Therefore, even in a dynamic and stochastic scenario, with machine breakdowns, quality problems, raw material delays, and accuracy issues, the model proved efficient in mitigating these variations’ effects.
Journal: International Journal of Production Research
Pages: 3059-3083
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2217297
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# input file: TPRS_A_2220826_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Francesco Pilati
Author-X-Name-First: Francesco
Author-X-Name-Last: Pilati
Author-Name: Riccardo Tronconi
Author-X-Name-First: Riccardo
Author-X-Name-Last: Tronconi
Title: Multi-objective optimisation for sustainable few-to-many pickup and delivery vehicle routing problem
Abstract: 
 E-commerce is a continuously growing sector significantly affected by sustainability issues during the last few years. To deal with economic, environmental and social sustainability aspects, e-commerce platforms consolidate orders to pick-up several requests from the same location, defining the so-called Few-to-Many Pick-up and Delivery Vehicle Routing Problem (F-M VRPPD). The proposed contribution addresses the optimisation of this problem by developing a multi-objective simulated annealing algorithm distinguished by four tailored Local Search (LS) operators specifically developed to increase the probability to identify feasible solutions and decrease the computational time. This algorithm is validated with several instances of a case study e-commerce platform based in an European mountain region. Firstly, the original LS operators are compared to benchmark literature ones to solve identical problems, reporting better performance in 84% of these instances. Furthermore, for the most relevant scenarios significant results are presented and discussed concerning the economic, environmental and social performance of the defined solutions according to the characteristics of the instances, as the routes height profile and the drivers’ metabolic energy consumption. The tri-dimensional Pareto frontiers suggest how through a slight worsening in the economic objective function it is possible to improve the social one by up to 18.3% on average.
Journal: International Journal of Production Research
Pages: 3146-3175
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2220826
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2220826
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# input file: TPRS_A_2242508_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Nikolai Kazantsev
Author-X-Name-First: Nikolai
Author-X-Name-Last: Kazantsev
Author-Name: Michael DeBellis
Author-X-Name-First: Michael
Author-X-Name-Last: DeBellis
Author-Name: Qudamah Quboa
Author-X-Name-First: Qudamah
Author-X-Name-Last: Quboa
Author-Name: Pedro Sampaio
Author-X-Name-First: Pedro
Author-X-Name-Last: Sampaio
Author-Name: Nikolay Mehandjiev
Author-X-Name-First: Nikolay
Author-X-Name-Last: Mehandjiev
Author-Name: Iain Duncan Stalker
Author-X-Name-First: Iain Duncan
Author-X-Name-Last: Stalker
Title: An ontology-guided approach to process formation and coordination of demand-driven collaborations
Abstract: 
 Demand shocks and fluctuations underscore the need for new approaches to coordinate collaboration between firms to scale up production. This paper proposes an approach to formalise product and process requirements via a collaboration ontology and applies semantic reasoning techniques for process formation. Our approach contributes to production research by providing flexibility in coordinating firms engaged in demand-driven collaboration. The proposed approach has four core dimensions: (1) The Collaboration ontology builds on a set of product assembly requirements, process steps, their input/output resources and semantic rules; (2) the ontology reasoner derives resource dependencies between the steps; (3) the java tool interprets resource dependencies as possible transitions in Business Process Management Notation (BPMN); (4) a workflow engine executes the generated product assembly process. The approach and the ontology were validated in an industrial aerospace tendering scenario demonstrating its practical relevance for firms seeking demand-driven collaborations to react to production changes. Finally, we position and explain our contributions to the body of knowledge in collaborative production engineering.
Journal: International Journal of Production Research
Pages: 3398-3414
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2242508
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# input file: TPRS_A_2227903_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Fernanda Strozzi
Author-X-Name-First: Fernanda
Author-X-Name-Last: Strozzi
Author-Name: Rossella Pozzi
Author-X-Name-First: Rossella
Author-X-Name-Last: Pozzi
Title: Trend and seasonality features extraction with pre-trained CNN and recurrence plot
Abstract: 
 GoogLeNet is a pre-trained Convolutional Neural Network (CNN) that allows transfer learning and has achieved high recognition rates in image classification tasks. A Recurrence Plot (RP) is an imaging method that depicts the recurrence of the state space system using coloured points and lines in 2D images. This work contributes to facilitating time series feature extraction by proposing a method that applies the GoogLeNet to time series images obtained with RP. The developed method is tested using simulated time series and selected time series from the M3 competition dataset. The results shows that the transfer learning approach allowed the extraction of business time series features by means of a GoogLeNet fine-tuned using 100 simulated time series. The combination of GoogLeNet and RPs outperforms the alternative and easier combination of GoogLeNet and plots of the time series and support the convenience of the RP transformation step. This application of deep learning techniques to business time series imaging offers opportunity for further developments.
Journal: International Journal of Production Research
Pages: 3251-3262
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2227903
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2227903
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# input file: TPRS_A_2232050_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Violetta Giada Cannas
Author-X-Name-First: Violetta Giada
Author-X-Name-Last: Cannas
Author-Name: Maria Pia Ciano
Author-X-Name-First: Maria Pia
Author-X-Name-Last: Ciano
Author-Name: Mattia Saltalamacchia
Author-X-Name-First: Mattia
Author-X-Name-Last: Saltalamacchia
Author-Name: Raffaele Secchi
Author-X-Name-First: Raffaele
Author-X-Name-Last: Secchi
Title: Artificial intelligence in supply chain and operations management: a multiple case study research
Abstract: 
 Artificial intelligence (AI) is increasingly considered a source of competitive advantage in operations and supply chain management (OSCM). However, many organisations still struggle to adopt it successfully and empirical studies providing clear indications are scarce in the literature. This research aims to shed light on how AI applications can support OSCM processes and to identify benefits and barriers to their implementation. To this end, it conducts a multiple case study with semi-structured interviews in six companies, totalling 17 implementation cases. The Supply Chain Operations Reference (SCOR) model guided the entire study and the analysis of the results by targeting specific processes. The results highlighted how AI methods in OSCM can increase the companies’ competitiveness by reducing costs and lead times and improving service levels, quality, safety, and sustainability. However, they also identify barriers in the implementation of AI, such as ensuring data quality, lack of specific skills, need for high investments, lack of clarity on economic benefits and lack of experience in cost analysis for AI projects. Although the nature of the study is not suitable for wide generalisation, it offers clear guidance for practitioners facing AI dilemmas in specific SCOR processes and provides the basis for further future research.
Journal: International Journal of Production Research
Pages: 3333-3360
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2232050
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2232050
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# input file: TPRS_A_2231088_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yeonju Lee
Author-X-Name-First: Yeonju
Author-X-Name-Last: Lee
Author-Name: Youngju Kim
Author-X-Name-First: Youngju
Author-X-Name-Last: Kim
Author-Name: Bogyeong Lee
Author-X-Name-First: Bogyeong
Author-X-Name-Last: Lee
Author-Name: Chang Ouk Kim
Author-X-Name-First: Chang Ouk
Author-X-Name-Last: Kim
Title: Discovery of fault-introducing tool groups with a numerical association rule mining method in a printed circuit board production line
Abstract: 
 Large-scale manufacturers aim to reduce the number of faulty products by finding tools or process factors that cause product faults through tool monitoring. The causes of faulty electronic components such as semiconductor chips and printed circuit boards (PCBs) include abnormalities in single tools and abnormalities caused by interactions between the tools of a specific process and a related process. Here, the tools exhibiting an interaction effect are called the fault-introducing tool group. This study presents a numerical association rule mining method for discovering the fault-introducing tool groups based on a genetic algorithm. A novel fitness function and rule pruning process are developed to identify the fault-introducing tool groups. The effectiveness of the method is verified using simulations and a case study of actual PCB production lines. The proposed method can discover fault-introducing tool groups better than machine learning algorithms. Additionally, the method can accurately identify fault-introducing tool groups in various manufacturing environments, such as those with highly skewed yield distributions or variations in yield distributions over time. In an actual PCB production line, the groups identified by the proposed method produced up to 36.5% more faulty chips than those identified by the comparison models.
Journal: International Journal of Production Research
Pages: 3305-3319
Issue: 9
Volume: 62
Year: 2024
Month: 05
X-DOI: 10.1080/00207543.2023.2231088
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2231088
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# input file: TPRS_A_2251159_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Dounia Skalli
Author-X-Name-First: Dounia
Author-X-Name-Last: Skalli
Author-Name: Abdelkabir Charkaoui
Author-X-Name-First: Abdelkabir
Author-X-Name-Last: Charkaoui
Author-Name: Anass Cherrafi
Author-X-Name-First: Anass
Author-X-Name-Last: Cherrafi
Author-Name: Alireza Shokri
Author-X-Name-First: Alireza
Author-X-Name-Last: Shokri
Author-Name: Jose Arturo Garza-Reyes
Author-X-Name-First: Jose Arturo
Author-X-Name-Last: Garza-Reyes
Author-Name: Jiju Antony
Author-X-Name-First: Jiju
Author-X-Name-Last: Antony
Title: Analysis of factors influencing Circular-Lean-Six Sigma 4.0 implementation considering sustainability implications: an exploratory study
Abstract: 
 In this study, we develop a new paradigm, Circular Lean Six Sigma 4.0 (CLSS4.0) to promote manufacturing sustainability. This paper aims to provide a practical and holistic view of the drivers and barriers that can help companies design an integrated CLSS4.0 model. The paper is based on a qualitative exploratory study using multiple case studies within 12 Moroccan manufacturing firms conducted through semi-structured interviews with top executive managers. The results show that the drivers are related to expected operational and environmental performance, increasing customer requirements, gaining competitive advantage and market growth while barriers are related to insufficient tangible (finance, human and equipment) and intangible (skills and techniques) resources, data privacy, technical issues and management support. The proposed framework identifies the assessment of drivers and barriers and their attributes as a starting point for managers to lead the CLSS4.0 transformation, thereby contributing to its successful implementation. To the best of our knowledge, this study is among the very first studies to discuss the CLSS4.0 drivers and barriers. It could be useful to managers as a diagnostic tool to assess their ability to implement CLSS4.0 before investing in the initiative.
Journal: International Journal of Production Research
Pages: 3890-3917
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2251159
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2251159
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# input file: TPRS_A_2251064_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yilin Fang
Author-X-Name-First: Yilin
Author-X-Name-Last: Fang
Author-Name: Zhiyao Li
Author-X-Name-First: Zhiyao
Author-X-Name-Last: Li
Author-Name: Siwei Wang
Author-X-Name-First: Siwei
Author-X-Name-Last: Wang
Author-Name: Xinwei Lu
Author-X-Name-First: Xinwei
Author-X-Name-Last: Lu
Title: Multi-objective multi-fidelity optimisation for position-constrained human-robot collaborative disassembly planning
Abstract: 
 Human-robot collaborative disassembly lines are widely used by remanufacturing companies to disassemble end-of-life (EOL) products. When disassembling large-sized EOL products, each workstation on a disassembly line is generally divided into multiple operating positions, so that different operators can disassemble the same product at their respective positions at the same time, thereby greatly improving efficiency. This paper focuses on a position-constrained human-robot collaborative disassembly planning (PC-HRCDP) problem for the above-mentioned lines, including three subproblems of disassembly sequence planning, disassembly line balancing and robot path planning. A multi-objective mixed integer programming model for PC-HRCDP is developed to solve small-scale instances. Furthermore, a multi-objective multi-fidelity optimisation (MO-MFO) algorithm is proposed to solve large-scale instances. Comprehensive experiments are conducted based on 10 problem instances generated in this study. Experimental results show that the proposed MO-MFO is better than a high-fidelity optimisation algorithm in terms of running time. In addition, benefiting from the strategy of MO-MFO to allocate the limited high-fidelity computational budget to solutions in the two stages of multi-objective optimisation and optimal sampling, MO-MFO is significantly better than the existing representative multi-fidelity optimisation algorithms in terms of the hyper-volume and the inverted generational distance.
Journal: International Journal of Production Research
Pages: 3872-3889
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2251064
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2251064
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# input file: TPRS_A_2254402_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Bipan Zou
Author-X-Name-First: Bipan
Author-X-Name-Last: Zou
Author-Name: Siqing Wu
Author-X-Name-First: Siqing
Author-X-Name-Last: Wu
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Zhe Yuan
Author-X-Name-First: Zhe
Author-X-Name-Last: Yuan
Author-Name: Yuqian Shi
Author-X-Name-First: Yuqian
Author-X-Name-Last: Shi
Title: Delivery network design of a locker-drone delivery system
Abstract: 
 Drones are increasingly used for last-mile delivery due to their speed and cost-effectiveness. This study focuses on a novel locker-drone delivery system, where trucks transport parcels from the warehouse to lockers, and drones complete the final delivery. This system is ideal for community and intra-facility logistics. The research optimises the network design by determining the location of lockers, the number of drones at each locker, and the assignment of demands to lockers, minimising operating costs. Both single-parcel and multi-parcel capacity drones are examined. We build an optimisation model for each system, considering drone service capacity as a critical constraint. We design an algorithm combining average sample approximation and a genetic algorithm to address demand uncertainty. The algorithm's efficiency is validated through comparative analysis with Gurobi. Numerical experiments, using real and generated data, optimise the network design. Results show that the multi-capacity drone system requires fewer lockers and drones than the single-capacity system. Although the single-capacity system yields lower drone delivery costs, it incurs higher truck delivery costs. Additionally, a comprehensive cost analysis compares the cost-efficiency of the locker-drone system with a conventional drone delivery system, revealing the cost-saving advantage of the locker-drone system.
Journal: International Journal of Production Research
Pages: 4097-4121
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2254402
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2254402
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# input file: TPRS_A_2251602_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Huiwen Wang
Author-X-Name-First: Huiwen
Author-X-Name-Last: Wang
Author-Name: Liang Liao
Author-X-Name-First: Liang
Author-X-Name-Last: Liao
Author-Name: Wen Yi
Author-X-Name-First: Wen
Author-X-Name-Last: Yi
Author-Name: Lu Zhen
Author-X-Name-First: Lu
Author-X-Name-Last: Zhen
Title: Transportation scheduling for modules used in modular integrated construction
Abstract: 
 Modular integrated construction (MiC) is an innovative construction method that is widely used in practice, but high transportation cost is an obstacle to its wider implementation. This paper is motivated by the real-world need for a scientific approach for MiC transport scheduling, and addresses the practical problem of how to achieve on-time door-to-door MiC delivery in an economical manner. An innovative integer programming model is formulated with the objective of minimising the total transportation costs, including trailer rental, fuel costs, and worker salaries. A case study based on Hong Kong data validates that the developed model can be efficiently solved for problems of practical size. The results also demonstrate that the derived MiC schedule plan can reduce transportation costs by 58.7% compared with a just-in-time (JIT) strategy, thus bringing great economic benefits to off-site construction practitioners. Useful managerial implications related to on-site MiC storage areas are derived through sensitivity analysis. Overall, this paper sets the ground for the application of mathematical programming methodology to the off-site construction field. Future research may be devoted to MiC transport scheduling under uncertainty.
Journal: International Journal of Production Research
Pages: 3918-3931
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2251602
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2251602
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# input file: TPRS_A_2253311_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Mohammad Rohaninejad
Author-X-Name-First: Mohammad
Author-X-Name-Last: Rohaninejad
Author-Name: Behdin Vahedi-Nouri
Author-X-Name-First: Behdin
Author-X-Name-Last: Vahedi-Nouri
Author-Name: Zdeněk Hanzálek
Author-X-Name-First: Zdeněk
Author-X-Name-Last: Hanzálek
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Title: An integrated lot-sizing and scheduling problem in a reconfigurable manufacturing system under workforce constraints
Abstract: 
 Nowadays, achieving higher levels of flexibility in manufacturing systems is necessary to maintain and enhance competitiveness. Accordingly, a new generation of production machine, namely Reconfigurable Machine Tool (RMT), has recently been introduced that can be effectively adapted to changes. Nevertheless, such systems are more worker-reliant, and neglecting workforce aspects results in suboptimal or even infeasible production schedules. In this regard, this study investigates an integrated lot-sizing and scheduling problem benefiting from RMTs under workforce constraints. First, a novel Mixed-Integer Linear Programming (MILP) model is provided to formulate the problem. Afterward, to confront the high complexity of the problem, an efficient Decomposition Heuristic (DH) empowered by a tailored feasibility cut is devised. A combination of MILP and Constraint Programming (CP) is employed in the DH to model the relevant master and sub-problems, respectively. Finally, the performance of the DH compared to the MILP model and an extended lower bound is evaluated. Moreover, the advantages of utilizing RMTs in the system are explored based on four defined key performance indicators.
Journal: International Journal of Production Research
Pages: 3994-4013
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2253311
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2253311
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# input file: TPRS_A_2252526_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Ashkan Amirnia
Author-X-Name-First: Ashkan
Author-X-Name-Last: Amirnia
Author-Name: Samira Keivanpour
Author-X-Name-First: Samira
Author-X-Name-Last: Keivanpour
Title: A context-aware real-time human-robot collaborating reinforcement learning-based disassembly planning model under uncertainty
Abstract: 
 Herein, we present a real-time multi-agent deep reinforcement learning model as a disassembly planning framework for human–robot collaboration. This disassembly plan optimises sequences to minimise operation time and the disassembling costs of end-of-life (EoL) products. Combining different data-driven decision-making tools, the plan aims to handle the complexities and uncertainties of disassembly tasks. Based on the physical features and geometric limitations of EoL product components, we calculate product disassembly difficulty scores. Subsequently, the deep reinforcement learning model integrates these scores into planning process. The model allocates tasks in real time according to the online conditions of the human operator, cobot, and product, enabling the model to cope with uncertainties that may change the process routine. We also present different scenarios wherein a cobot collaborates with human operators with different skill levels. To evaluate model performance, we compare it with baseline models in terms of the convergence time and incorporated disassembly features. The analysis indicates that our model converges three times faster than a baseline model applied to the same case study. Moreover, our model includes more features of the disassembly problem in its decision-making process than any other baseline model.
Journal: International Journal of Production Research
Pages: 3972-3993
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2252526
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2252526
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# input file: TPRS_A_2251060_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Max Helm
Author-X-Name-First: Max
Author-X-Name-Last: Helm
Author-Name: Alexandra Malikova
Author-X-Name-First: Alexandra
Author-X-Name-Last: Malikova
Author-Name: Joakim Kembro
Author-X-Name-First: Joakim
Author-X-Name-Last: Kembro
Title: Rooting out the root causes of order fulfilment errors: a multiple case study
Abstract: 
 While recent technological advancements have enabled improved performance in warehouse operations, companies still struggle with eliminating errors such as incorrect/damaged items or the wrong quantity sent to customers. Such errors result in inefficient resource use, costly returns handling, and customer dissatisfaction. Despite the importance of errors, current knowledge of the underlying causes is limited. This paper addresses the gap by investigating error causes through a relatively new technology – intelligent video analysis (IVA), an additional tool for analysing warehouse operations. A multiple case study involving companies that have implemented IVA in their outbound warehouse operations (i.e. order picking, packing, and sorting) was conducted. This study is the first to investigate implementations of IVA, offering novel empirical insights into error root causes. It shows how many errors reported by customers are actually not made by humans in outbound warehouse operations but are attributable to faulty customer claims, inbound warehouse operation errors, and malfunctioning technology. This study offers interesting insights into the interaction of various technical, organisational, and human factors, thereby contributing to the literature on sociotechnical systems and the human-centric Industry 5.0. Finally, the study outlines a way forward for managers to address and further reduce errors occurring in warehouse operations.
Journal: International Journal of Production Research
Pages: 3853-3871
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2251060
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2251060
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# input file: TPRS_A_2253328_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Dmitry Ivanov
Author-X-Name-First: Dmitry
Author-X-Name-Last: Ivanov
Title: Two views of supply chain resilience
Abstract: 
 The purpose of this paper is to explore adaptation-based and stability-based views of supply chain resilience to analyse what insights these different perspectives, individually and collectively, offer for theory and practice. In the stability-based view, resilience is triggered by disruptions and performance deviations to return to some ‘normal’ states. This view accounts for known-known uncertainty. The adaptation-based view shifts the focus from avoiding oscillations and recovering some stable states toward proactive adaptation and performance persistence. The adaptation-based view aims at designing structurally adaptable networks with process flexibility and actively used redundancy. It considers resilience from the value-creation perspective accounting for unknown-unknown uncertainties. Stability-based approach views resilience as an outcome or quantity. Adaptation-based approach considers resilience as a property or quality. A combination of stability- and adaptation-based approaches is imperative for building a strong supply chain immunity through an integration of general protection and adaptability. These approaches complement each other depending on the knowledge of and attitude to uncertainty by decision-makers. A combination of the two views helps consider resilience both as a quantity to measure how sick the supply chain is and to understand how the resilience comes about to ensure the quality of the network health and viability.
Journal: International Journal of Production Research
Pages: 4031-4045
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2253328
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2253328
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# input file: TPRS_A_2250009_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Dóra Longauer
Author-X-Name-First: Dóra
Author-X-Name-Last: Longauer
Author-Name: Tamás Vasvári
Author-X-Name-First: Tamás
Author-X-Name-Last: Vasvári
Author-Name: Zsuzsanna Hauck
Author-X-Name-First: Zsuzsanna
Author-X-Name-Last: Hauck
Title: Investigating make-or-buy decisions and the impact of learning-by-doing in the semiconductor industry
Abstract: 
 Learning-by-doing is an important concept in economics as it is one of the main driving forces of economic progress. However, corporate learning is a slow process, so outsourcing manufacturing can override the long-term benefits of accumulating productivity knowledge. Semiconductor industry is also strongly featured by the learning effect, however, due to high capital requirements of building fabs, there are companies that fully outsource, while others try to keep production in-house. The chosen business model now gets further importance due to bottlenecks and supply issues perceived in the industry since the COVID-19 outbreak. Accordingly, we model the make-or-buy decision problem of a firm that decides on the optimal mix of outsourcing and in-house production, considering productivity gain via learning-by-doing and the economic impact of resilience. By presenting numerical simulations, we aim to capture the pre-pandemic and the current state of the semiconductor industry. Our model highlights that tendencies of being fabless were reasonable in the past. Although recent industry conditions have made in-house production more beneficial, this optimal strategy may be fragile due to changes of relative production costs or the extent of economic impact of chip shortages, which may underline the relevance of government incentives aiming to revitalise semiconductor industry.
Journal: International Journal of Production Research
Pages: 3835-3852
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2250009
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# input file: TPRS_A_2250008_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yoshinori Suzuki
Author-X-Name-First: Yoshinori
Author-X-Name-Last: Suzuki
Author-Name: Meltem Denizel
Author-X-Name-First: Meltem
Author-X-Name-Last: Denizel
Title: An efficient system of incentivizing truck drivers to accept night loads
Abstract: 
 Night deliveries are increasingly used by motor carriers to cut costs, but many carriers struggle to secure night truck drivers because many drivers dislike night driving. Monetary incentives are offered to drivers to accept night loads, but the incentive system currently used in practice is inefficient, as it not only pays more incentives than necessary but also does not incentivize the right drivers, both of which increase costs. This paper develops a new incentive system that allows carriers to secure night drivers at lower costs. Based on the interviews conducted with seven motor carriers, as well as the analysis of large night delivery data, we propose a bi-level programming approach that (1) generates a unique incentive for each driver based on his/her night driving performance, and (2) implicitly aligns the incentive paid to each driver with his/her reservation price. Simulation experiments conducted with real-world data showed that by using our approach carriers can not only avoid over-incentivizing drivers, but also (1) incentive only the right set of drivers who can bring cost savings and (2) encourage other drivers to improve night driving. Results also showed that our approach may give cost savings of up to 2.5% over the current system.
Journal: International Journal of Production Research
Pages: 3819-3834
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2250008
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2250008
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# input file: TPRS_A_2254405_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yun Dong
Author-X-Name-First: Yun
Author-X-Name-Last: Dong
Author-Name: Xiangling Zhao
Author-X-Name-First: Xiangling
Author-X-Name-Last: Zhao
Title: Multiobjective analytical evolutionary algorithm for train stowage planning problem of steel industry
Abstract: 
 The train stowage planning problem (TSPP) of the steel industry aims to select steel coils and allocate them to trains cost-effectively. It is a key component in the transportation of steel products. This study focuses on a multiobjective train stowage planning problem (MoTSPP) that maximises both the loading efficiency of the crane and the loading rate of the train. The MoTSPP also considers operation constraints related to steel coils, train wagons, and stowage modes in real-life railway transportation. An integer programming model is established to mathematically describe this problem. To obtain an efficient solution, a multiobjective analytical evolutionary algorithm (MAEA) that combines evolutionary algorithm (EA) with machine learning (ML) is presented. The EA part is a multiobjective differential evolution that introduces guided evolution and parameter adaptation to produce promising individuals and parameters, respectively. ML part adopts clustering algorithm and surrogate model to accelerate the search. Extensive comparisons and insight analyses are conducted from various perspectives to demonstrate the effectiveness and efficiency of the MAEA for solving the MoTSPP.
Journal: International Journal of Production Research
Pages: 4122-4142
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2254405
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2254405
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# input file: TPRS_A_2252523_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yuting Wu
Author-X-Name-First: Yuting
Author-X-Name-Last: Wu
Author-Name: Ling Wang
Author-X-Name-First: Ling
Author-X-Name-Last: Wang
Author-Name: Jing-fang Chen
Author-X-Name-First: Jing-fang
Author-X-Name-Last: Chen
Author-Name: Jie Zheng
Author-X-Name-First: Jie
Author-X-Name-Last: Zheng
Author-Name: Zixiao Pan
Author-X-Name-First: Zixiao
Author-X-Name-Last: Pan
Title: A reinforcement learning driven two-stage evolutionary optimisation for hybrid seru system scheduling with worker transfer
Abstract: 
 As a new production pattern, the hybrid seru system (HSS) originated from the actual production scenario. In the HSS, the implementation of the worker transfer strategy can further enhance the system's flexibility but is rarely studied at present. In this paper, we develop a reinforcement learning driven two-stage evolutionary algorithm (RL-TEA) to address the hybrid seru system scheduling problem with worker transfer (HSSSP-WT). To conquer this complex problem, the HSSSP-WT is divided into worker assignment-related subproblems (WS) and batch scheduling-related subproblems (BS) according to the problem characteristics. To effectively solve the subproblems, a probability model-based exploration and a lower bound-guided heuristic are presented for the WS, and a greedy search is designed for the BS. Meanwhile, to improve search efficiency and effectiveness, a knowledge-based selection mechanism is proposed to determine which subproblem group to optimise in each generation by fusing a reinforcement learning technique and a lower bound filtering strategy. Moreover, an elite enhancement strategy inspired by the problem property is designed to improve the solution quality. Experimental results demonstrate the effectiveness of the worker transfer strategy and the superior performance of the RL-TEA compared with the state-of-the-art algorithms in solving the HSSSP-WT.
Journal: International Journal of Production Research
Pages: 3952-3971
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2252523
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2252523
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# input file: TPRS_A_2253326_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xiaohan Wang
Author-X-Name-First: Xiaohan
Author-X-Name-Last: Wang
Author-Name: Lin Zhang
Author-X-Name-First: Lin
Author-X-Name-Last: Zhang
Author-Name: Yongkui Liu
Author-X-Name-First: Yongkui
Author-X-Name-Last: Liu
Author-Name: Yuanjun Laili
Author-X-Name-First: Yuanjun
Author-X-Name-Last: Laili
Title: An improved deep reinforcement learning-based scheduling approach for dynamic task scheduling in cloud manufacturing
Abstract: 
 Dynamic task scheduling problem in cloud manufacturing (CMfg) is always challenging because of changing manufacturing requirements and services. To make instant decisions for task requirements, deep reinforcement learning-based (DRL-based) methods have been broadly applied to learn the scheduling policies of service providers. However, the current DRL-based scheduling methods struggle to fine-tune a pre-trained policy effectively. The resulting training from scratch takes more time and may easily overfit the environment. Additionally, most DRL-based methods with uneven action distribution and inefficient output masks largely reduce the training efficiency, thus degrading the solution quality. To this end, this paper proposes an improved DRL-based approach for dynamic task scheduling in CMfg. First, the paper uncovers the causes behind the inadequate fine-tuning ability and low training efficiency observed in existing DRL-based scheduling methods. Subsequently, a novel approach is proposed to address these issues by updating the scheduling policy while considering the distribution distance between the pre-training dataset and the in-training policy. Uncertainty weights are introduced to the loss function, and the output mask is extended to the updating procedures. Numerical experiments on thirty actual scheduling instances validate that the solution quality and generalization of the proposed approach surpass other DRL-based methods at most by 32.8% and 28.6%, respectively. Additionally, our method can effectively fine-tune a pre-trained scheduling policy, resulting in an average reward increase of up to 23.8%.
Journal: International Journal of Production Research
Pages: 4014-4030
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2253326
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2253326
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# input file: TPRS_A_2254406_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Mohamed-Larbi Rebaiaia
Author-X-Name-First: Mohamed-Larbi
Author-X-Name-Last: Rebaiaia
Author-Name: Daoud Ait-Kadi
Author-X-Name-First: Daoud
Author-X-Name-Last: Ait-Kadi
Title: A new integrated strategy for optimising the maintenance cost of complex systems using reliability importance measures
Abstract: 
 With the aging of production systems, failure modes become more common resulting in additional maintenance costs. To reduce these costs excess, flexible and smart maintenance strategies should be considered. This article proposes an integrated condition-based maintenance method associating opportunistic and importance measure concepts (IMC). The objective of an IMC-based model is to determine the contribution of the system’s components according to their criticality degree for reliability improvement and maintenance planning. The identification of the best maintenance planning consists of determining the expected minimal cost that guarantees the repair actions of a group of critical components in one shot. Therefore, determining IMC values is not so easy for complex systems, it requires knowing their operational structure, the determination of the reliability value of each configuration and finally calculating each component's IMC degree and ranking them for the prioritisation selection. For testing the proposed method, an industrial case study has been used, regarding a complex system whose components fail at random times. The system undergoes minimal repairs if one or more components fail accidentally or by decision after inspection actions. The numerical results show that the developed approach incurs minimal maintenance costs, and can be integrated as a decision-aid solution for manufacturers.
Journal: International Journal of Production Research
Pages: 4143-4164
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2254406
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# input file: TPRS_A_2252108_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Likun Wang
Author-X-Name-First: Likun
Author-X-Name-Last: Wang
Author-Name: Zi Wang
Author-X-Name-First: Zi
Author-X-Name-Last: Wang
Author-Name: Peter Kendall
Author-X-Name-First: Peter
Author-X-Name-Last: Kendall
Author-Name: Kevin Gumma
Author-X-Name-First: Kevin
Author-X-Name-Last: Gumma
Author-Name: Alison Turner
Author-X-Name-First: Alison
Author-X-Name-Last: Turner
Author-Name: Svetan Ratchev
Author-X-Name-First: Svetan
Author-X-Name-Last: Ratchev
Title: Digital-twin deep dynamic camera position optimisation for the V-STARS photogrammetry system based on 3D reconstruction
Abstract: 
 Photogrammetry systems are widely used in industrial manufacturing applications as an assistance measurement tool. Not only does it provide high-precision feedback for assembly process inspection and product quality assessment, but also it can improve the flexibility and robustness of manufacturing systems and production lines. However, with growing global competition and demands, companies are forced to enhance production efficiency, shorten production lifecycle and increase product variety by incorporating reconfigurable factory design that can meet challenging timeline and requirements. Although dynamic facility layout is widely investigated, the position selection for the photogrammetry system in dynamic manufacturing environment is usually overlooked. In this paper, dynamic layout of the V-STARS photogrammetry system is investigated and optimised in a digital-twin environment using deep reinforcement learning. The learning objectives are derived from the field of view (FoV) evaluation from point clouds 3D reconstruction, and collision detection from the digital twin simulated in Visual Components. The application feasibility of the proposed dynamic layout optimisation of the V-STARS photogrammetry system is verified with a real world industrial application.
Journal: International Journal of Production Research
Pages: 3932-3951
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2252108
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# input file: TPRS_A_2254851_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Julia Miyaoka
Author-X-Name-First: Julia
Author-X-Name-Last: Miyaoka
Author-Name: Katy S. Azoury
Author-X-Name-First: Katy S.
Author-X-Name-Last: Azoury
Title: Optimal and simple approximate solutions to a production-inventory system with two production rates
Abstract: 
 We consider a production-inventory system in which the facility produces continuously, switching between two production rates: one faster and one slower than the average demand rate. Demand follows a compound Poisson process, and the size of each demand request is an exponential random variable. Unsatisfied demand is backordered. The production-inventory system is controlled by a two-critical number policy 
 $ \left ( r,R\right ) $ (r,R), whereby production switches from the slower rate to the faster rate when inventory drops below level r and from the faster rate to the slower rate when inventory reaches level R. A fixed cost occurs whenever production switches rates. Our analysis covers two cases: 
 $ r\geq 0 $ r≥0 and the less studied case of 
 $ r\leq 0. $ r≤0. We use a level crossing approach to derive the steady-state distribution of the inventory level. Using the steady-state distribution of the inventory level, we calculate the total expected inventory holding, backorder, and switchover costs for each of the two cases. We outline how to obtain the optimal policy through a search of the expected cost functions. We also propose heuristics that give simple closed-form solutions with near-optimal performance. Through a numerical study, we illustrate the importance of considering the 
 $ r\leq ~0 $ r≤ 0 case.
Journal: International Journal of Production Research
Pages: 4165-4180
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2254851
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2254851
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# input file: TPRS_A_2253475_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Thi-Thu-Tam Nguyen
Author-X-Name-First: Thi-Thu-Tam
Author-X-Name-Last: Nguyen
Author-Name: Adnane Cabani
Author-X-Name-First: Adnane
Author-X-Name-Last: Cabani
Author-Name: Iyadh Cabani
Author-X-Name-First: Iyadh
Author-X-Name-Last: Cabani
Author-Name: Koen De Turck
Author-X-Name-First: Koen
Author-X-Name-Last: De Turck
Author-Name: Michel Kieffer
Author-X-Name-First: Michel
Author-X-Name-Last: Kieffer
Title: Load prediction of parcel pick-up points: model-driven vs data-driven approaches
Abstract: 
 Pick-Up Points (PUPs) represent an alternative delivery option for online purchases. Parcels are delivered at a reduced cost to PUPs and wait until being picked up by customers or returned to the original warehouse if their sojourn time is over. When the chosen PUP is overloaded, the parcel may be refused and delivered to the next available PUP on the carrier tour. This paper presents and compares forecasting approaches for the load of a PUP to help PUP management companies balance delivery flows and reduce PUP overload. The parcel life-cycle has been taken into account in the forecasting process via models of the flow of parcel orders, the parcel delivery delays, and the pick-up process. Model-driven and data-driven approaches are compared in terms of load-prediction accuracy. For the considered example, the best approach (which makes use of the relationship of the load with the delivery and pick-up processes) is able to predict the load up to 4 days ahead with mean absolute errors ranging from 3.16 parcels (1 day ahead) to 8.51 parcels (4 days ahead) for a PUP with an average load of 45 parcels.
Journal: International Journal of Production Research
Pages: 4046-4075
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2253475
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2253475
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# input file: TPRS_A_2253925_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Chengshuai Li
Author-X-Name-First: Chengshuai
Author-X-Name-Last: Li
Author-Name: Yuyan Han
Author-X-Name-First: Yuyan
Author-X-Name-Last: Han
Author-Name: Biao Zhang
Author-X-Name-First: Biao
Author-X-Name-Last: Zhang
Author-Name: Yuting Wang
Author-X-Name-First: Yuting
Author-X-Name-Last: Wang
Author-Name: Junqing Li
Author-X-Name-First: Junqing
Author-X-Name-Last: Li
Author-Name: Kaizhou Gao
Author-X-Name-First: Kaizhou
Author-X-Name-Last: Gao
Title: A novel collaborative iterative greedy algorithm for hybrid flowshop scheduling problem with batch processing machines and variable sublots
Abstract: 
 Lot streaming technology enables continuous overlapping operations, which is of great significance in shortening production cycles, reducing unnecessary waiting time, and increasing production capacity. However, the capacity constraint of batch processing machines may lead to inevitable variations in sublots. Therefore, the key focus of our research is to control variations of sublot for maximising benefits. In view of this, we investigate a hybrid flowshop scheduling problem (HFSP) with batch processing machines and variable sublots (HFSP-BVS) integrating sequence-dependent setup times and transportation times. To address HFSP-BVS, a MILP model is first established, and a novel collaborative iterative greedy (NCIG) algorithm is proposed to optimise the cumulative payoffs associated with delivery dates. In NCIG, a collaborative initialisation method by extracting good information from an archive is proposed, and a specific destruction-reconfiguration strategy is designed to control the variations of sublots in the batch processing stage. Furthermore, a dynamic acceptance criterion is designed to balance the algorithm's exploitation and exploration capabilities. Lastly, we conduct comparisons between the NCIG algorithm and five other metaheuristic algorithms on 100 test instances. The results show that NCIG outperforms them by 1.89% and 61.42% on average in terms of the total penalty and RPI values, respectively.
Journal: International Journal of Production Research
Pages: 4076-4096
Issue: 11
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2253925
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# input file: TPRS_A_2266765_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Marc Füchtenhans
Author-X-Name-First: Marc
Author-X-Name-Last: Füchtenhans
Author-Name: Christoph H. Glock
Author-X-Name-First: Christoph H.
Author-X-Name-Last: Glock
Title: The impact of incentive-based programmes on job-shop scheduling with variable machine speeds
Abstract: 
 Given the high demand for energy in the manufacturing industry and the increasing use of renewable but volatile energy sources, it becomes increasingly important to coordinate production and energy availability. With the help of incentive-based programmes, grid operators can incentivise consumers to adjust power demand in critical situations such that grid stability is not threatened. On the consumer side, energy-efficient scheduling models can be used to make energy consumption more flexible. This paper proposes a bi-objective job-shop scheduling problem with variable machine speeds that aims on minimising the total energy consumption and total weighted tardiness simultaneously. We use a genetic algorithm to solve the model and derive Pareto frontiers to analyse the trade-off between both conflicting objectives. We gain insights into how incentive-based programmes can be integrated into machine scheduling models and analyse the potential interdependencies and benefits that result from this integration.
Journal: International Journal of Production Research
Pages: 4546-4564
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2266765
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2266765
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# input file: TPRS_A_2254858_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Fuqing Zhao
Author-X-Name-First: Fuqing
Author-X-Name-Last: Zhao
Author-Name: Hui Zhang
Author-X-Name-First: Hui
Author-X-Name-Last: Zhang
Author-Name: Ling Wang
Author-X-Name-First: Ling
Author-X-Name-Last: Wang
Author-Name: Tianpeng Xu
Author-X-Name-First: Tianpeng
Author-X-Name-Last: Xu
Author-Name: Ningning Zhu
Author-X-Name-First: Ningning
Author-X-Name-Last: Zhu
Author-Name: Jonrinaldi Jonrinaldi
Author-X-Name-First: Jonrinaldi
Author-X-Name-Last: Jonrinaldi
Title: A multi-objective discrete differential evolution algorithm for energy-efficient distributed blocking flow shop scheduling problem
Abstract: 
 The energy problem in green manufacturing has attracted enormous attention from researchers and practitioners in the manufacturing domain with the global energy crisis and the aggravation of environmental pollution. The distributed blocking flow shop scheduling problem (DBFSP) has considerable application scenarios in connection with its widespread application in the industry under the background of intelligent manufacturing. A multi-objective discrete differential evolution (MODE) algorithm is proposed to solve the energy-efficient distributed blocking flow shop scheduling problem (EEDBFSP) with the objectives of the makespan and total energy consumption (TEC) in this paper. The cooperative initialisation strategy is proposed to generate the initial population of the EEDBFSP. The mutation, crossover, and selection operators are redesigned to enable the MODE algorithm as applied to discrete space. A local search strategy based on the knowledge of five operators is introduced to enhance the exploitation capability of the MODE algorithm in the EEDBFSP. The non-critical path energy-efficient strategy is proposed to reduce energy consumption according to the specific constraints in the EEDBFSP. The effectiveness of each strategy in the MODE algorithm is verified and compared with the state-of-the-art algorithms. The numerical results demonstrate that the MODE algorithm is the efficient optimiser for solving the EEDBFSP.
Journal: International Journal of Production Research
Pages: 4226-4244
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2254858
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# input file: TPRS_A_2262051_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Timur Narbaev
Author-X-Name-First: Timur
Author-X-Name-Last: Narbaev
Author-Name: Öncü Hazir
Author-X-Name-First: Öncü
Author-X-Name-Last: Hazir
Author-Name: Balzhan Khamitova
Author-X-Name-First: Balzhan
Author-X-Name-Last: Khamitova
Author-Name: Sayazhan Talgat
Author-X-Name-First: Sayazhan
Author-X-Name-Last: Talgat
Title: A machine learning study to improve the reliability of project cost estimates
Abstract: 
 Project managers need reliable predictive analytics tools to make effective project intervention decisions throughout the project life cycle. This study uses Machine learning (ML) to enhance the reliability in project cost forecasting. A XGBoost forecasting model is developed and computational experiments are conducted using real data of 110 projects representing 1268 cost data points. The developed model performs better than some Earned value management (EVM), ML (Random forest, Support vector regression, LightGBM, and CatBoost), and non-linear growth (Gompertz and Logistic) models. The model produces more accurate estimates at the early, middle, and late stages of the project execution, allowing for early warning signals for more effective cost control. In addition, it shows more accurate estimates in most projects tested, suggesting consistency when repeatedly used in practice. Project forecasting studies mainly used ML to estimate the project duration; a few ML studies estimated the project cost at the project’s conceptual stage. This study uses real data and EVM metrics, proposing an effective XGBoost model for forecasting the cost throughout the project life cycle.
Journal: International Journal of Production Research
Pages: 4372-4388
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2262051
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# input file: TPRS_A_2263577_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Nilgün İnce
Author-X-Name-First: Nilgün
Author-X-Name-Last: İnce
Author-Name: Derya Deliktaş
Author-X-Name-First: Derya
Author-X-Name-Last: Deliktaş
Author-Name: İhsan Hakan Selvi
Author-X-Name-First: İhsan
Author-X-Name-Last: Hakan Selvi
Title: A comprehensive literature review of the flowshop group scheduling problems: systematic and bibliometric reviews
Abstract: 
 This paper deals with an overview of flowshop group scheduling problems in the manufacturing environment. The aim of this paper is twofold: (i) making a comprehensive survey of research on flowshop group scheduling problems in manufacturing systems, and (ii) presenting a bibliometric analysis. We address the general definition of flowshop group scheduling problems and provide a taxonomy of methodologies used in previous literature. The papers are presented from several perspectives, including the utilised objective functions, a transformation of problem structure, benchmarks in existing literature, and solution approaches. Additionally, bibliometric analysis, including keyword and journal analyses, is conducted for articles published between 1986 and 2022. Finally, suggestions for future developments are listed to further consolidate this area.
Journal: International Journal of Production Research
Pages: 4565-4594
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2263577
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2263577
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# input file: TPRS_A_2257807_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Rony Mitra
Author-X-Name-First: Rony
Author-X-Name-Last: Mitra
Author-Name: Ayush Dongre
Author-X-Name-First: Ayush
Author-X-Name-Last: Dongre
Author-Name: Piyush Dangare
Author-X-Name-First: Piyush
Author-X-Name-Last: Dangare
Author-Name: Adrijit Goswami
Author-X-Name-First: Adrijit
Author-X-Name-Last: Goswami
Author-Name: Manoj Kumar Tiwari
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Tiwari
Title: Knowledge graph driven credit risk assessment for micro, small and medium-sized enterprises
Abstract: 
 Micro, Small, and Medium-sized Enterprises (MSMEs) are essential for the growth and development of the country's economy, as they create jobs, generate income, and foster production and innovation. In recent years, credit risk assessment (CRA) has been an essential process used by financial institutions to evaluate the creditworthiness of MSMEs and determine the likelihood of default. Traditionally, CRA has relied on credit scores and financial statements, but with the advent of machine learning (ML) algorithms, lenders have a new tool at their disposal. By and large, ML algorithms are designed to classify borrowers based on their credit history and transactional data while leveraging the entity relationship involved in credit transactions. This study introduces an innovative knowledge graph-driven credit risk assessment model (RGCN-RF) based on the Relational Graph Convolutional Network (RGCN) and Random Forest (RF) algorithm. RGCN is employed to identify topological structures and relationships, which is currently nascent in traditional credit risk assessment methods. RF categorises MSMEs based on the enterprise embedding vector generated from RGCN. Extensive experimentation is conducted to assess model performance utilising the Indian MSMEs database. The balanced accuracy of 92% obtained using the RGCN-RF model demonstrates a considerable advancement over prior techniques in identifying risk-free enterprises.
Journal: International Journal of Production Research
Pages: 4273-4289
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2257807
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2257807
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# input file: TPRS_A_2254854_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Jiarui Xie
Author-X-Name-First: Jiarui
Author-X-Name-Last: Xie
Author-Name: Chonghui Zhang
Author-X-Name-First: Chonghui
Author-X-Name-Last: Zhang
Author-Name: Manuel Sage
Author-X-Name-First: Manuel
Author-X-Name-Last: Sage
Author-Name: Mutahar Safdar
Author-X-Name-First: Mutahar
Author-X-Name-Last: Safdar
Author-Name: Yaoyao Fiona Zhao
Author-X-Name-First: Yaoyao Fiona
Author-X-Name-Last: Zhao
Title: A sequential cross-product knowledge accumulation, extraction and transfer framework for machine learning-based production process modelling
Abstract: 
 Machine learning is a promising method to model production processes and predict product quality. It is challenging to accurately model complex systems due to data scarcity, as mass customisation leads to various high-variety low-volume products. This study conceptualised knowledge accumulation, extraction, and transfer (KAET) to exploit the knowledge embedded in similar entities to address data scarcity. A sequential cross-product KAET (SeqTrans) is proposed to conduct KAET, integrating data preparation and preprocessing, feature selection (FS), feature learning (FL), and transfer learning (TL). The FS and FL modules conduct knowledge extraction and help address various practical challenges such as changing operating conditions and unbalanced datasets. In this paper, sequential TL is introduced to production modelling to conduct knowledge transfer among multiple entities. The first case study of auxetic material performance prediction demonstrates the effectiveness of sequential TL. Compared with conventional TL, sequential TL can achieve the same test mean square errors with 300 fewer training examples when facing data scarcity. In the second case study, balancing anomaly detection models were constructed for two gas turbines in the same series using real-world production data. With SeqTrans, the F1-score of the anomaly detection model of the data-poor engine was improved from 0.769 to 0.909.
Journal: International Journal of Production Research
Pages: 4181-4201
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2254854
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# input file: TPRS_A_2258237_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Julian Baals
Author-X-Name-First: Julian
Author-X-Name-Last: Baals
Title: Environmental aspects in supplier networks-a bi-objective just-in-time truck routing problem
Abstract: 
 Freight transportation, including just-in-time (JIT) supplier networks, accounts for a substantial part of the global carbon dioxide (CO
 $ _2 $ 2) emissions. The JIT truck routing problem (TRP-JIT) presented in the recent literature consists of several suppliers serving a single original equipment manufacturer (OEM). A logistics provider organises the milk-run routes. The shipments are available after their release dates at the suppliers and should be delivered on their due dates at the OEM with minimal total earliness-tardiness penalties (first objective). Unlike previous research on the TRP-JIT, we focus on its environmental impact: (1) We include the weight-distance (second objective), depending on the truck's curb weight, the load, and the transportation distance. (2) We adapt a state-of-the-art large neighbourhood search (LNS) from the literature considering both objectives. (3) The LNS is embedded in bi-criterial frameworks, i.e. ε-constraint and weighted sum methods. Thereby, we estimate Pareto frontiers with at least 60 solutions in less than 25 min for instances with 99 shipments. From a managerial perspective, increasing the difference between the release and due dates for a better JIT performance may worsen the environmental impact. Lighter trucks can reduce the environmental costs without affecting the JIT performance, whereas a smaller fleet negatively affects both objectives.
Journal: International Journal of Production Research
Pages: 4290-4313
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2258237
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2258237
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# input file: TPRS_A_2266063_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Daoheng Zhang
Author-X-Name-First: Daoheng
Author-X-Name-Last: Zhang
Author-Name: Hasan Hüseyin Turan
Author-X-Name-First: Hasan Hüseyin
Author-X-Name-Last: Turan
Author-Name: Ruhul Sarker
Author-X-Name-First: Ruhul
Author-X-Name-Last: Sarker
Author-Name: Daryl Essam
Author-X-Name-First: Daryl
Author-X-Name-Last: Essam
Title: Integrating production, replenishment and fulfillment decisions for supply chains: a target-based robust optimisation approach
Abstract: 
 In this paper, a three-echelon supply chain problem under demand uncertainty is considered. The problem is formulated as a multiperiod two-stage stochastic optimisation model. The first stage, consisting of production and replenishment decisions, is integrated with the second stage, which comprises reactive fulfillment decisions, allowing seamless determination as demands are revealed over time. The demand in each period is characterised by an uncertainty set based on the nominal value and demand bounds. We propose a target-based robust optimisation (TRO) approach to determine the most robust planning with respect to a pre-specified cost target. The proposed TRO approach can trade off the total cost (performance) and model feasibility in the presence of demand perturbation (robustness) by fine-tuning the cost target. The robust counterpart is converted to a quadratically constrained linear programming (QCLP) problem, which can be solved by commercial solvers. Numerical experiments demonstrate that the TRO approach can outperform traditional robust optimisation methods in terms of both cost and feasibility against demand uncertainty by enabling precise adjustment of the cost target. Importantly, the TRO approach provides a flexible means to strike a balance between performance and robustness metrics, making it a valuable tool for supply chain planning under uncertain conditions.
Journal: International Journal of Production Research
Pages: 4494-4529
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2266063
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2266063
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# input file: TPRS_A_2262616_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Hanghao Cui
Author-X-Name-First: Hanghao
Author-X-Name-Last: Cui
Author-Name: Xinyu Li
Author-X-Name-First: Xinyu
Author-X-Name-Last: Li
Author-Name: Liang Gao
Author-X-Name-First: Liang
Author-X-Name-Last: Gao
Author-Name: Chunjiang Zhang
Author-X-Name-First: Chunjiang
Author-X-Name-Last: Zhang
Title: Multi-population genetic algorithm with greedy job insertion inter-factory neighbourhoods for multi-objective distributed hybrid flow-shop scheduling with unrelated-parallel machines considering tardiness
Abstract: 
 Distributed manufacturing is gradually becoming the future trend. The fierce market competition makes manufacturing companies focus on productivity and product delivery. The hybrid flow shop scheduling problem (HFSP) is common in manufacturing. Considering the difference of machines at the same stage, the multi-objective distributed hybrid flow shop scheduling problem with unrelated parallel machines (MODHFSP-UPM) is studied with minimum makespan and total tardiness. An improved multi-population genetic algorithm (IMPGA) is proposed for MODHFSP-UPM. The neighbourhood structure is essential for meta-heuristic-based solving algorithms. The greedy job insertion inter-factory neighbourhoods and corresponding move evaluation method are designed to ensure the efficiency of local search. To enhance the optimisation ability and stability of IMPGA, sub-regional coevolution among multiple populations and re-initialisation procedure based on probability sampling are designed, respectively. In computational experiments, 120 instances (including the same proportion of medium and large-scale problems) are randomly generated. The IMPGA performs best in all indicators (spread, generational distance, and inverted generational distance), significantly outperforming existing efficient algorithms for MODHFSP-UPM. Finally, the proposed method effectively solves a polyester film manufacturing case, reducing the makespan and total tardiness by 40% and 60%, respectively.
Journal: International Journal of Production Research
Pages: 4427-4445
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2262616
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2262616
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# input file: TPRS_A_2259502_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Arturo Wenzel
Author-X-Name-First: Arturo
Author-X-Name-Last: Wenzel
Author-Name: Antoine Sauré
Author-X-Name-First: Antoine
Author-X-Name-Last: Sauré
Author-Name: Alejandro Cataldo
Author-X-Name-First: Alejandro
Author-X-Name-Last: Cataldo
Author-Name: Pablo A. Rey
Author-X-Name-First: Pablo A.
Author-X-Name-Last: Rey
Author-Name: César Sánchez
Author-X-Name-First: César
Author-X-Name-Last: Sánchez
Title: An approximate dynamic programming approach to network-based scheduling of chemotherapy treatment sessions
Abstract: 
 A solution approach is proposed for the interday problem of assigning chemotherapy sessions at a network of treatment centres with the goal of increasing the cost-efficiency of system-wide capacity use. This network-based scheduling procedure is subject to the condition that both the first and last sessions of a patient's treatment protocol are administered at the same centre the patient is referred to by their oncologist. All intermediate sessions may be administered at other centres. It provides a systematic way of identifying effective multi-appointment scheduling policies that exploit the total capacity of a networked system, allowing patients to be treated at centres other than their home centre. The problem is modelled as a Markov decision process which is then solved approximately using techniques of approximate dynamic programming. The benefits of the approach are evaluated and compared through simulation with the existing manual scheduling procedures at two treatment centres in Santiago, Chile. The results suggest that the approach would obtain a 20% reduction in operating costs for the whole system and cut existing first-session waiting times by half. A key conclusion, however, is that a network-based scheduling procedure brings no real benefits if it is not implemented in conjunction with a proactive assignment policy like the one proposed in this paper.
Journal: International Journal of Production Research
Pages: 4314-4330
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2259502
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# input file: TPRS_A_2255681_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Biao Han
Author-X-Name-First: Biao
Author-X-Name-Last: Han
Author-Name: Quan-Ke Pan
Author-X-Name-First: Quan-Ke
Author-X-Name-Last: Pan
Author-Name: Liang Gao
Author-X-Name-First: Liang
Author-X-Name-Last: Gao
Title: A cooperative iterated greedy algorithm for the serial distributed permutation flowshop scheduling problem
Abstract: 
 This paper addresses a serial distributed permutation flowshop scheduling problem (SDPFSP) inspired by a printed circuit board assembly process that contains two production stages linked by a transportation stage, where the scheduling problem in each production stage can be seen as a distributed permutation flowshop scheduling problem (DPFSP). A sequence-based mixed-integer linear programming model is established. A solution representation consisting of two components, one component per stage, is presented and a makespan calculation method is given for the representation. Two suites of accelerations based on the insertion neighbourhood are proposed to reduce the computational complexity. A cooperative iterated greedy (CIG) algorithm is developed with two subloops, each of which optimises a component of the solution. A collaboration mechanism is used to conduct the collaboration of the two subloops effectively. Problem-specific operators including the NEH-based heuristics, destruction, reconstruction and three local search procedures, are designed. Extensive computational experiments and statistical analysis verify the validity of the model, the effectiveness of the proposed CIG algorithm and the superiority of the proposed CIG over the existing methods for solving the problem under consideration.
Journal: International Journal of Production Research
Pages: 4245-4272
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2255681
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2255681
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# input file: TPRS_A_2266066_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Paweł Litwin
Author-X-Name-First: Paweł
Author-X-Name-Last: Litwin
Author-Name: Dario Antonelli
Author-X-Name-First: Dario
Author-X-Name-Last: Antonelli
Author-Name: Dorota Stadnicka
Author-X-Name-First: Dorota
Author-X-Name-Last: Stadnicka
Title: Employing disabled workers in production: simulating the impact on performance and service level
Abstract: 
 Disabled people can be successfully employed in most production processes, provided that one knows how to exploit their abilities and take into account their limitations in order to give them an appropriate job. However, because the level and type of production must be constantly adapted to the needs of the market, the involvement of disabled people in the production process may also change. Additionally, people with disabilities have limitations as well as additional rights that must be considered. As a result, the organisation and planning of their work, side by side with other employees, becomes more complex. Computer simulations can be a support for organising and planning the involvement of employees with disabilities in production processes. The aim of the article is to show how simulations can facilitate the organisation of work of employees with disabilities, with the changing demand for manufactured products. The paper identifies the factors that should be considered, and then presents how the employment of disabled people can affect the operation of the production line and the commercial image of the company. The study uses a combination of System Dynamics and Discrete Event Simulations. The relevant data for the simulation were derived from a production company.
Journal: International Journal of Production Research
Pages: 4530-4545
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2266066
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2266066
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# input file: TPRS_A_2262065_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Shijuan Yang
Author-X-Name-First: Shijuan
Author-X-Name-Last: Yang
Author-Name: Jianjun Wang
Author-X-Name-First: Jianjun
Author-X-Name-Last: Wang
Author-Name: Xiaoying Cheng
Author-X-Name-First: Xiaoying
Author-X-Name-Last: Cheng
Author-Name: Jiawei Wu
Author-X-Name-First: Jiawei
Author-X-Name-Last: Wu
Author-Name: Jinpei Liu
Author-X-Name-First: Jinpei
Author-X-Name-Last: Liu
Title: Quality design based on kernel trick and Bayesian semiparametric model for multi-response processes with complex correlations
Abstract: 
 Processes or products are typically complex systems with numerous interrelated procedures and interdependent components. This results in complex relationships between responses and input factors, as well as complex nonlinear correlations among multiple responses. If the two types of complex correlations in the quality design cannot be properly dealt with, it will affect the prediction accuracy of the response surface model, as well as the accuracy and reliability of the recommended optimal solutions. In this paper, we combine kernel trick-based kernel principal component analysis, spline-based Bayesian semiparametric additive model, and normal boundary intersection-based evolutionary algorithm to address these two types of complex correlations. The effectiveness of the proposed method in modeling and optimisation is validated through a simulation study and a case study. The results show that the proposed Bayesian semiparametric additive model can better describe the process relationships compared to least squares regression, random forest regression, and support vector basis regression, and the proposed multi-objective optimisation method performs well on several indicators mentioned in the paper.
Journal: International Journal of Production Research
Pages: 4407-4426
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2262065
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2262065
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# input file: TPRS_A_2263884_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Sergio Gil-Borrás
Author-X-Name-First: Sergio
Author-X-Name-Last: Gil-Borrás
Author-Name: Eduardo G. Pardo
Author-X-Name-First: Eduardo G.
Author-X-Name-Last: Pardo
Author-Name: Ernesto Jiménez
Author-X-Name-First: Ernesto
Author-X-Name-Last: Jiménez
Author-Name: Kenneth Sörensen
Author-X-Name-First: Kenneth
Author-X-Name-Last: Sörensen
Title: The time-window strategy in the online order batching problem
Abstract: 
 When an order arrives at a warehouse it is usually assigned to a batch and a decision is made on how long to wait before assigning the batch to a picker and starting the picking tour. If the idle time of the pickers is minimised, the batch is immediately assigned, and the picking starts. Alternatively, if a time window is introduced, other orders may arrive, and more efficient batches may be formed. The method to decide how long to wait (the time-window strategy) is therefore important but, surprisingly, almost completely overlooked in the literature. In this paper, we demonstrate that this lack of attention is unwarranted, and that the time-window method significantly influences the overall warehouse performance. In the context of the online order batching problem (OOBP), we first demonstrate that the effects of different time-window strategies are independent of the methods used to solve the other subproblems of the OOBP (batching and routing). Second, we propose two new time-window strategies, compare them to existing methods, and prove that our methods outperform those in the literature under various scenarios. Finally, we show how time-window methods influence different objective functions of the OOBP when varying numbers of orders and pickers.
Journal: International Journal of Production Research
Pages: 4446-4469
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2263884
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2263884
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# input file: TPRS_A_2260495_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Giovanni Paolo Carlo Tancredi
Author-X-Name-First: Giovanni Paolo Carlo
Author-X-Name-Last: Tancredi
Author-Name: Eleonora Bottani
Author-X-Name-First: Eleonora
Author-X-Name-Last: Bottani
Author-Name: Giuseppe Vignali
Author-X-Name-First: Giuseppe
Author-X-Name-Last: Vignali
Title: Digital twin-enabled process control in the food industry: proposal of a framework based on two case studies
Abstract: 
 Nowadays many processes in the food industry are monitored in an automatic way, with the purpose of minimising the need for workforce and of ensuring the proper control of the quality and safety of the foodstuff. All the sensors share data with a centralised management unit, where often a Manufacturing Execution System collects and evaluates them. As reported in recent research, however, a further step that can be undertaken, exploiting Industry 4.0 enabling technologies, is the implementation of digital twin approaches, with the additional aim to prevent possible issues during production. In line with these considerations, this work aims at showing two different digital twin models intended for improving the control of as many real food systems. Liquid and powder fluids are taken as examples for highlighting the differences in the optimization of the two food processes, as well as for fully exploring the potential of the digital twin approach. Finally, based on the real data taken from two pilot plants, a framework for the selection of the best digital twin tool in the food sector is delineated.
Journal: International Journal of Production Research
Pages: 4331-4348
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2260495
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2260495
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# input file: TPRS_A_2265508_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Ai Zhao
Author-X-Name-First: Ai
Author-X-Name-Last: Zhao
Author-Name: Jonathan F. Bard
Author-X-Name-First: Jonathan F.
Author-X-Name-Last: Bard
Title: Batch scheduling in a multi-purpose system with machine downtime and a multi-skilled workforce
Abstract: 
 The paper presents a discrete-time mixed-integer linear programming (MILP) model for a generalised flexible job-shop scheduling problem as represented by a state-task network. The problem is characterised by reentrant flow, sequence-dependent changeover time, machine downtime, and skilled labour requirements. Two preprocessing procedures are proposed to reduce the size of the MILP model, and represent a major contribution of the research. The procedures reduce the number of assignment variables by exploiting job precedence and workforce qualifications. Machine availability for each task is determined as a function of possible start and end times, given duration, and maintenance schedule. The overall objective is to maximise the number of scheduled tasks while minimising their total finish time. Computational experiments are conducted with real and randomly generated instances. The results show that optimal solutions can be obtained for medium-size problems within a reasonable amount of time, primarily due to the use of the preprocessing procedures.
Journal: International Journal of Production Research
Pages: 4470-4493
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2265508
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2265508
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:12:p:4470-4493



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# input file: TPRS_A_2260896_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Sen Xue
Author-X-Name-First: Sen
Author-X-Name-Last: Xue
Author-Name: Chuanhou Gao
Author-X-Name-First: Chuanhou
Author-X-Name-Last: Gao
Title: Use statistical analysis to approximate integrated order batching problem
Abstract: 
 This paper highlights the tight relationship between the picking and packing processes in warehouse management and the need to consider them as an integrated problem. The study describes and models this integrated problem as a mixed-integer programming model, to optimise overall labour costs by determining the assignment of the subsets of orders, i.e. batches, for picking and packing. To address the issue of model complexity, the paper presents a statistical-based framework for generating approximate models and selecting the optimal one through examination. Based on the examination results, a pair-swapping heuristic is additionally proposed to be combined as a hybrid algorithm. Numerical experiments based on a real-world case demonstrate the effectiveness of the framework-proposed and selected hybrid algorithm by comparison with other framework-proposed approximate models, a solver, and existing heuristics. Our findings indicate that the combined usage of integrated picking and packing processes planning and the hybrid algorithm proposed and selected within the statistical-based framework can effectively reduce the cost of warehouse management.
Journal: International Journal of Production Research
Pages: 4349-4371
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2260896
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2260896
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:12:p:4349-4371



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# input file: TPRS_A_2254855_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Jing Wei Teoh
Author-X-Name-First: Jing Wei
Author-X-Name-Last: Teoh
Author-Name: Wei Lin Teoh
Author-X-Name-First: Wei Lin
Author-X-Name-Last: Teoh
Author-Name: Michael B.C. Khoo
Author-X-Name-First: Michael B.C.
Author-X-Name-Last: Khoo
Author-Name: Giovanni Celano
Author-X-Name-First: Giovanni
Author-X-Name-Last: Celano
Author-Name: Zhi Lin Chong
Author-X-Name-First: Zhi Lin
Author-X-Name-Last: Chong
Title: Optimal designs of the omnibus SPRT control chart for joint monitoring of process mean and dispersion
Abstract: 
 The vast majority of control schemes related to the sequential probability ratio test (SPRT) are designed for the purpose of monitoring only the process mean. Nonetheless, most manufacturing processes are vulnerable to external factors that cause the process mean and variability to change simultaneously. It is, therefore, crucial to consider a joint scheme for monitoring both the location and scale parameters of a production process. In this article, we develop a scheme that combines both mean and variance information in a single SPRT, known as the omnibus SPRT (OSPRT) chart. Expressions for the run-length properties of the OSPRT chart are derived by means of the Markov chain approach. We also propose optimal designs for the OSPRT chart based on two different metrics, i.e. by minimising the average time to signal and the average extra quadratic loss. Through a comprehensive analysis, this article reveals that the optimal OSPRT chart outperforms the classical 
 $ \bar{X} $ X¯-S, weighted-loss cumulative sum, absolute-value SPRT, and two maximum weighted-moving-average-type charts. The optimal OSPRT chart also has the advantage of collecting a small number of samples on average before producing a decision. Finally, the implementation of the OSPRT chart is presented with a wire bonding industrial dataset.
Journal: International Journal of Production Research
Pages: 4202-4225
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2254855
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2254855
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# input file: TPRS_A_2262053_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Su Xiu Xu
Author-X-Name-First: Su Xiu
Author-X-Name-Last: Xu
Author-Name: Yu Ning
Author-X-Name-First: Yu
Author-X-Name-Last: Ning
Author-Name: Huibing Cheng
Author-X-Name-First: Huibing
Author-X-Name-Last: Cheng
Author-Name: Abraham Zhang
Author-X-Name-First: Abraham
Author-X-Name-Last: Zhang
Author-Name: Yuan Gao
Author-X-Name-First: Yuan
Author-X-Name-Last: Gao
Author-Name: George Q. Huang
Author-X-Name-First: George Q.
Author-X-Name-Last: Huang
Title: Optimal vehicle fleet planning and collaboration under carbon neutrality: a game-theoretic perspective
Abstract: 
 This paper studies the optimal vehicle fleet planning and collaboration problem for a fuel vehicle (FV) transport service provider, a commercial electric vehicle (CEV) transport service provider, and a carbon emission treatment agency under carbon neutrality. The FV transport service provider pays a fixed fee or a portion of its sales revenue to a carbon emission treatment agency in exchange for technology to reduce its carbon emissions, and it can adopt three strategies (i.e., no emission reduction, purchasing technology for emission reduction, and entrusting a carbon emission treatment agency). We derive each party’s optimal fleet size, price, and profit in the three scenarios. Our results suggest that carbon emission reduction strategies may improve the market performance of the FV transport service provider. Then, we find no certain strategy is always preferable to another: the optimal cooperation strategy between the transport service provider and carbon emission treatment agency depends on the fixed technology fee, ratio of revenue sharing, government penalty, the transport service market potential, and consumer green preference, as well as the cost per CEV. This paper gives the transport service provider and carbon emission treatment agency a full picture of whether, when, and how to collaborate in green commerce.
Journal: International Journal of Production Research
Pages: 4389-4406
Issue: 12
Volume: 62
Year: 2024
Month: 06
X-DOI: 10.1080/00207543.2023.2262053
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2262053
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110640_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Andrea Rossi
Author-X-Name-First: Andrea
Author-X-Name-Last: Rossi
Author-Name: Gino Dini
Author-X-Name-First: Gino
Author-X-Name-Last: Dini
Title: Dynamic scheduling of FMS using a real-time genetic algorithm
Abstract: 
 The paper presents a genetic algorithm capable of generating optimised production plans in flexible manufacturing systems. The ability of the system to generate alternative plans following part-flow changes and unforeseen situations is particularly stressed (dynamic scheduling). Two contrasting objectives represented by the reduction of machine idle-times, thanks to dynamic scheduling computation and the reduction of the makespan, are taken into account by the proposed system. The key-point is the real-time response obtained by an optimised evolutionary strategy capable of minimising the number of genetic operations needed to reach the optimal schedule in complex manufacturing systems.
Journal: International Journal of Production Research
Pages: 1-20
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189545
File-URL: http://hdl.handle.net/10.1080/002075400189545
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110641_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: B. K. A. Ngoi
Author-X-Name-First: B. K. A.
Author-X-Name-Last: Ngoi
Author-Name: B.H. Lim
Author-X-Name-First: B.H.
Author-X-Name-Last: Lim
Author-Name: P.S. Ang
Author-X-Name-First: P.S.
Author-X-Name-Last: Ang
Title: Nexus method for stack analysis of geometric dimensioning and tolerancing (GDT) problems
Abstract: 
 This paper describes a method called the Nexus method used for evaluating tolerance stack problems with position, circular runout, total runout and concentricity tolerances. The method constructs a graphical representation of features termed the Nexus cell. The cell contains all the geometric information of the feature in numerical values. After each feature is represented by a Nexus cell, the cells are linked up to form the Nexus model for the part. Once the model is completed, it can be used to evaluate GDT problems associated with the part. The method is capable of arriving at accurate results when dealing with several special cases of position tolerances. Applications of the proposed method have been illustrated and possible uses of such a method were discussed.
Journal: International Journal of Production Research
Pages: 21-37
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189554
File-URL: http://hdl.handle.net/10.1080/002075400189554
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110642_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Robin G. Qiu
Author-X-Name-First: Robin G.
Author-X-Name-Last: Qiu
Author-Name: Sanjay B. Joshi
Author-X-Name-First: Sanjay B.
Author-X-Name-Last: Joshi
Title: Structured adaptive supervisory control model and software development for a flexible manufacturing system
Abstract: 
 A three-step approach is proposed to substantially reduce the high cost of development of control software for an FMS on the shop floor. First, by introducing the concept of multiple computing processes into Automata Theory, a finite capacity machine (FCM) is presented as an extended finite machine. An FCM is used to model the control of a flexible manufacturing system, which avoids the state explosion problem. Secondly, a structured adaptive supervisory control (SASC) model meeting the desired control objectives for an FMS is derived from a composed FCM. The SASC model can be constructed systematically. Finally, generic software components for an SASC model are described, which allow the SASC model to be cost-effectively transferred into shop-floor applicable control software.
Journal: International Journal of Production Research
Pages: 39-49
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189563
File-URL: http://hdl.handle.net/10.1080/002075400189563
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110643_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Aline Dumoulin
Author-X-Name-First: Aline
Author-X-Name-Last: Dumoulin
Author-Name: Carlo Vercellis
Author-X-Name-First: Carlo
Author-X-Name-Last: Vercellis
Title: Tactical models for hierarchical capacitated lot-sizing problems with setups and changeovers
Abstract: 
 In this paper, we propose a modelling approach for the medium term planning of manufacturing systems characterized by coexisting large volume and small volume products, in which changeovers play a critical role in achieving maximum efficiency. Although the model is based upon the large time bucket paradigm, it is capable of representing start-ups by sequencing the lots of items produced in long sequences. Specifically, we consider a capacitated lot-sizing problem with parallel machines, in which the products have a three-level hierarchical structure: end items are aggregated into families, which in turn are aggregated into types. Minor set-ups and major changeovers take place when switching between families within a type or between types, respectively. The resulting mathematical programming problem is decomposed via Lagrangean relaxation, leading to sub-problems that can be solved in polynomial time. The whole approach has been validated by applying it to large size case studies drawn from the textile industry.
Journal: International Journal of Production Research
Pages: 51-67
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189572
File-URL: http://hdl.handle.net/10.1080/002075400189572
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110644_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Zhiwen Zhao
Author-X-Name-First: Zhiwen
Author-X-Name-Last: Zhao
Author-Name: Luc Laperriere
Author-X-Name-First: Luc
Author-X-Name-Last: Laperriere
Title: Adaptive direct slicing of the solid model for rapid prototyping
Abstract: 
 The geometric description used to represent solid objects significantly affects the accuracy and quality of the final parts produced with rapid prototyping (RP) technology. This paper discusses the alternative method of adaptive direct slicing for RP. Direct slicing generates precise contours for each layer from the solid model and avoids an intermediate representation. Adaptive slicing modifies the layer thickness to take into account the curvature of the surface of the solid model in the vertical direction, to alleviate the staircase effect, and to decrease the number of layers. Thereby, adaptive direct slicing potentially enables part fabrication with higher accuracy and production efficiency. This paper presents a new, practical approach to adaptive direct slicing based on the area deviation ratio. The slicing strategy and algorithm are also described. The corresponding procedure was implemented and tested on Windows 95/98 and NT 4.0 with AutoCAD R14.
Journal: International Journal of Production Research
Pages: 69-83
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189581
File-URL: http://hdl.handle.net/10.1080/002075400189581
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110645_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: R. Shafaei
Author-X-Name-First: R.
Author-X-Name-Last: Shafaei
Author-Name: P. Brunn
Author-X-Name-First: P.
Author-X-Name-Last: Brunn
Title: Workshop scheduling using practical (inaccurate) data Part 3: A framework to integrate job releasing, routing and scheduling functions to create a robust predictive schedule
Abstract: 
 A comprehensive simulation study conducted by the authors investigated the robustness of a predictive scheduling system in a dynamic and stochastic environment. The results revealed that to improve the robustness of a scheduling system, besides using a robust scheduling method with a frequent rescheduling policy, the shop load should be well controlled and kept balanced. Integrating the planning and the scheduling functions has been shown to achieve this objective. This paper discusses the effects of the planning i.e. job releasing and routing and the scheduling functions in creating a robust schedule and a framework to integrate the above functions is proposed. This system consists of a planning module that is concerned with job releasing and routing decisions and a scheduling module that provides the detailed scheduling. A mathematical model using the integer programming technique is use to demonstrate a solution for the planning module. In addition, a heuristic algorithm is used to solve the scheduling problem. It is shown that, in terms of shop load balance level and job delivery time, the proposed system performs better than a benchmark loading strategy on the basis of minimum processing cost.
Journal: International Journal of Production Research
Pages: 85-99
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189590
File-URL: http://hdl.handle.net/10.1080/002075400189590
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110646_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Franco Caron
Author-X-Name-First: Franco
Author-X-Name-Last: Caron
Author-Name: Gino Marchet
Author-X-Name-First: Gino
Author-X-Name-Last: Marchet
Author-Name: Alessandro Perego
Author-X-Name-First: Alessandro
Author-X-Name-Last: Perego
Title: Optimal layout in low-level picker-to-part systems
Abstract: 
 The paper presents an analytical approach to layout design of the picking area in low-level, picker-to-part systems using COI (cube per order index)-based and random storage policies. The layout of the picking area is one of the major issues in increasing picking system productivity, i.e. in reducing the time required to complete a given set of orders, and must take account of the inter-relationship between the main operating policies, i.e. storage, routing and batching. The main system parameters affecting the layout design are the total length of the picking aisles, the number of pick stops per tour and the shape of the COI-based ABC curve. A formula that relates the optimal number of aisles to the above parameters will be presented, together with the increase in the expected tour distance stemming from the adoption of a non-optimal number of aisles. The study thus provides a comprehensive framework for layout design.
Journal: International Journal of Production Research
Pages: 101-117
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189608
File-URL: http://hdl.handle.net/10.1080/002075400189608
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# input file: TPRS_A_10110647_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Prasad K. D. V. Yarlagadda
Author-X-Name-First: Prasad K. D. V.
Author-X-Name-Last: Yarlagadda
Title: Prediction of die casting process parameters by using an artificial neural network model for zinc alloys
Abstract: 
 Pressure die casting is an important production process. In pressure die casting, the first setting of process parameters is established through guess work. Experts use their previous experience and knowledge to develop a solution for a new application. Due to rapid expansion in the die casting process to produce better quality products in a short period of time, there is ever increasing demand to replace the time-consuming and expert-reliant traditional trial and error methods of establishing process parameters. A neural network system is developed to generate the process parameters for the pressure die casting process. The system aims to replace the existing high-cost, time-consuming and expertdependent trial and error approach for determining the process parameters. The scope of this work includes analysing a physical model of the pressure die casting filling stage based on governing equations of die cavity filling and the collection of feasible casting data for the training of the network. The training data were generated by using ZN-DA3 material on a hot chamber die casting machine with a plunger diameter of 60 mm. The present network was developed using the MATLAB application toolbox. In this work, the neural network was developed by comparing three different training algorithms: i.e. error backpropagation algorithm; momentum and adaptive learning algorithm; and Levenberg-Marquardt approximation algorithm. It was found that the Levenberg-Marquardt approximation algorithm was the preferred method for this application as it reduced the sum-squared error to a small value. The accuracy of the developed network was tested by comparing the data generated from the network with those of an expert from a local die casting industry. It was established that by using this network the selection of process parameters becomes much easier, so that it can be used by a novice user without prior knowledge of the die casting process or optimization techniques.
Journal: International Journal of Production Research
Pages: 119-139
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189617
File-URL: http://hdl.handle.net/10.1080/002075400189617
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Handle: RePEc:taf:tprsxx:v:38:y:2000:i:1:p:119-139



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# input file: TPRS_A_10110648_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Hemant V. Kher
Author-X-Name-First: Hemant V.
Author-X-Name-Last: Kher
Author-Name: Manoj K. Malhotra
Author-X-Name-First: Manoj K.
Author-X-Name-Last: Malhotra
Author-Name: Daniel C. Steele
Author-X-Name-First: Daniel C.
Author-X-Name-Last: Steele
Title: The effect of push and pull lot splitting approaches on lot traceability and material handling costs in stochastic flow shop environments
Abstract: 
 This study evaluates how the procedures followed in splitting job lots on the shop floor influence both material handling and lot integrity in stochastic flow shop environments. Former work has shown that lot splitting improves flow time and customer service performance, but with an increased number of transfers along with a corresponding increase in material handling costs. Physical lot integrity, which is important to lot tracing, has not been considered in prior literature. In order to overcome these limitations and address material handling concerns better, we define a new measure of performance called the lot integrity loss exposure (LILE). We use this and other measures to show that the traditional 'push' approach that has been followed in modelling lot splitting complicates lot traceability in the shop and leads to an excessive number of transfers. As an alternative, we propose a 'pull' approach in which an order is split between any successive pair of machines only on an as-needed basis. The push and pull approaches for lot splitting are compared under a range of conditions characterized by factors such as machine utilization levels within the shop, setup-to-processing time ratios, and number of splits created in job lots. Our results indicate that relative to the push approach, pull lot splitting helps significantly in reducing the number of transfers incurred and in maintaining a greater degree of physical lot integrity. At the same time, there is no significant difference in the two approaches with respect to improvements in flow time and customer service measures. Both the degree to which lot integrity is preserved, and the extent of savings in material handling that result from using the pull approach, are shown to be most pronounced under conditions characterized by high machine utilizations rates and setup-to-processing time ratios. Managerial implications of our study along with further research directions in this area are also discussed.
Journal: International Journal of Production Research
Pages: 141-160
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189626
File-URL: http://hdl.handle.net/10.1080/002075400189626
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110649_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yohanan Arzi
Author-X-Name-First: Yohanan
Author-X-Name-Last: Arzi
Author-Name: Avi Herbon
Author-X-Name-First: Avi
Author-X-Name-Last: Herbon
Title: Machine learning based adaptive production control for a multi-cell flexible manufacturing system operating in a random environment
Abstract: 
 An adaptive production control approach is used for controlling a multi-cell FMS with machines subject to failures, operating in a highly changing produce-toorder environment. A probabilistic machine learning procedure is integrated within a two-level Distribution Production Control System (DPCS). This enables the DPCS to adapt itself to large fluctuations in demand as well as to other stochastic factors. An extensive simulation study shows that the proposed adaptive control approach significantly improves the production system performance in terms of a combined measure of throughput and order tardiness. The proposed DPCS can be easily implemented as a real-time DPCS due to its simplicity, modularity and the limited information it requires. The proposed adaptive scheme can be integrated in any parametric production control system.
Journal: International Journal of Production Research
Pages: 161-185
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189635
File-URL: http://hdl.handle.net/10.1080/002075400189635
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110650_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Ilan Gilboa
Author-X-Name-First: Ilan
Author-X-Name-Last: Gilboa
Author-Name: Yale T. Herer
Author-X-Name-First: Yale T.
Author-X-Name-Last: Herer
Author-Name: Haya Kaspi
Author-X-Name-First: Haya
Author-X-Name-Last: Kaspi
Author-Name: Tzvi Raz
Author-X-Name-First: Tzvi
Author-X-Name-Last: Raz
Title: Optimal design of the inspection buffer for an unreliable process
Abstract: 
 Placing an inspection buffer immediately after an unreliable process subject to failure protects the process customers from receiving non-conforming products. Such protection is achieved by screening the buffer contents whenever a shift in the process is detected. Previous studies have suggested that, if properly designed, such buffers can reduce overall costs. In this paper we make two types of contributions to the study of inspection buffers. First, we refine the model proposed by Klastorin et al. (1993), by incorporating a more efficient way of sampling, a more realistic objective function and more accurate cost expressions. Second, we provide analytical results to assist in the calculation of the economically optimal buffer size. Specifically, these include conditions for determining whether an inspection buffer is at all justified and a theorem for bounding the search for the optimal buffer size. The performance of the search bound and the sensitivity of the model are examined computationally.
Journal: International Journal of Production Research
Pages: 187-205
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189644
File-URL: http://hdl.handle.net/10.1080/002075400189644
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_10110651_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: R. Kolisch
Author-X-Name-First: R.
Author-X-Name-Last: Kolisch
Author-Name: K. Hess
Author-X-Name-First: K.
Author-X-Name-Last: Hess
Title: Efficient methods for scheduling make-to-order assemblies under resource, assembly area and part availability constraints
Abstract: 
 We consider the problem of scheduling multiple, large-scale, make-to-order assemblies under resource, assembly area, and part availability constraints. Such problems typically occur in the assembly of high-volume, discrete maketo-order products. Based on a list scheduling procedure proposed by Kolisch in 1999 we introduce three efficient heuristic solution methods. Namely, a biased random sampling method and two tabu search-based large-step optimization methods. The two latter methods differ in the employed neighbourhood. The first one uses a simple API-neighbourhood while the second one uses a more elaborated so-called 'critical neighbourhood' which makes use of problem insight. All three procedures are assessed on a systematically generated set of test instances. The results indicate that especially the large-step optimization method with the critical neighbourhood gives very good results which are significant better than simple single-pass list scheduling procedures.
Journal: International Journal of Production Research
Pages: 207-228
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189653
File-URL: http://hdl.handle.net/10.1080/002075400189653
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Handle: RePEc:taf:tprsxx:v:38:y:2000:i:1:p:207-228



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# input file: TPRS_A_10110652_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Y. Won
Author-X-Name-First: Y.
Author-X-Name-Last: Won
Title: New p-median approach to cell formation with alternative process plans
Abstract: 
 This paper considers the machine-part clustering under the assumption of alternative process plans for each part. Kusiak's p-median model of part family formation dealing with the problem has critical disadvantages in that the model requires too many binary variables and constraints and the number of part families must be known in advance. Furthermore, the solution quality of the model in terms of the number of exceptional elements is poor for ill-structured problems. Motivated by Viswanathan's work, this paper proposes two new p- median models using new measures of similarity between machine pairs: one with the prespecified number of cells and the other without the prespecified number of cells. Computational experience shows the applicability of new p-median models of machine cell formation over Kusiak's model.
Journal: International Journal of Production Research
Pages: 229-240
Issue: 1
Volume: 38
Year: 2000
Month: 1
X-DOI: 10.1080/002075400189662
File-URL: http://hdl.handle.net/10.1080/002075400189662
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Handle: RePEc:taf:tprsxx:v:38:y:2000:i:1:p:229-240

Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2279145_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Jing Wang
Author-X-Name-First: Jing
Author-X-Name-Last: Wang
Author-Name: Deming Lei
Author-X-Name-First: Deming
Author-X-Name-Last: Lei
Author-Name: Hongtao Tang
Author-X-Name-First: Hongtao
Author-X-Name-Last: Tang
Title: An adaptive artificial bee colony for hybrid flow shop scheduling with batch processing machines in casting process
Abstract: 
 Hybrid flow shop scheduling problem (HFSP) with real-life constraints has been extensively considered; however, HFSP with batch processing machines (BPM) at a middle stage is seldom investigated. In this study, HFSP with BPM at a middle stage in hot & cold casting process is considered and an adaptive artificial bee colony (AABC) is proposed to minimise makespan. To produce high quality solutions, an adaptive search process with employed bee phase and adaptive search step is implemented. Adaptive search step, which may be onlooker bee phase or cooperation or empty, is decided by evolution quality and an adaptive threshold. Cooperation is performed between the improved solutions of one employed bee swarm and the unimproved solutions of another swarm. Six search operators are constructed and search operator is adaptively adjusted. A new scout phase is also given. A lower bound is provided and proved. Extensive experiments are conducted. The computational results validate that new strategies such as cooperation are effective and efficient and AABC can obtain better results than methods from existing literature on the considered problem.
Journal: International Journal of Production Research
Pages: 4793-4808
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2279145
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2279145
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# input file: TPRS_A_2280998_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Omar Abbaas
Author-X-Name-First: Omar
Author-X-Name-Last: Abbaas
Author-Name: Jose A. Ventura
Author-X-Name-First: Jose A.
Author-X-Name-Last: Ventura
Title: A multi-agent resource bidding algorithm for order acceptance and assembly job shop scheduling
Abstract: 
 This study uses an agent-based approach with a combinatorial auction mechanism to solve the joint order acceptance and assembly job shop scheduling problem. A set of jobs is offered. Each job has a revenue, ready time, due date, deadline, and consists of a set of operations with precedence relationships. Jobs that deviate from their due dates incur earliness/tardiness penalties. An operation may require several units of capacity per time unit and a resource could have multiple units of capacity. The manufacturer can reject any job to satisfy the capacity constraints and maximise the overall profit. We develop a mathematical model for the problem, then use an agent-based approach to solve it. First, the relaxed problem is decomposed into a set of job-level subproblems. Each job is optimised individually without considering the capacity constraints. Profitable jobs at the individual level submit their optimal schedules as combinatorial bids to an auctioneer to acquire combinations of resource capacity-time units. Then, the auctioneer records the profit upper bound, resolves capacity conflicts to reach a feasible solution, records the profit lower bound, and updates the dual variables. Experimental results show that the proposed methodology can solve large-sized problems in reasonable CPU times.
Journal: International Journal of Production Research
Pages: 4856-4883
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2280998
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2280998
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# input file: TPRS_A_2270076_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Hu Qin
Author-X-Name-First: Hu
Author-X-Name-Last: Qin
Author-Name: Haocheng Zhuang
Author-X-Name-First: Haocheng
Author-X-Name-Last: Zhuang
Author-Name: Chunlong Yu
Author-X-Name-First: Chunlong
Author-X-Name-Last: Yu
Author-Name: Jiliu Li
Author-X-Name-First: Jiliu
Author-X-Name-Last: Li
Title: A matheuristic approach for the multi-level capacitated lot-sizing problem with substitution and backorder
Abstract: 
 The lot-sizing problem aims at determining the products to be produced and their quantities for each time period, which is a difficult problem in production planning. This problem becomes even more complicated when practical aspects such as limited production capacity, bill of materials, and item substitution are considered. In this paper, we study a new variant of the lot-sizing problem, called the multi-level capacitated lot-sizing problem with substitution and backorder. Unlike previous studies, this variant considers substitutions at both the product and component levels, which is based on the real needs of manufacturers to increase planning flexibility. Backorders are allowed, but should be delivered within a certain time limitation. We formulate this problem using a mathematical programming model. A matheuristic approach is proposed to solve the problem. This first generates an initial feasible solution using a relax-and-fix algorithm, and then improves it using a hybrid fix-and-optimise algorithm. The proposed algorithm is calibrated with a full factorial design of experiments, and its efficiency is well validated. Finally, through extensive numerical experiments, we analyse the properties of this new lot-sizing problem, such as the effect of substitution options, and the influence of backorder time limitation, and provide several useful managerial insights for manufacturing companies to save costs in production planning.
Journal: International Journal of Production Research
Pages: 4645-4673
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2270076
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2270076
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# input file: TPRS_A_2274340_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Fatima Ezzahra Achamrah
Author-X-Name-First: Fatima Ezzahra
Author-X-Name-Last: Achamrah
Author-Name: Mariam Lafkihi
Author-X-Name-First: Mariam
Author-X-Name-Last: Lafkihi
Author-Name: Eric Ballot
Author-X-Name-First: Eric
Author-X-Name-Last: Ballot
Title: A dynamic and reactive routing protocol for the physical internet network
Abstract: 
 The Physical Internet (PI) offers an innovative approach to logistics networks, focussing on operational, digital, and physical interconnectivity through encapsulation, interfaces, and protocols. However, PI network can be complex to manage due to its dynamic structure and the need for routing protocols that adapt to continually evolving circumstances. This paper proposes a dynamic and reactive routing protocol for a PI sub-network, leveraging well-known Internet techniques, namely ‘Route Request’ and ‘Route Reply’. The objective is to enable dynamic, self-starting, multi-hop routing among nodes, ensuring continuous connectivity even amidst network disruptions. Moreover, the protocol incorporates reactive assignment algorithms to address disruptions, such as product shortages and resource unavailability. Additionally, the protocol is innovative in considering each container and resource's preferences and local knowledge of the system's known state. To include preferences in decision-making, we incorporate the Technique for Order Preference by Similarity to Ideal Solution and goal programming. Finally, we use multi-agent simulation and real order data from two major French retail chains to evaluate the protocol's performance. Results showed improved routing robustness and efficiency amidst disruptions compared to state-of-the-art methods. Various scenarios have been examined to yield promising insights for future research and practical applications in the realm of the PI.
Journal: International Journal of Production Research
Pages: 4735-4753
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2274340
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2274340
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# input file: TPRS_A_2280882_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Rebaiaia Mohamed-Larbi
Author-X-Name-First: Rebaiaia
Author-X-Name-Last: Mohamed-Larbi
Author-Name: Ait-Kadi Daoud
Author-X-Name-First: Ait-Kadi
Author-X-Name-Last: Daoud
Title: Condition-based maintenance optimisation for multi-component systems using mean residual life
Abstract: 
 This paper aims to propose a Novel Condition-based maintenance (CBM) decision aid model for optimising the maintenance of complex multi-component systems. As the degradation level of each component is assumed to be independent and stochastic, it follows a specific probability distribution determined from historical data of experimental observations and inspection. The main objective is to optimise the total cost for providing maintenance actions and reducing the excess of spare parts usage. The decision support model consists of determining measurements on components with the aim of estimating the instant of time of removing predictively one or a group of components before they fail. The measurement model includes the mean residual lifetime (MRL) and some extensions developed for this purpose. For demonstrating the pertinency of the proposed model, we use a preventive maintenance strategy for one-component systems and a grouping/opportunistic maintenance for multi-component systems. Besides, a numerical comparative study performing these measurements is carried out using several examples and a case study from Electric energy distribution systems. The solution is illustrated as a decision-making optimal model for optimising the maintenance operations’ costs and the total number of spare parts. The numerical results and the comparison show the efficiency of the proposed approach.
Journal: International Journal of Production Research
Pages: 4831-4855
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2280882
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2280882
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# input file: TPRS_A_2269275_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Vladmir Polotski
Author-X-Name-First: Vladmir
Author-X-Name-Last: Polotski
Author-Name: Jean-Pierre Kenné
Author-X-Name-First: Jean-Pierre
Author-X-Name-Last: Kenné
Author-Name: Ali Gharbi
Author-X-Name-First: Ali
Author-X-Name-Last: Gharbi
Title: Estimation-based production control of manufacturing–remanufacturing systems with uncertain seasonal return and imprecise demand and inventory
Abstract: 
 Hybrid manufacturing systems utilising raw materials and returned end-of-life products for production are studied. The systems are failure-prone and subject to inventory, market demand and return uncertainties. Thanks to growing environmental and sustainability concerns, the manufacturing sector is currently experiencing a significant growth in the popularity of reverse logistics. However, the practical implementation of production control in such systems is challenging due to return flow uncertainty and variability. To address this challenge, an estimation-based control using the Kalman filter is proposed in this research. The demand and return models employed contain random and deterministic components, with the latter being time-invariant for demand and uncertain with seasonal variations for return. The processing steps used include the estimation of inventory levels and demand and return components, return forecasting allowing cost computation over a long horizon, and the determination of the production and disposal policies adapting to market variations and uncertainties. We classify the systems according to relationships between their production capacity, demand and return ranges. We then present an extensive numerical study of optimal policies for various system classes and show that adaptive policies outperform the conventional ones, thus proving the effectiveness of the proposed production control approach for complex industrially oriented systems.
Journal: International Journal of Production Research
Pages: 4595-4622
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2269275
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2269275
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# input file: TPRS_A_2275635_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Victor Delpla
Author-X-Name-First: Victor
Author-X-Name-Last: Delpla
Author-Name: Kevin Chapron
Author-X-Name-First: Kevin
Author-X-Name-Last: Chapron
Author-Name: Jean-Pierre Kenné
Author-X-Name-First: Jean-Pierre
Author-X-Name-Last: Kenné
Author-Name: Lucas A. Hof
Author-X-Name-First: Lucas A.
Author-X-Name-Last: Hof
Title: A novel approach for predicting Lockout/Tagout safety procedures for smart maintenance strategies
Abstract: 
 This article presents an approach for predicting Lockout/Tagout (LOTO) procedure sheets, which are commonly used in the manufacturing industry to prevent premature equipment restart during maintenance. The prediction problem of energetic devices to lock from machine names is regarded as a multi-task classification problem. The dataset was obtained by processing LOTO sheets in Portable Document Format (PDF). The K-Nearest Neighbours (KNN), Random Forest (RF), and Deep Neural Network (DNN) algorithms were compared for this problem. The best prediction performance was achieved with the DNN method, with top-1 accuracies exceeding 63% and top-2 accuracies exceeding 90% for all devices. The sensitivity analysis conducted on the results indicates that the approach is robust and reliable, regardless of the industrial sector considered. In other words, the approach is not significantly affected by variations in the industry or its specific characteristics. These results suggest that the proposed approach can be used to assist workers in drafting LOTO sheets, and offers strong potential for concrete applications in safety management in the era of smart manufacturing.
Journal: International Journal of Production Research
Pages: 4754-4775
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2275635
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2275635
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# input file: TPRS_A_2279130_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Ziliang Wang
Author-X-Name-First: Ziliang
Author-X-Name-Last: Wang
Author-Name: Chenhao Zhou
Author-X-Name-First: Chenhao
Author-X-Name-Last: Zhou
Author-Name: Ada Che
Author-X-Name-First: Ada
Author-X-Name-Last: Che
Author-Name: Jingkun Gao
Author-X-Name-First: Jingkun
Author-X-Name-Last: Gao
Title: A policy-based Monte Carlo tree search method for container pre-marshalling
Abstract: 
 The container pre-marshalling problem (CPMP) aims to minimise the number of reshuffling moves, ultimately achieving an optimised stacking arrangement in each bay based on the priority of containers during the non-loading phase. Given the sequential decision nature, we formulated the CPMP as a Markov decision process (MDP) model to account for the specific state and action of the reshuffling process. To address the challenge that the relocated container may trigger a chain effect on the subsequent reshuffling moves, this paper develops an improved policy-based Monte Carlo tree search (P-MCTS) to solve the CPMP, where eight composite reshuffling rules and modified upper confidence bounds are employed in the selection phases, and a well-designed heuristic algorithm is utilised in the simulation phases. Meanwhile, considering the effectiveness of reinforcement learning methods for solving the MDP model, an improved Q-learning is proposed as the compared method. Numerical results show that the P-MCTS outperforms all compared methods in scenarios where all containers have different priorities and scenarios where containers can share the same priority.
Journal: International Journal of Production Research
Pages: 4776-4792
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2279130
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2279130
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# input file: TPRS_A_2270719_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Alexandra Brintrup
Author-X-Name-First: Alexandra
Author-X-Name-Last: Brintrup
Author-Name: Edward Kosasih
Author-X-Name-First: Edward
Author-X-Name-Last: Kosasih
Author-Name: Philipp Schaffer
Author-X-Name-First: Philipp
Author-X-Name-Last: Schaffer
Author-Name: Ge Zheng
Author-X-Name-First: Ge
Author-X-Name-Last: Zheng
Author-Name: Guven Demirel
Author-X-Name-First: Guven
Author-X-Name-Last: Demirel
Author-Name: Bart L. MacCarthy
Author-X-Name-First: Bart L.
Author-X-Name-Last: MacCarthy
Title: Digital supply chain surveillance using artificial intelligence: definitions, opportunities and risks
Abstract: 
 Digital Supply Chain Surveillance (DSCS) is the proactive monitoring and analysis of digital data that allows firms to extract information related to a supply network, without the explicit consent of firms involved in the supply chain. AI has made DSCS to become easier and larger-scale, posing significant opportunities for automated detection of actors and dependencies involved in a supply chain, which in turn, can help firms to detect risky, unethical and environmentally unsustainable practices. Here, we define DSCS, review priority areas using a survey conducted in the UK. Visibility, sustainability, resilience are significant areas that DSCS can support, through a number of machine-learning approaches and predictive algorithms. Despite anecdotal narrative on the importance of explainability of algorithmic results, practitioners often prefer accuracy over explainability; however, there are significant differences between industrial sectors and application areas. Using a case study, we highlight a number of concerns on the unchecked use of AI in DSCS, such as bias or misinterpretation resulting in erroneous conclusions, which may lead to suboptimal decisions or relationship damage. Building on this, we develop and discuss a number of illustrative cases to highlight risks that practitioners should be aware of, proposing key areas of further research.
Journal: International Journal of Production Research
Pages: 4674-4695
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2270719
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2270719
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# input file: TPRS_A_2280696_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xiang Sun
Author-X-Name-First: Xiang
Author-X-Name-Last: Sun
Author-Name: Shunsheng Guo
Author-X-Name-First: Shunsheng
Author-X-Name-Last: Guo
Author-Name: Jun Guo
Author-X-Name-First: Jun
Author-X-Name-Last: Guo
Author-Name: Baigang Du
Author-X-Name-First: Baigang
Author-X-Name-Last: Du
Author-Name: Zhijie Yang
Author-X-Name-First: Zhijie
Author-X-Name-Last: Yang
Author-Name: Kaipu Wang
Author-X-Name-First: Kaipu
Author-X-Name-Last: Wang
Title: A Pareto-based hybrid genetic simulated annealing algorithm for multi-objective hybrid production line balancing problem considering disassembly and assembly
Abstract: 
 Most existing studies about line balancing problems mainly focus on disassembly and assembly separately, which rarely integrate these two modes into a system. However, as critical activities in the remanufacturing field, assembly and disassembly share many similarities, such as working tools and processing sequence. Thus, this paper proposes a multi-objective hybrid production line balancing problem with a fixed number of workstations (HPLBP-FNW) considering disassembly and assembly to optimise cycle time, total cost, and workload smoothness simultaneously. And a novel Pareto-based hybrid genetic simulated annealing algorithm (PB-HGSA) is designed to solve it. In PB-HGSA, the two-point crossover and hybrid mutation operator are proposed to produce potential non-dominated solutions (NDSs). Then, a local search method based on a parallel simulated annealing algorithm is designed for providing a depth search around the NDSs to balance the global and local search ability. Numerical results by comparing PB-HGSA with the well-known algorithms verify the effectiveness of PB-HGSA in solving HPLBP-FNW. Moreover, the managerial insights based on a case study are given to inspire enterprise companies to consider hybrid production line in the remanufacturing process, which is beneficial to reduce the cycle time and total cost and improve the service life of the equipment.
Journal: International Journal of Production Research
Pages: 4809-4830
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2280696
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2280696
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# input file: TPRS_A_2269565_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Pierre Bouquet
Author-X-Name-First: Pierre
Author-X-Name-Last: Bouquet
Author-Name: Ilya Jackson
Author-X-Name-First: Ilya
Author-X-Name-Last: Jackson
Author-Name: Mostafa Nick
Author-X-Name-First: Mostafa
Author-X-Name-Last: Nick
Author-Name: Amin Kaboli
Author-X-Name-First: Amin
Author-X-Name-Last: Kaboli
Title: AI-based forecasting for optimised solar energy management and smart grid efficiency
Abstract: 
 This paper considers two pertinent research inquiries: ‘Can an AI-based predictive framework be utilised for the optimisation of solar energy management?’ and ‘What are the ways in which the AI-based predictive framework can be integrated within the Smart Grid infrastructure to improve grid reliability and efficiency?’ The study deploys a Deep Learning model based on Long Short-Term Memory techniques, leading to refined accuracy in solar electricity generation forecasts. Such an AI-supported methodology aids power grid operators in comprehensive planning, thereby ensuring a robust electricity supply. The effectiveness of this framework is tested using performance metrics such as MAE, RMSE, nMAE, nRMSE, and 
 $ R^2 $ R2. A persistent model is utilised as a reference for comparison. Despite a slight decrease in predictive precision with the expansion of the forecast horizon, the proposed AI-based framework consistently surpasses the persistent model, particularly for horizons beyond two hours. Therefore, this research underscores the potential of AI-based prediction in fostering efficient solar energy management and enhancing Smart Grid reliability and efficiency.
Journal: International Journal of Production Research
Pages: 4623-4644
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2269565
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2269565
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# input file: TPRS_A_2271093_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yitian Liu
Author-X-Name-First: Yitian
Author-X-Name-Last: Liu
Author-Name: Kang Hu
Author-X-Name-First: Kang
Author-X-Name-Last: Hu
Author-Name: Ruifeng Zhou
Author-X-Name-First: Ruifeng
Author-X-Name-Last: Zhou
Author-Name: Xianfeng Ai
Author-X-Name-First: Xianfeng
Author-X-Name-Last: Ai
Author-Name: Yunqing Chen
Author-X-Name-First: Yunqing
Author-X-Name-Last: Chen
Title: Data driven design optimisation: an empirical study of demand discovery combining theory of planned behaviour and Bayesian networks
Abstract: 
 Many theoretical methods have been applied to research user behaviour and requirements. However, the uncertainty associated with customer characteristics often biases the conclusions drawn from customer research and affects the effectiveness of product design. In this paper, Bayesian networks (BN) are introduced into the research on customer behaviour analysis based upon theory of planned behaviour (TPB), and an analysis model driven by customer research data is established from the perspective of user behaviour intention to guide design optimisation. Combining the User background Factor with the TPB Factor, the model analyses the uncertainty of the association between the two, and corrects the errors in the designer's prior knowledge through structural learning. By a case study the paper finds that the evaluations that enhance customers’ subjective norms and perceived behavioural control lead to a greater probability of purchase or use. In addition, customers with specific characteristics are more inclined to generate behaviour intention. The paper finally provides a design optimisation plan based upon the result of the research and discusses about the advantages of the research approaches and the directions of future researches.
Journal: International Journal of Production Research
Pages: 4696-4716
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2271093
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2271093
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# input file: TPRS_A_2343391_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Yosra Mezghani
Author-X-Name-First: Yosra
Author-X-Name-Last: Mezghani
Author-Name: S. Ehsan Hashemi-Petroodi
Author-X-Name-First: S. Ehsan
Author-X-Name-Last: Hashemi-Petroodi
Author-Name: Simon Thevenin
Author-X-Name-First: Simon
Author-X-Name-Last: Thevenin
Author-Name: Alexandre Dolgui
Author-X-Name-First: Alexandre
Author-X-Name-Last: Dolgui
Title: Robust design and reconfiguration planning of mixed-model assembly lines under uncertain evolutions of product family
Abstract: 
 Assembly lines commonly run for dozens of years before being decommissioned. As product families may evolve several times per year by following the needs of sales and marketing, process engineers reconfigure the lines several dozens of times throughout their life cycle. If the line is not flexible enough, these reconfigurations may be costly, and they can lead to poor efficiency. The present work investigates the possibility of designing a line while accounting for product evolution throughout the life cycle of the line. The evolution of the product family is unknown and we consider a robust optimisation approach. We study a mixed-model assembly line, where each station contains a worker/robot and its equipment. The line produces different product models from the same family, and a reconfiguration occurs when a new product model replaces one of the current variants in the product family. Reconfiguration re-arranges resources and equipment pieces, and it can re-assign some tasks. In this study, we formulate a novel Mixed-Integer Linear Programming (MILP) that minimizes the total cost of the initial design and future reconfigurations of the line over some future product family evolution for the worst case. We consider the worst-case among different scenarios that represent possible production requirements of the new product model. An adversarial approach is also developed to solve large-size instances. We perform computational experiments on the benchmark data from the literature. The results show the proposed adversarial approach performs well, and the proposed robust model significantly reduces the design and reconfiguration costs when compared to the classical approach that designs and reconfigures by accounting only for the current product family.
Journal: International Journal of Production Research
Pages: 4957-4979
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2024.2343391
File-URL: http://hdl.handle.net/10.1080/00207543.2024.2343391
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# input file: TPRS_A_2282186_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Hamzaoui Mohammed Adel
Author-X-Name-First: Hamzaoui
Author-X-Name-Last: Mohammed Adel
Author-Name: Sari Zaki
Author-X-Name-First: Sari
Author-X-Name-Last: Zaki
Author-Name: Belghoul Leila
Author-X-Name-First: Belghoul
Author-X-Name-Last: Leila
Title: Dual cycle time modelling and design optimisation for the bidirectional flow-rack AS/RS
Abstract: 
 This article discusses the problem of evaluating performance and optimising the design of Automated Storage/Retrieval Systems (AS/RS) in a steady state, with a focus on the dual cycle in the bidirectional flow-rack (BFR) AS/RS. To accomplish this, two well-known approaches (discrete and continuous) are utilised to model the dual cycle time. The developed models reveal that the system is near optimal when designed to be square in time. Furthermore, the continuous models are shown to be relatively accurate compared to the discrete counterparts, with discrepancies under 6%. Subsequently, the optimal dimensions of the system are identified through design optimisation aimed at minimising the cycle time. The findings indicate the optimal depth decreases as load rate increases, while optimal height and length follow a cubic root function of system volume. Approximate formulas are derived, allowing for direct calculation of optimal dimensions based on the system size and its load rate. Finally, the article evaluates the system's overall performance by calculating its throughput, providing a tool to estimate capacity. These findings provide an essential tool for optimising the system's performance in a steady state during the upstream design and installation phase, prior to making significant investments.
Journal: International Journal of Production Research
Pages: 4926-4956
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2282186
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2282186
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# input file: TPRS_A_2274335_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Kendrik Yan Hong Lim
Author-X-Name-First: Kendrik Yan Hong
Author-X-Name-Last: Lim
Author-Name: Theresia Stefanny Yosal
Author-X-Name-First: Theresia Stefanny
Author-X-Name-Last: Yosal
Author-Name: Chun-Hsien Chen
Author-X-Name-First: Chun-Hsien
Author-X-Name-Last: Chen
Author-Name: Pai Zheng
Author-X-Name-First: Pai
Author-X-Name-Last: Zheng
Author-Name: Lihui Wang
Author-X-Name-First: Lihui
Author-X-Name-Last: Wang
Author-Name: Xun Xu
Author-X-Name-First: Xun
Author-X-Name-Last: Xu
Title: Graph-enabled cognitive digital twins for causal inference in maintenance processes
Abstract: 
 The increasing complexity of industrial systems demands more effective and intelligent maintenance approaches to address manufacturing defects arising from faults in multiple asset modules. Traditional digital twin (DT) systems, however, face limitations in interoperability, knowledge sharing, and causal inference. As such, cognitive digital twins (CDTs) can add value by managing a collaborative web of interconnected systems, facilitating advanced cross-domain analysis and dynamic context considerations. This paper introduces a CDT system that leverages industrial knowledge graphs (iKGs) to support maintenance planning and operations. By employing a design structure matrix (DSM) to model dependencies and relationships, a semantic translation approach maps the knowledge into a graph-based representation for reasoning and analysis. An automatic solution generation mechanism, utilising graph sequencing with Louvain and PageRank algorithms, derives feasible solutions, which can be validated via simulation to minimise production disruption impacts. The CDT system can also identify potential disruptions in new product designs, thus enabling preventive actions to be taken. A case study featuring a print production manufacturing line illustrates the CDT system's capabilities in causal inference and solution explainability. The study concludes with a discussion of limitations and future directions, providing valuable guidelines for manufacturers aiming to enhance reactive and predictive maintenance strategies.
Journal: International Journal of Production Research
Pages: 4717-4734
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2274335
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2274335
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# input file: TPRS_A_2270689_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Hamzea Al-Jabouri
Author-X-Name-First: Hamzea
Author-X-Name-Last: Al-Jabouri
Author-Name: Ahmed Saif
Author-X-Name-First: Ahmed
Author-X-Name-Last: Saif
Author-Name: Abdelhakim Khatab
Author-X-Name-First: Abdelhakim
Author-X-Name-Last: Khatab
Author-Name: Claver Diallo
Author-X-Name-First: Claver
Author-X-Name-Last: Diallo
Author-Name: Uday Venkatadri
Author-X-Name-First: Uday
Author-X-Name-Last: Venkatadri
Title: A critical review of selective maintenance for mission-oriented systems: challenges and a roadmap for novel contributions
Abstract: 
 The selective maintenance problem (SMP) arises in many mission-oriented multi-component systems that are operated for consecutive missions interspersed with finite breaks, during which only limited component repairs can be performed due to constrained resources. This NP-hard problem decides which components to maintain and to what levels of repair to guarantee a pre-specified performance level during the subsequent mission. Over the last two decades, a sizeable body of literature has been published on this topic. However, the contributions have stagnated in quality, and most articles deal with small to moderate problems. This paper provides a critical review of the SMP literature. A total of 136 research articles related to SMP are reviewed and a selection of key representative models is discussed in detail. This review is framed according to two feature categories: formulation characteristics, composed of three sub-groups of characteristics related to the system, maintenance and mathematical model characteristics; and solution approaches, grouped by exact methods and approximate algorithms. This critical review is aimed at identifying drawbacks, shortcomings, and blind spots of the SMP literature, and providing a roadmap for the challenges to be addressed and innovative future research topics to further advance the academic and industrial contributions of SMP.
Journal: International Journal of Production Research
Pages: 4980-5015
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2270689
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2270689
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# input file: TPRS_A_2281665_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Sadaf Shams-Shemirani
Author-X-Name-First: Sadaf
Author-X-Name-Last: Shams-Shemirani
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Author-Name: Alireza Amjadian
Author-X-Name-First: Alireza
Author-X-Name-Last: Amjadian
Author-Name: Bahar Motamedi-Vafa
Author-X-Name-First: Bahar
Author-X-Name-Last: Motamedi-Vafa
Title: Simulation and process mining in a cross-docking system: a case study
Abstract: 
 The increasing development of the competitive market has forced organisations to make great efforts in the processes of supply, production, and distribution to meet customer demand in the shortest time and at the lowest cost. A cross-docking (CD) system is one of the successful and practical strategies in this field considered by researchers in various fields. Also, business process management plays a key role in continuous improvement and increased productivity. In today’s digital age, due to the ability to record all activities, process mining is an important method to identify the current situation and improve productivity. In this research, a newly established CD belonging to a chain store is studied to improve the current situation, in which different goods enter and then exit after different processes. The purpose of this study is to obtain the optimal number of doors and loaders as sources. First, helping an RFID system, all activities are recorded, and the current situation of the processes is monitored, and then, the real process model is identified using heuristic and inductive miner algorithms. After adapting to the event log by using the simulation process in Arena software, different scenarios are examined, and the best possible case is presented.
Journal: International Journal of Production Research
Pages: 4902-4925
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2281665
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2281665
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# input file: TPRS_A_2281664_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Jianbo Yu
Author-X-Name-First: Jianbo
Author-X-Name-Last: Yu
Author-Name: Yanshu Wang
Author-X-Name-First: Yanshu
Author-X-Name-Last: Wang
Author-Name: Qingfeng Li
Author-X-Name-First: Qingfeng
Author-X-Name-Last: Li
Author-Name: Hao Li
Author-X-Name-First: Hao
Author-X-Name-Last: Li
Author-Name: Mingyan Ma
Author-X-Name-First: Mingyan
Author-X-Name-Last: Ma
Author-Name: Peilun Liu
Author-X-Name-First: Peilun
Author-X-Name-Last: Liu
Title: Cascaded adaptive global localisation network for steel defect detection
Abstract: 
 Defect detection is crucial in ensuring the quality of steel products. This paper proposes a novel deep neural network, cascaded adaptive global location network (CAGLNet), for detecting steel surface defects. The main objective of this study is to address the challenges associated with the irregular shape and dense spatial distribution of defects on steel. To achieve this goal, CAGLNet integrates a feature extraction network that combines residual and feature pyramid networks, a cascade adaptive tree-structure region proposal network (CAT-RPN) that eliminates the need for prior knowledge, and a global localisation regression for steel defect detection. This paper evaluates the effectiveness of CAGLNet on the NEU-DET dataset and demonstrates that the proposed model achieves an average accuracy of 85.40% with a fast frames per second of 10.06, outperforming those state-of-the-art methods. These results suggest that CAGLNet has the potential to significantly improve the effectiveness of defect detection in industrial production processes, leading to increased production yield and cost savings.Abbreviations: AT-RPN, adaptive tree-structure region proposal network; CAGLNet, cascaded adaptive global location network; CAT-RPN, cascade adaptive tree-structure region proposal network; CNN, convolutional neural network; DNN, deep neural network; EPNet, edge proposal network; FPN, feature pyramid network; FCOS, fully convolutional one-stage detector; FPS, frames per second; GMM, Gaussian mixture model; IoU, intersection-over-union; ROIAlign, region of interest align; RPN, region proposal network; ResNet, residual network; ResNet50_FPN, residual network and feature pyramid network; SABL, side aware boundary localisation; SSD, single-shot multiBox detector; TPE, Tree-structured Parzen estimator
Journal: International Journal of Production Research
Pages: 4884-4901
Issue: 13
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2281664
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2281664
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# input file: TPRS_A_2289644_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Fengmei Xu
Author-X-Name-First: Fengmei
Author-X-Name-Last: Xu
Author-Name: Feifei Shan
Author-X-Name-First: Feifei
Author-X-Name-Last: Shan
Author-Name: Feng Yang
Author-X-Name-First: Feng
Author-X-Name-Last: Yang
Author-Name: Ting Chen
Author-X-Name-First: Ting
Author-X-Name-Last: Chen
Title: The impacts of gray products and counterfeits in the luxury industry
Abstract: 
 With the rapid development of e-commerce, both gray products and counterfeit products are particularly serious in the luxury industry. This paper develops an analytical framework to investigate the interaction among the gray market, the counterfeit market and the authorised market, and examines how luxury manufacturers should manage unfair competition from gray products and/or counterfeit products. First, regardless of the existence of counterfeit products, the manufacturer can benefit from gray products when the status utility is moderate. Second, counterfeit products may benefit the manufacturer, depending on the availability of gray products and the physical resemblance of counterfeit products. Third, gray product may benefit the counterfeiter while counterfeit product always harms the gray marketer. Finally, we reveal that gray products can help luxury manufacturers fight against counterfeit products. In particular, gray products can reduce the demand for counterfeit products and even drive counterfeit products out of the market when the physical resemblance of counterfeit products is sufficiently low. Our findings provide several new managerial insights for luxury manufacturers and gray marketers.
Journal: International Journal of Production Research
Pages: 5252-5268
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2289644
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2289644
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# input file: TPRS_A_2289183_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xihui Wang
Author-X-Name-First: Xihui
Author-X-Name-Last: Wang
Author-Name: Anqi Zhu
Author-X-Name-First: Anqi
Author-X-Name-Last: Zhu
Author-Name: Yu Fan
Author-X-Name-First: Yu
Author-X-Name-Last: Fan
Author-Name: Liang Liang
Author-X-Name-First: Liang
Author-X-Name-Last: Liang
Title: An inventory rotation mechanism for relief supplies considering recycling and remanufacturing
Abstract: 
 Relief supply inventories are important in disaster response operations. To address the problem of dead stocks and avoid relief supply expiration, such inventories must be renewed periodically. Different from the traditional shelf-life rotation mechanism (i.e. renewal of the entire inventory at the expiration date), which pays more attention to decreasing the quantity of dead stocks, the novel period rotation mechanism that we design in this study will gradually rotate relief supplies according to their shelf life. We propose a mathematical programming model to minimise the total cost of relief organisations and conduct a case study and analyse the sensitivity of key parameters using real-world data. Results show that our rotation mechanism can substantially reduce the financial burden on relief organisations and improve the quality of relief supplies for victims. The novelty of our study includes: (1) We introduce a new approach that can rotate multiple times, through which we consider the quality of relief supplies; (2) We incorporate recycling and remanufacturing into the rotation process; and (3) We adopt an inductive reasoning method to develop the model with demand and time uncertainties. We prove the feasibility of our model and contributions of our study to humanitarian logistics practice and research.
Journal: International Journal of Production Research
Pages: 5211-5235
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2289183
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2289183
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# input file: TPRS_A_2283569_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Caio dos Santos
Author-X-Name-First: Caio
Author-X-Name-Last: dos Santos
Author-Name: José C. G. Andrade
Author-X-Name-First: José C. G.
Author-X-Name-Last: Andrade
Author-Name: Washington A. Oliveira
Author-X-Name-First: Washington A.
Author-X-Name-Last: Oliveira
Author-Name: Christiano Lyra
Author-X-Name-First: Christiano
Author-X-Name-Last: Lyra
Title: Optimal allocation of fast charging stations for large-scale transportation systems
Abstract: 
 The modern quest for sustainable cities increasingly relies on using distributed energy resources (DERs), which requires new planning practices. This paper proposes an optimisation strategy to solve the fast charging station (FCS) allocation of electric vehicles (EVs). A mixed-integer programming (MIP) model minimises investment and operation costs, considering the building of FCSs with photovoltaic (PV) systems over carports and battery energy storage systems (BESSs) as planning alternatives. The embedded set covering problem has special aspects that allow the development of a novel approach to evaluate candidate sites to accommodate FCSs. A preprocessing strategy is developed to fine-tune the entire solution space. A multiobjective approach is used to obtain an optimal compromise solution for the MIP model when it is required to serve the maximum number of EV owners at the lowest possible cost. The combined strategies reduce the computational burden, allowing full-scale studies of EV charging system planning. The results of studies using a real-world Brazilian case certify the benefits of the proposed strategy in the FCS allocation problem and in optimising the operation when considering renewable alternatives.
Journal: International Journal of Production Research
Pages: 5087-5107
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2283569
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2283569
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# input file: TPRS_A_2286627_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Rim Slama
Author-X-Name-First: Rim
Author-X-Name-Last: Slama
Author-Name: Ilhem Slama
Author-X-Name-First: Ilhem
Author-X-Name-Last: Slama
Author-Name: Houda Tlahig
Author-X-Name-First: Houda
Author-X-Name-Last: Tlahig
Author-Name: Pierre Slangen
Author-X-Name-First: Pierre
Author-X-Name-Last: Slangen
Author-Name: Oussama Ben-Ammar
Author-X-Name-First: Oussama
Author-X-Name-Last: Ben-Ammar
Title: An overview on human-centred technologies, measurements and optimisation in assembly systems
Abstract: 
 This paper offers an in-depth examination of the ergonomics of human-centred assembly systems in Industry 4.0, where manual tasks remain essential. The use of advanced technologies such as motion capture (MOCAP) and virtual reality (VR) is analysed as ways to enhance system efficiency and improve worker well-being. The paper highlights the importance of optimising assembly system performance while considering both economic and human factors. Metrics to assess ergonomic risk and productivity are discussed based on human-centred technologies, and existing operational research models are explored to analyse how human factors could be considered in optimising system performance. Additionally, the paper explores potential future directions and how they could play a role in Industry 4.0.
Journal: International Journal of Production Research
Pages: 5336-5358
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2286627
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2286627
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# input file: TPRS_A_2283568_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Xavier Delorme
Author-X-Name-First: Xavier
Author-X-Name-Last: Delorme
Author-Name: Paolo Gianessi
Author-X-Name-First: Paolo
Author-X-Name-Last: Gianessi
Title: Line balancing and task scheduling to minimise power peak of reconfigurable manufacturing systems
Abstract: 
 Energy efficiency has become a major concern for manufacturing systems, due to industry being the largest user of scarce, finite energy sources, and also to recent events which have pushed energy prices to alarming levels. In the present Industry 4.0 context, Reconfigurable Manufacturing Systems (RMS) are therefore one of the most promising manufacturing paradigm. In this paper, we investigate the suitability of one of the most common types of RMS, the Parallel-Serial manufacturing line with Crossover, to help minimise the peak of the electric power consumption. More specifically, the balancing of such a production line is studied, so as to integrate power peak minimisation from the design stage. Thus, we define the Parallel-Serial-with-Crossover Assembly Line Balancing Problem with Power Peak Minimization, a new combinatorial NP-hard problem. We also propose a suitable time-indexed Integer Linear Program that integrates balancing and scheduling decisions and a matheuristic algorithm designed to tackle large-size instances. Both approaches are tested on a wide set of instances. The computational results show that relevant power peak reductions can be achieved (33% on average), opening up promising perspectives from both algorithmic and managerial viewpoints.
Journal: International Journal of Production Research
Pages: 5061-5086
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2283568
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2283568
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# input file: TPRS_A_2291519_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Matteo Capponi
Author-X-Name-First: Matteo
Author-X-Name-Last: Capponi
Author-Name: Riccardo Gervasi
Author-X-Name-First: Riccardo
Author-X-Name-Last: Gervasi
Author-Name: Luca Mastrogiacomo
Author-X-Name-First: Luca
Author-X-Name-Last: Mastrogiacomo
Author-Name: Fiorenzo Franceschini
Author-X-Name-First: Fiorenzo
Author-X-Name-Last: Franceschini
Title: Assessing perceived assembly complexity in human-robot collaboration processes: a proposal based on Thurstone’s law of comparative judgement
Abstract: 
 Due to the growing demand for customised products, companies have faced increasing product and process complexity levels. To address this issue, manufacturing processes should become more flexible. One of the most promising technologies to achieve this goal is collaborative robotics (or ‘cobots’). In collaborative assembly processes, human and robot combine their skills. However, the co-existence of humans and cobots in the same workspace may influence the operators’ perception of assembly complexity. The analysis and control of assembly complexity are crucial to achieving better performances in terms of process quality and operators’ well-being. Many qualitative methods have been proposed in the literature to provide a holistic assessment of assembly complexity. This paper proposes a novel method to define a quantitative scale of perceived assembly complexity, based on Thurstone Law of Comparative Judgements. This method was applied to an experimental case-study concerning the assembly of three different products in two modalities (i.e. manual and collaborative). Regression analysis showed that the perceived complexity may be related to the occurrence of process failures and to the perceived workload. The method also proved capable of identifying assembly processes where cobot assistance was helpful, providing process designers with a supporting tool to minimise perceived complexity.
Journal: International Journal of Production Research
Pages: 5315-5335
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2291519
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2291519
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# input file: TPRS_A_2284480_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: The Editors
Title: Correction
Journal: International Journal of Production Research
Pages: 5359-5359
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2284480
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2284480
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2283570_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Daniele Giovanni Gioia
Author-X-Name-First: Daniele Giovanni
Author-X-Name-Last: Gioia
Author-Name: Edoardo Fadda
Author-X-Name-First: Edoardo
Author-X-Name-Last: Fadda
Author-Name: Paolo Brandimarte
Author-X-Name-First: Paolo
Author-X-Name-Last: Brandimarte
Title: Rolling horizon policies for multi-stage stochastic assemble-to-order problems
Abstract: 
 Assemble-to-order approaches deal with randomness in demand for end items by producing components under uncertainty, but assembling them only after demand is observed. Such planning problems can be tackled by stochastic programming, but true multistage models are computationally challenging and only a few studies apply them to production planning. Solutions based on two-stage models are often short-sighted and unable to effectively deal with non-stationary demand. A further complication may be the scarcity of available data, especially in the case of correlated and seasonal demand. In this paper, we compare different scenario tree structures. In particular, we enrich a two-stage formulation by introducing a piecewise linear approximation of the value of the terminal inventory, to mitigate the two-stage myopic behaviour. We compare the out-of-sample performance of the resulting models by rolling horizon simulations, within a data-driven setting, characterised by seasonality, bimodality, and correlations in the distribution of end item demand. Computational experiments suggest the potential benefit of adding a terminal value function and illustrate interesting patterns arising from demand correlations and the level of available capacity. The proposed approach can provide support to typical MRP/ERP systems, when a two-level approach is pursued, based on master production and final assembly scheduling.
Journal: International Journal of Production Research
Pages: 5108-5126
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2283570
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2283570
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# input file: TPRS_A_2284835_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Vivek Roy
Author-X-Name-First: Vivek
Author-X-Name-Last: Roy
Author-Name: Tobias Schoenherr
Author-X-Name-First: Tobias
Author-X-Name-Last: Schoenherr
Author-Name: Jayanth Jayaram
Author-X-Name-First: Jayanth
Author-X-Name-Last: Jayaram
Title: Digital enabled agility: Industry 4.0 unlocking real-time information processing, traceability, and visibility to unleash the next extent of agility
Abstract: 
 Digital enabled agility reflects the transformative outset of an organisation to first upgrade its business processes digitally towards facilitating real-time information processing/capabilities. Second, tapping from real-time capabilities, digital enabled agility maximises an agile response's efficacy in enhancing the sophistication of rapidity, flexibility, and sensing involved. In this backdrop, driven by newer IT infrastructure and disruptive technology, this research accentuates on Industry 4.0 digitalisation to understand how a manufacturer can gain digital enabled agility. An empirical survey of manufacturers within the premise of Industry 4.0 is conducted. Drawn from the findings, the capabilities of traceability and visibility can be facilitated by Industry 4.0 that would improve information sharing and information quality in real-time. These capabilities are key propellants to unlock the digital extent of agility. This research however details further how this scope of agility is an extension to that of the scope of typical agility in terms of its ability to handle expansive information processing needs and dynamic coordination/resource orchestration. Insights are weaved under the purviews of (a) organisational information processing view and (b) the manufacturer who is coordinating contemporary dynamic production and allied value chain requirements.
Journal: International Journal of Production Research
Pages: 5127-5148
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2284835
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2284835
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# input file: TPRS_A_2282751_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Dieter E. Wolf
Author-X-Name-First: Dieter E.
Author-X-Name-Last: Wolf
Author-Name: Louis Louw
Author-X-Name-First: Louis
Author-X-Name-Last: Louw
Author-Name: Daniel Palm
Author-X-Name-First: Daniel
Author-X-Name-Last: Palm
Title: An analysis of blockchain versus relational databases for digitalising information flows in global supply chains using the analytic network process
Abstract: 
 Global trade is plagued by slow and inefficient manual processes associated with physical documents. Firms are constantly looking for new ways to improve transparency and increase the resilience of their supply chains. This can be solved by the digitalisation of supply chains and the automation of document- and information-sharing processes. Blockchain is touted as a solution to these issues due to its unique combination of features, such as immutability, decentralisation and transparency. A lack of business cases that quantify the costs and benefits causes uncertainty regarding the truth of these claims. This paper explores how the costs and benefits of a blockchain-based solution for digitalising and automating documentation flows in cross-border supply chains compare to a conventional centralised relational database solution. The research described in this paper uses primary data collected through semi-structured interviews with industry experts, as well as secondary data from literature. Two models based on existing services were developed and the costs and benefits compared and then analysed using the Architecture Trade-off Analysis Method (ATAM) and the Analytic Network Process (ANP). Findings from the analysis show that a consortium blockchain solution like TradeLens is the favourable solution for digitalising and automating information flows in cross-border supply chains.
Journal: International Journal of Production Research
Pages: 5016-5035
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2282751
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2282751
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# input file: TPRS_A_2285421_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Erica Pastore
Author-X-Name-First: Erica
Author-X-Name-Last: Pastore
Author-Name: Arianna Alfieri
Author-X-Name-First: Arianna
Author-X-Name-Last: Alfieri
Author-Name: Andrea Matta
Author-X-Name-First: Andrea
Author-X-Name-Last: Matta
Author-Name: Barbara Previtali
Author-X-Name-First: Barbara
Author-X-Name-Last: Previtali
Title: Analytical models for flow time estimation of additive manufacturing machines
Abstract: 
 The use of Additive Manufacturing (AM) technology has largely increased in the last years. Because of its large differences from conventional technologies, the use of AM in production systems might call for new strategies in production planning and control. To this aim, this paper proposes analytical models to predict aggregate performance measures such as flow time, work in process, and production throughput, for production systems characterised by Laser Powder Bed Fusion AM technology. These indicators could be used both in operations strategy development and in technology comparison. The proposed models differentiate for their detail of the analysis and the number of input parameters that need to be estimated. The results show that the level of detail of the model affects the analysis leading to quite different values of the performance measures, especially in the case of highly saturated systems. Also, a discussion about the applicability of the proposed model to other AM technologies show whether and to what extent the proposed models can be applied for modelling other AM technologies.
Journal: International Journal of Production Research
Pages: 5168-5184
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2285421
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2285421
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# input file: TPRS_A_2289643_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Rong Wang
Author-X-Name-First: Rong
Author-X-Name-Last: Wang
Author-Name: Peng Yang
Author-X-Name-First: Peng
Author-X-Name-Last: Yang
Author-Name: Yeming Gong
Author-X-Name-First: Yeming
Author-X-Name-Last: Gong
Author-Name: Cheng Chen
Author-X-Name-First: Cheng
Author-X-Name-Last: Chen
Title: Operational policies and performance analysis for overhead robotic compact warehousing systems with bin reshuffling
Abstract: 
 This paper studies a novel robotic warehousing system called the overhead robotic compact storage and retrieval system, which can free up the floor space occupation at a low cost. Bins, as basic storage containers, are stacked on top of each other to form a bin stack. Along overhead tracks, bin-picking robots transport bins between storage/retrieval positions and workstations with the aid of track-changing robots. Little research has been done to study operational policies and performance analysis for this new robotic compact warehousing system. We propose a nested queuing network model that considers two transportation resources and performs reinforcement learning using real data to improve the reshuffling efficiency. We find that reinforcement learning based reshuffling policy greatly reduces the reshuffling distance and saves computation time compared to existing policies. We find that the storage policy of stacks affects the optimal width/length ratio regardless of the system height. Interestingly, we obtain the number of robots that can stabilise the system to avoid an explosion of the order queue; two more robots than that number will produce relatively low throughput times. Compared to an AutoStore system, using our system reduces cost by 30% with a slight increase in throughput time.
Journal: International Journal of Production Research
Pages: 5236-5251
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2289643
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2289643
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Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2290699_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Eyüp Ensar Işık
Author-X-Name-First: Eyüp Ensar
Author-X-Name-Last: Işık
Author-Name: Seyda Topaloglu Yildiz
Author-X-Name-First: Seyda Topaloglu
Author-X-Name-Last: Yildiz
Title: Integer and constraint programming models for the straight and U-shaped assembly line balancing with hierarchical worker assignment problem
Abstract: 
 The solution to the assembly line balancing with the hierarchical worker assignment problem (ALBHWP) provides the optimal allocation of workers and tasks to the stations that minimise the total worker cost. In the ALBHWP, tasks differ in terms of the qualification requirements of workers, and the qualification levels of workers are hierarchical. In the hierarchical workforce structure, a lower qualified worker can be replaced by higher qualified ones with higher costs, while the vice versa is not applicable. This problem has only been studied for straight assembly lines so far. In this paper, we introduce the ALBHWP for U-shaped assembly lines. We developed integer and constraint programming models for solving the ALBHWP and compared their effectiveness using an extensive set of benchmark instances. We solved the ALBHWP for straight and U-shaped assembly lines comparatively. Constraint programming models have been statistically proven to provide better quality solutions faster than integer programming models. Besides, the CP model outperforms the only available metaheuristic in the literature for the S-ALBHWP in almost all problem sizes. Another observation is that a U-shaped line design is more cost-effective than a straight line design, but solving the ALBHWP for U-shaped lines is more difficult regarding computational complexity.
Journal: International Journal of Production Research
Pages: 5269-5292
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2290699
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2290699
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:14:p:5269-5292



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# input file: TPRS_A_2285403_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Dominik Zehetner
Author-X-Name-First: Dominik
Author-X-Name-Last: Zehetner
Author-Name: Margaretha Gansterer
Author-X-Name-First: Margaretha
Author-X-Name-Last: Gansterer
Title: Decentralised collaborative job reassignments in additive manufacturing
Abstract: 
 Cloud Manufacturing (CMfg) is a promising approach that leverages the sharing economy to reduce costs and enhance supply chain flexibility. Particularly, when utilised alongside Additive Manufacturing (AM), CMfg is considered a key enabler for collaborative production (CP) systems. However, there is still a lack of planning models that reduce entry barriers for CP. Therefore, we propose a decentralised CP planning framework for AM. In our approach, machines autonomously select jobs from an existing production plan to forward them to other suppliers that can produce these parts more efficiently. A CMfg platform facilitates job forwarding and creates promising part bundles and manufacturing machines autonomously places bids on the packages via a combinatorial 
 $ 2^{nd} $ 2nd price reverse auction. Costs of the reallocated bundles are shared throughout a Shapley value-based approach without the need to disclose critical information. We benchmark our proposed framework against a centralised planning approach and find that it achieves comparable effectiveness as the benchmark solution. We also show that this mechanism promotes individual rationality and that agents particularly benefit when participating in both offering and acquiring production jobs through the auction.
Journal: International Journal of Production Research
Pages: 5149-5167
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2285403
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2285403
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# input file: TPRS_A_2289073_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Jingyan Li
Author-X-Name-First: Jingyan
Author-X-Name-Last: Li
Author-Name: Xiang Ji
Author-X-Name-First: Xiang
Author-X-Name-Last: Ji
Author-Name: Sandun C. Perera
Author-X-Name-First: Sandun C.
Author-X-Name-Last: Perera
Title: Behaviour-based pricing for multi-version information goods
Abstract: 
 Behaviour-based pricing (BBP) is commonly observed in the information goods industry. Information goods providers typically sell multi-version products and have implemented different BBP strategies for their products. However, previous research on BBP is mostly limited to single-version products, which may not effectively guide practical decision-making regarding multi-version products. This gap sparks interest in how BBP can be applied to multi-version information goods. We show that the equilibrium pricing strategy depends on the quality gap between the products and how much consumers and the firm value future benefits. The firm should implement BBP for both high- and low-quality products if it values future benefits more than consumers do. If consumers value future benefits more than the firm, the firm should not implement BBP for either product. Moreover, when the firm and consumers value future benefits equally, the firm should only practice BBP for the low-quality product. Our calculations of consumer surplus and social welfare reveal that the absence of BBP doesn't always lead to the maximum benefits for consumers and society. Interestingly, if the firm values future benefits more than its consumers do, applying BBP only to high-quality products or both products may lead to higher consumer surplus and social welfare.
Journal: International Journal of Production Research
Pages: 5185-5210
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2289073
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2289073
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:14:p:5185-5210



Template-Type: ReDIF-Article 1.0
# input file: TPRS_A_2283566_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Tingting Chen
Author-X-Name-First: Tingting
Author-X-Name-Last: Chen
Author-Name: Feng Chu
Author-X-Name-First: Feng
Author-X-Name-Last: Chu
Author-Name: Jiantong Zhang
Author-X-Name-First: Jiantong
Author-X-Name-Last: Zhang
Author-Name: Jiaqing Sun
Author-X-Name-First: Jiaqing
Author-X-Name-Last: Sun
Title: Sustainable collaborative strategy in pharmaceutical refrigerated logistics routing problem
Abstract: 
 The rapid growth of pharmaceutical refrigerated logistics poses sustainability challenges, including elevated costs, energy consumption, and resource inefficiency. Collaborating multiple depots can enhance logistics efficiency when standalone distribution centres have limited transport resources, i.e. refrigerated vehicles. However, the sustainable benefits and performance across different strategies remain unexplored. This study fills this research gap by addressing a refrigerated pharmaceutical routing problem. While many collaborative strategies prioritise economic and environmental benefits, our approach highlights a vital social indicator: maintaining vehicle flow equilibrium at each depot during collaboration. This ensures the stability of transport resources for all stakeholders, promoting sustainable collaborative logistics. The problem is formulated as a multi-depot vehicle routing problem with time windows (MDVRPTW). Three collaborative strategies using Clustering VRP (CLUVRP) and improved Open VRP (OVRP) are proposed and compared. We develop two approaches to address traditional OVRP limitations in ensuring vehicle flow equilibrium at each depot. Our models consider perishable pharmaceuticals and time-dependent travel speeds. Three hybrid heuristics based on Simulated Annealing and Variable Neighborhood Search (SAVNS) are proposed and evaluated for efficacy. Computational experiments and a case study demonstrate distinct sustainable benefits across various strategies, offering valuable insights for decision-makers in the refrigerated logistics market.
Journal: International Journal of Production Research
Pages: 5036-5060
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2283566
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2283566
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# input file: TPRS_A_2290700_J.xml processed with: repec_from_jats12.xsl darts-xml-transformations-20240209T083504 git hash: db97ba8e3a
Author-Name: Changxuan Zhao
Author-X-Name-First: Changxuan
Author-X-Name-Last: Zhao
Author-Name: Mahmoud Dinar
Author-X-Name-First: Mahmoud
Author-X-Name-Last: Dinar
Author-Name: Shreyes N. Melkote
Author-X-Name-First: Shreyes N.
Author-X-Name-Last: Melkote
Title: Deep learning and sequence mining for manufacturing process and sequence selection
Abstract: 
 Automatic determination of manufacturing process sequences for the physical production of given part designs is key to facilitate on-demand cyber manufacturing. In this work, we propose an integrated framework that (i) identifies manufacturing features from 3D part designs using a Graph Neural Network (GNN), (ii) identifies the manufacturing processes necessary to produce all features in the part using a Convolutional Neural Network (CNN) that considers shape, material properties, and quality information, and (iii) outputs an ordered manufacturing sequence that can produce the designed part with the help of sequence mining. Using these methods, the knowledge required to enable automated manufacturing process selection is easily scalable and updatable without requiring manual population of ad-hoc or rule-based descriptions. We present exemplar implementations of the proposed framework by suggesting manufacturing sequences for discrete parts with multiple features. The suggested manufacturing sequences demonstrate the potential of the proposed framework for use in future on-demand cyber manufacturing applications.
Journal: International Journal of Production Research
Pages: 5293-5314
Issue: 14
Volume: 62
Year: 2024
Month: 07
X-DOI: 10.1080/00207543.2023.2290700
File-URL: http://hdl.handle.net/10.1080/00207543.2023.2290700
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Handle: RePEc:taf:tprsxx:v:62:y:2024:i:14:p:5293-5314